Advanced Obesity Treatment Selection among Adolescents in a Pediatric Weight Management Program
Abstract
Background: Treatment options for adolescents with obesity are limited. Yet, therapies previously reserved for adults, such as medications and bariatric surgery, are increasingly available to adolescents in tertiary obesity treatment settings. We aimed to identify the factors associated with selecting an advanced obesity treatment (diets, medications, and surgery) beyond lifestyle therapy among adolescents presenting to a tertiary, pediatric weight management program.
Methods: We conducted a secondary analysis of adolescents (N = 220) who participated in a longitudinal, observational case–control study within a pediatric weight management program. The exposures were potential individual and clinical factors, including sociodemographic characteristics and comorbidities. The outcome was treatment selection, dichotomized into lifestyle vs. advanced treatment. We modeled associations between these factors and treatment selection using logistic regression, controlling for confounding variables (age, race/ethnicity, sex, and insurance).
Results: The study population included a majority of non-Hispanic Black (50.5%) and Hispanic/Latino (19.5%) adolescents, of whom 25.5% selected advanced treatment. Adolescents were more likely to choose an advanced treatment option if they had a greater BMI [odds ratio (OR) 1.09, 95% confidence interval (95% CI) 1.04–1.15], lived further from the clinic (OR 1.03, 95% CI 1.00–1.05), and had an elevated glycohemoglobin level (OR 2.46, 95% CI 1.24–4.92).
Conclusions: A significant fraction of adolescents seeking obesity treatment in a specialized care setting chose new and emerging obesity treatments, particularly those at high risk of developing diabetes. These findings can inform patient–clinician obesity treatment discussions in specialty care settings.
Clinical Trial Registration number: NCT03139877.
Introduction
Approximately one in five children nationwide have obesity, and the prevalence of severe obesity among adolescents is still rising.1,2 Adolescents diagnosed with obesity are more likely to continue to have obesity into adulthood and are at an increased risk of developing cardiometabolic risk factors, prediabetes, and hypertension.3–5 Those with severe obesity are more likely to develop these comorbidities during adolescence.3,5,6 Given the relative resistance of obesity to lifestyle therapy, the development of more advanced treatment options, including pharmacotherapy and bariatric surgery, for youth with obesity is accelerating. The effectiveness of pharmacotherapy varies among agents, but generally results in a 2%–4% reduction in BMI.7 Additionally, bariatric surgery produces significant and sustained weight loss in adolescents.8,9 Despite these treatment successes, advanced therapeutic approaches for adolescents remain limited compared with the available adult obesity treatment options. At present, three pharmacotherapies are FDA approved for use in adolescents: orlistat, available for long-term obesity treatment; phentermine, available for short-term use; and liraglutide, which was recently approved in 2020.10 All other pharmacotherapy options use off-label prescriptions for youth.11 Given the associated uncertainties and potential for additional risks, it remains unclear what factors lead clinicians, adolescents, and their families to pursue these treatments.
Clinicians and adolescents must weigh each treatment option's benefits and risks when electing for more advanced obesity treatment in pediatric tertiary care settings. Many studies have described factors broadly influencing adolescents' treatment decisions, including peer and parent influence, socioemotional factors, quality of life, and treatment efficacy.12–15 Additionally, evidence suggests that adolescents are more likely to make riskier health decisions.12,16 Studies evaluating adolescent obesity treatment decisions have described the amount of adolescent involvement in the final decision.17 Still, they do not discuss how adolescents make this decision when faced with increasing numbers of options.17,18 Only limited evidence qualitatively evaluates adolescent bariatric surgery decision-making,19,20 and more studies have described how patient-level factors may be predictive of obesity treatment selection in adults.21,22 To promote the selection of the best treatment option for an adolescent, a shared decision-making process between the clinician, adolescent, and family is utilized in clinical settings.23–25 Understanding the measurable patient-level and clinical factors that lead adolescents to select advanced treatment in tertiary obesity care settings is needed to better inform patient–clinician treatment discussions and decisions.
Therefore, we utilized data from a longitudinal, observational case–control study (NCT03139877) of adolescents from a tertiary weight management program to conduct a secondary analysis to fill this gap.26 These adolescents (N = 220) were enrolled upon presentation to the weight management program with the primary objective of identifying mechanisms underlying microbiome regulation before and after obesity treatment, which included lifestyle therapy only and advanced treatment options. Demographic characteristics, anthropometrics, and clinical laboratories were collected at enrollment into the study, allowing for investigation of the individual and clinical factors associated with advanced treatment selection beyond lifestyle therapy in tertiary, pediatric weight management programs.
Methods
Study Design and Population
This was a longitudinal, observational case–control study in a pediatric, tertiary care, obesity treatment program, the details of which have been previously published.26 This study enrolled a convenience sample of adolescents, aged 10–18 years, who had not received intensive weight reduction therapy and presented to the clinic for initial evaluation. Other inclusion criteria included sexual maturity rating ≥2, age- and sex-specific BMI ≥95th percentile, and expected enrollment in the obesity treatment program for more than 6 months. The study enrolled four groups of adolescents; these groups were those receiving (1) standard of care consisting of intensive lifestyle modification and free participation in a physical activity program, Bull City Fit, (2) the standard of care and a low-carbohydrate diet, (3) the standard of care and pharmacotherapy, and (4) the standard of care and bariatric surgery. Each participant's therapy was determined by usual clinical care, medical recommendations, and family preference. Clinicians have standardized training in child obesity treatment and utilize a shared decision-making tool and note template to discuss all available obesity treatment options for the primary indication of weight loss with adolescents when first presenting to the clinic. Therefore, these treatment options are presented similarly to all patients, and practices vary minimally among clinicians. Adolescents who participated in the study were required to provide stool samples at 6-week increments over 6 months and blood samples at baseline, 3 months, and 6 months for development of a biorepository used to study microbiome signatures and also to fill out surveys measuring nutrition and physical activity upon enrollment. We abstracted all demographic, anthropometric, and laboratory data from the electronic medical record, collected as a part of routine clinical care. Sociodemographic data are self-reported and collected by the Duke University Medical Center for documentation in the electronic medical record.
Participants were recruited from the Duke Healthy Lifestyles program, a referral-based, multidisciplinary, pediatric weight management program located in Durham, NC. Physicians refer children and adolescents who have obesity, defined as a BMI ≥95th percentile for age and sex. The clinic serves a diverse population; adolescents aged 10–18 years, which is the same range as the study cohort, are 55% female, 37% Black, and 30% Hispanic and 70% of visits are covered by public health insurance. Additionally, the majority have severe obesity: 37% have class 1 obesity, 39% have class 2 obesity, and 31% have class 3 obesity. The Healthy Lifestyles clinical protocol has been previously described27 and meets the current standard of clinical care recommended for pediatric obesity treatment.28 The study was approved by the Duke University Health System Institutional Review Board. The protocol was registered on Clinicaltrials.gov.
Measures
Outcomes
The primary outcome was treatment selected at the adolescent's initial visit to the clinic. This included lifestyle therapy only, lifestyle therapy and low-carbohydrate diet, lifestyle therapy and medications (metformin, topiramate, phentermine, and lisdexamfetamine), or lifestyle therapy and bariatric surgery. Treatment choice was dichotomized into lifestyle therapy only vs. lifestyle therapy and advanced treatment (low-carbohydrate diet, medications, and bariatric surgery). We defined the advanced treatment group as any treatment option beyond standard of care lifestyle modification. Low-carbohydrate diet was included as an advanced treatment option due to the increased frequency of monitoring and required laboratory studies.
Potential predictors
The potential baseline factors for this analysis were patient-level and clinical factors measured at the initial clinical visit. Sociodemographic factors included age, sex, race/ethnicity (non-Hispanic White, non-Hispanic Black, non-Hispanic other, and Hispanic/Latino), annual household income in dollars (<25,000; 25,000 to <50,000; 50,000 to <75,000; 75,000 to <100,000; and ≥100,000), and insurance type (Private and Medicaid). Anthropometric measurements included height, measured using a Seca 242 stadiometer (Hamburg, Germany); weight, measured on a Tanita (Tanita, TBF 300, Arlington Heights, IL); and BMI, which was directly measured using height and weight on the calibrated Tanita. The distance of the home from the clinic was also included and was calculated using the patient's home address in the electronic medical record.
Potential predictive clinical factors for this analysis included depression, prediabetes, hyperlipidemia, hypertriglyceridemia, low high-density lipoprotein (HDL), and risk of nonalcoholic fatty liver disease (NAFLD). Depression was evaluated using the Patient Health Questionaire-9 as part of clinical care and was dichotomized into no or minimal depression (≤4) or mild to severe depression (≥5).29,30 Other comorbidities included were prediabetes, diagnosed using glycohemoglobin level ≥5.7 IU/dL; hyperlipidemia, diagnosed using low-density lipoprotein (LDL) cholesterol level ≥120 mg/dL; hypertriglyceridemia, diagnosed using fasting triglyceride level ≥110 mg/dL; and low HDL, diagnosed by HDL level <40 mg/dL. The risk of NAFLD was defined using the alanine transaminase level ≥40 U/L. Elevated insulin (≥20 uIU/mL) and glucose (≥120 mg/dL) levels were also included as potential predictive clinical factors. Abnormal values were defined according to the American Academy of Pediatrics and American Diabetes Association guidelines.31–33
Statistical Analysis
Baseline characteristics and clinical factors were described by treatment selection. Continuous variables are summarized as mean [standard deviation (SD)] or median (interquartile range), and categorical variables are summarized as frequency (percentage). Logistic regression models were fit to assess the association between each risk factor of interest and selecting advanced treatment options, compared with selecting lifestyle therapy only, with and without covariate adjustment. Covariates were identified a priori based on hypothesized confounders and prior studies, including age, race/ethnicity, sex, and insurance type. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were reported. All analyses were performed in R 4.0.0.34 Statistical significance was defined as p < 0.05.
Results
Baseline Characteristics of the Observational Cohort
This observational cohort study included a total of 220 adolescents with a mean age of 13.5 years (SD 2.3) and BMI of 35 kg/m2 (SD 9.4) at study enrollment (Table 1). The majority of the study population were female (60%), and over half (55.2%) had an annual household income less than $50,000. The sample was diverse as 50.5% were non-Hispanic Black and 19.5% were Hispanic/Latino.
| Baseline characteristics | Total population (N = 220) | Lifestyle treatment (N = 164) | Low-carbohydrate diet (N = 14) | Medication (N = 36) | Weight-loss surgery (N = 6) |
|---|---|---|---|---|---|
| Age at enrollment, years | 13.5 (2.3) | 13.3 (2.2) | 14.6 (2.2) | 13.8 (2.3) | 16.4 (1.7) |
| BMI | 35 (9.4) | 33.3 (6.3) | 38.4 (12.7) | 36.5 (6.5) | 63.5 (27.4) |
| Sex | |||||
| Female | 132 (60.0) | 97 (59.1) | 10 (74.1) | 22 (61.1) | 3 (50.0) |
| Male | 88 (40.0) | 67 (40.9) | 4 (28.6) | 14 (38.9) | 3 (50.0) |
| Race/ethnicity | |||||
| Hispanic/Latino | 43 (19.5) | 36 (22.0) | 2 (14.3) | 5 (13.9) | 0 (0) |
| Non-Hispanic White | 46 (20.9) | 32 (19.5) | 4 (28.6) | 7 (19.4) | 3 (50.0) |
| Non-Hispanic Black | 111 (50.5) | 83 (50.6) | 6 (42.9) | 19 (52.8) | 3 (50.0) |
| Non-Hispanic other | 20 (9.1) | 13 (7.9) | 2 (14.3) | 5 (13.9) | 0 (0) |
| Annual household income (dollars) | |||||
| <25,000 | 42 (25.5) | 32 (26.0) | 0 (0) | 9 (32.1) | 1 (33.3) |
| 25,000 to <50,000 | 49 (29.7) | 38 (30.9) | 3 (27.3) | 7 (25.0) | 1 (33.3) |
| 50,000 to <75,000 | 26 (15.8) | 19 (15.4) | 3 (27.3) | 4 (14.3) | 0 (0) |
| 75,000 to <100,000 | 18 (10.9) | 14 (11.4) | 1 (9.1) | 2 (7.1) | 1 (33.3) |
| ≥100,000 | 29 (17.6) | 19 (15.4) | 4 (36.4) | 6 (21.4) | 0 (0) |
| Other | 1 (0.6) | 1 (0.8) | 0 (0.0) | 0 (0) | 0 (0) |
| Missing | 55 | 41 | 3 | 8 | 3 |
| Insurance type | |||||
| Private | 83 (37.7) | 56 (34.1) | 9 (64.3) | 14 (38.9) | 4 (66.7) |
| Medicaid | 127 (62.3) | 108 (65.9) | 5 (35.7) | 22 (61.1) | 2 (33.3) |
Age and BMI are presented as mean (SD), and all other characteristics are presented as n (%).
SD, standard deviation.
The majority of adolescents selected lifestyle-only treatment (74.5%; Table 1). However, a large proportion of adolescents chose advanced treatment options, including low-carbohydrate diets (6.4%), medications (16.4%), and bariatric surgery (2.7%). The most common medicine utilized for treatment was metformin (55.6%), while lisdexamfetamine (16.7%), phentermine (19.4%), and topiramate (8.3%) were less commonly used.
Characteristics of Adolescents Selecting Lifestyle and Advanced Treatment Options
In bivariate analyses, age was the only sociodemographic factor associated with more advanced treatment choices. Adolescents selecting advanced treatment options were older (14.3 years; SD 2.3) compared with adolescents who selected lifestyle-only treatment (13.3 years; SD 2.2; OR 1.22, 95% CI 1.06–1.39; p = 0.005; Tables 2 and 4). The median distance from the clinic was greater for adolescents selecting advanced treatment options (12.4 vs. 8.0 miles). In the unadjusted analyses, a one-unit increase in distance from the clinic was associated with increased odds of selecting advanced therapy compared with lifestyle therapy only (OR 1.03, 95% CI 1.01–1.05; p = 0.011; Table 4).
| Lifestyle treatment only | Advanced treatment selection | |
|---|---|---|
| n (%) | 164 (74.5) | 56 (25.5) |
| Age at enrollment, years | 13.3 (2.2) | 14.3 (2.3) |
| Distance from the clinic, miles | 8.0 (5.0–18.5) | 12.4 (4.8–29.9) |
| Sex | ||
| Female | 97 (59.1) | 35 (62.5) |
| Male | 67 (40.9) | 21 (37.5) |
| Race/ethnicity | ||
| Hispanic/Latino | 36 (22.0) | 7 (12.5) |
| Non-Hispanic White | 32 (19.5) | 14 (25.0) |
| Non-Hispanic Black | 83 (50.6) | 28 (50.0) |
| Non-Hispanic other | 13 (7.9) | 7 (12.5) |
| Insurance | ||
| Private | 56 (34.1) | 27 (48.2) |
| Medicaid | 108 (65.9) | 29 (51.8) |
| Annual household income (dollars) | ||
| <25,000 | 32 (26.0) | 10 (23.8) |
| 25,000 to <50,000 | 38 (30.9) | 11 (26.2) |
| 50,000 to <75,000 | 19 (15.4) | 7 (16.7) |
| 75,000 to <100,000 | 14 (11.4) | 4 (9.5) |
| ≥100,000 | 19 (15.4) | 10 (23.8) |
| Other | 1 (0.8) | 0 (0.0) |
Age at enrollment is presented as mean (SD), and distance from the clinic is presented as median (interquartile range). All other variables are presented as n (%).
| N | Unadjusted | Adjusted | |||
|---|---|---|---|---|---|
| OR (95% CI) | p | OR (95% CI) | p | ||
| Sociodemographic factors | |||||
| Agea | 220 | 1.22 (1.06–1.39) | 0.005 | 1.04 (0.88–1.23) | 0.628 |
| Distance from the clinicb | 216 | 1.03 (1.01–1.05) | 0.011 | 1.03 (1.00–1.05) | 0.018 |
| Race/ethnicityc | 210 | ||||
| Hispanic/Latino | Reference | Reference | |||
| Non-Hispanic White | 1.92 (0.68–5.44) | 0.221 | 2.03 (0.60–6.88) | 0.253 | |
| Non-Hispanic Black | 1.52 (0.60–3.85) | 0.373 | 1.38 (0.52–3.67) | 0.515 | |
| Non-Hispanic other | 2.67 (0.77–9.22) | 0.121 | 2.24 (0.59–8.46) | 0.235 | |
| Incomeb (dollars) | 164 | ||||
| <25,000 | Reference | Reference | |||
| 25,000 to <50,000 | 0.93 (0.35–2.46) | 0.878 | 0.67 (0.24–1.90) | 0.451 | |
| 50,000 to <75,000 | 1.18 (0.38–3.61) | 0.773 | 0.61 (0.17–2.25) | 0.458 | |
| 75,000 to <100,000 | 0.91 (0.24–3.42) | 0.894 | 0.28 (0.05–1.46) | 0.131 | |
| ≥100,000 | 1.68 (0.59–4.79) | 0.328 | 0.68 (0.15–3.24) | 0.633 | |
| Clinical factors | |||||
| BMIb | 220 | 1.09 (1.04–1.13) | <0.001 | 1.09 (1.04–1.15) | <0.001 |
| Depressionb | 159 | 1.56 (0.77–3.13) | 0.216 | 1.35 (0.63–2.89) | 0.444 |
| Elevated glycohemoglobinb | 210 | 2.12 (1.13–3.98) | 0.020 | 2.46 (1.24–4.92) | 0.010 |
| Elevated insulinb | 195 | 2.49 (1.27–4.86) | 0.008 | 2.82 (1.36–5.84) | 0.005 |
| Elevated glucose | 215 | — | 0.014d | — | — |
| Elevated LDLb | 214 | 1.79 (0.96–3.34) | 0.069 | 1.64 (0.85–3.17) | 0.139 |
| Low HDLb | 215 | 1.34 (0.68–2.64) | 0.390 | 1.29 (0.62–2.65) | 0.495 |
| Elevated triglyceridesb | 215 | 1.61 (0.86–2.99) | 0.136 | 2.25 (1.11–4.58) | 0.025 |
| Elevated ALTb | 216 | 1.47 (0.53–4.09) | 0.457 | 1.72 (0.56–5.29) | 0.343 |
a
Model controlled for race/ethnicity, sex, insurance type, and BMI.
b
Models controlled for age, race/ethnicity, sex, and insurance type.
c
Model controlled for age, sex, insurance type, and elevated glycohemoglobin.
d
Due to zero cell count, the p-value was obtained from Fisher's exact test.
95% CI, 95% confidence interval; OR, odds ratio.
Clinical factors associated with advanced treatment selection were BMI, and glycohemoglobin, insulin, and glucose levels (Table 3). Adolescents selecting advanced treatment options had a higher BMI (39.8 kg/m2; SD 14.2), compared with adolescents who selected lifestyle therapy only (33.3 kg/m2; SD 6.3; OR 1.09; 95% CI 1.04–1.13; p < 0.001). Additionally, 50% of adolescents selecting advanced treatment options had an elevated glycohemoglobin level, while only 32.1% of adolescents selecting lifestyle-only treatment had an elevated glycohemoglobin level (p = 0.020). This association was also true for other markers of future diabetes risk, such as elevated blood insulin (p = 0.008) and glucose (p = 0.014) levels. Having elevated glycohemoglobin and insulin levels was associated with 2.12 (95% CI 1.13–3.98) and 2.49 (95% CI 1.27–4.86) increased odds of selecting advanced treatments compared with selecting lifestyle therapy only, respectively (Table 4).
| Lifestyle treatment only (N = 164) | Advanced treatment selection (N = 56) | |
|---|---|---|
| BMI | 33.3 (6.3) | 39.8 (14.2) |
| Depression | ||
| None or minimal | 70/115 (60.9) | 22/44 (50.0) |
| Mild to severe | 45/115 (39.1) | 22/44 (50.0) |
| Elevated glycohemoglobin | ||
| Yes | 50/156 (32.1) | 27/54 (50.0) |
| No | 106/156 (67.9) | 27/54 (50.0) |
| Elevated insulin | ||
| Yes | 37/145 (25.5) | 23/50 (46.0) |
| No | 108/145 (74.5) | 27/50 (54.0) |
| Elevated glucose | ||
| Yes | 0/162 (0.0) | 3/53 (5.7) |
| No | 162/162 (100.0) | 50/53 (94.3) |
| Elevated LDL | ||
| Yes | 62/161 (38.5) | 28/53 (52.8) |
| No | 99/161 (61.5) | 25/53 (47.2) |
| Low HDL | ||
| Yes | 41/161 (25.5) | 17/54 (31.5) |
| No | 120/161 (74.5) | 37/54 (68.5) |
| Elevated triglycerides | ||
| Yes | 59/161 (36.6) | 26/54 (48.1) |
| No | 102/161 (63.4) | 28/54 (51.9) |
| Elevated ALT | ||
| Yes | 13/163 (8.0) | 6/53 (11.3) |
| No | 150/163 (92.0) | 47/53 (88.7) |
BMI is presented as mean (SD), and all other variables are presented as n (%).
ALT, alanine transaminase; HDL, high-density lipoprotein; LDL, low-density lipoprotein.
Sociodemographic and Clinical Factors Associated with Advanced Treatment Selection
In adjusted analyses, a further distance from the clinic, higher BMI, and elevated glycohemoglobin, insulin, and triglyceride levels were associated with greater odds of selecting advanced treatment (Table 4). Elevated glycohemoglobin and insulin levels were associated with 2.46 (95% CI 1.24–4.92) and 2.82 (95% CI 1.36–5.84) greater odds of selecting advanced treatment compared with lifestyle therapy only, respectively. Additionally, a higher BMI and further distance from the clinic were associated with greater odds of selecting advanced treatment (OR 1.09, 95% CI 1.04–1.15; OR 1.03, 95% CI 1.00–1.05, respectively). Age was not associated with higher odds of selecting an advanced treatment option over lifestyle therapy only in adjusted analyses (OR 1.04, 95% CI 0.88–1.23). Notably, a diagnosis of depression was not associated with advanced treatment selection in adjusted or unadjusted analyses.
Discussion
This analysis highlights sociodemographic and clinical factors associated with advanced treatment selection, which is increasingly available in pediatric specialty obesity care settings for adolescents. Among many sociodemographic and clinical factors included in this analysis, we identified a greater BMI, further distance from the clinic, and diagnosis of prediabetes or hypertriglyceridemia as factors associated with increased likelihood of selecting an advanced treatment option. These results better inform patient–clinician treatment discussions and allow clinicians to better understand which factors, when present, may influence treatment decision-making in their adolescent populations.
Adolescents are more frequently opting for advanced treatment options, including low-carbohydrate diets, medications, and surgery. We found that nearly one in four adolescents selected an advanced therapy, which often requires increased clinical monitoring and more frequent visits. Despite increased clinical care, bariatric surgery may be cost-effective after 5 years, depending on the number of comorbidities experienced by an adolescent.35 The acceptability of advanced treatment among adolescents supports a pressing need for rigorous testing of therapies approved for adults in youth who are seeking out these treatments.10
While numerous studies have evaluated factors predictive of weight loss across various weight management programs and obesity treatments,36 few report on factors predictive of treatment selection among adolescents. We identified that a greater adolescent BMI was associated with advanced treatment selection, and found that age was not associated with advanced treatment selection when adjusting for BMI. These results are consistent with literature showing that adolescents with greater BMI are less likely to respond to lifestyle therapy,12 which may motivate adolescents to opt for advanced therapies despite more potential risks. Notably, we found no association between clinical depression and selection of advanced therapies, which builds upon available evidence among adolescents pursuing bariatric surgery.37 Together, these findings are in line with current clinical guidance for advanced obesity treatment options recommending the use of BMI thresholds rather than age limits and formal mental health evaluation and treatment if indicated.11,37
We also found that adolescents selecting advanced treatments were more likely to live further from the clinic than adolescents who opted for lifestyle therapy only. Adolescents selecting advanced treatments lived approximately 4 miles further away than adolescents selecting lifestyle therapy alone. While we expected that adolescents pursuing more advanced treatment options would travel from much further distances, lifestyle therapy alone does require monthly visits with a provider. Therefore, traveling even a short distance further to the clinic monthly may not be a feasible treatment approach for some adolescents. Instead, these adolescents may choose advanced treatments that require more frequent initial clinical monitoring ultimately resulting in less frequent visits and travel. The lack of approved and accessible obesity care for adolescents in the United States has been well documented,38 also suggesting that adolescents may be more willing to travel to tertiary, pediatric obesity care settings for these advanced treatment options that are not offered in their home communities.
Of many potential obesity comorbidities diagnosed in adolescence, a diagnosis of prediabetes was associated with more than twice the likelihood of choosing an advanced treatment option. Notably, no consensus exists for the use of metformin in treating prediabetes in adolescents,39 and clinician prescribing practices vary in the absence of clear recommendations.40 These findings suggest that adolescents and their families may perceive prediabetes as associated with more health risks, compelling them to choose a more advanced treatment. In the setting of increasingly available targeted pharmacotherapy, this presents an opportunity to refine clinician risk communication strategies with adolescents and their families. For example, adolescents presenting to pediatric weight management programs often have more than one comorbidity to discuss during the visit. Yet, among many comorbidities included in this analysis, only prediabetes and hypertriglyceridemia, for which the mainstay of treatment is already recommended lifestyle therapy, were predictive of patients choosing advanced treatment options. Therefore, a better approach for clinicians may be to highlight the most meaningful comorbidities to the patient in these discussions. Further research is needed to quantitatively and qualitatively evaluate how adolescents understand obesity-associated health risks to better inform shared decision-making conversations in these specialty care settings.
While the study's strengths include a diverse, prospective observational cohort of adolescents participating in a weight management program, the study has limitations. First, we cannot determine the driver of decision-making and cannot differentiate the role of the adolescent, family, and clinician. For example, we cannot assign weights to clinician, adolescent, and parent perceptions of a diagnosis of prediabetes in the final recommendations and choices for weight management. Importantly, shared decision-making is used in this tertiary, pediatric weight management program for all patients, with final decisions made by the adolescent and their family after medical counseling and personal preferences are elicited. Additionally, the sample size does not allow us to differentiate factors associated with each independent treatment track. The risk-to-benefit assessment for advanced diets, medications, and surgery varies dramatically, and we cannot separate these differences in this analysis. Due to the small size of each advanced treatment group, we did not complete any sensitivity analyses looking for associations with independent treatment tracks or with the advanced group defined as including only adolescents choosing medication and surgery. As this study enrolled a convenience sample of adolescents from the larger clinic population, adolescents who chose to enroll in a study collecting stool and blood samples may represent a skewed subset of the larger clinical population. While the demographic characteristics of the overall clinic population are similar to that of the enrolled cohort, lifestyle and advanced treatment selection in this analysis may not be representative of the entire clinic population. Finally, while a number of different potential predictive factors were included in this analysis, the potential predictive variables were limited by those available in the dataset. There are several other factors that could be predictive of adolescent treatment choice, including prior weight-loss attempts, length of previous obesity treatment trials, and family weight and associated obesity comorbidities, which were not captured. Future prospective quantitative and qualitative research studies that include these potential predictor variables are needed to better understand how adolescents make obesity treatment decisions and to inform clinical obesity treatment conversations with adolescents.
Conclusions
Adolescents attending tertiary, pediatric weight management programs are increasingly choosing advanced treatment options, including pharmacotherapy and bariatric surgery. Clinicians can utilize the patient-level factors identified here to modify current approaches to health risk communication and treatment discussions by highlighting prediabetes as a meaningful comorbidity in adolescents' and parents' decision. Further research is needed to expand treatments previously reserved for adults to adolescent populations interested in receiving them.
Acknowledgments
The authors would like to thank the study participants and their families for participating in this study.
Disclaimer
The contents of this article are solely the authors' responsibility and do not necessarily represent the official views of NCATS or NIH.
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Copyright 2022, Mary Ann Liebert, Inc., publishers.
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Published in print: June 2022
Published online: 18 May 2022
Published ahead of print: 9 November 2021
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Authors' Contributions
L.S., A.C.S., and S.C.A. conceptualized and designed the study. T.T. conducted data analyses. All authors contributed to writing, reviewing, and revising the manuscript and they approved the manuscript for submission.
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No competing financial interests exist.
Funding Information
This study was supported by the National Institutes of Health (NIH), grant R24-DK110492. The Duke Biostatistics, Epidemiology, and Research Design Methods Core's support of this project was made possible, in part, by a CTSA Grant (UL1TR002553) from the National Center for Advancing Translational Sciences (NCATS) of the NIH and the NIH Roadmap for Medical Research.
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