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The effect of screen time during secondary school on percent body fat was examined in a cohort of 744 Canadian adolescents aged 12-13 years at baseline. Participants completed self-reported questionnaires on television viewing and computer use in 19 survey cycles over 57 months from 1999 to 2005. Triceps skinfold thickness and subscapular skinfold thickness were measured in survey cycles 1 and 19. Four screen-time trajectory groups identified in growth mixture modeling included steady-low screen time (73% of the sample), steady-high (10%), increasers (9%), and decreasers (8%). The effect of screen-time trajectory on percent body fat at survey cycle 19 was modeled in boys and girls separately by using linear regression, adjusting for baseline percent body fat and physical activity. Relative to that of steady-low screen-time trajectory group boys, percent body fat was 2.9 (95% confidence interval: 0.7, 5.0) and 2.4 (95% confidence interval: 0.5, 4.2) percentage units higher on average among "increasers" and "steady-high" trajectory group boys, respectively. There was no evidence that screen time has an effect on percent body fat in girls overall, although physical activity modified the association between screen time and percent body fat in both sexes. Efforts to prevent obesity in youth should emphasize reducing screen time.

Few prospective studies of smoking initiation have investigated a wide range of time-varying and invariant predictor variables at the individual and contextual levels concurrently. In this study (1999-2005), 877 Canadian students (mean age = 12.7 years) who had never smoked at baseline completed self-report questionnaires on cigarette smoking and 32 predictor variables in 20 survey cycles during secondary school. Height and weight were measured in survey cycles 1, 12, and 19. School administrators completed questionnaires on school tobacco control policies/activities, and trained observers collected data on access to tobacco products in commercial establishments near schools. Younger age, single-parent family status, smoking by parents, siblings, friends, and school staff, stress, impulsivity, lower self-esteem, feeling a need to smoke, not doing well at school, susceptibility to tobacco advertising, alcohol use, use of other tobacco products, and attending a smoking-tolerant school were independent determinants of smoking initiation. Independent determinants of daily smoking onset among initiators of nondaily smoking included smoking by siblings and friends, feeling a need to smoke, susceptibility to tobacco advertising, use of other tobacco products, and self-perceived mental and physical addiction. Adolescent tobacco control programs should address multiple individual and contextual-level risk factors. Strategies that address nicotine dependence symptoms are also needed for adolescents who have already initiated smoking.

Most existing coronary risk assessment methods are based on baseline data only. The authors compared the predictive ability of coronary multivariable risk scores based on updated versus baseline risk factors and investigated the optimal frequency of updating. Data from 16 biennial examinations of 4,962 subjects from the original Framingham Heart Study (1948-1978) were used. The predictive ability of three multivariable risk scores was evaluated through 10-fold cross-validation. The baseline-only multivariable risk score was computed using baseline values of coronary risk factors applied to a Cox model estimated from baseline data. The two other approaches relied on updated risk factors and included them in the models estimated from, respectively, baseline and updated data. All analyses were stratified by sex and age. For 30, 14, and 10 years of follow-up, the predictive ability of the baseline-only multivariable risk score was substantially poorer than that of the models using updated risk factors. Between the two latter models, the one estimated from updated data ensured better prediction than the one estimated from baseline data for 30 years of follow-up among younger subjects only. The results suggest that coronary risk assessment can be improved by utilizing updated risk factors and that the optimal frequency of updating may vary across subpopulations.

Neighborhood socioeconomic environment may be a determinant of injection drug use cessation. The authors used data from a prospective cohort study of Baltimore City, Maryland, injection drug users assessed between 1990 and 2006. The study examined the relation between living in a poorer neighborhood and the probability of injection cessation among active injectors, independent of individual characteristics and while respecting the temporality of potential confounders, exposure, and outcome. Participants’ residences were geocoded, and the crude, adjusted, and inverse probability of exposure weighted associations between neighborhood poverty and injection drug use cessation were estimated. Weighted models showed a strong association between neighborhood poverty and injection drug use cessation; living in a neighborhood with fewer than 10%, compared with more than 30%, of residents in poverty was associated with a 44% increased odds of not injecting in the prior 6 months (odds ratio = 1.44, 95% confidence interval: 1.14, 1.82). Results show that neighborhood environment may be an important determinant of drug injection behavior independent of individual-level characteristics.