Web‐Based Data to Quantify Meteorological and Geographical Effects on Heat Stroke: Case Study in China. (6th August 2022)

• Record Type: Journal Article
• Authors: Han, Qinmei; Liu, Zhao; Jia, Junwen; Anderson, Bruce T.; Xu, Wei; Shi, Peijun
• Is Part Of: GeoHealth. Volume 6:Number 8(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-08-06
• Subjects: internet search data -- random forest -- heat strokes -- meteorological variables -- spatial variations -- China; Environmental health -- Periodicals; Electronic journals; Periodicals; 616.98
• DOI: 10.1029/2022GH000587
• Languages: English
• ISSNs: 2471-1403

Abstract

Abstract: Heat stroke is a serious heat‐related health outcome that can eventually lead to death. Due to the poor accessibility of heat stroke data, the large‐scale relationship between heat stroke and meteorological factors is still unclear. This work aims to clarify the potential relationship between meteorological variables and heat stroke, and quantify the meteorological threshold that affected the severity of heat stroke. We collected daily heat stroke search index (HSSI) and meteorological data for the period 2013–2020 in 333 Chinese cities to analyze the relationship between meteorological variables and HSSI using correlation analysis and Random forest (RF) model. Temperature and relative humidity (RH) accounted for 62% and 9% of the changes of HSSI, respectively. In China, cases of heat stroke may start to occur when temperature exceeds 36°C and RH exceeds 58%. This threshold was 34.5°C and 79% in the north of China, and 36°C and 48% in the south of China. Compared to RH, the threshold of temperature showed a more evident difference affected by altitude and distance from the ocean, which was 35.5°C in inland cities and 36.5°C in coastal cities; 35.5°C in high‐altitude cities and 36°C in low‐altitude cities. Our findings provide a possible way to analyze the interaction effect of meteorological variables on heat‐related illnesses, and emphasizes the effects of geographical environment. The meteorological threshold quantified in this research can also support policymaker to establish a better meteorological warning system for public health. Plain Language Summary: The impact of extreme heat events on population has become of urgent public health concern. In China, the real mortality and morbidity data are not publicly available and data of some diseases are not enough recorded. Thus, it is difficult to build a solid relationship between heat strokes and meteorological variables in large spatial scale. Internet search data, highly correlated with real heat stoke cases, was adopted as a new data set in our research instead of the heat‐related morbidity data to investigate the relationship between heat strokes and multiple meteorological variables. According to Random forest model, temperature and relative humidity (RH) were identified as the most important factor, which mainly affected the severity of heat strokes. We quantified the meteorological threshold that affected the severity of heat strokes as well. Heat strokes may start to occur when temperature exceeds 36°C and RH exceeds 58% in China. The temperature of this threshold is higher in the south or low‐latitude region or coastal region of China. This work provides new insights for health research and help to timely alert the public in adverse weather conditions. Key Points: Internet search data could help to evaluate the health impact in large scale to address the data shortage Increasing temperature and relative humidity (RH) led to sharply increased heat stroke, particularly when maximum temperature exceeds 36°C and RH exceeds 58% Meteorological threshold was affected by geographical factors like altitude, latitude and distance from ocean