Читать книгу The Science of Health Disparities Research - Группа авторов - Страница 35

The concept of allostatic load and the biomarkers used to study it have been widely accepted in studies of how behavioral, social, and biological exposures combine to influence the wear and tear on the human body and predispose it to disease. Numerous biomarkers are now in frequent use in many studies and are gradually providing a clearer picture of the role of stress and allostatic load in health disparities [3, 29]. For example, a review by Rodriquez et al. describes markers of allostatic load (e.g., systolic and diastolic blood pressure; hemoglobin A_1c; C‐reactive protein; dehydroepiandrosterone; cortisol; telomeres) representing multiple biological systems (e.g., cardiovascular, metabolic, inflammatory, neuroendocrine) that are derived from research among minority and disparity populations (see Table 2.1) [30]. Research is also showing that measures of allostasis differ by racial/ethnic group and, therefore, need to have a range. For example, cardiometabolic risk factors for Whites with a body mass index (BMI) of 25 appeared at a much lower BMI than in patients from other groups: 22.9 for African Americans, 21.5 for Hispanics, 20.9 for Chinese, and 19.6 for South Asians. After controlling for lifestyle factors such as smoking, alcohol intake, exercise, and diet, only 21% of Whites had cardiometabolic risk factors but normal BMIs, whereas 39% of Hispanic Americans and 44% of South Asians had a normal weight but a higher risk for chronic diseases that are usually associated with being overweight [31].

Table 2.1 Representative list of biomarkers for allostatic load [3, 22].

Biomarkers of allostatic load
Biomarker	Function	Typical measures
Cardiovascular
Systolic blood pressure	Cardiovascular activity	Mean of 3, resting, (mm Hg)
Diastolic blood pressure	Cardiovascular activity	Mean of 3, resting, (mm Hg)
Heart rate	Cardiovascular activity	Mean of 3, resting, (bpm)
Peak expiratory flow	Lung function	Highest of 3, Peak flow, (l min−1)
Metabolic
HDL, mmol l−1	Low levels, unfavorable	Serum, nonfasting, (mmol l−1)
LDL	Low levels, favorable	Serum, nonfasting, (mmol l−1)
Triglyceride	High levels, unfavorable	Serum, nonfasting, (mmol l−1)
Total cholesterol/HDL	Low levels, favorable	Ratio <5.9
BMI	Measure of adiposity	BMI >30
WHR (waist: hip)	Abdominal adiposity	WHR >9.94
HbA1c	Measure of insulin resistance	mmol mol−1
Inflammation
IGF‐1	Inflammation	Serum nonfasting, (nmol l−1)
Fibrinogen	Blood clotting, thrombosis risk	Serum, nonfasting, (g l−1)
IgE	Type I hypersensitivity	KU l−1
CRP	Acute inflammation	Citrated plasma, (mg l−1)
Neuroendocrine
DHEA‐S	HPA antagonist	Urinary, (ng ml−1)
Cortisol t1	HPA function	Salivary, 45 after awakening, (nmol l−1)
Cortisol t2	HPA function	Salivary, 3 after awakening, (nmol l−1)
Epigenetic
DNA methylation	Embedded cellular aging	Circulating white cells
Telomere shortening	Cellular aging	Circulating leukocytes

HDL, high density lipoprotein; LDL, low density lipoprotein; WHR, waist to hip ratio; CRP, C‐reactive protein; DHEA‐S, dihydroepiandosterone sulfate; HPA, hypothalamus pituitary adrenal axis.

Several cohort studies have documented clear associations between adverse childhood experiences and allostatic load for both men and women, with major influences on health behaviors, BMI, and socioeconomic factors in adult life [29]. Studies measuring allostatic load across ethnic and racial populations demonstrate how a multitude of social factors, including discrimination, can contribute to overall allostatic load, significantly alter health aging, and act as an early indicator of subsequent disease burden [32].

In the following sections, we provide examples of how such studies are increasing our understanding of causal mechanisms and how they impact health disparities and provide new and important insights for future interventions.