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Hospital admissions attributable to reduced air pollution due to clean-air policies in China

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Huimeng Liu
Huimeng Liu
Huimeng Liu
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Jian Lei
Jian Lei
Jian Lei
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Yuewei Liu
Yuewei Liu
Yuewei Liu
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Tong Zhu
Tong Zhu
Tong Zhu
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Abstract and Figures

The Air Pollution Prevention and Control Action Plan (APPCAP) is considered to be the most stringent air pollution control policy in China implemented since 2013. This policy is a milestone in China to mitigate serious air pollution. However, health benefits attributable to reduced fine-particulate air pollution after the implementation of the APPCAP have not been quantitatively estimated on a PM2.5 constituent-specific and morbidity cause-specific basis. Here we conducted a nationwide case-crossover study based on hospital admission records in 292 Chinese cities during 2013-2017. Compared with 2013, the annual average concentrations of PM2.5 and black carbon (BC) in 2017 decreased by 28.61% and 20.35%, respectively. As a result, the average relative reductions in annual attributable fractions of nine major cause-specific hospital admissions associated with PM2.5 and BC were 30.00% and 21.14%, respectively, among which annual attributable fraction for depression showed the largest reduction. Nationally, cities with higher reductions in PM2.5 and BC were found to have higher absolute reductions in annual hospital admission attributable fractions associated with PM2.5 and BC, and geographic inequality in health benefits still existed. Our study highlights the substantial wide-ranging health benefits of reduced PM2.5 and BC levels following the nationwide implementation of the APPCAP in China.
Spatial distribution of city-specific annual absolute declining rates of ambient PM2.5 and its major constituents in 292 Chinese cities of prefecture level or above during 2013-2017 City-specific annual absolute declining rates in ambient PM2.5 and its major constituents were estimated by the Theil-Sen median slope estimator (presented in micrograms per cubic meter per year). Deeper color presents a larger decline per year. Cities in gray were not included in the analyses because no hospital admission data were available during the study period.
Spatial distribution of city-specific annual absolute declining rates of ambient PM2.5 and its major constituents in 292 Chinese cities of prefecture level or above during 2013-2017 City-specific annual absolute declining rates in ambient PM2.5 and its major constituents were estimated by the Theil-Sen median slope estimator (presented in micrograms per cubic meter per year). Deeper color presents a larger decline per year. Cities in gray were not included in the analyses because no hospital admission data were available during the study period.
… 
Annual attributable fractions of major cause-specific hospital admissions associated with ambient PM2.5 and BC at lag01 in 292 Chinese cities of prefecture level or above during 2013-2017 The annual attributable fractions for cause-specific hospital admissions were calculated based on the exposure-response relationships with a theoretical minimal risk exposure level of 0 μg/m³ as the reference concentration. Annual attributable fractions of hospital admissions for asthma were not included in the figure because of the insignificant associations with PM2.5 and BC. Annual attributable fractions of major cause-specific hospital admissions were calculated based on relative risks generated from the basic single-constituent model and were calculated for cities with hospital admission data in that year. Each dot represents a point estimate of the annual attributable fraction. Each line connecting the points presents the trend of annual attributable hospital admission fractions associated with ambient PM2.5 and BC.
Annual attributable fractions of major cause-specific hospital admissions associated with ambient PM2.5 and BC at lag01 in 292 Chinese cities of prefecture level or above during 2013-2017 The annual attributable fractions for cause-specific hospital admissions were calculated based on the exposure-response relationships with a theoretical minimal risk exposure level of 0 μg/m³ as the reference concentration. Annual attributable fractions of hospital admissions for asthma were not included in the figure because of the insignificant associations with PM2.5 and BC. Annual attributable fractions of major cause-specific hospital admissions were calculated based on relative risks generated from the basic single-constituent model and were calculated for cities with hospital admission data in that year. Each dot represents a point estimate of the annual attributable fraction. Each line connecting the points presents the trend of annual attributable hospital admission fractions associated with ambient PM2.5 and BC.
… 
Total avoided numbers of cause-specific hospital admissions attributable to cumulative reductions in ambient PM2.5 and BC in 292 Chinese cities of prefecture level or above during 2014-2017 compared with 2013 Supplementary Table 15 shows the summary admission numbers for different cause-specific hospital admissions during the study period. Overall, n = 48,623,468. Error bars represent 95% CIs. Each line connecting the error bars illustrates the range of avoided number of cause-specific hospital admissions attributable to the cumulative reduction in PM2.5 or BC during 2014-2017 compared with 2013.
Total avoided numbers of cause-specific hospital admissions attributable to cumulative reductions in ambient PM2.5 and BC in 292 Chinese cities of prefecture level or above during 2014-2017 compared with 2013 Supplementary Table 15 shows the summary admission numbers for different cause-specific hospital admissions during the study period. Overall, n = 48,623,468. Error bars represent 95% CIs. Each line connecting the error bars illustrates the range of avoided number of cause-specific hospital admissions attributable to the cumulative reduction in PM2.5 or BC during 2014-2017 compared with 2013.
… 
Spatial distribution of city-specific absolute reductions in annual average concentrations of ambient PM2.5 and BC and average annual hospital admission attributable fractions of nine major cause-specific hospital admissions associated with ambient PM2.5 and BC in 292 Chinese cities of prefecture level or above in 2017 compared with 2013 a,c, Spatial distribution of city-specific absolute reductions in annual average concentrations of ambient PM2.5 (a) and BC (c). b,d, Spatial distribution of city-specific absolute reductions in annual hospital admission attributable fractions associated with ambient PM2.5 (b) and BC (d). City-specific annual attributable fractions were averaged for nine major cause-specific hospital admissions with significant associations with PM2.5 and BC. Absolute reduction in annual attributable fraction was calculated by subtracting the annual attributable fraction in 2017 from the annual attributable fraction in 2013 for each city. For cities with data fewer than 5 years (the number of cities with data fewer than 5 years ranged from 54 for depression to 87 for heart failure), absolute reductions in annual attributable fraction were calculated by subtracting the annual attributable fraction in the last year with data from the annual attributable fraction in the first year with data, and absolute reductions in PM2.5 and BC were calculated by subtracting the annual average concentrations in the last year with data from the annual average concentrations in the first year with data. The annual attributable fractions for cause-specific hospital admissions were calculated based on the exposure-response relationships with a theoretical minimal risk exposure level of 0 μg/m³ as the reference concentration. Negative numbers in absolute reductions represent increases in air pollution concentrations and attributable fractions over the study period. Deeper color presents a larger decline. Cities in gray were not included in the analyses because no hospital admission data were available during the study period.
Spatial distribution of city-specific absolute reductions in annual average concentrations of ambient PM2.5 and BC and average annual hospital admission attributable fractions of nine major cause-specific hospital admissions associated with ambient PM2.5 and BC in 292 Chinese cities of prefecture level or above in 2017 compared with 2013 a,c, Spatial distribution of city-specific absolute reductions in annual average concentrations of ambient PM2.5 (a) and BC (c). b,d, Spatial distribution of city-specific absolute reductions in annual hospital admission attributable fractions associated with ambient PM2.5 (b) and BC (d). City-specific annual attributable fractions were averaged for nine major cause-specific hospital admissions with significant associations with PM2.5 and BC. Absolute reduction in annual attributable fraction was calculated by subtracting the annual attributable fraction in 2017 from the annual attributable fraction in 2013 for each city. For cities with data fewer than 5 years (the number of cities with data fewer than 5 years ranged from 54 for depression to 87 for heart failure), absolute reductions in annual attributable fraction were calculated by subtracting the annual attributable fraction in the last year with data from the annual attributable fraction in the first year with data, and absolute reductions in PM2.5 and BC were calculated by subtracting the annual average concentrations in the last year with data from the annual average concentrations in the first year with data. The annual attributable fractions for cause-specific hospital admissions were calculated based on the exposure-response relationships with a theoretical minimal risk exposure level of 0 μg/m³ as the reference concentration. Negative numbers in absolute reductions represent increases in air pollution concentrations and attributable fractions over the study period. Deeper color presents a larger decline. Cities in gray were not included in the analyses because no hospital admission data were available during the study period.
… 
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Nature Medicine | Volume 31 | May 2025 | 1688–1697 1688
nature medicine
Article
https://doi.org/10.1038/s41591-025-03515-y
Hospital admissions attributable to reduced
air pollution due to clean-air policies in China
Huimeng Liu1,2,3,4,17, Jian Lei1,2,3,4,17, Yuewei Liu 5 , Tong Zhu 6,
Kahung Chan 7, Xi Chen 8, Jing Wei9, Furong Deng10, Ge Li1,2,3,4,
Yunxing Jiang1,2,3,4, Lijun Bai1,2,3,4, Kai Wang1,2,3,4, Juan Chen1,2,3,4, Yang Lan1,2,3,4,
Xi Xia 1,2,3,4, Jinxi Wang11, Chen Wei11, Yinxiang Li12, Renjie Chen 13,
Jicheng Gong6, Xiaoli Duan14, Kai Zhang15, Haidong Kan 13, Xiaoming Shi 16,
Xinbiao Guo 10 & Shaowei Wu 1,2,3,4
The Air Pollution Prevention and Control Action Plan (APPCAP) is considered
to be the most stringent air pollution control policy in China implemented
since 2013. This policy is a milestone in China to mitigate serious air
pollution. However, health benets attributable to reduced ne-particulate
air pollution after the implementation of the APPCAP have not been
quantitatively estimated on a PM2.5 constituent-specic and morbidity
cause-specic basis. Here we conducted a nationwide case-crossover study
based on hospital admission records in 292 Chinese cities during 2013-
2017. Compared with 2013, the annual average concentrations of PM2.5 and
black carbon (BC) in 2017 decreased by 28.61% and 20.35%, respectively.
As a result, the average relative reductions in annual attributable fractions
of nine major cause-specic hospital admissions associated with PM2.5 and
BC were 30.00% and 21.14%, respectively, among which annual attributable
fraction for depression showed the largest reduction. Nationally, cities
with higher reductions in PM2.5 and BC were found to have higher absolute
reductions in annual hospital admission attributable fractions associated
with PM2.5 and BC, and geographic inequality in health benets still existed.
Our study highlights the substantial wide-ranging health benets of reduced
PM2.5 and BC levels following the nationwide implementation of the APPCAP
in China.
To date, ambient particulate matter remains a major contributor
to global disease burden. Strong evidence has linked exposure to par-
ticulate matter with an aerodynamic diameter of 2.5 μm or less (PM
2.5
)
pollution to an array of adverse health outcomes, including mortality
or morbidity of respiratory disease
1
, cardiovascular disease (CVD)
2
and
mental health conditions3. In particular, short-term exposure to PM2.5
has been found to trigger the onset of disease episodes such as cardio-
vascular events and psychiatric symptom episodes, which may request
subsequent hospital admissions for intensive treatment
4,5
. Compared
with mortality, morbidity risk measured by hospital admission may
serve as a more sensitive health indicator to capture the acute health
effects of environmental exposures5–7.
With the rapid economic growth and urban development over
the three decades from the 1980s to the 2000s, China has experienced
severe fine-particulate air pollution8. To mitigate fine-particulate air pol-
lution levels and related health impacts, the State Council of China intro-
duced the Air Pollution Prevention and Control Action Plan (APPCAP)
in 2013. This plan introduced ten specific measures spanning industrial
emissions control, clean energy promotion, vehicle emission standards
improvements, air-quality monitoring systems optimization and tax
Received: 8 July 2024
Accepted: 15 January 2025
Published online: 14 March 2025
Check for updates
A full list of afiliations appears at the end of the paper. e-mail: liuyuewei@mail.sysu.edu.cn; shaowei_wu@xjtu.edu.cn
Content courtesy of Springer Nature, terms of use apply. Rights reserved
... From 2013 to 2021, the PM2.5 concentration decreased from 48.0 µg/m 3 to 27. µg/m 3 , with more significant reductions in key regions such as Beijing-Tianjin-Hebei, th Yangtze River Delta, and the Pearl River Delta [28]. The division of the five major ke control regions in China is primarily based on the severity of pollution and administrativ divisions, facilitating regional joint prevention and control [29]. However, from the per ...
... From 2013 to 2021, the PM 2.5 concentration decreased from 48.0 µg/m 3 to 27.3 µg/m 3 , with more significant reductions in key regions such as Beijing-Tianjin-Hebei, the Yangtze River Delta, and the Pearl River Delta [28]. The division of the five major key control regions in China is primarily based on the severity of pollution and administrative divisions, facilitating regional joint prevention and control [29]. However, from the perspective of health risk prevention and control, this division still has certain limitations. ...
... The delineation of health risk prevention and control areas provides targeted strategies for air pollution management and risk avoidance for both the government and the public. For the government, different types of control areas require specific measures: in coordinated prevention and control areas, the focus should be on the synergistic control of O 3 and PM 2.5 , based on their regional and seasonal correlations [24,25]; in PM 2.5 prevention and control areas, emphasis should be placed on reducing both primary and secondary PM 2.5 emissions, while promoting green transformation in industry and transportation [28]; in O 3 prevention and control areas, controlling VOCs and NOx precursors and updating species-specific emission inventories are key [29]. For the public, raising environmental health awareness is critical [30][31][32]. ...
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  • Mar 2023
  • EUR HEART J
Aims: The available literature on morbidity risk of cardiovascular diseases associated with ambient ozone pollution is still limited. This study examined the potential acute effects of exposure to ambient ozone pollution on hospital admissions of cardiovascular events in China. Methods and results: A two-stage multi-city time-series study approach was used to explore the associations of exposure to ambient ozone with daily hospital admissions (n = 6 444 441) for cardiovascular events in 70 Chinese cities of prefecture-level or above during 2015-17. A 10 μg/m3 increment in 2-day average daily 8 h maximum ozone concentrations was associated with admission risk increases of 0.46% [95% confidence interval (CI): 0.28%, 0.64%] in coronary heart disease, 0.45% (95% CI: 0.13%, 0.77%) in angina pectoris, 0.75% (95% CI: 0.38%, 1.13%) in acute myocardial infarction (AMI), 0.70% (95% CI: 0.41%, 1.00%) in acute coronary syndrome, 0.50% (95% CI: 0.24%, 0.77%) in heart failure, 0.40% (95% CI: 0.23%, 0.58%) in stroke and 0.41% (95% CI: 0.22%, 0.60%) in ischemic stroke, respectively. The excess admission risks for these cardiovascular events associated with high ozone pollution days (with 2-day average 8-h maximum concentrations ≥100 µg/m3 vs. < 70 µg/m3) ranged from 3.38% (95% CI: 1.73%, 5.06%) for stroke to 6.52% (95% CI: 2.92%, 10.24%) for AMI. Conclusion: Ambient ozone was associated with increased hospital admission risk for cardiovascular events. Greater admission risks for cardiovascular events were observed under high ozone pollution days. These results provide evidence for the harmful cardiovascular effects of ambient ozone and call for special attention on the control of high ozone pollution.
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