Invited commentary: beyond frequencies and coefficients--toward meaningful descriptions for life course epidemiology.

The expected doubling of the elderly population in the United States by year 2030 poses a major challenge to public health and medical care systems because of limited and progressive diminution of resources for public health and medical care for the elderly (1). This challenge highlights the urgent need for effective programs and policies aimed at the prevention of diseases and maintenance of health over the life span of individuals. Such programs must rely on solid, translatable evidence from population-based etiologic studies. However, both etiologic studies of healthy aging and the translation of study findings into programs and policies are exceedingly complex. For example, to identify accurately and precisely the predictors of the onset and the progression of diseases and functional decline, we must contend with not only 1) multiple arrays of time-varying risk and protective factors and 2) multiple morbidities and functional outcomes over time but also 3) synergism among these factors, 4) risk accumulation processes, and 5) latency periods. To develop tailored prevention programs for implementation at optimal times to maximize benefits and costeffectiveness, decision makers need detailed documentation of the changes in the population distribution of the causes of disease onset and disease progression with increasing age, as well as comprehensive and accurate risk information on priority subgroups. These challenges for etiologic research and for evidence translation call for inventive approaches in epidemiologic research and practice. One valuable and increasingly popular approach is the life course framework for epidemiologic research and public health program and policy development (2, 3). This approach integrates streams of disciplinaryspecific theories and methodologies from biology, human development, public health, and medicine, as well as the social and policy sciences, to account for health and disease over the life span of individuals. The life course framework unifies theories of disease causation and progression in individuals and populations across many conceptual domains that include 1) multiple multilevel determinants of disease, 2) critical and sensitive exposure time periods, 3) accumulation of risk and protection, and 4) the dynamic interplay among biology, adaptive processes, and sociocultural, environmental, and historical contexts (4). The life course approach, while interdisciplinary and integrative, presents epidemiologists and other health researcherswith alarming complexity.However, it is perhaps themost comprehensive approach epidemiologists and others might take to begin to accumulate answers to the most fundamental of all public health questions: What actions (in the form of intervention programs and public policies) need to be taken at what age across the life span of individuals to prevent disease and enhance health? Kuh et al. (5) take the life course approach to quantify the effects of physical growth and developmental milestones in childhood, since these affect physical functioning at midlife. To do these analyses, they use data collected from a representative sample of the intended target population, the British cohort born in 1946.More specifically, they usedmultiple linear regression to quantify the effects on standard physical performance measures at age 53 years of 1) height-adjusted weight, separately for each follow-up age; 2) the effect of each sex-stratified interval weight and height velocity from birth through age 53 years, adjusted for lifetime social class, current physical activity, and current health status; and 3) the residual effects of age at meeting developmental motor milestones, cognitive ability score at age 8 years, motor coordination score at age 15 years, and age at puberty, by increment adjustment for sex, growth trajectories, childhood social class, and other adult risk factors. In doing these analyses,