2022

Background. There are numerous observations of reward sensitivity being associated with different psychiatric disorders. Nonetheless, most studies investigating this relationship have been cross-sectional. Additionally, current knowledge is fragmentary as studies often investigate only one disorder at a time. The present study addresses these gaps by investigating whether reward sensitivity at age 13 predicts the course of nine psychopathology domains (attention and hyperactivity, autism spectrum, reactive aggression, proactive aggression, mood, anxiety, smoking, alcohol use, and cannabis use) over a 14-year follow-up period. Methods. We used dimensional outcomes on 2,523 individuals over five measurement waves between ages 13 and 26 of the Dutch Tracking Adolescents' Individual Lives Survey (TRAILS). Reward sensitivity was measured with the Behavioral Activation System (BAS) scale. The longitudinal associations between reward sensitivity and psychopathology were examined using growth curve analysis within a multilevel framework. Results. Reward sensitivity at age 13 was associated with changes in psychopathology over time. Reward sensitivity had a stable main effect on the future course of reactive and proactive aggression problems and anxiety problems. The effect of reward sensitivity increased over time for alcohol and cannabis use. Post-hoc analyses showed that reward sensitivity also had a stable effect on attention problems and hyperactivity and smoking when based on the fun-seeking subscale for both domains and when changing the informant who reported on attention problems and hyperactivity. No evidence was found for a longitudinal association between reward sensitivity and autism spectrum problems and mood problems. Conclusion. The current study provides evidence for the long-lasting effects of reward sensitivity on the course of different domains of psychopathology.

Introduction. Dynamic relations between genetic, hormone, and pre- and postnatal environments are theorized as critically important for adolescent substance use but are rarely tested in multifactorial models. This study assessed the impact of interactions of genetic risk and cortisol reactivity with prenatal and parenting influences on both any and frequency of adolescent substance use. Methods. Data are from the TRacking Adolescents' Individual Lives Survey (TRAILS), a prospective longitudinal, multi-rater study of 2,230 Dutch adolescents. Genetic risk was assessed via 3 substance-specific polygenic scores. Mothers retrospectively reported prenatal risk when adolescents were 11 years old. Adolescents rated their parents' warmth and hostility at age 11. Salivary cortisol reactivity was measured in response to a social stress task at age 16. Adolescents' self-reported cigarette, alcohol, and cannabis use frequency at age 16. Results. A multivariate hurdle regression model showed that polygenic risk for smoking, alcohol, and cannabis predicted any use of each substance, respectively, but predicted more frequent use only for smoking. Blunted cortisol reactivity predicted any use and more frequent use for all 3 outcomes. There were 2 interactions: blunted cortisol reactivity exacerbated the association of polygenic risk with any smoking and the association of prenatal risk with any alcohol use. Conclusion. Polygenic risk seems of importance for early use but less so for frequency of use, whereas blunted cortisol reactivity was correlated with both. Blunted cortisol reactivity may also catalyze early risks for substance use, though to a limited degree. Gene-environment interactions play no role in the context of this multifactorial model. © 2021 S. Karger AG, Basel.

Both social causation and health-related selection may influence educational gradients in alcohol use in adolescence and young adulthood. The social causation theory implies that the social environment (e.g. at school) influences adolescents' drinking behaviour. Conversely, the health-related selection hypothesis posits that alcohol use (along other health-related characteristics) predicts lower educational attainment. From past studies it is unclear which of these mechanisms predominates, as drinking may be both a cause and consequence of low educational attainment. Furthermore, educational gradients in alcohol use may reflect the impact of 'third variables' already present in childhood, such as parental socioeconomic status (SES), effortful control, and IQ. We investigated social causation and health-related selection in the development of educational gradients in alcohol use from adolescence to young adulthood in a selective educational system. We used data from a Dutch population-based cohort (TRAILS Study; n = 2,229), including measurements of educational level and drinking at ages around 14, 16, 19, 22, and 26 years (waves 2 to 6). First, we evaluated the directionality in longitudinal associations between education and drinking with cross-lagged panel models, with and without adjusting for pre-existing individual differences using fixed effects. Second, we assessed the role of childhood characteristics around age 11 (wave 1), i.e. IQ, effortful control, and parental SES, both as confounders in these associations, and as predictors of educational level and drinking around age 14 (wave 2). In fixed effects models, lower education around age 14 predicted increases in drinking around 16. From age 19 onward, we found a tendency towards opposite associations, with higher education predicting increases in alcohol use. Alcohol use was not associated with subsequent changes in education. Childhood characteristics strongly predicted education around age 14 and, to a lesser extent, early drinking. We mainly found evidence for the social causation theory in early adolescence, when lower education predicted increases in subsequent alcohol use. We found no evidence in support of the health-related selection hypothesis with respect to alcohol use. By determining initial educational level, childhood characteristics also predict subsequent trajectories in alcohol use.

Highlights

• A life-course study based on a large cohort of 2,229 adolescents
• Adolescents with similar MHRB patterns can reach adulthood with different levels of changes in mental health problems
• Mental health problems at age 11 were a predictor of mental health at age 23, with MHRBs explaining only a small part
• A continuity of obesity-related MHRBs throughout adolescence was associated with changes in mental health.