Lara J Morris1, Catherine D'Este2, Kerry Sargent-Cox3, Kaarin J Anstey4. 1. Centre for Research on Ageing, Health and Wellbeing, Research School of Population Health, Australian National University, Building 62, Eggleston Road, Canberra, ACT 2601, Australia. Electronic address: Lara.morris@anu.edu.au. 2. National Centre for Epidemiology & Population Health, Research School of Population Health, Australian National University, Building 62, Eggleston Road, Canberra, ACT 2601, Australia. Electronic address: Catherine.deste@anu.edu.au. 3. Centre for Research on Ageing, Health and Wellbeing, Research School of Population Health, Australian National University, Building 62, Eggleston Road, Canberra, ACT 2601, Australia. Electronic address: Kerry.sargent-cox@anu.edu.au. 4. Centre for Research on Ageing, Health and Wellbeing, Research School of Population Health, Australian National University, Building 62, Eggleston Road, Canberra, ACT 2601, Australia. Electronic address: Kaarin.anstey@anu.edu.au.
Abstract
OBJECTIVE: To examine clustering among three major lifestyle risk factors for chronic disease (smoking, alcohol, and physical inactivity) and define sociodemographic subgroups with elevated risks of multiple lifestyle risk factors. METHOD: Data on 6052 adults aged 28-32, 48-52, and 68-72 from wave 3 (2007-2010) of the PATH Through Life Cohort Study, Australia, were used to estimate prevalence of individual and combinations of risk factors, and multinomial regression analysis undertaken to examine demographic factors associated with number of risks. RESULTS: Clustering of risks varied by age and gender, with more people than expected having none or all of the risk factors. Smoking clustered with harmful alcohol use, as well as physical inactivity. No relationship was observed between physical inactivity and alcohol use. Several sociodemographic characteristics were associated with the number of lifestyle risk factors including partner status, gender, age, education, and physical and mental health related quality of life. CONCLUSIONS: The tendency for lifestyle risk factors to aggregate in different subgroups has meaningful implications for health promotion strategies. Better insight in the more vulnerable subpopulations that are at higher risk of displaying multiple lifestyle risk factors is of importance if we wish to reduce the population propensity for chronic disease.
OBJECTIVE: To examine clustering among three major lifestyle risk factors for chronic disease (smoking, alcohol, and physical inactivity) and define sociodemographic subgroups with elevated risks of multiple lifestyle risk factors. METHOD: Data on 6052 adults aged 28-32, 48-52, and 68-72 from wave 3 (2007-2010) of the PATH Through Life Cohort Study, Australia, were used to estimate prevalence of individual and combinations of risk factors, and multinomial regression analysis undertaken to examine demographic factors associated with number of risks. RESULTS: Clustering of risks varied by age and gender, with more people than expected having none or all of the risk factors. Smoking clustered with harmful alcohol use, as well as physical inactivity. No relationship was observed between physical inactivity and alcohol use. Several sociodemographic characteristics were associated with the number of lifestyle risk factors including partner status, gender, age, education, and physical and mental health related quality of life. CONCLUSIONS: The tendency for lifestyle risk factors to aggregate in different subgroups has meaningful implications for health promotion strategies. Better insight in the more vulnerable subpopulations that are at higher risk of displaying multiple lifestyle risk factors is of importance if we wish to reduce the population propensity for chronic disease.
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