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Development and validation of a lifestyle risk index to screen for metabolic syndrome and its components in two multi-ethnic cohorts.
Lim, Shan Xuan; Lim, Charlie Guan Yi; Müller-Riemenschneider, Falk; van Dam, Rob M; Sim, Xueling; Chong, Mary Foong-Fong; Chia, Airu.
Affiliation
  • Lim SX; 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.
  • Lim CGY; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
  • Müller-Riemenschneider F; 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.
  • van Dam RM; 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.
  • Sim X; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
  • Chong MF; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
  • Chia A; Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore. Electronic address: chia-airu@nus.edu.sg.
Prev Med ; 179: 107821, 2024 Feb.
Article in En | MEDLINE | ID: mdl-38122937
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.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Metabolic Syndrome / Diabetes Mellitus, Type 2 Limits: Female / Humans / Male Language: En Journal: Prev Med Year: 2024 Type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Metabolic Syndrome / Diabetes Mellitus, Type 2 Limits: Female / Humans / Male Language: En Journal: Prev Med Year: 2024 Type: Article