Disease burden of COPD attributable to PM2.5 in China, Japan and South Korea from 1990 to 2019: a comparative study based on Global Burden of Disease Study 2019

Abstract

Objective

We hope to reveal the changing trends of chronic obstructive pulmonary disease (COPD) burden attributable to particulate matter pollution (PM_2.5) and its age, period and cohort effects in China, Japan and Korea.

Design

We analysed the trend of COPD disease burden attributable to PM_2.5 from 1990 to 2019 based on the latest Global Burden of Disease Database (GBD 2019) using JoinPoint model and analysed the effect of age, period and cohort on COPD burden attributable to PM_2.5 in China, Japan and Korea from 1990 to 2019 using age-period-cohort model (model).

Setting

GBD data from 1990 to 2019.

Participants

Data were publicly available and individuals were not involved.

Main outcomes

Outcomes included the age standardised mortality rate (ASMR), the age-standardised disability-adjusted life year (DALY), average annual per cent change (AAPC), net drift, local drift, longitudinal age curves, period (cohort) rate ratios, age (period, cohort) bias coefficient.

Results

From 1990 to 2019, the ASMR of COPD attributable to PM_2.5 in China (AAPC=−5.862), Japan (AAPC=−1.715) and Korea (AAPC=−1.831) showed a downward trend. The age-standardised DALY of COPD attributable to PM_2.5 in China (AAPC=−5.821), Japan (AAPC=−1.39) and Korea (AAPC=−1.239) showed a downward trend. Mortality of COPD attributable to PM_2.5 increased slowly with age in Korea and Japan. Mortality of COPD attributable to PM_2.5 in China decreased after rising (95% CI: 404.66 to 466.01). Mortality of COPD attributable to PM_2.5 decreased over time in China and Korea, while it increased in Japan from 2015 to 2019. In China and Japan, mortality of COPD attributable to PM_2.5 was approximately lower the later the birth, while in Korea it decreased after an increase (95% CI: 2.13 to 2.40) in the 1900–1910.

Conclusions

Most COPD burden attributable to PM_2.5 is on the decline; COPD mortality attributable to PM_2.5 both increased with age and decreased with time and cohort. Countries with high burden should develop targeted measures to control PM_2.5.

Correspondence to Bei Li; [email protected] ; Professor Yi-Li Zhang; [email protected]

Strengths and limitations of this study

• This study comprehensively described and compared the mortality rate and disability-adjusted life year of chronic obstructive pulmonary disease (COPD) attributed to particulate matter pollution in China, Japan and South Korea.

• This study evaluated the long-term trend changes of COPD attributed to particulate matter pollution in the three countries.

• This study analysed the age effect, period effect and cohort effect of COPD attributed to particulate matter pollution in the three countries.

• One of limitations was Global Burden of Disease Database (GBD 2019) collected missing data by modifying and adjusting data sources and collection assessment methods, which could not eliminate data bias and affected the accuracy of the results.

• Another limitation was this study used GBD 2019 data, and the particulate matter_2.5 exposure classification was limited by the data, which only included ambient particulate matter and household air pollution.

• The third limitation was the age-period-cohort model only considered the effects of age, period and cohort without further analysis of other risk factors.

Background

Air pollution is the largest environmental cause of increased non-accidental mortality and morbidity, and a significant global health threat.^{1 2} In fact, according to the State of Global Air 2020, a staggering 6.67 million people worldwide are predicted to die from air pollution in 2019, underscoring the gravity of this global health threat.³ Air pollution is usually quantified according to particulate pollution and ozone,⁴ where particulate pollution is a crucial factor in air pollution, as clinical studies have demonstrated that particulate pollution has a greater impact on health than gaseous components.⁵ Particulate matter (PM_2.5) is defined as particles with a diameter of 2.5 microns or smaller, and it can be divided into ambient particulate matter pollution (APM) and household air pollution from solid fuels (HAP). In 2019, the disease burden due to APM is the seventh highest for all ages, with average concentrations exceeding the WHO air quality guidelines of 10 µg/m³ and affecting over 90% of the world’s population.³ The situation is further compounded by increasingly alarming exposure to APM in a majority of developing countries in recent years.⁶ HAP mainly refers to PM_2.5 exposure from home heating or cooking through polluting fuels such as wood, coal, kerosene. Despite the downward trend in overall HAP exposure, nearly 3 billion people worldwide still rely on polluting fuels for daily household living in 2019,⁷ and 32% of Chinese still use solid fuels for cooking or heating.⁸ Cohort studies conducted worldwide consistently highlight a clear correlation between exposure to PM_2.5 and mortality and disease incidence,^9–11 while particulate pollution conclusively causes acute lower respiratory disease, cerebrovascular disease, ischaemic heart disease, chronic obstructive pulmonary disease (COPD) and lung cancer.¹²

Over the past few decades, epidemiological studies and meta-analyses have established that both short-term and long-term exposure to PM pollution are associated with COPD.^13–15 Particulate pollution is a top three risk factor for COPD-related death and disability.¹⁶ Respirable PM in the environment leads to an increase in reactive oxygen species (ROS). Excess ROS affects mitochondria, resulting in severe mitochondrial dysfunction. This, in turn, activates processes such as autophagy, mitophagy and apoptosis,¹⁷ which can induce airway inflammation, airway wall remodelling, emphysematous lesions, lung function impairment and mucus hypersecretion.^18–20 In addition, it is not just a matter of public health, as COPD also carries an economic cost.²¹ The direct medical costs of COPD alone in the USA are projected to skyrocket to an alarming US$800.9 billion over the next two decades.²² Overall, COPD is a formidable health problem that warrants increased attention and concerted effort in both developed and developing countries.

It is worth noting that East Asia, for instance, has the highest number of COPD cases, deaths and disability-adjusted life years (DALYs) on the global stage.²³ In East Asia, China, Japan and South Korea belong to its three largest economies, with economies exceeding one-fifth of the world’s total. These three countries have similar cultural backgrounds but are at different stages of socioeconomic development, with Japan and South Korea ahead of China in terms of urbanisation and industrialisation. In 2019, China ranked first in air pollution-related deaths and second in air pollution-related DALYs,²⁴ which shows that air pollution in China leads to a very serious disease burden, and similarly, South Korea faces a more serious air pollution problems, while Japan has a relatively better pollution situation.²⁵ Analysing and comparing the disease burden of COPD due to PM in the three countries will help in tracking the effectiveness of national prevention and control programmes. It will also help in preventing the disease burden of COPD due to air pollution and developing targeted strategies for managing PM pollution and COPD prevention.

However, previous studies have mainly focused on analysing the effect of PM_2.5 on COPD and its potential mechanisms in a particular country or global,^{26 27} and few studies have analysed the disease burden of COPD due to APM and HAP in three countries, China, Japan and Korea,²⁵ while few studies have been able to further investigate the age, period and cohort effects of PM_2.5 and COPD using the age-period-cohort (APC) model.^{25 27} APC models are able to estimate the independent effects of age, period and cohort on disease,²⁸ helping us to understand COPD caused by PM_2.5 from a historical perspective, such as disease screening modalities, treatments or interventions and lifestyle changes.^{29 30} Therefore, this study subdivided PM_2.5 into HAP and APM, aiming to analyse the changes in COPD disease burden attributable to PM_2.5 and its age, period and cohort effects in China, Japan and Korea from 1990 to 2019 and to provide feasible and targeted policy recommendations for countries and regions with high disease burden.

Methods

Data sources

The study is based on Global Burden of Disease Database (GBD 2019) from the Institute for Health Metrics and Evaluation in Washington, USA. GBD 2019 provides population estimates for 204 countries and territories from 1950 to 2019, and also provides data on the incidence, number of deaths and DALYs for 369 diseases and injuries for 204 countries and territories from 1990 to 2019.³¹ The GBD updates and adds new data and methodological enhancements to the estimation of the entire time series after each change to adjust for bias.³² This study uses GBD 2019 data to report the burden of COPD disease attributable to PM pollution in China, Japan, Korea and global from 1990 to 2019. A detailed description of the GBD 2019 methodology used to analyse the burden of disease was previously published³³ and GBD 2019 can be accessed at https://vizhub.healthdata.org/gbd-results/.

COPD definition

COPD data for this study were obtained from GBD 2019. The COPD data reported in GBD 2019 used the Global Initiative for Chronic Obstructive Lung Disease (GOLD) standard definition: when the ratio of maximum forced expiratory air volume to total forced expiratory volume in the first second of expiration after bronchodilation has a value <0.7.²³ Alternative definitions for evaluating whether a person has COPD include the pre-bronchodilator GOLD criteria, the post-bronchodilator lower limit of normal, the pre-bronchodilator lower limit of normal and the European Respiratory Society guidelines.³⁴

Particulate matter pollution assessment

We used HAP and APM data from GBD 2019 as an indicator of PM pollution. GBD defines PM_2.5 as fine particles with an aerodynamic diameter of 2.5 µm or less in 1 m³ of air when exposed to it. In this case, APM is measured by the annual average PM_2.5 concentration in the air, which is estimated at a spatial resolution of 0.1°×0.1° grid from satellite observations, chemical transport models and ground monitoring data.³⁵ HAP was defined as the daily average PM_2.5 exposure due to the use of household solid fuels, which was obtained from measurements of PM_2.5 concentrations in kitchens and living areas.³⁵

Statistical analysis

JoinPoint regression analysis

This study describes the level of COPD disease burden due to PM_2.5 from 1990 to 2019 by age-standardised mortality and DALY. We applied log-linear models of JoinPoint regression models to fit age standardised mortality rate (ASMR) and age-standardised DALY data on COPD attributable to PM_2.5. The average annual per cent change (AAPC) was calculated by a log-linear model to observe the trend of death and DALY in COPD attributable to PM_2.5 in China, Japan, Korea and global.

Age-period-cohort analysis

This study further explored the age effect, period effect and cohort effect of the changing pattern of COPD mortality attributable to PM_2.5 by using the APC model. The APC model is based on the Poisson distribution and can address the problem that there is a linear relationship between age, period and cohort to estimate the effect that age, period and cohort have on disease.³⁶ In this paper, the following indicators are estimated by the APC model: net drift, an overall log-linear trend indicating the overall annual percentage change in disease using period and birth cohort adjustments; local drift, a log-linear trend in the period and birth cohort for each age group, representing the annual percentage change for each age group; longitudinal age curves, reflecting period deviation-adjusted longitudinal age-specific values, used to infer the effect of age effects on trends in COPD; period (cohort) rate ratios, which allow inference of the influence of period or cohort effects on trends in COPD; age (period, cohort) bias coefficient, reflecting the curvature within a certain age (period, cohort).

The APC model in this paper uses the APC model Web Analysis Tool provided by the International Agency for Cancer (https://analysistools.cancer.gov/apc/). Based on the GBD 2019 data and the characteristics of the APC model webpage analysis tool, this study selected COPD mortality data at 5-year intervals as an age group. Since the mortality data for COPD under 25 years of age was 0, data under 25 years of age were excluded from this study and a total of 15 age groups were ultimately included. In terms of period division, this paper divides 1990–2019 into six periods according to 5 years as a time period. The formula of birth cohort is: birth cohort=period age, and this paper calculates the value of birth cohort according to the data characteristics.

Excel 2019 software was used to organise data; JoinPoint Regression Program V.4.9.0.0 software was applied to analyse the trend of COPD attributed to PM_2.5; APC model Web Analysis Tool was used to fit the APC model and use the web page itself with Wald χ² test for parameter estimation; Origin 2021 software was used for plotting. The test level for all statistical models in this paper was α=0.05 (two-sided).

Patient and public involvement

None.

Results

Descriptive analysis of COPD attributable to PM_2.5 in China, Japan, Korea and global

The ASMRs in China, Japan, Korea and global all showed a decreasing trend, with the highest and largest decrease in China (figure 1A). From 1990 to 2019, the age-standardised DALYs for COPD attributable to PM_2.5 and attributable to APM in China showed a decreasing trend but remained at the highest level compared with Japan, Korea and global, while the DALY for age-standardised COPD attributable to HAP in China dropped below the global level in 2015. In addition, COPD caused by APM was higher than COPD caused by HAP in Japan and Korea, while COPD caused by HAP was higher than COPD caused by APM in China and global (figure 1B).

Figure 1. (A) ASMR of COPD attributable to PM 2.5 (a), HAP (b) and APM (c) in China, Japan, Korea and global, 1990-2019; (B) age-standardised DALY of COPD attributable to PM 2.5 (a), HAP (b) and APM (c) in China, Japan, Korea and global, 1990-2019. APM, ambient PM; ASMR, age standardised mortality rate; COPD, chronic obstructive pulmonary disease; DALY, disability-adjusted life year; HAP, household air pollution; PM, particulate matter.

Temporal trends in COPD disease burden attributable to particulate matter pollution in China, Japan, Korea and global

The ASMR and age standardised DALY AAPC of COPD attributable to PM pollution in China, Japan, South Korea and global from 1990 to 2019 are shown in tables 1 and 2. The JoinPoint model results showed that except for the global trend of increasing ASMR in COPD attributed to APM by gender (AAPC=0.473, p<0.05), all other ASMR showed a decreasing trend (p<0.05). Except for the age standardised DALY of COPD attributed to APM among global women, which is statistically insignificant, all others are significant and show a downward trend under the 0.05 test standard (p<0.05).

Table 1

Trends in age standardised mortality rate of chronic obstructive pulmonary disease attributable to PM_2.5, 1990–2019

Risk	Sex	China		Japan		Korea		Global
		AAPC	95% CI	AAPC	95% CI	AAPC	95% CI	AAPC	95% CI
PM2.5	Both	−5.862*	(−6.058 to 5.666)	−1.715*	(−1.978 to 1.452)	−1.831*	(−2.118 to 1.543)	−3.263*	(−3.448 to 3.079)
	Male	−5.199*	(−5.503 to 4.894)	−1.733*	(−1.916 to 1.549)	−1.629*	(−2.248 to 1.007)	−3.218*	(−3.446 to 2.990)
	Female	−6.442*	(−6.734 to 6.150)	−2.008*	(−2.210 to 1.805)	−2.447*	(−2.663 to 2.230)	−3.397*	(−3.524 to 3.269)
HAP	Both	−9.518*	(−9.678 to 9.358)	−8.432*	(−8.750 to 8.113)	−13.912*	(−14.287 to 13.537)	−5.551*	(−5.715 to 5.387)
	Male	−9.296*	(−9.556 to 9.035)	−8.379*	(−8.635 to 8.123)	−13.557*	(−13.844 to 13.268)	−5.727*	(−5.919 to 5.535)
	Female	−9.706*	(−9.880 to 9.532)	−8.584*	(−8.880 to 8.286)	−14.283*	(−14.635 to 13.930)	−5.395*	(−5.555 to 5.235)
APM	Both	−2.563*	(−3.061 to 2.063)	−1.669*	(−1.932 to 1.404)	−1.735*	(−2.030 to 1.438)	0.473*	(−0.620 to 0.326)
	Male	−2.196*	(−2.477 to 1.914)	−1.696*	(−1.887 to 1.505)	−1.555*	(−2.186 to 0.921)	−0.607*	(−0.766 to 0.449)
	Female	−2.903*	(−3.340 to 2.465)	−1.945*	(−2.149 to 1.741)	−2.332*	(−2.560 to 2.105)	−0.404*	(−0.601 to 0.208)

*Statistically significant (p<0.05).

AAPC, average annual per cent change; APM, ambient PM; HAP, household air pollution; PM, particulate matter.

Table 2

Trends in age-standardised disability-adjusted life year of chronic obstructive pulmonary disease attributable to PM_2.5, 1990–2019

Risk	Sex	China		Japan		Korea		Global
		AAPC	95% CI	AAPC	95% CI	AAPC	95% CI	AAPC	95% CI
PM2.5	Both	−5.821*	(−6.051 to 5.590)	−1.390*	(−1.490 to 1.290)	−1.239*	(−1.595 to 0.882)	−3.118*	(−3.267 to 2.968)
	Male	−5.427*	(−5.695 to 5.157）	−1.485*	(−1.594 to 1.376)	−1.200*	(−1.691 to 0.707)	−3.170*	(−3.315 to 3.024)
	Female	−6.120*	(−6.284 to 5.956)	−1.457*	(−1.554 to 1.360)	−1.734*	(−1.976 to 1.491)	−3.110*	(−3.244 to 2.976)
HAP	Both	−9.434*	(−9.646 to 9.223)	−8.209*	(−8.335 to 8.082)	−13.353*	(−13.626 to 13.080)	−5.296*	(−5.413 to 5.178)
	Male	−9.372*	(−9.540 to 9.204)	−8.278*	(−8.393 to 8.163)	−13.232*	(−13.551 to 12.913)	−5.545*	(−5.685 to 5.405)
	Female	−9.467*	(−9.649 to 9.286)	−8.203*	(−8.343 to 8.062)	−13.637*	(−13.970 to 13.303)	−5.052*	(−5.185 to 4.920)
APM	Both	−2.430*	(−2.828 to 2.030)	−1.340*	(−1.438 to 1.241)	−1.146*	(−1.504 to 0.786)	−0.342*	(−0.457 to 0.227)
	Male	−2.406*	(−2.683 to 2.128)	−1.442*	(−1.550 to 1.335)	−1.126*	(−1.627 to 0.622)	−0.561*	(−0.666 to 0.456)
	Female	−2.399*	(−2.702 to 2.094)	−1.393*	(−1.491 to 1.294)	−1.618*	(−1.862 to 1.374)	−0.097*	(−0.273 to 0.079)

*Statistically significant (p<0.05).

AAPC, average annual per cent change; APM, ambient PM; HAP, household air pollution; PM, particulate matter.

Age-period-cohort analysis of COPD mortality attributable to PM_2.5 in China, Japan, Korea and worldwide, 1990–2019

Wald χ² test results and bias coefficients for the APC model

The results of the Wald χ² test of the APC model showed that COPD mortality attributable to HAP in Japan and Korea did not meet the requirements of the APC model, and their local drift values, all cohort Relative Risk (RR), all age deviations, all period deviations and all cohort deviations were statistically insignificant and the remaining age, period and cohort effects of mortality and the remaining estimated parameters were statistically significant (p<0.05), as shown in table 3. In the subsequent analysis, we will analyse and report detailed APC effects for items tested significant by the Wald χ² test.

Table 3

Age-period-cohort analysis of chronic obstructive pulmonary disease mortality attributable to PM_2.5 from 1990 to 2019

Item

Wald χ2 of age standardised mortality rate

China

Japan

Korea

Global

PM2.5

HAP

APM

PM2.5

HAP

APM

PM2.5

HAP

APM

PM2.5

HAP

APM

Net drift=0

5292.73*

8368.81*

1794.23*

73.58*

5.34*

70.00*

340.30*

9.80*

325.92*

6449.76*

10637.70*

302.04*

All local drifts=net drift

659.44*

436.37*

705.61*

52.09*

0.46

52.22*

235.32*

1.47

233.70*

469.18*

124.43*

332.17*

All period RR=1

5336.33*

8633.93*

2151.61*

580.53*

12.39*

561.94*

461.67*

13.33*

449.83*

6472.05*

10800.65*

360.72*

All cohort RR=1

34393.88*

61059.97*

8567.39*

1627.03*

201.65

1532.71*

2095.55*

142.41

1978.60*

24919.32*

41972.37*

996.88*

All age deviations=0

1294.81*

1191.16*

1598.51*

1451.12*

7.76

1439.57*

271.56*

0.84

269.42*

11409.16*

9304.07*

8512.42*

All period deviations=0

61.53*

560.05*

265.12*

530.04*

6.88

514.28*

129.88*

2.41

130.46*

33.99*

255.48*

42.32*

All cohort deviations=0

660.09*

436.80*

710.82*

55.31*

0.47

55.44*

242.18*

1.5

240.54*

479.55*

141.15*

333.89*

*Statistically significant (p<0.05).

APM, ambient PM; HAP, household air pollution; PM, particulate matter; RR, Relative Risk.

Net drift and local drift

As shown in figure 2, the net drift values of COPD mortality rates attributed to PM_2.5 in China, Japan, South Korea and global from 1990 to 2019 were −7.40% (95% CI: −7.59% to –7.20%), −2.02% (95% CI: −2.48% to –1.56%), −3.78% (95% CI: −4.17% to –3.39%) and −3.80% (95% CI: −3.89% to –3.71%), respectively. The net drift of COPD mortality attributable to HAP was −10.93% (95% CI: –11.16% to –10.71%) and −5.86% (95% CI: −5.97% to –5.76%) in China and global, respectively. The net drift of COPD mortality attributable to APM was −3.92% (95% CI: −4.10% to –3.74%), −1.98% (95% CI: −2.43% to –1.52%), −3.71% (95% CI: −4.11% to –3.31%) and −0.95% (95% CI: −1.06% to –0.85%) in China, Japan, Korea and global, respectively. The local drift values of COPD mortality attributable to PM_2.5 and APM in Korea showed an overall increasing trend with age and all showed positive values at the age group of 95 years or older. Global local drift values for COPD mortality attributable to APM generally increased with age and started to show positive values at the age group 90–95 years. In addition, the local drift values of COPD mortality rates attributed to PM_2.5, HAP and APM in the three countries and globally are generally increasing with age, but all are below zero.

Figure 2. Net and local drift values of chronic obstructive pulmonary disease mortality attributable to particulate matter 2.5 (A) household air pollution (B) and ambient particulate matter (C) in China, Japan, Korea and globally, 1990-2019.

Age effect

After correcting for period effects and birth cohort effects, COPD mortality attributable to PM_2.5 increased slowly with age in Korea and Japan. Global COPD mortality attributable to PM_2.5 peaks in the 85–90 years age group and then declines. The increase in COPD mortality attributable to PM_2.5 in China was large until the age group 90–95 years and decreased to 434.25/100 000 (95% CI: 404.66 to 466.01) after the age group 90–95 years. Global COPD mortality attributable to HAP peaked in the 80–85 years age group and then declined sharply to 32.76/100 000 (95% CI: 30.71 to 34.94). COPD mortality attributable to HAP in China peaked at 78.17 per 100 000 (95% CI: 75.54 to 80.89) in the 85–90 years age group and then declined continuously. COPD mortality attributable to APM increased with age in China, Japan, Korea and globally. See online supplemental figure 1 for details.

Period effect

Using 2000–2004 as a control group, COPD mortality attributable to PM_2.5 decreased significantly over time in China, Korea and globally, whereas it increased slightly in Japan from 2015 to 2019. COPD mortality attributable to HAP in China and globally all decreased significantly over time. COPD mortality attributable to APM in China, Korea and globally showed a decreasing trend over time, but in Japan, the mortality rate of COPD attributable to APM has shown a decreasing trend between 1990 and 2015, dropping to the minimum value of 0.85 (95% CI: 0.80 to 0.89) and rising to 0.91 (95% CI: 0.84 to 0.98) from 2015 to 2019. See online supplemental figure 2 for details.

Cohort effect

In China, Japan and globally, COPD mortality attributable to PM_2.5 was approximately lower the later the birth and gradually decreased in Korea after a small increase to a peak of 2.26 (95% CI: 2.13 to 2.40) in the 1900–1910 birth cohort. Late birth cohorts with COPD mortality attributable to HAP were lower than early birth cohorts in both China and globally. COPD mortality attributable to APM in China and Japan gradually decreased with increasing birth year. Global COPD mortality attributable to APM fluctuated slightly during the 1990–1915 birth cohort and then declined slowly. COPD mortality attributable to APM in Korea showed an increasing trend during the 1895–1910 birth cohort and decreased after peaking in 1910. Online supplemental figure 3 for details.

Discussion

This study provides an update on trends in the disease burden of COPD attributable to PM_2.5, HAP and APM in the three major Asian economies of China, Japan and Korea, as well as globally. We found a decreasing trend in ASMR and age-standardised DALY for COPD attributable to PM_2.5, HAP and APM in all regions, except for a global overall trend in ASMR for COPD attributable to APM among all genders. COPD attributable to PM pollution shows a decreasing trend in most regions and is inextricably linked to local environmental health policies. In 2013, the WHO designated PM_2.5 as a carcinogen and recommended that the population-weighted APM should be less than 10 µg/m³. In high-income countries, several strategies have been implemented to reduce air pollution. These include switching to cleaner fuels, improving emission control technologies and enhancing public environmental education.^{37 38} Since 2013, China has implemented systematic regulations that have resulted in a 33.3% decrease in annual average PM_2.5 concentrations from 2013 to 2017.³⁹ In contrast, the global all-sex ASMR for COPD attributable to APM is on the rise, which may be due to the increase in PM pollution in countries with low socioeconomic development.²⁷

The results showed large regional differences in ASMR and age-standardised DALY for COPD attributable to PM_2.5, HAP and APM. The burden of COPD disease attributable to PM pollution in China is much higher than the levels in Japan and Korea, and there is a gap with global levels. This difference may be related to socioeconomic development,²⁷ where China is a developing country with further economic construction to be advanced, while Japan and South Korea are developed countries with economic development levels ahead of the world average. Large-scale energy consumption and power generation in low-income and middle-income countries generate large amounts of pollution during the industrialisation process.³³ A Chinese study, noting that urbanisation and industrialisation have increased PM emissions in Chinese cities, found that 64.2% of 338 PM_2.5 samples exceeded National Standard I, 53.0% of 338 PM₁₀ samples exceeded National Standard II and 70.7% of urban ambient air quality exceeded National Standard III.⁴⁰ In addition, more residents in low-income and middle-income countries rely on traditional energy sources for home cooking and heating, and in China, 32% of Chinese still use solid fuels for heating and cooking, resulting in much higher levels of exposure to PM pollution than in high-income countries.^{8 41} At the same time, countries with higher levels of development may have more stringent air quality controls,⁴² and some studies have clearly indicated that Japan and South Korea have conducted air quality research in an effort to alleviate air pollution problems within their borders, leading to relatively clean air quality in Japan and South Korea compared with other Northeast Asian countries.⁴³ A study measuring the accessibility and quality of healthcare across countries by constructing a Healthcare Access and Quality (HAQ) Index found that high Socio-demographic Index (SDI) countries had higher HAQ scores, with Japan scoring 94, South Korea 90 and China 78.⁴⁴ In low-income and middle-income countries, the lack of high-quality public healthcare may exacerbate the burden of PM_2.5-attributable COPD due to economic deprivation and relatively poor health awareness among the population.⁴⁵ Therefore, differences in the level of healthcare among the three countries may also explain the differences in COPD attributable to PM_2.5 in China, Japan and South Korea.

Interestingly, we focused on the difference in COPD risk due to HAP and APM, with COPD due to APM being higher than COPD due to HAP in Japan and Korea, and conversely, COPD due to HAP being higher than COPD due to APM in China and globally. The reason for this opposite result may be that residents of economically developed areas use less solid fuels. It has been noted that biomass fuel exposure is a major risk factor for COPD in poor and developing countries.⁴⁶ In resource-limited environments, readily available solid fuels such as wood, charcoal, dried branches, crop residues and animal dung cakes are used as cooking fuels in less developed countries, covering more than 200 chemical and compound groups, 90% of which are in the respirable size range.⁴⁷ Exposure to biomass fuel smoke increased the odds of developing COPD by 2.3 times compared with no exposure to biomass smoke.⁴⁶ Thus, there is no doubt that biomass fuel exposure is an important risk factor for chronic lung disease in developing country populations and a potential causative agent of respiratory disease. In conclusion, policy actions in China and developing countries around the world to reduce the burden of COPD caused by PM_2.5 should focus on HAP emission concentrations, while economically developed countries should pay more attention to APM control.

We analysed the effect of age on COPD attributed to PM_2.5 and showed that COPD mortality attributed to APM increased with age in China, Japan, Korea and globally. COPD mortality attributable to HAP declined sharply after peaking in the 80–85 years age group globally and declining after peaking in the 85–90 years age group in China. Similar to our findings, several studies have shown that the burden of COPD caused by APM is heavier in the elderly population.^{48 49} This may be due to the weaker immune and lung function, high likelihood of chronic diseases, higher sensitivity to chemicals and greater susceptibility to air pollution in the elderly compared with the young.⁵⁰ Therefore, there is a need for all countries to take measures to address the healthcare issues arising from population ageing. In addition, the decrease in COPD mortality rates attributed to HAP in the global and China during the advanced age stage may be due to the large base of early life exposure to HAP among residents in the region, and the inconvenience of movement and sudden decrease in HAP exposure after being too old, ultimately leading to a sharp decline in COPD mortality rates attributed to HAP in the advanced age group.

COPD mortality attributable to HAP decreased significantly over time in China and globally. COPD mortality attributable to APMs in China, Korea and globally showed a decreasing trend over time, but Japan’s showed a decreasing trend from 1990 to 2015 and a small increase from 2015 to 2019. Temporal effects are usually influenced by a complex set of environmental factors and historical events.⁵¹ The Chinese government attaches great importance to the air pollution problem and has reduced PM_2.5 exposure through measures such as improving stove programmes and planning waste emission standards for factories.^{27 52} In addition, advanced drug therapy and other interventions in China have controlled the risk factors for COPD and well prevented further COPD progression.²⁷ In the last decade or so, Korea has introduced laws and regulations such as the Emission Reduction Plan and Special Measures for Air Quality to address PM pollution,⁵³ and guaranteed effective treatment for patients with COPD through the universal health insurance system, thereby reducing the severity of the disease and mortality.⁵⁴ Japan has seen a small increase in COPD mortality attributable to APM in recent years, which we speculate may be due to increased air pollution and increased patient mortality due to the growth in the number of cars.⁵⁵ Therefore, all governments need to continue to jointly adopt multiple regulations and measures to manage air pollution and clinical treatment techniques to promote primary and secondary prevention of COPD disease.

In both China and globally, COPD mortality attributable to HAP is lower in late birth cohorts compared with early birth cohorts. COPD mortality attributable to APM in China, Japan and globally decreased gradually with increasing year of birth overall. COPD mortality attributable to APM in Korea showed an increasing trend during the birth cohort of 1895–1910 and decreased after peaking in 1910. We hypothesise that the decrease in COPD mortality attributable to PM pollution in recent years is related to people’s lifestyle, change in thinking, external environment and risk factor exposure. Younger generations receive more comprehensive health education about the effects of unhealthy lifestyle and dietary habits on lung function and are thus better equipped to avoid COPD mortality-related risk factors.^{56 57} In addition, economic development and environmental improvements are important reasons for the reduced risk of COPD mortality attributable to PM pollution in young people.⁵⁶

There are also some limitations in this study. First, this study used GBD 2019 for data analysis, and GBD 2019 collected missing data by modifying and adjusting data sources and collection assessment methods, which could not eliminate data bias and affected the accuracy of the results. Second, this study used GBD 2019 data, and the PM_2.5 exposure classification was limited by the data, which only included ambient PM and household air pollution. Third, the APC model only considered the effects of age, period and cohort without further analysis of other risk factors.

Conclusion

We observed an upward trend in ASMR and age-standardised DALY for COPD attributed to PM_2.5, HAP and APM in all regions, except for those globally attributed to APM. There were large regional differences in ASMR and age-standardised DALYs for COPD attributable to PM_2.5, HAP and APM, with China having the highest burden of COPD disease. The risk of COPD due to HAP and APM differed, with COPD due to APM being higher than COPD due to HAP in Japan and Korea and COPD due to HAP being higher than COPD due to APM in China and globally. Overall, COPD mortality attributable to PM_2.5 both increased with age and decreased with time and cohort. Based on the above findings, we call on countries with high disease burden to refer to the public health policies of Japan and Korea and take targeted, site-specific policy measures to reduce the disease burden of COPD caused by PM_2.5 according to pollutant types and age groups.

Thanks to the Institute for Health Metrics and Evaluation, the group and organisation that supports the data.

Data availability statement

Data are available in a public, open access repository. We have described clearly how to obtain data for GBD2019 in manuscript.

Ethics statements

Patient consent for publication

Not applicable.

Ethics approval

Not applicable.

Footnote

Contributors BL and X-FC conceptualised the paper. X-FC did the statistical analysis and drafted the manuscript. S-HM and R-QG conducted the research and data collection. BL and Y-LZ reviewed and edited the writing. BL and J-DZ re-reviewed and co-revised the manuscript from the English language perspective. BL is responsible for the overall content as guarantor. All authors made significant intellectual contributions to multiple revisions of the draft. All authors have read and agreed to the published version of the manuscript.

Funding This research was funded by Collaborative Education Project of University-Industry Cooperation, Ministry of Education, grant number 202102487058; School of Health Management National Subject Incubation Program Project in 2022, grant number 2022RFT005; General Program of Philosophy and Social Science Planning of Guangdong Province in 2023, grant number GD23CGL09; Guangzhou City Philosophy and Social Science Development 14th Five-Year Plan 2023 Subjects, grant number 2023GZGJ108.

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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