Effect of cross-level interaction between individual and neighborhood socioeconomic status on adult mortality rates

Am J Public Health. 2006 Dec;96(12):2145-53. doi: 10.2105/AJPH.2004.060970. Epub 2006 Oct 31.


Objective: We examined whether the influence of neighborhood-level socioeconomic status (SES) on mortality differed by individual-level SES.

Methods: We used a population-based, mortality follow-up study of 4476 women and 3721 men, who were predominately non-HIspanic White and aged 25-74 years at baseline, from 82 neighborhoods in 4 California cities. Participants were surveyed between 1979 and 1990, and were followed until December 31, 2002 (1148 deaths; mean follow-up time 17.4 years). Neighborhood SES was defined by 5 census variables and was divided into 3 levels. Individual SES was defined by a composite of educational level and household income and was divided into tertiles.

Results: Death rates among women of low SES were highest in high-SES neighborhoods (1907/100000 person-years), lower in moderate-SES neighborhoods (1323), and lowest in low-SES neighborhoods (1128). Similar to women, rates among men of low SES were 1928, 1646, and 1590 in high-, moderate-, and low-SES neighborhoods, respectively. Differences were not explained by individual-level baseline risk factors.

Conclusion: The disparities in mortality by neighborhood of residence among women and men of low SES demonstrate that they do not benefit from the higher quality of resources and knowledge generally associated with neighborhoods that have higher SES.

Publication types

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

MeSH terms

  • Adult
  • Aged
  • California / epidemiology
  • Cause of Death
  • Censuses
  • Educational Status
  • Female
  • Geography
  • Health Services Accessibility
  • Humans
  • Income / statistics & numerical data
  • Male
  • Middle Aged
  • Mortality*
  • Poverty Areas*
  • Residence Characteristics / classification*
  • Residence Characteristics / statistics & numerical data
  • Social Class*
  • Survival Analysis
  • Urban Health / statistics & numerical data*
  • Vulnerable Populations*