Abstract
Background:
Epidemiological studies have demonstrated a causal relationship between ambient ozone (O3) and mortality from chronic obstructive pulmonary disease (COPD), which is the only outcome considered in the Global Burden of Disease Study 2021 for O3. This study aims to evaluate the temporal trend and spatial distribution of the COPD burden attributable to O3 across China from 1990 to 2021.
Methods:
The ambient O3 concentrations in China were estimated. Based on the methodology framework and standard analytical methods applied in the Global Burden of Disease Study 2021, we estimated the annual number, age-standardized rate, and percentage of deaths and disability-adjusted life-years (DALYs) from COPD attributable to O3 pollution during 1990–2021 at the national and provincial levels in China.
Results:
In 2021, a total of 125.7 (95% uncertainty interval [UI], 26.4–228.3) thousand deaths and 1917.5 (95% UI, 398.7–3504.6) thousand DALYs from COPD were attributable to ambient O3 pollution in China, accounting for 9.8% (95% UI, 2.1–17.0%) and 8.1% (95% UI, 1.8–14.1%) of the total COPD deaths and DALYs, respectively. Generally, a higher burden was observed among males, the elderly, and the population residing in regions with worse health conditions. The age-standardized rates of COPD deaths and DALYs per 100,000 populations ranged from 0.5 (95% UI, 0–1.4) and 8.1 (95% UI, 0.7–20.9) in Hong Kong to 22.8 (95% UI, 3.9–43.5) and 396.6 (95% UI, 68.9–763.7) in Xizang. From 1990 to 2021, there was a notable decrease in the age-standardized rates of COPD-related deaths (68.2%, 95% UI, 60.1–74.9%) and DALYs (71.5%, 95% UI, 63.7–77.6%), especially in regions with poor health conditions. However, the attributable numbers and percentages changed relatively marginally.
Conclusions:
Ambient O3 pollution is a major contributor to the COPD burden in China. Our findings highlight the significant spatial heterogeneity across different provinces and underscore the implementation of geographically tailored policies to effectively reduce O3 pollution and alleviate the associated disease burden.
Keywords: Ozone, Chronic obstructive pulmonary disease, Global Burden of Disease 2021, Death, Disability-adjusted life year
Introduction
Ambient air pollution is a leading environmental risk factor of premature mortality and disability worldwide.[1–3] Among various criteria air pollutants, ozone (O3) is the only air pollutant, besides fine particulate matter, that is widely recognized to have independent health effects.[4,5] O3 is a typical secondary pollutant formed by a series of sunlight-driven reactions involving volatile organic compounds and nitrogen oxides.[6] In the context of global climate change, ground-level O3 pollution is a growing challenge in high-income and low-and-middle-income countries.[7] In China, despite noteworthy reductions in particulate matter air pollution following clean air actions since 2013, O3 pollution has continuously increased and has become a prominent environmental issue.[8–10]
Existing evidence has demonstrated that among different health outcomes, only chronic obstructive pulmonary disease (COPD) is causally linked with O3.[11–14] COPD is a common chronic respiratory condition characterized by persistent and irreversible airflow obstruction that makes breathing difficult.[15,16] Previous evidence has further indicated a close association between COPD and other comorbid conditions, including respiratory infections, cardiovascular diseases, renal dysfunction, diabetes mellitus, depression, and anxiety.[17] During the past few decades, COPD has become one of the major causes of morbidity, mortality, and disability both globally and in China, resulting in considerable clinical, economic, and societal burdens.[18,19] According to the Global Burden of Diseases (GBD) Study 2021, there were approximately 3.7 million deaths due to COPD in 2021 worldwide, accounting for over 5% of the total deaths.[20] Given the rapidly aging trend in China, the burden of COPD is expected to increase in the coming decades.[15] Thus, it is crucial to evaluate the burden of COPD attributable to ambient O3 pollution and implement preventive measures to mitigate this disease burden.
In 2021, it is estimated that approximately 490,000 COPD deaths could be attributed to ambient O3 pollution globally, of which more than a quarter occurred in China.[5] Previously, several studies have examined the COPD burden associated with O3 exposure in China, most of which were limited to single cities or regions.[16,21] Only two nationwide studies have been conducted[22,23]; however, both were based on the GBD Study conducted before 2017 and neither provided annual estimates. Therefore, it is essential to assess the COPD burden attributable to O3 exposure at yearly and provincial levels across China based on the latest GBD data. This not only provides insights into the temporal trends and spatial distribution of the burden but also informs the development of targeted interventions to protect respiratory health in the future.
To address this gap, we conducted an in-depth evaluation on the annual disease burden of COPD attributable to ambient O3 pollution at both the national and provincial levels in China from 1990 to 2021, based on data from GBD 2021.
Methods
Overview
Data on the disease burden attributable to ambient O3 air pollution were extracted from the GBD Study 2021, which applied a health impact function to estimate O3 concentrations and O3-attributable COPD burden in 204 countries and territories and 811 subnational locations from 1990 to 2021 by sex and age categories. A detailed description of the methodology of the GBD Study 2021 and a comparative risk assessment involving the disease burden caused by ambient O3 were introduced comprehensively in a recently published paper.[5] This study summarizes the disease burden in China at the national and provincial levels. A total of 33 provincial administrative units were included, comprising 22 provinces, five autonomous regions, four municipalities, and two special administrative regions (i.e., the Hong Kong and Macao Special Administrative Regions). Data from the Taiwan Province of China were not included. Both mortality and disability-adjusted life-years (DALYs) attributable to ambient O3 air pollution were evaluated. Considering the anonymity of the GBD, ethical approval was not required.
Ambient O3 pollution estimation
Exposure to ambient O3 pollution was defined as the population-weighted highest seasonal (6-month) average of the 8-h daily maximum ozone concentrations. Exposure to ambient O3 pollution for each 0.1° × 0.1° grid cell globally from 1990 to 2017 was estimated by integrating O3 ground measurement data and chemical transport model estimates using Bayesian maximum entropy.[24] The exposure estimates for the later years were extrapolated from these results. The O3 monitoring data were obtained from the Tropospheric Ozone Assessment Report, which contains the world’s largest collection of surface O3 metrics.[24,25] A combination of global atmospheric chemical transport models was used in the analysis, many of which simulated the specified dynamics of the Chemistry-Climate Model Initiative.[26,27] The world is divided into eight regions: East Asia, South Central Asia, Oceania, Africa, Europe, Russia, South America, and North America. In each region, each model was weighted to minimize the difference between the multi-model averages and observations, as previously described.[4] China primarily falls within East Asia, with smaller areas extending into South Asia, Central Asia, and Russia.
Disease burden attributable to ambient O3 pollution
In the GBD Study 2021, the cause-specific burden of potential risk factors was assessed by calculating the attributable deaths and DALYs associated with various diseases. This estimation process was facilitated through a comparative risk assessment framework predicted on a causal web of hierarchically organized, potentially combinative, and modifiable risks. The detailed procedures have been published previously.[5] Specifically, a literature review of studies investigating long-term ozone exposure and COPD was conducted, and five cohorts from the USA, UK, and Canada were included.[28–30] Then, a Bayesian, regularized, trimmed meta-regression tool was used to conduct a meta-analysis of these five observations. As in the GBD 2019 Study, the theoretical minimum risk exposure level was based on the exposure distribution from the Cancer Prevention Study II by Turner et al[30]. It is a uniform distribution around the minimum and 5th percentile observed in the cohort (i.e., 29.1–35.7 part per billion [ppb]).
In this study, the number, age-standardized rate, and percentage of deaths and DALYs from COPD attributable to O3 air pollution in China from 1990 to 2021 were estimated. The corresponding disease burden is reported according to sex, age, and province. In accordance with earlier research in China,[22,31] the provincial administrative units were further categorized into five areas according to the health metrics including life expectancy, mortality of stomach, lung, liver, and esophageal cancer, as well as COPD, ischemic heart disease, and stroke. Health Area 1 has the lowest mortality rates, including Beijing, Hong Kong, Macao, Shanghai, Tianjin, and Zhejiang. Health Area 2 has a relatively high life expectancy and the lowest mortality rates of ischemic heart disease and stroke, including Fujian, Guangdong, Hainan, Hubei, Hunan, and Jiangsu. Health Area 3 has middle life expectancy, and higher mortality due to ischemic heart disease, stroke, and the four major cancers, including Anhui, Hebei, Heilongjiang, Henan, Inner Mongolia, Jilin, Liaoning, Ningxia, Shaanxi, Shandong, and Shanxi. Health Area 4 exhibits lower than average life expectancy, relatively low mortality from ischemic heart disease and stroke, and high mortality from COPD, including Chongqing, Gansu, Jiangxi, Sichuan, and Yunnan. Health Area 5 has the lowest average life expectancy, low mortality from ischemic heart disease, and high mortality from COPD, including Guangxi, Guizhou, Qinghai, Xizang, and Xinjiang. In general, from Health Areas 1–5, the overall health condition of the residents gradually deteriorates.
All results were reported as estimates and 95% uncertainty intervals (UIs) based on the 2.5th and 97.5th percentiles values of 500 draws (i.e., 500 random samples from the estimate’s distribution). All statistical analyses were conducted in R software (version 4.3.2) with “ggplot2” package.
Results
The COPD burden attributable to O3 pollution, as measured by the number, age-standardized rate, and percentage of deaths and DALYs, is listed in Tables 1 and 2. In 2021, there were 125.7 (95% UI, 26.4–228.3) thousand deaths and 1917.5 (95% UI 398.7–3504.6) thousand DALYs from COPD attributable to ambient O3 pollution in China, which accounted for 9.8% (95% UI, 2.1–17.0%) and 8.1% (95% UI, 1.8–14.1%) of the total deaths and DALYs due to COPD, respectively. The estimated age-standardized COPD death and DALY rates attributable to O3 were 7.2 (95% UI, 1.5–13.0) and 100.7 (95% UI, 21.1–182.8) per 100,000, respectively.
Table 1.
Deaths, age-standardized death rates, and percentage of deaths from COPD attributable to ambient ozone pollution in China during 1990 and 2021, n (95% UI).
| Parameters | Death (thousand) | Age-standardized death rate per 100,000 | Percentage of death (%) | ||||||
|---|---|---|---|---|---|---|---|---|---|
| 1990 | 2021 | Percent change (%) | 1990 | 2021 | Percent change (%) | 1990 | 2021 | Percent change | |
| Total | 120.6 (25.9, 212.6) | 125.7 (26.4, 228.3) | 4.2 (–19.0, 32.2) | 22.6 (4.8, 39.8) | 7.2 (1.5, 13.0) | −68.2 (–74.9, –60.1) | 9.7 (2.2, 17.1) | 9.8 (2.1, 17.0) | 0.3 (–2.5, 4.3) |
| Sex | |||||||||
| Male | 62.6 (14.0, 111.5) | 73.1 (14.6, 132.5) | 16.7 (–17.2, 52.0) | 27.9 (6.3, 49.0) | 10.3 (2.1, 18.7) | –62.9 (–73.8, –53.1) | 9.8 (2.2, 17.2) | 9.7 (2.1, 16.8) | –0.7 (–4.0, 3.1) |
| Female | 58.0 (11.8, 103.2) | 52.6 (11.1, 94.9) | –9.3 (–38.8, 41.7) | 19.4 (3.9, 34.6) | 5.2 (1.1, 9.4) | –73.1 (–81.7, –58.5) | 9.7 (2.2, 17.0) | 9.8 (2.2, 17.1) | 1.6 (–2.4, 8.1) |
| Age (years) | |||||||||
| ≤24 | – | – | – | – | – | – | – | – | – |
| 25–29 | 0.2 (0, 0.3) | 0 (0, 0.1) | –82.0 (–86.4, –74.0) | 0.1 (0, 0.2) | 0 (0, 0.1) | –77.2 (–82.8, –67.0) | 9.7 (2.2, 17.0) | 9.2 (2.0, 16.2) | –5.4 (–11.1, –0.1) |
| 30–34 | 0.3 (0.1, 0.5) | 0.1 (0, 0.1) | –69.7 (–76.8, –58.4) | 0.3 (0.1, 0.5) | 0.1 (0, 0.1) | –77.9 (–83.1, –69.7) | 9.8 (2.2, 17.0) | 9.6 (2.1, 16.8) | –2.1 (–7.0, 3.7) |
| 35–39 | 0.5 (0.1, 1.0) | 0.1 (0, 0.2) | –76.9 (–82.6, –65.7) | 0.6 (0.1, 1.1) | 0.1 (0, 0.2) | –80.1 (–85.0, –70.5) | 10.0 (2.3, 17.7) | 9.6 (2.1, 16.8) | –3.5 (–10.0, 2.2) |
| 40–44 | 0.9 (0.2, 1.6) | 0.2 (0.1, 0.4) | –74.2 (–80.7, –64.2) | 1.3 (0.3, 2.4) | 0.3 (0.1, 0.5) | –81.1 (–85.8, –73.7) | 9.9 (2.3, 17.3) | 9.4 (2.1, 16.6) | –4.4 (–9.4, 1.2) |
| 45–49 | 1.3 (0.3, 2.3) | 0.5 (0.1, 0.9) | –61.6 (–71.7, –45.7) | 2.5 (0.6, 4.4) | 0.4 (0.1, 0.8) | –82.0 (–86.7, –74.6) | 9.9 (2.3, 17.3) | 9.3 (2.1, 16.4) | –5.8 (–11.2, –0.5) |
| 50–54 | 3.1 (0.7, 5.4) | 1.3 (0.3, 2.4) | –57.5 (–69.5, –41.6) | 6.5 (1.4, 11.3) | 1.1 (0.2, 2.0) | –83.2 (–88.0, –76.9) | 9.8 (2.3, 17.0) | 9.5 (2.1, 16.3) | –3.6 (–9.0, 1.6) |
| 55–59 | 5.5 (1.2, 9.6) | 2.5 (0.5, 4.6) | –54.7 (–66.5, –35.7) | 12.6 (2.8, 22.1) | 2.3 (0.5, 4.2) | –82.1 (–86.8, –74.6) | 9.7 (2.2, 17.1) | 9.5 (2.1, 16.5) | –2.8 (–7.2, 2.8) |
| 60–64 | 9.6 (2.0, 16.8) | 3.9 (0.8, 7.0) | –59.6 (–70.9, –45.3) | 27.1 (5.7, 47.6) | 5.3 (1.1, 9.6) | –80.4 (–85.9, –73.5) | 9.8 (2.2, 17.3) | 9.7 (2.2, 17.0) | –0.9 (–5.7, 5.1) |
| 65–69 | 14.4 (3.1, 25.1) | 8.9 (1.8, 16.6) | –38.0 (–54.0, –15.8) | 52.8 (11.3, 91.9) | 11.6 (2.3, 21.7) | –78.0 (–83.7, –70.1) | 9.8 (2.2, 17.2) | 9.6 (2.2, 16.7) | –1.1 (–4.8, 3.8) |
| 70–74 | 23.1 (5.2, 41.0) | 16.4 (3.4, 29.6) | –29.2 (–46.9, –7.0) | 123.0 (27.6, 218.0) | 30.8 (6.3, 55.5) | –75.0 (–81.3, –67.2) | 9.8 (2.2, 17.3) | 9.7 (2.1, 16.6) | –1.4 (–5.0, 3.7) |
| 75–79 | 24.5 (5.0, 43.3) | 21.2 (4.4, 38.6) | –13.3 (–31.7, 11.2) | 215.3 (44.3, 380.4) | 64.1 (13.4, 116.7) | –70.2 (–76.5, –61.8) | 9.7 (2.2, 17.1) | 9.6 (2.1, 16.8) | –0.6 (–4.2, 4.1) |
| ≥80 | 37.2 (7.8, 64.5) | 70.5 (14.8, 126.0) | 89.2 (52.3, 134.9) | 508.0 (105.9, 880.1) | 214.3 (45.1, 383.0) | –57.8 (–66.1, –47.6) | 9.7 (2.1, 17.1) | 9.9 (2.2, 17.1) | 1.4 (–1.7, 5.6) |
COPD: Chronic obstructive pulmonary disease; UI: Uncertainty interval; –: Not available.
Table 2.
DALYs, age-standardized DALYs rates, and percentage of DALYs from COPD attributable to ambient ozone pollution in China during 1990 and 2021, n (95% UI).
| Parameters | DALY (thousand) | Age-standardized DALY rate per 100,000 | Percentage of DALY (%) | ||||||
|---|---|---|---|---|---|---|---|---|---|
| 1990 | 2021 | Percent change (%) | 1990 | 2021 | Percent change (%) | 1990 | 2021 | Percent change | |
| Total | 2354.9 (508.0, 4148.0) | 1917.5 (398.7, 3504.6) | –18.6 (–37.0, 5.2) | 353.9 (75.5, 625.8) | 100.7 (21.1, 182.8) | –71.5 (–77.6, –63.7) | 9.0 (2.0, 15.8) | 8.1 (1.8, 14.1) | –10.2 (–14.7, –4.6) |
| Sex | |||||||||
| Male | 1279.4 (282.2, 2292.4) | 1154.0 (230.8, 2111.3) | –9.8 (–37.5, 20.4) | 428.1 (96.5, 754.0) | 140.5 (28.2, 255.3) | –67.2 (–76.7, –57.4) | 9.2 (2.1, 16.3) | 8.5 (1.9, 14.9) | –7.3 (–11.7, –2.8) |
| Female | 1075.4 (218.7, 1920.6) | 763.5 (159.8, 1385.0) | –29.0 (–52.5, 14.7) | 301.1 (61.3, 536.3) | 72.5 (15.2, 131.4) | –75.9 (–83.8, –61.8) | 8.8 (2.0, 15.6) | 7.5 (1.6, 13.1) | –14.7 (–23.5, –1.8) |
| Age (years) | |||||||||
| ≤24 | – | – | – | – | – | – | – | – | – |
| 25–29 | 9.9 (2.2, 17.3) | 1.8 (0.4, 3.1) | –82.1 (–86.5, –74.1) | 9.0 (2.0, 15.7) | 2.0 (0.4, 3.6) | –77.3 (–82.9, –67.1) | 6.2 (1.4, 11.0) | 3.2 (0.7, 5.9) | –48.5 (–58.5, –37.2) |
| 30–34 | 15.2 (3.0, 26.9) | 4.6 (1.0, 8.3) | –69.6 (–76.8, –58.3) | 17.2 (3.4, 30.5) | 3.8 (0.8, 6.8) | –77.9 (–83.1, –69.6) | 7.1 (1.6, 12.5) | 4.0 (0.8, 7.4) | –42.9 (–52.5, –31.9) |
| 35–39 | 28.5 (6.0, 50.8) | 6.6 (1.5, 12.1) | –76.9 (–82.6, –65.7) | 31.2 (6.5, 55.6) | 6.2 (1.4, 11.4) | –80.1 (–85.0, –70.4) | 7.9 (1.8, 14.0) | 4.7 (1.0, 8.5) | –40.8 (–50.6, –28.9) |
| 40–44 | 43.2 (9.4, 76.1) | 11.1 (2.4, 20.1) | –74.3 (–80.7, –64.2) | 64.4 (14.1, 113.4) | 12.2 (2.6, 22.0) | –81.1 (–85.9, –73.8) | 8.5 (1.9, 14.8) | 5.6 (1.2, 9.8) | –34.2 (–43.1, –25.8) |
| 45–49 | 55.2 (12.3, 97.8) | 21.2 (4.3, 39.6) | –61.7 (–71.7, –45.9) | 107.0 (23.7, 189.4) | 19.2 (3.9, 35.9) | –82.1 (–86.8, –74.7) | 8.4 (1.9, 14.6) | 5.5 (1.2, 9.5) | –34.8 (–44.3, –25.3) |
| 50–54 | 118.4 (25.4, 206.0) | 50.3 (9.7, 92.8) | –57.5 (–69.5, –41.6) | 248.1 (53.2, 431.7) | 41.6 (8.0, 76.8) | –83.2 (–88.0, –76.9) | 8.7 (2.0, 15.3) | 6.2 (1.3, 10.8) | –29.3 (–37.8, –20.7) |
| 55–59 | 183.7 (40.5, 321.6) | 83.4 (16.7, 153.5) | –54.6 (–66.4, –35.6) | 423.5 (93.3, 741.6) | 75.8 (15.2, 139.6) | –82.1 (–86.7, –74.6) | 8.9 (2.0, 15.6) | 6.6 (1.4, 11.3) | –25.6 (–32.6, –17.2) |
| 60–64 | 276.8 (58.6, 485.7) | 111.5 (22.1, 202.5) | –59.7 (–71.0, –45.5) | 783.4 (165.9, 1374.6) | 152.7 (30.3, 277.4) | –80.5 (–86.0, –73.6) | 9.1 (2.1, 16.1) | 7.4 (1.6, 12.8) | –19.1 (–26.6, –11.4) |
| 65–69 | 349.8 (74.9, 608.5) | 216.4 (43.3, 403.0) | –38.1 (–54.1, –16.0) | 1282.1 (274.6, 2230.6) | 282.1 (56.4, 525.4) | –78.0 (–83.7, –70.1) | 9.1 (2.1, 16.0) | 7.7 (1.7, 13.2) | –16.0 (–22.1, –8.9) |
| 70–74 | 462.3 (103.9, 819.3) | 327.2 (66.9, 590.6) | –29.2 (–46.9, –7.1) | 2456.6 (551.9, 4354.1) | 614.0 (125.6, 1108.1) | –75.0 (–81.3, –67.2) | 9.3 (2.1, 16.4) | 8.2 (1.8, 14.3) | –11.9 (–17.1, –6.0) |
| 75–79 | 392.9 (80.8, 693.9) | 339.0 (70.8, 616.6) | –13.7 (–32.0, 10.7) | 3452.3 (709.7, 6097.5) | 1023.6 (213.9, 1861.9) | –70.4 (–76.6, –62.0) | 9.3 (2.1, 16.4) | 8.4 (1.8, 14.6) | –9.3 (–13.7, –3.6) |
| ≥80 | 419.1 (87.4, 725.7) | 744.5 (156.4, 1331.7) | 77.7 (42.4, 120.7) | 5716.3 (1191.7, 9898.4) | 2263.7 (475.4, 4049.0) | –60.4 (–68.3, –50.8) | 9.4 (2.1, 16.6) | 9.0 (2.0, 15.7) | –4.7 (–8.4, –0.1) |
COPD: Chronic obstructive pulmonary disease; DALYs: Disability-adjusted life-years; UI: Uncertainty interval; –: Not available.
There was higher O3-related COPD burden among males than in females. Specifically, a total of 73.1 (95% UI, 14.6–132.5) thousand deaths and 1154.0 (95% UI, 230.8–2111.3) thousand DALYs due to COPD were attributable to ambient O3 pollution among males, while 52.6 (95% UI, 11.1–94.9) thousand deaths and 763.5 (95% UI, 159.8–1385.0) thousand DALYs were among females. The age-standardized rate of COPD mortality and DALYs among males (10.3 [95% UI, 2.1–18.7] and 140.5 [95% UI, 28.2–255.3] per 100,000, respectively) was approximately twice that among females (5.2 [95% UI, 1.1–9.4] and 72.5 [95% UI, 15.2–131.4] per 100,000, respectively). However, the percentage of deaths and DALYs was generally comparable between the sexes. There were no O3-related COPD deaths or DALYs among individuals aged <25 years, whereas the corresponding burden increased gradually with age and peaked in the oldest age group (≥80 years). A similar trend was observed for death and DALYs rates, although the attributable percentages were generally comparable across different age groups.
The disease burden attributable to O3 pollution varies substantially across the provinces in China [Table 3 and Figure 1]. Generally, Health Areas 3–5, where residents experienced relatively worse health conditions, faced a more pronounced COPD burden due to O3 pollution than other regions in China. Geographically, this burden is particularly high in the northern (especially North China Plain) and western regions of China. Specifically, the age-standardized deaths and DALYs rates of COPD attributable to O3 were the highest in Xizang (22.8 [95% UI, 3.9–43.5] and 396.6 [95% UI, 68.9–763.7] per 100,000, respectively), followed by Qinghai (19.2 [95% UI, 3.5–37.5] and 287.3 [95% UI, 52.2–559.6] per 100,000, respectively), while the lowest rates were reported in Hong Kong (0.5 [95% UI, 0–1.4] and 8.1 [95% UI, 0.7–20.9] per 100,000, respectively) and Macao (1.7 [95% UI, 0–4.7] and 26.0 [95% UI, 0–71.6] per 100,000, respectively).
Table 3.
Age-standardized death and DALYs rates of COPD attributable to ambient ozone air pollution in China during 1990–2021, by province (data from the Taiwan Province of China were not included).
| Parameters | Age-standardized death rate per 100,000 (95% UI) | Age-standardized DALY rate per 100,000 (95% UI) | ||||
|---|---|---|---|---|---|---|
| 1990 | 2021 | Percent change (%) | 1990 | 2021 | Percent change (%) | |
| China | 22.6 (4.8, 39.8) | 7.2 (1.5, 13.0) | –68.2 (–74.9, –60.1) | 353.9 (75.5, 625.8) | 100.7 (21.1, 182.8) | –71.5 (–77.6, –63.7) |
| Health Area 1 | ||||||
| Beijing | 16.2 (2.8, 30.0) | 7.8 (1.5, 13.5) | –52.1 (–65.2, –25.3) | 233.3 (40.3, 440.1) | 100.1 (19.5, 175.1) | –57.1 (–69.2, –31.0) |
| Hong Kong | 0.1 (0, 0.7) | 0.5 (0, 1.4) | – | 1.6 (0, 11.0) | 8.1 (0.7, 20.9) | – |
| Macao | 1.1 (0, 6.8) | 1.7 (0, 4.7) | – | 19.2 (0, 117.8) | 26.0 (0, 71.6) | – |
| Shanghai | 14.8 (2.4, 28.8) | 8.2 (1.5, 14.7) | –44.8 (–66.5, –5.9) | 211.5 (33.8, 416.6) | 103.6 (18.8, 187.5) | –51.0 (–71.0, –14.7) |
| Tianjin | 23.9 (4.3, 43.2) | 6.2 (1.2, 11.4) | –74.0 (–82.0, –61.9) | 340.7 (63.0, 617.3) | 82.8 (15.2, 155.7) | –75.7 (–83.3, –64.2) |
| Zhejiang | 18.7 (3.1, 37.3) | 9.8 (1.7, 18.2) | –47.5 (–63.7, –22.1) | 270.9 (44.5, 539.2) | 124.5 (21.6, 231.9) | –54.0 (–68.1, –29.3) |
| Health Area 2 | ||||||
| Fujian | 9.4 (1.5, 18.7) | 2.1 (0.3, 4.4) | –77.6 (–84.2, –69.4) | 147.1 (23.2, 291.3) | 28.9 (4.5, 60.9) | –80.3 (–86.3, –72.1) |
| Guangdong | 12.2 (2.1, 24.6) | 3.9 (0.7, 7.8) | –68.0 (–75.8, –58.1) | 188.1 (32.9, 382.7) | 52.7 (9.0, 107.3) | –72.0 (–79.1, –62.2) |
| Hainan | 8.6 (1.5, 18.2) | 2.2 (0.3, 5.5) | –74.0 (–86.7, –58.8) | 136.8 (23.3, 290.1) | 32.5 (4.6, 77.5) | –76.2 (–88.0, –61.4) |
| Hubei | 19.9 (3.4, 37.9) | 7.2 (1.3, 13.9) | –63.6 (–72.2, –50.6) | 304.2 (52.2, 568.9) | 99.4 (18.0, 190.3) | –67.3 (–75.4, –55.7) |
| Hunan | 17.3 (2.9, 34.9) | 5.2 (1.0, 10.6) | –69.8 (–77.1, –58.5) | 267.4 (44.2, 537.0) | 74.0 (13.5, 151.9) | –72.3 (–79.7, –61.6) |
| Jiangsu | 29.7 (5.4, 53.6) | 9.3 (1.6, 17.1) | –68.7 (–76.4, –58.3) | 418.8 (76.0, 760.8) | 117.8 (21.4, 218.4) | –71.9 (–78.8, –62.1) |
| Health Area 3 | ||||||
| Anhui | 28.0 (5.3, 49.6) | 4.6 (0.8, 8.6) | –83.7 (–88.1, –77.4) | 429.6 (79.2, 765.4) | 62.6 (11.6, 118.8) | –85.4 (–89.5, –79.5) |
| Hebei | 21.7 (4.5, 39.5) | 11.9 (2.3, 21.7) | –45.3 (–59.7, –26.0) | 331.3 (70.0, 606.0) | 169.6 (31.9, 312.1) | –48.8 (–63.1, –29.0) |
| Heilongjiang | 15.9 (2.9, 31.5) | 2.5 (0.4, 5.4) | –84.0 (–89.2, –76.4) | 248.6 (45.4, 491.5) | 37.2 (6.3, 76.7) | –85.0 (–89.9, –77.9) |
| Henan | 23.4 (4.5, 40.3) | 7.2 (1.4, 13.0) | –69.2 (–78.1, –58.6) | 359.1 (70.7, 631.6) | 103.6 (19.6, 187.1) | –71.2 (–79.7, –60.6) |
| Inner Mongolia | 26.4 (5.4, 48.3) | 8.7 (1.7, 15.7) | –67.0 (–74.5, –57.2) | 398.6 (82.0, 730.9) | 120.0 (22.7, 218.4) | –69.9 (–77.2, –60.1) |
| Jilin | 10.1 (1.6, 19.5) | 4.5 (0.7, 8.4) | –55.8 (–68.3, –34.6) | 152.2 (24.2, 295.7) | 62.9 (10.4, 118.2) | –58.7 (–70.6, –38.4) |
| Liaoning | 8.0 (1.3, 15.1) | 6.2 (1.2, 11.5) | –23.1 (–46.5, 15.4) | 117.4 (19.6, 222.8) | 85.1 (16.6, 158.8) | –27.5 (–50.0, 9.8) |
| Ningxia | 34.7 (6.1, 62.3) | 9.1 (1.7, 17.0) | –73.9 (–81.7, –64.3) | 525.8 (93.6, 952.4) | 124.5 (23.7, 236.9) | –76.3 (–83.7, –67.0) |
| Shaanxi | 27.9 (4.9, 51.8) | 6.5 (1.1, 11.8) | –76.7 (–83.3, –66.3) | 435.1 (76.1, 807.2) | 91.4 (15.5, 168.1) | –79.0 (–85.4, –69.0) |
| Shandong | 30.0 (5.9, 54.3) | 9.2 (1.8, 16.3) | –69.5 (–77.3, –57.5) | 453.7 (90.8, 816.0) | 128.9 (25.3, 226.8) | –71.6 (–79.4, –59.6) |
| Shanxi | 28.5 (5.6, 51.0) | 6.8 (1.2, 12.5) | –76.1 (–83.0, –67.9) | 434.4 (85.2, 783.1) | 94.7 (16.9, 172.8) | –78.2 (–84.8, –70.1) |
| Health Area 4 | ||||||
| Chongqing | 37.0 (7.0, 70.0) | 6.6 (1.2, 13.5) | –82.2 (–87.5, –76.3) | 606.9 (114.7, 1153.1) | 94.4 (16.5, 193.7) | –84.4 (–89.3, –78.7) |
| Gansu | 51.6 (9.1, 91.3) | 11.9 (2.1, 21.5) | –77.0 (–82.6, –70.3) | 825.2 (146.5, 1448.4) | 175.8 (32.1, 320.4) | –78.7 (–84.2, –71.8) |
| Jiangxi | 16.8 (2.9, 34.6) | 5.2 (1.0, 10.8) | –68.8 (–75.5, –59.6) | 268.7 (46.7, 555.5) | 72.2 (14.3, 148.0) | –73.1 (–79.5, –64.5) |
| Sichuan | 36.5 (6.1, 66.3) | 10.1 (1.6, 19.3) | –72.4 (–79.5, –63.8) | 619.6 (103.9, 1131.5) | 148.9 (24.2, 287.4) | –76.0 (–82.5, –67.0) |
| Yunnan | 19.5 (3.4, 38.3) | 9.9 (1.7, 20.2) | –49.6 (–61.1, –34.7) | 315.0 (54.5, 625.8) | 143.7 (25.1, 296.6) | –54.4 (–66.1, –39.2) |
| Health Area 5 | ||||||
| Guangxi | 8.8 (1.7, 17.8) | 2.1 (0.3, 4.8) | –75.8 (–84.4, –65.9) | 140.0 (26.4, 284.7) | 30.3 (4.5, 68.1) | –78.4 (–86.4, –68.9) |
| Guizhou | 16.7 (2.7, 33.3) | 4.4 (0.7, 10.2) | –73.5 (–83.1, –62.4) | 269.2 (42.9, 543.0) | 63.7 (9.8, 144.7) | –76.3 (–85.3, –65.3) |
| Qinghai | 68.2 (13.1, 123.4) | 19.2 (3.5, 37.5) | –71.8 (–79.1, –62.9) | 1113.9 (214.3, 2023.0) | 287.3 (52.2, 559.6) | –74.2 (–81.5, –64.9) |
| Xizang | 70.5 (12.8, 127.9) | 22.8 (3.9, 43.5) | –67.6 (–77.2, –56.6) | 1293.1 (231.4, 2364.1) | 396.6 (68.9, 763.7) | –69.3 (–79.0, –58.4) |
| Xinjiang | 42.8 (8.4, 76.7) | 16.3 (3.1, 30.8) | –61.9 (–71.7, –49.1) | 701.6 (134.6, 1254.5) | 248.3 (46.1, 465.2) | –64.6 (–74.2, –51.9) |
COPD: Chronic obstructive pulmonary disease; DALYs: Disability-adjusted life-years; UI: Uncertainty interval; –: Not available.
Figure 1.
Number, age-standardized rate, and percentage of deaths and DALYs from COPD attributable to ambient ozone pollution in provinces of China in 2021 (data from the Taiwan Province of China were not included). (A) Deaths attributable to ambient ozone pollution; (B) Age-standardized death rates attributable to ambient ozone pollution; (C) Percentage of deaths attributable to ambient ozone pollution; (D) DALYs attributable to ambient ozone pollution; (E) Age-standardized DALY rates attributable to ambient ozone pollution; (F) Percentage of DALYs attributable to ambient ozone pollution. COPD: Chronic obstructive pulmonary disease; DALY: Disability-adjusted life-year.
Figure 2 illustrates the annual number, age-standardized rate, percentage of deaths, and DALYs of COPD attributable to ambient O3 pollution in China between 1990 and 2021. There was a gradual increase in the number and percentage of COPD deaths and DALYs attributed to O3 pollution during the first two decades, followed by a fast decline since approximately 2010. Subsequently, a minor peak was observed in 2017, before the burden began to decrease. The age-standardized rates of death and DALY remained relatively stable during the first two decades and then began to decline rapidly. There was also a minor peak in 2017, before the rate resumed declining. Specifically, the number of COPD deaths increased by 4.2% (95% UI, –19.0% to 32.2%) from 1990 to 2021, which was prominently driven by the increase among males (percent change: 16.7% [95% UI, –17.2% to 52.0%]) and the elderly people (≥80 years) (percent change: 89.2% [95% UI, 52.3–134.9%]). In contrast, the number of DALYs and age-standardized rates of deaths and DALYs decreased by 18.6% (95% UI, −5.2% to 37.0%), 68.2% (95% UI, 60.1–74.9%), and 71.5% (95% UI, 63.7–77.6%) over the period, respectively. From 2010 to 2021, the age-standardized rates of deaths and DALYs decreased by 57.0% (95% UI, 49.5–64.9%) and 57.8% (95% UI, 49.8–66.1%), respectively [Supplementary Tables 1 and 2, http://links.lww.com/CM9/C263]. Substantial reductions were observed in both sexes and across all age groups, particularly in younger individuals.
Figure 2.
Number, age-standardized rate, and percentage of deaths and DALYs (estimates and 95% uncertainty intervals) from COPD attributable to ambient ozone pollution in China during 1990–2021. (A) Deaths attributable to ambient ozone pollution; (B) Age-standardized death rates attributable to ambient ozone pollution; (C) Percentage of deaths attributable to ambient ozone pollution; (D) DALYs attributable to ambient ozone pollution; (E) Age-standardized DALY rates attributable to ambient ozone pollution; (F) Percentage of DALYs attributable to ambient ozone pollution. COPD: Chronic obstructive pulmonary disease; DALYs: Disability-adjusted life-years.
The age-standardized rates of COPD deaths and DALYs attributable to ambient O3 pollution consistently decreased in all provinces from 1990 to 2021 [Table 3]. However, the magnitude of this reduction varied among the provinces. Generally, the reduction in COPD burden attributable to O3 pollution was more pronounced in provinces of Health Areas 3–5 than in other areas. Specifically, Heilongjiang and Anhui experienced the highest decline (84.0% [95% UI, 76.4–89.2%] and 83.7% [95% UI, 77.4–88.1%] for age-standardized death rates, and 85.0% [95% UI, 77.9–89.9%] and 85.4% [95% UI, 79.5–89.5%] for age-standardized DALY rates). Liaoning had the lowest decrease of 23.1% (95% UI, −15.4% to 46.5%) in the age-standardized death rate and 27.5% (95% UI, −9.8% to 50.0%) in the age-standardized DALY rate, followed by Shanghai and Hebei. Similarly, the decline in the COPD burden from 2010 to 2021 was more notable in Health Areas 3–5. Reductions in the age-standardized rates of COPD deaths and DALYs ranged from 0.9% (95% UI, −25.8% to 23.2%) and 1.1% (95% UI, −26.8% to 24.5%) in Beijing to 82.8% (95% UI, 74.0–91.1%) and 83.0% (95% UI, 73.7–91.2%) in Guizhou [Supplementary Table 3, http://links.lww.com/CM9/C263].
Discussion
In this study, based on data from the GBD 2021, we assessed the spatiotemporal trends of COPD deaths and DALYs attributable to ambient O3 pollution at both the national and provincial levels in China. Nationally, ambient O3 pollution was responsible for approximately 126 thousand deaths and 2 million DALYs from COPD in 2021, with a relatively higher burden observed among males and the elderly population. Significant variations were found across provinces, with a more pronounced burden in regions where residents experienced worse health conditions. Over the past three decades, substantial reductions in the age-standardized rates of O3-related COPD deaths and DALYs have been observed, although the absolute numbers and attributable fractions have changed relatively marginally.
Accumulating epidemiological studies have observed adverse respiratory effects of long-term O3 exposure; however, few have evaluated the corresponding disease burden. For example, the US Environmental Protection Agency concluded that long-term exposure to O3 is likely to have a causal relationship with respiratory health in 2020.[32] A cohort of approximately 450 thousand participants from 96 metropolitan statistical areas of the US during 1977–2000 reported that O3 contributed independently to increased deaths from respiratory causes.[33] Another prospective cohort of middle-aged and elderly people from six states in US and two metropolitan areas from 1995 to 2011 demonstrated significantly increased COPD mortality with long-term O3 exposure.[14] Two cohort studies (one in Suzhou, China and the other in low- and middle-income regions in western China) further illustrated positive associations between ambient O3 exposure and COPD morbidity.[11,34] Although a few studies have estimated the COPD burden related to long-term O3 exposure in China, most have been limited to single cities.[16,21] Only two studies have assessed the corresponding burden at the national level;[22,23] however, both were based on data before 2017 and neither provided an annual estimation. Using the standardized analytical methodology of the GBD, the present study provides comprehensive and latest evidence on the disease burden caused by ambient O3 pollution in different provinces in China, filling the gap in prior research and offering valuable insights for policy formulation and environmental protection.
There was notable heterogeneity in the O3-related burden across the different sex and age categories. In agreement with previous findings,[35,36] males bear a heavier COPD burden due to O3 pollution. One possible reason might be that there were slightly more deaths and DALYs due to COPD among males.[20] Besides, smoking is much more prevalent among males than females, which is also a major risk factor for COPD. Mechanistically, cigarette smoking can shift the longitudinal distribution of O3 uptake toward a distal distribution, thus exacerbating health effects in the population.[37,38] Another contributing factor is that males are more frequently engaged in outdoor occupations, leading to increased exposure to O3 pollution.[39] Furthermore, the burden of COPD attributable to O3 tends to gradually increase as the population ages. Previous evidence has also illustrated the greater effects of O3 among elderly people.[7,35,40] As individuals age, their respiratory system undergoes degenerative changes, including reduced lung function and capacity to resist toxic substances and repair damaged tissue.[41] The higher prevalence of comorbidities among the elderly might further exacerbate their vulnerability to O3-related respiratory diseases.[18,42] This demographic susceptibility highlights the need for targeted interventions and public health initiatives to protect vulnerable groups from the respiratory disease burden associated with ambient O3 pollution.
The COPD burden shows substantial heterogeneity in China at the provincial level. In general, regions where residents experienced relatively worse health conditions (i.e., Health Areas 3–5) faced a higher burden of COPD. This disparity is largely attributable to significant differences in socioeconomic development, healthcare infrastructure, and risk factor control among the different areas. Low socio-economic development typically leads to limited public health awareness, insufficient social support, and inadequate medical care.[31] All these factors could interact with each other and contribute directly or indirectly to exacerbating susceptibility to COPD and O3-related health effects.[19,43] Furthermore, the temporal changes in the COPD burden attributable to O3 pollution showed a similar pattern among different provinces, although the magnitude of these changes differed. The largest decline was observed in Health Areas 3–5, which generally experienced a higher disease burden, suggesting more significant improvements in health conditions and reduced disparities across regions. In the future, governments should continue to pay more attention to vulnerable areas and implement province-specific measures to control O3 pollution and reduce the related disease burden.
Over the past three decades, there has been a notable temporal trend in O3-related COPD burden. Despite the remarkable decrease in age-standardized rate of COPD deaths and DALYs attributable to O3, the attributable death rate in China during 2021 still exceeded the global average level. In addition, there is little change in the number and percentage of COPD deaths and DALYs between 1990 and 2021. In 2021, the absolute number of deaths and DALYs of COPD attributed to O3 pollution accounts for approximately a quarter of the estimate globally, and one-tenth of the total COPD deaths and DALYs across the country. One of the contributors to this issue might be the aging population in China,[19,44] which results in a higher absolute number of COPD-related deaths among the elderly, even as mortality rates decrease. The persistently increasing concentrations of O3 in China are another significant contributor.[8,9] Despite the considerable reduction in fine particulate matter levels in China owing to the implementation of air pollution control policies since 2013,[45–47] temporal variations in O3 pollution showed an increasing trend during the same period and became a major environmental concern in many metropolitan areas.[9] Our findings underscore the critical challenge of O3-related COPD burden in China and emphasize the importance of addressing O3 pollution and promoting healthy aging to effectively mitigate the burden of respiratory diseases attributable to O3 pollution.
Despite the comprehensive epidemiological data extracted from the GBD Study 2021 and advanced statistical modeling techniques, the present study has some limitations. First, ground monitoring of O3 was not widely applied in China until 2013; consequently, there may have been inherent bias when correcting O3 estimates based on monitoring data from earlier years. Second, we calculated the disease burden at the provincial level, which may fail to account for local heterogeneity within one province. Third, the concentration–response relationships utilized in this study primarily stemmed from large-scale cohorts in Western countries.[4] This may introduce bias into the estimates because of the disparities in population characteristics and pollution patterns between China and Western nations. Fourth, the evaluation only considered diseases (i.e., COPD) that have been shown to have a causal relationship with O3. However, as O3 research progresses, additional diseases may become associated with O3 exposure. Therefore, the burden related to O3 could have been underestimated. Finally, only ambient O3 pollution was considered when estimating the disease burden. However, individuals typically spend most of their daily time indoors. Thus, future research should focus on actual exposure levels to O3 and provide a more comprehensive evaluation of the corresponding disease burden.
In summary, ambient O3 pollution has imposed a substantial burden of COPD in China over the past three decades. Despite the remarkable decrease in attributable death and DALY rates, the attributable numbers and percentages remain a major concern. Vulnerable populations, including males, the elderly, and individuals residing in regions with worse health conditions, are disproportionately affected. Our results underscore the importance of continued and more stringent efforts to reduce air pollutants, especially O3, to protect the public from health hazards. Additionally, the development of geographically tailored strategies is essential for mitigating the disease burden across different provinces.
Funding
This work was supported by grants from the National Natural Science Foundation of China (No.82030103), and the National Key Research and Development Program of China (No.2022YFC3702701).
Conflicts of interest
None.
Footnotes
Yixuan Jiang and Fanshu Yan contributed equally to this work.
How to cite this article: Jiang YX, Yan FS, Kan HD, Zhou MG, Yin P, Chen RJ. Burden of chronic obstructive pulmonary disease attributable to ambient ozone pollution across China and its provinces, 1990–2021: An analysis for the Global Burden of Disease Study 2021. Chin Med J 2024;137:3126–3135. doi: 10.1097/CM9.0000000000003415
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