Cargando…

Typical patterns of modifiable health risk factors (MHRFs) in elderly women in Germany: results from the cross-sectional German Health Update (GEDA) study, 2009 and 2010

BACKGROUND: Modifiable health risk factors (MHRFs) significantly affect morbidity and mortality rates and frequently occur in specific combinations or risk clusters. Using five MHRFs (smoking, high-risk alcohol consumption, physical inactivity, low intake of fruits and vegetables, and obesity) this...

Descripción completa

Detalles Bibliográficos
Autores principales: Jentsch, Franziska, Allen, Jennifer, Fuchs, Judith, von der Lippe, Elena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5379506/
https://www.ncbi.nlm.nih.gov/pubmed/28372561
http://dx.doi.org/10.1186/s12905-017-0380-4
_version_ 1782519619950477312
author Jentsch, Franziska
Allen, Jennifer
Fuchs, Judith
von der Lippe, Elena
author_facet Jentsch, Franziska
Allen, Jennifer
Fuchs, Judith
von der Lippe, Elena
author_sort Jentsch, Franziska
collection PubMed
description BACKGROUND: Modifiable health risk factors (MHRFs) significantly affect morbidity and mortality rates and frequently occur in specific combinations or risk clusters. Using five MHRFs (smoking, high-risk alcohol consumption, physical inactivity, low intake of fruits and vegetables, and obesity) this study investigates the extent to which risk clusters are observed in a representative sample of women aged 65 and older in Germany. Additionally, the structural composition of the clusters is systematically compared with data and findings from other countries. METHODS: A pooled data set of Germany’s representative cross-sectional surveys GEDA09 and GEDA10 was used. The cohort comprised 4,617 women aged 65 and older. Specific risk clusters based on five MHRFs are identified, using hierarchical cluster analysis. The MHRFs were defined as current smoking (daily or occasionally), risk alcohol consumption (according to the Alcohol Use Disorders Identification Test, a sum score of 4 or more points), physical inactivity (less active than 5 days per week for at least 30 min and lack of sports-related activity in the last three months), low intake of fruits and vegetables (less than one serving of fruits and one of vegetables per day), and obesity (a body mass index equal to or greater than 30). A total of 4,292 cases with full information on these factors are included in the cluster analysis. Extended analyses were also performed to include the number of chronic diseases by age and socioeconomic status of group members. RESULTS: A total of seven risk clusters were identified. In a comparison with data from international studies, the seven risk clusters were found to be stable with a high degree of structural equivalency. CONCLUSION: Evidence of the stability of risk clusters across various study populations provides a useful starting point for long-term targeted health interventions. The structural clusters provide information through which various MHRFs can be evaluated simultaneously.
format Online
Article
Text
id pubmed-5379506
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-53795062017-04-07 Typical patterns of modifiable health risk factors (MHRFs) in elderly women in Germany: results from the cross-sectional German Health Update (GEDA) study, 2009 and 2010 Jentsch, Franziska Allen, Jennifer Fuchs, Judith von der Lippe, Elena BMC Womens Health Research Article BACKGROUND: Modifiable health risk factors (MHRFs) significantly affect morbidity and mortality rates and frequently occur in specific combinations or risk clusters. Using five MHRFs (smoking, high-risk alcohol consumption, physical inactivity, low intake of fruits and vegetables, and obesity) this study investigates the extent to which risk clusters are observed in a representative sample of women aged 65 and older in Germany. Additionally, the structural composition of the clusters is systematically compared with data and findings from other countries. METHODS: A pooled data set of Germany’s representative cross-sectional surveys GEDA09 and GEDA10 was used. The cohort comprised 4,617 women aged 65 and older. Specific risk clusters based on five MHRFs are identified, using hierarchical cluster analysis. The MHRFs were defined as current smoking (daily or occasionally), risk alcohol consumption (according to the Alcohol Use Disorders Identification Test, a sum score of 4 or more points), physical inactivity (less active than 5 days per week for at least 30 min and lack of sports-related activity in the last three months), low intake of fruits and vegetables (less than one serving of fruits and one of vegetables per day), and obesity (a body mass index equal to or greater than 30). A total of 4,292 cases with full information on these factors are included in the cluster analysis. Extended analyses were also performed to include the number of chronic diseases by age and socioeconomic status of group members. RESULTS: A total of seven risk clusters were identified. In a comparison with data from international studies, the seven risk clusters were found to be stable with a high degree of structural equivalency. CONCLUSION: Evidence of the stability of risk clusters across various study populations provides a useful starting point for long-term targeted health interventions. The structural clusters provide information through which various MHRFs can be evaluated simultaneously. BioMed Central 2017-04-04 /pmc/articles/PMC5379506/ /pubmed/28372561 http://dx.doi.org/10.1186/s12905-017-0380-4 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Jentsch, Franziska
Allen, Jennifer
Fuchs, Judith
von der Lippe, Elena
Typical patterns of modifiable health risk factors (MHRFs) in elderly women in Germany: results from the cross-sectional German Health Update (GEDA) study, 2009 and 2010
title Typical patterns of modifiable health risk factors (MHRFs) in elderly women in Germany: results from the cross-sectional German Health Update (GEDA) study, 2009 and 2010
title_full Typical patterns of modifiable health risk factors (MHRFs) in elderly women in Germany: results from the cross-sectional German Health Update (GEDA) study, 2009 and 2010
title_fullStr Typical patterns of modifiable health risk factors (MHRFs) in elderly women in Germany: results from the cross-sectional German Health Update (GEDA) study, 2009 and 2010
title_full_unstemmed Typical patterns of modifiable health risk factors (MHRFs) in elderly women in Germany: results from the cross-sectional German Health Update (GEDA) study, 2009 and 2010
title_short Typical patterns of modifiable health risk factors (MHRFs) in elderly women in Germany: results from the cross-sectional German Health Update (GEDA) study, 2009 and 2010
title_sort typical patterns of modifiable health risk factors (mhrfs) in elderly women in germany: results from the cross-sectional german health update (geda) study, 2009 and 2010
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5379506/
https://www.ncbi.nlm.nih.gov/pubmed/28372561
http://dx.doi.org/10.1186/s12905-017-0380-4
work_keys_str_mv AT jentschfranziska typicalpatternsofmodifiablehealthriskfactorsmhrfsinelderlywomeningermanyresultsfromthecrosssectionalgermanhealthupdategedastudy2009and2010
AT allenjennifer typicalpatternsofmodifiablehealthriskfactorsmhrfsinelderlywomeningermanyresultsfromthecrosssectionalgermanhealthupdategedastudy2009and2010
AT fuchsjudith typicalpatternsofmodifiablehealthriskfactorsmhrfsinelderlywomeningermanyresultsfromthecrosssectionalgermanhealthupdategedastudy2009and2010
AT vonderlippeelena typicalpatternsofmodifiablehealthriskfactorsmhrfsinelderlywomeningermanyresultsfromthecrosssectionalgermanhealthupdategedastudy2009and2010