Trend in obesity prevalence in European adult cohort populations during follow-up since 1996 and their predictions to 2015

TY - JOUR

T1 - Trend in obesity prevalence in European adult cohort populations during follow-up since 1996 and their predictions to 2015

AU - Ruesten, Anne von

AU - Steffen, Annika

AU - Floegel, Anna

AU - A, Daphne L van der

AU - Masala, Giovanna

AU - Tjønneland, Anne

AU - Halkjaer, Jytte

AU - Palli, Domenico

AU - Wareham, Nicholas J

AU - Loos, Ruth J F

AU - Sørensen, Thorkild I A

AU - Boeing, Heiner

PY - 2011/11/10

Y1 - 2011/11/10

N2 - Objective: To investigate trends in obesity prevalence in recent years and to predict the obesity prevalence in 2015 in European populations. Methods: Data of 97 942 participants from seven cohorts involved in the European Prospective Investigation into Cancer and Nutrition (EPIC) study participating in the Diogenes project (named as "Diogenes cohort" in the following) with weight measurements at baseline and follow-up were used to predict future obesity prevalence with logistic linear and non-linear (leveling off) regression models. In addition, linear and leveling off models were fitted to the EPIC-Potsdam dataset with five weight measures during the observation period to find out which of these two models might provide the more realistic prediction. Results: During a mean follow-up period of 6 years, the obesity prevalence in the Diogenes cohort increased from 13% to 17%. The linear prediction model predicted an overall obesity prevalence of about 30% in 2015, whereas the leveling off model predicted a prevalence of about 20%. In the EPIC-Potsdam cohort, the shape of obesity trend favors a leveling off model among men (R 2 = 0.98), and a linear model among women (R 2 = 0.99). Conclusion: Our data show an increase in obesity prevalence since the 1990ies, and predictions by 2015 suggests a sizeable further increase in European populations. However, the estimates from the leveling off model were considerably lower.

AB - Objective: To investigate trends in obesity prevalence in recent years and to predict the obesity prevalence in 2015 in European populations. Methods: Data of 97 942 participants from seven cohorts involved in the European Prospective Investigation into Cancer and Nutrition (EPIC) study participating in the Diogenes project (named as "Diogenes cohort" in the following) with weight measurements at baseline and follow-up were used to predict future obesity prevalence with logistic linear and non-linear (leveling off) regression models. In addition, linear and leveling off models were fitted to the EPIC-Potsdam dataset with five weight measures during the observation period to find out which of these two models might provide the more realistic prediction. Results: During a mean follow-up period of 6 years, the obesity prevalence in the Diogenes cohort increased from 13% to 17%. The linear prediction model predicted an overall obesity prevalence of about 30% in 2015, whereas the leveling off model predicted a prevalence of about 20%. In the EPIC-Potsdam cohort, the shape of obesity trend favors a leveling off model among men (R 2 = 0.98), and a linear model among women (R 2 = 0.99). Conclusion: Our data show an increase in obesity prevalence since the 1990ies, and predictions by 2015 suggests a sizeable further increase in European populations. However, the estimates from the leveling off model were considerably lower.

U2 - 10.1371/journal.pone.0027455

DO - 10.1371/journal.pone.0027455

M3 - Journal article

SN - 1932-6203

VL - 6

SP - e27455

JO - PLoS Computational Biology

JF - PLoS Computational Biology

IS - 11

ER -