Predicting healthy lifestyle patterns among retirement age older adults in the WELL study: A latent class analysis of sex differences

• Published in: Maturitas 2014-01, Vol.77 (1), p.41-46
• Main Authors: Södergren, Marita, Wang, Wei Chun, Salmon, Jo, Ball, Kylie, Crawford, David, McNaughton, Sarah A
• Format: Article
• Language: English
• Subjects: Biological and medical sciences; Body Mass Index; Educational Status; Female; Food habits; Gynecology. Andrology. Obstetrics; Health Behavior; Health Status; Human activities; Humans; Internal Medicine; Life Style; Lifestyle; Male; Medical sciences; Medicin och hälsovetenskap; Middle Aged; Obstetrics and Gynecology; Prevention and actions; Puberal and climacteric disorders (male and female); Public health. Hygiene; Public health. Hygiene-occupational medicine; Retirement; Sex Factors; Specific populations (family, woman, child, elderly...)
• ISSN: 0378-5122; 1873-4111; 1873-4111
• DOI: 10.1016/j.maturitas.2013.09.010

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.