Gender-differences in predictors for time to metabolic syndrome resolution: A secondary analysis of a randomized controlled trial study

Seung Ah Choe, Nan He Yoon, Seunghyun Yoo, Hyekyeong Kim

Research output: Contribution to journalArticlepeer-review

Abstract

Understanding gender differences in health-related behaviors and their impacts is a crucial aspect of effective primary care. We studied gender-based differences in predictors of metabolic syndrome (MetS) resolution among newly diagnosed MetS patients. This study was a secondary analysis of a prospective clinical trial study comprising of 637 middle-aged and older adults (226 men and 411 women) who underwent a regular health checkup and were newly diagnosed with MetS at 16 different health clinics of 14 metropolitan cities and provinces. We conducted Cox proportional hazard analysis to estimate cumulative probability of MetS resolution within a 12-month observation period. Among the 637 patients, 47.6% of participants achieved MetS resolution. The resolution rate was similar among men and women (44.7% and 49.1%, respectively, P = 0.320). Low household income (Hazard ratio = 2.62, 95% confidence interval: 1.13–6.08) and current employment (2.29, 1.26–4.13) were associated with a higher cumulative probability of MetS resolution in men than in women. For women, however, longer sleeping hours (1.18, 1.04–1.34) and living with a partner (1.58, 1.06–2.35) were positive predictors of MetS resolution. Being overweight (0.63, 0.44–0.89) was associated with lower cumulative probability of MetS resolution in women than in men. The factors associated with cumulative probability of MetS resolution within the 12-month follow-up were different between men and women. These findings facilitate further exploration on gender-based differences in risk factors for less optimal improvements in MetS.

Original languageEnglish
Article numbere0234035
JournalPLoS ONE
Volume15
Issue number6
DOIs
StatePublished - Jun 2020

Bibliographical note

Publisher Copyright:
© 2020 Choe et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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