Marita Södergren1, Wei Chun Wang2, Jo Salmon2, Kylie Ball2, David Crawford2, Sarah A McNaughton2. 1. Centre for Physical Activity and Nutrition Research, School of Exercise and Nutrition Sciences, Deakin University, 221 Burwood Hwy, Burwood, Victoria 3125, Australia; Centre of Family Medicine, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Alfred Nobels allé 12, SE-141 83 Huddinge, Sweden. Electronic address: marita.sodergren@ki.se. 2. Centre for Physical Activity and Nutrition Research, School of Exercise and Nutrition Sciences, Deakin University, 221 Burwood Hwy, Burwood, Victoria 3125, Australia.
Abstract
OBJECTIVES: The aim of this study was to identify subgroups of retirement age older adults with respect to their lifestyle patterns of eating, drinking, smoking, physical activity and TV viewing behaviors, and to examine the association between these patterns and socio-demographic covariates. METHODS: The sample consisted of 3133 older adults aged 55-65 years from the Wellbeing, Eating and Exercise for a Long Life (WELL) study, 2010. This study used latent class analysis (stratified by sex), with a set of lifestyle indicators and including socio-demographic covariates. Statistical analyses were performed by generalized linear latent and mixed models in Stata. RESULTS: Two classes of lifestyle patterns were identified: Healthy (53% men and 72% women) and less healthy lifestyles. Physical activity, TV-viewing time, and fruit intake were good indicators distinguishing the "Healthier" class, whereas consumption of vegetables, alcohol (men) and fast food (women) could not clearly discriminate older adults in the two classes. Class membership was associated with education, body mass index, and self-rated health. CONCLUSIONS: This study contributes to the literature on lifestyle behaviors among older adults, and provides evidence that there are meaningful sex differences in lifestyle behaviors between subgroups of older adults. From a policy perspective, understanding indicators or "markers" of healthy and less healthy lifestyle patterns is important for identifying target groups for interventions.
OBJECTIVES: The aim of this study was to identify subgroups of retirement age older adults with respect to their lifestyle patterns of eating, drinking, smoking, physical activity and TV viewing behaviors, and to examine the association between these patterns and socio-demographic covariates. METHODS: The sample consisted of 3133 older adults aged 55-65 years from the Wellbeing, Eating and Exercise for a Long Life (WELL) study, 2010. This study used latent class analysis (stratified by sex), with a set of lifestyle indicators and including socio-demographic covariates. Statistical analyses were performed by generalized linear latent and mixed models in Stata. RESULTS: Two classes of lifestyle patterns were identified: Healthy (53% men and 72% women) and less healthy lifestyles. Physical activity, TV-viewing time, and fruit intake were good indicators distinguishing the "Healthier" class, whereas consumption of vegetables, alcohol (men) and fast food (women) could not clearly discriminate older adults in the two classes. Class membership was associated with education, body mass index, and self-rated health. CONCLUSIONS: This study contributes to the literature on lifestyle behaviors among older adults, and provides evidence that there are meaningful sex differences in lifestyle behaviors between subgroups of older adults. From a policy perspective, understanding indicators or "markers" of healthy and less healthy lifestyle patterns is important for identifying target groups for interventions.
Keywords:
AIC; Akaike information criterion; BIC; BMI; Bayesian information criterion; CI; Food habits; Health behavior; Human activities; IPAQ; International Physical Activity Questionnaire; LCA; LTPA; Lifestyle; OR; WELL; Wellbeing, Eating and Exercise for a Long Life; body mass index; confidence interval; latent class analysis; leisure-time physical activity; odds ratio
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