Clustering of Lifestyle Behaviors and Their Association With Risk of Metabolic Syndrome Among Adults in Taiwan: Nationwide Cross-Sectional Study.

Abstract

Background: Metabolic syndrome (MetS) is a multifaceted health condition influenced by physiological and lifestyle factors, leading to increased risks of cardiovascular disease and other chronic health issues. Lifestyle behaviors often manifest in various clustering patterns, and evidence of their impact on MetS remains limited.

Objective: This study explores the relationship of latent classes of lifestyle behaviors with the risk of MetS and its components.

Methods: This cross-sectional study used data from Taiwan's 2020-2022 Adult Preventive Health Services Database, which was linked to 2020-2022 National Health Insurance claim data. The study included 241,156 adults aged 40 years and older who participated in adult preventive health services between 2020 and 2022. Lifestyle behaviors were assessed through smoking, alcohol consumption, betel quid chewing, and physical activities. Latent class analysis was used to identify lifestyle behavior patterns, while binary logistic regression examined the association of these patterns with MetS risk and its components.

Results: The latent class analysis identified 5 distinct lifestyle behavior patterns, with an overall MetS prevalence of 35.72% (86,143/241,156). Compared to the "healthy lifestyle" group (27,465/241,156, 11.39% prevalence), the "insufficiently physically active (IPA)" group (182,101/241,156, 75.51%, adjusted odds ratio [aOR] 1.41, 95% CI 1.37-1.45; P<.001), the "occasional drinking but physically active" group (18,244/241,156, 7.57%, aOR 1.27, 95% CI 1.21-1.32; P<.001), the "occasional drinking and regular smoking with IPA" group (9539/241,156, 3.96%, aOR 2.38, 95% CI 2.26-2.50; P<.001), and the "unhealthy in all behaviors" group (3807/241,156, 1.58%, aOR 2.38, 95% CI 2.22-2.55; P<.001) showed significantly higher odds of developing MetS. Compared to the "healthy lifestyle" group, all other lifestyle patterns were also associated with significantly higher odds of central obesity (P<.001), elevated blood pressure (P<.001), elevated fasting blood glucose (P<.001), elevated fasting triglycerides (P<.001), and reduced high-density lipoprotein cholesterol (P<.001), with the most potent effects observed in the "occasional drinking and regular smoking with IPA" group and the "unhealthy in all behaviors" group. An exception was noted for the "occasional drinking but physically active" group, which showed a significantly lower likelihood of reduced high-density lipoprotein cholesterol (aOR 0.90, 95% CI 0.85-0.94; P<.001).

Conclusions: Engaging in sufficient physical activity and adopting multibehavior interventions tailored to specific lifestyle patterns are crucial for effectively preventing MetS in adults.