These findings represent the first serologic evidence that prenatal influenza plays a role in schizophrenia. If confirmed, the results may have implications for the prevention of schizophrenia and for unraveling pathogenic mechanisms of the disorder.

Objective To examine the relation between birth weight and measured intelligence at age 7 years in children within the normal range of birth weight and in siblings. Design Cohort study of siblings of the same sex. Setting 12 cities in the United States. Subjects 3484 children of 1683 mothers in a birth cohort study during the years 1959 through 1966. The sample was restricted to children born at >37 weeks gestation and with birth weights of 1500-3999 g. Main outcome measure Full scale IQ at age 7 years. Results Mean IQ increased monotonically with birth weight in both sexes across the range of birth weight in a linear regression analysis of one randomly selected sibling per family (n = 1683) with adjustment for maternal age, race, education, socioeconomic status, and birth order. Within same sex sibling pairs, differences in birth weight were directly associated with differences in IQ in boys (812 pairs, predicted IQ difference per 100 g change in birth weight = 0.50, 95% confidence interval 0.28 to 0.71) but not girls (871 pairs, 0.10, − 0.09 to 0.30). The effect in boys remained after differences in birth order, maternal smoking, and head circumference were adjusted for and in an analysis restricted to children with birth weight > 2500 g. Conclusion The increase in childhood IQ with birth weight continues well into the normal birth weight range. For boys this relation holds within same sex sibships and therefore cannot be explained by confounding from family social environment.

The focus of this paper is regression analysis of clustered data. Although the presence of intracluster correlation (the tendency for items within a cluster to respond alike) is typically viewed as an obstacle to good inference, the complex structure of clustered data offers significant analytic advantages over independent data. One key advantage is the ability to separate effects at the individual (or item-specific) level and the group (or cluster-specific) level. We review different approaches for the separation of individual-level and cluster-level effects on response, their appropriate interpretation and give recommendations for model fitting based on the intent of the data analyst. Unlike many earlier papers on this topic, we place particular emphasis on the interpretation of the cluster-level covariate effect. The main ideas of the paper are highlighted in an analysis of the relationship between birth weight and IQ using sibling data from a large birth cohort study.

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We sought to examine the relationship between maternal exposure to adult respiratory infections and schizophrenia spectrum disorder (SSD) in the Prenatal Determinants of Schizophrenia (PDS) Study, a large birth cohort investigation. Previous work suggests that second trimester exposure to respiratory infection may be a risk factor for SSD. We therefore examined whether this class of infection was associated with adult SSD. For this purpose, we capitalized on several design advantages of the PDS Study, including a comprehensive, prospective data base on physician-diagnosed infections and a continuous followup in which diagnoses of SSD were made, in the majority, by face-to-face interview. Second trimester exposure to respiratory infections was associated with a significantly increased risk of SSD, adjusting for maternal smoking, education, and race (rate ratio [RR] = 2.13 [1.05-4.35], chi2 = 4.36, df= 1,p = 0.04); no associations were shown for first trimester and third trimester exposure to these respiratory infections. These findings support-and extend-previous studies suggesting that second trimester respiratory infections are risk factors for SSD. This study therefore has implications toward uncovering the etiology of schizophrenia and developing preventive strategies.