ArticleAmerican journal of epidemiology2022
Marginal Structural Models for Life-Course Theories and Social Epidemiology: Definitions, Sources of Bias, and Simulated Illustrations.
Article in American journal of epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Longitudinal changes in cardiorespiratory fitness and risk of depressive and anxiety disorders in a nationwide cohort of 7 million participants.Scientific reports · 2026Article
- Life-course Psychosocial Adversity and Biological Aging in the Hispanic Community Health Study / Study of Latinos: A Life-course Model Analysis.Research square · 2026Article
- The impact of school absence on mental health in children and young people: Analysis of an English national birth cohort.PloS one · 2026Article
- Article
- On the current and future potential of simulations based on directed acyclic graphs.Global epidemiology · 2025Article
- Prosocial Intentions and Subsequent Cognitive Health: A Prospective Cohort Study.The journals of gerontology. Series B, Psychological sciences and social sciences · 2025Article
- Methods for structural sexism and population health research: Introducing a novel analytic framework to capture life-course and intersectional effects.Social science & medicine (1982) · 2024Article
- Specification curve analysis to identify heterogeneity in risk factors for dementia: findings from the UK Biobank.BMC medicine · 2024Article
- Receptive and participatory arts engagement and subsequent healthy aging: Evidence from the Health and Retirement Study.Social science & medicine (1982) · 2023Article
- Alcohol brief intervention, specialty treatment and drinking outcomes at 12 months: Results from a systematic alcohol screening and brief intervention initiative in adult primary care.Drug and alcohol dependence · 2022Article
- Rural residence across the life course and late-life cognitive decline in KHANDLE: A causal inference study.Alzheimer's & dementia (Amsterdam, Netherlands)Article
Corrections and comments
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Authors and funding
7 authors.
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Abstract
Social epidemiology aims to identify social structural risk factors, thus informing targets and timing of interventions. Ascertaining which interventions will be most effective and when they should be implemented is challenging because social conditions vary across the life course and are subject to time-varying confounding. Marginal structural models (MSMs) may be useful but can present unique challenges when studying social epidemiologic exposures over the life course. We describe selected MSMs corresponding to common theoretical life-course models and identify key issues for consideration related to time-varying confounding and late study enrollment. Using simulated data mimicking a cohort study evaluating the effects of depression in early, mid-, and late life on late-life stroke risk, we examined whether and when specific study characteristics and analytical strategies may induce bias. In the context of time-varying confounding, inverse-probability-weighted estimation of correctly specified MSMs accurately estimated the target causal effects, while conventional regression models showed significant bias. When no measure of early-life depression was available, neither MSMs nor conventional models were unbiased, due to confounding by early-life depression. To inform interventions, researchers need to identify timing of effects and consider whether missing data regarding exposures earlier in life may lead to biased estimates.
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