Commentary: Causal Inference for Social Exposures.

Commentary: Causal Inference for Social Exposures. Annu Rev Public Health. 2019 Jan 02;: Authors: Kaufman JS Abstract Social epidemiology seeks to describe and quantify the causal effects of social institutions, interactions, and structures on human health.To accomplish this task, we define exposures as treatments and posit populations exposed or unexposed to these well-defined regimens. This inferential structure allows us to unambiguously estimate and interpret quantitative causal parameters and to investigate how these may be affected by biases such as confounding. This paradigm has been challenged recently by some critics who favor broadening the exposures that may be studied beyond treatments to also consider states. Defining the exposure protocol of an observational study is a continuum of specificity, and one may choose to loosen this definition, incurring the cost of causal parameters that become commensurately more vague. The advantages and disadvantages of broader versus narrower definitions of exposure are matters of continuing debate in social epidemiology as in other branches of epidemiology. Expected final online publication date for the Annual Review of Public Health Volume 40 is April 1, 2019. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates. PMID: 30601720 [PubMed - as supplied by publisher]
Source: Annual Review of Public Health - Category: International Medicine & Public Health Authors: Tags: Annu Rev Public Health Source Type: research