Associations between socioeconomic status and allostatic load: effects of neighborhood poverty and tests of mediating pathways

Am J Public Health. 2012 Sep;102(9):1706-14. doi: 10.2105/AJPH.2011.300412. Epub 2012 Feb 16.


Objectives: We examined relationships between neighborhood poverty and allostatic load in a low- to moderate-income multiracial urban community. We tested the hypothesis that neighborhood poverty is associated with allostatic load, controlling for household poverty. We also examined the hypotheses that this association was mediated by psychosocial stress and health-related behaviors.

Methods: We conducted multilevel analyses using cross-sectional data from a probability sample survey in Detroit, Michigan (n = 919) and the 2000 US Census. The outcome measure was allostatic load. Independent variables included neighborhood and household poverty, psychosocial stress, and health-related behaviors. Covariates included neighborhood and individual demographic characteristics.

Results: Neighborhood poverty was positively associated with allostatic load (P < .05), independent of household poverty and controlling for potential confounders. Relationships between neighborhood poverty were mediated by self-reported neighborhood environment stress but not by health-related behaviors.

Conclusions: Neighborhood poverty is associated with wear and tear on physiological systems, and this relationship is mediated through psychosocial stress. These relationships are evident after accounting for household poverty levels. Efforts to promote health equity should focus on neighborhood poverty, associated stressful environmental conditions, and household poverty.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • African Continental Ancestry Group
  • Allostasis / physiology*
  • Cross-Sectional Studies
  • European Continental Ancestry Group
  • Female
  • Health Behavior
  • Health Surveys
  • Hispanic Americans
  • Humans
  • Male
  • Michigan / epidemiology
  • Middle Aged
  • Poverty / statistics & numerical data*
  • Regression Analysis
  • Residence Characteristics / statistics & numerical data*
  • Social Class*
  • Stress, Psychological / epidemiology
  • Urban Population