Estimating the Impact of Health-related Behaviors on Geographic Variation in Cardiovascular Mortality: A New Approach Based on the Synthesis of Ecological and Individual-level Data.

Background: Incidence of and mortality from cardiovascular disease (CVD) exhibit a strong geographical pattern, with inhabitants of more affluent neighborhoods showing a substantially lower risk of CVD mortality than inhabitants of deprived neighborhoods. Thus far, there is insufficient evidence as to what extent these differences can be attributed to differences in health-related behaviors.

Methods: Using a Hierarchical Related Regression approach, we combined individual and aggregate (ecological) data to investigate the extent to which small-area variation in CVD mortality in Dutch neighborhoods can be explained by several behavioral risk factors (i.e., smoking, drinking, overweight, and physical inactivity). The proposed approach combines the benefits of both an ecological analysis (in terms of data availability and statistical power) and an individual-level analysis (in terms of identification of the parameters and interpretation of the results).

Results: After correcting for differences in age and sex, accounting for differences in the behavioral risk factors reduces income-related inequalities in CVD mortality by approximately 30%.

Conclusions: Direct targeting of the excess prevalence of unhealthy behaviors in deprived neighborhoods is identified as a relevant strategy to reduce inequalities in CVD mortality. Our results also show that the proposed Hierarchical Related Regression approach provides a powerful method for the investigation of small-area variation in health outcomes.