Jos W. R. Twisk

Overweight and obesity in youth are important public health concerns and are of particular interest because of possible long-term associations with adult weight status and morbidity. The aim of this study was to systematically review the literature and update evidence concerning persistence of childhood overweight. A computerized bibliographical search--restricted to studies with a prospective or retrospective longitudinal design--was conducted. Two authors independently extracted data and assessed the methodological quality of the included studies in four dimensions (i) study population and participation rate; (ii) study attrition; (iii) data collection and (iv) data analysis. Conclusions were based on a rating system of three levels of evidence. A total of 25 publications were selected for inclusion in this review. According to a methodological quality assessment, 13 studies were considered to be of high quality. The majority of these high-quality studies were published after 2001, indicating that recently published data, in particular, provide us with reliable information. All included studies consistently report an increased risk of overweight and obese youth becoming overweight adults, suggesting that the likelihood of persistence of overweight into adulthood is moderate for overweight and obese youth. However, predictive values varied considerably. Limiting aspects with respect to generalizability and methodological issues are discussed.

"This book discusses the most important techniques available for longitudinal data analysis, from simple techniques such as the paired t-test and summary statistics, to more sophisticated ones such as generalized estimating of equations and mixed model analysis. A distinction is made between longitudinal analysis with continuous, dichotomous and categorical outcome variables. The emphasis of the discussion lies in the interpretation and comparison of the results of the different techniques. The second edition includes new chapters on the role of the time variable and presents new features of longitudinal data analysis. Explanations have been clarified where necessary and several chapters have been completely rewritten. The analysis of data from experimental studies and the problem of missing data in longitudinal studies are discussed. Finally, an extensive overview and comparison of different software packages is provided. This practical guide is essential for non-statisticians and researchers working with longitudinal data from epidemiological and clinical studies"--

AIMS/HYPOTHESIS: An earlier meta-analysis showed that diabetes is a risk factor for the development and/or recurrence of depression. Yet whether this risk is different for studies using questionnaires than for those relying on diagnostic criteria for depression has not been examined. This study examined the association of diabetes and the onset of depression by reviewing the literature and conducting a meta-analysis of longitudinal studies on this topic. METHODS: EMBASE, MEDLINE and PsycInfo were searched for articles published up to September 2009. All studies that examined the relationship between type 2 diabetes and the onset of depression were included. Pooled relative risks were calculated using fixed and random effects models. RESULTS: Eleven studies met our inclusion criteria for this meta-analysis. Based on the pooled data, including 48,808 cases of type 2 diabetes without depression at baseline, the pooled relative risk was 1.24 (95% CI 1.09-1.40) for the random effects model. This risk was significantly higher for studies relying on diagnostic criteria of depression than for studies using questionnaires. However, this difference was no longer significant when controlled for year of publication. CONCLUSIONS/INTERPRETATION: Compared with non-diabetic controls, people with type 2 diabetes have a 24% increased risk of developing depression. The mechanisms underlying this relationship are still unclear and warrant further research.