Seasonal variations of the prevalence of metabolic syndrome and its markers using big-data of health check-ups.

Metabolic syndrome STL Seasonal trend decomposition Seasonal variation Specific health checkups

Journal

Environmental health and preventive medicine
ISSN: 1347-4715
Titre abrégé: Environ Health Prev Med
Pays: Japan
ID NLM: 9609642

Informations de publication

Date de publication:
2024
Historique:
medline: 22 1 2024
pubmed: 22 1 2024
entrez: 21 1 2024
Statut: ppublish

Résumé

It is crucial to understand the seasonal variation of Metabolic Syndrome (MetS) for the detection and management of MetS. Previous studies have demonstrated the seasonal variations in MetS prevalence and its markers, but their methods are not robust. To clarify the concrete seasonal variations in the MetS prevalence and its markers, we utilized a powerful method called Seasonal Trend Decomposition Procedure based on LOESS (STL) and a big dataset of health checkups. A total of 1,819,214 records of health checkups (759,839 records for men and 1,059,375 records for women) between April 2012 and December 2017 were included in this study. We examined the seasonal variations in the MetS prevalence and its markers using 5 years and 9 months health checkup data and STL analysis. MetS markers consisted of waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), fasting plasma glucose (FPG). We found that the MetS prevalence was high in winter and somewhat high in August. Among men, MetS prevalence was 2.64 ± 0.42 (mean ± SD) % higher in the highest month (January) than in the lowest month (June). Among women, MetS prevalence was 0.53 ± 0.24% higher in the highest month (January) than in the lowest month (June). Additionally, SBP, DBP, and HDL-C exhibited simple variations, being higher in winter and lower in summer, while WC, TG, and FPG displayed more complex variations. This finding, complex seasonal variations of MetS prevalence, WC, TG, and FPG, could not be derived from previous studies using just the mean values in spring, summer, autumn and winter or the cosinor analysis. More attention should be paid to factors affecting seasonal variations of central obesity, dyslipidemia and insulin resistance.

Sections du résumé

BACKGROUND BACKGROUND
It is crucial to understand the seasonal variation of Metabolic Syndrome (MetS) for the detection and management of MetS. Previous studies have demonstrated the seasonal variations in MetS prevalence and its markers, but their methods are not robust. To clarify the concrete seasonal variations in the MetS prevalence and its markers, we utilized a powerful method called Seasonal Trend Decomposition Procedure based on LOESS (STL) and a big dataset of health checkups.
METHODS METHODS
A total of 1,819,214 records of health checkups (759,839 records for men and 1,059,375 records for women) between April 2012 and December 2017 were included in this study. We examined the seasonal variations in the MetS prevalence and its markers using 5 years and 9 months health checkup data and STL analysis. MetS markers consisted of waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), fasting plasma glucose (FPG).
RESULTS RESULTS
We found that the MetS prevalence was high in winter and somewhat high in August. Among men, MetS prevalence was 2.64 ± 0.42 (mean ± SD) % higher in the highest month (January) than in the lowest month (June). Among women, MetS prevalence was 0.53 ± 0.24% higher in the highest month (January) than in the lowest month (June). Additionally, SBP, DBP, and HDL-C exhibited simple variations, being higher in winter and lower in summer, while WC, TG, and FPG displayed more complex variations.
CONCLUSIONS CONCLUSIONS
This finding, complex seasonal variations of MetS prevalence, WC, TG, and FPG, could not be derived from previous studies using just the mean values in spring, summer, autumn and winter or the cosinor analysis. More attention should be paid to factors affecting seasonal variations of central obesity, dyslipidemia and insulin resistance.

Identifiants

pubmed: 38246652
doi: 10.1265/ehpm.23-00216
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2

Auteurs

Hiroe Seto (H)

Graduate School of Human Sciences, Osaka University.
Health Care Division, Health and Counseling Center, Osaka University.

Hiroshi Toki (H)

Health Care Division, Health and Counseling Center, Osaka University.
Research Center for Nuclear Physics, Osaka University.

Shuji Kitora (S)

Health Care Division, Health and Counseling Center, Osaka University.

Asuka Oyama (A)

Health Care Division, Health and Counseling Center, Osaka University.

Ryohei Yamamoto (R)

Health Care Division, Health and Counseling Center, Osaka University.
Laboratory of Behavioral Health Promotion, Department of Health Promotion, Graduate School of Medicine, Osaka University.

Classifications MeSH