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      Evaluating the evidence for models of life course socioeconomic factors and cardiovascular outcomes: a systematic review

      research-article
      1 , , 1 , 1
      BMC Public Health
      BioMed Central

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          Abstract

          Background

          A relatively consistent body of research supports an inverse graded relationship between socioeconomic status (SES) and cardiovascular disease (CVD). More recently, researchers have proposed various life course SES hypotheses, which posit that the combination, accumulation, and/or interactions of different environments and experiences throughout life can affect adult risk of CVD. Different life course designs have been utilized to examine the impact of SES throughout the life course. This systematic review describes the four most common life course hypotheses, categorizes the studies that have examined the associations between life course SES and CVD according to their life course design, discusses the strengths and weaknesses of the different designs, and summarizes the studies' findings.

          Methods

          This research reviewed 49 observational studies in the biomedical literature that included socioeconomic measures at a time other than adulthood as independent variables, and assessed subclinical CHD, incident CVD morbidity and/or mortality, and/or the prevalence of traditional CVD risk factors as their outcomes. Studies were categorized into four groups based upon life course design and analytic approach. The study authors' conclusions and statistical tests were considered in summarizing study results.

          Results

          Study results suggest that low SES throughout the life course modestly impacts CVD risk factors and CVD risk. Specifically, studies reviewed provided moderate support for the role of low early-life SES and elevated levels of CVD risk factors and CVD morbidity and mortality, little support for a unique influence of social mobility on CVD, and consistent support for the detrimental impact of the accumulation of negative SES experiences/conditions across the life course on CVD risk.

          Conclusions

          While the basic life course SES study designs have various methodologic and conceptual limitations, they provide an important approach from which to examine the influence of social factors on CVD development. Some limitations may be addressed through the analysis of study cohorts followed from childhood, the evaluation of CVD risk factors in early and middle adulthood, and the use of multiple SES measures and multiple life course analysis approaches in each life course study.

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          Most cited references88

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          Identifiability and exchangeability for direct and indirect effects.

          We consider the problem of separating the direct effects of an exposure from effects relayed through an intermediate variable (indirect effects). We show that adjustment for the intermediate variable, which is the most common method of estimating direct effects, can be biased. We also show that even in a randomized crossover trial of exposure, direct and indirect effects cannot be separated without special assumptions; in other words, direct and indirect effects are not separately identifiable when only exposure is randomized. If the exposure and intermediate never interact to cause disease and if intermediate effects can be controlled, that is, blocked by a suitable intervention, then a trial randomizing both exposure and the intervention can separate direct from indirect effects. Nonetheless, the estimation must be carried out using the G-computation algorithm. Conventional adjustment methods remain biased. When exposure and the intermediate interact to cause disease, direct and indirect effects will not be separable even in a trial in which both the exposure and the intervention blocking intermediate effects are randomly assigned. Nonetheless, in such a trial, one can still estimate the fraction of exposure-induced disease that could be prevented by control of the intermediate. Even in the absence of an intervention blocking the intermediate effect, the fraction of exposure-induced disease that could be prevented by control of the intermediate can be estimated with the G-computation algorithm if data are obtained on additional confounding variables.
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            Fallibility in estimating direct effects.

            We use causal graphs and a partly hypothetical example from the Physicians' Health Study to explain why a common standard method for quantifying direct effects (i.e. stratifying on the intermediate variable) may be flawed. Estimating direct effects without bias requires that two assumptions hold, namely the absence of unmeasured confounding for (1) exposure and outcome, and (2) the intermediate variable and outcome. Recommendations include collecting and incorporating potential confounders for the causal effect of the mediator on the outcome, as well as the causal effect of the exposure on the outcome, and clearly stating the additional assumption that there is no unmeasured confounding for the causal effect of the mediator on the outcome.
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              US mortality by economic, demographic, and social characteristics: the National Longitudinal Mortality Study.

              A large US sample was used to estimate the effects of race, employment status, income, education, occupation, marital status, and household size on mortality. Approximately 530,000 persons 25 years of age or more were identified from selected Current Population Surveys between 1979 and 1985. These individuals were followed for mortality through use of the National Death Index for the years 1979 through 1989. Higher mortality was found in Blacks than in Whites less than 65 years of age; in persons not in the labor force, with lower incomes, with less education, and in service and other lower level occupations; and in persons not married and living alone. With occasional exceptions, in specific sex and age groups, these relationships were reduced but remained strong and statistically significant when each variable was adjusted for all of the other characteristics. The relationships were generally weaker in individuals 65 years of age or more. Employment status, income, education, occupation, race, and marital status have substantial net associations with mortality. This study identified segments of the population in need of public health attention and demonstrated the importance of including these variables in morbidity and mortality studies.
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                Author and article information

                Journal
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                2005
                20 January 2005
                : 5
                : 7
                Affiliations
                [1 ]Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
                Article
                1471-2458-5-7
                10.1186/1471-2458-5-7
                548689
                15661071
                eee2673f-dc27-4f11-acaf-0805b60a6cc0
                Copyright © 2005 Pollitt et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 8 July 2004
                : 20 January 2005
                Categories
                Research Article

                Public health
                Public health

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