Do Behavioral Risk Factors for Prediabetes and Insulin Resistance Differ across the Socioeconomic Gradient? Results from a Community-Based Epidemiologic Survey.

To examine whether behavioral risk factors associated with diabetes (diet, BMI, waist circumference, physical activity, and sleep duration) are also related to both prediabetes and insulin resistance (IR), we used data from Boston Area Community Health (BACH) Survey (2010-2012, n = 3155). Logistic and linear regression models were used to test the association of lifestyle factors with prediabetes status, insulin resistance, and prediabetes or insulin resistance. All regression models were stratified by education and income levels (to examine whether risk factors had differential effects across socioeconomic factors) and adjusted for age, gender, race/ethnicity, family history of diabetes, and smoking status. We found that large waist circumference was consistently associated with higher levels of insulin resistance (IR) and increased odds of prediabetes. While the association between large waist circumference and IR was consistent across all levels of SES (P < 0.001), the association between large waist circumference and prediabetes was only statistically significant in the highest socioeconomic strata with odds ratios of 1.68 (95% CI 1.07-2.62) and 1.88 (95% CI 1.22-2.92) for postgraduate degree and income strata, respectively. There was no association between diet, physical activity, sleep duration, and the presence of multiple risk factors and prediabetes or IR within SES strata.

Prevalence and psychiatric comorbidity of attention-deficit/hyperactivity disorder in an adolescent Finnish population.

OBJECTIVE: The purpose of the study was to estimate the prevalence of attention-deficit/hyperactivity disorder (ADHD) and its clinical characteristics in the Northern Finland Birth Cohort 1986. METHOD: A general population Northern Finland Birth Cohort 1986 of 9,432 children followed prospectively from the early fetal period was surveyed at adolescence (ages 16-18) for ADHD behaviors. Among 6,622 respondents to the survey, a subset of 457 likely cases and controls were evaluated for ADHD and other psychiatric disorders. Chi-square and descriptive statistics were used to examine clinical characteristics of ADHD in the subset, and logistic regression was used to estimate prevalence by weighted extrapolation in the larger cohort. RESULTS: The estimated prevalence of ADHD among adolescents in the Northern Finland Birth Cohort 1986 is 8.5% with a male/female ratio of 5.7:1. The distribution of ADHD subtypes among the ADHD adolescents is 28% Combined, 64% Inattentive, and 8% Hyperactive-Impulsive. A lifetime diagnosis of a broadly defined ADHD (probable or definite) had a prevalence of 18.2% with a male/female odds ratio (OR) of 3.2. This lifetime diagnosis of ADHD is significantly associated with anxiety (OR 2.4), mood (OR 2.9), and disruptive behavioral disorders (OR 17.3) in the cohort. CONCLUSIONS: ADHD is a common neurobehavioral disorder among Northern Finnish adolescents and significantly associated with psychiatric comorbidity in adolescence.