Modeling the Cumulative Effects of Social Exposures on Health: Moving beyond Disease-Specific Models

International Journal of Environmental Research and Public Health

Heather L. White¹  Patricia O�mpo²  Rahim Moineddin² 

[1] Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON M5T 3M6, Canada; E-Mail:;Institute for Clinical Evaluative Sciences, Toronto, ON M4N 3M5, Canada; E-Mails:

关键词: social determinants;    socioeconomic position;    multinomial regression;    multilevel modeling;    health inequities;   

DOI  :  10.3390/ijerph10041186

来源: mdpi

【 摘 要 】

The traditional explanatory models used in epidemiology are “disease specific”, identifying risk factors for specific health conditions. Yet social exposures lead to a generalized, cumulative health impact which may not be specific to one illness. Disease-specific models may therefore misestimate social factors’ effects on health. Using data from the Canadian Community Health Survey and Canada 2001 Census we construct and compare “disease-specific” and “generalized health impact” (GHI) models to gauge the negative health effects of one social exposure: socioeconomic position (SEP). We use logistic and multinomial multilevel modeling with neighbourhood-level material deprivation, individual-level education and household income to compare and contrast the two approaches. In disease-specific models, the social determinants under study were each associated with the health conditions of interest. However, larger effect sizes were apparent when outcomes were modeled as compound health problems (0, 1, 2, or 3+ conditions) using the GHI approach. To more accurately estimate social exposures’ impacts on population health, researchers should consider a GHI framework.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.