ArticleBMC public health2023
Research on the relationship between common metabolic syndrome and meteorological factors in Wuhu, a subtropical humid city of China.
Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 7 citations in OpenAlex.
- Seasonal Variation in Metabolic Syndrome and Its Association With Meteorological Factors: A Large Population-Based Study in Fukushima, 2012-2022.Journal of epidemiology and global health · 2026Article
- Effects of temperature and humidity on hospitalizations for metabolic syndrome with cerebral infarction among older adults in Panzhihua: a distributed lag non-linear model analysis.Frontiers in public health · 2026Article
- Lethal Heat and Humidity Events.Annual review of environment and resources · 2025Article
- County-level modeled extreme heat risk and premature all-cause mortality related to cardio-kidney-metabolic syndrome in the United States: A cross-sectional analysis.American journal of preventive cardiology · 2025Article
- Exploring the effect of a sweltering environment on the risk of death from cardiovascular diseases.Frontiers in neurology · 2024Article
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Authors and funding
13 authors at 3 institutions in 1 country.
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Abstract
As climate conditions deteriorate, human health faces a broader range of threats. This study aimed to determine the risk of death from metabolic syndrome (MetS) due to meteorological factors. We collected daily data from 2014 to 2020 in Wuhu City, including meteorological factors, environmental pollutants and death data of common MetS (hypertension, hyperlipidemia and diabetes), as well as a total number of 15,272 MetS deaths. To examine the relationship between meteorological factors, air pollutants, and MetS mortality, we used a generalized additive model (GAM) combined with a distributed delay nonlinear model (DLNM) for time series analysis. The relationship between the above factors and death outcomes was preliminarily evaluated using Spearman analysis and structural equation modeling (SEM). As per out discovery, diurnal temperature range (DTR) and daily mean temperature (T mean) increased the MetS mortality risk notably. The ultra low DTR raised the MetS mortality risk upon the general people, with the highest RR value of 1.033 (95% CI: 1.002, 1.065) at lag day 14. In addition, T mean was also significantly associated with MetS death. The highest risk of ultra low and ultra high T mean occured on the same day (lag 14), RR values were 1.043 (95% CI: 1.010, 1.077) and 1.032 (95% CI: 1.003, 1.061) respectively. Stratified analysis's result showed lower DTR had a more pronounced effect on women and the elderly, and ultra low and high T mean was a risk factor for MetS mortality in women and men. The elderly need to take extra note of temperature changes, and different levels of T mean will increase the risk of death. In warm seasons, ultra high RH and T mean can increase the mortality rate of MetS patients.
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