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Introduction: There is increasing interest in the clustering of risk behaviours in adolescence. However, few studies have examined what clusters of risk behaviours exist among adolescents, their early-life predictors, and their associations with later health.Methods: We analysed data derived from 8754 participants (women 53.3%) in the 1970 British Cohort Study. Latent class analysis was used to identify clusters of risk behaviours at age 16. Regression modelling was then used to examine predictors of clusters and their consequences of risk behaviours and health outcomes at age 42.Results: We identified two latent classes: a risky-behaviour (men: 20.0%, women: 23.6%) and less-risky-behaviour class. Among men, those in the risky-behaviour class were more likely to report smoking, multiple binge drinking, sexual debut before 16, involvement in fights and delinquency than were women. Membership in risky-behaviour class was mainly predicted by sociodemographic and parental risk behaviours and monitoring. The risky-behaviour class at age 16 was associated with the following outcome age 42: smoking status (more strongly among women), excessive alcohol consumption (more strongly among men), worse self-rated health (more strongly among men), and psychological distress (only among women).Conclusions: Engagement in multiple risk behaviours in adolescence is an important driver of health inequalities later in life. Early life intervention, for example via school-based interventions, may be warranted for favourable lifelong health. [ABSTRACT FROM AUTHOR]

Purpose To examine the associations between social class at ages 0, 5, 10, 30, and 34 years and physical activity at age 34 years using a novel approach to analysis of life course data. Methods We used structural equation modeling to compare three competing models in life course epidemiology: the accumulation of risk model with additive effects, the accumulation of risk model with trigger effect, and the critical period model. Data were from a nationally representative prospective cohort of 16,571 British men and women born in 1970. Outcomes were physical activity during leisure time, during transports, and at work. Results For all three domains of physical activity, for men and women, the accumulation of risk model with additive effects fit the data best. In this model, social class at ages 0, 5, 10, 30, and 34 years were associated with physical activity at age 34 years, although the magnitude and the direction of the associations for social class at each age varied by physical activity outcome and by sex. Conclusions Structural equation modeling appears to be a helpful tool in selecting among competing models in life course epidemiology. [ABSTRACT FROM AUTHOR]

Longitudinal data are used to explore the reliability of long‐term illness measures using information on ‘long‐term/permanent sickness or disability’ as recorded via the question on economic activity in the Census of England and Wales. Specifically it is asked ‘what evidence is there that individuals answer the item on long‐term sickness or disability in the same way at different time points?’. The research is based on data from the Office for National Statistics Longitudinal Study (LS) and the responses of persons who reported long‐term sickness or disability in 1971 are tracked to see if they also reported long‐term sickness or disability in 1981 and 1991. That a large number of people reported long‐term sickness or disability at three Census points suggests that the measure was reliable. In addition, it is suggested that a degree of content validity has been achieved with respect to the understanding of the concept of ‘long‐termness’. It is concluded that longitudinal data provide a valuable way of investigating the reliability and validity of frequently used categorical measures and can help to distinguish between the extent to which a phenomenon such as long‐term sickness is ‘new’ or ‘ongoing’. [ABSTRACT FROM AUTHOR]