Dietary and Policy Priorities for Cardiovascular Disease, Diabetes, and Obesity
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Abstract
Suboptimal nutrition is a leading cause of poor health. Nutrition and policy science have advanced rapidly, creating confusion yet also providing powerful opportunities to reduce the adverse health and economic impacts of poor diets. This review considers the history, new evidence, controversies, and corresponding lessons for modern dietary and policy priorities for cardiovascular diseases, obesity, and diabetes mellitus. Major identified themes include the importance of evaluating the full diversity of diet-related risk pathways, not only blood lipids or obesity; focusing on foods and overall diet patterns, rather than single isolated nutrients; recognizing the complex influences of different foods on long-term weight regulation, rather than simply counting calories; and characterizing and implementing evidence-based strategies, including policy approaches, for lifestyle change. Evidence-informed dietary priorities include increased fruits, nonstarchy vegetables, nuts, legumes, fish, vegetable oils, yogurt, and minimally processed whole grains; and fewer red meats, processed (eg, sodium-preserved) meats, and foods rich in refined grains, starch, added sugars, salt, and trans fat. More investigation is needed on the cardiometabolic effects of phenolics, dairy fat, probiotics, fermentation, coffee, tea, cocoa, eggs, specific vegetable and tropical oils, vitamin D, individual fatty acids, and diet-microbiome interactions. Little evidence to date supports the cardiometabolic relevance of other popular priorities: eg, local, organic, grass-fed, farmed/wild, or non–genetically modified. Evidence-based personalized nutrition appears to depend more on nongenetic characteristics (eg, physical activity, abdominal adiposity, gender, socioeconomic status, culture) than genetic factors. Food choices must be strongly supported by clinical behavior change efforts, health systems reforms, novel technologies, and robust policy strategies targeting economic incentives, schools and workplaces, neighborhood environments, and the food system. Scientific advances provide crucial new insights on optimal targets and best practices to reduce the burdens of diet-related cardiometabolic diseases.
Introduction
Suboptimal diet is the leading risk factor for death and disability in the United States and worldwide.1,2 Among disadvantaged populations in all nations, hunger and malnutrition cause enormous suffering. Simultaneously, diet-related cardiometabolic diseases such as coronary heart disease (CHD), stroke, type 2 diabetes mellitus, and obesity produce even larger global health burdens. Other vascular conditions including peripheral arterial disease, chronic kidney disease, cognitive decline, heart failure, and atrial fibrillation are also influenced by diet-related risk factors. Worldwide, chronic diseases will cause $17.3 trillion of cumulative economic loss between 2011 and 2030 from healthcare expenditures, reduced productivity, and lost capital.3 Considering these health and economic burdens, diet-related illnesses are among the leading priorities of our time.
In recent years, global dietary patterns have shifted in nearly every nation in the world.4 At the same time, nutrition science has advanced remarkably. In comparison with historical dietary recommendations which were based largely on cross-national studies, short-term experiments, and animal models, nutrition science has been transformed in the past 2 decades by more rigorous evidence from well-designed metabolic studies, prospective cohorts, and randomized clinical trials.
Several key lessons have emerged (Table 1). First, it is now evident that dietary habits influence diverse cardiometabolic risk factors, including not only obesity and low-density lipoprotein (LDL) cholesterol, but also blood pressure (BP), glucose-insulin homeostasis, lipoprotein concentrations and function, oxidative stress, inflammation, endothelial health, hepatic function, adipocyte metabolism, cardiac function, metabolic expenditure, pathways of weight regulation, visceral adiposity, and the microbiome (Figure 1). Whereas decades of dietary recommendations focused on dietary fat and blood cholesterol and current dietary discussions are often preoccupied with total calories and obesity, the full health impact of diet extends far beyond these pathways. Cardiometabolic consequences of any nutrient, food, or overall diet should not be extrapolated from any single surrogate outcome,5 but assessed based on the totality of evidence including interventional trials evaluating multiple risk pathways, prospective cohort studies of clinical events, and, where available, randomized trials of clinical events.6,7
| Diverse physiological effects of diet | Dietary habits influence a myriad of cardiometabolic risk factors, including blood pressure, glucose-insulin homeostasis, lipoprotein concentrations and function, inflammation, endothelial health, hepatic function, adipocyte metabolism, cardiac function, metabolic expenditure, and pathways of weight regulation, visceral adiposity, and the microbiome. Focus on single surrogate outcomes can be misleading. Based on these diverse effects, diet quality is more relevant than quantity, and the primary emphasis should be cardiovascular and metabolic health, not simply body weight or obesity. |
| Importance of foods and diet patterns | Specific foods and overall diet patterns, rather than single isolated nutrients, are most relevant for cardiometabolic health. The historical focus on isolated nutrients contributes to confusion about what constitutes a healthy diet, distracts from more effective strategies, and drives industry, policy makers, and the public toward diets which meet selected nutrient cut points but provide little health benefit. |
| Complexity of obesity and weight regulation | Diet quality influences diverse pathways related to weight homeostasis, including satiety, hunger, brain reward, glucose-insulin responses, hepatic de novo lipogenesis, adipocyte function, metabolic expenditure, and the microbiome. For long-term weight control, all calories are not created equal because of the divergent long-term effects of different foods on these pathways of weight homeostasis. |
| Individual, health systems, and policy approaches for behavior change | Multiple evidence-based strategies for improving dietary behaviors have now been identified, including at the individual (patient) level, in health systems, and in populations. Integrated, multicomponent approaches that include upstream policy measures, midstream educational efforts, and downstream community and environmental approaches may be especially effective. |
Figure 1. Diet and cardiovascular and metabolic risk – pathways and mechanisms. Each of these dietary factors influences many or even all of these pathways, which could also be modified in some cases by underlying individual characteristics. Selected major effects are detailed in the text sections on each dietary factor.
A second key lesson is the importance of specific foods and overall diet patterns, rather than single isolated nutrients, for cardiometabolic risk.8,9 Indeed, focusing on isolated nutrients often leads to paradoxical dietary choices and industry formulations. A food-based approach also better facilitates public guidance and minimizes industry manipulation.
Third, the science of obesity has progressed dramatically. Similar to lessons for CHD risk, the primary prevention of obesity – avoidance of long-term weight gain – may prove more effective and enduring than secondary prevention – obesity treatment after it has occurred. The diverse, complex physiological mechanisms of long-term weight homeostasis are also being elucidated. These lines of evidence indicate that an energy-imbalance concept of obesity is oversimplified. Whereas short-term weight loss can be achieved by any type of calorie-reduced diet, in the long term, counting calories may not be biologically nor behaviorally relevant. Rather, the quality and types of foods consumed influence diverse pathways related to weight homeostasis, such as satiety, hunger, brain reward, glucose-insulin responses, hepatic de novo lipogenesis, adipocyte function, metabolic expenditure, and the microbiome. Thus, all calories are not equal for long-term adiposity: certain foods impair pathways of weight homeostasis, others have relatively neutral effects, and others promote the integrity of weight regulation.
Finally, major strides have been made in the science of individual, sociocultural, and environmental determinants of dietary choices. Influences are complex, including individual-level, sociocultural, community, agricultural, industry, governmental, and global contributors.10 Several individual, health system, and policy-level strategies now have strong evidence for efficacy.11 Elucidation of methods for better translation of these approaches is needed.
This article summarizes the modern evidence for health effects of diet on cardiometabolic diseases, including key evidence-based priorities, relevant mechanisms, and major unanswered questions, and the evidence on barriers and opportunities for behavior change in the clinic, health system, and population, including novel policy and technology strategies.
Nutrients, Foods, and Diet Patterns – a Historical Evolution
In 1747, Captain James Lind performed one of the earliest recorded clinical trials. Based on earlier observations, he assigned British sailors who had scurvy to several different treatments.9,12 Only 1 group – those receiving citrus fruits – improved, providing new evidence that a specific dietary factor could cure disease. By the turn of the century, the British fleet routinely added lemon or lime juice to rations, a practice making them famous as “limeys”.
Yet, it was not until 1932 that the first vitamin was isolated – vitamin C – and was verified as the active protective constituent against scurvy. This confirmed, for the first time, that specific dietary nutrients could prevent disease. Over the next 2 decades, an explosion of nutrition science confirmed other single-nutrient diseases such as beriberi (thiamine), pellagra (niacin), anemia (iron), goiter (iodine), night blindness (vitamin A), and rickets (vitamin D). Coincident to these scientific advances, geopolitical events – the Great Depression, World War II – greatly magnified attention on food shortages and nutrient inadequacy. Indeed, the first Recommended Dietary Allowances originated in 1941 by order of President Franklin Roosevelt, when he convened the National Nutrition Conference on Defense to ensure a population fit for war by minimizing nutrient deficiency diseases.13,14 That same year, the American Medical Association declared that, “research in nutrition be encouraged” with primary aims of “estimating the amounts of essential nutrients in foods,” “detection of nutritional deficiency states,” and more precise determination of “optimum and minimum requirements” for each nutrient.15 Consequently, all of the first Recommended Dietary Allowances focused on nutrient deficiency, including for calories, protein, iron, calcium, thiamin, riboflavin, niacin, and vitamins A, C, and D. Based on this chance convergence of scientific and geopolitical events, US dietary guidelines over most of the 20th century emphasized prevention of single-nutrient deficiencies.14
With the modernization of agriculture, food processing, and food formulations, nutrient deficiencies rapidly receded in the United States and other high-income nations. In their place, a growing epidemic of chronic diseases was recognized. Beginning in 1980, for the first time, US dietary guidelines began to focus on chronic disease.14 The main available evidence derived from less robust study designs: eg, crude cross-national comparisons, short-term experiments of surrogate outcomes in healthy volunteers. Furthermore, after decades of emphasis on deficiency diseases, the single-nutrient paradigm continued to dominate research approaches and interpretations. Together, these factors caused oversimplified inferences on how diet influences cardiovascular disease (CVD), diabetes mellitus, and obesity. Scientists and policy makers intuitively followed earlier methods that had been so successful in reducing deficiencies: identify the relevant nutrient, establish its target intake, and translate this to recommendations. To many, saturated fat and cholesterol became the causes of CHD, and total fat became the cause of obesity. Thus, the 1980 Dietary Guidelines remained heavily nutrient-focused: “avoid too much fat, saturated fat, and cholesterol; eat foods with adequate starch and fiber; avoid too much sugar; avoid too much sodium.”
Modern evidence now demonstrates the limitations of this single-nutrient component focus. The framework of Recommended Dietary Allowances was quickly recognized as methodologically and conceptually inappropriate for chronic diseases, leading to the creation of new nutrient-based metrics (eg, Adequate Intakes; Acceptable Macronutrient Distribution Ranges) which were themselves limited by imprecise definitions and inconsistent usage.16 Furthermore, although scientific investigation of macro- and micronutrients remains essential to elucidate biological mechanisms, the complex matrix of foods, food processing, and food preparation strongly modifies the final health effects.8,9,17,18 Translation of nutrient-based targets to the public also proved difficult: few people understand or can accurately estimate without guidance their daily consumption of nutrients such as calories, fats, cholesterol, fiber, salt, or single vitamins. Most importantly, methodologic advances in nutrition science now demonstrate that nutrient-focused metrics are inadequate to explain most effects of diet on chronic diseases. Rather, cardiometabolic diseases are largely influenced not by single nutrients, but by specific foods and overall diet patterns.19–21
These historical events elucidate the current state of nutrition. Modern dietary science is surprisingly young – only 83 years have elapsed since the first vitamin was isolated – and much of its existence was focused on single-nutrient diseases. The major impact of diet on chronic diseases was not widely appreciated until even more recently, 35 to 40 years ago. And, not until the last 15 to 20 years has the scientific methodology become sufficiently advanced to provide strong, consistent inference on diet, chronic diseases, and relevant metabolic pathways. Thus, the present period is one of exciting, rapid transition away from single-nutrient theories and simple surrogate outcomes and toward foods, dietary patterns, and evaluation of clinical end points. This transition forms the basis for our modern understanding of diet and cardiometabolic health.
Dietary Patterns
Dietary patterns represent the overall combination of foods habitually consumed, which together produce synergistic health effects. Evidence-informed beneficial diet patterns share several key characteristics (Table 2).19,21–23 These include more minimally processed foods such as fruits, nuts/seeds, vegetables (excluding russet or white potatoes), legumes, whole grains, seafood, yogurt, and vegetable oils; and fewer red meats, processed (sodium-preserved) meats, and foods rich in refined grains, starches, and added sugars. Such diets are higher in fiber, vitamins, antioxidants, minerals, phenolics, and unsaturated fats, and lower in glycemic index, glycemic load, salt, and trans fat.
| Goal* | One Serving Equals… | Examples | ||
|---|---|---|---|---|
| Consume more | Fruits | 3 servings/d | 1 medium-sized fruit; ½ cup of fresh, frozen, or unsweetened canned fruit; ½ cup of dried fruit; ½ cup of 100% juice | Blueberries, strawberries, apple, orange, banana, grapes, grapefruit, avocado, mango. Whole fruits are preferable to 100% juice, which should be limited to no more than 1 serving/d. |
| Nuts, seeds | 4 servings/wk | 1 ounce | Almonds, walnuts, peanuts, hazelnuts, cashews, pecans, Brazil nuts, sunflower seeds, sesame seeds. | |
| Vegetables, including legumes (excluding russet or white potatoes) | 3 servings/d | 1 cup of raw leafy vegetables; ½ cup of cut-up raw vegetables, cooked vegetables, or 100% vegetable juice | Spinach, kale, and other green leafy plants; broccoli, carrots, onions, peppers; peas, beans, lentils. Minimize starchy vegetables, especially russet or white potatoes. | |
| Whole grains† | 3 servings/d, in place of refined grains | 1 slice of whole-grain bread; 1 cup of high-fiber, whole-grain cereal; ½ cup of cooked whole-grain rice, pasta, or cereal | Oats, bulgur, whole-wheat couscous, barley, whole-grain breads and cereals, brown rice. | |
| Fish, shellfish | ≥2 servings/wk | 3.5 ounces (100 g) | The best choices are oily fish such as salmon, tuna, mackerel, trout, herring, and sardines. | |
| Dairy products, especially yogurt and cheese ‡ | 2–3 servings/d | 1 cup of milk or yogurt; 1 ounce of cheese | Whole-fat or low-fat yogurt, cheese, milk. | |
| Vegetable oils | 2–6 servings/d | 1 teaspoon oil, 1 tablespoon vegetable spread | The best evidence supports phenolic- and unsaturated fat–rich oils such as soybean, canola, and extra virgin olive oil; also consider safflower oil, peanut oil, and soft margarine spreads made with these oils. | |
| Consume less | Refined grains, starches, added sugars† | No more than 1–2 servings/d | 1 slice of bread, ½ cup of rice or cereal, 1 sweet or dessert | White bread, white rice, most breakfast cereals, crackers, granola bars, sweets, bakery desserts, added sugars. |
| Processed meats | No more than 1 serving/wk | 1.75 ounces (50 g) | Preserved (sodium, nitrates) meats such as bacon, sausage, hot dogs, pepperoni, salami, low-fat deli meats (eg, chicken, turkey, ham, beef). | |
| Unprocessed red meats | No more than 1–2 servings/wk | 3.5 ounces (100 g) | Fresh/frozen beef, pork, lamb. | |
| Industrial trans fat § | Don’t eat | Any food containing or made with partially hydrogenated vegetable oil | Certain stick margarines, commercially prepared baked foods (cookies, pies, donuts, etc0), snack foods, deep-fried foods. | |
| Sugar-sweetened beverages | Don’t drink | 8 ounces of beverage; 1 small sweet, pastry, or dessert | Sugar-sweetened soda, fruit drinks, sports drinks, energy drinks, iced teas. | |
| Sodium | No more than 2000 mg/d | n/a | Sodium is commonly high in foods as a preservative or to mask unpleasant flavors when previously cooked. Common sources include bread, chicken (often injected to increase succulence), cheese, processed meats, soups, canned foods. | |
The scientific concordance, controversy, and related evidence for these and other key dietary targets are variable (Table 3). As described above, this reflects the youthful nature of the science of nutrition and chronic disease, together with the remarkable advances in research and knowledge over just the past 1–2 decades.
| Broad Concordance and Less Controversy or Uncertainty† | General Concordance but Some Remaining Controversy and Uncertainty | Substantial Controversy and Uncertainty | Insufficient Evidence for Meaningful Conclusions | |
|---|---|---|---|---|
| Benefits of: | Fruits, nonstarchy vegetables, nuts/seeds, legumes, yogurtDietary fiber, potassiumModerate alcohol useMediterranean-style or higher fat DASH-style diet patterns | Seafood, whole grainsCertain vegetable oils (eg, soybean, canola, extra virgin olive)n-3 and n-6 polyunsaturated fats, plant-derived monounsaturated fatsPhenolic compounds | Cheese, low-fat milkCertain vegetable oils (eg, corn, sunflower, safflower)Total or animal-derived monounsaturated fatsCoffee, tea, cocoaVitamin D, magnesium, fish oil | Whole-fat milkStarchy vegetables other than potatoesCoconut oil |
| Harms of: | Partially hydrogenated vegetable oils, processed meatsHigh sodiumSugar-sweetened beverages, foods rich in refined grains, starches, added sugarsGreater than moderate alcohol use | Moderate sodiumWhite/russet potatoesHigh glycemic index/load | Saturated fats, dietary cholesterolUnprocessed red meats, eggsButter | Whole-fat milkPalm oil |
| Little effect of: | Total fat | Total carbohydrateIsolated antioxidant vitamins, calcium | Poultry100% fruit juiceTotal protein, specific amino acidsNoncaloric sweeteners | Concepts of local, organic, farmed/wild, grass fed, genetic modification |
The most well-studied dietary patterns are traditional Mediterranean and DASH diets (see http://circ.ahajournals.org/content/123/24/2870/T3.expansion.html). In comparison with the conventional low-fat, high-carbohydrate DASH diet, a modified DASH diet higher in vegetable fats and lower in carbohydrates – ie, more similar to a Mediterranean diet – produces larger cardiometabolic benefits.24–26 Both Mediterranean and DASH diet patterns improve a range of risk factors, reduce long-term weight gain, and are consistently associated with lower risk of clinical events.19,21,27–29 Pathways of benefit appear diverse, including effects on BP, glucose-insulin homeostasis, blood lipids and lipoproteins, inflammation, endothelial function, arrhythmic risk, and possibly coagulation/thrombosis, paraoxonase 1 activity, and the gut microbiome.20,21,30 Based on sociocultural and feasibility considerations, not every population in the world can consume a traditional Mediterranean diet. Other examples of Mediterranean-style dietary patterns, with adaption to various regions of the world, have been proposed.31
Randomized clinical trials in both primary and secondary prevention populations confirm the benefits of healthful, food-based diet patterns that were identified in prospective cohort studies and short-term interventional trials: such diets significantly reduce both cardiovascular events and diabetes mellitus.32–35 In comparison, both observational cohorts and randomized trials confirm little clinical benefit of diets focused on isolated nutrient targets, such as low-fat, low-saturated fat diets, which produce no significant benefits on cardiovascular disease, diabetes mellitus, or insulin resistance.36–39 This contrast in effectiveness of healthful, food-based versus nutrient-focused dietary targets is exemplified by comparing the results of 2 of the largest, longest-duration dietary trials ever performed (Figure 2).
Figure 2. Contrasting results of randomized controlled dietary trials focusing on isolated nutrients (Top) versus food-based diet patterns (Bottom). The Women’s Health Initiative (WHI, Top) focused on nutrient targets and reducing total fat and achieved large long-term changes in these targets, yet had no significant effect on cardiovascular disease or diabetes mellitus. The Prevención con Dieta Mediterránea (PREDIMED) trial (Bottom) focused on food-based diet patterns and increasing specific healthful foods, especially nuts and extra virgin olive oil (EVOO), with smaller dietary changes than in WHI, yet demonstrating significant reduction in cardiovascular disease and diabetes mellitus. Both trials successfully altered long-term diets, although with more modest dietary changes in PREDIMED. However, only the food-based intervention resulted in clinical benefit. CHD indicates coronary heart disease; CI, confidence interval; HR, hazard ratio; MI, myocardial infarction. Adapted from Howard et al36 with permission of the publisher. Copyright © 2006, JAMA; and Estruch et al34 with permission of the publisher. Copyright © 2013, The New England Journal of Medicine. Authorization for this adaptation has been obtained both from the owner of the copyright in the original work and from the owner of copyright in the translation or adaptation.
Based on this evidence, the 2015 Dietary Guidelines Advisory Committee concluded that low-fat diets have no effect on CVD and emphasized the importance of healthful, food-based diet patterns.21 Notably, because additives such as sodium and industrial trans fats can be added to or removed from otherwise similar commercially prepared foods, a specific emphasis on their reduction is also warranted.21
Focusing on overall diet patterns, rather than individual nutrients or foods, can also facilitate individual behavioral counseling and population dietary recommendations, because such patterns permit greater flexibility and personal preferences in diet choices.21 In addition, such patterns can lead to health benefits by means of smaller changes across several dietary factors, rather than major changes in a few factors, potentially increasing effectiveness and compliance.
People who follow vegetarian diets are often health conscious and tend toward healthful food patterns. However, vegetarianism per se is neither necessary nor sufficient for a good diet: indeed, french fries and soda are vegetarian, as are other harmful factors such as refined grains, starches, added sugars, sweets, trans fats, and sodium. Thus, a vegetarian diet is not a guarantee of health, whereas a nonvegetarian diet can be rich in healthful foods. A cardioprotective diet pattern must be characterized by the healthful foods that are included, not simply specific items to be avoided (Table 2).
Other increasingly popular dietary patterns include low-carbohydrate diets (minimizing all carbohydrates) and paleo diets (attempting to conform to food types consumed over millennia during human evolution). A main benefit of both low-carbohydrate and paleo diets is reduced refined grains, starches, and added sugars, which represent the majority of total carbohydrates and ultraprocessed foods in modern diets (see Carbohydrate-Rich Foods, below). Paleo diets also emphasize fruits, nonstarchy vegetables, nuts, and fish, each of which has health benefits. However, focus on low carbohydrate could paradoxically reduce intakes of other, healthful carbohydrate-containing foods such as fruits, legumes, and minimally processed whole grains; while paleo guidelines often recommend liberal intakes of red meats, lard, and salt and the avoidance of legumes and dairy. A maximally beneficial diet pattern should concurrently emphasize reductions in refined (not all) carbohydrates, processed meats, and foods high in sodium and trans fat; moderation in unprocessed red meats, poultry, eggs, and milk; and high intakes of fruits, nuts, fish, vegetables (excluding russet/white potatoes), vegetable oils, minimally processed whole grains, legumes, and yogurt (Figure 3).
Figure 3. Evidence-based dietary priorities for cardiometabolic health. The placement of each food/factor is based on its net effects on cardiometabolic health, across all risk pathways and clinical end points, and the strength of the evidence, as well. For dietary factors not listed (eg, coffee, tea, cocoa), the current evidence remains insufficient to identify these as dietary priorities for either increased or decreased consumption (see Table 3).
Diet Quality, Energy Balance, Obesity, and Weight Gain
Just as the science of cardiovascular risk is moving away from theories based on single-nutrient components and single-surrogate outcomes toward empirical evidence on foods and dietary patterns and clinical events, the science of obesity is moving away from simplistic ideas of energy balance, will power, and calorie counting toward the elucidation of effects of foods and diet patterns on the complex physiological determinants of long-term weight regulation. Of course, total calories matter in the short term, which is why people can initially lose weight on nearly any type of diet21 – and explaining why so many fad diets initially seem to work. In the short term, the best predictor of success is mindfulness with one’s chosen diet. However, for long-term weight maintenance and for cardiometabolic health independent of adiposity, healthful food–based patterns are most relevant (Table 2).21
Because obesity is so challenging to treat after it has developed, the primary prevention of weight gain is a promising strategy for individual patients and for populations. An average American adult gains only ≈1 lb (0.45 kg) per year,28 consistent with habitual excess energy intakes as small as ≈50 kcal/d explaining the gradual weight gain seen in many people.40 This finding accentuates just how well our body’s homeostatic mechanisms actually function to maintain long-term weight stability. Yet, when sustained over many years, this minor annual weight gain drives population obesity, eg, leading to 10 lbs weight gain over 10 years, 20 lbs over 20 years, and so on.
In many countries, the current obesity epidemic is a striking change from decades of prior relative stability; in the United States, for instance, obesity began steeply rising only about 30 years ago.41 Abdominal adiposity, which produces the largest metabolic harms, has also increased to a greater extent than overall weight in many nations, especially in younger women and certain middle-income countries.42 This modern rise in overweight and obesity is also occurring in children across most nations.43 The full long-term health consequences of adiposity in these youthful generations remain to be seen, in whom rates of type 2 diabetes mellitus, nonalcoholic fatty liver disease, dyslipidemia, and hypertension exceed anything observed at these ages in previous human history.44 The escalation of adiposity at youngest ages, including those <5 years of age, is also informative for considering potential causes. At such ages, population-wide declines in willpower, ability to count calories, or physical activity are difficult to invoke, reinforcing the likely role of environmental determinants of weight dysregulation.
Elucidating the specific dietary and nondietary determinants of long-term weight homeostasis is critical to understand and reverse the environmental changes contributing to this population imbalance. Growing evidence suggests that energy imbalance is a consequence of multiple complex, upstream effects, in particular poor diet quality (Figure 4). In other words, poor diet quality is a driver of excess diet quantity. Furthermore, independently of energy balance, diet quality influences metabolic risk and propensity toward abdominal adiposity. Mechanisms appear to include calorie-independent effects of different types of foods on satiety, glucose-insulin responses,45 liver fat synthesis,46 adipocyte function,47 visceral adiposity,48 brain craving and reward,49 and even metabolic expenditure.50 The gut microbiome also appears increasingly important; eg, probiotics in yogurt appear to interact with microbiota to reduce weight gain.28,29,51–54 In addition, independent of calories and body weight, one’s dietary pattern strongly influences metabolic dysfunction including the risk of diabetes mellitus.19,21 This is analogous to the weight-independent metabolic benefits of physical activity; diet quality has similar robust metabolic benefits (or harms).
Figure 4. Diet quality, obesity, and metabolic risk – a modern paradigm. Diet quality influences risk of adiposity through multiple pathways, including altering energy intake, energy expenditure, microbiome-host interactions, body fat composition, and metabolic function.
Based on these influences, when consumed over years, certain foods may interfere with long-term weight homeostasis, others have relatively neutral effects, and others promote healthy weight regulation (Figure 5).19,21 For long-term weight gain, food rich in refined grains, starches, and sugar appear to be major culprits.28,29 Such rapidly digested, low-fiber carbohydrates drive many obesogenic pathways.45,46,48–50 Key foods in this group include potatoes, white bread, white rice, refined breakfast cereals, crackers, sweets, soda, and other ultraprocessed foods high in starches or sugars. In contrast, intakes of other foods, such as low-fat milk and whole-fat milk, appear relatively neutral, suggesting they do not perturb the normal homeostatic mechanisms for long-term weight control.29,51 For meats, cheese, and eggs, influences on long-term weight gain appear to vary depending on whether they are consumed together with refined carbohydrates (in which case more weight gain is evident) or in place of refined carbohydrates (in which less weight gain or even relative weight loss is seen).29
Figure 5. Protein-rich foods and long-term weight gain in 3 separate US prospective cohort studies, based on 16 to 24 years of follow-up. Weight changes every 4 years are shown for each 1-serving/d increase in consumption; decreased consumption would be associated with the inverse weight changes. To convert pounds to kilograms to pounds, divide by 2.2. All weight changes were adjusted for age, baseline body mass index, sleep duration, and concurrent changes in smoking status, physical activity, television watching, alcohol use, and consumption of fruits, vegetables, glycemic load, and all of the dietary factors in the figure simultaneously. NHS indicates Nurses’ Health Study; and HPFS, Health Professionals Follow-up Study. Reproduced from Smith et al29 with permission of the publisher. Copyright © 2015, The American Journal of Clinical Nutrition.
Conversely, increased fruits, nonstarchy vegetables, nuts, yogurt, fish, and whole grains each appear to protect against chronic weight gain: the more these foods are consumed, the less the average weight gain.28,29,51,55 The mechanistic pathways underlying these observed benefits are still being elucidated, but may partly reflect opposing, protective effects in comparison with those of rapidly digested, refined carbohydrates.
Based on these complexities, choosing foods based on calorie content can lead to paradoxical dietary choices, industry formulations, and policy recommendations. For example, the US National School Lunch Programs recently banned whole milk, but allows sugar-sweetened chocolate skim milk.56 This untested intervention in 31 000 000 American children is based on hypothesized effects of total calories, total fat, and saturated fat in milk,56 rather than empirical evidence on the health effects of whole versus skim milk. Longitudinal studies suggest no harms of whole-fat milk for obesity, diabetes mellitus, or cardiovascular disease in adults28,29,51,57,58; that dairy fat may have potential benefits for diabetes mellitus59–61; that people switching to low-fat dairy products compensate elsewhere in their diet by increasing consumption of carbohydrates29; and that children who habitually drink low-fat milk gain more weight, and those who drink whole-fat milk gain less weight, over time.62–66 Many other ironies result from a calorie focus: eg, recommendations to consume fat-free salad dressing, in which healthful vegetable oils have been removed and replaced with starch, sugar, and salt; to minimize nuts because of their fat content and energy density; and to consume low-fat deli meats that are loaded with sodium.
In sum, modern evidence indicates that different foods have very different obesogenic potential depending on their influence on complex, multifactorial pathways of weight regulation. To prevent long-term weight gain, calories and portion sizes from certain types of foods should be minimized; from others, not emphasized; and from others, actually increased. Other conventional metrics – eg, total fat, energy density, even added sugar– may not reliably identify how specific foods influence weight gain.28,29,51 Consistent with this modern science, the 2015 Dietary Guidelines Advisory Committee Report emphasizes food-based, healthful diet patterns as a primary recommendation to address obesity.21
Several other lifestyle factors appear to interact with diet to influence adiposity. These include TV watching, sleep duration, circadian alignment, and possibly maternal-fetal (eg, placental) influences.28,41,67–70 For example, lower sleep duration and altered circadian rhythms are linked to greater weight gain and obesity, alter hunger and food preferences, and may influence leptin, ghrelin, insulin, and gut-peptide concentrations.28,67 Greater hours spent TV watching also independently increase obesity and weight gain28,68; 2 randomized trials in children suggest this is primarily mediated by changes in diet (rather than changes in, physical activity) owing to increased eating in front of the TV and altered food choices attributable to viewed marketing.71,72 Increasing physical activity, of course, has complementary benefits on weight maintenance and metabolic health. Other societal and environmental influences likely have additional effects, including education, income, race/ethnicity, social norms and networks, industry marketing, and local food availability.10,11,73
In sum, these complex and often insidious influences make unintended weight gain very easy. Conversely, based on these effects, modest behavioral and environmental improvements can attenuate or reverse chronic energy gaps, weight gain, and adiposity. Based on current available evidence, key diet-related priorities to reduce adiposity are reduction in refined grains, starches, sugars, and meats; limiting industry marketing especially from TV; increasing intakes of fruits, vegetables, nuts, yogurt, fish, vegetable oils, and whole grains; sleeping at least 7 to 8 hours nightly; and further elucidating maternal-fetal, microbiome, and sleep/circadian influences.
Individual Susceptibility – Genetics and Personalized Nutrition
Interest is growing in quantifying and understanding the determinants of interindividual variation in responses to diet. One aim is personalized nutrition – the ability to provide customized dietary advice specialized to each person’s unique profile of genes and other underlying characteristics.
Although candidate gene approaches have identified several potential gene-diet interactions for traits including blood cholesterol levels, a major challenge has been lack of replication.74–77 Even for better documented gene-diet interactions – eg, for the APOE locus, dietary saturated fat, and LDL-cholesterol; or for the CETP locus, alcohol, and high-density lipoprotein (HDL) cholesterol – evidence for clinical relevance of these differences remains weak.74 Large investigations pooling multiple cohorts have observed main (population) effects of either dietary influences or genes on major cardiometabolic risk factors, but evidence for interactions between diet and these genes is uncommon and, more relevantly, magnitudes of such potential interactions are often small.78–83 One of the more promising gene-diet interactions, notable in Hispanic populations, involves PNPLA3 and sugar consumption in relation to obesity and liver fat accumulation84–86; additional interaction with dietary polyunsaturated fats could also be present.87 Potential influences of diet on epigenetic changes (eg, DNA methylation) and subsequent cardiometabolic risk pathways are also of considerable interest,88 but relevant between-individual variation in these diet-epigenetic responses has yet to be identified. At present, compelling evidence is lacking to design personalized nutritional recommendations for cardiometabolic health based on genetic variation.
Other underlying individual characteristics may be better determinants of personalized guidance. For instance, carbohydrate-induced glycemic responses appear especially detrimental in women,89 suggesting the particular need for women to avoid rapidly digested carbohydrates. Other studies suggest that people with greater insulin resistance experience greater short-term weight loss with low-carbohydrate than with low-fat diets.90 Similarly, patients with diabetes mellitus, impaired glucose tolerance, or atherogenic dyslipidemia may also benefit most from reducing refined carbohydrates and increasing proteins and vegetable fats.91–93 In addition, personalized cognitive-behavioral and culturally and socioeconomically sensitive strategies increase effectiveness of clinical approaches to behavior change.94,95
Overall, although a promise of precision medicine has been promoted,96 the massive, rapid shifts in cardiometabolic disease occurring across nations and within populations over time97 demonstrate the dominant influence of environmental risk factors–and therefore the crucial importance of population approaches to address these environmental risks, including improved nutrition. In addition, population strategies to address diet, such as economic incentives, can reduce socioeconomic-related disparities in health, whereas individual-based approaches may exacerbate inequities.98,99 Evidence-based personalized approaches, especially related to underlying nongenetic characteristics, should be considered a complement to such population efforts.
Food Processing
Potential health effects of food processing are receiving increasing attention.100–102 Nearly all foods must undergo some processing to be consumed – eg, cooking, smoking, drying, salting, fermenting, preserving, heating, milling, refining. Benefits of processing include improved palatability, variety, nutrient bioavailability, shelf life, and convenience, and reduced risk of food-borne pathogens. Potential harms include loss of nutrients such as fiber, phenolics, minerals, fatty acids, vitamins, and other bioactives; increased doses and rapidity of digestion of starch and sugar; and introduction of harmful factors such as sodium, other preservatives, trans fats, heterocyclic amines, advanced glycation end products, and other compounds.
Many healthful foods are minimally processed (eg, fruits, nuts, seafood), whereas several classes of processed foods are harmful (eg, refined grains and cereals, preserved meats and other high-sodium foods, food made with partially hydrogenated oils). This can lead to an impression to always select “natural” and always avoid processed or ultraprocessed foods. Because many minimally processed foods are healthful, and many more highly processed foods are not, this can serve as a useful general rule. However, it is not absolute. For example, some more natural foods such as eggs, butter, and unprocessed red meats are not linked to improved cardiometabolic outcomes (see Foods, below), whereas other packaged or processed foods (eg, nut- and fruit-rich snacks, phenolic- and polyunsaturated-rich vegetable oils and margarines) improve cardiometabolic health.
Consequently, both the type of food and its processing are relevant. Rather than focusing only on natural versus processed, the clinician, consumer, policy maker, and food producer should emphasize foods that are both innately healthful and less processed; and reject foods rich in refined grains, starch, and added sugars and harmful additives such as sodium and trans fat (Table 2). In addition, as the global food system moves toward more processed foods,103 further rigorous investigation is needed to define and disseminate methods for optimal processing, rather than an impractical focus on complete absence of processing.
Dietary Supplements, Functional Foods
Use of dietary supplements, often at high or pharmacological doses, is commonplace, despite the absence of convincing evidence for health benefits. Many supplements have been evaluated in observational studies and controlled trials as potential therapies to prevent CVD or other conditions (Table 4).104–110 Evaluated doses in such trials have often exceeded usual or even recommended dietary intakes, often under the assumptions that higher levels would produce greater benefits, and that there was little risk of harm. Evidence has accrued that most of these supplements have little CVD benefit, and that certain supplements including β-carotene, calcium, and vitamin E may even be harmful.105–108,111–113 Presently, fish oil may be considered as a supplement for CVD prevention, especially among patients with prevalent CHD, based on reduction of cardiac death109 (see Fish, above). Overall, the current evidence does not support use of other dietary supplements to duplicate or complement the cardioprotective benefits of consumption of healthful foods.
| β-Carotene | Some cohort studies have linked low serum levels or low dietary intake of β-carotene with higher CVD risk. Trials of β-carotene supplements document no benefit in the general population and increased risk of lung cancer in patients who were at high risk of lung cancer. |
| Calcium | Meta-analysis of trials suggests that calcium supplementation could increase the risk of myocardial infarction. No evidence for cardiometabolic benefits. |
| Vitamin D | Evidence from observational studies indicates that low serum vitamin D levels, which are largely determined by sun exposure, are associated with higher risk of CVD. Trials of vitamin D supplementation have not shown reductions in risk of CVD. Additional trials using higher doses of vitamin D supplementation are ongoing. |
| Vitamin E | Several prospective cohort studies have linked vitamin E consumption or supplementation with lower risk of CHD. Trials have failed to show reductions in CVD events with supplemental vitamin E, and 2 meta-analyses suggest that high-dose vitamin E supplements may increase total mortality. |
| Folic acid, Vitamins B6, B12 | Observational studies have associated low folate intake, low serum folate levels, and high homocysteine levels with higher risk of CVD outcomes. Trials have confirmed that folic acid supplementation lowers blood homocysteine levels. Long-term trials have not documented benefits of folic acid with or without vitamin B6 and vitamin B12 on CVD outcomes. In some trials, supplemental folic acid was associated with increased risk of CVD. |
| Fish oil | Multiple cohort studies have documented an inverse relationship between fish intake and subsequent CHD, in particular, CHD death. A meta-analysis of trials, largely in higher-risk populations, demonstrated a reduction in cardiac death with fish oil supplementation, largely because of the benefits in patients with prevalent CHD. |
| Multivitamins | Although some cohort studies have seen lower CVD risk with multivitamin supplements, several trials, rated to be of fair to poor quality, have not documented any clear CVD benefit of multivitamin use in mixed populations. |
Similar to dietary supplements, functional foods attempt to improve health by incorporating bioactive compounds that may alter lipid, vascular, and other metabolic pathways, microbiome composition and function, and digestive and inflammatory systems.114–121 Such putative compounds include specific peptides, fatty acids, phenolics, vitamins, dietary fibers, prebiotics/probiotics, and plant sterols/stanols. Many of these bioactive compounds have demonstrated effects on cardiovascular risk pathways in animal and human studies; effects on blood lipids have been most often studied. To date, the potential impact of these and other promising functional foods on clinical end points is generally not established and requires investigation.
Based on cholesterol-lowering effects, some organizations suggest that functional foods with plant sterols/stanols can be considered for people with higher cholesterol levels who do not qualify for or have insufficient response to pharmacotherapy116; although others have concluded that plant sterols/stanols could have unacceptable toxicities.122,123 In the Prevención con Dieta Mediterránea (PREDIMED) trial, supplementation with extra virgin olive oil or mixed nuts, combined with advice to consume a Mediterranean-type diet, led to significant reductions in cardiovascular events,34 suggesting that these more natural foods could be considered as evidence-informed functional foods to reduce CVD events.
Emerging Issues: Organic, Genetic Modification
Public and media attention have increasingly considered whether foods are organic (ie, produced without artificial chemicals or pesticides) or genetically modified. Compared with conventionally grown foods, organically grown foods can contain higher concentrations of phenolic compounds and fewer pesticide residues; yet, they also have similar nutrient profiles in many other respects.124–126 Evidence for the health relevance of the observed differences in certain trace compounds has generally not been identified and remains controversial.127–129
Genetic modification uses biotechnology to alter crop or livestock genes to improve insect or virus resistance, herbicide tolerance, nutritional qualities, or resistance to environmental stressors. In light of challenges in population growth, global climate, soil and water availability, and changing pathogens, genetic modification holds promise to improve production, healthfulness, and sustainability. Several groups reviewing the evidence for the health hazards of genetic modification have found no evidence for harms130–134; however, methods for such evaluation remain heterogeneous.135–139 Based on first principles, genetic modification should be considered a tool, not an end point: its potential effects on human health (positive, neutral, negative) will relate to the specific compositional changes in the food, not to the method itself.140
Based on current evidence, whether a food is organic or genetically modified appears to be of relatively small health relevance in comparison with the overall types of foods and diet patterns actually consumed (Table 2). Health and environmental effects of both organic and genetically modified foods require continued evaluation as these technologies progress.
Foods and Cardiometabolic Health
Individual foods represent a complex matrix of fatty acids, proteins, carbohydrate quality, micronutrients, phytochemicals, and preparation and processing methods that together modify cardiometabolic risk.9,141 Inference on the health effects of different foods is optimally derived from well-designed prospective observational and interventional studies of clinical end points, together with supportive evidence from interventional studies of surrogate risk markers. Relevant mechanisms and pathways are further informed and elucidated by animal and experimental models. Cardiometabolic effects of different foods can be envisioned along a spectrum of benefit versus harm (Figure 3): when considering the health effects of any food, it is important to consider: compared with what?
Fruits, Nonstarchy Vegetables, Legumes, Nuts/Seeds
Minimally processed, plant-derived foods such as fruits, nonstarchy vegetables, beans/legumes, and nuts/seeds are consistently linked to better cardiometabolic outcomes (Figure 6).142–145 These observed long-term benefits are supported by controlled trials of surrogate outcomes and clinical end points using dietary patterns rich in these foods.19–21 The effects of specific subtypes of these foods are less well established. The foods richest in phytochemicals (eg, berries, nuts) appear to be particularly potent.
Figure 6. Meta-analyses of foods and coronary heart disease, stroke, and diabetes mellitus. BMI indicates body mass index; CHD, coronary heart disease; CI, confidence interval; CVD, cardiovascular disease; PC, prospective cohort; RCT, randomized clinical trial; and RR, relative risk.
Starchy Vegetables
Potatoes are a widely consumed starchy vegetable. Although potatoes contain fiber, potassium, vitamins C and B6, and other trace minerals, they predominantly contain starch (long chains of glucose) that is rapidly digested in the mouth and stomach. This high-glucose load and rapid digestion would predict cardiometabolic harms, similar to white rice and white bread (see Carbohydrate-Rich Foods, below). Relatively few long-term studies have assessed potatoes and cardiometabolic outcomes. Among those that have, higher intake of potatoes, including boiled and baked potatoes, is prospectively linked to higher incidence of diabetes mellitus, whereas potatoes, corn, and peas are linked to greater long-term weight gain, in contrast to nonstarchy vegetables that are associated with protection against weight gain and diabetes mellitus.28,55,146,147 Potatoes have also been cross-sectionally linked to greater diabetes mellitus, higher blood glucose, and lower HDL-cholesterol,148 and, in retrospective studies, higher risk of stroke.149 Based on these concerns, russet/white potatoes are generally excluded from recommendations to increase vegetable consumption.
The long-term effects of other specific varieties of potatoes or other starchy vegetables are less established. Cassava is starch-rich, similar to peeled potatoes, but the long-term cardiometabolic effects remain uncertain150,151; glycemic responses may be ameliorated by its consumption in mixed meals. Similarly, the long-term health effects of yams, sweet potatoes, and parsnips (which each tend to contain relatively less starch relative to fiber compared with russet or white potatoes), corn (which can be considered either a grain or vegetable), and peas (which is a legume) are not well established. In recent work, among major vegetables consumed in the United States, potatoes, corn, and peas were each associated with long-term weight gain, whereas other vegetable subtypes were each associated with weight loss.55
Based on high-starch content, greater glycemic responses, and some adverse long-term associations with clinical endpoints, high intakes of potatoes are not advisable. If consumed, small portion sizes, including the (nutrient-rich) skin, and mixed meals (eg, mixed with healthful foods such as vegetable oils, fish, nonstarchy vegetables) would be prudent.
Carbohydrate-Rich Foods
Carbohydrate-rich foods comprise about half or more of all calories in most diets globally. Although total carbohydrate consumption has little relation to cardiometabolic health, the quality of carbohydrate-rich foods is linked to risk (Figures 6 and 7).152–160 Notably, the conventional chemistry-based classification of simple (sugar) versus complex (starch) carbohydrates has little physiological relevance, because saccharide chain length has little influence on digestion rate or metabolic effects of different carbohydrates. More meaningful characteristics include dietary fiber content, glycemic responses to digestion, processing (intact, partially milled, fully milled, liquid), and whole-grain content.19
Figure 7. Meta-analyses of nutrients and coronary heart disease, stroke, and diabetes mellitus. CHD indicates coronary heart disease; CI, confidence interval; LA, linoleic acid; PC, prospective cohort; RCT, randomized clinical trial; RR, relative risk; and SFA, saturated fatty acid.
Each of these metrics can be altered relatively independently (Figure 8). Whole grains include endosperm (starch), bran (fiber, protein, B vitamins, minerals, flavonoids, tocopherols), and germ (protein, fatty acids, antioxidants, phytochemicals). When whole grains are intact (eg, quinoa) or partially intact (eg, steel-cut oats, stone-ground bread), the bran protects the starchy endosperm from oral, gastric, and intestinal digestion, thereby reducing glycemic responses. In finely milled whole-grain products (eg, most whole-grain breads, breakfast cereals), the bran (fiber) and germ content remain similar, but the exposed endosperm can be rapidly digested, resulting in higher glycemic responses. When the bran and germ are removed entirely (eg, refined grains: white bread, white rice, most cereals and crackers), only starchy endosperm remains, with high glycemic response and containing little fiber, minerals, or other nutrients. Some high-starch vegetables (eg, russet or white potatoes) have similar metabolic characteristics as refined grains (see Starchy Vegetables, below). Refined grains and high-starch vegetables are digested rapidly, with blood glucose and insulin responses that can be similar to simple sugars. Finally, sugars in liquid form (eg, soda, sports drinks, sweetened ice teas) appear even less satiating and more obesogenic than equivalent sugar in solid form (see Sugar-Sweetened Beverages, Noncaloric Sweeteners; and Carbohydrates, Added Sugars, Fructose; below).
Figure 8. For defining carbohydrate quality, several characteristics appear to independently alter the cardiometabolic health effects of carbohydrate-rich foods. These include whole-grain content (top left panel), ie, based on the content of milled, semiprocessed, or intact whole grain including the bran and germ; fiber content (top right panel), influenced largely by the content of bran; food structure (bottom left panel), in particular, whether the food is solid or liquid (such as sugar-sweetened beverages); and glycemic response (bottom right panel), determined by the amount and accessibility of starch and sugar. GI indicates glycemic index.
Based on these effects, refined grains (starchy endosperm without the bran or germ), other starch-rich foods (eg, white potatoes), and added sugars appear to induce relatively similar cardiometabolic harms. When starch enters the mouth without the natural shelter of a whole-grain or fiber-rich food structure, oral amylase promptly initiates its breakdown into free glucose, a process rapidly completed in the upper small intestine. Consequently, refined grains such as white bread, corn flakes, and rice; starchy foods such as russet or white potatoes; and pure table sugar all produce brisk rises in blood glucose and insulin (known as their glycemic index; or, when multiplied by portion size, as their glycemic load).161 This rapid digestion may induce multiple adverse effects, potentially stimulating reward/craving areas in the brain, activating hepatic de novo lipogenesis, increasing uric acid production, and promoting visceral adiposity.49,162–166 In addition, high glycemic load diets may even reduce total energy expenditure.50
In addition to direct harms, low-quality carbohydrates such as refined grains, certain potatoes, sugar-sweetened beverages (SSBs), and sweets may increase cardiometabolic risk by displacing other, healthier foods in the diet, eg, fruits, vegetables, nuts, legumes, and minimally processed whole grains. Consistent with this constellation of adverse effects, poor-quality carbohydrates are associated with long-term weight gain, diabetes mellitus, and CVD.29,89,158,167 Harms appear to be larger in women89,167 and others predisposed to insulin resistance and atherogenic dyslipidemia, and smaller in men and in younger, lean individuals with high physical activity.
Based on their adverse effects and pervasiveness in modern diets, reducing refined grains, starches, and added sugars is a major dietary priority for cardiometabolic health.21 Although SSB intake is declining in the United States, intakes of added sugars in other foods and, even more so, of refined grains continue to represent a major part of the diet. Currently, nearly 3 in 4 Americans consume too many refined grain products.21 Indeed, many people seek out these products, erroneously believing they are beneficial based on their promotion as low-fat or fat-free foods. Recognizing this pervasive confusion, the 2015 Dietary Guidelines Advisory Committee specified that, “consumption of ‘low-fat’ or ‘nonfat’ products with high amounts of refined grains and added sugars should be discouraged.”21 Because of the multiple independent characteristics that influence carbohydrate quality (eg, fiber, glycemic response, processing, whole-grain content), no single criterion appears perfect for distinguishing carbohydrate-rich foods. Among several recommended metrics, a ratio of total carbohydrate to dietary fiber (g/serving) of <10:1 is a helpful practical guide to identify more healthful grain choices.168,169
Meats
Similar to many other foods, guidelines on meat consumption in cardiometabolic health were historically based on minimally adjusted ecological comparisons and theorized effects of isolated nutrient content (eg, saturated fat, dietary cholesterol). However, modern evidence supports relatively neutral cardiovascular effects of saturated fat and dietary cholesterol and more relevant effects of other compounds in meats, such as heme iron, sodium, and other preservatives (see Nutrients and Cardiometabolic Health, below).
Consistent with these findings, although a minority of individual studies suggest similar cardiovascular risk for unprocessed red meat versus processed meats,170,171 many other individual studies and meta-analyses support a much stronger effect of processed meats, including low-fat deli meats, on CVD (Figure 6).172–174 Based on the observed effect sizes and relationships seen with other, noncardiovascular outcomes, residual confounding could explain some or all of the observed modest associations of unprocessed red meat with CVD.175 In contrast, the observed association of processed meats with CVD is quite plausible: much of it can be explained merely by the predicted effects of the high levels of sodium (~400% higher in processed meats) on BP levels and the subsequent effects of this elevated BP on clinical endpoints.176 Diet-microbiome interactions may also play a role,177 although such interactions would predict similar or stronger risk for unprocessed red meats than processed meats, when in fact the reverse is seen in many populations.
Interestingly, both red and processed meats, regardless of fat content, are linked to a higher incidence of diabetes mellitus, although with approximately double the risk, gram-for-gram, for processed meats than for unprocessed red meats.172,178 Mechanisms require further study, but this observed risk for diabetes mellitus may be linked to iron content179,180 and possibly lipid and amino acid metabolites, advanced glycation end products, trimethylamine N-oxide, and nitrates/nitrites.181,182
In sum, these findings provide little support for conventional guidelines to choose meats based on fat content, ie to focus on selecting lower-fat or lean meats. Rather, it would be prudent to consume small amounts of unprocessed red meats (eg, 1–2 servings/wk) to obtain readily bioavailable iron and zinc, while minimizing or entirely avoiding processed meats such as bacon, sausage, salami, and low-fat processed deli meats (chicken, turkey, pork, roast beef).183
Differences in bovine feeding systems can influence nutrient contents of meats. For example, in comparison with grain, grass feeding results in less intramuscular fat and therefore, when visible (extramuscular) fat is trimmed away, higher contents of omega-3 polyunsaturated fats, conjugated linoleic acid, and vitamins A and E, and lower contents of saturated, monounsaturated, and trans-18:1 fats.184,185 However, although grass feeding consistently increases the relative proportions (as a percent age of total fatty acids) of omega-3 fats, the absolute content (g per 100 g beef) can be the same, higher, or even lower because of decreased total fat content of the meat.184,185 Thus, the health implications of grass feeding and these modest nutrient differences require further study.
Poultry, Eggs
Relatively few studies have focused on poultry as a risk factor for CVD or diabetes mellitus, with few systematic reviews or meta-analyses (Figure 6).174 In several large studies, poultry is not significantly associated with CVD events;174,186–189 and in other cohorts, with modestly lower risk of CVD, with smaller observed benefits than seen for fish, nuts, or legumes.52,53 Large studies evaluating poultry and incident diabetes mellitus have shown mixed results including higher risk, no risk, and lower risk.178,190–195 These conflicting findings do not permit a strong inference on the cardiometabolic effects of poultry.
Egg consumption has no significant association with incident CVD in general populations (Figure 6).196,197 Conversely, eggs may influence and interact with diabetes mellitus.197 Frequent consumers (7+ eggs/wk) have higher new-onset diabetes mellitus; and among patients with prevalent diabetes mellitus, frequent consumers experience more clinical CVD events. On the other hand, higher egg consumption is associated with lower risk of hemorrhagic stroke,196 potentially related to the protective effects of dietary cholesterol on vascular fragility.198,199 As with poultry, the relevance of these conflicting findings remains uncertain. Overall evidence suggests small cardiometabolic effects of occasional consumption (eg, up to 2–3 eggs/wk); and possible harm with frequent consumption, especially among diabetics patients. Of note, the 2015 Dietary Guidelines Advisory Committee concluded that dietary cholesterol is not a “nutrient of concern for overconsumption,”21 based on low mean population cholesterol intake and no appreciable relationships between dietary cholesterol and serum cholesterol or clinical cardiovascular events in general populations.21a
In sum, occasional consumption of poultry and eggs appears relatively neutral for cardiometabolic health, without strong evidence for either risks or benefits. Until more evidence is generated, it may be prudent to consider these foods as healthful alternatives to harmful foods (eg, processed meats, refined grains, sugars) and yet as relatively unhealthy alternatives in comparison with beneficial foods (eg, fish, nuts, legumes, fruits).
Fish
The cardiovascular effects of fish and omega-3 consumption have been studied for decades. In comparison with little or no consumption, moderate consumption of fish (≈2+ servings/wk) and long-chain omega-3 (≈250 mg/d) associates with lower risk of fatal CHD (Figures 6 and 7).200–202 In contrast, higher intakes do not appear to appreciably reduce risk further. In comparison with fatal cardiac events, fish consumption has weaker associations with nonfatal cardiac events and with stroke.201,203,204 The specificity for fatal CHD, rather than all CVD events, suggests that this association may not be fully explained by residual confounding. This finding is also consistent with meta-analyses of randomized fish oil trials that demonstrate risk reductions for cardiac death, but not total CVD, CHD, or stroke.109 However, these latter pooled results obscure the differences in results of individual randomized trials over time: 4 of 5 earlier trials, yet none of several newer trials, demonstrate benefits.205 These discrepant results could be attributable to more aggressive lipid- and BP-lowering drug treatment in recent trials. Alternatively, because the dose-response effect of omega-3’s for fatal CHD appears nonlinear,200,201 higher background intakes of fish among subjects enrolled in more recent trials may have diminished the ability to detect any benefits of adding fish oil.205 Additional clinical trials of fish oil supplements are ongoing,206 but may not be adequately powered to evaluate fatal (rather than total) CHD or subgroups with low fish intake, for whom the benefits appear most plausible.
Notably, in meta-analyses of multiple controlled interventions, fish and omega-3 consumption improve major physiological risk factors for CVD including BP, heart rate, endothelial function, triglycerides, and adiponectin.201,205 Omega-3s also reduce inflammatory biomarkers, reduce myocardial oxygen use, and enhance cardiac function.201,205 Overall, although the null results of recent fish oil trials are concerning, the cumulative evidence from observational studies, clinical trials, and controlled interventional studies continues to favor plausible cardiovascular benefits of modest dietary fish consumption, in particular for the endpoint of CHD death. Based on conflicting findings from recent trials, fish oil supplementation has uncertain benefits but an excellent safety profile and may be considered as an adjunct to fish intake or for high-risk patients who do not eat fish.
The effects of fish consumption on other vascular conditions including stroke, heart failure, atrial fibrillation, and cognitive decline remain unclear, with conflicting findings.201,203,207,208 Fish and omega-3 intake also have little association with the risk for diabetes mellitus, although protective associations are seen in Asian populations209–211 and fish oil supplementation modestly raises adiponectin.212 Types of fish consumed and preparation methods may influence cardiometabolic effects, with greatest benefits perhaps obtained from nonfried, dark-meat (oily) fish that contain up to 10-fold higher omega-3 fatty acids than white-meat fish.201
Growing evidence suggests that the presence of persistent organic pollutants (eg, dioxins, polychlorinated biphenyls) may partly reduce cardiometabolic benefits of fish consumption213–215; less evidence suggests a potential for net harm, due to the countervailing benefits of omega-3s. Methylmercury consumed from fish has no detectable influence on incident cardiovascular events, hypertension, or diabetes mellitus.216–218 To optimize neurodevelopment in their children attributable to the benefits of fish consumption, women who are or may become pregnant or nursing should follow US Food and Drug Administration guidance to eat 2 to 3 servings/wk of a variety of fish lower in mercury, while avoiding only selected specific species (Gulf of Mexico tilefish, shark, swordfish, king mackerel; albacore tuna up to 6 oz/wk).219
While patients often ask about health effects of farmed (aquaculture) versus wild-caught species, few species are commonly available as both: most are either predominantly farmed (eg, tilapia, catfish, carp, shrimp, oysters) or wild-caught (eg, tuna, pollock, crab, cod).220 One exception is salmon, of which about one-third are wild-caught (principally from Alaska) and two-thirds are farmed (eg, from Norway, Chile). Because farmed salmon are fed, while wild salmon hunt for their food, farmed salmon have similar or higher levels of omega-3 fatty acids201 and likely similar net health benefits.200
Milk, Cheese, Yogurt
The cardiometabolic effects of different dairy foods represent a major unanswered question of modern nutrition science. Most dietary guidelines simply group different types together (eg, grouping milk, cheese, and yogurt as “dairy”), categorize these by fat content, and then recommend selection of low-fat products.21 Such recommendations largely derive from theoretical considerations about selected single nutrients (calcium, vitamin D, calories, saturated fat), rather than empirical evidence on health effects of the actual foods.
In longitudinal studies evaluating habitual intakes of dairy foods, relationships with CVD and diabetes mellitus do not consistently differ by fat content but appear more specific to food type: eg, cheese, yogurt, milk, butter (Figure 6).57,221–226 For example, the intake of yogurt, but not milk, is consistently associated with lower incidence of diabetes mellitus, whereas the intake of cheese, which has high calorie, fat, and saturated fat content, is also associated with lower diabetes risk in several although not all studies.57,179–184,224,226–228 Although total milk intake is generally unassociated with diabetes mellitus, fermented milk is linked to lower risk,57,227,229 suggesting a potential influence of fermentation, particularly in light of the separate findings for cheese. Bacterial cultures used for fermentation can synthesize vitamin K2 (menaquinones), which may improve insulin sensitivity.230,231 These findings suggest that the health effects of dairy may depend on multiple complex characteristics, eg, probiotics in yogurt, fermentation of cheese. The metabolic effects of specific dairy foods and fermented products represent promising areas for further investigation.
In short-term randomized trials, adding milk or dairy to energy-restricted diets increases lean mass and reduces body fat, whereas no significant body compositional effects are seen when adding dairy to ad libitum diets.232,233 Long-term effects may vary by the type of dairy. For instance, children who drink more low-fat milk gain more weight, whereas those who drink more whole-fat milk gain less weight, over time.62–66 In longitudinal studies among adults, neither low-fat nor whole-fat milk are appreciably related to chronic weight gain.28,29,51 This lack of difference may relate to caloric compensation: when adults consume more low-fat dairy, they compensate in the long term by increasing their consumption of carbohydrates.29
The STRIP trial randomly assigned 1062 Finnish infants to dietary intervention versus control, with follow-up for up to 20 years. For the first 3 years, the intervention focused on lowering total fat and saturated fat, while also increasing unsaturated fats from canola oil, other vegetable oils, and fish. At 3 years, no differences were seen in body weight, even among children most compliant with the low-fat diet.234 Subsequently, the intervention group received comprehensive dietary counseling, including to replace saturated fat with unsaturated fat, reduce salt intake, replace refined grains/cereals with whole grains, increase dietary fiber, increase fruits and vegetables, avoid smoking, and be physically active.235 The control group received only basic health education. Unsurprisingly, this comprehensive lifestyle advice, in comparison with no intervention, improved metabolic health.235 These results provide little inference on the specific effects of lowering saturated fat or dairy fat among children.
The impact of cheese consumption on long-term weight may vary depending on how it is consumed: more weight gain is seen when cheese is accompanied by refined carbohydrates, and less weight gain or even relative weight loss when cheese replaces refined carbohydrates.29 Yogurt appears protective against long-term weight gain,28,29,51 although when sugar-sweetened, approximately half the benefit appears lost.29 Animal-experimental studies and trials in humans suggest that probiotics and probiotic-microbiome interactions play a key role in the protective effects of yogurt, both for obesity and related conditions such as gestational diabetes.52–54,236–241
Interestingly, dairy fat itself may promote cardiometabolic health. In cohorts using objective blood biomarkers, greater dairy fat consumption is associated with a lower incidence of diabetes mellitus59–61,242,243 and CHD,39,244,245 and with mixed findings for stroke.246 It remains unclear whether such findings relate to health benefits of specific dairy fatty acids (eg, branched-chain fatty acids, medium-chain saturated fats, specific ruminant trans fats), other lipid-soluble factors in dairy fat, other factors in high-fat dairy foods (eg, production of vitamin K2 from fermentation of cheese), or unknown endogenous (nondietary) determinants of these blood biomarkers.247 Whatever the explanation, little evidence supports the opposing hypothesis, ie, the superiority of low-fat dairy products for health, including for risk of obesity.
In sum, dairy products represent a diverse class of foods, with complex effects that vary by specific product type and with emerging mechanistic pathways that appear to include influences of fermentation and probiotics. No long-term studies support harms, and emerging evidence suggests some potential benefits, of dairy fat or high-fat dairy foods such as cheese. Together these findings provide little support for the prevailing recommendations for dairy intake that are based largely on calcium and vitamin D contents, rather than complete cardiometabolic effects; that emphasize low-fat dairy based on theorized influences on obesity and CHD, rather than empirical evidence; or that consider dairy as a single category, rather than separately evaluating different dairy foods. The current science supports consuming more yogurt and possibly cheese; with the choice between low-fat versus whole-fat being personal preference, pending further investigation. This new evidence also calls for substantial further investment in research on cardiometabolic effects of dairy foods, including relevant components and molecular mechanisms.
Butter
In a large pooling project of European cohorts, individuals consuming any butter, in comparison with none, experienced a lower risk of diabetes mellitus.248 However, among butter consumers, no further dose-response was seen, suggesting potential for reverse causation (bias) among nonconsumers. In either case, these findings would suggest that butter is, at worst, neutral for diabetes mellitus. Butter consumption is also not significantly associated with incident CHD,223 stroke,222 or total mortality58 (Figure 6). Remarkably few studies have reported on these relationships, suggesting potential for publication bias. Because such bias would skew toward the reporting of large associations, the absence of significant associations in published reports makes it implausible that multiple other studies have identified but not reported harmful relationships. Increases in butter consumption are associated with modestly greater long-term weight gain.29 In sum, butter appears relatively neutral for cardiometabolic health, consistent with findings for total saturated fat (see Saturated Fat, below); and slightly adverse for long-term weight regulation.
Vegetable Oils
The cardiometabolic effects of vegetable oils have conventionally been considered in light of their fatty acid composition, ie, of monounsaturated, polyunsaturated, and saturated fats (see sections on each of these fats, below). Emerging evidence suggests that health effects may also relate to other constituents, in particular, flavonoid (phenolic) compounds (see Phenolic Compounds, below).30,249–252 For instance, extra virgin olive oil contains oleocanthal, a phenolic that binds cyclooxygenase (COX) 1 and 2 receptors (causing a characteristic burning throat sensation, similar to that induced by chewing no coated aspirin) and exhibits anti-inflammatory properties.30,251,252 In the PREDIMED randomized trial, participants receiving extra virgin olive oil and dietary advice to consume a Mediterranean diet experienced 30% lower risk of stroke, MI, or death, in comparison with control.34 In the intervention group, ≈60% of the extra virgin olive oil simply replaced regular olive oil, commonly used in Spain. These findings, together with mixed evidence for cardiovascular benefits of monounsaturated fats21 (see below), which represent most of the fats in olive oil, suggest that fatty acid profiles may not be the only relevant determinant of health effects of oils.
Little investigation has been done on the long-term health effects of tropical oils, such as palm or coconut. These oils contain saturated fat, but also other compounds, eg, medium-chain fatty acids in coconut oil that could have health benefits.253 Modern nutritional science has demonstrated the limitations of drawing conclusions about health effects of any food product based on theories about its nutrient contents.9 Thus, long-term investigations are urgently needed to make evidence-informed decisions about avoiding or increasing the use of tropical oils. Industrially interesterified oils are increasingly common, but similarly without long-term evidence on their health effects or safety.254
Based on overall evidence for cardiometabolic effects, the current evidence supports generally increased consumption of vegetable oils in place of refined grains, starches, sugars, meats, butter, and lard. Among different oils, the benefits of soybean, extra virgin olive, and canola oil may be best established. Virgin oils (eg, extra virgin olive oil, virgin soybean oil) may be preferable because of their low-temperature refining that may better preserve trace phenolic compounds; further study of how processing methods of vegetable oils influence phytochemicals and health effects is needed. In the future, certain vegetable oil blends may offer particular cardiometabolic benefits, eg, combining flax and safflower oils, or canola oil and omega-3 fatty acids.255 Sufficient evidence to support strong promotion or avoidance of tropical oils is lacking. Additional metabolic and long-term studies of different specific vegetable oils, including refined and unrefined versions, are urgently needed.
SSBs, Noncaloric Sweeteners
Both long-term prospective cohorts and clinical trials demonstrate that SSBs increase adiposity.256 Per serving, SSBs associate with greater long-term weight gain than nearly any other dietary factor.28 These effects are likely attributable to their high glycemic and insulin responses and low satiation (see Carbohydrate-Rich Foods, above). SSBs are also associated with increased incidence of diabetes mellitus and CHD (Figure 6).257,258 These effects appear partly but not entirely mediated by adiposity, consistent with independent adverse effects of SSBs on other pathways such as hepatic de novo lipogenesis, visceral fat accumulation, and uric acid production (see Carbohydrate, Added Sugars, Fructose, below). Globally, SSB consumption is highest at younger ages,259 boding poorly for long-term global health if such high intake continues as these populations age. Worldwide, 184 000 cardiometabolic deaths per year are estimated to be attributable to SSB consumption.260
With growing policy attention on sugar-sweetened beverages and added sugars, the food industry is increasingly seeking low-calorie and noncaloric alternatives.261 These include artificial sweeteners (eg, saccharin, sucralose, aspartame) and natural low-calorie (also termed high-intensity or nonnutritive) sweeteners (eg, stevia). Based on long-term observational studies and intermediate-duration (eg, 2 years) clinical trials,28,256 these appear to be better alternatives than sugar for people who consume large quantities of SSBs. However, based on animal experiments and limited human data, these artificial and nonnutritive sweeteners may not be benign, with potential for impact on cognitive processes (eg, reward, taste perception), oral-gastrointestinal taste receptors, glucose-insulin and energy homeostasis, metabolic hormones, and the gut microbiome.262–265 Cognitive effects, for example, may be especially relevant in children: if tastes become accustomed to such intense sweetness, will palates and attraction be reduced for naturally sweet, healthful foods such as apples or carrots? In sum, based on limited available evidence, artificial and nonnutritive sweeteners appear to be a useful intermediate step to reduce harms of SSBs (eg, to switch from regular to diet soda) but should subsequently also be reduced (eg, to switch from diet soda to seltzer water) to prevent potential long-term harms. Other uses of such sweeteners should not yet be considered innocuous for cardiometabolic health.
100% Fruit Juice
Although SSB and 100% fruit juice have similar sugar content, the latter is linked to relatively smaller long-term weight gain.28 Furthermore, the intake of sugar-sweetened fruit juice, but not 100% fruit juice, is associated with incident diabetes mellitus in longitudinal studies (Figure 6).257,266 These findings suggest that 100% fruit juice may have other beneficial components, eg, dietary fiber, vitamins, and phytochemicals, that at least partly offset any harms. In short-term trials, fruit juice has no appreciable effects on blood pressure, cholesterol levels, or glucose-insulin homeostasis.267,268 In sum, moderate intake of 100% juice (eg, up to one serving/d) appears reasonable, especially given the low intakes of whole fruit in most populations; higher intake of 100% juice may not be prudent because of links to long-term weight gain.
Coffee, Tea
While coffee is commonly thought of in relation to its caffeine content, it represents a liquid extract of legumes (coffee beans) that contains many active compounds. Both caffeinated and decaffeinated coffee are associated with lower onset of diabetes mellitus in a dose-dependent fashion (Figure 6).269 Coffee intake also is associated with lower risk of CHD and stroke but in a nonlinear fashion: in comparison with no intake, the lowest risk is seen at 3 to 4 cups/d, with increasing risk at higher intakes.270 Several small controlled trials have evaluated the potential effects of habitual coffee consumption on cardiometabolic risk factors, with mixed and inconsistent findings to date.271–273 A Mendelian randomization study, evaluating genetic variants linked to coffee intake, did not find associations with any cardiovascular or metabolic risk factors.274
Similar to coffee consumption, tea consumption is associated with a lower risk of diabetes mellitus and CVD, especially comparing very frequent consumption (3–4 cups/d) with none (Figure 6).275,276 Yet, controlled trials of tea have not identified robust benefits on markers of glucose-insulin homeostasis.277,278 In comparison, in meta-analyses of trials, green tea, black tea, and herbal roselle tea each modestly lower BP,279–281 whereas green and black tea, but not herbal roselle tea, also lower LDL-cholesterol.282–284
Overall, observational studies support potential cardiometabolic benefits of both coffee and tea. Plausible biological mechanisms that could explain the size of these associations have not been confirmed, with the exception perhaps for tea and cardiovascular risk. Based on current data, tea and coffee do not increase cardiometabolic risk and can be safely consumed, and green and black tea may reduce cardiovascular risk. Further research on these potential benefits is needed before actively encouraging consumption as a means to reduce risk.
Alcohol
Habitual heavy alcohol use causes up to one-third of nonischemic dilated cardiomyopathy in many nations.285 Ventricular dysfunction is often irreversible, even when alcohol use is stopped; while continued drinking is associated with high mortality. Habitual alcohol and acute binges are associated with higher risk of atrial fibrillation.286 Like other liquid calories (with the exception of milk), alcohol intake also is associated with higher long-term weight gain.287 Conversely, in comparison with nondrinkers, regular moderate alcohol consumption – up to ≈2 drinks per day for men, ≈1 to 1.5 drink per day for women – is associated with lower incidence of CHD and diabetes mellitus, although not stroke.288,289 Such observational analyses could partly overestimate benefits, because never drinkers could include those who have avoided alcohol because of unmeasured factors that relate to later poor health.290 Yet, magnitudes and consistency of observed lower risks of CHD and diabetes across diverse populations, together with favorable effects on HDL-cholesterol, insulin resistance, and fibrinogen in controlled trials,291 provide strong evidence for at least some cardiometabolic benefit of moderate alcohol use. Although a common perception is that the effects are specific to red wine, cardiometabolic benefits have also been seen for white wine, beer, and spirits.292 This could relate to the physiological effects of alcohol itself,291 or the phenolics in wine and beer, as well.292
Alcohol use exhibits a “J-shape” with all-cause mortality, with lowest risk observed between 1 drink/wk and 1 drink/d, and higher risk thereafter.289 In addition, the pattern of drinking is important: benefits are seen with moderate use across multiple days per week, not with high levels on a few days.293 Across the population, alcohol produces net harms because of the increased risk of cancers, liver disease, cardiomyopathy, accidents, violence, homicides, and suicides.1,294 Thus, alcohol intake should not be recommended as a means to reduce CVD risk. Adults who already drink alcohol should be advised to limit their use to moderate levels.
Nutrients and Cardiometabolic Health
Phenolic Compounds
Bioactive polyphenols include flavonols (eg, in onions, broccoli, tea, various fruits), flavones (in parsley, celery, chamomile tea), flavanones (in citrus fruits), flavanols (flavan-3-ols) such as catechins and procyanidins (in cocoa, apples, grapes, red wine, tea), anthocyanidins (in colored berries), and isoflavones (in soy). In laboratory studies and randomized trials, flavonoid-rich cocoa has small but measurable benefits on BP, endothelial function, insulin resistance, and blood lipids.295–297 BP-lowering occurs with as little as 6.3 g/d (30 kcal/d) of commercial dark chocolate and correlates with increased endothelial nitric oxide production.298 The latter mechanism also suggests potential cardiovascular benefits beyond lower BP per se. A few short-term trials of other dietary sources (eg, tea, red wine, grapes) or specific flavonoid extracts have not consistently improved BP, lipid levels, or endothelial function.295–297 Some observational studies evaluating total or selected dietary flavonoids observe lower risk of cardiometabolic events299,300; no long-term clinical trials have been performed. The remarkable heterogeneity of different flavonoids and their dietary sources limits inference for class effects, and clinical benefits and dose-responses are not well-established. Yet, many foods with growing evidence for cardiometabolic benefits – eg, berries,301 nuts,145 extra virgin olive oil34 – are rich in phenolics, and the documented physiological effects are promising and provide clear impetus for further study.
Sodium
In North America and Europe, most sodium (≈75%) comes from packaged foods and restaurants, and a minority from home cooking or table salt; whereas in Asian countries, most sodium comes from soy sauce and salt added during cooking or at the table.302 Nearly every country in the world exceeds the recommended mean national intake of 2000 mg/d.303
Sodium raises BP in a dose-dependent fashion, with stronger effects among older individuals, people who have hypertension, and blacks.304 In meta-analyses of longitudinal studies, high sodium intakes are associated with incident total stroke, stroke mortality, and CHD mortality (Figure 7).305–307 This is supported by the strength of BP as a surrogate outcome308 and by ecological and experimental studies of sodium and CVD.304 Indeed, the latter studies suggest that chronically high sodium induces additional, BP-independent damage to renal, myocardial, and vascular tissues.309,310
Nearly all observational studies demonstrate a positive association between very high sodium intakes (eg, 4000+ mg/d) and CVD events, in particular stroke.305–307 Some studies have also observed a potential J-shaped relationship, with increased CVD risk at modest intakes (eg, <3000 g/d).311–313 These findings have generated recent controversy about the optimal lowest levels of sodium consumption.314
The assessment of sodium in observational studies, whether by urine spot, 24-hour collection, or diet questionnaire, has unique potential biases.315 These include potential for incomplete 24-hour urine collections (leading to underestimation of sodium intake, especially in less compliant, sicker individuals); reverse causation (ie, due to at-risk subjects, such as those with higher BP or diabetes mellitus, actively lowering their sodium intake); confounding by physical activity (which increases total energy consumption, that then increases total sodium intake316); and confounding by frailty and other reasons for low total energy consumption (given the very strong correlation between sodium and total energy consumption). These limitations together could explain the J-shapes seen in certain observational studies.
In comparison, during extended surveillance in a large sodium study that excluded sick individuals at baseline and collected multiple 24-hour urine samples per subject, minimizing the potential influence of these biases, participants with lowest intakes (<2300 mg/d) experienced 32% lower CVD risk than those consuming high intakes, with evidence for linearly decreasing risk.317 In ecological studies, the lowest mean intake level associated with both lower systolic BP and a lower rise in BP with aging is 614 mg/d.318 In randomized controlled feeding trials, BP reductions have been documented down to intakes of 1500 mg/d.319 In meta-analyses of prospective observational studies, the lowest mean intakes associated with lower risk of CVD events ranged from 1787 to 2391 mg/d.305 Together, these findings support the recommended target intakes in current national and international dietary guidelines, which range from 1200 to 2400 mg/d.110,313,320–323
Although large reductions in sodium can increase renin-aldosterone and serum triglyceride levels,324 the effects of more moderate, gradual reductions on these pathways are not established. It also remains unclear whether such physiological effects could offset, let alone reverse, the BP-lowering benefits of sodium reduction in order to explain the J-shaped relations with CVD risk seen in some observational studies. Overall, although adverse effects of rapid sodium reduction cannot be excluded, and true optimal lower limits remain uncertain, the sum of evidence suggests that optimal levels of sodium intake are ≈2000 mg/d193,200–204 (or lower).304 Based on a target consumption level of 2000 mg/d, 1.65 million annual global cardiovascular deaths are estimated to be attributable to excess sodium intake.304
Potassium, Calcium, Magnesium
Vegetables, fruits, whole grains, legumes, nuts, and dairy are major sources of minerals. In randomized trials, potassium lowers BP, with stronger effects among individuals who have hypertension and when dietary sodium intake is high.325 This BP lowering has been correlated with both increased urinary potassium excretion and a lower urine sodium-to-potassium ratio. Consistent with these benefits, potassium-rich diets are associated with lower risk of CVD, especially stroke (Figure 7).326 Diets rich in potassium also attenuate, whereas diets low in potassium exacerbate, the BP-raising effects of sodium. For instance, a Mediterranean or DASH-type diet (eg, richer in fruits, vegetables, nuts) reduces, whereas a typical Western diet increases, the BP-raising effects of sodium.326,327 In sum, the evidence strongly supports the importance of potassium-rich foods for reducing BP and CVD.
In short-term trials, calcium and magnesium supplements also modestly lower BP, although with substantial heterogeneity among studies. However, calcium supplements with or without vitamin D may significantly increase risk of MI in long-term randomized trials.328,329 In observational analyses, dietary and blood magnesium levels are inversely associated with CVD, especially fatal CHD330; long-term trials have not been performed. Calcium and magnesium supplements cannot yet be recommended for general CVD prevention.
Antioxidant Vitamins
Several vitamins and nutrients are associated with lower CVD risk in observational studies, but trials of supplements, including folate, B vitamins, β-carotene, vitamin C, vitamin E, and selenium, have shown no significant effects on atherosclerosis progression or CVD events.19,331,332 Most of these trials, for reasons of power, evaluated up to a few years of treatment in patients with established CVD or at high risk. In contrast, most observational studies evaluated long-term or habitual intake among generally healthy populations. Thus, discrepancies in findings could relate in part to different time periods of biological sensitivity — eg, some vitamins and nutrients could be important only early in the disease course. Such explanations require confirmation in prospective studies and trials. Discrepancies between observational studies and supplement trials may also relate to residual bias in observational studies, eg from other lifestyle behaviors (ie, observed benefits are not attributable to diet) or from other nutritional factors in vitamin-rich foods (ie, observed benefits are caused by diet but not by the specific measured vitamins or nutrients). For example, diets higher in antioxidant vitamins tend to be rich in fruits, vegetables, nuts, and whole grains, foods that contain multiple other beneficial factors including other vitamins, minerals, phytochemicals, and fiber, and being foods that can provide benefit by replacing unhealthful foods, as well. Thus, isolating one or even several components of these foods in a supplement may not produce similar effects as would occur from consuming the whole food.8,9
Vitamin D
Observational studies demonstrate links between higher plasma vitamin D, which is largely driven by sun exposure, and CVD risk; however, large trials of vitamin D supplements have shown no benefits.104 If higher plasma vitamin D proves to lower CVD risk, brief sun exposure can efficiently provide such levels in comparison with dietary intake. Ongoing trials are now testing whether higher doses of vitamin D supplements influence CVD; for now, such supplementation is not warranted as a means to improve cardiometabolic health.
Carbohydrates, Added Sugars, Fructose
For decades, carbohydrates were considered a foundation of a healthful diet, as evidenced by the placement of grain products at the base of the 1992 Food Guide Pyramid. Since that time, it has become clear that, although total carbohydrate has little influence on cardiometabolic health, the types and quality of carbohydrate have a major impact (Figures 6 and 7; see Carbohydrate-Rich Foods, above). Certain carbohydrate-containing foods (eg, fruits, legumes, vegetables, minimally processed whole grains) are protective, whereas foods rich in refined grains (eg, white bread, white rice, crackers, cereals, bakery desserts), starches (eg, russet or white potatoes), and added sugars (eg, SSBs, candy) are harmful. Because of this diversity, the cardiometabolic effects of total carbohydrate are modified by the quality of carbohydrate. For people who consume mostly low-fiber, rapidly digested, refined grains, starches, and added sugars, a lowering of total carbohydrate will produce substantial metabolic benefits. Yet, recommending a low-carbohydrate diet per se is not ideal: the focus should be on reducing less healthful carbohydrates, not all carbohydrates.
The US Food and Drug Administration has recently proposed revising the Nutrition Facts Panel to include added sugars.333 Although added sugars are not healthful, targeting added sugars alone, rather than overall carbohydrate quality, could push consumers toward foods low in added sugars but rich in equally harmful refined complex carbohydrates (eg, many breakfast cereals, breads, crackers); and away from otherwise healthful foods containing modest amounts of added sugar (eg, nuts or minimally processed whole grain–rich cereals sweetened with honey). Appropriately, the 2015 Dietary Guidelines Advisory Committee explicitly advises restriction of both refined grains and added sugars.21
Much public attention has focused on the potential harms of high-fructose corn syrup. Because glucose, the main sugar in regular corn syrup (which is mostly starch), tastes less sweet than fructose, high-fructose corn syrup has been modified to increase the fructose-to-glucose ratio to about 1:1, ie, a similar ratio as in natural sugar (sucrose) found in cane sugar, beet sugar, or honey. Consequently, there are few expected or observed physiological or health differences between high-fructose corn syrup versus sucrose.165,166,334 In contrast, there are important metabolic differences between glucose and fructose – each equally present in both high-fructose corn syrup and natural sugar (sucrose). In particular, high doses of rapidly digested glucose induce postprandial hyperglycemia, hyperinsulinemia, and related metabolic disturbances. When glycogen stores are replete, excess glucose is further converted to fat via hepatic de novo lipogenesis. In comparison, high doses of rapidly digested fructose have little influence on blood glucose or insulin levels, but more directly stimulate hepatic de novo lipogenesis, hepatic and visceral adiposity, and uric acid production.164–166 Thus, high doses of rapidly digested glucose and fructose are each harmful, with such effects occurring via both separate and partly overlapping pathways. In contrast, low doses of slowly digested glucose or fructose (eg, as found in fruit) would each have minimal cardiometabolic harms. Ultimately, the health differences between high-fructose corn syrup versus natural added sugar are small in comparison with their overall dose, rapidity of digestion, and accompanying nutrients in the foods in which they are consumed.
Total Fat
In 1980, the US Dietary Guidelines recommended limiting dietary fat to <30% of calories. Based on evidence for harms of very low-fat diets, and little evidence to support a 30% restriction, the Guidelines were moderated in 2005 to a new range of 20% to 35% of calories.335 A primary motivation for restricting total fat was to lower saturated fat and dietary cholesterol because of concern that these increased cardiovascular risk. Thus, total fat was targeted as a means to lower saturated fat. In addition, based on the calorie density of fat and some limited interventional studies, it was theorized that low-fat diets might help prevent obesity.335 Unfortunately, the focus on restricting total fat did not account for the health benefits of high intakes of plant-derived fats (see Nuts, Vegetable Oils, above) nor the harms of processed carbohydrates (see Carbohydrate-Rich Foods, above), the most common replacement when dietary fat is reduced.
In recent years, the lack of cardiometabolic benefit of low-fat diets has been convincingly demonstrated. In trials of short-term weight loss, high-fat diets are at least as effective as low-fat diets (see Dietary Quality, Energy Balance).21 For long-term weight maintenance, the fat content of foods is a poor metric for differentiating protective versus harmful effects.28,29,51 Both prospective cohorts and large randomized trials confirm that low-fat diets have no benefits for major chronic diseases (Figure 7).157,331 The large WHI randomized trial substantially lowered total dietary fat among nearly 50 000 US women followed for nearly a decade, and did not show benefits for any major end point including heart disease (Figure 2, top), stroke, cancers, diabetes mellitus, or insulin resistance.36–39 In contrast, randomized trials have confirmed the many prior observational cohort findings that diets higher in healthful fats, including in excess of the current 35% limit, reduce the risk of cardiovascular disease (Figure 2, bottom) and diabetes mellitus.24,25,34,35 These latter trials confirm decades-old ecological evidence that some of the healthiest traditional diets in the world are rich in fats from vegetable oils, nuts, and seafood.19 Based on this evidence, the 2015 Dietary Guidelines Advisory Committee stated, for the first time, that dietary guidelines should not focus on lowering total fat.21
The current restriction on total fat shapes numerous government feeding programs and policies;336 drives industry marketing of fat-reduced desserts, snacks, salad dressings, processed meats, and low-fat other products of poor nutritional value; and leads most Americans to actively avoid dietary fat337 and instead consume far too many refined carbohydrates.21 Avoidance of total fat also undermines attempts to limit refined starch and added sugar, while discouraging the food industry from providing products higher in healthful fats. Based on the accumulated evidence, a comprehensive restructuring of nutritional policy away from fat reduction is warranted.336
Saturated Fat
Saturated fat represents a highly heterogeneous category of fatty acids, with chain lengths ranging from 6 to 24 carbons, deriving from diverse foods, and possessing dissimilar biology. For instance, palmitic acid (16:0) exhibits in vitro adverse effects; whereas medium-chain (6:0–12:0), odd-chain (15:0, 17:0), and very long-chain (20:0–24:0) saturated fats may have metabolic benefits.61,338,339 This biological and metabolic diversity does not support the grouping together of all saturated fatty acids based on only one chemistry characteristic: the absence of double bonds.340
Even for any single saturated fatty acid, the physiological effects are complex. For instance, in comparison with carbohydrate, 16:0 raises blood LDL-cholesterol, yet simultaneously raises HDL-cholesterol, reduces triglyceride-rich lipoproteins and remnants, and has no appreciable effect on ApoB,341 the most salient LDL-related characteristic. Effects of 16:0 on ApoCIII, an apolipoprotein modifier of LDL- and HDL-related risk, are unknown; the triglyceride-lowering effects of 16:0341 would suggest potential benefit on lowering ApoCIII. Saturated fats also lower lipoprotein(a), an independent and casual cardiovascular risk factor,342 in comparison with monounsaturated fat or carbohydrate.343
Dietary saturated fats are also obtained from very different foods – eg, cheese, grain-based desserts, dairy desserts, chicken, processed meats, unprocessed red meat, milk, yogurt, butter, vegetable oils, and nuts. Each of these possesses, in addition to saturated fat, numerous other ingredients and characteristics that modify their health effects. Judging the long-term health impact of foods or diets based on isolated macronutrient composition is unsound, often creating paradoxical food choices and product formulations.336,340 Furthermore, tissue levels of even-chain saturated fatty acids (eg, 14:0, 16:0), that appear most harmful in vitro, commonly result from endogenous hepatic synthesis of fat in response to dietary intake of carbohydrate46; 14:0 and 16:0 blood levels correlate more with intakes of dietary starches and added sugars than meats or dairy.61
These complexities clarify why total saturated fat consumption has little relation to health. Judging a food or a person’s diet as harmful because it contains more saturated fat, or as beneficial because it contains less, is unsound. This is consistent with the many longitudinal cohort studies demonstrating largely neutral effects of overall saturated fat intake (Figure 7).39,157,344 Consistent with this, meats higher in processing and sodium, rather than saturated fat, are most strongly linked to CHD (see Meats, above). Cheese, a leading source of saturated fat, is also linked to neutral or even beneficial effects on CHD and diabetes mellitus (see Milk, Cheese, Yogurt, above). In sum, these lines of evidence – complex lipid effects including little influence on ApoB, no relation of overall intake with CHD, and no observed cardiovascular harm for most major food sources – provide powerful and consistent evidence for absence of appreciable harms of total saturated fat.
Yet, while certain saturated fat–containing foods such as dairy, nuts, and vegetable oils promote health,20 these findings do not support the benefits of other saturated fat-rich foods. Although unprocessed red meats and butter may be relatively neutral for CHD, no studies demonstrate appreciable benefits, all meats appear to increase diabetes mellitus, and processed meats are strongly linked to CHD (see Meats, above).20,29,173,178 This is the mistake of recent media reports: conflating complexities of health effects and benefits of some saturated fat–containing foods (and possibly some specific saturated fatty acids) with unsupported recommendations to eat more butter and bacon as routes to health.345
Yet, even among scientists, the cardiovascular health effects of saturated fat remain a controversial topic. Continued prioritization of saturated fat reduction appears to rely on selected evidence: eg, effects on LDL-cholesterol alone (discounting the other, complex lipid and lipoprotein effects); historical ecological trends in certain countries (eg, Finland) but not in others; and expedient comparisons with polyunsaturated fat, the most healthful macronutrient. For example, although falling blood cholesterol concentrations in some Western countries correlate with decreases in national saturated fat intake, trends in intakes of dietary fats cannot explain most of the blood cholesterol changes across or within most nations. For instance, total blood cholesterol fell similarly in the United States and France between 1980 and 2000, but national changes in dietary fats may explain only ≈20% of the decline in the United States, and virtually none of the decline in France.346
In certain Western nations, statin use may account for a large proportion of declining blood cholesterol after 2000347,348; however, because of the relatively low use for primary prevention before this period, statins cannot explain the observed similar declines in blood cholesterol over the preceding 20 to 30 years. Reasons for the large and steady declines in blood cholesterol and blood pressure over the past 4 decades in nearly all Western nations are not fully elucidated, particularly when viewed against the backdrop of increasing obesity. The extent to which these pervasive declines reflect trends in medication use, dietary fats, other dietary changes, physical activity, or other unknown influences (eg, related to fetal nutrition, the microbiome, or other unknown pathways) remains unclear.
Based on the similar cardiovascular effects of consuming total carbohydrate versus saturated fat, and the comparative benefit of polyunsaturated fats, guidelines to lower saturated fat are increasingly highlighting the importance of consuming polyunsaturated fats as the specific replacement.21 Yet, the resulting benefit appears specific to increased intake of polyunsaturated fat, rather than reduced saturated fat. For instance, total saturated fat, carbohydrate, and protein each appear relatively neutral for CHD, whereas the effects of total monounsaturated fat remain uncertain (see below).21,349 The relatively neutral effects of each of these macronutrients likely reflect substantial heterogeneity in nutrient subtypes and food sources within each of these categories. In comparison with any of these broad categories, polyunsaturated fat appears to be similarly beneficial.350 Consequently, it makes little sense to focus on saturated fat, which represents a smaller proportion of calories than these other macronutrients, especially carbohydrate. Indeed, in comparison with refined carbohydrates, saturated fat appears slightly beneficial.155,351 These lines of evidence support guidelines to increase healthful vegetable oils rich in polyunsaturated fats and phenolics, optimally in place of refined grains, starches, and added sugars.
Monounsaturated Fat
Although monounsaturated fat (predominantly oleic acid, 18:1) has conventionally been considered a cardioprotective fat, the evidence supporting this notion is mixed (Figure 7).21,39,157,352 Monounsaturated fat improves BP and cholesterol353 and, when consumed in place of saturated fat, lowers glucose among those predisposed to insulin resistance.354 Yet, total monounsaturated fat intake is not associated with lower incidence of diabetes mellitus355; it is associated with trends toward greater CVD in some cohort studies155; and it increases atherosclerosis in primate experiments, potentially because of the enrichment of LDL cholesteryl oleate and increased LDL proteoglycan binding.356 Taken together, the current evidence for cardiometabolic benefits of total monounsaturated fat (largely oleic acid) is not strong.21
The food source may modify these health effects. For instance, cohort studies suggest that the consumption of olive oil, but not mixed animal and plant sources of monounsaturated fat, is linked to lower risk,352 whereas vegetable oil sources of monounsaturated fat increase LDL cholesteryl oleate but reduce LDL proteoglycan binding.357 These results suggest that other compounds in these fats/oils may modify the overall health effects (see Phenolic Compounds, below). Thus, focusing on specific types of foods and oils, rather than monounsaturated fat content per se, may be most prudent. Extra virgin olive oil and mixed nuts, and perhaps high-oleic canola oil, appear to be good dietary choices to improve cardiometabolic health.24,25,34,35,145,255
Polyunsaturated Fat
Polyunsaturated fats include n-6 and n-3 fatty acids, with this distinction based on the carbon location of the first double bond. The most common are n-6 linoleic acid (LA, 18:2n-6) and n-3 α-linoleic acid (ALA, 18:3n-3), derived principally from vegetables and their oils (eg, soybean, canola, flaxseed, walnuts). Seafood is the major source of long-chain n-3 polyunsaturated fats, principally EPA and DHA.201 Although the liver readily synthesizes saturated and monounsaturated fats from carbohydrate (by means of hepatic de novo lipogenesis), humans cannot synthesize or interconvert LA or ALA, making them essential fatty acids that must be consumed in the diet. Humans also synthesize relatively little EPA and DHA,344 for which diet remains the major source. Evidence for cardiometabolic effects of seafood-derived n-3 fats are reviewed above (see Fish).
LA consumption lowers LDL-cholesterol and triglyceride-rich lipoproteins and raises HDL-cholesterol.349 Although potential proinflammatory effects of LA have been theorized358 and popularized, such inference is based largely on rodent experiments, with little supportive evidence in humans.359–362 Indeed, in people, LA appears to have anti-inflammatory and insulin-sensitizing effects.363–365 In controlled trials, in comparison with saturated fat, LA reduces hepatic steatosis and systemic inflammation and increases lean muscle mass.366,367 Arachidonic acid, the prototypical metabolite of LA, is also commonly considered proinflammatory, but is also the natural precursor to specialized proresolving mediators of inflammation.368,369 In prospective studies, higher biomarker levels of arachidonic acid are linked to significantly lower risk of CHD.39 LA is also associated with significantly lower risk of CHD (Figure 7), whether in comparison with carbohydrate or saturated fat350; and, in meta-analysis of controlled clinical trials, consumption of n-6–rich vegetable oils, in place of animal fats, reduces CHD events (Figure 7).349 Notably, in these latter trials, the average intake of n-6 polyunsaturated fat was ≈15% energy,349 higher than current dietary guidelines that recommend no more than 10% to 11% energy from polyunsaturated fat.370
In comparison with seafood sources, ALA is a relatively available and inexpensive plant source of n-3 polyunsaturated fat. Ecological studies suggest health benefits of increasing ALA intakes in populations with low overall n-3 polyunsaturated fat intake.356 Yet, the findings of trials of ALA and risk markers, such as platelet function, inflammation, endothelial function, and arterial compliance, and observational studies of ALA’s association with CVD and diabetes mellitus endpoints, have been mixed and inconclusive.371,372 Few long-term trials of ALA and clinical events have been conducted; in 1 Dutch trial, 40 months of an ALA-containing margarine led to a small, nonsignificant reduction in major cardiovascular events (hazard ratio, 0.91; 95% confidence interval, 0.78–1.05).373 Further investigation of ALA’s role in cardiometabolic health is warranted (Figure 7).211,372
LA has similar CHD benefits whether replacing carbohydrate or saturated fat (see Saturated Fat, above).349,350 Thus, increased consumption of polyunsaturated fat-rich vegetable oils is an evidence-based strategy to lower CHD risk, whether in place of saturated fat or carbohydrate. Optimally, polyunsaturated fat-rich vegetable oils should perhaps replace refined starches and added sugars, given the independent harms of these refined carbohydrates. Because the controlled trials demonstrating CHD benefits of PUFA used soybean oil,349 which contains both n-6 (LA) and n-3 (ALA) polyunsaturated fats, the selection of vegetable oils containing both n-6 and n-3 fatty acids (eg, soybean, canola) may be most prudent. Because both n-3 and n-6 polyunsaturated fats are beneficial, little interaction between them is evident, and the n-3:n-6 ratio is not a practical metric to evaluate health effects.364,374
Trans Fatty Acids
Trans fatty acids (TFAs) are mono- or polyunsaturated fats with one or more double bonds in a trans position, rather than the mammalian synthesized cis position. Although small amounts of natural TFA are found in meats and milk of ruminants (eg, cow, sheep, goat; formed by gut microorganisms), these contribute minimally to diet (<0.5%E) and do not associate with CVD risk375; indeed, trans-16:1n-7, a trace TFA biomarker of dairy fat, is linked to a lower risk of diabetes mellitus and sudden cardiac death.247 Conversely, high levels of industrially produced TFA can be consumed from partially hydrogenated vegetable oils, which typically contain 30% to 60% TFA. These fats have industrial advantages for commercial deep frying, baked goods, packaged snacks, and shortening. Higher TFA intake from partially hydrogenated oils is consistently associated with the risk of CHD and sudden death (Figure 7).331,376 In trials, TFAs have unique adverse effects on blood lipids and lipoproteins, including raising LDL-cholesterol, ApoB, triglycerides, and lipoprotein(a), and lowering HDL-cholesterol and ApoA1; these effects are generally consistent whether the TFA replaces saturated, monounsaturated, or polyunsaturated fat.377 TFAs also appear to have nonlipid adverse effects, promoting inflammation, endothelial dysfunction, insulin resistance, visceral adiposity, and arrhythmia, although the strength of evidence for these different nonlipid effects varies.378,379 In sum, the implicated pathways suggest that TFA-containing partially hydrogenated oils influence pathways related to adipocyte dysfunction and insulin resistance. Emerging evidence suggests that 18:2 TFA isomers may be the most adverse; these can be formed through not only partial hydrogenation, but also other industrial processes such as oil deodorization and high-temperature cooking.380,381 Because partially hydrogenated oils are food additives with clear adverse effects, their elimination is a public health priority.247,382–384
Protein
The cardiometabolic effects of dietary protein are not well established. In meta-analysis of randomized trials, increased protein consumption has little effect on cardiometabolic risk factors including adiposity, lipids, blood pressure, inflammation, or glucose.385 Few longitudinal studies have reported on total protein intake and CHD events, with generally null results.189,386 This is not surprising: similar to total fat or total carbohydrate, total protein represents the sum of very different foods (red meats, processed meats, milk, cheese, yogurt, fish, nuts, legumes, etc) with widely divergent health effects. Thus, a focus on dietary protein per se appears much less relevant for CVD than a focus on specific types of foods consumed. A few cohorts have seen protective associations of animal protein intake with the risk of hemorrhagic stroke; causality and mechanisms remain unclear, but have been hypothesized to relate to the potentially protective effects of animal protein or dietary cholesterol on vascular fragility.198,199
Behavior Change
Barriers and Opportunities for Healthy Eating
Many current approaches to improving nutrition – eg, clinical counseling, food labels, menu labeling, dietary guidelines – arise from an implicit assumption that dietary habits are primarily a function of individual choice. In reality, multiple complex factors influence dietary choices (Figure 9). Even at the individual level, dietary habits are determined not simply by personal preference but also by familial norms, education, income, nutritional and cooking knowledge and skills, and health status.387 Additional relevant factors include attitudes toward food and health, incentives, motivation, and values.388 Other lifestyle behaviors such as television watching and sleep also influence patterns of food consumption.28,71,72,389 Outside the individual, sociocultural determinants include cultural norms, social pressures, and social networks.390 Additional environmental influences include neighborhood accessibility (eg, food availability, cost, convenience). Each of these individual, environmental, and sociocultural determinants is shaped by, and in turn shapes, much broader drivers of food choice such as agricultural policy and production practices, food industry formulations and marketing, national and international trade agreements, other market forces, climate, and agricultural policies.391 These complex determinants each represent a potential barrier, but also a promising lever and opportunity, for encouraging healthful diets.
Figure 9. Barriers and opportunities for healthy eating. Reproduced from Afshin et al10 with permission of the publisher. Copyright © 2014, John Wiley & Sons, Ltd.
Some have argued that humans are biologically wired to prefer specific unhealthful foods, eg, rich in fat, sugar, and salt. This perspective is overly simplistic and inconsistent with several lines of empirical evidence. For instance, most dietary fats are healthful, making a food’s fat content a poor marker of its intrinsic harm or benefit (see Total Fat). In addition, taste preferences are highly complex, influenced by considerations of aroma, appearance, color, shape, and texture. The observed diversity of diets within and across individuals, generations, cultures, and populations further belies a particular biological preference for food.4,346,392–394 Even the brain’s unconscious reward/craving (addiction) centers are plastic and can be trained over months to respond to healthful rather than unhealthful foods.395 Furthermore, for the food industry, the success or failure of specific products has often depended not on differences in contents of fat, sugar, or salt, but on the prowess and power of their convenience, packaging, marketing, and promotion.396 Undoubtedly, taste plays a role in consumer choice, but so do availability, price, packaging, marketing, convenience, and culturally driven perceptions of norms, status, and prestige. Each of these levers are powerful and can be used to influence the selection of healthier foods.
Clinical (Individual-Based) Strategies
Numerous randomized controlled trials have identified effective approaches for successful individual behavior change (Table 5).94,95 These strategies have demonstrated efficacy and should be incorporated by providers into their practice to target specific dietary behaviors and other lifestyle habits, such as tobacco use, physical inactivity, and medication noncompliance. Providers should recognize that, although patient compliance with both lifestyle and medications is similarly imperfect, such strategies, even imperfectly implemented, improve clinical outcomes.397
| • Specific, proximal, shared goals. Set specific, proximal goals in collaboration with the patient, including a personalized plan to achieve the goals (eg, increase fruits by 1 serving/d over the next 3 mo).• Self-monitoring. Establish a strategy for self-monitoring, such as a dietary or physical activity diary or web-based or mobile phone application.• Scheduled follow-up. Schedule regular follow-up (in-person, telephone, written, or electronic), with clear frequency and duration of contacts, to assess success, reinforce progress, and set new goals as necessary• Regular feedback. Provide feedback on progress toward goals, including using in person, telephone, or electronic feedback.• Self-efficacy.* Increase the patient’s perception that they can successfully change their behavior.• Motivational interviewing.† Use motivational interviewing when patients are resistant or ambivalent about behavior change.• Family and peer support. Arrange long-term support from family, friends, or peers for behavior change, such as in workplace, school, or community programs.• Multicomponent approaches. Combine 2 or more of the above strategies into the behavior change effort. |
Health Systems Strategies
For many clinicians, a variety of barriers within the health system can limit their ability to fully implement effective behavior change strategies. Such barriers might include, for example, limited patient visit time to focus on behavior change, insufficient financial or other provider incentives for health promotion, suboptimal knowledge or experience on the most effective behavior change strategies and relevant behavioral targets, and inadequate tools for assessing and monitoring behaviors over time. Specific changes in the healthcare system can strongly support and facilitate behavior change efforts by providers (Table 6).10,95,398,399 Such healthcare systems approaches are being introduced for tobacco and obesity control efforts. Many electronic medical records systems have fields for tobacco use and body weight, although their accuracy and consistency of use remain variable. The expansion of these healthcare system approaches to target diet quality is crucial, especially in light of new incentives in the Affordable Care Act for creating new electronic health record systems and for focusing on prevention in Accountable Care Organizations.
| • Ongoing training for providers on evidence-based behavior change strategies as well as relevant dietary targets, including relevant ethnic and cultural issues. |
| • Integrated systems to facilitate coordinated care by multidisciplinary teams, including physicians, nurse practitioners, dieticians, physical activity specialists, and social workers. |
| • Practical electronic systems to help assess, track, and report on specific dietary behaviors, including during, before, and after provider visits. |
| • Electronic systems for scheduling and tracking regular follow-up visits for behavior change. |
| • Electronic systems to facilitate provision of feedback to patients and providers on progress during behavior change efforts. |
| • Reimbursement guidelines and incentives that reward behavior change efforts. |
| • Restructuring of practice goals and quality benchmarks to incorporate key dietary interventions and targets. |
Novel Technology Strategies
Recent years have witnessed an explosion of novel personal technologies that aim to improve health, including mobile device applications (mHealth), Internet-based programs, and personal tracking devices (eg, FitBits). These technologies are promising because of the potential for low cost, scalability, use in multiple settings (including middle- and low-income nations), and opportunities for continuous, personalized modifications and improvements. Many incorporate established behavior-change strategies (Table 5) such as setting proximal, targeted goals; self-monitoring; feedback; and peer support.
A systematic review identified numerous randomized trials and quasi-experimental studies evaluating these approaches for dietary change and/or weight loss (Afshin A, Mozaffarian D; unpublished data; 2015). Most were Internet based or combined Internet and mobile approaches. The great majority had durations between 6 weeks and 6 months; very few extended beyond 1 year. Approximately two-thirds of these studies identified improved dietary behaviors or greater weight loss with the use of these novel technologies, in comparison with usual care. Although promising, little is known on their long-term effectiveness and sustainability, and longer-term studies are required.
Policy Strategies
Given the key roles of social and environmental factors in shaping dietary habits, policy (population-based) approaches are crucial to achieve broad success. Effective strategies can be designed and implemented at local levels (eg, schools, worksites, communities), and at city, state, national, and international levels. Several specific approaches have strong evidence for efficacy (Table 7).10,11 These experiences generally demonstrate that education or information alone, without additional economic or environmental changes, has a limited influence on behavior.11,400,401 Integrated, multicomponent approaches that include upstream policy measures, midstream educational efforts, and downstream community and environmental approaches may be especially effective. Policy strategies can complement health systems efforts while also reducing social and racial disparities caused by the clustering of suboptimal diet habits, local environments, and disease risk factors.
| Media and education | • Sustained, focused media and education campaigns, using multiple modes, for increasing consumption of specific healthful foods or reducing consumption of specific less healthful foods or beverages, either alone or as part of multicomponent strategies.*• On-site supermarket and grocery store educational programs to support the purchase of healthier foods. |
| Labeling and information | • Mandated nutrition facts panels or front-of-pack labels/icons as a means to influence industry product formulations.† |
| Economic incentives | • Subsidy strategies to lower prices of more healthful foods and beverages.‡• Tax strategies to increase prices of less healthful foods and beverages.‡• Long-term changes in broad agricultural policies (not subsidies alone) to create infrastructure that facilitates production, transportation, storage, and marketing of healthier foods. |
| Schools | • Multicomponent interventions focused on improving both diet and physical activity, including specialized educational curricula, trained teachers, supportive school policies, a formal physical education program, serving of healthier food and beverage options, and a parental/family component.• School garden programs including nutrition and gardening education and hands-on gardening experiences.• Fresh fruits and vegetables programs that provide free fruits and vegetables to students during the school day. |
| Workplaces | • Comprehensive worksite wellness programs including dietary, physical activity, and tobacco cessation/prevention components.• Increased availability of healthier food/beverage options and strong nutrition standards for foods and beverages served, in combination with on-site prompts, labels, or icons to select healthier choices. |
| Neighborhood environment | • Increased availability of supermarkets near homes.§ |
| Quality standards | • Quality standards for marketing of foods and beverages to children, including on television, near schools and public places frequented by youths, on packages, or in other fashions. (IIa B).†• Quality standards on harmful (eg, sodium, partially hydrogenated oil) or beneficial (eg, healthful fats) ingredients in foods. |
Several factors have limited the translation of this knowledge to action, including evolving messages and confusion about specific dietary priorities, uncertainty regarding effective methods for behavior change, and inadequate tools to monitor diets efficiently. Fortunately, other public health successes for complex behavioral challenges- eg, tobacco use, motor vehicle safety-encourage optimism for the success of concerted multicomponent strategies that include strong quality standards and policy actions to improve diet. At the population level, even modest shifts in risk factors can substantially and rapidly alter population health.97,402
Role of Multiple Stakeholders
Successful, sustainable improvements in population dietary behaviors will require close collaboration among multiple stakeholders, including academics, clinicians, health systems, insurers, community organizations, schools, workplaces, advocacy groups, policy makers, farmers, retailers, restaurants, and food manufacturers.10,391,403 For instance, academic institutions should prioritize research on optimal dietary targets and cost-effective policies; engage with communities, advocacy groups, and policy makers; and inform and evaluate industry efforts. Clinicians should implement behavior change strategies; advocate for broad health system changes to support these efforts; and engage with local communities. Communities, schools, and workplaces should demand and support comprehensive programs for dietary change. Advocacy groups should partner with scientists to disseminate best practices while holding government and industry accountable for meaningful action.
Local and national governments should prioritize nutrition and facilitate participation of other stakeholders in policy development, implementation, and evaluation. Based on its impact on health, the environment, and the economy, nutrition is among the leading global issues of our time. Policy makers at all levels must recognize and focus on these topics. Surveillance, monitoring, and evaluation of dietary habits and diet-related policies are necessary to develop solutions, assess whether implemented programs have intended effects, identify and address disparities, and detect unintended consequences. Organized global public health efforts must complement these activities, assist smaller governments with effective food policies, and provide a countervailing force to multinational industry lobbying. Key global economic and political institutions that must play more assertive roles include the United Nations, the World Health Organization, the World Trade Organization, and the World Bank.
The food industry, from agricultural producers to food manufacturers, retailers, and restaurants, must also commit to healthier foods. Although big food has shared many tactics with big tobacco – eg, lobbying, deception, denial, resistance to regulation404 – these 2 industries are not fully analogous. The food industry is far more heterogeneous, from types of products to strengths of commitment to healthfulness. The food industry has also demonstrated some responsiveness to dietary guidelines and public preferences over the past 40 years: eg, generating low-fat products, margarines, noncaloric sweeteners, low-carbohydrate products, gluten-free and organic foods, and many others. Our food systems have also made tremendous progress in reducing food-borne illness, increasing volume and production, improving convenience and stability, and reducing cost – all important priorities of the last century. Healthfulness for chronic diseases, in particular, cardiometabolic diseases, has been the great failure – one that must now be addressed with modern nutrition and policy science. Perhaps most importantly, with tobacco, the ultimate aim is total elimination. In contrast, we need major agribusiness, food manufacturers, and retailers to successfully feed the 7+ billion people on the planet. These businesses must support and be informed by modern evidence, advance their technical expertise to formulate and sell healthier products, and use consumer education, marketing, and product pricing to promote dietary health. Agriculture and food industry should form transparent, sincere partnerships with advocacy groups, governments, and other stakeholders to replace less healthy foods with more healthful options. Their ultimate success must be linked to selling of healthful, optimally processed foods in a sustainable and profitable fashion.
Motor vehicle safety provides an informative analogy (Figure 10). The US Centers for Disease Control and Prevention named reduced fatalities from motor vehicle accidents as one of the top 5 public health successes of the 20th century.405 This remarkable success was not achieved merely by national driving guidelines, motor vehicle labeling, or other consumer-focused education – ie, many of the current emphases for dietary change – but by a comprehensive, multicomponent effort targeting the consumer (driver), product (car), environment (road), and culture (particularly drunk driving). This provides a road map for improving population diets: address the consumer, the product (foods and beverages), the environment (retailers, cafeterias, restaurants), and the culture (unhealthy eating, marketing). For instance, just as driving under the influence of alcohol is now socially stigmatized, the acceptability of fast foods, soda, and ultraprocessed products, including industry and celebrity marketing of such foods, must be reduced. Just as the auto industry remains successful and profitable, and the public continues to use and benefit from cars, a similar multicomponent, evidence-informed approach is needed to produce a successful, profitable food system that provides safe, healthful products.
Figure 10. A roadmap for improving population dietary habits. Top, A great public health success of the 20th century was a 90% reduction in deaths from motor vehicle accidents, from 18 to 1.7 deaths per million vehicle miles. Bottom, This remarkable triumph was achieved by a comprehensive, multicomponent effort targeting the driver, car, road, and culture. This provides a road map for improving population diets: address the consumer, the product (foods and beverages), the environment (retailers, cafeterias, restaurants), and the culture (unhealthy eating). MADD indicates Mothers Against Drunk Driving. Top reproduced from Centers for Disease Prevention and Control405.
Conclusions – The Way Forward
The global challenges of diet-related obesity, diabetes mellitus, and CVD present enormous health and economic burdens403 and emphasize the imperative of prioritizing nutrition in clinical care, advocacy, research, and policy. Scientific advances provide a wealth of new evidence to identify several key dietary priorities for cardiometabolic health. These include food-based priorities for more fruits, nonstarchy vegetables, nuts, legumes, fish, vegetable oils, yogurt, and whole grains; and fewer processed (sodium-preserved) meats and foods higher in refined carbohydrates and salt (Figure 3). Red meats should be minimized to prevent diabetes mellitus; butter used occasionally but not emphasized; and other foods (eg, unprocessed poultry, eggs) consumed in moderation according to personal preference. Coffee and tea can be enjoyed, with possible (but not yet confirmed) benefits; and alcohol, if consumed, should be moderate (up to 1 drink/d for women and 2 drinks/d for men). Harmful additives, in particular sodium, trans fat, and added sugar, will generally be lower in such diets and must be further minimized through strong policy actions. There is growing evidence and consensus for such food-based dietary patterns as the best means to reduce CVD, obesity and weight gain, and diabetes mellitus,21 replacing outdated emphases on total fat, other isolated nutrients, and calorie counting. Clinical behavior-change efforts, health system changes, novel technologies, and robust policy strategies must complement and facilitate these individual food choices, which together will reduce cardiometabolic disease and economic burdens across the population.
Acknowledgments
I am grateful for the indispensable contributions over the years to my knowledge and perspectives on nutrition science and policy resulting from collaborations and conversations with many friends and colleagues, including David Siscovick, Rozenn Lemaitre, Walter Willett, Frank Hu, David Ludwig, Simon Capewell, Renata Micha, Jason Wu, Ashkan Afshin, and many others. I also thank Masha Shulkin and Ashley Wright for their assistance with the drafting of Figures 6 and 7; and the Circulation editors and peer reviewers for their critical comments during the preparation of this article.
Sources of Funding
This work was supported by the National Health, Lung, and Blood Institute (R01 HL085710, R01 HL115189), National Institutes of Health.
Disclosures
Ad hoc honoraria or consulting from Bunge, Haas Avocado Board, Amarin, Astra Zeneca, Boston Heart Diagnostics, GOED, and Life Sciences Research Organization; chapter royalties from UpToDate; and scientific advisory boards, Unilever North America (ended 2014) and Elysium Health. Harvard University holds a patent, listing Dr Mozaffarian as 1 of 3 coinventors, for use of transpalmitoleic acid to prevent and treat insulin resistance, type 2 diabetes mellitus, and related conditions.
Footnotes
References
- 1.
Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, Amann M, Anderson HR, Andrews KG, Aryee M, Atkinson C, Bacchus LJ, Bahalim AN, Balakrishnan K, Balmes J, Barker-Collo S, Baxter A, Bell ML, Blore JD, Blyth F, Bonner C, Borges G, Bourne R, Boussinesq M, Brauer M, Brooks P, Bruce NG, Brunekreef B, Bryan-Hancock C, Bucello C, Buchbinder R, Bull F, Burnett RT, Byers TE, Calabria B, Carapetis J, Carnahan E, Chafe Z, Charlson F, Chen H, Chen JS, Cheng AT, Child JC, Cohen A, Colson KE, Cowie BC, Darby S, Darling S, Davis A, Degenhardt L, Dentener F, Des Jarlais DC, Devries K, Dherani M, Ding EL, Dorsey ER, Driscoll T, Edmond K, Ali SE, Engell RE, Erwin PJ, Fahimi S, Falder G, Farzadfar F, Ferrari A, Finucane MM, Flaxman S, Fowkes FG, Freedman G, Freeman MK, Gakidou E, Ghosh S, Giovannucci E, Gmel G, Graham K, Grainger R, Grant B, Gunnell D, Gutierrez HR, Hall W, Hoek HW, Hogan A, Hosgood HD, Hoy D, Hu H, Hubbell BJ, Hutchings SJ, Ibeanusi SE, Jacklyn GL, Jasrasaria R, Jonas JB, Kan H, Kanis JA, Kassebaum N, Kawakami N, Khang YH, Khatibzadeh S, Khoo JP, Kok C, Laden F, Lalloo R, Lan Q, Lathlean T, Leasher JL, Leigh J, Li Y, Lin JK, Lipshultz SE, London S, Lozano R, Lu Y, Mak J, Malekzadeh R, Mallinger L, Marcenes W, March L, Marks R, Martin R, McGale P, McGrath J, Mehta S, Mensah GA, Merriman TR, Micha R, Michaud C, Mishra V, Mohd Hanafiah K, Mokdad AA, Morawska L, Mozaffarian D, Murphy T, Naghavi M, Neal B, Nelson PK, Nolla JM, Norman R, Olives C, Omer SB, Orchard J, Osborne R, Ostro B, Page A, Pandey KD, Parry CD, Passmore E, Patra J, Pearce N, Pelizzari PM, Petzold M, Phillips MR, Pope D, Pope CA, Powles J, Rao M, Razavi H, Rehfuess EA, Rehm JT, Ritz B, Rivara FP, Roberts T, Robinson C, Rodriguez-Portales JA, Romieu I, Room R, Rosenfeld LC, Roy A, Rushton L, Salomon JA, Sampson U, Sanchez-Riera L, Sanman E, Sapkota A, Seedat S, Shi P, Shield K, Shivakoti R, Singh GM, Sleet DA, Smith E, Smith KR, Stapelberg NJ, Steenland K, Stöckl H, Stovner LJ, Straif K, Straney L, Thurston GD, Tran JH, Van Dingenen R, van Donkelaar A, Veerman JL, Vijayakumar L, Weintraub R, Weissman MM, White RA, Whiteford H, Wiersma ST, Wilkinson JD, Williams HC, Williams W, Wilson N, Woolf AD, Yip P, Zielinski JM, Lopez AD, Murray CJ, Ezzati M, AlMazroa MA, Memish ZA . A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010.Lancet. 2012; 380:2224–2260. doi: 10.1016/S0140-6736(12)61766-8.CrossrefMedlineGoogle Scholar - 2. US Burden of Disease Collaborators.The state of US health, 1990–2010: burden of diseases, injuries, and risk factors.JAMA. 2013; 310:591–608CrossrefMedlineGoogle Scholar
- 3.
Bloom DE, Cafiero ET, Jané-Llopis E, Abrahams-Gessel S, Bloom LR, Fathima S, Feigl AB, Gaziano T, Mowafi M, Pandya A, Prettner K, Rosenberg L, Seligman B, Stein AZ, Weinstein C . The Global Economic Burden of Noncommunicable Diseases. Geneva, Switzerland: World Economic Forum; 2011.Google Scholar - 4.
Imamura F, Micha R, Khatibzadeh S, Fahimi S, Shi P, Powles J, Mozaffarian D . Dietary quality among men and women in 187 countries in 1990 and 2010: a systematic assessment.Lancet Glob Health. 2015; 3:e132–e142CrossrefMedlineGoogle Scholar - 5.
Stampfer MJ, Hu FB, Manson JE, Rimm EB, Willett WC . Primary prevention of coronary heart disease in women through diet and lifestyle.N Engl J Med. 2000; 343:16–22. doi: 10.1056/NEJM200007063430103.CrossrefMedlineGoogle Scholar - 6.
Blumberg J, Heaney RP, Huncharek M, Scholl T, Stampfer M, Vieth R, Weaver CM, Zeisel SH . Evidence-based criteria in the nutritional context.Nutr Rev. 2010; 68:478–484. doi: 10.1111/j.1753-4887.2010.00307.x.CrossrefMedlineGoogle Scholar - 7.
Satija A, Yu E, Willett WC, Hu FB . Understanding nutritional epidemiology and its role in policy.Adv Nutr. 2015; 6:5–18. doi: 10.3945/an.114.007492.CrossrefMedlineGoogle Scholar - 8.
Jacobs DR, Tapsell LC . Food, not nutrients, is the fundamental unit in nutrition.Nutr Rev. 2007; 65:439–450.CrossrefMedlineGoogle Scholar - 9.
Mozaffarian D, Ludwig DS . Dietary guidelines in the 21st century–a time for food.JAMA. 2010; 304:681–682. doi: 10.1001/jama.2010.1116.CrossrefMedlineGoogle Scholar - 10.
Afshin A, Micha R, Khatibzadeh S, Schmidt LA, Mozaffarian D . Dietary policies to reduce non-communicable diseases. In:, Brown GW, Yamey G, Wamala S , eds. The Handbook of Global Health Policy, 1st ed. West Sussex, UK: John Wiley & Sons, Ltd; 2014.CrossrefGoogle Scholar - 11.
Mozaffarian D, Afshin A, Benowitz NL, Bittner V, Daniels SR, Franch HA, Jacobs DR, Kraus WE, Kris-Etherton PM, Krummel DA, Popkin BM, Whitsel LP, Zakai NA ; American Heart Association Council on Epidemiology and Prevention, Council on Nutrition, Physical Activity and Metabolism, Council on Clinical Cardiology, Council on Cardiovascular Disease in the Young, Council on the Kidney in Cardiovasc. Population approaches to improve diet, physical activity, and smoking habits: a scientific statement from the American Heart Association.Circulation. 2012; 126:1514–1563. doi: 10.1161/CIR.0b013e318260a20b.LinkGoogle Scholar - 12.
Lind J . A Treatise of the Scurvy. London: A. Millar; 1753.Google Scholar - 13. National Nutrition Conference for Defense. National Nutrition Conference for Defense.JAMA. 1941; 116:2598–2599.CrossrefGoogle Scholar
- 14.
Davis C, Saltos E . Dietary recommendations and how they have changed over time.America’s Eating Habits: Changes and Consequences. Washington, DC: US Department of Agriculture, Economic Research Service; 1999. Agriculture Information Bulletin No. 750.Google Scholar - 15. American Medical Association. National nutrition.JAMA. 1941; 116:2854–2855.CrossrefGoogle Scholar
- 16.
Harper AE . Evolution of recommended dietary allowances–new directions?Annu Rev Nutr. 1987; 7:509–537. doi: 10.1146/annurev.nu.07.070187.002453.CrossrefMedlineGoogle Scholar - 17.
Jacobs DR, Tapsell LC . Food synergy: the key to a healthy diet.Proc Nutr Soc. 2013; 72:200–206. doi: 10.1017/S0029665112003011.CrossrefMedlineGoogle Scholar - 18.
Fardet A . A shift toward a new holistic paradigm will help to preserve and better process grain products’ food structure for improving their health effects.Food Funct. 2015; 6:363–382. doi: 10.1039/c4fo00477a.CrossrefMedlineGoogle Scholar - 19.
Mozaffarian D, Appel LJ, Van Horn L . Components of a cardioprotective diet: new insights.Circulation. 2011; 123:2870–2891. doi: 10.1161/CIRCULATIONAHA.110.968735.LinkGoogle Scholar - 20.
Mozaffarian D . Nutrition and cardiovascular disease and metabolic diseases., Mann DL, Zipes DP, Libby P, Bonow RO , eds. In: Braunwald’s Heart Disease; A Textbook of Cardiovascular Medicine, 10th ed. Philadelphia, PA: Elsevier/Saunders; 2014;1001–1014.Google Scholar - 21. Dietary Guidelines Advisory Committee.Scientific Report of the 2015 Dietary Guidelines Advisory Committee.2015. http://www.health.gov/dietaryguidelines/2015-scientific-report/. Accessed March 25, 2015.Google Scholar
- 21a.
Mozaffarian D, Ludwig DS . Dietary cholesterol and blood cholesterol concentrations-reply.JAMA.2015; 314:2084–2085.Google Scholar - 22.
Perrin AE, Simon C, Hedelin G, Arveiler D, Schaffer P, Schlienger JL . Ten-year trends of dietary intake in a middle-aged French population: relationship with educational level.Eur J Clin Nutr. 2002; 56:393–401. doi: 10.1038/sj.ejcn.1601322.CrossrefMedlineGoogle Scholar - 23. Harvard Heart Letter. Latest thinking on a “cardioprotective” diet.2011. www.health.harvard.edu. Accessed December 12, 2013.Google Scholar
- 24.
Appel LJ, Sacks FM, Carey VJ, Obarzanek E, Swain JF, Miller ER, Conlin PR, Erlinger TP, Rosner BA, Laranjo NM, Charleston J, McCarron P, Bishop LM ; OmniHeart Collaborative Research Group. Effects of protein, monounsaturated fat, and carbohydrate intake on blood pressure and serum lipids: results of the OmniHeart randomized trial.JAMA. 2005; 294:2455–2464. doi: 10.1001/jama.294.19.2455.CrossrefMedlineGoogle Scholar - 25.
Gadgil MD, Appel LJ, Yeung E, Anderson CA, Sacks FM, Miller ER . The effects of carbohydrate, unsaturated fat, and protein intake on measures of insulin sensitivity: results from the OmniHeart trial.Diabetes Care. 2013; 36:1132–1137. doi: 10.2337/dc12-0869.CrossrefMedlineGoogle Scholar - 26.
Haring B, von Ballmoos MC, Appel LJ, Sacks FM . Healthy dietary interventions and lipoprotein (a) plasma levels: results from the Omni Heart Trial.PLoS One. 2014; 9:e114859. doi: 10.1371/journal.pone.0114859.CrossrefMedlineGoogle Scholar - 27.
Djoussé L, Akinkuolie AO, Wu JH, Ding EL, Gaziano JM . Fish consumption, omega-3 fatty acids and risk of heart failure: a meta-analysis.Clin Nutr. 2012; 31:846–853. doi: 10.1016/j.clnu.2012.05.010.CrossrefMedlineGoogle Scholar - 28.
Mozaffarian D, Hao T, Rimm EB, Willett WC, Hu FB . Changes in diet and lifestyle and long-term weight gain in women and men.N Engl J Med. 2011; 364:2392–2404. doi: 10.1056/NEJMoa1014296.CrossrefMedlineGoogle Scholar - 29.
Smith JD, Hou T, Ludwig DS, Rimm EB, Willett W, Hu FB, Mozaffarian D . Changes in intake of protein foods, carbohydrate amount and quality, and long-term weight change: results from 3 prospective cohorts.Am J Clin Nutr. 2015; 101:1216–1224. doi: 10.3945/ajcn.114.100867.CrossrefMedlineGoogle Scholar - 30.
Lou-Bonafonte JM, Gabás-Rivera C, Navarro MA, Osada J . PON1 and Mediterranean Diet.Nutrients. 2015; 7:4068–4092. doi: 10.3390/nu7064068.CrossrefMedlineGoogle Scholar - 31.
Anand SS, Hawkes C, de Souza RJ, Mente A, Dehghan M, Nugent R, Zulyniak MA, Weis T, Bernstein AM, Krauss RM, Kromhout D, Jenkins DJ, Malik V, Martinez-Gonzalez MA, Mozaffarian D, Yusuf S, Willett WC, Popkin BM . Food consumption and its impact on cardiovascular disease: importance of solutions focused on the globalized food system: a report from the Workshop Convened by the World Heart Federation.J Am Coll Cardiol. 2015; 66:1590–1614. doi: 10.1016/j.jacc.2015.07.050.CrossrefMedlineGoogle Scholar - 32.
de Lorgeril M, Salen P, Martin JL, Monjaud I, Delaye J, Mamelle N . Mediterranean diet, traditional risk factors, and the rate of cardiovascular complications after myocardial infarction: final report of the Lyon Diet Heart Study.Circulation. 1999; 99:779–785.LinkGoogle Scholar - 33.
Estruch R, Martínez-González MA, Corella D, Salas-Salvadó J, Ruiz-Gutiérrez V, Covas MI, Fiol M, Gómez-Gracia E, López-Sabater MC, Vinyoles E, Arós F, Conde M, Lahoz C, Lapetra J, Sáez G, Ros E ; PREDIMED Study Investigators. Effects of a Mediterranean-style diet on cardiovascular risk factors: a randomized trial.Ann Intern Med. 2006; 145:1–11.CrossrefMedlineGoogle Scholar - 34.
Estruch R, Ros E, Salas-Salvado J, Covas MI, Pharm D, Corella D, Aros F, Gomez-Gracia E, Ruiz-Gutierrez V, Fiol M, Lapetra J, Lamuela-Raventos RM, Serra-Majem L, Pinto X, Basora J, Munoz MA, Sorli JV, Martinez JA, Martinez-Gonzalez MA . Primary prevention of cardiovascular disease with a Mediterranean diet.N Engl J Med. 2013; 368:1279–1290.CrossrefMedlineGoogle Scholar - 35.
Salas-Salvadó J, Bulló M, Estruch R, Ros E, Covas MI, Ibarrola-Jurado N, Corella D, Arós F, Gómez-Gracia E, Ruiz-Gutiérrez V, Romaguera D, Lapetra J, Lamuela-Raventós RM, Serra-Majem L, Pintó X, Basora J, Muñoz MA, Sorlí JV, Martínez-González MA . Prevention of diabetes with Mediterranean diets: a subgroup analysis of a randomized trial.Ann Intern Med. 2014; 160:1–10. doi: 10.7326/M13-1725.CrossrefMedlineGoogle Scholar - 36.
Howard BV, Van Horn L, Hsia J, Manson JE, Stefanick ML, Wassertheil-Smoller S, Kuller LH, LaCroix AZ, Langer RD, Lasser NL, Lewis CE, Limacher MC, Margolis KL, Mysiw WJ, Ockene JK, Parker LM, Perri MG, Phillips L, Prentice RL, Robbins J, Rossouw JE, Sarto GE, Schatz IJ, Snetselaar LG, Stevens VJ, Tinker LF, Trevisan M, Vitolins MZ, Anderson GL, Assaf AR, Bassford T, Beresford SA, Black HR, Brunner RL, Brzyski RG, Caan B, Chlebowski RT, Gass M, Granek I, Greenland P, Hays J, Heber D, Heiss G, Hendrix SL, Hubbell FA, Johnson KC, Kotchen JM . Low-fat dietary pattern and risk of cardiovascular disease: the Women’s Health Initiative Randomized Controlled Dietary Modification Trial.JAMA. 2006; 295:655–666. doi: 10.1001/jama.295.6.655.CrossrefMedlineGoogle Scholar - 37.
Tinker LF, Bonds DE, Margolis KL, Manson JE, Howard BV, Larson J, Perri MG, Beresford SA, Robinson JG, Rodríguez B, Safford MM, Wenger NK, Stevens VJ, Parker LM ; Women’s Health Initiative. Low-fat dietary pattern and risk of treated diabetes mellitus in postmenopausal women: the Women’s Health Initiative randomized controlled dietary modification trial.Arch Intern Med. 2008; 168:1500–1511. doi: 10.1001/archinte.168.14.1500.CrossrefMedlineGoogle Scholar - 38.
Micha R, Mozaffarian D . Saturated fat and cardiometabolic risk factors, coronary heart disease, stroke, and diabetes: a fresh look at the evidence.Lipids. 2010; 45:893–905. doi: 10.1007/s11745-010-3393-4.CrossrefMedlineGoogle Scholar - 39.
Chowdhury R, Warnakula S, Kunutsor S, Crowe F, Ward HA, Johnson L, Franco OH, Butterworth AS, Forouhi NG, Thompson SG, Khaw KT, Mozaffarian D, Danesh J, Di Angelantonio E . Association of dietary, circulating, and supplement fatty acids with coronary risk: a systematic review and meta-analysis.Ann Intern Med. 2014; 160:398–406. doi: 10.7326/M13-1788.CrossrefMedlineGoogle Scholar - 40.
Roncaglioni MC, Tombesi M, Avanzini F, Barlera S, Caimi V, Longoni P, Marzona I, Milani V, Silletta MG, Tognoni G, Marchioli R . n-3 fatty acids in patients with multiple cardiovascular risk factors.N Engl J Med. 2013; 368:1800–1808CrossrefMedlineGoogle Scholar - 41.
Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, de Ferranti S, Després JP, Fullerton HJ, Howard VJ, Huffman MD, Judd SE, Kissela BM, Lackland DT, Lichtman JH, Lisabeth LD, Liu S, Mackey RH, Matchar DB, McGuire DK, Mohler ER, Moy CS, Muntner P, Mussolino ME, Nasir K, Neumar RW, Nichol G, Palaniappan L, Pandey DK, Reeves MJ, Rodriguez CJ, Sorlie PD, Stein J, Towfighi A, Turan TN, Virani SS, Willey JZ, Woo D, Yeh RW, Turner MB ; American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics–2015 update: a report from the American Heart Association.Circulation. 2015; 131:e29–e322. doi: 10.1161/CIR.0000000000000152.LinkGoogle Scholar - 42.
Albrecht SS, Gordon-Larsen P, Stern D, Popkin BM . Is waist circumference per body mass index rising differentially across the United States, England, China and Mexico?Eur J Clin Nutr. 2015CrossrefMedlineGoogle Scholar - 43.
de Onis M, Blössner M, Borghi E . Global prevalence and trends of overweight and obesity among preschool children.Am J Clin Nutr. 2010; 92:1257–1264. doi: 10.3945/ajcn.2010.29786.CrossrefMedlineGoogle Scholar - 44.
Estrada E, Eneli I, Hampl S, Mietus-Snyder M, Mirza N, Rhodes E, Sweeney B, Tinajero-Deck L, Woolford SJ, Pont SJ ; Children’s Hospital Association. Children’s Hospital Association consensus statements for comorbidities of childhood obesity.Child Obes. 2014; 10:304–317. doi: 10.1089/chi.2013.0120.CrossrefMedlineGoogle Scholar - 45.
Brand-Miller J, McMillan-Price J, Steinbeck K, Caterson I . Dietary glycemic index: health implications.J Am Coll Nutr. 2009; 28(suppl):446S–449S.CrossrefMedlineGoogle Scholar - 46.
Volk BM, Kunces LJ, Freidenreich DJ, Kupchak BR, Saenz C, Artistizabal JC, Fernandez ML, Bruno RS, Maresh CM, Kraemer WJ, Phinney SD, Volek JS . Effects of step-wise increases in dietary carbohydrate on circulating saturated fatty acids and palmitoleic acid in adults with metabolic syndrome.PLoS One. 2014; 9:e113605. doi: 10.1371/journal.pone.0113605.CrossrefMedlineGoogle Scholar - 47.
Ludwig DS, Friedman MI . Increasing adiposity: consequence or cause of overeating?JAMA. 2014; 311:2167–2168. doi: 10.1001/jama.2014.4133.CrossrefMedlineGoogle Scholar - 48.
Browning JD, Baker JA, Rogers T, Davis J, Satapati S, Burgess SC . Short-term weight loss and hepatic triglyceride reduction: evidence of a metabolic advantage with dietary carbohydrate restriction.Am J Clin Nutr. 2011; 93:1048–1052. doi: 10.3945/ajcn.110.007674.CrossrefMedlineGoogle Scholar - 49.
Lennerz BS, Alsop DC, Holsen LM, Stern E, Rojas R, Ebbeling CB, Goldstein JM, Ludwig DS . Effects of dietary glycemic index on brain regions related to reward and craving in men.Am J Clin Nutr. 2013; 98:641–647. doi: 10.3945/ajcn.113.064113.CrossrefMedlineGoogle Scholar - 50.
Ebbeling CB, Swain JF, Feldman HA, Wong WW, Hachey DL, Garcia-Lago E, Ludwig DS . Effects of dietary composition on energy expenditure during weight-loss maintenance.JAMA. 2012; 307:2627–2634. doi: 10.1001/jama.2012.6607.CrossrefMedlineGoogle Scholar - 51.
Wang H, Troy LM, Rogers GT, Fox CS, McKeown NM, Meigs JB, Jacques PF . Longitudinal association between dairy consumption and changes of body weight and waist circumference: the Framingham Heart Study.Int J Obes (Lond). 2014; 38:299–305. doi: 10.1038/ijo.2013.78.CrossrefMedlineGoogle Scholar - 52.
Poutahidis T, Kleinewietfeld M, Smillie C, Levkovich T, Perrotta A, Bhela S, Varian BJ, Ibrahim YM, Lakritz JR, Kearney SM, Chatzigiagkos A, Hafler DA, Alm EJ, Erdman SE . Microbial reprogramming inhibits Western diet-associated obesity.PLoS One. 2013; 8:e68596. doi: 10.1371/journal.pone.0068596.CrossrefMedlineGoogle Scholar - 53.
Park DY, Ahn YT, Park SH, Huh CS, Yoo SR, Yu R, Sung MK, McGregor RA, Choi MS . Supplementation of Lactobacillus curvatus HY7601 and Lactobacillus plantarum KY1032 in diet-induced obese mice is associated with gut microbial changes and reduction in obesity.PLoS One. 2013; 8:e59470. doi: 10.1371/journal.pone.0059470.CrossrefMedlineGoogle Scholar - 54.
Power SE, O’Toole PW, Stanton C, Ross RP, Fitzgerald GF . Intestinal microbiota, diet and health.Br J Nutr. 2014; 111:387–402. doi: 10.1017/S0007114513002560.CrossrefMedlineGoogle Scholar - 55.
Bertoia ML, Mukamal KJ, Cahill LE, Hou T, Ludwig DS, Mozaffarian D, Willett WC, Hu FB, Rimm EB . Changes in intake of fruits and vegetables and weight change in United States men and women followed for up to 24 years: analysis from three prospective cohort studies.PLoS Med. 2015; 12:e1001878. doi: 10.1371/journal.pmed.1001878.CrossrefMedlineGoogle Scholar - 56. Food and Nutrition Service, US Department of Agriculture.Nutrition standards in the national school lunch and school breakfast programs.2012. https://www.federalregister.gov/articles/2012/01/26/2012-1010/nutrition-standards-in-the-national-school-lunch-and-school-breakfast-programs. Accessed May 26, 2015.Google Scholar
- 57.
Sluijs I, Forouhi NG, Beulens JW, van der Schouw YT, Agnoli C, Arriola L, Balkau B, Barricarte A, Boeing H, Bueno-de-Mesquita HB, Clavel-Chapelon F, Crowe FL, de Lauzon-Guillain B, Drogan D, Franks PW, Gavrila D, Gonzalez C, Halkjaer J, Kaaks R, Moskal A, Nilsson P, Overvad K, Palli D, Panico S, Quirós JR, Ricceri F, Rinaldi S, Rolandsson O, Sacerdote C, Sánchez MJ, Slimani N, Spijkerman AM, Teucher B, Tjonneland A, Tormo MJ, Tumino R, van der A DL, Sharp SJ, Langenberg C, Feskens EJ, Riboli E, Wareham NJ ; InterAct Consortium. The amount and type of dairy product intake and incident type 2 diabetes: results from the EPIC-InterAct Study.Am J Clin Nutr. 2012; 96:382–390. doi: 10.3945/ajcn.111.021907.CrossrefMedlineGoogle Scholar - 58.
O’Sullivan TA, Hafekost K, Mitrou F, Lawrence D . Food sources of saturated fat and the association with mortality: a meta-analysis.Am J Public Health. 2013; 103:e31–e42. doi: 10.2105/AJPH.2013.301492.CrossrefMedlineGoogle Scholar - 59.
Mozaffarian D, Cao H, King IB, Lemaitre RN, Song X, Siscovick DS, Hotamisligil GS . Trans-palmitoleic acid, metabolic risk factors, and new-onset diabetes in U.S. adults: a cohort study.Ann Intern Med. 2010; 153:790–799. doi: 10.7326/0003-4819-153-12-201012210-00005.CrossrefMedlineGoogle Scholar - 60.
Mozaffarian D, de Oliveira Otto MC, Lemaitre RN, Fretts AM, Hotamisligil G, Tsai MY, Siscovick DS, Nettleton JA . trans-Palmitoleic acid, other dairy fat biomarkers, and incident diabetes: the Multi-Ethnic Study of Atherosclerosis (MESA).Am J Clin Nutr. 2013; 97:854–861. doi: 10.3945/ajcn.112.045468.CrossrefMedlineGoogle Scholar - 61.
Forouhi NG, Koulman A, Sharp SJ, Imamura F, Kröger J, Schulze MB, Crowe FL, Huerta JM, Guevara M, Beulens JW, van Woudenbergh GJ, Wang L, Summerhill K, Griffin JL, Feskens EJ, Amiano P, Boeing H, Clavel-Chapelon F, Dartois L, Fagherazzi G, Franks PW, Gonzalez C, Jakobsen MU, Kaaks R, Key TJ, Khaw KT, Kühn T, Mattiello A, Nilsson PM, Overvad K, Pala V, Palli D, Quirós JR, Rolandsson O, Roswall N, Sacerdote C, Sánchez MJ, Slimani N, Spijkerman AM, Tjonneland A, Tormo MJ, Tumino R, van der A DL, van der Schouw YT, Langenberg C, Riboli E, Wareham NJ . Differences in the prospective association between individual plasma phospholipid saturated fatty acids and incident type 2 diabetes: the EPIC-InterAct case-cohort study.Lancet Diabetes Endocrinol. 2014; 2:810–818. doi: 10.1016/S2213-8587(14)70146-9.CrossrefMedlineGoogle Scholar - 62.
Scharf RJ, Demmer RT, DeBoer MD . Longitudinal evaluation of milk type consumed and weight status in preschoolers.Arch Dis Child. 2013; 98:335–340. doi: 10.1136/archdischild-2012-302941.CrossrefMedlineGoogle Scholar - 63.
Noel SE, Ness AR, Northstone K, Emmett P, Newby PK . Associations between flavored milk consumption and changes in weight and body composition over time: differences among normal and overweight children.Eur J Clin Nutr. 2013; 67:295–300. doi: 10.1038/ejcn.2012.123.CrossrefMedlineGoogle Scholar - 64.
Huh SY, Rifas-Shiman SL, Rich-Edwards JW, Taveras EM, Gillman MW . Prospective association between milk intake and adiposity in preschool-aged children.J Am Diet Assoc. 2010; 110:563–570. doi: 10.1016/j.jada.2009.12.025.CrossrefMedlineGoogle Scholar - 65.
Berkey CS, Rockett HR, Willett WC, Colditz GA . Milk, dairy fat, dietary calcium, and weight gain: a longitudinal study of adolescents.Arch Pediatr Adolesc Med. 2005; 159:543–550. doi: 10.1001/archpedi.159.6.543.CrossrefMedlineGoogle Scholar - 66.
Noel SE, Ness AR, Northstone K, Emmett P, Newby PK . Milk intakes are not associated with percent body fat in children from ages 10 to 13 years.J Nutr. 2011; 141:2035–2041. doi: 10.3945/jn.111.143420.CrossrefMedlineGoogle Scholar - 67.
Gonnissen HK, Hulshof T, Westerterp-Plantenga MS . Chronobiology, endocrinology, and energy- and food-reward homeostasis.Obes Rev. 2013; 14:405–416. doi: 10.1111/obr.12019.CrossrefMedlineGoogle Scholar - 68.
Haines J, McDonald J, O’Brien A, Sherry B, Bottino CJ, Schmidt ME, Taveras EM . Healthy Habits, Happy Homes: randomized trial to improve household routines for obesity prevention among preschool-aged children.JAMA Pediatr. 2013; 167:1072–1079. doi: 10.1001/jamapediatrics.2013.2356.CrossrefMedlineGoogle Scholar - 69.
Corfe BM, Harden CJ, Bull M, Garaiova I . The multifactorial interplay of diet, the microbiome and appetite control: current knowledge and future challenges.Proc Nutr Soc. 2015: 74:235–244XXX.CrossrefMedlineGoogle Scholar - 70.
Catalano P, deMouzon SH . Maternal obesity and metabolic risk to the offspring: why lifestyle interventions may have not achieved the desired outcomes.Int J Obes (Lond). 2015; 39:642–649. doi: 10.1038/ijo.2015.15.CrossrefMedlineGoogle Scholar - 71.
Robinson TN . Reducing children’s television viewing to prevent obesity: a randomized controlled trial.JAMA. 1999; 282:1561–1567.CrossrefMedlineGoogle Scholar - 72.
Epstein LH, Roemmich JN, Robinson JL, Paluch RA, Winiewicz DD, Fuerch JH, Robinson TN . A randomized trial of the effects of reducing television viewing and computer use on body mass index in young children.Arch Pediatr Adolesc Med. 2008; 162:239–245. doi: 10.1001/archpediatrics.2007.45.CrossrefMedlineGoogle Scholar - 73.
Christakis NA, Fowler JH . The spread of obesity in a large social network over 32 years.N Engl J Med. 2007; 357:370–379. doi: 10.1056/NEJMsa066082.CrossrefMedlineGoogle Scholar - 74.
Corella D, Ordovas JM . Nutrigenomics in cardiovascular medicine.Circ Cardiovasc Genet. 2009; 2:637–651. doi: 10.1161/CIRCGENETICS.109.891366.LinkGoogle Scholar - 75.
Kalantarian S, Rimm EB, Herrington DM, Mozaffarian D . Dietary macronutrients, genetic variation, and progression of coronary atherosclerosis among women.Am Heart J. 2014; 167:627–635.e1. doi: 10.1016/j.ahj.2014.01.001.CrossrefMedlineGoogle Scholar - 76.
Abdullah MM, Jones PJ, Eck PK . Nutrigenetics of cholesterol metabolism: observational and dietary intervention studies in the postgenomic era.Nutr Rev. 2015; 73:523–543. doi: 10.1093/nutrit/nuv016.CrossrefMedlineGoogle Scholar - 77.
Villegas R, Goodloe RJ, McClellan BE, Boston J, Crawford DC . Gene-carbohydrate and gene-fiber interactions and type 2 diabetes in diverse populations from the National Health and Nutrition Examination Surveys (NHANES) as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study.BMC Genet. 2014; 15:69. doi: 10.1186/1471-2156-15-69.CrossrefMedlineGoogle Scholar - 78.
Nettleton JA, Hivert MF, Lemaitre RN, McKeown NM, Mozaffarian D, Tanaka T, Wojczynski MK, Hruby A, Djoussé L, Ngwa JS, Follis JL, Dimitriou M, Ganna A, Houston DK, Kanoni S, Mikkilä V, Manichaikul A, Ntalla I, Renström F, Sonestedt E, van Rooij FJ, Bandinelli S, de Koning L, Ericson U, Hassanali N, Kiefte-de Jong JC, Lohman KK, Raitakari O, Papoutsakis C, Sjogren P, Stirrups K, Ax E, Deloukas P, Groves CJ, Jacques PF, Johansson I, Liu Y, McCarthy MI, North K, Viikari J, Zillikens MC, Dupuis J, Hofman A, Kolovou G, Mukamal K, Prokopenko I, Rolandsson O, Seppälä I, Cupples LA, Hu FB, Kähönen M, Uitterlinden AG, Borecki IB, Ferrucci L, Jacobs DR, Kritchevsky SB, Orho-Melander M, Pankow JS, Lehtimäki T, Witteman JC, Ingelsson E, Siscovick DS, Dedoussis G, Meigs JB, Franks PW . Meta-analysis investigating associations between healthy diet and fasting glucose and insulin levels and modification by loci associated with glucose homeostasis in data from 15 cohorts.Am J Epidemiol. 2013; 177:103–115. doi: 10.1093/aje/kws297.CrossrefMedlineGoogle Scholar - 79.
Smith CE, Ngwa J, Tanaka T, Qi Q, Wojczynski MK, Lemaitre RN, Anderson JS, Manichaikul A, Mikkilä V, van Rooij FJ, Ye Z, Bandinelli S, Frazier-Wood AC, Houston DK, Hu F, Langenberg C, McKeown NM, Mozaffarian D, North KE, Viikari J, Zillikens MC, Djoussé L, Hofman A, Kähönen M, Kabagambe EK, Loos RJ, Saylor GB, Forouhi NG, Liu Y, Mukamal KJ, Chen YD, Tsai MY, Uitterlinden AG, Raitakari O, van Duijn CM, Arnett DK, Borecki IB, Cupples LA, Ferrucci L, Kritchevsky SB, Lehtimäki T, Qi L, Rotter JI, Siscovick DS, Wareham NJ, Witteman JC, Ordovás JM, Nettleton JA . Lipoprotein receptor-related protein 1 variants and dietary fatty acids: meta-analysis of European origin and African American studies.Int J Obes (Lond). 2013; 37:1211–1220. doi: 10.1038/ijo.2012.215.CrossrefMedlineGoogle Scholar - 80.
Tanaka T, Ngwa JS, van Rooij FJ, Zillikens MC, Wojczynski MK, Frazier-Wood AC, Houston DK, Kanoni S, Lemaitre RN, Luan J, Mikkilä V, Renstrom F, Sonestedt E, Zhao JH, Chu AY, Qi L, Chasman DI, de Oliveira Otto MC, Dhurandhar EJ, Feitosa MF, Johansson I, Khaw KT, Lohman KK, Manichaikul A, McKeown NM, Mozaffarian D, Singleton A, Stirrups K, Viikari J, Ye Z, Bandinelli S, Barroso I, Deloukas P, Forouhi NG, Hofman A, Liu Y, Lyytikäinen LP, North KE, Dimitriou M, Hallmans G, Kähönen M, Langenberg C, Ordovas JM, Uitterlinden AG, Hu FB, Kalafati IP, Raitakari O, Franco OH, Johnson A, Emilsson V, Schrack JA, Semba RD, Siscovick DS, Arnett DK, Borecki IB, Franks PW, Kritchevsky SB, Lehtimäki T, Loos RJ, Orho-Melander M, Rotter JI, Wareham NJ, Witteman JC, Ferrucci L, Dedoussis G, Cupples LA, Nettleton JA . Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake.Am J Clin Nutr. 2013; 97:1395–1402. doi: 10.3945/ajcn.112.052183.CrossrefMedlineGoogle Scholar - 81.
Qi Q, Kilpeläinen TO, Downer MK, Tanaka T, Smith CE, Sluijs I, Sonestedt E, Chu AY, Renström F, Lin X, Ängquist LH, Huang J, Liu Z, Li Y, Asif Ali M, Xu M, Ahluwalia TS, Boer JM, Chen P, Daimon M, Eriksson J, Perola M, Friedlander Y, Gao YT, Heppe DH, Holloway JW, Houston DK, Kanoni S, Kim YM, Laaksonen MA, Jääskeläinen T, Lee NR, Lehtimäki T, Lemaitre RN, Lu W, Luben RN, Manichaikul A, Männistö S, Marques-Vidal P, Monda KL, Ngwa JS, Perusse L, van Rooij FJ, Xiang YB, Wen W, Wojczynski MK, Zhu J, Borecki IB, Bouchard C, Cai Q, Cooper C, Dedoussis GV, Deloukas P, Ferrucci L, Forouhi NG, Hansen T, Christiansen L, Hofman A, Johansson I, Jørgensen T, Karasawa S, Khaw KT, Kim MK, Kristiansson K, Li H, Lin X, Liu Y, Lohman KK, Long J, Mikkilä V, Mozaffarian D, North K, Pedersen O, Raitakari O, Rissanen H, Tuomilehto J, van der Schouw YT, Uitterlinden AG, Zillikens MC, Franco OH, Shyong Tai E, Ou Shu X, Siscovick DS, Toft U, Verschuren WM, Vollenweider P, Wareham NJ, Witteman JC, Zheng W, Ridker PM, Kang JH, Liang L, Jensen MK, Curhan GC, Pasquale LR, Hunter DJ, Mohlke KL, Uusitupa M, Cupples LA, Rankinen T, Orho-Melander M, Wang T, Chasman DI, Franks PW, Sørensen TI, Hu FB, Loos RJ, Nettleton JA, Qi L . FTO genetic variants, dietary intake and body mass index: insights from 177,330 individuals.Hum Mol Genet. 2014; 23:6961–6972. doi: 10.1093/hmg/ddu411.CrossrefMedlineGoogle Scholar - 82.
Dashti HS, Follis JL, Smith CE, Tanaka T, Cade BE, Gottlieb DJ, Hruby A, Jacques PF, Lamon-Fava S, Richardson K, Saxena R, Scheer FA, Kovanen L, Bartz TM, Perälä MM, Jonsson A, Frazier-Wood AC, Kalafati IP, Mikkilä V, Partonen T, Lemaitre RN, Lahti J, Hernandez DG, Toft U, Johnson WC, Kanoni S, Raitakari OT, Perola M, Psaty BM, Ferrucci L, Grarup N, Highland HM, Rallidis L, Kähönen M, Havulinna AS, Siscovick DS, Räikkönen K, Jørgensen T, Rotter JI, Deloukas P, Viikari JS, Mozaffarian D, Linneberg A, Seppälä I, Hansen T, Salomaa V, Gharib SA, Eriksson JG, Bandinelli S, Pedersen O, Rich SS, Dedoussis G, Lehtimäki T, Ordovás JM . Habitual sleep duration is associated with BMI and macronutrient intake and may be modified by CLOCK genetic variants.Am J Clin Nutr. 2015; 101:135–143. doi: 10.3945/ajcn.114.095026.CrossrefMedlineGoogle Scholar - 83.
Smith CE, Follis JL, Nettleton JA, Foy M, Wu JH, Ma Y, Tanaka T, Manichakul AW, Wu H, Chu AY, Steffen LM, Fornage M, Mozaffarian D, Kabagambe EK, Ferruci L, Chen YD, Rich SS, Djoussé L, Ridker PM, Tang W, McKnight B, Tsai MY, Bandinelli S, Rotter JI, Hu FB, Chasman DI, Psaty BM, Arnett DK, King IB, Sun Q, Wang L, Lumley T, Chiuve SE, Siscovick DS, Ordovás JM, Lemaitre RN . Dietary fatty acids modulate associations between genetic variants and circulating fatty acids in plasma and erythrocyte membranes: meta-analysis of nine studies in the CHARGE consortium.Mol Nutr Food Res. 2015; 59:1373–1383. doi: 10.1002/mnfr.201400734.CrossrefMedlineGoogle Scholar - 84.
Goran MI, Walker R, Allayee H . Genetic-related and carbohydrate-related factors affecting liver fat accumulation.Curr Opin Clin Nutr Metab Care. 2012; 15:392–396. doi: 10.1097/MCO.0b013e3283544477.CrossrefMedlineGoogle Scholar - 85.
Sevastianova K, Santos A, Kotronen A, Hakkarainen A, Makkonen J, Silander K, Peltonen M, Romeo S, Lundbom J, Lundbom N, Olkkonen VM, Gylling H, Fielding BA, Rissanen A, Yki-Järvinen H . Effect of short-term carbohydrate overfeeding and long-term weight loss on liver fat in overweight humans.Am J Clin Nutr. 2012; 96:727–734. doi: 10.3945/ajcn.112.038695.CrossrefMedlineGoogle Scholar - 86.
Ebbeling CB, Feldman HA, Chomitz VR, Antonelli TA, Gortmaker SL, Osganian SK, Ludwig DS . A randomized trial of sugar-sweetened beverages and adolescent body weight.N Engl J Med. 2012; 367:1407–1416. doi: 10.1056/NEJMoa1203388.CrossrefMedlineGoogle Scholar - 87.
Santoro N, Savoye M, Kim G, Marotto K, Shaw MM, Pierpont B, Caprio S . Hepatic fat accumulation is modulated by the interaction between the rs738409 variant in the PNPLA3 gene and the dietary omega6/omega3 PUFA intake.PLoS One. 2012; 7:e37827. doi: 10.1371/journal.pone.0037827.CrossrefMedlineGoogle Scholar - 88.
Szarc vel Szic K, Declerck K, Vidaković M, Vanden Berghe W . From inflammaging to healthy aging by dietary lifestyle choices: is epigenetics the key to personalized nutrition?Clin Epigenetics. 2015; 7:33. doi: 10.1186/s13148-015-0068-2.CrossrefMedlineGoogle Scholar - 89.
Mirrahimi A, de Souza RJ, Chiavaroli L, Sievenpiper JL, Beyene J, Hanley AJ, Augustin LS, Kendall CW, Jenkins DJ . Associations of glycemic index and load with coronary heart disease events: a systematic review and meta-analysis of prospective cohorts.J Am Heart Assoc. 2012; 1:e000752. doi: 10.1161/JAHA.112.000752.LinkGoogle Scholar - 90.
Gardner CD . Tailoring dietary approaches for weight loss.Int J Obes Suppl. 2012; 2(suppl 1):S11–S15. doi: 10.1038/ijosup.2012.4.CrossrefMedlineGoogle Scholar - 91.
Thomas DE, Elliott EJ . The use of low-glycaemic index diets in diabetes control.Br J Nutr. 2010; 104:797–802. doi: 10.1017/S0007114510001534.CrossrefMedlineGoogle Scholar - 92.
Dong JY, Zhang ZL, Wang PY, Qin LQ . Effects of high-protein diets on body weight, glycaemic control, blood lipids and blood pressure in type 2 diabetes: meta-analysis of randomised controlled trials.Br J Nutr. 2013; 110:781–789. doi: 10.1017/S0007114513002055.CrossrefMedlineGoogle Scholar - 93.
Viana LV, Gross JL, Azevedo MJ . Dietary intervention in patients with gestational diabetes mellitus: a systematic review and meta-analysis of randomized clinical trials on maternal and newborn outcomes.Diabetes Care. 2014; 37:3345–3355. doi: 10.2337/dc14-1530.CrossrefMedlineGoogle Scholar - 94.
Artinian NT, Fletcher GF, Mozaffarian D, Kris-Etherton P, Van Horn L, Lichtenstein AH, Kumanyika S, Kraus WE, Fleg JL, Redeker NS, Meininger JC, Banks J, Stuart-Shor EM, Fletcher BJ, Miller TD, Hughes S, Braun LT, Kopin LA, Berra K, Hayman LL, Ewing LJ, Ades PA, Durstine JL, Houston-Miller N, Burke LE ; American Heart Association Prevention Committee of the Council on Cardiovascular Nursing. Interventions to promote physical activity and dietary lifestyle changes for cardiovascular risk factor reduction in adults: a scientific statement from the American Heart Association.Circulation. 2010; 122:406–441. doi: 10.1161/CIR.0b013e3181e8edf1.LinkGoogle Scholar - 95.
Spring B, Ockene JK, Gidding SS, Mozaffarian D, Moore S, Rosal MC, Brown MD, Vafiadis DK, Cohen DL, Burke LE, Lloyd-Jones D ; American Heart Association Behavior Change Committee of the Council on Epidemiology and Prevention, Council on Lifestyle and Cardiometabolic Health, Council for High Blood Pressure Research, and Council on Cardiovascular and Stroke Nursing. Better population health through behavior change in adults: a call to action.Circulation. 2013; 128:2169–2176. doi: 10.1161/01.cir.0000435173.25936.e1.LinkGoogle Scholar - 96.
Collins FS, Varmus H . A new initiative on precision medicine.N Engl J Med. 2015; 372:793–795. doi: 10.1056/NEJMp1500523.CrossrefMedlineGoogle Scholar - 97.
Capewell S, O’Flaherty M . Rapid mortality falls after risk-factor changes in populations.Lancet. 2011; 378:752–753. doi: 10.1016/S0140-6736(10)62302-1.CrossrefMedlineGoogle Scholar - 98.
McGill R, Anwar E, Orton L, Bromley H, Lloyd-Williams F, O’Flaherty M, Taylor-Robinson D, Guzman-Castillo M, Gillespie D, Moreira P, Allen K, Hyseni L, Calder N, Petticrew M, White M, Whitehead M, Capewell S . Are interventions to promote healthy eating equally effective for all? Systematic review of socioeconomic inequalities in impact.BMC Public Health. 2015; 15:457. doi: 10.1186/s12889-015-1781-7.CrossrefMedlineGoogle Scholar - 99.
Guzman-Castillo M, Ahmed R, Hawkins N, Scholes S, Wilkinson E, Lucy J, Capewell S, O’Flaherty M . The contribution of primary prevention medication and dietary change in coronary mortality reduction in England between 2000 and 2007: a modelling study.BMJ open. 2015; 5:e006070CrossrefMedlineGoogle Scholar - 100.
Hoffman R, Gerber M . Food processing and the Mediterranean diet.Nutrients. 2015; 7:7925–7964. doi: 10.3390/nu7095371.CrossrefMedlineGoogle Scholar - 101.
Louzada ML, Baraldi LG, Steele EM, Martins AP, Canella DS, Moubarac JC, Levy RB, Cannon G, Afshin A, Imamura F, Mozaffarian D, Monteiro CA . Consumption of ultra-processed foods and obesity in Brazilian adolescents and adults.Prev Med. 2015; 81:9–15. doi: 10.1016/j.ypmed.2015.07.018.CrossrefMedlineGoogle Scholar - 102.
Dobarganes C, Márquez-Ruiz G . Possible adverse effects of frying with vegetable oils.Br J Nutr. 2015; 113(suppl 2):S49–S57. doi: 10.1017/S0007114514002347.CrossrefMedlineGoogle Scholar - 103.
Monteiro CA, Moubarac JC, Cannon G, Ng SW, Popkin B . Ultra-processed products are becoming dominant in the global food system.Obes Rev. 2013; 14Suppl 2:21–28. doi: 10.1111/obr.12107.CrossrefMedlineGoogle Scholar - 104.
Ford JA, MacLennan GS, Avenell A, Bolland M, Grey A, Witham M ; RECORD Trial Group. Cardiovascular disease and vitamin D supplementation: trial analysis, systematic review, and meta-analysis.Am J Clin Nutr. 2014; 100:746–755. doi: 10.3945/ajcn.113.082602.CrossrefMedlineGoogle Scholar - 105.
Bjelakovic G, Nikolova D, Gluud LL, Simonetti RG, Gluud C . Mortality in randomized trials of antioxidant supplements for primary and secondary prevention: systematic review and meta-analysis.JAMA. 2007; 297:842–857. doi: 10.1001/jama.297.8.842.CrossrefMedlineGoogle Scholar - 106.
Miller ER, Pastor-Barriuso R, Dalal D, Riemersma RA, Appel LJ, Guallar E . Meta-analysis: high-dosage vitamin E supplementation may increase all-cause mortality.Ann Intern Med. 2005; 142:37–46.CrossrefMedlineGoogle Scholar - 107.
Miller ER, Juraschek S, Pastor-Barriuso R, Bazzano LA, Appel LJ, Guallar E . Meta-analysis of folic acid supplementation trials on risk of cardiovascular disease and risk interaction with baseline homocysteine levels.Am J Cardiol. 2010; 106:517–527. doi: 10.1016/j.amjcard.2010.03.064.CrossrefMedlineGoogle Scholar - 108.
Huang HY, Caballero B, Chang S, Alberg AJ, Semba RD, Schneyer CR, Wilson RF, Cheng TY, Vassy J, Prokopowicz G, Barnes GJ, Bass EB . The efficacy and safety of multivitamin and mineral supplement use to prevent cancer and chronic disease in adults: a systematic review for a National Institutes of Health state-of-the-science conference.Ann Intern Med. 2006; 145:372–385.CrossrefMedlineGoogle Scholar - 109.
Rizos EC, Ntzani EE, Bika E, Kostapanos MS, Elisaf MS . Association between omega-3 fatty acid supplementation and risk of major cardiovascular disease events: a systematic review and meta-analysis.JAMA. 2012; 308:1024–1033. doi: 10.1001/2012.jama.11374.CrossrefMedlineGoogle Scholar - 110. Dietary Guidelines Advisory Committee. 2010 Report of the Dietary Guidelines Advisory Committee on the Dietary Guidelines for Americans.2010. http://www.cnpp.usda.gov/DGAs2010-DGACReport.htm. Accessed September 26, 2010.Google Scholar
- 111.
Autier P, Gandini S . Vitamin D supplementation and total mortality: a meta-analysis of randomized controlled trials.Arch Intern Med. 2007; 167:1730–1737. doi: 10.1001/archinte.167.16.1730.CrossrefMedlineGoogle Scholar - 112.
Mozaffarian D . UpToDate: Fish oil and marine omega-3 fatty acids.2010. http://www.uptodate.com/patients/content/topic.do?topicKey=~P22PNBTmTumdat. Accessed October 13, 2010.Google Scholar - 113.
Bolland MJ, Avenell A, Baron JA, Grey A, MacLennan GS, Gamble GD, Reid IR . Effect of calcium supplements on risk of myocardial infarction and cardiovascular events: meta-analysis.BMJ. 2010; 341:c3691.CrossrefMedlineGoogle Scholar - 114.
Basu A, Rhone M, Lyons TJ . Berries: emerging impact on cardiovascular health.Nutr Rev. 2010; 68:168–177. doi: 10.1111/j.1753-4887.2010.00273.x.CrossrefMedlineGoogle Scholar - 115.
Huang WY, Davidge ST, Wu J . Bioactive natural constituents from food sources-potential use in hypertension prevention and treatment.Crit Rev Food Sci Nutr. 2013; 53:615–630. doi: 10.1080/10408398.2010.550071.CrossrefMedlineGoogle Scholar - 116.
Gylling H, Plat J, Turley S, Ginsberg HN, Ellegård L, Jessup W, Jones PJ, Lütjohann D, Maerz W, Masana L, Silbernagel G, Staels B, Borén J, Catapano AL, De Backer G, Deanfield J, Descamps OS, Kovanen PT, Riccardi G, Tokgözoglu L, Chapman MJ ; European Atherosclerosis Society Consensus Panel on Phytosterols. Plant sterols and plant stanols in the management of dyslipidaemia and prevention of cardiovascular disease.Atherosclerosis. 2014; 232:346–360. doi: 10.1016/j.atherosclerosis.2013.11.043.CrossrefMedlineGoogle Scholar - 117.
Mirmiran P, Bahadoran Z, Azizi F . Functional foods-based diet as a novel dietary approach for management of type 2 diabetes and its complications: a review.World J Diabetes. 2014; 5:267–281. doi: 10.4239/wjd.v5.i3.267.CrossrefMedlineGoogle Scholar - 118.
Mehta N, Ahlawat SS, Sharma DP, Dabur RS . Novel trends in development of dietary fiber rich meat products-a critical review.J Food Sci Technol. 2015; 52:633–647. doi: 10.1007/s13197-013-1010-2.CrossrefMedlineGoogle Scholar - 119.
Bhat ZF, Kumar S, Bhat HF . Bioactive peptides of animal origin: a review.J Food Sci Technol. 2015; 52:5377–5392. doi: 10.1007/s13197-015-1731-5.CrossrefMedlineGoogle Scholar - 120.
Ryan PM, Ross RP, Fitzgerald GF, Caplice NM, Stanton C . Functional food addressing heart health: do we have to target the gut microbiota?Curr Opin Clin Nutr Metab Care. 2015; 18:566–571. doi: 10.1097/MCO.0000000000000224.CrossrefMedlineGoogle Scholar - 121.
Sharma S, Puri S . Prebiotics and lipid metabolism: a review.Altern Ther Health Med. 2015; 21(suppl 3):34–42.MedlineGoogle Scholar - 122.
Vergès B, Fumeron F . Potential risks associated with increased plasma plant-sterol levels.Diabetes Metab. 2015; 41:76–81. doi: 10.1016/j.diabet.2014.11.003.CrossrefMedlineGoogle Scholar - 123.
Weingärtner O, Teupser D, Patel SB . The atherogenicity of plant sterols: the evidence from genetics to clinical trials.J AOAC Int. 2015; 98:742–749. doi: 10.5740/jaoacint.SGEWeingartner.CrossrefMedlineGoogle Scholar - 124.
Dangour AD, Dodhia SK, Hayter A, Allen E, Lock K, Uauy R . Nutritional quality of organic foods: a systematic review.Am J Clin Nutr. 2009; 90:680–685. doi: 10.3945/ajcn.2009.28041.CrossrefMedlineGoogle Scholar - 125.
Smith-Spangler C, Brandeau ML, Hunter GE, Bavinger JC, Pearson M, Eschbach PJ, Sundaram V, Liu H, Schirmer P, Stave C, Olkin I, Bravata DM . Are organic foods safer or healthier than conventional alternatives?: a systematic review.Ann Intern Med. 2012; 157:348–366. doi: 10.7326/0003-4819-157-5-201209040-00007.CrossrefMedlineGoogle Scholar - 126.
Barański M, Srednicka-Tober D, Volakakis N, Seal C, Sanderson R, Stewart GB, Benbrook C, Biavati B, Markellou E, Giotis C, Gromadzka-Ostrowska J, Rembiałkowska E, Skwarło-Sońta K, Tahvonen R, Janovská D, Niggli U, Nicot P, Leifert C . Higher antioxidant and lower cadmium concentrations and lower incidence of pesticide residues in organically grown crops: a systematic literature review and meta-analyses.Br J Nutr. 2014; 112:794–811. doi: 10.1017/S0007114514001366.CrossrefMedlineGoogle Scholar - 127.
Dangour AD, Lock K, Hayter A, Aikenhead A, Allen E, Uauy R . Nutrition-related health effects of organic foods: a systematic review.Am J Clin Nutr. 2010; 92:203–210. doi: 10.3945/ajcn.2010.29269.CrossrefMedlineGoogle Scholar - 128.
Załęcka A, Bügel S, Paoletti F, Kahl J, Bonanno A, Dostalova A, Rahmann G . The influence of organic production on food quality - research findings, gaps and future challenges.J Sci Food Agric. 2014; 94:2600–2604. doi: 10.1002/jsfa.6578.CrossrefMedlineGoogle Scholar - 129.
Johansson E, Hussain A, Kuktaite R, Andersson SC, Olsson ME . Contribution of organically grown crops to human health.Int J Environ Res Public Health. 2014; 11:3870–3893. doi: 10.3390/ijerph110403870.CrossrefMedlineGoogle Scholar - 130. American Medical Association.AMA Report on Genetically Modified Crops and Foods 2001.https://www.isaaa.org/kc/Publications/htm/articles/Position/ama.htm. Accessed July 16, 2015.Google Scholar
- 131.
Key S, Ma JK, Drake PM . Genetically modified plants and human health.J R Soc Med. 2008; 101:290–298. doi: 10.1258/jrsm.2008.070372.CrossrefMedlineGoogle Scholar - 132. American Association for the Advancement of Science. Statement by the AAAS Board of Directors On Labeling of Genetically Modified Foods.2013. http://www.aaas.org/sites/default/files/AAAS_GM_statement.pdf. Accessed July 16, 2015.Google Scholar
- 133. World Health Organization. Frequently asked questions on genetically modified foods.2014. http://www.who.int/foodsafety/areas_work/food-technology/Frequently_asked_questions_on_gm_foods.pdf?ua=1. Accessed July 16, 2015.Google Scholar
- 134.
Van Eenennaam AL, Young AE . Prevalence and impacts of genetically engineered feedstuffs on livestock populations.J Anim Sci. 2014; 92:4255–4278. doi: 10.2527/jas.2014-8124.CrossrefMedlineGoogle Scholar - 135.
Domingo JL, Giné Bordonaba J . A literature review on the safety assessment of genetically modified plants.Environ Int. 2011; 37:734–742. doi: 10.1016/j.envint.2011.01.003.CrossrefMedlineGoogle Scholar - 136.
Hammond B, Kough J, Herouet-Guicheney C, Jez JM ; ILSI International Food Biotechnology Committee Task Force on Use of Mammalian Toxicology Studies in Safety Assessment of GM Foods. Toxicological evaluation of proteins introduced into food crops.Crit Rev Toxicol. 2013; 43(suppl 2):25–42. doi: 10.3109/10408444.2013.842956.CrossrefMedlineGoogle Scholar - 137.
Bartholomaeus A, Parrott W, Bondy G, Walker K ; ILSI International Food Biotechnology Committee Task Force on Use of Mammalian Toxicology Studies in Safety Assessment of GM Foods. The use of whole food animal studies in the safety assessment of genetically modified crops: limitations and recommendations.Crit Rev Toxicol. 2013; 43Suppl 2:1–24. doi: 10.3109/10408444.2013.842955.CrossrefMedlineGoogle Scholar - 138.
Nicolia A, Manzo A, Veronesi F, Rosellini D . An overview of the last 10 years of genetically engineered crop safety research.Crit Rev Biotechnol. 2014; 34:77–88. doi: 10.3109/07388551.2013.823595.CrossrefMedlineGoogle Scholar - 139.
Devos Y, Aguilera J, Diveki Z, Gomes A, Liu Y, Paoletti C, du Jardin P, Herman L, Perry JN, Waigmann E . EFSA’s scientific activities and achievements on the risk assessment of genetically modified organisms (GMOs) during its first decade of existence: looking back and ahead.Transgenic Res. 2014; 23:1–25. doi: 10.1007/s11248-013-9741-4.CrossrefMedlineGoogle Scholar - 140. Institute of Medicine. Safety of Genetically Modified Foods: Approaches to Assessing Unintended Health Effects. Washington DC: The National Academies Press; 2004.Google Scholar
- 141.
Micha R, Wallace SK, Mozaffarian D . Red and processed meat consumption and risk of incident coronary heart disease, stroke, and diabetes mellitus: a systematic review and meta-analysis.Circulation. 2010; 121:2271–2283. doi: 10.1161/CIRCULATIONAHA.109.924977.LinkGoogle Scholar - 142.
Gan Y, Tong X, Li L, Cao S, Yin X, Gao C, Herath C, Li W, Jin Z, Chen Y, Lu Z . Consumption of fruit and vegetable and risk of coronary heart disease: a meta-analysis of prospective cohort studies.Int J Cardiol. 2015; 183:129–137. doi: 10.1016/j.ijcard.2015.01.077.CrossrefMedlineGoogle Scholar - 143.
Hu D, Huang J, Wang Y, Zhang D, Qu Y . Fruits and vegetables consumption and risk of stroke: a meta-analysis of prospective cohort studies.Stroke. 2014; 45:1613–1619. doi: 10.1161/STROKEAHA.114.004836.LinkGoogle Scholar - 144.
Li M, Fan Y, Zhang X, Hou W, Tang Z . Fruit and vegetable intake and risk of type 2 diabetes mellitus: meta-analysis of prospective cohort studies.BMJ Open. 2014; 4:e005497. doi: 10.1136/bmjopen-2014-005497.CrossrefMedlineGoogle Scholar - 145.
Afshin A, Micha R, Khatibzadeh S, Mozaffarian D . Consumption of nuts and legumes and risk of incident ischemic heart disease, stroke, and diabetes: a systematic review and meta-analysis.Am J Clin Nutr. 2014; 100:278–288. doi: 10.3945/ajcn.113.076901.CrossrefMedlineGoogle Scholar - 146.
Halton TL, Willett WC, Liu S, Manson JE, Stampfer MJ, Hu FB . Potato and french fry consumption and risk of type 2 diabetes in women.Am J Clin Nutr. 2006; 83:284–290.CrossrefMedlineGoogle Scholar - 147.
Heidari-Beni M, Golshahi J, Esmaillzadeh A, Azadbakht L . Potato consumption as high glycemic index food, blood pressure, and body mass index among Iranian adolescent girls.ARYA Atheroscler. 2015; 11(suppl 1):81–87.MedlineGoogle Scholar - 148.
Khosravi-Boroujeni H, Mohammadifard N, Sarrafzadegan N, Sajjadi F, Maghroun M, Khosravi A, Alikhasi H, Rafieian M, Azadbakht L . Potato consumption and cardiovascular disease risk factors among Iranian population.Int J Food Sci Nutr. 2012; 63:913–920. doi: 10.3109/09637486.2012.690024.CrossrefMedlineGoogle Scholar - 149.
Khosravi-Boroujeni H, Saadatnia M, Shakeri F, Keshteli AH, Esmaillzadeh A . A case-control study on potato consumption and risk of stroke in central Iran.Arch Iran Med. 2013; 16:172–176. doi: 013163/AIM.009.MedlineGoogle Scholar - 150.
Manwa B, Kashongwe Z, Bahindwa B, Kolanowski J, Hermans MP . Dietary cassava, beta-cell function and hyperbolic product loss rate in type 2 diabetes patients from South Kivu.Diabetes Metab. 2010; 36:108–113. doi: 10.1016/j.diabet.2009.08.001.CrossrefMedlineGoogle Scholar - 151.
Rosa ML, Falcão PM, Yokoo EM, da Cruz Filho RA, Alcoforado VM, de Souza Bda S, Pinto FN, Nery AB . Brazil’s staple food and incident diabetes.Nutrition. 2014; 30:365–368. doi: 10.1016/j.nut.2013.09.004.CrossrefMedlineGoogle Scholar - 152.
Tang G, Wang D, Long J, Yang F, Si L . Meta-analysis of the association between whole grain intake and coronary heart disease risk.Am J Cardiol. 2015; 115:625–629. doi: 10.1016/j.amjcard.2014.12.015.CrossrefMedlineGoogle Scholar - 153.
Mellen PB, Walsh TF, Herrington DM . Whole grain intake and cardiovascular disease: a meta-analysis.Nutr Metab Cardiovasc Dis. 2008; 18:283–290. doi: 10.1016/j.numecd.2006.12.008.CrossrefMedlineGoogle Scholar - 154.
Aune D, Norat T, Romundstad P, Vatten LJ . Whole grain and refined grain consumption and the risk of type 2 diabetes: a systematic review and dose-response meta-analysis of cohort studies.Eur J Epidemiol. 2013; 28:845–858. doi: 10.1007/s10654-013-9852-5.CrossrefMedlineGoogle Scholar - 155.
Jakobsen MU, O’Reilly EJ, Heitmann BL, Pereira MA, Bälter K, Fraser GE, Goldbourt U, Hallmans G, Knekt P, Liu S, Pietinen P, Spiegelman D, Stevens J, Virtamo J, Willett WC, Ascherio A . Major types of dietary fat and risk of coronary heart disease: a pooled analysis of 11 cohort studies.Am J Clin Nutr. 2009; 89:1425–1432. doi: 10.3945/ajcn.2008.27124.CrossrefMedlineGoogle Scholar - 156.
Cai X, Wang C, Wang S, Cao G, Jin C, Yu J, Li X, Yan J, Wang F, Yu W, Ding F . Carbohydrate intake, glycemic index, glycemic load, and stroke: a meta-analysis of prospective cohort studies.Asia Pac J Public Health. 2015; 27:486–496. doi: 10.1177/1010539514566742.CrossrefMedlineGoogle Scholar - 157.
Alhazmi A, Stojanovski E, McEvoy M, Garg ML . Macronutrient intakes and development of type 2 diabetes: a systematic review and meta-analysis of cohort studies.J Am Coll Nutr. 2012; 31:243–258.CrossrefMedlineGoogle Scholar - 158.
Bhupathiraju SN, Tobias DK, Malik VS, Pan A, Hruby A, Manson JE, Willett WC, Hu FB . Glycemic index, glycemic load, and risk of type 2 diabetes: results from 3 large US cohorts and an updated meta-analysis.Am J Clin Nutr. 2014; 100:218–232. doi: 10.3945/ajcn.113.079533.CrossrefMedlineGoogle Scholar - 159.
Wu Y, Qian Y, Pan Y, Li P, Yang J, Ye X, Xu G . Association between dietary fiber intake and risk of coronary heart disease: a meta-analysis.Clin Nutr. 2015; 34:603–611. doi: 10.1016/j.clnu.2014.05.009.CrossrefMedlineGoogle Scholar - 160.
Yao B, Fang H, Xu W, Yan Y, Xu H, Liu Y, Mo M, Zhang H, Zhao Y . Dietary fiber intake and risk of type 2 diabetes: a dose-response analysis of prospective studies.Eur J Epidemiol. 2014; 29:79–88. doi: 10.1007/s10654-013-9876-x.CrossrefMedlineGoogle Scholar - 161.
Atkinson FS, Foster-Powell K, Brand-Miller JC . International tables of glycemic index and glycemic load values: 2008.Diabetes Care. 2008; 31:2281–2283. doi: 10.2337/dc08-1239.CrossrefMedlineGoogle Scholar - 162.
Lê KA, Bortolotti M . Role of dietary carbohydrates and macronutrients in the pathogenesis of nonalcoholic fatty liver disease.Curr Opin Clin Nutr Metab Care. 2008; 11:477–482. doi: 10.1097/MCO.0b013e328302f3ec.CrossrefMedlineGoogle Scholar - 163.
Gower BA, Goss AM . A lower-carbohydrate, higher-fat diet reduces abdominal and intermuscular fat and increases insulin sensitivity in adults at risk of type 2 diabetes.J Nutr. 2015; 145:177S–183S. doi: 10.3945/jn.114.195065.CrossrefMedlineGoogle Scholar - 164.
Basaranoglu M, Basaranoglu G, Sabuncu T, Sentürk H . Fructose as a key player in the development of fatty liver disease.World J Gastroenterol. 2013; 19:1166–1172. doi: 10.3748/wjg.v19.i8.1166.CrossrefMedlineGoogle Scholar - 165.
Stanhope KL . Sugar consumption, metabolic disease and obesity: the state of the controversy [published online ahead of print September 17, 2015].Crit Rev Clin Lab Sci. doi: 10.3109/10408363.2015.1084990. Accessed October 11, 2015. http://www.tandfonline.com/doi/abs/10.3109/10408363.2015.1084990?journalCode=ilab20CrossrefGoogle Scholar - 166.
Malik VS, Hu FB . Fructose and cardiometabolic health: what the evidence from sugar-sweetened beverages tells us.J Am Coll Cardiol. 2015; 66:1615–1624. doi: 10.1016/j.jacc.2015.08.025.CrossrefMedlineGoogle Scholar - 167.
Fan J, Song Y, Wang Y, Hui R, Zhang W . Dietary glycemic index, glycemic load, and risk of coronary heart disease, stroke, and stroke mortality: a systematic review with meta-analysis.PLoS One. 2012; 7:e52182. doi: 10.1371/journal.pone.0052182.CrossrefMedlineGoogle Scholar - 168.
Lloyd-Jones DM, Hong Y, Labarthe D, Mozaffarian D, Appel LJ, Van Horn L, Greenlund K, Daniels S, Nichol G, Tomaselli GF, Arnett DK, Fonarow GC, Ho PM, Lauer MS, Masoudi FA, Robertson RM, Roger V, Schwamm LH, Sorlie P, Yancy CW, Rosamond WD ; American Heart Association Strategic Planning Task Force and Statistics Committee. Defining and setting national goals for cardiovascular health promotion and disease reduction: the American Heart Association’s strategic Impact Goal through 2020 and beyond.Circulation. 2010; 121:586–613. doi: 10.1161/CIRCULATIONAHA.109.192703.LinkGoogle Scholar - 169.
Mozaffarian RS, Lee RM, Kennedy MA, Ludwig DS, Mozaffarian D, Gortmaker SL . Identifying whole grain foods: a comparison of different approaches for selecting more healthful whole grain products.Public Health Nutr. 2013; 16:2255–2264.CrossrefMedlineGoogle Scholar - 170.
Sinha R, Cross AJ, Graubard BI, Leitzmann MF, Schatzkin A . Meat intake and mortality: a prospective study of over half a million people.Arch Intern Med. 2009; 169:562–571. doi: 10.1001/archinternmed.2009.6.CrossrefMedlineGoogle Scholar - 171.
Bernstein AM, Sun Q, Hu FB, Stampfer MJ, Manson JE, Willett WC . Major dietary protein sources and risk of coronary heart disease in women.Circulation. 2010; 122:876–883. doi: 10.1161/CIRCULATIONAHA.109.915165.LinkGoogle Scholar - 172.
Pan A, Sun Q, Bernstein AM, Schulze MB, Manson JE, Willett WC, Hu FB . Red meat consumption and risk of type 2 diabetes: 3 cohorts of US adults and an updated meta-analysis.Am J Clin Nutr. 2011; 94:1088–1096. doi: 10.3945/ajcn.111.018978.CrossrefMedlineGoogle Scholar - 173.
Chen GC, Lv DB, Pang Z, Liu QF . Red and processed meat consumption and risk of stroke: a meta-analysis of prospective cohort studies.Eur J Clin Nutr. 2013; 67:91–95. doi: 10.1038/ejcn.2012.180.CrossrefMedlineGoogle Scholar - 174.
Abete I, Romaguera D, Vieira AR, Lopez de Munain A, Norat T . Association between total, processed, red and white meat consumption and all-cause, CVD and IHD mortality: a meta-analysis of cohort studies.Br J Nutr. 2014; 112:762–775. doi: 10.1017/S000711451400124X.CrossrefMedlineGoogle Scholar - 175.
Mozaffarian D . Meat intake and mortality: evidence for harm, no effect, or benefit?Arch Intern Med. 2009; 169:1537–1538; author reply 1539. doi: 10.1001/archinternmed.2009.277.CrossrefMedlineGoogle Scholar - 176.
Al-Solaiman Y, Jesri A, Mountford WK, Lackland DT, Zhao Y, Egan BM . DASH lowers blood pressure in obese hypertensives beyond potassium, magnesium and fibre.J Hum Hypertens. 2010; 24:237–246. doi: 10.1038/jhh.2009.58.CrossrefMedlineGoogle Scholar - 177.
Tang WH, Hazen SL . The contributory role of gut microbiota in cardiovascular disease.J Clin Invest. 2014; 124:4204–4211. doi: 10.1172/JCI72331.CrossrefMedlineGoogle Scholar - 178.
Bendinelli B, Palli D, Masala G, Sharp SJ, Schulz MB, Guevara M, van der AD, Sera F, Amiano P, Balkau B, Barricarte A, Boeing H, Crowe FL, Dahm CC, Dalmeijer G, de Lauzon-Guillain B, Egeberg R, Fagherazzi G, Franks PW, Krogh V, Huerta JM, Jakszyn P, Khaw KT, Li K, Mattiello A, Nilsson PM, Overvad K, Ricceri F, Rolandsson O, Sanchez MJ, Slimani N, Sluijs I, Spijkerman AM, Teucher B, Tjonneland A, Tumino R, van den Berg SW, Forouhi NG, Langeberg C, Feskens EJ, Riboli E, Wareham NJ . Association between dietary meat consumption and incident type 2 diabetes: the EPIC-InterAct study.Diabetologia. 2013; 56:47–59CrossrefMedlineGoogle Scholar - 179.
Swaminathan S, Fonseca VA, Alam MG, Shah SV . The role of iron in diabetes and its complications.Diabetes Care. 2007; 30:1926–1933. doi: 10.2337/dc06-2625.CrossrefMedlineGoogle Scholar - 180.
Zhao Z, Li S, Liu G, Yan F, Ma X, Huang Z, Tian H . Body iron stores and heme-iron intake in relation to risk of type 2 diabetes: a systematic review and meta-analysis.PLoS One. 2012; 7:e41641. doi: 10.1371/journal.pone.0041641.CrossrefMedlineGoogle Scholar - 181.
Wittenbecher C, Mühlenbruch K, Kröger J, Jacobs S, Kuxhaus O, Floegel A, Fritsche A, Pischon T, Prehn C, Adamski J, Joost HG, Boeing H, Schulze MB . Amino acids, lipid metabolites, and ferritin as potential mediators linking red meat consumption to type 2 diabetes.Am J Clin Nutr. 2015; 101:1241–1250. doi: 10.3945/ajcn.114.099150.CrossrefMedlineGoogle Scholar - 182.
Kim Y, Keogh J, Clifton P . A review of potential metabolic etiologies of the observed association between red meat consumption and development of type 2 diabetes mellitus.Metabolism. 2015; 64:768–779. doi: 10.1016/j.metabol.2015.03.008.CrossrefMedlineGoogle Scholar - 183.
Micha R, Michas G, Lajous M, Mozaffarian D . Processing of meats and cardiovascular risk: time to focus on preservatives.BMC Med. 2013; 11:136. doi: 10.1186/1741-7015-11-136.CrossrefMedlineGoogle Scholar - 184.
Daley CA, Abbott A, Doyle PS, Nader GA, Larson S . A review of fatty acid profiles and antioxidant content in grass-fed and grain-fed beef.Nutr J. 2010; 9:10. doi: 10.1186/1475-2891-9-10.CrossrefMedlineGoogle Scholar - 185.
Van Elswyk ME, McNeill SH . Impact of grass/forage feeding versus grain finishing on beef nutrients and sensory quality: the U.S. experience.Meat Sci. 2014; 96:535–540. doi: 10.1016/j.meatsci.2013.08.010.CrossrefMedlineGoogle Scholar - 186.
Nagao M, Iso H, Yamagishi K, Date C, Tamakoshi A . Meat consumption in relation to mortality from cardiovascular disease among Japanese men and women.Eur J Clin Nutr. 2012; 66:687–693. doi: 10.1038/ejcn.2012.6.CrossrefMedlineGoogle Scholar - 187.
Takata Y, Shu XO, Gao YT, Li H, Zhang X, Gao J, Cai H, Yang G, Xiang YB, Zheng W . Red meat and poultry intakes and risk of total and cause-specific mortality: results from cohort studies of Chinese adults in Shanghai.PLoS One. 2013; 8:e56963. doi: 10.1371/journal.pone.0056963.CrossrefMedlineGoogle Scholar - 188.
Lee JE, McLerran DF, Rolland B, Chen Y, Grant EJ, Vedanthan R, Inoue M, Tsugane S, Gao YT, Tsuji I, Kakizaki M, Ahsan H, Ahn YO, Pan WH, Ozasa K, Yoo KY, Sasazuki S, Yang G, Watanabe T, Sugawara Y, Parvez F, Kim DH, Chuang SY, Ohishi W, Park SK, Feng Z, Thornquist M, Boffetta P, Zheng W, Kang D, Potter J, Sinha R . Meat intake and cause-specific mortality: a pooled analysis of Asian prospective cohort studies.Am J Clin Nutr. 2013; 98:1032–1041. doi: 10.3945/ajcn.113.062638.CrossrefMedlineGoogle Scholar - 189.
Haring B, Gronroos N, Nettleton JA, von Ballmoos MC, Selvin E, Alonso A . Dietary protein intake and coronary heart disease in a large community based cohort: results from the Atherosclerosis Risk in Communities (ARIC) study [corrected].PLoS One. 2014; 9:e109552. doi: 10.1371/journal.pone.0109552.CrossrefMedlineGoogle Scholar - 190.
van Dam RM, Willett WC, Rimm EB, Stampfer MJ, Hu FB . Dietary fat and meat intake in relation to risk of type 2 diabetes in men.Diabetes Care. 2002; 25:417–424.CrossrefMedlineGoogle Scholar - 191.
Montonen J, Järvinen R, Heliövaara M, Reunanen A, Aromaa A, Knekt P . Food consumption and the incidence of type II diabetes mellitus.Eur J Clin Nutr. 2005; 59:441–448. doi: 10.1038/sj.ejcn.1602094.CrossrefMedlineGoogle Scholar - 192.
Villegas R, Shu XO, Gao YT, Yang G, Cai H, Li H, Zheng W . The association of meat intake and the risk of type 2 diabetes may be modified by body weight.Int J Med Sci. 2006; 3:152–159.CrossrefMedlineGoogle Scholar - 193.
Männistö S, Kontto J, Kataja-Tuomola M, Albanes D, Virtamo J . High processed meat consumption is a risk factor of type 2 diabetes in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention study.Br J Nutr. 2010; 103:1817–1822. doi: 10.1017/S0007114510000073.CrossrefMedlineGoogle Scholar - 194.
Steinbrecher A, Erber E, Grandinetti A, Kolonel LN, Maskarinec G . Meat consumption and risk of type 2 diabetes: the Multiethnic Cohort.Public Health Nutr. 2011; 14:568–574. doi: 10.1017/S1368980010002004.CrossrefMedlineGoogle Scholar - 195.
Kurotani K, Nanri A, Goto A, Mizoue T, Noda M, Oba S, Kato M, Matsushita Y, Inoue M, Tsugane S ; Japan Public Health Center-based Prospective Study Group. Red meat consumption is associated with the risk of type 2 diabetes in men but not in women: a Japan Public Health Center-based Prospective Study.Br J Nutr. 2013; 110:1910–1918. doi: 10.1017/S0007114513001128.CrossrefMedlineGoogle Scholar - 196.
Rong Y, Chen L, Zhu T, Song Y, Yu M, Shan Z, Sands A, Hu FB, Liu L . Egg consumption and risk of coronary heart disease and stroke: dose-response meta-analysis of prospective cohort studies.BMJ. 2013; 346:e8539.CrossrefMedlineGoogle Scholar - 197.
Shin JY, Xun P, Nakamura Y, He K . Egg consumption in relation to risk of cardiovascular disease and diabetes: a systematic review and meta-analysis.Am J Clin Nutr. 2013; 98:146–159. doi: 10.3945/ajcn.112.051318.CrossrefMedlineGoogle Scholar - 198.
Ding EL, Mozaffarian D . Optimal dietary habits for the prevention of stroke.Semin Neurol. 2006; 26:11–23. doi: 10.1055/s-2006-933305.CrossrefMedlineGoogle Scholar - 199.
Iso H . Lifestyle and cardiovascular disease in Japan.J Atheroscler Thromb. 2011; 18:83–88.CrossrefMedlineGoogle Scholar - 200.
Mozaffarian D, Rimm EB . Fish intake, contaminants, and human health: evaluating the risks and the benefits.JAMA. 2006; 296:1885–1899. doi: 10.1001/jama.296.15.1885.CrossrefMedlineGoogle Scholar - 201.
Mozaffarian D, Wu JH . Omega-3 fatty acids and cardiovascular disease: effects on risk factors, molecular pathways, and clinical events.J Am Coll Cardiol. 2011; 58:2047–2067. doi: 10.1016/j.jacc.2011.06.063.CrossrefMedlineGoogle Scholar - 202.
Zheng J, Huang T, Yu Y, Hu X, Yang B, Li D . Fish consumption and CHD mortality: an updated meta-analysis of seventeen cohort studies.Public Health Nutr. 2012; 15:725–737. doi: 10.1017/S1368980011002254.CrossrefMedlineGoogle Scholar - 203.
Larsson SC, Orsini N, Wolk A . Long-chain omega-3 polyunsaturated fatty acids and risk of stroke: a meta-analysis.Eur J Epidemiol. 2012; 27:895–901. doi: 10.1007/s10654-012-9748-9.CrossrefMedlineGoogle Scholar - 204.
Leung Yinko SS, Stark KD, Thanassoulis G, Pilote L . Fish consumption and acute coronary syndrome: a meta-analysis.Am J Med. 2014; 127:848–57.e2. doi: 10.1016/j.amjmed.2014.04.016.CrossrefMedlineGoogle Scholar - 205.
Wu JH, Mozaffarian D . ω-3 fatty acids, atherosclerosis progression and cardiovascular outcomes in recent trials: new pieces in a complex puzzle.Heart. 2014; 100:530–533. doi: 10.1136/heartjnl-2013-305257.CrossrefMedlineGoogle Scholar - 206.
Pradhan AD, Manson JE . Update on the Vitamin D and OmegA-3 trial (VITAL) [published online ahead of print April 9, 2015].J Steroid Biochem Mol Biol. doi: 10.1016/j.jsbmb.2015.04.006. Accessed October 11, 2015. http://www.sciencedirect.com/science/article/pii/S096007601500103XCrossrefGoogle Scholar - 207.
Chowdhury R, Stevens S, Gorman D, Pan A, Warnakula S, Chowdhury S, Ward H, Johnson L, Crowe F, Hu FB, Franco OH . Association between fish consumption, long chain omega 3 fatty acids, and risk of cerebrovascular disease: systematic review and meta-analysis.BMJ. 2012; 345:e6698.CrossrefMedlineGoogle Scholar - 208.
Mozaffarian D, Wu JH, de Oliveira Otto MC, Sandesara CM, Metcalf RG, Latini R, Libby P, Lombardi F, O’Gara PT, Page RL, Silletta MG, Tavazzi L, Marchioli R . Fish oil and post-operative atrial fibrillation: a meta-analysis of randomized controlled trials.J Am Coll Cardiol. 2013; 61:2194–2196. doi: 10.1016/j.jacc.2013.02.045.CrossrefMedlineGoogle Scholar - 209.
Zheng JS, Huang T, Yang J, Fu YQ, Li D . Marine N-3 polyunsaturated fatty acids are inversely associated with risk of type 2 diabetes in Asians: a systematic review and meta-analysis.PLoS One. 2012; 7:e44525. doi: 10.1371/journal.pone.0044525.CrossrefMedlineGoogle Scholar - 210.
Zhou Y, Tian C, Jia C . Association of fish and n-3 fatty acid intake with the risk of type 2 diabetes: a meta-analysis of prospective studies.Br J Nutr. 2012; 108:408–417. doi: 10.1017/S0007114512002036.CrossrefMedlineGoogle Scholar - 211.
Wu JH, Micha R, Imamura F, Pan A, Biggs ML, Ajaz O, Djousse L, Hu FB, Mozaffarian D . Omega-3 fatty acids and incident type 2 diabetes: a systematic review and meta-analysis.Br J Nutr. 2012; 107(suppl 2):S214–S227. doi: 10.1017/S0007114512001602.CrossrefMedlineGoogle Scholar - 212.
Wu JH, Cahill LE, Mozaffarian D . Effect of fish oil on circulating adiponectin: a systematic review and meta-analysis of randomized controlled trials.J Clin Endocrinol Metab. 2013; 98:2451–2459. doi: 10.1210/jc.2012-3899.CrossrefMedlineGoogle Scholar - 213.
Turyk M, Anderson H, Knobeloch L, Imm P, Persky V . Organochlorine exposure and incidence of diabetes in a cohort of Great Lakes sport fish consumers.Environ Health Perspect. 2009; 117:1076–1082. doi: 10.1289/ehp.0800281.CrossrefMedlineGoogle Scholar - 214.
Bergkvist C, Berglund M, Glynn A, Wolk A, Åkesson A . Dietary exposure to polychlorinated biphenyls and risk of myocardial infarction - a population-based prospective cohort study.Int J Cardiol. 2015; 183:242–248. doi: 10.1016/j.ijcard.2015.01.055.CrossrefMedlineGoogle Scholar - 215.
Song Y, Chou EL, Baecker A, You NY, Sun Q, Liu S . Endocrine-disrupting chemicals, risk of type 2 diabetes, and diabetes-related metabolic traits: a systematic review and meta-analysis [published online ahead of print June 29, 2015].J Diabetes. doi: 10.1111/1753-0407.12325. Accessed October 11, 2015. http://onlinelibrary.wiley.com.CrossrefGoogle Scholar - 216.
Wolff E, Dansinger ML . Soft drinks and weight gain: how strong is the link?Medscape J Med. 2008; 10:189.MedlineGoogle Scholar - 217.
Mozaffarian D, Shi P, Morris JS, Grandjean P, Siscovick DS, Spiegelman D, Willett WC, Rimm EB, Curhan GC, Forman JP . Mercury exposure and risk of hypertension in US men and women in 2 prospective cohorts.Hypertension. 2012; 60:645–652. doi: 10.1161/HYPERTENSIONAHA.112.196154.LinkGoogle Scholar - 218.
Mozaffarian D, Shi P, Morris JS, Grandjean P, Siscovick DS, Spiegelman D, Hu FB . Methylmercury exposure and incident diabetes in U.S. men and women in two prospective cohorts.Diabetes Care. 2013; 36:3578–3584. doi: 10.2337/dc13-0894.CrossrefMedlineGoogle Scholar - 219. US Food And Drug Administration, US Environmental Protection Agency.Fish: What Pregnant Women and Parents Should Know.2014. http://www.fda.gov/downloads/Food/FoodborneIllnessContaminants/Metals/UCM400358.pdf. Accessed May 27, 2015.Google Scholar
- 220. National Oceanic and Atmospheric Administration.NOAA Fish Watch: The suprising sources of your favorite seafoods.2011. http://www.fishwatch.gov/features/top10seafoods_and_sources_10_10_12.html. Accessed July 16, 2015.Google Scholar
- 221.
Soedamah-Muthu SS, Verberne LD, Ding EL, Engberink MF, Geleijnse JM . Dairy consumption and incidence of hypertension: a dose-response meta-analysis of prospective cohort studies.Hypertension. 2012; 60:1131–1137. doi: 10.1161/HYPERTENSIONAHA.112.195206.LinkGoogle Scholar - 222.
Hu D, Huang J, Wang Y, Zhang D, Qu Y . Dairy foods and risk of stroke: a meta-analysis of prospective cohort studies.Nutr Metab Cardiovasc Dis. 2014; 24:460–469. doi: 10.1016/j.numecd.2013.12.006.CrossrefMedlineGoogle Scholar - 223.
Qin LQ, Xu JY, Han SF, Zhang ZL, Zhao YY, Szeto IM . Dairy consumption and risk of cardiovascular disease: an updated meta-analysis of prospective cohort studies.Asia Pac J Clin Nutr. 2015; 24:90–100.MedlineGoogle Scholar - 224.
Gao D, Ning N, Wang C, Wang Y, Li Q, Meng Z, Liu Y, Li Q . Dairy products consumption and risk of type 2 diabetes: systematic review and dose-response meta-analysis.PLoS One. 2013; 8:e73965. doi: 10.1371/journal.pone.0073965.CrossrefMedlineGoogle Scholar - 225.
Aune D, Norat T, Romundstad P, Vatten LJ . Dairy products and the risk of type 2 diabetes: a systematic review and dose-response meta-analysis of cohort studies.Am J Clin Nutr. 2013; 98:1066–1083. doi: 10.3945/ajcn.113.059030.CrossrefMedlineGoogle Scholar - 226.
Chen M, Sun Q, Giovannucci E, Mozaffarian D, Manson JE, Willett WC, Hu FB . Dairy consumption and risk of type 2 diabetes: 3 cohorts of US adults and an updated meta-analysis.BMC Med. 2014; 12:215. doi: 10.1186/s12916-014-0215-1.CrossrefMedlineGoogle Scholar - 227.
Ericson U, Hellstrand S, Brunkwall L, Schulz CA, Sonestedt E, Wallström P, Gullberg B, Wirfält E, Orho-Melander M . Food sources of fat may clarify the inconsistent role of dietary fat intake for incidence of type 2 diabetes.Am J Clin Nutr. 2015; 101:1065–1080. doi: 10.3945/ajcn.114.103010.CrossrefMedlineGoogle Scholar - 228.
Diaz-Lopez A, Bullo M, Martinez-Gonzalez MA, Corella D, Estruch R, Fito M, Gomez-Gracia E, Fiol M, Garcia de la Corte FJ, Ros E, Babio N, Serra-Majem L, Pinto X, Munoz MA, Frances F, Buil-Cosiales P, Salas-Salvado J . Dairy product consumption and risk of type 2 diabetes in an elderly Spanish Mediterranean population at high cardiovascular risk [published online ahead of print February 7, 2015].Eur J Nutr. doi:10.1007/s00394-015-0855-8. Accessed October 11, 2015. http://link.springer.com/article/10.1007%2Fs00394-015-0855-8CrossrefGoogle Scholar - 229.
Nestel PJ, Mellett N, Pally S, Wong G, Barlow CK, Croft K, Mori TA, Meikle PJ . Effects of low-fat or full-fat fermented and non-fermented dairy foods on selected cardiovascular biomarkers in overweight adults.Br J Nutr. 2013; 110:2242–2249. doi: 10.1017/S0007114513001621.CrossrefMedlineGoogle Scholar - 230.
Walther B, Karl JP, Booth SL, Boyaval P . Menaquinones, bacteria, and the food supply: the relevance of dairy and fermented food products to vitamin K requirements.Adv Nutr. 2013; 4:463–473. doi: 10.3945/an.113.003855.CrossrefMedlineGoogle Scholar - 231.
Choi HJ, Yu J, Choi H, An JH, Kim SW, Park KS, Jang HC, Kim SY, Shin CS . Vitamin K2 supplementation improves insulin sensitivity via osteocalcin metabolism: a placebo-controlled trial.Diabetes Care. 2011; 34:e147. doi: 10.2337/dc11-0551.CrossrefMedlineGoogle Scholar - 232.
Chen M, Pan A, Malik VS, Hu FB . Effects of dairy intake on body weight and fat: a meta-analysis of randomized controlled trials.Am J Clin Nutr. 2012; 96:735–747. doi: 10.3945/ajcn.112.037119.CrossrefMedlineGoogle Scholar - 233.
Abargouei AS, Janghorbani M, Salehi-Marzijarani M, Esmaillzadeh A . Effect of dairy consumption on weight and body composition in adults: a systematic review and meta-analysis of randomized controlled clinical trials.Int J Obes (Lond). 2012; 36:1485–1493. doi: 10.1038/ijo.2011.269.CrossrefMedlineGoogle Scholar - 234.
Niinikoski H, Viikari J, Rönnemaa T, Helenius H, Jokinen E, Lapinleimu H, Routi T, Lagström H, Seppänen R, Välimäki I, Simell O . Regulation of growth of 7- to 36-month-old children by energy and fat intake in the prospective, randomized STRIP baby trial.Pediatrics. 1997; 100:810–816.CrossrefMedlineGoogle Scholar - 235.
Nupponen M, Pahkala K, Juonala M, Magnussen CG, Niinikoski H, Rönnemaa T, Viikari JS, Saarinen M, Lagström H, Jula A, Simell O, Raitakari OT . Metabolic syndrome from adolescence to early adulthood: effect of infancy-onset dietary counseling of low saturated fat: the Special Turku Coronary Risk Factor Intervention Project (STRIP).Circulation. 2015; 131:605–613. doi: 10.1161/CIRCULATIONAHA.114.010532.LinkGoogle Scholar - 236.
Kadooka Y, Sato M, Imaizumi K, Ogawa A, Ikuyama K, Akai Y, Okano M, Kagoshima M, Tsuchida T . Regulation of abdominal adiposity by probiotics (Lactobacillus gasseri SBT2055) in adults with obese tendencies in a randomized controlled trial.Eur J Clin Nutr. 2010; 64:636–643. doi: 10.1038/ejcn.2010.19.CrossrefMedlineGoogle Scholar - 237.
Sharafedtinov KK, Plotnikova OA, Alexeeva RI, Sentsova TB, Songisepp E, Stsepetova J, Smidt I, Mikelsaar M . Hypocaloric diet supplemented with probiotic cheese improves body mass index and blood pressure indices of obese hypertensive patients–a randomized double-blind placebo-controlled pilot study.Nutr J. 2013; 12:138. doi: 10.1186/1475-2891-12-138.CrossrefMedlineGoogle Scholar - 238.
Jung SP, Lee KM, Kang JH, Yun SI, Park HO, Moon Y, Kim JY . Effect of Lactobacillus gasseri BNR17 on overweight and obese adults: a randomized, double-blind clinical trial.Korean J Fam Med. 2013; 34:80–89. doi: 10.4082/kjfm.2013.34.2.80.CrossrefMedlineGoogle Scholar - 239.
Kadooka Y, Sato M, Ogawa A, Miyoshi M, Uenishi H, Ogawa H, Ikuyama K, Kagoshima M, Tsuchida T . Effect of Lactobacillus gasseri SBT2055 in fermented milk on abdominal adiposity in adults in a randomised controlled trial.Br J Nutr. 2013; 110:1696–1703. doi: 10.1017/S0007114513001037.CrossrefMedlineGoogle Scholar - 240.
Sanchez M, Darimont C, Drapeau V, Emady-Azar S, Lepage M, Rezzonico E, Ngom-Bru C, Berger B, Philippe L, Ammon-Zuffrey C, Leone P, Chevrier G, St-Amand E, Marette A, Doré J, Tremblay A . Effect of Lactobacillus rhamnosus CGMCC1.3724 supplementation on weight loss and maintenance in obese men and women.Br J Nutr. 2014; 111:1507–1519. doi: 10.1017/S0007114513003875.CrossrefMedlineGoogle Scholar - 241.
Barrett HL, Dekker Nitert M, Conwell LS, Callaway LK . Probiotics for preventing gestational diabetes.Cochrane Database Syst Rev. 2014; 2:CD009951. doi: 10.1002/14651858.CD009951.pub2.CrossrefGoogle Scholar - 242.
Kratz M, Baars T, Guyenet S . The relationship between high-fat dairy consumption and obesity, cardiovascular, and metabolic disease.Eur J Nutr. 2013; 52:1–24. doi: 10.1007/s00394-012-0418-1.CrossrefMedlineGoogle Scholar - 243.
Kratz M, Marcovina S, Nelson JE, Yeh MM, Kowdley KV, Callahan HS, Song X, Di C, Utzschneider KM . Dairy fat intake is associated with glucose tolerance, hepatic and systemic insulin sensitivity, and liver fat but not β-cell function in humans.Am J Clin Nutr. 2014; 99:1385–1396. doi: 10.3945/ajcn.113.075457.CrossrefMedlineGoogle Scholar - 244.
Khaw KT, Friesen MD, Riboli E, Luben R, Wareham N . Plasma phospholipid fatty acid concentration and incident coronary heart disease in men and women: the EPIC-Norfolk prospective study.PLoS Med. 2012; 9:e1001255. doi: 10.1371/journal.pmed.1001255.CrossrefMedlineGoogle Scholar - 245.
de Oliveira Otto MC, Nettleton JA, Lemaitre RN, Steffen LM, Kromhout D, Rich SS, Tsai MY, Jacobs DR, Mozaffarian D . Biomarkers of dairy fatty acids and risk of cardiovascular disease in the Multi-ethnic Study of Atherosclerosis.J Am Heart Assoc. 2013; 2:e000092. doi: 10.1161/JAHA.113.000092.LinkGoogle Scholar - 246.
Yakoob MY, Shi P, Hu FB, Campos H, Rexrode KM, Orav EJ, Willett WC, Mozaffarian D . Circulating biomarkers of dairy fat and risk of incident stroke in U.S. men and women in 2 large prospective cohorts.Am J Clin Nutr. 2014; 100:1437–1447. doi: 10.3945/ajcn.114.083097.CrossrefMedlineGoogle Scholar - 247.
Mozaffarian D . Natural trans fat, dairy fat, partially hydrogenated oils, and cardiometabolic health: the Ludwigshafen Risk and Cardiovascular Health Study [published online ahead of print November 18, 2015].Eur Heart J. doi: 10.1093/eurheartj/ehv595. Accessed October 11, 2015. http://eurheartj.oxfordjournals.org/content/early/2015/11/17/eurheartj.ehv595CrossrefGoogle Scholar - 248.
Buijsse B, Boeing H, Drogan D, Schulze MB, Feskens EJ, Amiano P, Barricarte A, Clavel-Chapelon F, de Lauzon-Guillain B, Fagherazzi G, Fonseca-Nunes A, Franks PW, Huerta JM, Jakobsen MU, Kaaks R, Key TJ, Khaw KT, Masala G, Moskal A, Nilsson PM, Overvad K, Pala V, Panico S, Redondo ML, Ricceri F, Rolandsson O, Sánchez MJ, Sluijs I, Spijkerman AM, Tjonneland A, Tumino R, van der A DL, van der Schouw YT, Langenberg C, Sharp SJ, Forouhi NG, Riboli E, Wareham NJ ; InterAct Consortium. Consumption of fatty foods and incident type 2 diabetes in populations from eight European countries.Eur J Clin Nutr. 2015; 69:455–461. doi: 10.1038/ejcn.2014.249.CrossrefMedlineGoogle Scholar - 249.
Janu C, Kumar DRS, Reshma MV, Jayamurthy P, Sundaresan A, Nisha P . Comparative study on the total phenolic content and radical scavenging activity of common edible vegetable oils.J Food Biochem. 2014; 38:38–49.CrossrefGoogle Scholar - 250.
Tresserra-Rimbau A, Rimm EB, Medina-Remón A, Martínez-González MA, de la Torre R, Corella D, Salas-Salvadó J, Gómez-Gracia E, Lapetra J, Arós F, Fiol M, Ros E, Serra-Majem L, Pintó X, Saez GT, Basora J, Sorlí JV, Martínez JA, Vinyoles E, Ruiz-Gutiérrez V, Estruch R, Lamuela-Raventós RM ; PREDIMED Study Investigators. Inverse association between habitual polyphenol intake and incidence of cardiovascular events in the PREDIMED study.Nutr Metab Cardiovasc Dis. 2014; 24:639–647. doi: 10.1016/j.numecd.2013.12.014.CrossrefMedlineGoogle Scholar - 251.
Scotece M, Conde J, Abella V, Lopez V, Pino J, Lago F, Smith AB, Gómez-Reino JJ, Gualillo O . New drugs from ancient natural foods. Oleocanthal, the natural occurring spicy compound of olive oil: a brief history.Drug Discov Today. 2015; 20:406–410. doi: 10.1016/j.drudis.2014.10.017.CrossrefMedlineGoogle Scholar - 252.
Beauchamp GK, Keast RS, Morel D, Lin J, Pika J, Han Q, Lee CH, Smith AB, Breslin PA . Phytochemistry: ibuprofen-like activity in extra-virgin olive oil.Nature. 2005; 437:45–46. doi: 10.1038/437045a.CrossrefMedlineGoogle Scholar - 253.
Fernando WM, Martins IJ, Goozee KG, Brennan CS, Jayasena V, Martins RN . The role of dietary coconut for the prevention and treatment of Alzheimer’s disease: potential mechanisms of action.Br J Nutr. 2015; 114:1–14. doi: 10.1017/S0007114515001452.CrossrefMedlineGoogle Scholar - 254.
Hayes KC, Pronczuk A . Replacing trans fat: the argument for palm oil with a cautionary note on interesterification.J Am Coll Nutr. 2010; 29:253S–284SCrossrefMedlineGoogle Scholar - 255.
Jones PJ, Senanayake VK, Pu S, Jenkins DJ, Connelly PW, Lamarche B, Couture P, Charest A, Baril-Gravel L, West SG, Liu X, Fleming JA, McCrea CE, Kris-Etherton PM . DHA-enriched high-oleic acid canola oil improves lipid profile and lowers predicted cardiovascular disease risk in the canola oil multicenter randomized controlled trial.Am J Clin Nutr. 2014; 100:88–97. doi: 10.3945/ajcn.113.081133.CrossrefMedlineGoogle Scholar - 256.
Hu FB . Resolved: there is sufficient scientific evidence that decreasing sugar-sweetened beverage consumption will reduce the prevalence of obesity and obesity-related diseases.Obes Rev. 2013; 14:606–619. doi: 10.1111/obr.12040.CrossrefMedlineGoogle Scholar - 257.
Imamura F, O’Connor L, Ye Z, Mursu J, Hayashino Y, Bhupathiraju SN, Forouhi NG . Consumption of sugar sweetened beverages, artificially sweetened beverages, and fruit juice and incidence of type 2 diabetes: systematic review, meta-analysis, and estimation of population attributable fraction.BMJ. 2015; 351:h3576.CrossrefMedlineGoogle Scholar - 258.
Xi B, Huang Y, Reilly KH, Li S, Zheng R, Barrio-Lopez MT, Martinez-Gonzalez MA, Zhou D . Sugar-sweetened beverages and risk of hypertension and CVD: a dose-response meta-analysis.Br J Nutr. 2015; 113:709–717. doi: 10.1017/S0007114514004383.CrossrefMedlineGoogle Scholar - 259.
Singh GM, Micha R, Khatibzadeh S, Shi P, Lim S, Andrews KG, Engell RE, Ezzati M, Mozaffarian D , Global Burden of Diseases Nutrition and Chronic Diseases Expert Group. Global, regional, and national consumption levels of sugar-sweetened beverages, fruit juices, and milk: a systematic analysis including 195 country-specific nutrition surveys worldwide.PLoS One. 2015; 10:e0124845. doi: 10.1371/journal.pone.0124845.CrossrefMedlineGoogle Scholar - 260.
Singh GM, Micha R, Khatibzadeh S, Lim S, Ezzati M, Mozaffarian D , on behalf of the Global Burden of Diseases Nutrition and Chronic Diseases Expert Group. Estimated global, regional, and national disease burdens related to sugar-sweetened beverage consumption in 2010.Circulation. 2015; 132:639–666. doi: 10.1161/CIRCULATIONAHA.114.010636.LinkGoogle Scholar - 261.
Raben A, Richelsen B . Artificial sweeteners: a place in the field of functional foods? Focus on obesity and related metabolic disorders.Curr Opin Clin Nutr Metab Care. 2012; 15:597–604. doi: 10.1097/MCO.0b013e328359678a.CrossrefMedlineGoogle Scholar - 262.
Swithers SE, Martin AA, Davidson TL . High-intensity sweeteners and energy balance.Physiol Behav. 2010; 100:55–62. doi: 10.1016/j.physbeh.2009.12.021.CrossrefMedlineGoogle Scholar - 263.
Shankar P, Ahuja S, Sriram K . Non-nutritive sweeteners: review and update.Nutrition. 2013; 29:1293–1299. doi: 10.1016/j.nut.2013.03.024.CrossrefMedlineGoogle Scholar - 264.
Burke MV, Small DM . Physiological mechanisms by which non-nutritive sweeteners may impact body weight and metabolism.Physiol Behav. 2015; 152(pt B):381–388. doi: 10.1016/j.physbeh.2015.05.036.CrossrefMedlineGoogle Scholar - 265.
Pepino MY . Metabolic effects of non-nutritive sweeteners.Physiol Behav. 2015; 152(pt B):450–455. doi: 10.1016/j.physbeh.2015.06.024.CrossrefMedlineGoogle Scholar - 266.
Xi B, Li S, Liu Z, Tian H, Yin X, Huai P, Tang W, Zhou D, Steffen LM . Intake of fruit juice and incidence of type 2 diabetes: a systematic review and meta-analysis.PLoS One. 2014; 9:e93471. doi: 10.1371/journal.pone.0093471.CrossrefMedlineGoogle Scholar - 267.
Liu K, Xing A, Chen K, Wang B, Zhou R, Chen S, Xu H, Mi M . Effect of fruit juice on cholesterol and blood pressure in adults: a meta-analysis of 19 randomized controlled trials.PLoS One. 2013; 8:e61420. doi: 10.1371/journal.pone.0061420.CrossrefMedlineGoogle Scholar - 268.
Wang B, Liu K, Mi M, Wang J . Effect of fruit juice on glucose control and insulin sensitivity in adults: a meta-analysis of 12 randomized controlled trials.PLoS One. 2014; 9:e95323. doi: 10.1371/journal.pone.0095323.CrossrefMedlineGoogle Scholar - 269.
Ding M, Bhupathiraju SN, Chen M, van Dam RM, Hu FB . Caffeinated and decaffeinated coffee consumption and risk of type 2 diabetes: a systematic review and a dose-response meta-analysis.Diabetes Care. 2014; 37:569–586. doi: 10.2337/dc13-1203.CrossrefMedlineGoogle Scholar - 270.
Ding M, Bhupathiraju SN, Satija A, van Dam RM, Hu FB . Long-term coffee consumption and risk of cardiovascular disease: a systematic review and a dose-response meta-analysis of prospective cohort studies.Circulation. 2014; 129:643–659. doi: 10.1161/CIRCULATIONAHA.113.005925.LinkGoogle Scholar - 271.
Wedick NM, Brennan AM, Sun Q, Hu FB, Mantzoros CS, van Dam RM . Effects of caffeinated and decaffeinated coffee on biological risk factors for type 2 diabetes: a randomized controlled trial.Nutr J. 2011; 10:93. doi: 10.1186/1475-2891-10-93.CrossrefMedlineGoogle Scholar - 272.
Ohnaka K, Ikeda M, Maki T, Okada T, Shimazoe T, Adachi M, Nomura M, Takayanagi R, Kono S . Effects of 16-week consumption of caffeinated and decaffeinated instant coffee on glucose metabolism in a randomized controlled trial.J Nutr Metab. 2012; 2012:207426. doi: 10.1155/2012/207426.CrossrefMedlineGoogle Scholar - 273.
Steffen M, Kuhle C, Hensrud D, Erwin PJ, Murad MH . The effect of coffee consumption on blood pressure and the development of hypertension: a systematic review and meta-analysis.J Hypertens. 2012; 30:2245–2254. doi: 10.1097/HJH.0b013e3283588d73.CrossrefMedlineGoogle Scholar - 274.
Nordestgaard AT, Thomsen M, Nordestgaard BG . Coffee intake and risk of obesity, metabolic syndrome and type 2 diabetes: a Mendelian randomization study.Int J Epidemiol. 2015; 44:551–565. doi: 10.1093/ije/dyv083.CrossrefMedlineGoogle Scholar - 275.
Yang WS, Wang WY, Fan WY, Deng Q, Wang X . Tea consumption and risk of type 2 diabetes: a dose-response meta-analysis of cohort studies.Br J Nutr. 2014; 111:1329–1339. doi: 10.1017/S0007114513003887.CrossrefMedlineGoogle Scholar - 276.
Zhang C, Qin YY, Wei X, Yu FF, Zhou YH, He J . Tea consumption and risk of cardiovascular outcomes and total mortality: a systematic review and meta-analysis of prospective observational studies.Eur J Epidemiol. 2015; 30:103–113. doi: 10.1007/s10654-014-9960-x.CrossrefMedlineGoogle Scholar - 277.
Zheng XX, Xu YL, Li SH, Hui R, Wu YJ, Huang XH . Effects of green tea catechins with or without caffeine on glycemic control in adults: a meta-analysis of randomized controlled trials.Am J Clin Nutr. 2013; 97:750–762. doi: 10.3945/ajcn.111.032573.CrossrefMedlineGoogle Scholar - 278.
Li Y, Wang C, Huai Q, Guo F, Liu L, Feng R, Sun C . Effects of tea or tea extract on metabolic profiles in patients with type 2 diabetes mellitus: a meta-analysis of 10 randomized controlled trials [published ahead of print February 17, 2015].Diabetes Metab Res Rev. doi: 10.1002/dmrr.2641. Accessed October 11, 2015. http://onlinelibrary.wiley.com.CrossrefGoogle Scholar - 279.
Liu G, Mi XN, Zheng XX, Xu YL, Lu J, Huang XH . Effects of tea intake on blood pressure: a meta-analysis of randomised controlled trials.Br J Nutr. 2014; 112:1043–1054. doi: 10.1017/S0007114514001731.CrossrefMedlineGoogle Scholar - 280.
Yarmolinsky J, Gon G, Edwards P . Effect of tea on blood pressure for secondary prevention of cardiovascular disease: a systematic review and meta-analysis of randomized controlled trials.Nutr Rev. 2015; 73:236–246. doi: 10.1093/nutrit/nuv001.CrossrefMedlineGoogle Scholar - 281.
Serban C, Sahebkar A, Ursoniu S, Andrica F, Banach M . Effect of sour tea (Hibiscus sabdariffa L.) on arterial hypertension: a systematic review and meta-analysis of randomized controlled trials.J Hypertens. 2015; 33:1119–1127. doi: 10.1097/HJH.0000000000000585.CrossrefMedlineGoogle Scholar - 282.
Aziz Z, Wong SY, Chong NJ . Effects of Hibiscus sabdariffa L. on serum lipids: a systematic review and meta-analysis.J Ethnopharmacol. 2013; 150:442–450. doi: 10.1016/j.jep.2013.09.042.CrossrefMedlineGoogle Scholar - 283.
Onakpoya I, Spencer E, Heneghan C, Thompson M . The effect of green tea on blood pressure and lipid profile: a systematic review and meta-analysis of randomized clinical trials.Nutr Metab Cardiovasc Dis. 2014; 24:823–836. doi: 10.1016/j.numecd.2014.01.016.CrossrefMedlineGoogle Scholar - 284.
Wang D, Chen C, Wang Y, Liu J, Lin R . Effect of black tea consumption on blood cholesterol: a meta-analysis of 15 randomized controlled trials.PLoS One. 2014; 9:e107711. doi: 10.1371/journal.pone.0107711.CrossrefMedlineGoogle Scholar - 285.
Laonigro I, Correale M, Di Biase M, Altomare E . Alcohol abuse and heart failure.Eur J Heart Fail. 2009; 11:453–462. doi: 10.1093/eurjhf/hfp037.CrossrefMedlineGoogle Scholar - 286.
Larsson SC, Drca N, Wolk A . Alcohol consumption and risk of atrial fibrillation: a prospective study and dose-response meta-analysis.J Am Coll Cardiol. 2014; 64:281–289. doi: 10.1016/j.jacc.2014.03.048.CrossrefMedlineGoogle Scholar - 287.
Núñez-Córdoba JM, Valencia-Serrano F, Toledo E, Alonso A, Martínez-González MA . The Mediterranean diet and incidence of hypertension: the Seguimiento Universidad de Navarra (SUN) Study.Am J Epidemiol. 2009; 169:339–346. doi: 10.1093/aje/kwn335.CrossrefMedlineGoogle Scholar - 288.
Baliunas DO, Taylor BJ, Irving H, Roerecke M, Patra J, Mohapatra S, Rehm J . Alcohol as a risk factor for type 2 diabetes: a systematic review and meta-analysis.Diabetes Care. 2009; 32:2123–2132. doi: 10.2337/dc09-0227.CrossrefMedlineGoogle Scholar - 289.
Ronksley PE, Brien SE, Turner BJ, Mukamal KJ, Ghali WA . Association of alcohol consumption with selected cardiovascular disease outcomes: a systematic review and meta-analysis.BMJ. 2011; 342:d671.CrossrefMedlineGoogle Scholar - 290.
Willcox BJ, Willcox DC, Todoriki H, Fujiyoshi A, Yano K, He Q, Curb JD, Suzuki M . Caloric restriction, the traditional Okinawan diet, and healthy aging: the diet of the world’s longest-lived people and its potential impact on morbidity and life span.Ann N Y Acad Sci. 2007; 1114:434–455. doi: 10.1196/annals.1396.037.CrossrefMedlineGoogle Scholar - 291.
Brien SE, Ronksley PE, Turner BJ, Mukamal KJ, Ghali WA . Effect of alcohol consumption on biological markers associated with risk of coronary heart disease: systematic review and meta-analysis of interventional studies.BMJ. 2011; 342:d636.CrossrefMedlineGoogle Scholar - 292.
Arranz S, Chiva-Blanch G, Valderas-Martínez P, Medina-Remón A, Lamuela-Raventós RM, Estruch R . Wine, beer, alcohol and polyphenols on cardiovascular disease and cancer.Nutrients. 2012; 4:759–781. doi: 10.3390/nu4070759.CrossrefMedlineGoogle Scholar - 293.
Bagnardi V, Zatonski W, Scotti L, La Vecchia C, Corrao G . Does drinking pattern modify the effect of alcohol on the risk of coronary heart disease? Evidence from a meta-analysis.J Epidemiol Community Health. 2008; 62:615–619. doi: 10.1136/jech.2007.065607.CrossrefMedlineGoogle Scholar - 294.
Danaei G, Ding EL, Mozaffarian D, Taylor B, Rehm J, Murray CJ, Ezzati M . The preventable causes of death in the United States: comparative risk assessment of dietary, lifestyle, and metabolic risk factors.PLoS Med. 2009; 6:e1000058. doi: 10.1371/journal.pmed.1000058.CrossrefMedlineGoogle Scholar - 295.
Shrime MG, Bauer SR, McDonald AC, Chowdhury NH, Coltart CE, Ding EL . Flavonoid-rich cocoa consumption affects multiple cardiovascular risk factors in a meta-analysis of short-term studies.J Nutr. 2011; 141:1982–1988. doi: 10.3945/jn.111.145482.CrossrefMedlineGoogle Scholar - 296.
Corti R, Flammer AJ, Hollenberg NK, Lüscher TF . Cocoa and cardiovascular health.Circulation. 2009; 119:1433–1441. doi: 10.1161/CIRCULATIONAHA.108.827022.LinkGoogle Scholar - 297.
Hooper L, Kay C, Abdelhamid A, Kroon PA, Cohn JS, Rimm EB, Cassidy A . Effects of chocolate, cocoa, and flavan-3-ols on cardiovascular health: a systematic review and meta-analysis of randomized trials.Am J Clin Nutr. 2012; 95:740–751. doi: 10.3945/ajcn.111.023457.CrossrefMedlineGoogle Scholar - 298.
Taubert D, Roesen R, Lehmann C, Jung N, Schömig E . Effects of low habitual cocoa intake on blood pressure and bioactive nitric oxide: a randomized controlled trial.JAMA. 2007; 298:49–60. doi: 10.1001/jama.298.1.49.CrossrefMedlineGoogle Scholar - 299.
Perez-Vizcaino F, Duarte J . Flavonols and cardiovascular disease.Mol Aspects Med. 2010; 31:478–494. doi: 10.1016/j.mam.2010.09.002.CrossrefMedlineGoogle Scholar - 300.
Buitrago-Lopez A, Sanderson J, Johnson L, Warnakula S, Wood A, Di Angelantonio E, Franco OH . Chocolate consumption and cardiometabolic disorders: systematic review and meta-analysis.BMJ. 2011; 343:d4488.CrossrefMedlineGoogle Scholar - 301.
Basu A, Lyons TJ . Strawberries, blueberries, and cranberries in the metabolic syndrome: clinical perspectives.J Agric Food Chem. 2012; 60:5687–5692. doi: 10.1021/jf203488k.CrossrefMedlineGoogle Scholar - 302.
Brown IJ, Tzoulaki I, Candeias V, Elliott P . Salt intakes around the world: implications for public health.Int J Epidemiol. 2009; 38:791–813. doi: 10.1093/ije/dyp139.CrossrefMedlineGoogle Scholar - 303.
Powles J, Fahimi S, Micha R, Khatibzadeh S, Shi P, Ezzati M, Engell RE, Lim S, Danaei G, Mozaffarian D , On behalf of the Global Burden of Diseases Nutrition and Chronic Diseases Expert Group (NutriCoDE). Global, regional, and national sodium intakes in 1990 and 2010: a systematic analysis of 24 h urinary sodium excretion and dietary surveys worldwide.BMJ Open. 2013; 3:e003733CrossrefMedlineGoogle Scholar - 304.
Mozaffarian D, Fahimi S, Singh GM, Micha R, Khatibzadeh S, Engell RE, Lim S, Danaei G, Ezzati M, Powles J ; Global Burden of Diseases Nutrition and Chronic Diseases Expert Group. Global sodium consumption and death from cardiovascular causes.N Engl J Med. 2014; 371:624–634. doi: 10.1056/NEJMoa1304127.CrossrefMedlineGoogle Scholar - 305.
Aburto NJ, Ziolkovska A, Hooper L, Elliott P, Cappuccio FP, Meerpohl JJ . Effect of lower sodium intake on health: systematic review and meta-analyses.BMJ. 2013; 346:f1326.CrossrefMedlineGoogle Scholar - 306.
Poggio R, Gutierrez L, Matta MG, Elorriaga N, Irazola V, Rubinstein A . Daily sodium consumption and CVD mortality in the general population: systematic review and meta-analysis of prospective studies.Public Health Nutr. 2015; 18:695–704. doi: 10.1017/S1368980014000949.CrossrefMedlineGoogle Scholar - 307.
Li XY, Cai XL, Bian PD, Hu LR . High salt intake and stroke: meta-analysis of the epidemiologic evidence.CNS Neurosci Ther. 2012; 18:691–701. doi: 10.1111/j.1755-5949.2012.00355.x.CrossrefMedlineGoogle Scholar - 308. Institute of Medicine. Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Washington, DC: National Academies Press; 2010.Google Scholar
- 309.
Sacks FM, Campos H . Dietary therapy in hypertension.N Engl J Med. 2010; 362:2102–2112. doi: 10.1056/NEJMct0911013.CrossrefMedlineGoogle Scholar - 310.
Susic D, Frohlich ED . Salt consumption and cardiovascular, renal, and hypertensive diseases: clinical and mechanistic aspects.Curr Opin Lipidol. 2012; 23:11–16. doi: 10.1097/MOL.0b013e32834d9c52.CrossrefMedlineGoogle Scholar - 311.
O’Donnell M, Mente A, Rangarajan S, McQueen MJ, Wang X, Liu L, Yan H, Lee SF, Mony P, Devanath A, Rosengren A, Lopez-Jaramillo P, Diaz R, Avezum A, Lanas F, Yusoff K, Iqbal R, Ilow R, Mohammadifard N, Gulec S, Yusufali AH, Kruger L, Yusuf R, Chifamba J, Kabali C, Dagenais G, Lear SA, Teo K, Yusuf S ; PURE Investigators. Urinary sodium and potassium excretion, mortality, and cardiovascular events.N Engl J Med. 2014; 371:612–623. doi: 10.1056/NEJMoa1311889.CrossrefMedlineGoogle Scholar - 312.
Kalogeropoulos AP, Georgiopoulou VV, Murphy RA, Newman AB, Bauer DC, Harris TB, Yang Z, Applegate WB, Kritchevsky SB . Dietary sodium content, mortality, and risk for cardiovascular events in older adults: the Health, Aging, and Body Composition (Health ABC) Study.JAMA Intern Med. 2015; 175:410–419. doi: 10.1001/jamainternmed.2014.6278.CrossrefMedlineGoogle Scholar - 313.
Whelton PK, Appel LJ, Sacco RL, Anderson CA, Antman EM, Campbell N, Dunbar SB, Frohlich ED, Hall JE, Jessup M, Labarthe DR, MacGregor GA, Sacks FM, Stamler J, Vafiadis DK, Van Horn LV . Sodium, blood pressure, and cardiovascular disease: further evidence supporting the American Heart Association sodium reduction recommendations.Circulation. 2012; 126:2880–2889. doi: 10.1161/CIR.0b013e318279acbf.LinkGoogle Scholar - 314.
Strom BL, Anderson CA, Ix JH . Sodium reduction in populations: Insights from the Institute of Medicine Committee.JAMA. 2013:1–2Google Scholar - 315.
Cobb LK, Anderson CA, Elliott P, Hu FB, Liu K, Neaton JD, Whelton PK, Woodward M, Appel LJ ; American Heart Association Council on Lifestyle and Metabolic Health. Methodological issues in cohort studies that relate sodium intake to cardiovascular disease outcomes: a science advisory from the American Heart Association.Circulation. 2014; 129:1173–1186. doi: 10.1161/CIR.0000000000000015.LinkGoogle Scholar - 316.
Guenther PM, Lyon JM, Appel LJ . Modeling dietary patterns to assess sodium recommendations for nutrient adequacy.Am J Clin Nutr. 2013; 97:842–847. doi: 10.3945/ajcn.112.047779.CrossrefMedlineGoogle Scholar - 317.
Cook NR, Appel LJ, Whelton PK . Lower levels of sodium intake and reduced cardiovascular risk.Circulation. 2014; 129:981–989. doi: 10.1161/CIRCULATIONAHA.113.006032.LinkGoogle Scholar - 318. INTERSALT Cooperative Research Group. Intersalt: an international study of electrolyte excretion and blood pressure. Results for 24 hour urinary sodium and potassium excretion. Intersalt Cooperative Research Group.BMJ1988; 297:319–328CrossrefMedlineGoogle Scholar
- 319.
Sacks FM, Svetkey LP, Vollmer WM, Appel LJ, Bray GA, Harsha D, Obarzanek E, Conlin PR, Miller ER, Simons-Morton DG, Karanja N, Lin PH ; DASH-Sodium Collaborative Research Group. Effects on blood pressure of reduced dietary sodium and the Dietary Approaches to Stop Hypertension (DASH) diet. DASH-Sodium Collaborative Research Group.N Engl J Med. 2001; 344:3–10. doi: 10.1056/NEJM200101043440101.CrossrefMedlineGoogle Scholar - 320. National Institute for Health and Clinical Excellence. Prevention of Cardiovascular Disease at Population Level (NICE Public Health Guidance 25). London: National Institute for Health and Clinical Excellence; 2010.Google Scholar
- 321. Dietary Guidelines for Americans, 2010. Washington, DC:US Department of Agriculture, US Department of Health and Human Services;2010Google Scholar
- 322. World Health Organization. WHO Guideline: Sodium Intake For Adults and Children. Geneva, Switzerland: WHO; 2012.Google Scholar
- 323. Scientific Advisory Committee on Nutrition. Salt and Health. London: The Stationery Office; 2003.Google Scholar
- 324.
Graudal NA, Hubeck-Graudal T, Jurgens G . Effects of low sodium diet versus high sodium diet on blood pressure, renin, aldosterone, catecholamines, cholesterol, and triglyceride.Cochrane Database Syst Rev. 2011:CD004022.MedlineGoogle Scholar - 325.
Binia A, Jaeger J, Hu Y, Singh A, Zimmermann D . Daily potassium intake and sodium-to-potassium ratio in the reduction of blood pressure: a meta-analysis of randomized controlled trials.J Hypertens. 2015; 33:1509–1520. doi: 10.1097/HJH.0000000000000611.CrossrefMedlineGoogle Scholar - 326.
D’Elia L, Barba G, Cappuccio FP, Strazzullo P . Potassium intake, stroke, and cardiovascular disease a meta-analysis of prospective studies.J Am Coll Cardiol. 2011; 57:1210–1219. doi: 10.1016/j.jacc.2010.09.070.CrossrefMedlineGoogle Scholar - 327.
Sacks FM, Svetkey LP, Vollmer WM, Appel LJ, Bray GA, Harsha D, Obarzanek E, Conlin PR, Miller ER, Simons-Morton DG, Karanja N, Lin PH ; DASH-Sodium Collaborative Research Group. Effects on blood pressure of reduced dietary sodium and the Dietary Approaches to Stop Hypertension (DASH) diet. DASH-Sodium Collaborative Research Group.N Engl J Med. 2001; 344:3–10. doi: 10.1056/NEJM200101043440101.CrossrefMedlineGoogle Scholar - 328.
Bolland MJ, Grey A, Avenell A, Gamble GD, Reid IR . Calcium supplements with or without vitamin D and risk of cardiovascular events: reanalysis of the Women’s Health Initiative limited access dataset and meta-analysis.BMJ. 2011; 342:d2040.CrossrefMedlineGoogle Scholar - 329.
Mao PJ, Zhang C, Tang L, Xian YQ, Li YS, Wang WD, Zhu XH, Qiu HL, He J, Zhou YH . Effect of calcium or vitamin D supplementation on vascular outcomes: a meta-analysis of randomized controlled trials.Int J Cardiol. 2013; 169:106–111. doi: 10.1016/j.ijcard.2013.08.055.CrossrefMedlineGoogle Scholar - 330.
Del Gobbo LC, Imamura F, Wu JH, de Oliveira Otto MC, Chiuve SE, Mozaffarian D . Circulating and dietary magnesium and risk of cardiovascular disease: a systematic review and meta-analysis of prospective studies.Am J Clin Nutr. 2013; 98:160–173. doi: 10.3945/ajcn.112.053132.CrossrefMedlineGoogle Scholar - 331.
Mente A, de Koning L, Shannon HS, Anand SS . A systematic review of the evidence supporting a causal link between dietary factors and coronary heart disease.Arch Intern Med. 2009; 169:659–669. doi: 10.1001/archinternmed.2009.38.CrossrefMedlineGoogle Scholar - 332.
Ye Y, Li J, Yuan Z . Effect of antioxidant vitamin supplementation on cardiovascular outcomes: a meta-analysis of randomized controlled trials.PLoS One. 2013; 8:e56803. doi: 10.1371/journal.pone.0056803.CrossrefMedlineGoogle Scholar - 333. Proposed Changes to the Nutrition Facts Label.Silver Spring, MD:US Food and Drug Administration; 2015Google Scholar
- 334.
Ludwig DS . Examining the health effects of fructose.JAMA. 2013; 310:33–34. doi: 10.1001/jama.2013.6562.CrossrefMedlineGoogle Scholar - 335. Institute of Medicine. Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids (Macronutrients). Washington, DC: The National Academies Press; 2002.Google Scholar
- 336.
Mozaffarian D, Ludwig DS . The 2015 US Dietary Guidelines: lifting the ban on total dietary fat.JAMA. 2015; 313:2421–2422. doi: 10.1001/jama.2015.5941.CrossrefMedlineGoogle Scholar - 337. Gallup. Americans Still Avoid Fat More Than Carbs.2015. Accessed January 10, 2015. http://www.gallup.com/poll/174176/americans-avoid-fat-carbs.aspx.Google Scholar
- 338.
Malik VS, Chiuve SE, Campos H, Rimm EB, Mozaffarian D, Hu FB, Sun Q . Circulating very-long-chain saturated fatty acids and incident coronary heart disease in US men and women.Circulation. 2015; 132:260–268. doi: 10.1161/CIRCULATIONAHA.114.014911.LinkGoogle Scholar - 339.
Lemaitre RN, Fretts AM, Sitlani CM, Biggs ML, Mukamal K, King IB, Song X, Djoussé L, Siscovick DS, McKnight B, Sotoodehnia N, Kizer JR, Mozaffarian D . Plasma phospholipid very-long-chain saturated fatty acids and incident diabetes in older adults: the Cardiovascular Health Study.Am J Clin Nutr. 2015; 101:1047–1054. doi: 10.3945/ajcn.114.101857.CrossrefMedlineGoogle Scholar - 340.
Mozaffarian D . Diverging global trends in heart disease and type 2 diabetes: the role of carbohydrates and saturated fats.Lancet Diabetes Endocrinol. 2015; 3:586–588.CrossrefMedlineGoogle Scholar - 341.
Mensink RP, Zock PL, Kester AD, Katan MB . Effects of dietary fatty acids and carbohydrates on the ratio of serum total to HDL cholesterol and on serum lipids and apolipoproteins: a meta-analysis of 60 controlled trials.Am J Clin Nutr. 2003; 77:1146–1155.CrossrefMedlineGoogle Scholar - 342.
Nordestgaard BG, Chapman MJ, Ray K, Borén J, Andreotti F, Watts GF, Ginsberg H, Amarenco P, Catapano A, Descamps OS, Fisher E, Kovanen PT, Kuivenhoven JA, Lesnik P, Masana L, Reiner Z, Taskinen MR, Tokgözoglu L, Tybjærg-Hansen A ; European Atherosclerosis Society Consensus Panel. Lipoprotein(a) as a cardiovascular risk factor: current status.Eur Heart J. 2010; 31:2844–2853. doi: 10.1093/eurheartj/ehq386.CrossrefMedlineGoogle Scholar - 343.
Berglund L, Lefevre M, Ginsberg HN, Kris-Etherton PM, Elmer PJ, Stewart PW, Ershow A, Pearson TA, Dennis BH, Roheim PS, Ramakrishnan R, Reed R, Stewart K, Phillips KM ; DELTA Investigators. Comparison of monounsaturated fat with carbohydrates as a replacement for saturated fat in subjects with a high metabolic risk profile: studies in the fasting and postprandial states.Am J Clin Nutr. 2007; 86:1611–1620.CrossrefMedlineGoogle Scholar - 344.
Siri-Tarino PW, Sun Q, Hu FB, Krauss RM . Meta-analysis of prospective cohort studies evaluating the association of saturated fat with cardiovascular disease.Am J Clin Nutr. 2010; 91:502–509.CrossrefMedlineGoogle Scholar - 345.
Moran B, Harvard T. H . Is butter really back? Clarying the facts on fat.Chan School of Public Health Magazine. 2014. http://www.hsph.harvard.edu/magazine-features/is-butter-really-back/. Accessed May 29, 2015.Google Scholar - 346.
Micha R, Khatibzadeh S, Shi P, Fahimi S, Lim S, Andrews KG, Engell RE, Powles J, Ezzati M, Mozaffarian D , on behalf of the Global Burden of Diseases Nutrition and Chronic Diseases Expert Group (NutriCoDE). Global, regional, and national consumption levels of dietary fats and oils in 1990 and 2010: a systematic analysis including 266 country-specific nutrition surveys.BMJ. 2014; 348:g2272.CrossrefMedlineGoogle Scholar - 347.
Bandosz P, O’Flaherty M, Rutkowski M, Kypridemos C, Guzman-Castillo M, Gillespie DO, Solnica B, Pencina MJ, Wyrzykowski B, Capewell S, Zdrojewski T . A victory for statins or a defeat for diet policies? Cholesterol falls in Poland in the past decade: a modeling study.Int J Cardiol. 2015; 185:313–319. doi: 10.1016/j.ijcard.2015.03.079.CrossrefMedlineGoogle Scholar - 348.
Kypridemos C, Bandosz P, Hickey GL, Guzman-Castillo M, Allen K, Buchan I, Capewell S, O’Flaherty M . Quantifying the contribution of statins to the decline in population mean cholesterol by socioeconomic group in England 1991 - 2012: a modelling study.PLoS One. 2015; 10:e0123112.CrossrefMedlineGoogle Scholar - 349.
Mozaffarian D, Micha R, Wallace S . Effects on coronary heart disease of increasing polyunsaturated fat in place of saturated fat: a systematic review and meta-analysis of randomized controlled trials.PLoS Med. 2010; 7:e1000252. doi: 10.1371/journal.pmed.1000252.CrossrefMedlineGoogle Scholar - 350.
Farvid MS, Ding M, Pan A, Sun Q, Chiuve SE, Steffen LM, Willett WC, Hu FB . Dietary linoleic acid and risk of coronary heart disease: a systematic review and meta-analysis of prospective cohort studies.Circulation. 2014; 130:1568–1578. doi: 10.1161/CIRCULATIONAHA.114.010236.LinkGoogle Scholar - 351.
Jakobsen MU, Dethlefsen C, Joensen AM, Stegger J, Tjønneland A, Schmidt EB, Overvad K . Intake of carbohydrates compared with intake of saturated fatty acids and risk of myocardial infarction: importance of the glycemic index.Am J Clin Nutr. 2010; 91:1764–1768. doi: 10.3945/ajcn.2009.29099.CrossrefMedlineGoogle Scholar - 352.
Schwingshackl L, Hoffmann G . Monounsaturated fatty acids, olive oil and health status: a systematic review and meta-analysis of cohort studies.Lipids Health Dis. 2014; 13:154. doi: 10.1186/1476-511X-13-154.CrossrefMedlineGoogle Scholar - 353.
Schwingshackl L, Strasser B, Hoffmann G . Effects of monounsaturated fatty acids on cardiovascular risk factors: a systematic review and meta-analysis.Ann Nutr Metab. 2011; 59:176–186. doi: 10.1159/000334071.CrossrefMedlineGoogle Scholar - 354.
Schwingshackl L, Strasser B, Hoffmann G . Effects of monounsaturated fatty acids on glycaemic control in patients with abnormal glucose metabolism: a systematic review and meta-analysis.Ann Nutr Metab. 2011; 58:290–296. doi: 10.1159/000331214.CrossrefMedlineGoogle Scholar - 355.
Micha R, Mozaffarian D . Saturated fat and cardiometabolic risk factors, coronary heart disease, stroke, and diabetes: a fresh look at the evidence.Lipids. 2010; 45:893–905. doi: 10.1007/s11745-010-3393-4.CrossrefMedlineGoogle Scholar - 356.
Degirolamo C, Shelness GS, Rudel LL . LDL cholesteryl oleate as a predictor for atherosclerosis: evidence from human and animal studies on dietary fat.J Lipid Res. 2009; 50(suppl):S434–S439. doi: 10.1194/jlr.R800076-JLR200.CrossrefMedlineGoogle Scholar - 357.
Jones PJ, MacKay DS, Senanayake VK, Pu S, Jenkins DJ, Connelly PW, Lamarche B, Couture P, Kris-Etherton PM, West SG, Liu X, Fleming JA, Hantgan RR, Rudel LL . High-oleic canola oil consumption enriches LDL particle cholesteryl oleate content and reduces LDL proteoglycan binding in humans.Atherosclerosis. 2015; 238:231–238. doi: 10.1016/j.atherosclerosis.2014.12.010.CrossrefMedlineGoogle Scholar - 358.
Lands WE . Dietary fat and health: the evidence and the politics of prevention: careful use of dietary fats can improve life and prevent disease.Ann N Y Acad Sci. 2005; 1055:179–192. doi: 10.1196/annals.1323.028.CrossrefMedlineGoogle Scholar - 359.
Pischon T, Hankinson SE, Hotamisligil GS, Rifai N, Willett WC, Rimm EB . Habitual dietary intake of n-3 and n-6 fatty acids in relation to inflammatory markers among US men and women.Circulation. 2003; 108:155–160. doi: 10.1161/01.CIR.0000079224.46084.C2.LinkGoogle Scholar - 360.
Poudel-Tandukar K, Nanri A, Matsushita Y, Sasaki S, Ohta M, Sato M, Mizoue T . Dietary intakes of alpha-linolenic and linoleic acids are inversely associated with serum C-reactive protein levels among Japanese men.Nutr Res. 2009; 29:363–370. doi: 10.1016/j.nutres.2009.05.012.CrossrefMedlineGoogle Scholar - 361.
Kalogeropoulos N, Panagiotakos DB, Pitsavos C, Chrysohoou C, Rousinou G, Toutouza M, Stefanadis C . Unsaturated fatty acids are inversely associated and n-6/n-3 ratios are positively related to inflammation and coagulation markers in plasma of apparently healthy adults.Clin Chim Acta. 2010; 411:584–591. doi: 10.1016/j.cca.2010.01.023.CrossrefMedlineGoogle Scholar - 362.
Johnson GH, Fritsche K . Effect of dietary linoleic acid on markers of inflammation in healthy persons: a systematic review of randomized controlled trials.J Acad Nutr Diet. 2012; 112:1029–1041, 1041.e1. doi: 10.1016/j.jand.2012.03.029.CrossrefMedlineGoogle Scholar - 363.
Keys A, Menotti A, Karvonen MJ, Aravanis C, Blackburn H, Buzina R, Djordjevic BS, Dontas AS, Fidanza F, Keys MH . The diet and 15-year death rate in the seven countries study.Am J Epidemiol. 1986; 124:903–915.CrossrefMedlineGoogle Scholar - 364.
Harris WS, Mozaffarian D, Rimm E, Kris-Etherton P, Rudel LL, Appel LJ, Engler MM, Engler MB, Sacks F . Omega-6 fatty acids and risk for cardiovascular disease: a science advisory from the American Heart Association Nutrition Subcommittee of the Council on Nutrition, Physical Activity, and Metabolism; Council on Cardiovascular Nursing; and Council on Epidemiology and Prevention.Circulation. 2009; 119:902–907. doi: 10.1161/CIRCULATIONAHA.108.191627.LinkGoogle Scholar - 365.
Jebb SA, Lovegrove JA, Griffin BA, Frost GS, Moore CS, Chatfield MD, Bluck LJ, Williams CM, Sanders TA ; RISCK Study Group. Effect of changing the amount and type of fat and carbohydrate on insulin sensitivity and cardiovascular risk: the RISCK (Reading, Imperial, Surrey, Cambridge, and Kings) trial.Am J Clin Nutr. 2010; 92:748–758. doi: 10.3945/ajcn.2009.29096.CrossrefMedlineGoogle Scholar - 366.
Bjermo H, Iggman D, Kullberg J, Dahlman I, Johansson L, Persson L, Berglund J, Pulkki K, Basu S, Uusitupa M, Rudling M, Arner P, Cederholm T, Ahlström H, Risérus U . Effects of n-6 PUFAs compared with SFAs on liver fat, lipoproteins, and inflammation in abdominal obesity: a randomized controlled trial.Am J Clin Nutr. 2012; 95:1003–1012. doi: 10.3945/ajcn.111.030114.CrossrefMedlineGoogle Scholar - 367.
Rosqvist F, Iggman D, Kullberg J, Cedernaes J, Johansson HE, Larsson A, Johansson L, Ahlström H, Arner P, Dahlman I, Risérus U . Overfeeding polyunsaturated and saturated fat causes distinct effects on liver and visceral fat accumulation in humans.Diabetes. 2014; 63:2356–2368. doi: 10.2337/db13-1622.CrossrefMedlineGoogle Scholar - 368.
Serhan CN, Chiang N, Van Dyke TE . Resolving inflammation: dual anti-inflammatory and pro-resolution lipid mediators.Nat Rev Immunol. 2008; 8:349–361. doi: 10.1038/nri2294.CrossrefMedlineGoogle Scholar - 369.
Spite M, Clària J, Serhan CN . Resolvins, specialized proresolving lipid mediators, and their potential roles in metabolic diseases.Cell Metab. 2014; 19:21–36. doi: 10.1016/j.cmet.2013.10.006.CrossrefMedlineGoogle Scholar - 370. Joint FAO/WHO Expert Consultation on the Risks and Benefits of Fish Consumption. Executive Summary.2010. ftp://ftp.fao.org/FI/DOCUMENT/risk_consumption/executive_summary.pdf. Accessed May 21, 2010.Google Scholar
- 371.
Geleijnse JM, de Goede J, Brouwer IA . Alpha-linolenic acid: is it essential to cardiovascular health?Curr Atheroscler Rep. 2010; 12:359–367. doi: 10.1007/s11883-010-0137-0.CrossrefMedlineGoogle Scholar - 372.
Pan A, Chen M, Chowdhury R, Wu JH, Sun Q, Campos H, Mozaffarian D, Hu FB . α-Linolenic acid and risk of cardiovascular disease: a systematic review and meta-analysis.Am J Clin Nutr. 2012; 96:1262–1273. doi: 10.3945/ajcn.112.044040.CrossrefMedlineGoogle Scholar - 373.
Kromhout D, Giltay EJ, Geleijnse JM ; Alpha Omega Trial Group. n-3 fatty acids and cardiovascular events after myocardial infarction.N Engl J Med. 2010; 363:2015–2026. doi: 10.1056/NEJMoa1003603.CrossrefMedlineGoogle Scholar - 374.
Griffin BA . How relevant is the ratio of dietary n-6 to n-3 polyunsaturated fatty acids to cardiovascular disease risk? Evidence from the OPTILIP study.Curr Opin Lipidol. 2008; 19:57–62. doi: 10.1097/MOL.0b013e3282f2e2a8.CrossrefMedlineGoogle Scholar - 375.
Mozaffarian D, Aro A, Willett WC . Health effects of trans-fatty acids: experimental and observational evidence.Eur J Clin Nutr. 2009; 63(suppl 2):S5–S21. doi: 10.1038/sj.ejcn.1602973.CrossrefMedlineGoogle Scholar - 376.
Mozaffarian D, Katan MB, Ascherio A, Stampfer MJ, Willett WC . Trans fatty acids and cardiovascular disease.N Engl J Med. 2006; 354:1601–1613. doi: 10.1056/NEJMra054035.CrossrefMedlineGoogle Scholar - 377.
Howard BV, Manson JE, Stefanick ML, Beresford SA, Frank G, Jones B, Rodabough RJ, Snetselaar L, Thomson C, Tinker L, Vitolins M, Prentice R . Low-fat dietary pattern and weight change over 7 years: the Women’s Health Initiative Dietary Modification Trial.JAMA. 2006; 295:39–49. doi: 10.1001/jama.295.1.39.CrossrefMedlineGoogle Scholar - 378.
Micha R, Mozaffarian D . Trans fatty acids: effects on metabolic syndrome, heart disease and diabetes.Nat Rev Endocrinol. 2009; 5:335–344. doi: 10.1038/nrendo.2009.79.CrossrefMedlineGoogle Scholar - 379.
Wallace SK, Mozaffarian D . Trans-fatty acids and nonlipid risk factors.Curr Atheroscler Rep. 2009; 11:423–433.CrossrefMedlineGoogle Scholar - 380.
Lambelet P, Grandgirard A, Gregoire S, Juaneda P, Sebedio JL, Bertoli C . Formation of modified fatty acids and oxyphytosterols during refining of low erucic acid rapeseed oil.J Agric Food Chem. 2003; 51:4284–4290. doi: 10.1021/jf030091u.CrossrefMedlineGoogle Scholar - 381.
Velasco J, Marmesat S, Bordeaux O, Márquez-Ruiz G, Dobarganes C . Formation and evolution of monoepoxy fatty acids in thermoxidized olive and sunflower oils and quantitation in used frying oils from restaurants and fried-food outlets.J Agric Food Chem. 2004; 52:4438–4443. doi: 10.1021/jf030753f.CrossrefMedlineGoogle Scholar - 382. United Nations. Draft Outcome Document of the High-level Meeting on the Prevention and Control of Non-communicable Diseases. 2011.Accessed October 11, 2015. http://www.ncdalliance.org/sites/default/files/resource_files/UN%20High-Level%20Summit%20Zero%20Draft.pdf.Google Scholar
- 383.
Frieden TR, Berwick DM . The “Million Hearts” initiative–preventing heart attacks and strokes.N Engl J Med. 2011; 365:e27. doi: 10.1056/NEJMp1110421.CrossrefMedlineGoogle Scholar - 384. US Food and Drug Administration. FDA Cuts Trans Fat in Processed Foods.2015. http://www.fda.gov/ForConsumers/ConsumerUpdates/ucm372915.htm. Accessed July 16, 2015.Google Scholar
- 385.
Schwingshackl L, Hoffmann G . Long-term effects of low-fat diets either low or high in protein on cardiovascular and metabolic risk factors: a systematic review and meta-analysis.Nutr J. 2013; 12:48. doi: 10.1186/1475-2891-12-48.CrossrefMedlineGoogle Scholar - 386.
Nilsson LM, Winkvist A, Eliasson M, Jansson JH, Hallmans G, Johansson I, Lindahl B, Lenner P, Van Guelpen B . Low-carbohydrate, high-protein score and mortality in a northern Swedish population-based cohort.Eur J Clin Nutr. 2012; 66:694–700. doi: 10.1038/ejcn.2012.9.CrossrefMedlineGoogle Scholar - 387.
Brug J . Determinants of healthy eating: motivation, abilities and environmental opportunities.Fam Pract. 2008; 25(suppl 1):i50–i55. doi: 10.1093/fampra/cmn063.CrossrefMedlineGoogle Scholar - 388.
van’t Riet J, Sijtsema SJ, Dagevos H, De Bruijn GJ . The importance of habits in eating behaviour. An overview and recommendations for future research.Appetite. 2011; 57:585–596. doi: 10.1016/j.appet.2011.07.010.CrossrefMedlineGoogle Scholar - 389.
Patel SR, Hu FB . Short sleep duration and weight gain: a systematic review.Obesity (Silver Spring). 2008; 16:643–653. doi: 10.1038/oby.2007.118.CrossrefMedlineGoogle Scholar - 390.
Brug J, Kremers SP, Lenthe Fv, Ball K, Crawford D . Environmental determinants of healthy eating: in need of theory and evidence.Proc Nutr Soc. 2008; 67:307–316. doi: 10.1017/S0029665108008616.CrossrefMedlineGoogle Scholar - 391.
Nugent R . Bringing Agriculture to the Table: How Agriculture and Food Can Play a Role in Preventing Chronic Disease. The Chicago Council on Global Affairs.2011. Accessed October 11, 2015. http://www.thechicagocouncil.org/publication/bringing-agriculture-table-how-agriculture-and-food-policy-can-play-role-preventing.Google Scholar - 392.
Powles J, Fahimi S, Micha R, Khatibzadeh S, Shi P, Ezzati M, Engell RE, Lim S, Danaei G, Mozaffarian D , On behalf of the Global Burden of Diseases Nutrition and Chronic Diseases Expert Group (NutriCoDE). Global, regional, and national sodium intakes in 1990 and 2010: a systematic analysis of 24-hour urinary sodium excretion and dietary surveys worldwide.BMJ Open. 2013; 3:e003733.CrossrefMedlineGoogle Scholar - 393.
Micha R, Khatibzadeh S, Shi P, Andrews KG, Engell RE, Mozaffarian D . Global, regional and national consumption of major food groups in 1990 and 2010: a systematic analysis including 266 country-specific nutrition surveys worldwide.BMJ open. 2015; 5:e008705CrossrefMedlineGoogle Scholar - 394.
Singh GM, Micha R, Khatibzadeh S, Shi P, Lim S, Andrews KG, Engell RE, Ezzati M, Mozaffarian D ; Global Burden of Diseases Nutrition and Chronic Diseases Expert Group (NutriCoDE). Global, regional, and national consumption of sugar-sweetened beverages, fruit juices, and milk: a systematic assessment of beverage intake in 187 countries.PLoS One. 2015; 10:e0124845. doi: 10.1371/journal.pone.0124845.CrossrefMedlineGoogle Scholar - 395.
Deckersbach T, Das SK, Urban LE, Salinardi T, Batra P, Rodman AM, Arulpragasam AR, Dougherty DD, Roberts SB . Pilot randomized trial demonstrating reversal of obesity-related abnormalities in reward system responsivity to food cues with a behavioral intervention.Nutr Diabetes. 2014; 4:e129. doi: 10.1038/nutd.2014.26.CrossrefMedlineGoogle Scholar - 396.
Mozaffarian D . Salt, sugar, and fat or branding, marketing, and promotion?The Lancet. 2013; 382:1322–1323.CrossrefGoogle Scholar - 397.
Mozaffarian D, Wilson PW, Kannel WB . Beyond established and novel risk factors: lifestyle risk factors for cardiovascular disease.Circulation. 2008; 117:3031–3038. doi: 10.1161/CIRCULATIONAHA.107.738732.LinkGoogle Scholar - 398.
Bodenheimer T . Helping patients improve their health-related behaviors: what system changes do we need?Dis Manag. 2005; 8:319–330. doi: 10.1089/dis.2005.8.319.CrossrefMedlineGoogle Scholar - 399.
Simpson LA, Cooper J . Paying for obesity: a changing landscape.Pediatrics. 2009; 123(suppl 5):S301–S307. doi: 10.1542/peds.2008-2780I.CrossrefMedlineGoogle Scholar - 400.
Long MW, Tobias DK, Cradock AL, Batchelder H, Gortmaker SL . Systematic review and meta-analysis of the impact of restaurant menu calorie labeling.Am J Public Health. 2015; 105:e11–e24. doi: 10.2105/AJPH.2015.302570.CrossrefMedlineGoogle Scholar - 401.
Shangguan S, Smith J, Ma W, Tanz L, Afshin A, Mozaffarian D . Effectiveness of point-of-purchase labeling on dietary behaviors and nutrient contents of foods: A systemic review and meta-analysis (abstract).Circulation. 2015; 131:AP323–AP323.LinkGoogle Scholar - 402.
Ford ES, Ajani UA, Croft JB, Critchley JA, Labarthe DR, Kottke TE, Giles WH, Capewell S . Explaining the decrease in U.S. deaths from coronary disease, 1980-2000.N Engl J Med. 2007; 356:2388–2398. doi: 10.1056/NEJMsa053935.CrossrefMedlineGoogle Scholar - 403. Institute of Medicine. Promoting Cardiovascular Health in the Developing World: A Critical Challenge to Achieve Global Health. Washington, DC.: The National Academies Press; 2010.Google Scholar
- 404.
Nestle M . Food Politics: How the Food Industry Influences Nutrition, and Health, Revised and Expanded Edition. Los Angeles, CA: University of California Press; 2007.CrossrefGoogle Scholar - 405. Centers for Disease Control and Prevention (CDC). Motor-vehicle safety: a 20th century public health achievement.http://www.cdc.gov/mmwr/preview/mmwrhtml/mm4818a1.htm. Accessed December 17, 2015.Google Scholar
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