Does allostatic load calculation method matter? Evaluation of different methods and individual biomarkers functioning by race/ethnicity and educational level

Howard, Jeffrey T.; Sparks, P. Johnelle

doi:10.1002/ajhb.22843

Cited by 48 publications

(63 citation statements)

References 67 publications

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“…Although the operational definitions of allostatic load vary across studies [28], the allostatic load metric is considered a robust estimator of multi-system dysregulation in population studies [30]. While it is valuable to examine allostatic load as a composite score, examining dysregulation within the individual allostatic load systems can help identify underlying pathways through which the allostatic load response is manifested, according to the population’s specific characteristics [30]. As such, we examined whether the chronic stress associated with weight discrimination impacts both allostatic load and seven individual systems used to define allostatic load to elucidate the underlying pathways through which weight discrimination promotes dysregulation.…”

Section: Introductionmentioning

confidence: 99%

Perceived Weight Discrimination and 10-Year Risk of Allostatic Load Among US Adults

2016

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Background Discrimination promotes multisystem physiological dysregulation termed allostatic load, which predicts morbidity and mortality. It remains unclear whether weight-related discrimination influences allostatic load. Purpose The aim of this study was to prospectively examine 10-year associations between weight discrimination, allostatic load, and its components among adults 25–75 years in the Midlife Development in the US Biomarker Substudy. Methods Participants with information on weight discrimination were analyzed (n=986). At both timepoints, participants self-reported the frequency of perceived weight discrimination across nine scenarios as “never/rarely” (scored as 0), “sometimes” (1), or “often” (2). The two scores were averaged and then dichotomized as “experienced” versus “not experienced” discrimination. High allostatic load was defined as having ≥3 out of 7 dysregulated systems (cardiovascular, sympathetic/ parasympathetic nervous systems, hypothalamic pituitary axis, inflammatory, lipid/metabolic, and glucose metabolism), which collectively included 24 biomarkers. Relative risks (RR) were estimated from multivariate models adjusted for sociodemographic and health characteristics, other forms of discrimination, and BMI. Results Over 41% of the sample had obesity, and 6% reported weight discrimination at follow-up. In multivariable-adjusted analyses, individuals who experienced (versus did not experience) weight discrimination had twice the risk of high allostatic load (RR, 2.07; 95 % CI, 1.21; 3.55 for baseline discrimination; 2.16, 95 % CI, 1.39; 3.36 for long-term discrimination). Weight discrimination was associated with lipid/ metabolic dysregulation (1.56; 95 % CI 1.02, 2.40), glucose metabolism (1.99; 95 % CI 1.34, 2.95), and inflammation (1.76; 95 % CI 1.22, 2.54), but no other systems. Conclusions Perceived weight discrimination doubles the 10-year risk of high allostatic load. Eliminating weight stigma may reduce physiological dysregulation, improving obesity-related morbidity and mortality.

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Section: Introductionmentioning

confidence: 99%

Perceived Weight Discrimination and 10-Year Risk of Allostatic Load Among US Adults

2016

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“…AL is conceptualized as a latent construct that is best represented using a number of measured, biological indicator variables that represent stress‐mediated systemic physiological dysregulation (Howard & Sparks, ). In past research, a key determinant for selection of indicators included in AL measures has been the availability of and logistical access to various biomarkers that are believed to represent the key body systems involved in development of AL.…”

Section: Selection Of Al Indicatorsmentioning

confidence: 99%

Testing allostatic load factor structures among adolescents: A structural equation modeling approach

King

Garnier‐Villarreal

Simanek³

et al. 2019

American J Hum Biol

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Objectives: Allostatic load (AL) represents cumulative biological "wear and tear" that results from chronic stress exposure over time, ultimately increasing risk for chronic disease. A consensus is lacking regarding the best operationalization of AL, particularly for younger, less studied populations. The purpose of this study was to test multiple hypothesized factor structures for AL to determine the best measurement approach for adolescents. Methods: We analyzed biologic data for 1900 adolescents aged 12-18 from four waves (2003-2010) of the National Health and Nutrition Examination Survey. AL indicator variables included cardiovascular (systolic BP, creatinine), metabolic (HDL, LDL, triglycerides, insulin, fasting glucose, HA1C, body mass index [BMI], waist circumference), and immune (albumin, CRP, WBC, EBV) biomarkers. Structural equation modeling was used to test the fit of five hypothesized AL factor structures.Results: The data best supported a unidimensional factor structure, where the AL construct directly influenced each of the indicator variables. All but two of the indicators (HDL and albumin) had positive factor loadings, thus, as AL increases the values for those indicators also increase. The best indicators for AL were those measuring metabolic dysregulation, with BMI and waist circumference having the highest factor loadings (0.95 and 0.982, respectively). Conclusions: BMI and waist circumference may be some of the earliest clinical signs of elevated AL that manifest among adolescents. Future research should aim to include neuroendocrine biomarkers in their AL measures to have a more robust estimation of AL in younger populations.

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“…Differences in educational attainment may even influence which mediators directly reflect allostatic load development. Recently,Howard and Sparks (2016) reported that those with lower educational attainment had allostatic load scores primarily loading on both metabolic and immune biomarkers, while allostatic load primarily loaded on metabolic mediators only in those with higher educational attainment. SES influences how individuals interact with their cultures and environments, and such differences are reflected in variable assessments of allostatic load across social settings(McEwen & Seeman, 1999).…”

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confidence: 99%

“…Mediators contributing to allostatic load also may vary by ethnicity. For example, non-Hispanic "blacks" may have allostatic load scores primarily influenced by inflammatory processes whereas allostatic load in non-Hispanic "whites" may be driven mostly by metabolic mediators(Howard & Sparks, 2016).Allostatic load indices also are influenced by DNA variation. For example, telomere length is negatively associated with stressor exposure.…”

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confidence: 99%

Allostatic load and biological anthropology

Edes

Crews

2017

American J Phys Anthropol

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Multiple stressors affect developing and adult organisms, thereby partly structuring their phenotypes. Determining how stressors influence health, well-being, and longevity in human and nonhuman primate populations are major foci within biological anthropology. Although much effort has been devoted to examining responses to multiple environmental and sociocultural stressors, no holistic metric to measure stress-related physiological dysfunction has been widely applied within biological anthropology. Researchers from disciplines outside anthropology are using allostatic load indices (ALIs) to estimate such dysregulation and examine life-long outcomes of stressor exposures, including morbidity and mortality. Following allostasis theory, allostatic load represents accumulated physiological and somatic damage secondary to stressors and senescent processes experienced over the lifespan. ALIs estimate this wear-and-tear using a composite of biomarkers representing neuroendocrine, cardiovascular, metabolic, and immune systems. Across samples, ALIs are associated significantly with multiple individual characteristics (e.g., age, sex, education, DNA variation) of interest within biological anthropology. They also predict future outcomes, including aspects of life history variation (e.g., survival, lifespan), mental and physical health, morbidity and mortality, and likely health disparities between groups, by stressor exposures, ethnicity, occupations, and degree of departure from local indigenous life ways and integration into external and commodified ones. ALIs also may be applied to similar stress-related research areas among nonhuman primates. Given the reports from multiple research endeavors, here we propose ALIs may be useful for assessing stressors, stress responses, and stress-related dysfunction, current and long-term cognitive function, health and well-being, and risk of early mortality across many research programs within biological anthropology. K E Y W O R D Saging, allostasis, frailty, growth and development, nonhuman primates, senescence, stress | I N T R O D U C T I O NTraditional research foci within biological anthropology include variations in stress, morbidity, and mortality (for reviews, see Ice & James, 2007;Little, 2010). Despite this long-term focus, the field continues to pursue a reliable, relatively easy to apply metric for assessing lifetime stress and stress-related outcomes. We suggest incorporating the theory of allostasis and methods for assessing allostatic load within anthropological theory and methodology to aid in closing this gap. As a theory, allostasis was developed to explain how mammalian physiological responses to stressors in their environments evolved to maximize the probability of survival while limiting somatic damage (Korte, Koolhaas, Wingfield, & McEwen, 2005;McEwen & Stellar, 1993;McEwen & Wingfield, 2003;Sterling, 2004Sterling, , 2012Sterling & Eyer, 1988). Unfortunately, such beneficial defensive responses come at a cost and, over time, repeated allostatic activi...

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Does allostatic load calculation method matter? Evaluation of different methods and individual biomarkers functioning by race/ethnicity and educational level

Cited by 48 publications

References 67 publications

Perceived Weight Discrimination and 10-Year Risk of Allostatic Load Among US Adults

Perceived Weight Discrimination and 10-Year Risk of Allostatic Load Among US Adults

Testing allostatic load factor structures among adolescents: A structural equation modeling approach

Allostatic load and biological anthropology

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