Prevalence of major depression in preschool children

The prevalence of preschool major depressive disorder (MDD) was studied in the community. The whole population of children between 3 and 6 years attending preschool nurseries in three areas (one urban, one rural and one suburban) in Spain (n = 1,427) were contacted. Selection was by a two-stage procedure. At stage I, the ESDM 3-6, a screening measure for preschool depression, was used to identify a sample for more intensive interviewing. Sensitivity and specificity of the cut-off point of the ESDM 3–6 had been previously tested in a pilot study (n = 229). During the first stage, 222 preschool children (15.6%) were found to be probable depressives, because they scored 27 or more, the cut-off used. At stage II, the children were interviewed and diagnosed by the consensus of two clinicians, blind to the ESDM 3-6 results. DSM-IV diagnostic criteria were used to define caseness. A total of 16 children (1.12%) met the MDD criteria. The prevalence by areas was urban 0.87%, rural 0.88%, suburban 1.43%. Sex distribution prevalence was 1:1. This study is a contribution to the scarce epidemiology of preschool depression in the community

Genetic and environmental influences on the relation between attention problems and Attention Deficit Hyperactivity Disorder.

Objective: The assessment of symptoms of ADHD in children is usually based on a clinical interview or a behavior checklist. The aim of the present study is to investigate the extent to which these instruments measure an underlying construct and to estimate the genetic and environmental influences on individual differences in ADHD. Methods: Maternal ratings were collected on 10,916 twins from 5,458 families. Child Behavior Checklist (CBCL) ratings were available for 10,018, 6,565, and 5,780 twins at the ages 7, 10, and 12, respectively. The Conners Rating Scale (4,887 twins) and the DSM interview (1,006 twins) were completed at age 12. The magnitude of genetic and environmental influences on the variance of the three measures of ADHD and the covariance among the three measures of ADHD was obtained. Results: Phenotypic correlations range between .45 and .77. Variances and covariances of the measurements were explained mainly by genetic influences. The model that provided the best account of the data included an independent pathway for additive and dominant genetic effects. The genetic correlations among the measures collected at age 12 varied between .63 and 1.00. Conclusions: The genetic overlap between questionnaire ratings and the DSM-IV diagnosis of ADHD is high. Clinical and research implications of these findings are presented