Health Behavior Profiles Among Midlife Women: Identifying At-Risk Subgroups for Metabolic Syndrome Using Latent Class Analysis.

Journal Article (Journal Article)

Background

Metabolic syndrome is known as a lifestyle disease that results from poor health behaviors. Yet, little is known about the subgroups of midlife women with distinct health behavior profiles who are at risk for developing metabolic syndrome.

Purpose

This study aims to identify latent subgroups of midlife women with distinct health behavior profiles (physical activity, alcohol, diet, and smoking), to describe the characteristics of latent subgroups, and to examine the association between latent class membership and future development of metabolic syndrome.

Method

This is a secondary data analysis using baseline and follow-up data from years 1, 3, 5, and 7 (N = 3,100) from the Study of Women's Health Across the Nation (SWAN). Latent class analysis was used to identify latent subgroups of midlife women based on their distinct health behavior profiles. Bivariate and multiple logistic regression was conducted to examine the individual characteristics of each latent subgroup and its association with the future development of metabolic syndrome.

Result

A 4-class model was selected: Class 1 (Healthy), Class 2 (Healthy except alcohol), Class 3 (Healthy except diet), and Class 4 (Unhealthy). Significant differences in individual characteristics were found among the four latent classes (p < .001). The regression analysis found that Class 2 had lower odds of developing metabolic syndrome at all future visits with statistical significance reached at visit 3 (p < .05) while Class 4 had higher odds of developing metabolic syndrome at all visits except visit 3 when both compared to Class 1.

Conclusion

Clinicians should use the study findings to offer personalized approach to promote healthy behaviors and to guide future development of health promotion programs for midlife women.

Full Text

Duke Authors

Cited Authors

  • Min, SH; Docherty, SL; Im, E-O; Yang, Q

Published Date

  • August 2022

Published In

Volume / Issue

  • 56 / 9

Start / End Page

  • 946 - 958

PubMed ID

  • 35195674

Electronic International Standard Serial Number (EISSN)

  • 1532-4796

International Standard Serial Number (ISSN)

  • 0883-6612

Digital Object Identifier (DOI)

  • 10.1093/abm/kaac003

Language

  • eng