Seasonal Variation in Metabolic Syndrome and Its Association With Meteorological Factors: A Large Population-Based...

Seasonal variation in metabolic risk may be associated with meteorological factors, with potential implications for the prevention and control of metabolic syndrome (MetS). However, evidence on these patterns in large populations remains limited.

This study included 2,913,636 health checkup records from insured adults aged 35-74 years in Fukushima, Japan, between April 2012 and March 2022. Descriptive time-series analyses were conducted to examine seasonal variation in MetS prevalence and metabolic components. Generalised estimating equation models were used to assess associations of season with MetS status and metabolic components, while generalised additive models were applied to evaluate non-linear associations between meteorological factors and MetS status.

Overall, 26.3% of men and 8.9% of women had MetS. Compared with spring, after adjustment for meteorological factors, the odds of having MetS were 3% and 7% higher in autumn and winter in men, and 7% and 7% higher in women, respectively. Lower temperatures were associated with higher odds of having MetS in both sexes. Sunshine duration showed sex-specific associations: both shorter and longer sunshine duration were associated with lower odds of having MetS in men, whereas longer sunshine duration was associated with higher odds of having MetS in women. Waist circumference was significantly associated with temperature in women but not in men, and showed an approximately linear association with sunshine duration in men and a J-shaped association in women. Non-linear associations between meteorological factors and other metabolic components were also observed in both sexes. In particular, temperature was inversely associated with systolic and diastolic blood pressure and high-density lipoprotein cholesterol, moderately associated with fasting plasma glucose, and showed an approximately U-shaped association with triglycerides.

MetS status and metabolic components showed seasonal variation and were associated with meteorological conditions, particularly ambient temperature. These findings may help inform seasonal strategies for metabolic risk prevention and control.