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

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          Abstract

          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.

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          Most cited references65

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          The social determinants of health: coming of age.

          In the United States, awareness is increasing that medical care alone cannot adequately improve health overall or reduce health disparities without also addressing where and how people live. A critical mass of relevant knowledge has accumulated, documenting associations, exploring pathways and biological mechanisms, and providing a previously unavailable scientific foundation for appreciating the role of social factors in health. We review current knowledge about health effects of social (including economic) factors, knowledge gaps, and research priorities, focusing on upstream social determinants-including economic resources, education, and racial discrimination-that fundamentally shape the downstream determinants, such as behaviors, targeted by most interventions. Research priorities include measuring social factors better, monitoring social factors and health relative to policies, examining health effects of social factors across lifetimes and generations, incrementally elucidating pathways through knowledge linkage, testing multidimensional interventions, and addressing political will as a key barrier to translating knowledge into action.
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            Multilevel analyses of neighbourhood socioeconomic context and health outcomes: a critical review.

            Interest in the effects of neighbourhood or local area social characteristics on health has increased in recent years, but to date the existing evidence has not been systematically reviewed. Multilevel or contextual analyses of social factors and health represent a possible reconciliation between two divergent epidemiological paradigms-individual risk factor epidemiology and an ecological approach. Keyword searching of Index Medicus (Medline) and additional references from retrieved articles. All original studies of the effect of local area social characteristics on individual health outcomes, adjusted for individual socioeconomic status, published in English before 1 June 1998 and focused on populations in developed countries. The methodological challenges posed by the design and interpretation of multilevel studies of local area effects are discussed and results summarised with reference to type of health outcome. All but two of the 25 reviewed studies reported a statistically significant association between at least one measure of social environment and a health outcome (contextual effect), after adjusting for individual level socioeconomic status (compositional effect). Contextual effects were generally modest and much smaller than compositional effects. The evidence for modest neighbourhood effects on health is fairly consistent despite heterogeneity of study designs, substitution of local area measures for neighbourhood measures and probable measurement error. By drawing public health attention to the health risks associated with the social structure and ecology of neighbourhoods, innovative approaches to community level interventions may ensue.
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              Social conditions as fundamental causes of disease.

              Over the last several decades, epidemiological studies have been enormously successful in identifying risk factors for major diseases. However, most of this research has focused attention on risk factors that are relatively proximal causes of disease such as diet, cholesterol level, exercise and the like. We question the emphasis on such individually-based risk factors and argue that greater attention must be paid to basic social conditions if health reform is to have its maximum effect in the time ahead. There are two reasons for this claim. First we argue that individually-based risk factors must be contextualized, by examining what puts people at risk of risks, if we are to craft effective interventions and improve the nation's health. Second, we argue that social factors such as socioeconomic status and social support are likely "fundamental causes" of disease that, because they embody access to important resources, affect multiple disease outcomes through multiple mechanisms, and consequently maintain an association with disease even when intervening mechanisms change. Without careful attention to these possibilities, we run the risk of imposing individually-based intervention strategies that are ineffective and of missing opportunities to adopt broad-based societal interventions that could produce substantial health benefits for our citizens.
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                Author and article information

                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                25 March 2013
                April 2013
                : 10
                : 4
                : 1186-1201
                Affiliations
                [1 ]Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON M5T 3M6, Canada; E-Mail: heatherlynn.white@ 123456mail.utoronto.ca
                [2 ]Institute for Clinical Evaluative Sciences, Toronto, ON M4N 3M5, Canada; E-Mails: rahim.moineddin@ 123456utoronto.ca (R.M.); mathesonf@ 123456smh.ca (F.I.M.)
                [3 ]Centre for Research on Inner City Health, The Keenan Research Centre in the Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, ON M5C 1N8, Canada
                [4 ]Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5T 3M7, Canada
                [5 ]Department of Population, Reproductive and Family Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
                [6 ]Department of Family and Community Medicine, University of Toronto, Toronto, ON M5G 1V7, Canada
                Author notes
                [* ] Author to whom correspondence should be addressed; E-Mail: co’campop@ 123456smh.ca ; Tel.: +1-416-864-5403; Fax: +1-416-864-5485.
                Article
                ijerph-10-01186
                10.3390/ijerph10041186
                3709312
                23528813
                0fb028d5-9af1-4994-a89c-704c230bc7db
                © 2013 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/3.0/).

                History
                : 06 February 2013
                : 13 March 2013
                : 19 March 2013
                Categories
                Article

                Public health
                social determinants,socioeconomic position,multinomial regression,multilevel modeling,health inequities

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