Parent psychopathology and offspring mental disorders: results from the WHO World Mental Health Surveys

Background Associations between specific parent and offspring mental disorders are likely to have been overestimated in studies that have failed to control for parent comorbidity. Aims To examine the associations of parent with respondent disorders. Method Data come from the World Health Organization (WHO) World Mental Health Surveys (n = 51 507). Respondent disorders were assessed with the Composite International Diagnostic Interview and parent disorders with informant-based Family History Research Diagnostic Criteria interviews. Results Although virtually all parent disorders examined (major depressive, generalised anxiety, panic, substance and antisocial behaviour disorders and suicidality) were significantly associated with offspring disorders in multivariate analyses, little specificity was found. Comorbid parent disorders had significant sub-additive associations with offspring disorders. Population-attributable risk proportions for parent disorders were 12.4% across all offspring disorders, generally higher in high- and upper-middle-than low-/lower-middle-income countries, and consistently higher for behaviour (11.0-19.9%) than other (7.1-14.0%) disorders. Conclusions Parent psychopathology is a robust non-specific predictor associated with a substantial proportion of offspring disorders.

Factors Associated with Height Catch-Up and Catch-Down Growth Among Schoolchildren

In developed countries, children with intrauterine growth restriction (IUGR) or born preterm (PT) tend to achieve catch-up growth. There is little information about height catch-up in developing countries and about height catch-down in both developed and developing countries. We studied the effect of IUGR and PT birth on height catch-up and catch-down growth of children from two cohorts of liveborn singletons. Data from 1,463 children was collected at birth and at school age in Ribeirao Preto (RP), a more developed city, and in Sao Luis (SL), a less developed city. A change in z-score between schoolchild height z-score and birth length z-score >= 0.67 was considered catch-up; a change in z-score <=-0.67 indicated catch-down growth. The explanatory variables were: appropriate weight for gestational age/PT birth in four categories: term children without IUGR (normal), IUGR only (term with IUGR), PT only ( preterm without IUGR) and preterm with IUGR; infant's sex; maternal parity, age, schooling and marital status; occupation of family head; family income and neonatal ponderal index (PI). The risk ratio for catch-up and catch-down was estimated by multinomial logistic regression for each city. In RP, preterms without IUGR (RR = 4.13) and thin children (PI<10th percentile, RR = 14.39) had a higher risk of catch-down; catch-up was higher among terms with IUGR (RR = 5.53), preterms with IUGR (RR = 5.36) and children born to primiparous mothers (RR = 1.83). In SL, catch-down was higher among preterms without IUGR (RR = 5.19), girls (RR = 1.52) and children from low-income families ( RR = 2.74); the lowest risk of catch-down (RR = 0.27) and the highest risk of catch-up (RR = 3.77) were observed among terms with IUGR. In both cities, terms with IUGR presented height catch-up growth whereas preterms with IUGR only had height catch-up growth in the more affluent setting. Preterms without IUGR presented height catch-down growth, suggesting that a better socioeconomic situation facilitates height catch-up and prevents height catch-down growth.

Cause-specific mortality and income inequality in São Paulo, Brazil

OBJECTIVE: To analyze cause-specific mortality rates according to the relative income hypothesis. METHODS: All 96 administrative areas of the city of São Paulo, southeastern Brazil, were divided into two groups based on the Gini coefficient of income inequality: high (>0.25) and low (<0.25). The propensity score matching method was applied to control for confounders associated with socioeconomic differences among areas. RESULTS: The difference between high and low income inequality areas was statistically significant for homicide (8.57 per 10,000; 95%CI: 2.60;14.53); ischemic heart disease (5.47 per 10,000 [95%CI 0.76;10.17]); HIV/AIDS (3.58 per 10,000 [95%CI 0.58;6.57]); and respiratory diseases (3.56 per 10,000 [95%CI 0.18;6.94]). The ten most common causes of death accounted for 72.30% of the mortality difference. Infant mortality also had significantly higher age-adjusted rates in high inequality areas (2.80 per 10,000 [95%CI 0.86;4.74]), as well as among males (27.37 per 10,000 [95%CI 6.19;48.55]) and females (15.07 per 10,000 [95%CI 3.65;26.48]). CONCLUSIONS: The study results support the relative income hypothesis. After propensity score matching cause-specific mortality rates was higher in more unequal areas. Studies on income inequality in smaller areas should take proper accounting of heterogeneity of social and demographic characteristics.