Spatial spill-over effects of air pollution on aortality in Gansu Province, China

Data Availability. The datasets analysed during the study are available at: http://www.cnemc.cn/ and http://tjj.gansu.gov.cn/tjj/c109464/info_disp.shtml

KEYWORDS

mortality

air quality index

spatial econometrics analysis

TOPICS

State of the health of rural communities depending on various factors: social factors, accessibility of medical care, etc.

ABSTRACT

Introduction and objective:
Currently, air pollution remains a significant factor affecting health. The aim of the study is to explore the spatial distribution characteristics of air pollutants in Gansu Province, China, as well as the direct effects and spatial spill-over effects of air pollutants on mortality rates in various regions of the province.

Material and methods:
Panel data was collected from 2015–2022 (excluding 2020) and employed a panel spatial autoregressive model with fixed effects for both time and space, using three types of spatial weight matrices to explore the spatial impacts of air pollution on mortality rates among residents.

Results:
It was found that the mortality rate and degree of air pollution across various areas of Gansu were not randomly distributed, but showed obvious correlations and spatial aggregation characteristics. The median air quality index value significantly influenced the mortality rate of residents, and air pollution showed a spatial spill-over effect on the mortality rate. Mortality rates of the permanent population in a specific area were influenced not only by local air pollution but also by air pollution in neighbouring or economically-related areas. Numerical values of the direct and spatial spill-over effect of air pollution were calculated.

Conclusions:
It was concluded that air pollution significantly impacts the mortality rate among Gansu’s permanent residents through spatial spill-over effects. Collaborative efforts by governments across different regions are essential to mitigate the detrimental health effects of air pollution.

ABBREVIATIONS

– AQI – Air Quality Index; – PM10 – Particulate Matter; – PM2.5 – Inhalable particles – GDP – Gross Domestic Product – LISA – Local Indicator of Spatial Association – TLRM – Traditional Linear Regression Model – SAR – Spatial Autoregressive Model – SEM – Spatial Error Model – LM – Lagrange Multiplier tests – H-H – both the observed value of the local variable and its weighted average among neighbours exceed the overall average – L-L – both the observed and the neighboring weighted averages fall below the overall average – H-L – the observed value exceeds the average, but the weighted average among neighbours does not – L-H – the observed value falls below the average, but the weighted average among neighbours does not

ACKNOWLEDGEMENTS

The author expresses thanks to all members of the scientific research team and the researchers who participated in the study.

FUNDING

The study was supported by the National Natural Science Foundation of China (No.71861026).

REFERENCES (23)

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