中年妇女的健康行为概况:使用潜在类分析识别代谢综合征的危险亚组

Se Hee Min, Sharron L Docherty, Eun-Ok Im, Qing Yang
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引用次数: 5

摘要

背景:代谢综合征是一种由不良健康行为引起的生活方式疾病。然而,人们对具有不同健康行为特征的中年妇女的亚组知之甚少,她们有患代谢综合征的风险。目的:本研究旨在确定具有不同健康行为特征(体育活动、饮酒、饮食和吸烟)的中年妇女的潜在亚群,描述潜在亚群的特征,并研究潜在类成员与代谢综合征未来发展之间的关系。方法:这是一项二级数据分析,使用来自全国妇女健康研究(SWAN)的第1,3,5和7年的基线和随访数据(N = 3,100)。根据中年妇女不同的健康行为特征,使用潜在分类分析来确定潜在亚组。采用双变量和多元逻辑回归来检验每个潜在亚群的个体特征及其与代谢综合征未来发展的关系。结果:选取4类模型:1类(健康)、2类(健康除酒精)、3类(健康除饮食)和4类(不健康)。四个潜在类别的个体特征有显著差异(p < 0.001)。回归分析发现,与1班相比,2班在未来所有就诊中发生代谢综合征的几率较低,在第3次就诊时达到统计学意义(p < 0.05);而4班在除第3次就诊外的所有就诊中发生代谢综合征的几率均高于1班。结论:临床医生应根据本研究结果提供个性化的方法来促进中年妇女的健康行为,并指导今后健康促进项目的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Health Behavior Profiles Among Midlife Women: Identifying At-Risk Subgroups for Metabolic Syndrome Using Latent Class Analysis.

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.

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