Physical activity phenotypes identified by latent class analysis and their associations with metabolic syndrome among Korean adults

Metabolic syndrome is a major public health concern associated with increased risks of cardiovascular disease, type 2 diabetes, and premature mortality. Higher levels of physical activity have been associated with a lower prevalence of metabolic syndrome. Physical activity is a multidimensional behavior accumulated across occupational, transportation, leisure-time, and other domains. Conventional approaches examining individual activity components may not adequately capture how these behaviors coexist within individuals. This study aimed to identify physical activity phenotypes among Korean adults, evaluate their reproducibility, and examine their associations with metabolic syndrome. Data were obtained from 15,370 adults aged ≥ 19 years participating in the 2022–2024 Korea National Health and Nutrition Examination Survey. Latent class analysis using nine physical activity and sedentary behavior indicators was conducted in a 2022–2023 discovery sample and independently repeated in a 2024 validation sample. Pooled 2022–2024 data were used for association analyses. Survey-weighted multivariable logistic regression estimated odds ratios and 95% confidence intervals for metabolic syndrome, adjusting for demographic, lifestyle, and socioeconomic characteristics. Four phenotypes were identified, including Inactive (53.4%), Active All-rounders (22.8%), Active Commuters (18.8%), and Occupationally Active (5.0%). Phenotype profiles were highly reproducible in the validation sample, with correlations between corresponding profiles ranging from 0.995 to 1.000. Compared with the Inactive phenotype, Active All-rounders had lower odds of metabolic syndrome (odds ratio 0.63, 95% confidence interval 0.56–0.71; p < 0.001). Active Commuters also showed lower odds (odds ratio 0.87, 95% confidence interval 0.77–0.98; p = 0.019), although this association did not meet the Bonferroni-corrected significance threshold. The Occupationally Active phenotype was not significantly associated with metabolic syndrome (odds ratio 1.13, 95% confidence interval 0.93–1.37; p = 0.231). Distinct and reproducible physical activity phenotypes were identified among Korean adults. Engagement across multiple physical activity domains was associated with the lowest odds of metabolic syndrome, whereas occupational activity alone was not. These findings highlight the potential importance of considering the combination and context of physical activity behaviors for metabolic health.