Clustering of lifestyle factors and association with overweight in adolescents of the Kiel Obesity Prevention Study

Datos Bibliográficos

ID15095347
AutoresBeate Landsberg (Christian-Albrechts-Universität zu Kiel), Sandra Plachta-Danielzik, Sandra Plachta‐Danielzik (0000-0002-1945-4198, Christian-Albrechts-Universität zu Kiel), Dominique Lange (Christian-Albrechts-Universität zu Kiel), Maike Johannsen (Christian-Albrechts-Universität zu Kiel), Jasmin Seiberl (Christian-Albrechts-Universität zu Kiel), Manfred J Müller (0000-0001-9698-075X, Christian-Albrechts-Universität zu Kiel, autor de correspondencia)
Año2010
Volumen13
Número10A
Páginas1708-1715
Fecha de publicación2010-10-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaPublic Health Nutrition (JOURNAL)
Identificadores de la revistaISSN: 1368-9800 • E-ISSN: 1475-2727
EditorialCambridge University Press (CUP) (PUBLISHER)
DOI10.1017/s1368980010002260
PMID20883570
OpenAlexW2133081690
IdiomaEN
Citas recibidas14
Referencias citadas38

Objective To identify lifestyle clusters in adolescents and to characterize their association with overweight and obesity. Design Cross-sectional and longitudinal data of the Kiel Obesity Prevention Study. Setting Schools in Kiel, Germany. Subjects and methods Cross-sectional data of 1894 adolescents aged 14 years and 4-year longitudinal data of a subsample of 389 children aged 10 and 14 years. Self-reported data of physical activity, modes of commuting to school, media time, nutrition, alcohol consumption and smoking were used to identify lifestyle clusters with two-step cluster analysis. Obesity indices (height, weight, waist circumference and fat mass (FM)) were measured. Results Three lifestyle clusters were identified: a ‘low activity and low-risk behaviour’ cluster (cluster 1: n 740, 39·1 %); a ‘high media time and high-risk behaviour’ cluster (cluster 2: n 498, 26·3 %); and a ‘high activity and medium-risk behaviour’ cluster (cluster 3: n 656, 34·6 %). Strictly speaking, none of these clusters was considered to be markedly healthy. The prevalence of overweight and obesity tended to be lower in cluster 3 (15·9 %) than in clusters 1 (20·4 %) and 2 (20·5 %; P = 0·053). Longitudinally, 4-year changes in FM were found to be lowest in cluster 2, but the 4-year incidence rate of obesity was lowest in cluster 3. Conclusions Explicit healthy lifestyles do not exist, but an active lifestyle reduces the incidence of obesity. In adolescents, health promotion should take into account the diversity of lifestyles and address specific lifestyle clusters

Body mass index · Cluster (spacecraft · Cross-sectional study · Environmental health · Incidence (geometry · Longitudinal study · Obesity · Overweight · Screen time · Waist · Demography · Health and Lifestyle Studies · Medicine · Obesity, Physical Activity, Diet · Physical Activity and Health · Gerontology · Internal Medicine