Elsevier

Social Science & Medicine

Volume 192, November 2017, Pages 66-73
Social Science & Medicine

Review article
A systematic review of allostatic load in relation to socioeconomic position: Poor fidelity and major inconsistencies in biomarkers employed

https://doi.org/10.1016/j.socscimed.2017.09.025Get rights and content

Highlights

  • Allostatic load (AL) describes the biological effect of “cumulative wear and tear”.

  • The AL concept is operationalised through biomarker measurement.

  • AL is used to elucidate the biological basis of socioeconomic health differences.

  • Definitions are inconsistent and often show poor fidelity to the original concept.

  • Interpretation of AL should be subject to critical scrutiny.

Abstract

Background

The association between disease and socioeconomic position (SEP) is well established. Allostatic load (AL), or physiological ‘wear and tear’, is a concept that aims to elucidate the biological consequences of stress that may underlie these associations. The primary objective of this paper is to review the biomarkers and methods used to operationalise the concept of AL in studies analysing the association between AL and SEP.

Methods

Four databases (Embase, Global Health, MEDLINE, and PsychINFO) were searched using terms related to AL, biomarkers and SEP. Data extraction focused on the methods used to calculate AL indices. The frequency of pair-wise combinations of biomarkers were used to assess the level of overlap in AL definition between studies.

Results

Twenty-six studies analysing the association between AL and SEP were included. There was no consistent method of operationalizing AL across studies. Individual biomarkers and biological systems included in the AL index differed widely across studies, as did the method of calculating the AL index. All studies included at least one cardiovascular- and metabolic-related biomarker in AL indices, while only half of studies included at least one hypothalamic-pituitary-adrenal (HPA) axis biomarker and approximately one third an immune response-related biomarker. All but three studies found evidence of an association between lower SEP and higher AL.

Conclusions

Many studies lacked fidelity to the original concept of AL in which stress was considered central. The considerable variation in biomarkers used makes studies in this review difficult to compare. A more critical approach should be taken in the calculation of AL indices in particular to how far it captures the biological effects of psychosocial stress that may underlie socioeconomic differences in health.

Introduction

The social underpinnings of disease have been long acknowledged and an extensive body of literature has linked lower socioeconomic position (SEP) with adverse health outcomes (Marmot et al., 1991, Sapolsky, 2004, Taylor et al., 1997). The underlying mechanism for some diseases is better understood than others. For example, it is well established that in high income countries those of a lower SEP are more likely to smoke, be hypertensive and have increased cholesterol, which in turn results in an increased risk of cardiovascular disease (CVD) events (Fuller et al., 1983, Sterling and Eyer, 1981, Lynch, 2006, Kivimäki et al., 2008). However, the extent to which stress plays a role in the specific mechanisms through which social factors influence disease has remained elusive. Two key areas of research have emerged: one focused on how stress is related to behavioral mechanisms of disease and the other on the biological mechanisms responsible for translating stress into disease (Harbuz, 1999, Friedman et al., 1958, Kornitzer and Kittel, 1986, Shah and Cole, 2010). The latter has emphasized understanding how the body internalizes an external stressor on a physiological level and how well a person can adapt to changes in his or her environment. Allostasis is a concept describing the normal process of how the human body adapts in response to a given stimulus (Sterling and Eyer, 1988). Allostatic load (AL) is defined as the physiological “wear and tear” a person experiences across his or her life, for instance chronically elevated blood pressure resulting from a lifetime of occupational strain (McEwen and Stellar, 1993).

According to the original AL framework, stress hormones controlled by the hypothalamic-pituitary-adrenal (HPA) axis (e.g. cortisol, epinephrine, and norepinephrine) are the “primary mediators” of AL, which in turn mediate “secondary effectors” such as blood pressure, lipid metabolism, and inflammation (McEwen and Stellar, 1993, Smith and Vale, 2006). Poor health conditions resulting from extreme values of primary mediators and secondary effectors are “tertiary outcomes” (e.g. coronary heart disease, decreased physical capacity, obesity or severe cognitive decline) (Karlamangla et al., 2002, Gruenewald et al., 2006, Gruenewald et al., 2015). In the first study to calculate an AL index, measurements of 10 biomarkers were combined from three biological domains (cardiovascular and metabolic systems, and HPA axis) (Seeman et al., 1997). For clarity, in this paper AL index refers to the quantifiable variable, while allostatic load refers to the conceptual framework devised by McEwen & Stellar (McEwen and Stellar, 1993).

Since the term allostatic load was first introduced in 1993, the number of studies on AL have grown considerably. Between 2010 and 2017 the number of papers in PubMed mentioning AL have more than tripled, with 110 studies published in 2016 alone (Corlan, 2004). However, researchers have not taken a consistent approach to the way they have operationalised the concept. If AL is intended to measure the physiological response to stress, then the inclusion of primary mediators, such as HPA axis biomarkers (or equivalent), in an AL index is intrinsic to its definition.

These methodological inconsistencies make comparisons across studies challenging. There is therefore a need to determine how researchers define AL in the literature and to see how different definitions affect associations between stress, AL, and disease. No prior study has quantified the heterogeneity in AL indices. Previous reviews of AL, health disparities and outcomes have been performed, but none had a methodological focus, although some attention has been given to comparing different methods for how levels of constituent biomarkers should be arithmetically combined into a single index (Karlamangla et al., 2002, Seplaki et al., 2005, Seeman et al., 2001, Dowd and Simanek, 2009, Beckie, 2012, Mauss et al., 2015).

In this systematic review we have aimed to provide a comprehensive overview and discussion of the biomarker content and methods used to calculate AL in studies that have looked at its association with SEP. A secondary aim was to describe the associations of AL with SEP.

Section snippets

Search strategy & data extraction

The scope of this review was limited to the biological internalization of SEP and the effects of this stressor on AL, highlighting AL as a mechanism on the causal pathway between SEP and health outcomes (Fig. 1).

The literature review was restricted to peer-reviewed publications of human population studies that calculated an AL index and analysed the association between SEP as the main exposure and AL as the main outcome. Reviews, protocols, conference abstracts, and theoretical discussions were

Findings from the literature search

The search strategy outlined above identified 282 papers; five additional papers were included from cross-referencing previous systematic reviews resulting in 287 articles screened (Fig. 2). Thirty-one full text articles were reviewed after duplicate removal and title and abstract screening. Of these, five articles were excluded due to not reporting a direct measure of the association between AL and SEP, leaving a total of 26 articles. Of these 26, four analysed the National Health and

Discussion

We reviewed the methodologies used to operationalise the concept of allostatic load, a term intended to represent the biological “wear and tear” a person experiences throughout life. Our findings indicate there is no standard method of calculating an AL index in the literature on AL and SEP. Across the 26 studies in the literature review, there were 59 biomarkers combined in 20 different ways. Not only were studies dissimilar to one another, there was no study that used the same biomarkers as

References (62)

  • S.S. Merkin et al.

    Neighborhoods and cumulative biological risk profiles by race/ethnicity in a national sample of U.S. Adults: NHANES III

    Ann. Epidemiol.

    (2009 Mar)
  • B.K.W. Rainisch et al.

    Sociodemographic correlates of allostatic load among a national sample of adolescents: Findings from the National Health and Nutrition Examination Survey, 1999-2008

    J. Adolesc. Heal.

    (2013)
  • T. Robertson et al.

    The role of material, psychosocial and behavioral factors in mediating the association between socioeconomic position and allostatic load (measured by cardiovascular, metabolic and inflammatory markers)

    Brain Behav. Immun.

    (2015)
  • C.L. Seplaki et al.

    A comparative analysis of measurement approaches for physiological dysregulation in an older population

    Exp. Gerontol.

    (2005 May)
  • P. Sterling et al.

    Biological basis of stress-related mortality

    Soc. Sci. Med. Part E Med.

    (1981)
  • N.E. Adler et al.

    Socioeconomic inequalities in health: No easy solution

    JAMA

    (1993 Jun 23)
  • T.M. Beckie

    A systematic review of allostatic load, health, and health disparities

    Biol. Res. Nurs.

    (2012 Oct)
  • C.E. Bird et al.

    Neighbourhood socioeconomic status and biological ‘wear and tear’ in a nationally representative sample of US adults

    J. Epidemiol. Community Health

    (2010)
  • A.D. Corlan

    Medline Trend: Automated Yearly Statistics of PubMed Results for Any Query

    (2004)
  • J.B. Dowd et al.

    Socio-economic status, cortisol and allostatic load: a review of the literature

    Int. J. Epidemiol.

    (2009)
  • G.W. Evans et al.

    Childhood poverty, chronic stress, and adult working memory

    Proc. Natl. Acad. Sci. U. S. A.

    (2009)
  • M. Friedman et al.

    Changes in the serum cholesterol and blood clotting time in men subjected to cyclic variation of occupational stress

    Am. Hear Assoc. J.

    (1958)
  • E.M. Friedman et al.

    Early life adversity and adult biological risk profiles

    Psychosom. Med.

    (2015)
  • J.H. Fuller et al.

    Mortality from coronary heart disease and stroke in relation to degree of glycaemia: the Whitehall study

    Br. Med. J. Clin. Res. Ed.

    (1983 Sep 24)
  • C.R. Gale et al.

    Intelligence and socioeconomic position in childhood in relation to frailty and cumulative allostatic load in later life: the Lothian Birth Cohort 1936

    J Epidemiol Community Heal

    (2016)
  • L.C. Gallo et al.

    Espinosa de los Monteros K. Domains of chronic stress, lifestyle factors, and allostatic load in middle-aged Mexican-American women

    Ann. Behav. Med.

    (2011)
  • B. Galobardes et al.

    Measuring socioeconomic position in health research

    Br. Med. Bull.

    (2007)
  • T.L. Gruenewald et al.

    Combinations of Biomarkers Predictive of Later Life Mortality

    (2006)
  • T.L. Gruenewald et al.

    Does allostatic load underlie greater risk of coronary artery calcification in those of lower socioeconomic status?

    Psychosom. Med.

    (2015)
  • P.E. Gustafsson et al.

    Life-course accumulation of neighborhood disadvantage and allostatic load: empirical integration of three social determinants of health frameworks

    Am. J. Public Health

    (2014 May)
  • A.M. Hansen et al.

    Social gradient in allostatic load among Danish men and women in late midlife

    J. Aging Health

    (2014)
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