A spatiotemporal analysis of the association between carbon productivity, socioeconomics, medical resources and cardiovascular diseases in southeast rural China

Bibliographic Data

ID22078931
AuthorsXuwei Tang (0000-0002-0702-6719, Fujian Medical University), Zhiying Zhan (Fujian Medical University), Zhi-Ying Zhan, Zhixiang Rao (Fujian Medical University), Haiyin Fang, Hai-Yin Fang (Fujian Medical University), Jian Jiang (0009-0006-7198-3966, Fujian Medical University, corresponding author), Xiangju Hu (Gansu Provincial Center for Disease Control and Prevention), Zhijian Hu (0000-0002-6889-0789, Fujian Medical University, corresponding author)
Year2023
Volume11
Pages1079702-1079702
Publication date2023-07-06
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2023.1079702
PMID37483926
OpenAlexW4383314405
LanguageEN
Citations received1
References cited52

Introduction With China’s rapid industrialization and urbanization, China has been increasing its carbon productivity annually. Understanding the association between carbon productivity, socioeconomics, and medical resources with cardiovascular diseases (CVDs) may help reduce CVDs burden. However, relevant studies are limited. Objectives The study aimed to describe the temporal and spatial distribution pattern of CVDs hospitalization in southeast rural China and to explore its influencing factors. Methods In this study, 1,925,129 hospitalization records of rural residents in southeast China with CVDs were analyzed from the New Rural Cooperative Medical Scheme (NRCMS). The spatial distribution patterns were explored using Global Moran’s I and Local Indicators of Spatial Association (LISA). The relationships with influencing factors were detected using both a geographically and temporally weighted regression model (GTWR) and multiscale geographically weighted regression (MGWR). Results In southeast China, rural inpatients with CVDs increased by 95.29% from 2010 to 2016. The main groups affected were elderly and women, with essential hypertension (26.06%), cerebral infarction (17.97%), and chronic ischemic heart disease (13.81%) being the leading CVD subtypes. The results of LISA shows that central and midwestern counties, including Meilie, Sanyuan, Mingxi, Jiangle, and Shaxian, showed a high-high cluster pattern of CVDs hospitalization rates. Negative associations were observed between CVDs hospitalization rates and carbon productivity, and positive associations with per capita GDP and hospital beds in most counties ( p < 0.05). The association between CVDs hospitalization rates and carbon productivity and per capita GDP was stronger in central and midwestern counties, while the relationship with hospital bed resources was stronger in northern counties. Conclusion Rural hospitalizations for CVDs have increased dramatically, with spatial heterogeneity observed in hospitalization rates. Negative associations were found with carbon productivity, and positive associations with socioeconomic status and medical resources. Based on our findings, we recommend low-carbon development, use of carbon productivity as an environmental health metric, and rational allocation of medical resources in rural China

China · Economic growth · Environmental health · Geography · Industrialisation · Per capita · Population · Productivity · Urbanization · Climate Change and Health Impacts · Demography · Energy, Environment, Economic Growth · Health, Environment, Cognitive Aging · Medicine

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