Development and validation of a lifestyle risk index to screen for metabolic syndrome and its components in two multi-ethnic cohorts

Authors

Shan Xuan Lim, Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore. Electronic address: shan_xuan_lim@u.nus.edu.
Charlie Guan Lim, Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
Falk Müller-Riemenschneider, Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore; Digital Health Centre, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Rob M. van Dam, Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore; Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA.
Xueling Sim, Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
Mary Foong-Fong Chong, Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
Airu Chia, Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore. Electronic address: chia-airu@nus.edu.sg.

Document Type

Journal Article

Publication Date

12-18-2023

Journal

Preventive medicine

DOI

10.1016/j.ypmed.2023.107821

Keywords

Diet; Health behavior; Health status indicators; Healthy lifestyle; Metabolic syndrome; Sedentary behavior

Abstract

BACKGROUND: Metabolic syndrome (MetS) is a precursor to cardiovascular diseases and type 2 diabetes. Existing MetS prediction models relied heavily on biochemical measures and those based on non-invasive predictors such as lifestyle behaviours were limited. We aim to (1) develop a weighted lifestyle risk index for MetS and (2) externally validate this index using two Asian-based cohorts in Singapore. METHODS: Using data from the Multi-Ethnic Cohort (MEC) 1 (n = 2873, 41% male), multiple logistic regression was used to identify predictors associated with MetS. A weighted lifestyle risk index was generated using coefficients of the selected predictors in the development cohort (MEC1). Subsequently, the performance of the lifestyle risk index in predicting the occurrence of MetS within 10 years was assessed by discrimination and calibration in an external validation cohort (MEC2) (n = 6070, 43% male). RESULTS: A lifestyle risk index for MetS with nine predictors was developed (age, sex, ethnicity, having a family history of diabetes, BMI, diet, physical activity, smoking status, and screen time). This index demonstrated acceptable discrimination in the development cohort [AUC (95% CI) = 0.74 (0.71, 0.76)] and the validation cohort [AUC (95% CI) = 0.79 (0.77, 0.81)]. CONCLUSION: This lifestyle risk index exhibits potential for risk stratification in population-based screening programmes. Future research could apply a similar methodology to develop disease-specific lifestyle risk indices using nationwide registry-based data.

APA Citation

Lim, Shan Xuan; Lim, Charlie Guan; Müller-Riemenschneider, Falk; van Dam, Rob M.; Sim, Xueling; Chong, Mary Foong-Fong; and Chia, Airu, "Development and validation of a lifestyle risk index to screen for metabolic syndrome and its components in two multi-ethnic cohorts" (2023). GW Authored Works. Paper 3939.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/3939

Department

Exercise and Nutrition Sciences