Disentangling the interplay between genes, cognitive skills, and educational level in adolescent and young adult smoking - The TRAILS study.

Recent studies suggest that smoking and lower educational attainment may have genetic influences in common. However, little is known about the mechanisms through which genetics contributes to educational inequalities in adolescent and young adult smoking. Common genetic liabilities may underlie cognitive skills associated with both smoking and education, such as IQ and effortful control, in line with indirect health-related selection explanations. Additionally, by affecting cognitive skills, genes may predict educational trajectories and hereby adolescents' social context, which may be associated with smoking, consistent with social causation explanations. Using data from the Dutch TRAILS Study (N = 1581), we estimated the extent to which polygenic scores (PGSs) for ever smoking regularly (PGSSMOK) and years of education (PGSEDU) predict IQ and effortful control, measured around age 11, and whether these cognitive skills then act as shared predictors of smoking and educational level around age 16, 19, 22, and 26. Second, we assessed if educational level mediated associations between PGSs and smoking. Both PGSs were associated with lower effortful control, and PGSEDU also with lower IQ. Lower IQ and effortful control, in turn, predicted having a lower educational level. However, neither of these cognitive skills were directly associated with smoking behaviour after controlling for covariates and PGSs. This suggests that IQ and effortful control are not shared predictors of smoking and education (i.e., no indirect health-related selection related to cognitive skills). Instead, PGSSMOK and PGSEDU, partly through their associations with lower cognitive skills, predicted selection into a lower educational track, which in turn was associated with more smoking, in line with social causation explanations. Our findings suggest that educational differences in the social context contribute to associations between genetic liabilities and educational inequalities in smoking.

Socioeconomic inequalities in adolescent health behaviours across 32 different countries - The role of country-level social mobility.

Higher family affluence is associated with healthier behaviours in adolescents, but the strength of this association varies across countries. Differences in social mobility at the country-level, i.e. the extent to which adolescents develop a different socioeconomic status (SES) than their parents, may partially explain why the association between family affluence and adolescent health behaviours is stronger in some countries than in others. Using data from adolescents aged 11-15 years from 32 countries, participating in the 2017/2018 wave of the Health Behaviour in School-aged Children (HBSC) study (N = 185,086), we employed multilevel regression models with cross-level interactions to examine whether country-level social mobility moderates the association between family affluence and adolescent health behaviours (i.e. moderate-to-vigorous physical activity, vigorous physical activity, healthy and unhealthy foods consumption, having breakfast regularly, and weekly smoking). Higher family affluence was more strongly associated with higher levels of adolescent physical activity in countries characterized by high levels of social mobility. No cross-level interactions were found for any of the other health behaviours. Differences in social mobility at the country-level may contribute to cross-national variations in socioeconomic inequalities in adolescent physical activity. Further research can shed light on the mechanisms linking country-level social mobility to inequalities in adolescent physical activity to identify targets for policy and interventions.

Unique developmental trajectories of risk behaviors in adolescence and associated outcomes in young adulthood.

This study aimed at assessing developmental trajectories of risk behaviors from adolescence into young adulthood and their associations with outcomes in young adulthood (i.e. education, employment). Data of the TRacking Adolescents' Individual Lives Survey (TRAILS) including 2,149 participants (mean age = 13.6, SD = 0.5, 51% girls) were used to examine the development of alcohol, cannabis, smoking, and externalizing behavior. The results showed that the associations between these risk behaviors varied with age, and revealed varying developmental patterns throughout adolescence. Most notably alcohol use did not covary strongly with the other risk behaviors. The often assumed peak in risk behavior in adolescence was only found in a small group, and only for alcohol (7.4%) and cannabis use (3.4%), but not for smoking or externalizing behavior. Most adolescents revealed only low involvement in risk behavior, with the largest differences between low and high trajectories emerging in late adolescence (> 19 years). Clustering of risk behavior throughout adolescence is rather the exception than the rule and depends on age and type of risk behavior. Differences in risk behavior between individuals become the largest in late adolescence, possibly influencing successful transition into adulthood visible in educational attainment and employment.

Do online assessed self-report and behavioral measures of impulsivity-related constructs predict onset of substance use in adolescents?

INTRODUCTION: To prospectively predict the onset of use of alcohol, cigarettes and marijuana among Dutch adolescents, using behavioral and self-report measures of impulsivity-related facets. Specifically, we investigated whether behavioral measures of impulsivity predicted the onset of substance use above and beyond self-report measures of impulsivity and sensation seeking in an online sample. METHODS: Self-report and behavioral data from 284 adolescents (195 girls, mean age = 14.8 years, SD = 1.26) were collected at four time points over a period of two years, using an online survey system. Impulsivity-related facets were assessed at time point 1 with the Delay Discounting Task, the Balloon Analogue Risk Task and the Passive Avoidance Learning Task. We conducted logistic regression analysis to examine whether behavioral and self-report measures uniquely predicted onset of alcohol use, heavy episodic drinking, smoking and marijuana use. RESULTS: Onset of cigarette smoking was associated with behavioral assessment of impulsive decision making, but not after controlling for self-reported impulsivity and sensation seeking. Behavioral measures were sometimes associated with, but appeared not to prospectively predict, the onset of substance use in this online sample after controlling for self-report measures. CONCLUSIONS: Based on the present results, the added value of online behavioral assessment of impulsivity-related factors in the prediction of onset of substance use was not confirmed. We suggest that factors specific to each behavioral task underlie their lack of prediction and suggest that future research addresses limitations of current behavioral tasks to increase their validity in online testing.