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Ann Epidemiol. 2016 Jun;26(6):389-394.e2. doi: 10.1016/j.annepidem.2016.04.010. Epub 2016 May 3.

Conditions for valid estimation of causal effects on prevalence in cross-sectional and other studies.

Author information

1
Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA; Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA. Electronic address: wflande@sph.emory.edu.
2
Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA; Department of Environmental and Occupational Health, Rollins School of Public Health, Emory University, Atlanta, GA.
3
Air Pollution and Respiratory Health Branch, Division of Environmental Hazards and Health Effects, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA.

Abstract

PURPOSE:

Causal effects in epidemiology are almost invariably studied by considering disease incidence even when prevalence data are used to estimate the causal effect. For example, if certain conditions are met, a prevalence odds ratio can provide a valid estimate of an incidence rate ratio. Our purpose and main result are conditions that assure causal effects on prevalence can be estimated in cross-sectional studies, even when the prevalence odds ratio does not estimate incidence.

METHODS:

Using a general causal effect definition in a multivariate counterfactual framework, we define causal contrasts that compare prevalences among survivors from a target population had all been exposed at baseline with that prevalence had all been unexposed. Although prevalence is a measure reflecting a moment in time, we consider the time sequence to study causal effects.

RESULTS:

Effects defined using a contrast of counterfactual prevalences can be estimated in an experiment and, with conditions provided, in cross-sectional studies. Proper interpretation of the effect includes recognition that the target is the baseline population, defined at the age or time of exposure.

CONCLUSIONS:

Prevalences are widely reported, readily available measures for assessing disabilities and disease burden. Effects on prevalence are estimable in cross-sectional studies but only if appropriate conditions hold.

KEYWORDS:

Causal effects; Cross-sectional studies; Prevalence; Survey; Target population; Validity

PMID:
27287301
PMCID:
PMC4914045
DOI:
10.1016/j.annepidem.2016.04.010
[Indexed for MEDLINE]
Free PMC Article

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