Skip to main content
Intended for healthcare professionals

Abstract

The goal of assessing psychosocial stress as a process and outcome in naturalistic (i.e., field) settings is applicable across the social, biological, and health sciences. Meaningful measurement of biology-in-context is, however, far from simple or straightforward. In this brief methods review, we introduce theoretical framings, methodological conventions, and ethical concerns around field-collection of markers of psychosocial stress that have emerged from 50 years of research at the intersection of anthropology and human biology. Highlighting measures of psychosocial stress outcomes most often used in biocultural studies, we identify the circumstances under which varied measures are most appropriately applied and provide examples of the types of cutting-edge research questions these measures can address. We explain that field-based psychosocial stress measures embedded in different body systems are neither equivalent nor interchangeable, but this recognition strengthens the study of stress as always simultaneously cultural and biological, situated in local ecologies, social–political structures, and time.

Introduction

Stress is an encompassing term that refers to the body’s physiological response to environmental challenges—or stressors—that strain an individual’s ability to maintain homeostasis and undermine adaptive capacity (Ice and James 2007; Pearlin et al. 1981). Stressors can be physical (e.g., altitude), biological (e.g., disease and nutrition), or psychosocial in origin (e.g., discrimination and inequality). Here, we present an integrated approach to field-based measurement and interpretation of psychosocial stress outcomes using biomarkers as biologies-in-context. Our brief review is grounded in decades of biocultural research within anthropology and human biology that considers stress as a primary point to understand the dynamics between sociocultural and biological dimensions of the human experience (Dufour 2006; Hicks and Leonard 2015; Leatherman and Goodman 2020; Stinson et al. 2000). The history and relevance of this biocultural approach to the wider social, biological, and health-related sciences are explained elsewhere (Glass and McAtee 2006; Hertzman and Boyce 2010; Krieger 2001; McEwen 1998, 2012; Meloni 2014; Roberts and Rollins 2020; Sapolsky 1998; Taylor et al. 1997; Worthman and Kohrt 2005). Our goal, rather, is to identify key practices in field-based stress biomarker collections that have emerged from decades of biocultural research, including available options, agreed-on conventions, and ethical considerations.

Basic Principles: Biocultural Measurement of Psychosocial Stress Outcomes

Biocultural frameworks to understand stress processes overlap greatly with biosocial ones (e.g., McDade and Harris 2018, Roberts and Rollins 2020); both are based in a recognition of human biology as dynamically connected to social contexts across the life span and that neither can be fully explained without some consideration of the other. Perhaps the clearest distinction of a biocultural approach is the emphasis on integrating the proximate (highly local) context into research design, and thus the primacy of both fieldwork and theories related to local cultural and biological variation. Almost all biocultural research is field based, anchored in the fundamental understanding that physiological expressions of stress are dynamic and based in proximate context. Physical bodies are situated in time, space, and patterns of practice in the “situated biologies” of real people in the real world (Niewöhner and Lock 2018). Biocultural studies of stress, however, now place greater emphasis on how data collection and interpretation happen, so typically integrate methods such as extended participant observation and interviewing, which elucidate more detailed salient dimensions of the social stress process (Dufour 2006). This work is situated in varied theories of culture as highly localized phenomena that can be both a source of psychosocial stress and a means to alleviate or buffer it. One example of a specific theory is cultural consonance; operationally, it evaluates metrically the extent to which an individual aligns with locally shared norms and practices (Dressler 2017, 2020). For example, Dressler and colleagues (2016) found that lower cultural consonance in social support in Brazil was associated with higher stress measures (based on blood C-reactive protein). Another example is social theories of gender as structural inequality. For example, Nepali women are primarily responsible for household water, so low water access elevates their stress as measured by blood pressure—but not that of their husbands (Brewis et al. 2019). Without such proximal theorization of within-cultural variation, it is difficult to interpret when and why individual measures of stress vary, such as between those in the same household.
Drawing on political–economic theory, biocultural assessments of stress also recognize that the stress experience is often situated within historically inequitable social structures (Leatherman and Goodman 2020). Factors like wealth, power, prestige, social connection, and historical trauma are all important mediators or moderators of the stress process (Link and Phelan 1995; McEwen 1998, 2012; Sapolsky 1998), including what people perceive as stressful (Dressler 1991; Singer et al. 2016). Again, recognition that these unequal structures matter then demands integration into fieldwork of theory and methods for characterizing relevant aspects of the political–economic context and the place of sampled individuals within it, so that measures of psychosocial stress can be interpreted correctly (e.g., Dressler 2005; Flinn and England 1997; Hicks and Leonard 2015). Piperata et al. (2016, 2020) use this approach to understand how long-standing land distribution and economic policies led to widespread food insecurity and, relatedly, psychosocial stress among women in León, Nicaragua. In this context, asking others for food was so stigmatized that when women drew on their social networks to cope with food insecurity, it promoted more (rather than less) psychosocial stress.
Applying anthropological theories of human genetic and developmental adaptation, biocultural assessments of psychosocial stress also recognize that meaningful interpretation of stress outcome biomarkers must consider possible underlying variation in relevant physiological processes (e.g., Martin 2019). Individuals vary in physiological stress responses with a host of individual factors like genetic predispositions, prior environmental exposures, gender, body size or composition, and sleep patterns, to name a few. Relatedly, life history theory suggests that the way bodies identify and respond to stress varies by life stage and may include trade-offs across organ systems and over time (e.g., skeletal growth versus immune function) (see Shattuck-Heidorn et al. 2017). Due to this fully expected variation, individuals may experience—and physically manifest—the same event or environmental condition very differently not just from person to person, but also across time and with changing personal circumstances.
Relatedly, in a biocultural framework, population-level variation in underlying stress physiology is always assumed, a point especially relevant when comparing stress outcome measures beyond a well-defined local context. Many, often irreversible, phenotypic traits in humans reflect highly localized interactions between genotypes and the environment through the process of developmental plasticity. One of the best examples is the extreme variation in the measurable ranges of ovarian hormones in women entering puberty in ecologies with differing energetic demands (Ellison 1996). Thus, comparing stress outcomes across groups requires explicit theories of exactly how and why stress markers might vary, a point carefully developed in the earliest biocultural studies using adaptability frameworks (e.g., Baker et al. 1986) and still adhered to today.
Finally, varied stress biomarkers capture outcomes of different and interacting phenomena at multiple scales. As Table 1 outlines, psychosocial stress responses manifest across multiple organ systems and over varying time scales, meaning biomarkers can potentially capture stress in many different dimensions. Identifying distinctions between the available options and examples of cutting-edge studies being done with each is the focus of the next section.
Table 1. Some Commonly Applied Biomarkers for Field Measurement of Stress Outcomes.
Physiological system How stress connects to the marker Stress outcome biomarkers Time window Data collection in field Reason to use Technical challenges/disadvantages
Cardiovascular Activates sympathetic-adrenal–medullary (SAM) axis, releasing catecholamines that elevate heart rate and blood pressure Blood pressure (esp. arterial) Minutes to days Manual sphygmomanometer and stethoscope; automated devices (see https://www.validatebp.org/); or ambulatory monitoring Clear protocols, easy and cost effective, comparable across sites or through time, noninvasive, sensitive to variations in experiences of stress in context; automatic ambulatory monitoring can capture circadian variations in context Measurement is sensitive to environmental conditions (e.g., temperature), behavior (e.g., exercise, smoking, caffeine intake), and measurement technique (e.g., rounding error in manual measurement, calibration of electronic monitors)
    Heart rate variability Minutes to days Electronic monitor Non-invasive, remote monitoring facilitates tracking of situational micro-change over time Interpretation can be difficult; results can be situationally manipulated
Neuroendocrine Activates hypothalamic–pituitary–adrenal (HPA) axis creating hormone cascades through many organ systems Cortisol Hours, days, weeks, months, years Collection of saliva, urine, feces, milk, and blood for acute; hair and nails for chronic; teeth for developmental Direct measure of physiological stress response. Non-invasive collection options available (many of which do not require refrigeration). Samples can be analyzed in commercial labs. Cortisol is the most commonly used hormonal stress marker because it appears in many specimen types Acute measures must deal with issues of diurnal variation and blunting from chronic HPA-axis activation. Cortisol not always associated with stress as expressed by scales or survey instruments so not as reliable when used as a singular stress biomarker
Psychological Perceived threat with inability to cope activates distress emotions and undermines mental health, which is then described as symptoms Mental health scales, especially well validated ones like PSS (Cohen et al. 1983), CES-D (Radloff 1977), SRQ-20 (Beusenberg and Orley,
1994)
Days to weeks Self-report/interview Fast, easy, cheap, best captures human lived experience of stress. New measures are working to capture positive symptomology Local adaptation of validated scales is necessary as symptom expression reflects cultural idioms
Immunological Dampens immune response and elevates systemic inflammation Epstein-Barr virus (EBV), C-reactive protein (CRP), and Interleukin-6 (IL-6) Months, years Blood spot Can be detected in dried blood spots (finger prick), only small amount blood needed, and no refrigeration Invasive (finger prick)
Skeletal Interrupts growth at critical phases by diverting energy to maintain other systems Anthropometric measurement (height, sitting height, leg length, etc) Months or years Calibrated, precise measuring tools required Quick, easy, noninvasive, highly portable equipment available, highly comparable through time and across sites Other nonpsychosocial factors, such as dietary quality and disease exposure, influence measurement outcome
Subcellular/DNA Accelerates DNA methylation Epigenetic alterations to DNA Past trauma, sometimes years later, including in utero Blood spot or venous blood draw Methylation potentially signals trans-generational stress impacts Highly technical with low comparability across studies, costly, not easily detected in peripheral tissues most easily accessed in the field, invasive. May reflect varied stressors, like illness or diet
  Accelerates cell aging processes due to faster division Telomere shortening Years Venous blood, dried blood spot, or saliva Hallmark indicator of biological aging, may reflect wear-and-tear of cumulative stress exposure; predictive of cardiovascular disease, cancer, mortality As above

Measuring Psychosocial Stress in Context: Opportunities, Limitations, and Examples

Here, we outline (Table 1) and provide examples of the primary suite of readily available, acceptable biomarker-based methods for assessing psychosocial stress outcomes as biology-in-context. Biomarker here refers to variable, quantifiable expressions of physiological systems. Acceptable means considered by biocultural practitioners as adequately theorized to give meaningful results, sufficiently robust for field-based data collection, and ethically defensible. This list is not exhaustive, but rather highlights the methods widely applied and for which opportunities and limitations are reasonably recognized.
One of the first biomarkers applied in field-based psychosocial stress assessment, heightened blood pressure (e.g., McGarvey and Baker 1979; Scotch 1963), remains widely used because it is noninvasive and easy to measure. However, a lack of understanding as to why it varies individually, temporally, and across populations can lead to misinterpretation (James and Gerber 2018). Heart rate variability is a more recent and closely related measure (e.g., Bell et al. 2019). Both blood pressure and heart rate variability are captured relatively easily in the periphery of the body and have well-established connections to diseases like hypertension, obesity, and type 2-diabetes (Juster et al. 2010; Sapolsky 1998; Steptoe and Kivimäki 2013). This means they can illuminate biological pathways through which psychosocial stress influences human health (Crosswell and Lockwood 2020; Dressler 2004; Worthman and Costello 2009). For example, assessment of social contexts has clarified that greater exposure to market-based lifestyles and the internalization of new but unachievable social and economic expectations of success explain higher blood pressure levels and risk of chronic disease (Bindon et al. 1997; Dressler 1999; Dressler et al. 2005; Pollard et al. 2000; Silva et al. 2016; Steffen et al. 2006; Valeggia and Snodgrass 2015; Waldron et al. 1982). Psychosocial stressors such as racism have also been shown to explain blood pressure variability in the African diaspora better than skin tone or genetic ancestry, pointing to the primacy of sociocultural processes (Gravlee et al. 2005, 2009; Non et al. 2012). Another common and variable source of psychosocial stress relates to gendered expectations, responsibilities, and opportunities. Among Musuo in China, matrilineal social arrangements, which elevate women’s status, are associated with women’s lowered blood pressure while patrilineal arrangements are not (Reynolds et al. 2020).
Neuroendocrine–hormonal biomarkers reflect acute psychosocial stress activation of the hypothalamic–pituitary–adrenal (HPA) axis (Ice and James 2007). For example, in New Zealand, evening salivary cortisol levels were associated with both living in poverty and racial/ethnic discrimination among pregnant women (Thayer and Kuzawa 2014, 2015). Interestingly, their infants exhibited greater cortisol responses to vaccination, suggesting that maternal HPA activation during pregnancy had lasting effects on infants’ HPA axes. Cortisol is the most frequently used neuroendocrine biomarker of psychosocial stress, in part because it can be measured in a range of specimen types (e.g., saliva, blood spots, serum, hair, teeth, finger/toenails) that capture different time scales. The range of options is important as some specimen types are more field-friendly and culturally acceptable than others. In addition, in studies of acute stress, using minimally invasive specimen types like saliva to measure cortisol concentrations is preferred over serum/plasma, partly because saliva collection induces less stress (Vagnoli et al. 2015).
The immune system contains a host of receptors for stress hormones, including cortisol, and psychosocial stress can dampen the immune response, worsen levels of systemic inflammation, and increase susceptibility to disease (Cohen et al. 2019). Development of dried blood spot protocols allows indirect measurement of immune function (e.g., C-reactive protein [CRP], Epstein-Barr virus [EBV]) outside of traditional clinical settings (Cepon-Robins 2021; McDade et al. 2007). Individual experiences with changes in social, economic, or political hierarchies are then linked to variation in these measures (McDade 2002; McDade et al., 2000). In Peru, for example, Tallman (2018), using levels of EBV antibodies, illustrated how adoption of new ideas related to cash-wealth as a marker of success explained reduced immune function among men with lower socioeconomic status. Immune biomarkers can also illustrate the protective value of social institutions. In Bolivia, women with higher levels of emotional and instrumental support had less stress, as measured by lower EBV values (Hicks 2014).
Self-reports of mental health symptoms, including expressions of distress/emotion, on validated scales are also accepted by biocultural practitioners as a measure of stress. For example, Oths (1999) demonstrated how reported symptoms of debilidad (a local idiom related to chronic exhaustion) were associated with a gender imbalance in the household within the context of a stressful agricultural life at high altitude. In a water-insecure Bolivian informal settlement, gender roles, household conflicts, and perceptions of injustice around water insecurity better predicted expressions of anxiety and depression than lack of water alone (Wutich 2020). This approach recognizes that perceptual/cognitive processes around symptom expression are always filtered through both cultural and individual sieves. Accordingly, local adaptation and pretesting are considered standard practices even on otherwise widely validated scales. There are many ways this is achieved, including via ethnographically informed cognitive interviewing or cultural consensus/consonance analysis (e.g., Kaiser et al. 2013; Mendenhall et al. 2016; Snodgrass et al. 2017).
The biomarkers discussed above capture relatively recent (i.e., minutes to months) stress effects. However, innovation in measuring cortisol in hair, nails, and teeth provides information on stress exposure over longer periods. For example, Swales et al. (2018) documented higher hair cortisol associated with both recent and childhood traumatic events among a U.S. sample of pregnant women. Anthropometric measures reflecting delays or stalling of skeletal growth are also often applied as a signal of chronic psychosocial stress over months or years. Central here is the recognition that when psychosocial stressors accumulate or persist, toxic stress can compromise an individual’s ability to rebound from duress, and thus disrupt processes of growth and development (Frongillo et al. 1997; Nelson 2018). For example, among children in Mandeville, Jamaica, the quality of interactions with caregivers predicted individual growth trajectories (height-for-age) above other situational factors like place of residence (natal homes vs. institution) or diet (Nelson 2016).
Epigenetic modification represents a newer measure of stress (Thayer and Non 2015). For example, Congolese mothers’ traumatic experiences while pregnant were associated with DNA methylation in their newborns (Mulligan et al. 2012), and children conscripted in the 1996–2006 war in Nepal exhibited changes in regulatory genes relevant to their phenotypic resistance to viral infections (Kohrt et al. 2016). Another relatively novel stress measurement is epigenetic age (Ryan 2020), based on the recognition that psychosocial stress accelerates cell aging. While currently challenging to interpret, measures of cellular aging, such as telomere length, have the potential to be used to assess the longer-term effects of psychosocial stress on the body not visible through other means (Epel et al. 2004; Marioni et al. 2016; Rentscher et al. 2020; Zahran et al. 2015). For example, racial discrimination, but not other forms of unfair treatment, was associated with shortened telomeres among African Americans in Tallahassee, Florida, suggesting that lifetime exposure to racism may be uniquely stressful (Rej et al. 2020).
Of course, these varied stress markers are not discrete, because the systems they relate to are interconnected. For example, neuroendocrine–hormonal biomarkers reflect acute stress activation of the HPA axis (Ice and James 2007) and can be measured directly—but this activation also increases cardiac output (e.g., blood pressure) (Kaltsas and Chrousos 2007), serotonin, and dopamine, leading to the experience and reporting of depressive symptoms (see Sapolsky 2004). Biocultural studies of stress always assume interrelationships (including feedback loops), unless there is clear evidence to the contrary (though these complex interactions remain incompletely specified).
While interconnected, it is important to recognize that the measures are neither equivalent nor interchangeable. Varied measures can yield disparate findings, such as cortisol concentrations being unassociated with self-perceived psychosocial stress (e.g., Hollenbach et al. 2019; Olstad et al. 2016). Thus, reference categories for comparisons must account for temporal, individual, and population-level variation; universal benchmarks are unlikely to be useful (see, e.g., Hruschka 2021). Instead, each biomarker is considered to reflect just one version of a story about how social context becomes embodied, with its own time scale. For these reasons, studies ideally deploy a range of biomarkers and interpret them relationally as different embodied manifestations of stress. To accomplish this, many scholars have adopted models of allostatic load—defined the cumulative burden of chronic stress across body systems (see Edes and Crews 2017; Guidi et al. 2021).

Some Ethical Considerations

The collection of psychosocial stress outcome biomarkers among living people raises ethical issues. As noted, different specimen types are identified as harmful or not across communities, and stress measurement itself can induce stress. More broadly, the use of political–economic theory, often deployed in designing biocultural research, demands attention to equity, beneficence, and justice in researcher–community relationships, and careful consideration of how findings are communicated and applied (e.g., Leatherman and Goodman 2011; Wutich 2020). Deploying biomarkers in the contexts of situated knowledge elevates those responsibilities because it rests on established trusting and long-term relationships with cultural experts and study communities. Best practices involve transparent data-sharing practices, as determined through consultation with community members. Over the past 15–20 years, the data sovereignty movement has clarified and asserted Indigenous people’s rights to biomarker data collected in their communities. Access and benefit sharing frameworks (Hudson et al. 2020; Robinson 2015) establish terms for storage, accessing, and use that are mutually beneficial to researchers and study communities, and advance community goals in ways that adhere fully to local values. Biocultural researchers are extending the impact of their work through community-engaged, participatory research practices, offering communities benefits beyond near-term solutions to persistent risks. Examples include community education, youth leadership development, or policy advocacy (e.g., Boston et al. 2015; Schell and Tarbell 1998). That said, such ethically necessary practices invariably lengthen the time and complexity of studies, as well as cost. Accordingly, these ethical dimensions need to be planned at the outset of any field-based research.

Acknowledgments

We acknowledge the US National Science Foundation Cultural Anthropology Program grant (Award SBE-2017491) to the NSF Cultural Anthropology Methods Program and Drs. Amber Wutich, Alissa Ruth, and Melissa Beresford for their role in organizing the workshop that generated this collaboration. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Declaration of Conflicting Interests

The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Science Foundation grant number Award SBE-2017491.

ORCID iDs

References

Baker P. T., Hanna J. M., Baker T. S., eds. 1986. The Changing Samoans: Behavior and Health in Transition. Oxford: Oxford University Press.
Bell K. A., Akeeb A., Lavela J., Mellman T. A. 2019. Emotional response to perceived racism and nocturnal heart rate variability in young adult African Americans. Journal of Psychosomatic Research 121:88–92.
Beusenberg M., Orley J. H. 1994. A user’s guide to the self-reporting questionnaire (SRQ). World Health Organization, No. WHO/MNH/PSF/94.8.
Bindon J., R., Knight A., Dressler W. W., Crews D. E. 1997. Social context and psychosocial influences on blood pressure among American Samoans. American Journal of Physical Anthropology 103:7–18.
Boston P. Q., Mitchell M. M., Collum K., Gravlee C. C. 2015. Community engagement and health equity. Practicing Anthropology 37:28–32.
Brewis A., Choudhary N., Wutich A. 2019. Low water access as a gendered physiological stressor: Blood pressure evidence from Nepal. American Journal of Human Biology 31:e23234.
Cepon‐Robins T. J. 2021. Measuring attack on self: The need for field‐friendly methods development and research on autoimmunity in human biology. American Journal of Human Biology 33:e23544.
Cohen S., Murphy M. L. M., Prather A. A. 2019. Ten surprising facts about stressful life events and disease risk. Annual Review of Psychology 70:577–97.
Cohen S., Kamarck T., Mermelstein R. 1983. Perceived stress scale (PSS). Journal of Health and Social Behavior 24:385–96.
Crosswell A. D., Lockwood K. G. 2020. Best practices for stress measurement: How to measure psychological stress in health research. Health Psychology Open 7:2055102920933072.
Dressler W. W. 1991. Stress and Adaptation in the Context of Culture: Depression in a Southern Black Community. Albany: SUNY Press.
Dressler W. W. 1999. Modernization, stress, and blood pressure: New directions in research. Human Biology 71:583–605.
Dressler W. W. 2004. Culture and the risk of disease. British Medical Bulletin 69:21–31.
Dressler W. W. 2005. What’s cultural about biocultural research? Ethos 33:20–45.
Dressler W. W. 2017. Culture and the Individual: Theory and Method of Cultural Consonance. New York: Routledge.
Dressler W. W. 2020. Cultural consensus and cultural consonance: Advancing a cognitive theory of culture. Field Methods 32:383–98.
Dressler W. W., Balieiro M. C., Ribeiro R. P., Dos Santos J. E. 2016. Culture and the immune system: Cultural consonance in social support and c‐reactive protein in urban Brazil. Medical Anthropology Quarterly 30:259–77.
Dressler W. W., Oths K. S., Gravlee C. C. 2005. Race and ethnicity in public health research: Models to explain health disparities. Annual of Review of Anthropology 34:231–52.
Dufour D. L. 2006. Biocultural approaches in human biology. American Journal of Human Biology 18:1–9.
Edes A. N., Crews D. E. 2017. Allostatic load and biological anthropology. American Journal of Physical Anthropology 162:44–70.
Ellison P. T. 1996. Developmental influences on adult ovarian hormonal function. American Journal of Human Biology 8:725–34.
Epel E. S., Blackburn E. H., Lin J., Dhabhar F. D., Adler N. E., Morrow J. D., Cawthon R. M. 2004. Accelerated telomere shortening in response to life stress. Proceedings of the National Academy of Sciences of the United States of America 101:17312–15.
Flinn M. V., England B. G. 1997. Social economics of childhood glucocorticoid stress response and health. American Journal of Physical Anthropology 102:33–53.
Frongillo E. A. Jr, de Onis M., Hanson K. M. 1997. Socioeconomic and demographic factors are associated with worldwide patterns of stunting and wasting of children. The Journal of Nutrition 127:2302–9.
Glass T. A., McAtee M. J. 2006. Behavioral science at the crossroads in public health: Extending horizons, envisioning the future. Social Science and Medicine 62:1650–71.
Gravlee C. C. 2009. How race becomes biology: Embodiment of social inequality. American Journal of Physical Anthropology 139:47–57.
Gravlee C. C., Dressler W. W., Bernard H. R. 2005. Skin color, social classification, and blood pressure in southeastern Puerto Rico. American Journal of Public Health 95:2191–7.
Gravlee C. C., Non A. L., Mulligan C. J. 2009. Genetic ancestry, social classification, and racial inequalities in blood pressure in southeastern Puerto Rico. PLoS One 4:e6821.
Guidi J., Lucente M., Sonino N., Fava G. 2021. Allostatic load and its impact on health: A systematic review. Psychotherapy and Psychosomatics 90:11–27.
Hertzman C., Boyce T. 2010. How experience gets under the skin to create gradients in developmental health. Annual Review of Public Health 31:329–47.
Hicks K. 2014. A biocultural perspective on fictive kinship in the Andes: Social support and women’s immune function in El Alto, Bolivia. Medical Anthropology Quarterly 28:440–58.
Hicks K., Leonard W. R. 2015. Developmental systems and inequality: Linking evolutionary and political–economic theory in biological anthropology. Current Anthropology 55:523–50.
Hollenbach J. P., Kuo C.-L., Mu J., Gerrard M., Gherlone N., Sylvester F., Ojukwu M., Cloutier M. M. 2019. Hair cortisol, perceived stress, and social support in mother–child dyads living in an urban neighborhood. Stress 22:632–39.
Hruschka D. J. 2021. One size does not fit all: How universal standards for normal height can hide deprivation and create false paradoxes. American Journal of Human Biology 33:e23552.
Hudson M., Garrison N. A., Sterling R., Caron N. R., Fox K., Yracheta J., Anderson J., Wilcox P., Arbour L., Brown A., Taualii M., Kukutai T., Haring R., Te Aika B., Baynam G. S., Dearden P. K., Chagné D., Malhi R. S., Garba I., Tiffin N., Bolnick D., Stott M., Rolleston A. K., Ballantyne L. L., Lovett R., David-Chavez D., Martinez A., Sporle A., Walter M., Reading J., Carroll S. R. 2020. Rights, interests and expectations: Indigenous perspectives on unrestricted access to genomic data. Nature Reviews Genetics 21:377–84.
Ice G. H., James G. D., eds. 2007. Measuring Stress in Humans: A Practical Guide for the Field. New York: Cambridge University Press.
James G. D., Gerber L. M. 2018. Measuring arterial blood pressure in humans: Auscultatory and automatic measurement techniques for human biological field studies. American Journal of Human Biology 30:e23063.
Juster R. P., McEwen B. S., Lupien S. J. 2010. Allostatic load biomarkers of chronic stress and impact on health and cognition. Neuroscience & Biobehavioral Reviews 35:2–16.
Kaiser B. N., Kohrt B. A., Keys H. M., Khoury N. M., Brewster A.-R. T. 2013. Strategies for assessing mental health in Haiti: Local instrument development and transcultural translation. Transcultural Psychiatry 50:532–58.
Kaltsas G. A., Chrousos G. P. 2007. The neuroendocrinology of stress. In Handbook of Psychophysiology. 3rd ed., edited by Cacioppo J. T., Tassinary L. G., Berntson G., 303–18. New York: Cambridge University Press.
Kohrt B. A., Worthman C. M., Adhikari R. P., Luitel N. P., Arevalo J. M. G., Ma J., McCreath H., Seeman T. E., Crimmins E. M., Cole S. W. 2016. Psychological resilience and the gene regulatory impact of posttraumatic stress in Nepali child soldiers. Proceedings of the National Academy of Sciences of the United States of America 113:8156–61.
Krieger N. 2001. Theories for social epidemiology in the 21st century: An ecosocial perspective. International Journal of Epidemiology 30:668–77.
Leatherman T., Goodman A. H. 2011. Critical biocultural approaches in medical anthropology. In A Companion to Medical Anthropology, edited by Singer M., Erickson P. I., 29–48. West Sussex, UK: Wiley-Blackwell.
Leatherman T., Goodman A. H. 2020. Building on the biocultural syntheses: 20 years and still expanding. American Journal of Human Biology 32:e23360.
Link B. G., Phelan J. C. 1995. Social conditions as fundamental causes of disease. Journal of Health and Social Behavior (extra issue):80–94.
Marioni R. E., Harris S. E., Shah S., McRae A. F., von Zglinicki T., Martin-Ruiz C., Wray N. R., Visscher P. M., Deary I. J. 2016. The epigenetic clock and telomere length are independently associated with chronological age and mortality. International Journal of Epidemiology 45:424–32.
Martin M. A. 2019. Biological anthropology in 2018: Grounded in theory, questioning contexts, embracing innovation. American Anthropologist 121:417–30.
McDade T. W. 2002. Status incongruity in Samoan youth: A biocultural analysis of culture change, stress, and immune function. Medical Anthropology Quarterly 16:123–50.
McDade T. W., Harris K. M. 2018. The biosocial approach to human development, behavior, and health across the life course. The Russell Sage Foundation Journal of the Social Sciences 4:2–26.
McDade T. W., Stallings J. F., Worthman C. M. 2000. Culture change and stress in western Samoan youth: Methodological issues in the cross-cultural study of stress and immune function. American Journal of Human Biology 12:792–802.
McDade T. W., Williams S., Snodgrass J. J. 2007. What a drop can do: Dried blood spots as a minimally invasive method for integrating biomarkers into population-based research. Demography 44:899–925.
McEwen B. S. 1998. Stress, adaptation, and disease: Allostasis and allostatic load. Annals of the New York Academy of Sciences 840:33–44.
McEwen B. S. 2012. Brain on stress: How the social environment gets under the sin. Proceedings of the National Academy of Sciences 109:17180–5.
McGarvey S. T., Baker P. T. 1979. The effects of modernization and migration on Samoan blood pressures. Human Biology 51:461–79.
Meloni M. 2014. The social brain meets the reactive genome: Neuroscience, epigenetics and the new social biology. Frontiers in Human Neuroscience 8:309.
Mendenhall E., Yarris K., Kohrt B. A. 2016. Utilization of standardized mental health assessments in anthropological research: Possibilities and pitfalls. Culture, Medicine, and Psychiatry 40:726–45.
Mulligan C., D’Errico N., Stees J., Hughes D. 2012. Methylation changes at NR3C1 in newborns associate with maternal prenatal stress exposure and newborn birth weight. Epigenetics 7:853–7.
Nelson R. G. 2016. Residential context, institutional alloparental care, and child growth in Jamaica. American Journal of Human Biology 28:493–502.
Nelson R. G. 2018. Stress and growth. In The International Encyclopedia of Biological Anthropology, edited by Trevathan W., 1490–4. New York: Wiley.
Niewöhner J., Lock M. 2018. Situating local biologies: Anthropological perspectives on environment/human entanglements. BioSocieties 13:681–97.
Non A. L., Gravlee C. C., Mulligan C. J. 2012. Education, genetic ancestry, and blood pressure in African Americans and Whites. American Journal of Public Health 102:155–65.
Olstad D. L., Ball K., Wright C., Abbott G., Brown E., Turner A. I. 2016. Hair cortisol levels, perceived stress and body mass index in women and children living in socioeconomically disadvantaged neighborhoods: The READI study. Stress 19:158–67.
Oths K. S. 1999. Debilidad: A biocultural assessment of an embodied Andean illness. Medical Anthropology Quarterly 13:286–315.
Pearlin L. I., Lieberman M., Menaghan E., Mullan J. 1981. The stress process. Journal of Health and Social Behavior 22:337–56.
Piperata B. A., Salazar M., Schmeer K. K., Herrera-Rodríguez A. 2020. Tranquility is a child with a full belly: Pathways linking food insecurity and maternal mental health in Nicaragua. Ecology of Food and Nutrition 59:79–103.
Piperata B. A., Schmeer K. K., Herrera-Rodrigues A., Mariano V., Torres S. 2016. Food insecurity and maternal mental health in Nicaragua: Potential limitations on the moderating role of social support. Social Science and Medicine 171:9–17.
Pollard T. M., Ward G. A., Thornley J., Wooster G., Wooster J., Panter‐Brick C. 2000. Modernisation and children’s blood pressure: On and off the tourist trail in Nepal. American Journal of Human Biology 12:478–86.
Radloff L. S. 1977. The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement 1:385–401.
Rej P. H., HEAT Steering Committee, Gravlee C. C., Mulligan C. J. 2020. Shortened telomere length is associated with unfair treatment attributed to race in African Americans living in Tallahassee, Florida. American Journal of Human Biology 32:e23375.
Rentscher K. E., Carroll J. E., Mitchell C. 2020. Psychosocial stressors and telomere length: A current review of the science. Annual Review of Public Health 41:223–45.
Reynolds A. Z., Wander K., Sum C.-Y., Su M., Thompson M. E., Hooper P. L., Li H., Shenk M., Starkweather K., Blumenfield T., Mattison S. 2020. Matriliny reverses gender disparities in inflammation and hypertension among the Mosuo of China. Proceedings of the National Academy of Sciences 117:30324–7.
Roberts D. E., Rollins O. 2020. Why sociology matters to race and biosocial science. Annual Review of Sociology 46:195–214.
Robinson D. F. 2015. Biodiversity, Access and Benefit-Sharing: Global Case Studies. New York: Routledge.
Ryan C. P. 2020. “Epigenetic clocks”: Theory and applications in human biology. American Journal of Human Biology 33:e23488.
Sapolsky R. M. 1998. Why Zebras Don’t Get Ulcers—A Guide to Stress, Stress-Related Disorders and Coping. New York: W.H. Freeman Publishers.
Sapolsky R. M. 2004. Social status and health in humans and other animals. Annual Reviews in Anthropology 33:393–418.
Schell L. M., Tarbell A. M. 1998. A partnership study of PCBs and the health of Mohawk youth: Lessons from our past and guidelines for our future. Environmental Health Perspectives 106:833–40.
Scotch N. A. 1963. Sociocultural factors in the epidemiology of Zulu hypertension. American Journal of Public Health and the Nation’s Health 53:1205–13.
Shattuck-Heidorn H., Reiches M. W., Prentice A. M., Moore S. E., Ellison P. T. 2017. Energetics and the immune system: Trade-offs associated with non-acute levels of CRP in adolescent Gambian girls. Evolution, Medicine, and Public Health 1:27–38.
Silva H. P., Padez C., Moura E. A. F., Filgueiras L. A. 2016. Obesity, hypertension, social determinants of health and the epidemiologic transition among traditional Amazonian populations. Annals of Human Biology 43:371–81.
Singer M. K., Dressler W., George S., Baquet C. R., Bell R. A., Burhansstipanov L., Burke N. J., Dibble S., Elwood W., Garro L. 2016. Culture: The missing link in health research. Social Science and Medicine 170:237–46.
Snodgrass J. G., Lacy M. G., Upadhyay C. 2017. Developing culturally sensitive affect scales for global mental health research and practice: emotional balance, not named syndromes, in Indian Adivasi subjective well-being. Social Science & Medicine 187:174–83.
Steffen P. R., Smith T. B., Larson M., Butler L. 2006. Acculturation to Western society as a risk factor for high blood pressure: A meta-analytic review. Psychosomatic Medicine 68:386–97.
Steptoe A., Kivimäki M. 2013. Stress and cardiovascular disease: An update on current knowledge. Annual Review of Public Health 34:337–54.
Stinson S., Bogin B., Huss-Ashmore R., O’Rurke D., eds. 2000. Human Biology: An Evolutionary and Biocultural Perspective. New York: Wiley.
Swales D. A., Stout-Oswald S. A., Glynn L. M., Sandman C., Wing D. A., Poggi Davis E. 2018. Exposure to traumatic events in childhood predicts cortisol production among high risk pregnant women. Biological Psychology 139:186–92.
Tallman P. 2018. “Now we live for the money”: Shifting markers of status, stress, and immune function in the Peruvian Amazon. Ethos 46:134–57.
Taylor S. E., Repetti R. L., Seeman T. 1997. Health psychology: What is an unhealthy environment and how does it get under the skin? Annual Review of Psychology 48:411–47.
Thayer Z. M., Kuzawa C. W. 2014. Early origins of health disparities: Material deprivation predicts maternal evening cortisol in pregnancy and offspring cortisol reactivity in the first few weeks of life. American Journal of Human Biology 26:723–30.
Thayer Z. M., Kuzawa C. W., 2015. Ethnic discrimination predicts poor self-rated health and cortisol in pregnancy: Insights from New Zealand. Social Science and Medicine 128:36–42.
Thayer Z. M., Non A. L. 2015. Anthropology meets epigenetics: Current and future directions. American Anthropologist 117:722–35.
Vagnoli L., Caprilli S., Vernucci C., Zagni S., Mugnai F., Messeri A. 2015. Can presence of a dog reduce pain and distress in children during venipuncture? Pain Management Nursing 16:89–95.
Valeggia C. R., Snodgrass J. J. 2015. Health of indigenous peoples. Annual Review of Anthropology, 44:137–45.
Waldron I., Nowotarski M., Freimer M., Henry J. P., Post N., Witten C. 1982. Cross-cultural variation in blood pressure: A quantitative analysis of the relationships of blood pressure to cultural characteristics, salt consumption and body weight. Social Science and Medicine 16:419–30.
Worthman C. M., Costello E. J. 2009. Tracking biocultural pathways in population health: The value of biomarkers. Annals of Human Biology 36:281–97.
Worthman C. M., Kohrt B. 2005. Receding horizons of health: Biocultural approaches to public health paradoxes. Social Science and Medicine 61:861–78.
Wutich A. 2020. Water insecurity: An agenda for research and call to action for human biology. American Journal of Human Biology 32:e23345.
Zahran S., Snodgrass J. G., Maranon D. G., Upadhyay C., Granger D. A., Bailey S. M. 2015. Stress and telomere shortening among central Indian conservation refugees. Proceedings of the National Academy of Sciences 112:E928–36.

Cite article

Cite article

Cite article

OR

Download to reference manager

If you have citation software installed, you can download article citation data to the citation manager of your choice

Share options

Share

Share this article

Share with email
EMAIL ARTICLE LINK
Share on social media

Share access to this article

Create a link to share a read only version of this article with your colleagues and friends. For more information view the Sage Journals article sharing page.

Please read and accept the terms and conditions and check the box to generate a sharing link.

terms and conditions

Information, rights and permissions

Information

Published In

Article first published online: November 5, 2021
Issue published: November 2021

Rights and permissions

© The Author(s) 2021.
Request permissions for this article.

Authors

Affiliations

Alexandra Brewis
School of Human Evolution and Social Change, Arizona State University, Tempe, AZ, USA
Barbara A. Piperata
Department of Anthropology, The Ohio State University, Columbus, OH, USA
H. J. François Dengah, II
Department of Sociology and Anthropology, Utah State University, Logan, UT, USA
William W. Dressler
Department of Anthropology, University of Alabama, Tuscaloosa, AL, USA
Melissa A. Liebert
Department of Anthropology, Northern Arizona University, Flagstaff, AZ, USA
Siobhán M. Mattison
Department of Anthropology, University of New Mexico, Albuquerque, NM, and National Science Foundation, Alexandria, VA, USA
Rosalyn Negrón
Department of Anthropology, University of Massachusetts, Boston, MA, USA
Robin Nelson
School of Human Evolution and Social Change, Arizona State University, Tempe, AZ, USA
Kathryn S. Oths
Department of Anthropology, University of Alabama, Tuscaloosa, AL, USA
Jeffrey G. Snodgrass
Department of Anthropology and Geography, Colorado State University, Fort Collins, CO, USA
Susan Tanner
Department of Anthropology, University of Georgia, Athens, GA, USA
Zaneta Thayer
Department of Anthropology, Dartmouth College, Hanover, NH, USA
Katherine Wander
Department of Anthropology, Binghamton University (SUNY), Binghamton, NY, USA
Clarence C. Gravlee
Department of Anthropology, University of Florida, Gainesville, FL, USA

Notes

Alexandra Brewis, School of Human Evolution and Social Change, Arizona State University, 900 S Cady Mall, Tempe, AZ 85287-2402, USA. Email: [email protected]

Metrics and citations

Metrics

Journals metrics

This article was published in Field Methods.

VIEW ALL JOURNAL METRICS

Article usage*

Total views and downloads: 1352

*Article usage tracking started in December 2016


Articles citing this one

Receive email alerts when this article is cited

Web of Science: 5 view articles Opens in new tab

Crossref: 0

  1. Challenges and opportunities in rapid disaster research: lessons from ...
    Go to citation Crossref Google Scholar
  2. Applying minimally invasive biomarkers of chronic stress across comple...
    Go to citation Crossref Google Scholar
  3. Research Design and Methods in Medical Anthropology
    Go to citation Crossref Google Scholar

Figures and tables

Figures & Media

Tables

View Options

View options

PDF/ePub

View PDF/ePub

Get access

Access options

If you have access to journal content via a personal subscription, university, library, employer or society, select from the options below:


Alternatively, view purchase options below:

Purchase 24 hour online access to view and download content.

Access journal content via a DeepDyve subscription or find out more about this option.