Clusters of midlife women by physical activity and their racial/ethnic differences
- Authors
- Im, Eun-Ok; Ko, Young; Chee, Eunice; Chee, Wonshik; Mao, Jun James
- Issue Date
- Apr-2017
- Publisher
- LIPPINCOTT WILLIAMS & WILKINS
- Keywords
- Cluster analysis; Ethnicity; Middle age; Physical activity; Race; Women
- Citation
- MENOPAUSE-THE JOURNAL OF THE NORTH AMERICAN MENOPAUSE SOCIETY, v.24, no.4, pp.417 - 425
- Journal Title
- MENOPAUSE-THE JOURNAL OF THE NORTH AMERICAN MENOPAUSE SOCIETY
- Volume
- 24
- Number
- 4
- Start Page
- 417
- End Page
- 425
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/6281
- DOI
- 10.1097/GME.0000000000000769
- ISSN
- 1072-3714
- Abstract
- Objective: The purpose of this study was to identify clusters of midlife women by physical activity and to determine racial/ethnic differences in physical activities in each cluster. Methods: This was a secondary analysis of the data from 542 women (157 non-Hispanic [NH] Whites, 127 Hispanics, 135 NH African Americans, and 123 NH Asian) in a larger Internet study on midlife women's attitudes toward physical activity. The instruments included the Barriers to Health Activities Scale, the Physical Activity Assessment Inventory, the Questions on Attitudes toward Physical Activity, Subjective Norm, Perceived Behavioral Control, and Behavioral Intention, and the Kaiser Physical Activity Survey. The data were analyzed using hierarchical cluster analyses, analysis of variance, and multinominal logistic analyses. Results: A three-cluster solution was adopted: cluster 1 (high active living and sports/exercise activity group; 48%), cluster 2 (high household/caregiving and occupational activity group; 27%), and cluster 3 (low active living and sports/exercise activity group; 26%). There were significant racial/ethnic differences in occupational activities of clusters 1 and 3 (all P < 0.01). Compared with cluster 1, cluster 2 tended to have lower family income, less access to health care, higher unemployment, higher perceived barriers scores, and lower social influences scores (all P < 0.01). Compared with cluster 1, cluster 3 tended to have greater obesity, less access to health care, higher perceived barriers scores, more negative attitudes toward physical activity, and lower self-efficacy scores (all P < 0.01). Conclusions: Midlife women's unique patterns of physical activity and their associated factors need to be considered in future intervention development.
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