Stability of clustering of lifestyle risk factors in the Dutch adult population and the association with mental health

Abstract Background Lifestyle factors often co-occur in clusters. This study examines whether clusters of lifestyle risk factors, such as smoking, alcohol use, physical inactivity, poor diet, sexual risk behaviour, cannabis and other drug use, change over time in a representative sample of Dutch adults. Additionally, the association between mental health and self-reported depression of lifestyle clusters was examined. Methods Each year cross-sectional data of approximately 7500 individuals of 18 years and older from the annual Dutch Health Survey of 2014–2019 were used. Clusters were determine... Mehr ...

Verfasser: Dorsman, Hannah
de Hollander, Ellen
Wendel-Vos, Wanda
van Rossum, Caroline
Kemler, Ellen
Hupkens, Christianne
Hosper, Karen
de Beurs, Derek
Hiemstra, Marieke
Dokumenttyp: Artikel
Erscheinungsdatum: 2023
Reihe/Periodikum: European Journal of Public Health ; volume 33, issue 6, page 1001-1007 ; ISSN 1101-1262 1464-360X
Verlag/Hrsg.: Oxford University Press (OUP)
Schlagwörter: Public Health / Environmental and Occupational Health
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-26659711
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : http://dx.doi.org/10.1093/eurpub/ckad116

Abstract Background Lifestyle factors often co-occur in clusters. This study examines whether clusters of lifestyle risk factors, such as smoking, alcohol use, physical inactivity, poor diet, sexual risk behaviour, cannabis and other drug use, change over time in a representative sample of Dutch adults. Additionally, the association between mental health and self-reported depression of lifestyle clusters was examined. Methods Each year cross-sectional data of approximately 7500 individuals of 18 years and older from the annual Dutch Health Survey of 2014–2019 were used. Clusters were determined by a two-step cluster analysis. Furthermore, regression analyses determined the association between clusters of lifestyle risk factors and mental health. Results Results show six clusters composed of one, multiple or no lifestyle risk factors. The clusters remained relatively stable over time: in some clusters, the number of people slightly changed between 2014 and 2019. More specifically, clusters that increased in size were the cluster with no lifestyle risk factors and the cluster with multiple lifestyle risk factors. Furthermore, results show that clusters with none to a few lifestyle risk factors were associated with better mental health and a lower prevalence of self-reported depression compared with clusters with multiple lifestyle risk factors. Conclusions The clustering of lifestyle risk factors remained stable over time. People with multiple lifestyle risk factors had poorer mental health than those without risk factors. These findings may emphasize the need for intervention strategies targeting this subgroup with multiple lifestyle risk factors.