Background: A risk-targeted prevention strategy may efficiently utilize limited resources available for prevention of overweight and obesity. Likewise, more efficient intervention trials could be designed if selection of subjects was based on risk. The aim of the study was to develop a risk score predicting substantial weight gain among German adults.
View Article and Find Full Text PDFAim: This study aims to quantify longitudinal changes in waist circumference (WC) among adults aged 45-64 years in Germany.
Methods: Data of 15,444 men and 17,207 women from one nationwide and six regional prospective German cohort studies were analyzed. The sex-specific mean change in WC per year of follow-up was assessed for each study separately.
Objective: To study the association between socioeconomic status (SES) and annual relative change in anthropometric markers in the general German adult population.
Methods: Longitudinal data of 56,556 participants aged 18-83 years from seven population-based German cohort studies (CARLA, SHIP, KORA, DEGS, EPIC-Heidelberg, EPIC-Potsdam, PopGen) were analyzed by meta-analysis using a random-effects model. The indicators of SES were education and household income.
Background/objectives: The objective of this study was to quantify body weight changes in German adult populations during the past decades.
Subjects/methods: Longitudinal analysis of seven cohort studies covering different age ranges between 18 and 83 years. Baseline examinations were between 1994 and 2007 and follow-up durations between 4.
Aims/hypothesis: Studies on weight cycling and the risk of type 2 diabetes have revealed inconsistent results, possibly due to differences in the definition of weight fluctuations. Here, we investigated whether weight cycling during adulthood is related to diabetes risk in a large cohort study, using a complementary approach to define patterns of weight development.
Methods: Weight cycling, weight loss and weight gain were defined (1) a priori, using distinct categories, and (2) by functional principal component analysis (FPCA) to capture weight patterns in greater detail.