Lifestyle and socioeconomic determinants of multimorbidity patterns among mid-aged women: a longitudinal dtudy

Jackson, Caroline A., Dobson, Annette J., Tooth, Leigh R. and Mishra, Gita D. (2016) Lifestyle and socioeconomic determinants of multimorbidity patterns among mid-aged women: a longitudinal dtudy. Plos One, 11 6: . doi:10.1371/journal.pone.0156804


Author Jackson, Caroline A.
Dobson, Annette J.
Tooth, Leigh R.
Mishra, Gita D.
Title Lifestyle and socioeconomic determinants of multimorbidity patterns among mid-aged women: a longitudinal dtudy
Journal name Plos One   Check publisher's open access policy
ISSN 1932-6203
Publication date 2016-06-03
Year available 2016
Sub-type Article (original research)
DOI 10.1371/journal.pone.0156804
Open Access Status DOI
Volume 11
Issue 6
Total pages 16
Place of publication San Francisco, CA, United States
Publisher Public Library of Science
Collection year 2017
Language eng
Formatted abstract
Background: Little is known about patterns of associative multimorbidity and their aetiology. We aimed to identify patterns of associative multimorbidity among mid-aged women and the lifestyle and socioeconomic factors associated with their development.

Methods: Participants were from the Australian Longitudinal Study on Women's Health. We included 4896 women born 1946-51, without multimorbidity in 1998. We identified multimorbidity patterns at survey 6 (2010) using factor analysis, and related these patterns to baseline lifestyle and socioeconomic factors using logistic regression. We dichotomised factor scores and determined odds ratios (ORs) with 95% confidence intervals (CIs) for associations between characteristics and odds of a high versus low factor score.

Results: We identified five multimorbidity patterns: psychosomatic; musculoskeletal; cardiometabolic; cancer; and respiratory. Overweight and obesity were respectively associated with increased odds of having a high score for the musculoskeletal (adjusted ORs 1.45 [95% CI 1.23, 1.70] and 2.14 [95% CI 1.75, 2.60]) and cardiometabolic (adjusted ORs 1.53 [95% CI 1.31, 1.79] and 2.46 [95% CI 2.02, 2.98]) patterns. Physical inactivity was associated with increased odds of a high score for the psychosomatic, musculoskeletal and cancer patterns (adjusted ORs 1.41 [95% CI 1.13, 1.76]; 1.39 [95% CI 1.11, 1.74]; and 1.35 [95% CI 1.08, 1.69]). Smoking was associated with increased odds of a high score for the respiratory pattern. Education and ability to manage on income were associated with increased odds of a high score for the psychosomatic pattern (adjusted ORs 1.34 [95% CI 1.03, 1.75] and 1.73 [95% CI 1.37, 1.28], respectively) and musculoskeletal pattern (adjusted ORs 1.43 [95% CI 1.10, 1.87] and 1.38 [1.09, 1.75], respectively).

Conclusions: Distinct multimorbidity patterns can be identified among mid-aged women. Social inequality, physical activity and BMI are risk factors common to multiple patterns and are appropriate targets for reducing the risk of specific multimorbidity groups in mid-life women.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
School of Public Health Publications
 
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