A life course approach to chronic disease epidemiology

Annu Rev Public Health. 2005:26:1-35. doi: 10.1146/annurev.publhealth.26.021304.144505.


A life course approach to chronic disease epidemiology uses a multidisciplinary framework to understand the importance of time and timing in associations between exposures and outcomes at the individual and population levels. Such an approach to chronic diseases is enriched by specification of the particular way that time and timing in relation to physical growth, reproduction, infection, social mobility, and behavioral transitions, etc., influence various adult chronic diseases in different ways, and more ambitiously, by how these temporal processes are interconnected and manifested in population-level disease trends. In this review, we discuss some historical background to life course epidemiology and theoretical models of life course processes, and we review some of the empirical evidence linking life course processes to coronary heart disease, hemorrhagic stroke, type II diabetes, breast cancer, and chronic obstructive pulmonary disease. We also underscore that a life course approach offers a way to conceptualize how underlying socio-environmental determinants of health, experienced at different life course stages, can differentially influence the development of chronic diseases, as mediated through proximal specific biological processes.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Age Distribution
  • Anthropometry
  • Chronic Disease / epidemiology*
  • Cohort Effect
  • Demography
  • Environmental Exposure / adverse effects*
  • Environmental Exposure / analysis
  • Epidemiologic Methods*
  • Global Health
  • Growth
  • Health Behavior
  • Health Transition
  • Human Development*
  • Humans
  • Infections / epidemiology
  • Life Style*
  • Longevity
  • Models, Statistical*
  • Patient Care Team / organization & administration
  • Public Health
  • Reproduction
  • Residence Characteristics
  • Risk Assessment
  • Risk Factors
  • Time Factors
  • United States / epidemiology