Longitudinal analysis of the impact of neighborhood SES on incident coronary heart disease among women [presentation] Presentation uri icon
Overview
abstract
  • Objective: We assessed the relationship between neighborhood socioeconomic status (NSES) and incident coronary heart disease (CHD) among women, adjusting for individual sociodemographic characteristics, baseline health status and health behaviors. Study Design: Using 2-level hierarchical Cox proportional hazard regression models, we analyzed the Women’s Health Initiative Clinical Trial data, merged with tract-level Census data on neighborhood sociodemographic characteristics. Participants age 50-79 at baseline were recruited at 40 clinical and 36 satellite locations (1993-1998), and followed until at least March 2005. We examined three outcomes: time until first CHD event, time until CHD death or first MI, and time until CHD death. The NSES index included six educational and economic measures at the census tract-level. Population Studied: The sample (n= 68,132) was 81.7% non-Hispanic white, 10.3% non-Hispanic black, 4.2% Hispanic, and 3.8% other; 60.9% were married at baseline, 94.3% high school education or higher, and 64% had household incomes lower than $50,000. Principal Findings: Women residing in lower NSES neighborhoods experienced shorter time to first CHD event or CHD death/MI, after controlling for a number of sociodemographic characteristics and census tract-level characteristics. After additionally controlling for baseline health status and health behaviors, the effect of NSES decreased but remained statistically significant only for CHD death/MI and first CHD event. The relationship between NSES and incident CHD appeared to be mediated by baseline health status and health behaviors. Conclusions: Living in a lower NSES neighborhood was independently associated with greater CHD risk, above and beyond individual-level baseline characteristics.

  • Research
    keywords
  • Cardiovascular Diseases
  • Heart Diseases
  • Research Methods
  • Risk Factors
  • Socioeconomic Factors