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These results provide support for the construct validity and demonstrate adequate psychometric properties of a self-report instrument designed to measure childhood PLEs, providing evidence that the PQ-BC may be a useful measure of early risk for psychotic disorders. Furthermore, these data suggest that PLEs at school age are associated with many of the same familial, cognitive, and emotional factors associated with psychotic symptoms in older populations, consistent with the dimensionality of psychosis across the lifespan.

Research into environmental factors associated with suicide has historically focused on meteorological variables. Recently, a heightened risk of suicide related to short-term exposure to airborne particulate matter was reported. Here, we examined the associations between short-term exposure to nitrogen dioxide, particulate matter, and sulfur dioxide and completed suicide in Salt Lake County, Utah (n = 1,546) from 2000 to 2010. We used a time-stratified case-crossover design to estimate adjusted odds ratios for the relationship between suicide and exposure to air pollutants on the day of the suicide and during the days preceding the suicide. We observed maximum heightened odds of suicide associated with interquartile-range increases in nitrogen dioxide during cumulative lag 3 (average of the 3 days preceding suicide; odds ratio (OR) = 1.20, 95% confidence interval (CI): 1.04, 1.39) and fine particulate matter (diameter ≤2.5 μm) on lag day 2 (day 2 before suicide; OR = 1.05, 95% CI: 1.01, 1.10). Following stratification by season, an increased suicide risk was associated with exposure to nitrogen dioxide during the spring/fall transition period (OR = 1.35, 95% CI: 1.09, 1.66) and fine particulate matter in the spring (OR = 1.28, 95% CI: 1.01, 1.61) during cumulative lag 3. Findings of positive associations between air pollution and suicide appear to be consistent across study locations with vastly different meteorological, geographical, and cultural characteristics.

AimTo examine individual variability between perceived physical features and hormones of pubertal maturation in 9–10-year-old children as a function of sociodemographic characteristics.MethodsCross-sectional metrics of puberty were utilized from the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) Study—a multi-site sample of 9–10 year-olds (n = 11,875)—and included perceived physical features via the pubertal development scale (PDS) and child salivary hormone levels (dehydroepiandrosterone and testosterone in all, and estradiol in females). Multi-level models examined the relationships among sociodemographic measures, physical features, and hormone levels. A group factor analysis (GFA) was implemented to extract latent variables of pubertal maturation that integrated both measures of perceived physical features and hormone levels.ResultsPDS summary scores indicated more males (70%) than females (31%) were prepubertal. Perceived physical features and hormone levels were significantly associated with child’s weight status and income, such that more mature scores were observed among children that were overweight/obese or from households with low-income. Results from the GFA identified two latent factors that described individual differences in pubertal maturation among both females and males, with factor 1 driven by higher hormone levels, and factor 2 driven by perceived physical maturation. The correspondence between latent factor 1 scores (hormones) and latent factor 2 scores (perceived physical maturation) revealed synchronous and asynchronous relationships between hormones and concomitant physical features in this large young adolescent sample.ConclusionsSociodemographic measures were associated with both objective hormone and self-report physical measures of pubertal maturation in a large, diverse sample of 9–10 year-olds. The latent variables of pubertal maturation described a complex interplay between perceived physical changes and hormone levels that hallmark sexual maturation, which future studies can examine in relation to trajectories of brain maturation, risk/resilience to substance use, and other mental health outcomes.

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