Seasonal variations of the prevalence of metabolic syndrome and its markers using big-data of health check-ups.
Hiroe SetoHiroshi TokiShuji KitoraAsuka OyamaRyohei YamamotoPublished in: Environmental health and preventive medicine (2024)
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.
Keyphrases
- insulin resistance
- metabolic syndrome
- big data
- risk factors
- artificial intelligence
- adipose tissue
- high fat diet induced
- machine learning
- type diabetes
- high fat diet
- healthcare
- skeletal muscle
- uric acid
- public health
- polycystic ovary syndrome
- working memory
- mental health
- health information
- body mass index
- weight loss
- heat stress
- risk assessment
- physical activity
- weight gain
- human health
- climate change
- social media