Global, regional and national burden of chronic obstructive pulmonary disease and lower respiratory infection attributable to household air pollution and secondhand smoke from 1990 to 2021: an analysis of the Global Burden of Disease Study (GBD 2021)

Introduction

Globally, non-communicable chronic diseases pose the greatest health risk, contributing to about 2/3 of total deaths worldwide (1). Chronic respiratory disease (CRD) is a series of generalized classes of chronic diseases affecting alveoli and airways (2), including chronic obstructive pulmonary disease (COPD), asthma, pneumoconiosis, interstitial lung disease (ILD), and pulmonary sarcoidosis. In 2021, one in twenty individuals globally suffered from CRD, which caused 4.4 million deaths. Among these CRDs, COPD has a certain heterogeneous distribution and represents a significant contributor to morbidity and mortality worldwide. With 213.4 million (194.9–234.0 million) prevalent cases and 3.7 (3.3–4.1) million deaths, COPD had the second-highest prevalence and vast majority of deaths among CRDs in 2021 (3). As measured by 2021 disability-adjusted life years (DALYs), COPD ranked 6th and is forecasted to increase in ranking to 4th in 2050 (4).

Lower respiratory infection (LRI) remains a major public health concern. Despite the widespread implementation of non-pharmaceutical interventions during the coronavirus disease 2019 (COVID-19) pandemics, LRIs accounted for an estimated 344 million cases and 2.18 million fatalities other than severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2021 (5). Acute exacerbations of COPD are predominantly induced by LRIs (6). Exacerbations of COPD are linked to significant morbidity and mortality, while also elevating the patient’s risk of experiencing additional exacerbations in future (7).

Previous Global Burden of Disease Studies (GBDs) have reported declining age-standardized rates (ASRs) for COPD and LRIs, but with persistent regional disparities (8,9). However, most studies have two major limitations. Frist, they overlooked rapid urbanization and “energy stacking” in low- and middle-income countries (LMICs), which slowed the decline in household air pollution (HAP) exposure (10). Second, sparse longitudinal data on regional trends hinder interpretation across socioeconomic contexts (11,12). Although continuous high-quality data from the early 1990s are lacking, the 1990–2021 period can be divided into three meaningful phases: early (1990–2000, baseline with limited surveillance and early energy transition), middle [2000–2010, accelerated clean energy and initial Framework Convention on Tobacco Control (FCTC) implementation], and later (2010–2021, rapid aging, full FCTC, and COVID-19 disruptions) (13,14). This phase-specific approach helps clarify how distinct historical and policy contexts shape regional burden trajectories (15).

Considerable attention has been devoted to the impact of atmospheric pollution and cigarette smoking on respiratory diseases, such as COPD, asthma, and pneumonia (16,17). Although outdoor air pollution is increasingly acknowledged as a major contributing factor to the acute exacerbation of CRD, such as COPD (18), growing scientific studies have increasingly demonstrated that indoor air quality represents a major environmental health issue, given that individuals spend the majority of their time in indoor environments where pollution levels may substantially affect their well-being (19). In 2020, the World Health Organization (WHO) reported a striking figure: approximately 3.2 million lives are lost annually due to HAP (20). Globally, approximately 2.3 billion people—a striking figure—rely on kerosene or solid fuels for cooking (21). This practice is particularly common in middle- and low-income countries, especially among impoverished populations. Indoor air pollution is a predominant risk factor for COPD in middle- and low-income countries (22). For COPD patients with severely impaired lung function, the significant decline in exercise tolerance markedly reduces the spare time that they spend engaging in outdoor activities. Consequently, updating the global burden of COPD attributing to the impact of indoor pollution as an important risk factor is essential for warranting greater attention. From the identified studies, the most frequently focused on sources of indoor pollutants are secondhand smoke (SHS) and air pollution from burning solid fuels (23,24). Approximately 90% of COPD-related deaths occur in LMICs, yet respiratory research remains concentrated in high-income settings, creating a major knowledge gap (25). This paradox reflects global health inequity, prevalence may be higher in high-SDI regions due to better diagnostics and aging, but death rates are excessively high in low-resource settings. Barriers to effective COPD management in LMICs include limited access to spirometry, shortages of essential medications, insufficient oxygen therapy and vaccines, and lack of pulmonary rehabilitation (26,27). Additionally, about 30% of LMIC populations have no national COPD guideline, and existing guidelines meet only 42% of quality standards versus 66% in high-income countries (28,29). Strengthening evidence via standardized global data, such as GBD, is therefore essential to guide equitable resource allocation and prioritize high-burden populations. The GBD 2021 database provides a considerable amount of data and a reliable tool to investigate the attributable risk factors for COPD. In order to provide evidence for future COPD policy development, meanwhile considering the essential role of LRI in acute exacerbation of COPD, this study focused on analyzing the global, regional, and national burden of COPD as well as LRI attributing to SHS and HAP. We present this article in accordance with the GATHER reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0284/rc).

Methods

Data resource

All data utilized in this study were obtained from publicly accessible sources in the Global Health Data 2021(https://ghdx.healthdata.org/gbd-2021/). The GBD 2021 is a large-scale, multi-institutional research project involving 371 diseases and injuries, 87 associated risk factors, in 204 countries and territories for the years 1990–2021 (30). GBD study focuses on detailed, comprehensive, and timely reporting on population health on underlying causes of disability and premature death, which is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations (30). In the GBD 2021, COPD is defined following the Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria, which is based on post-bronchodilator spirometry measurements showing a forced expiratory volume in the 1st to forced vital capacity ratio (FEV₁/FVC) below 0.7. It is classified in the International Classification of Diseases (ICD)-10 by encoding J41, J42, J43, J44, and J47. LRI is defined as clinician-diagnosed pneumonia or bronchiolitis, based on established guidelines and supported by clinical and/or laboratory findings. It is classified in the ICD-10 by encoding A48.1, J09-J22, J85.1, P23-P23.9, U04, and 073.0-073.6, 079.82, 466-469, 480-489, 513.0, 770.0 in ICD-9. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Cause of death data from the GBD 2021 study undergo a standardized ‘garbage code’ redistribution process to improve internal consistency. In this process, codes classified as intermediate or non-specific (e.g., sepsis, heart failure, unspecified LRI) are algorithmically reassigned to underlying causes of death (31). For the present study focusing on COPD, we relied on the GBD-estimated redistributed death counts, which have been adjusted using multiple cause data and proportional allocation rules (31).

The mortality estimates for China used in this study are derived from GBD 2021. For 1990–2021, GBD compiled and standardized mortality data from multiple Chinese sources. The primary source for cause-specific mortality in China during the 1990s was the Disease Surveillance Points (DSP) system (32). Established in 1978, by 1990 the DSP comprised 145 surveillance points across 31 provinces, covering approximately 10 million residents (about 1% of China’s population at that time). However, the DSP points were predominantly located in large cities and more affluent rural areas, introducing a potential bias toward higher socioeconomic groups (33). GBD acknowledged this bias and developed methodological procedures to address it, including methods to aggregate county-level data for provincial analysis and to create specific garbage code redistribution procedures for China (32).

Significant definitions

The socio-demographic index (SDI), a composite measure of developmental status, demonstrates a strong correlation with population health outcomes. SDI represents the geometric mean of three normalized indices (ranging from 0 to 1): total fertility rate under the age of 25 (TFU25), average educational attainment for individuals aged 15 and above (EDU15+), and lag-distributed income (LDI) per capita. An SDI value of 0 represents the theoretical minimum level of development relevant to health, while a value of 1 indicates the theoretical maximum. In GBD 2021 (https://gbd2021.healthdata.org/gbd-results/), all countries were categorized into five different groups according to the SDI: low SDI: SDI <0.47; low-middle SDI: ≥0.47 and <0.62; middle SDI: ≥0.62 and <0.71; high-middle SDI: ≥0.71 and <0.81; high SDI: SDI ≥0.81.

DALYs, a widely adopted metric for assessing disease burden, quantify the cumulative loss of healthy life from disease onset until death, integrating both years of life lost (YLLs) and years lived with disability (YLDs), are mathematically represented in the following standard formula (34).

DALYs=YLLs+YLDs[1]

Statistical analyses

Joinpoint regression analysis was performed with the Joinpoint Regression Program software (version 5.1.0) to evaluate the age-standardized prevalence rate (ASPR), age-standardized incidence rate (ASIR), age-standardized DALYs rate (ASDR), and age-standardized mortality rate (ASMR) of COPD and LRI.

The estimated annual percentage change (EAPC) is a widely recognized and effectively employed metric that has been extensively applied in various studies to monitor trends of indicators such as prevalence, DALYs, and incidence rates over specific time periods, as defined by the following formula:

ln(y)=α+βx+ε;EAPC=100×[exp(β)−1][2]

In this formula, ‘y’ is ASMR, ASDR, ASIR, or ASPR; ‘x’ is the calendar year. An increasing trend in the ASR is inferred when both the estimated EAPC and the lower bound of its 95% uncertainty interval (UI) exceed zero. Conversely, a decreasing trend in the ASR is concluded when both the estimated EAPC and the upper bound of its 95% UI are below zero. In all other scenarios, the ASR is considered to remain stable (35).

Prediction model

In this study, Bayesian age-period-cohort (BAPC) and Autoregressive Integrated Moving Average (ARIMA) models, with well-calibrated probabilistic predictions, were applied to predict future disease burden of COPD and LRIs. The computational processes of BAPC or ARIMA graphic visualizations were created using the R statistical software (version 4.3.0) with packages respectively.

Results

Global burden analysis of COPD and LRIs from 1990 to 2021

The overall disease burden of COPD demonstrated a downward trend between 1990 and 2021 in 204 countries and territories. In 2021, a total of 213.39 (95% UI: 194.87–233.98) million prevalent cases of COPD were estimated. The ASPR was 2,512.86 (95% UI: 2,293.93–2,748.52) per 100,000, with a reduction of 1.46% compared with 1990. The ASDR was 940.66 (95% UI: 871.48–1,014.59) per 100,000, with a reduction of 37.00% compared with 1990. The ASMR was 45.22 (95% UI: 40.61–49.70) per 100,000, with a reduction of 37.12% compared with 1990. The EAPC for ASIR, ASPR, ASMR, and ASDR generally declined. From 1990 to 2021, the most pronounced increases in COPD prevalence were observed in Western Europe and North Africa. The steepest upward trends in ASPR during this period were notably observed in several countries including Libya (0.76, 95% UI: 0.74–0.89) and Algeria (0.62, 95% UI: 0.57–0.68) in Northern Africa, as well as Saudi Arabia (1.08, 95% UI: 1.04–1.10) and Iran (0.76, 95% UI: 0.730.78) in Western Asia. An upward ASDR trend, however, was sustained only in a limited number of nations, including Norway (1.46, 95% UI: 1.08–1.84) and Cuba (1.07, 95% UI: 0.891.26). Upward trends in ASMR were observed in Norway (2.22, 95% UI: 1.77–2.68), Cuba (1.17, 95% UI: 0.99–1.35), and Sweden (0.95, 95% UI: 0.64–1.27) (Figure 1).

Figure 1 The age-standardized rates of COPD and the EAPC of age-standardized rates from 204 countries and territories. (A) ASPR and EAPC of ASPR. (B) ASIR and EAPC of ASIR. (C) ASDR and EAPC of ASDR. (D) ASMR and EAPC of ASMR. ASDR, age-standardized DALYs rate; ASIR, age-standardized incidence rate; ASPR, age-standardized prevalence rate; COPD, chronic obstructive pulmonary disease; DALY, disability-adjusted life year; EAPC, estimated annual percentage change.

Globally, the overall disease burden of LRIs was decreased between 1990 to 2021 in 204 countries and territories. In 2021, a total of 757.00 (95% UI: 719.88–800.53) million prevalent cases of LRIs were estimated. In 2021, the ASPR was 94.42 (95% UI: 89.78–99.84) per 100,000, with a reduction of 32.83% compared with 1990. ASDR was 1168.80 (95% UI: 1,016.96–1,336.95) per 100,000, with a decline of 66.35% compared with 1990. ASMR was 28.67 (95% UI: 25.9231.07) per 100,000, with a decline of 53.62% compared with 1990. EAPC for ASIR, ASPR, ASMR, and ASDR were found generally declined in LRIs between 1990 to 2021. Despite the overall declining trend in the global burden of LRIs, EAPC for ASPR continued to increase in several countries. Such as Argentina (0.62, 95% UI: 0.57–0.68), Chad (0.17, 95% UI: −0.05 to 0.39) and Guinea (0.15, 95% UI: −0.12 to 0.43). Upward ASDR trend was sustained in a limited number of countries, such as Argentina and Zimbabwe, with EAPC for ASDR of (1.72, 95% UI: 1.37–2.07) and (0.81, 95% UI: 0.29–1.32), respectively. Upward mortality rates were observed in Argentina and several Asian countries as Malaysia, Thailand and Kuwait (Figure 2).

Figure 2 The age-standardized rates of LRIs and the EAPC of age-standardized rates from 204 countries and territories. (A) ASPR and EAPC of ASPR. (B) ASIR and EAPC of ASIR. (C) ASDR and EAPC of ASDR. (D) ASMR and EAPC of ASMR. ASDR, age-standardized DALYs rate; ASIR, age-standardized incidence rate; ASPR, age-standardized prevalence rate; DALY, disability-adjusted life year; EAPC, estimated annual percentage change; LRI, lower respiratory infection.

Differences in the disease burden of COPD and LRIs across age and sex

From 1990 to 2021, a consistent downward trend in ASDR and ASMR was observed in both male and female in COPD, accompanied by a slight decrease in ASPR. Higher ASPR, ASDR and ASMR were observed in male COPD patients than female (Figure 3). Same downward trend in ASPR, ASDR, ASMR was observed in both male and female in LRIs. Similarly, these ASRs listed above, were higher in male LRI than in female patients (Figure 4).

Figure 3 Temporal evolution of global COPD burden by gender. (A) Prevalence. (B) DALYs. (C) Mortality. ASDR, age-standardized DALYs rate; ASMR, age-standardized mortality rate; ASPR, age-standardized prevalence rate; COPD, chronic obstructive pulmonary disease; DALY, disability-adjusted life year.

Figure 4 Temporal evolution of global LRIs burden by gender. (A) Prevalence. (B) DALYs. (C) Mortality. ASDR, age-standardized DALYs rate; ASMR, age-standardized mortality rate; ASPR, age-standardized prevalence rate; DALY, disability-adjusted life year; LRI, lower respiratory infection.

To further investigate the temporal trends in the prevalence, incidence, mortality, and DALYs of COPD and LRIs across different age groups globally from 1990 to 2021, we obtained the corresponding data from the GBD database and analyzed the age-specific patterns of ASPR, ASDR, ASIR, and ASMR respectively. The results demonstrated that in the burden of COPD, showed positive percentage changes in females aged ≥75 years and males aged ≥80 years (Figure 5). Consequently, the disease burden of COPD in females aged ≥75 years might warrant particular additional attention. Regarding the disease burden of LRIs, all ASRs—including ASPR, ASDR, ASIR, and ASMR exhibited declining trends across both sexes and all age groups. A more pronounced decline was particularly observed among adolescents aged <15 years and older adults aged ≥60 years (Figure 6).

Figure 5 Temporal evolution of global COPD burden by ages. (A) ASPR. (B) ASIR. (C) ASDR. (D) ASMR. ASDR, age-standardized DALYs rate; ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate; ASPR, age-standardized prevalence rate; COPD, chronic obstructive pulmonary disease.

Figure 6 Temporal evolution of global LRIs burden by ages. (A) ASPR. (B) ASIR. (C) ASDR. (D) ASMR. ASDR, age-standardized DALYs rate; ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate; ASPR, age-standardized prevalence rate; LRI, lower respiratory infection.

Differences in COPD and LRIs burden across SDI levels

The global disease burden of COPD and LRIs from 1990 to 2021, were significantly influenced by the SDI. Through analyzing of ASDR for COPD across different SDI regions over the 32-year period revealed a progressive decline in ASDR over time with increasing SDI levels. When categorized by 2021 SDI levels globally, South Asia emerged with the highest ASDR (Figure 7A). Similar to COPD, ASDR in LRIs also demonstrated a significant inverse association with the SDI, exhibiting a progressive decline over the studied period as SDI levels increased. Sub-Saharan Africa exhibited the highest ASDR for LRIs, with South Asia demonstrating the second-highest burden among 2021’s SDI-stratified global regions (Figure 7B).

Figure 7 Differences in COPD (A) and LRIs (B) burden across SDI levels. ASDR, age-standardized DALYs rate; COPD, chronic obstructive pulmonary disease; LRI, lower respiratory infection; SDI, socio-demographic index.

Influence of SHS and HAP on the disease burden of COPD and LRIs

Globally, both SHS and HAP imposed a greater disease burden of COPD in males than in females. Furthermore, the overall COPD burden, such as ASDR and ASMR, attributable to these two risk factors in 2021 demonstrated a significant reduction compared with 1990 levels. Between 1990 and 2021, SHS-associated COPD burden demonstrated substantial declines in both ASMR and ASDR, with greater reductions observed in females (ASMR: −53.99%; ASDR: −53.05%) than males (ASMR: −41.25%; ASDR: −42.26%). HAP-associated COPD burden demonstrated a more pronounced declines in both ASMR and ASDR, with greater reductions observed in females (ASMR: −72.60%; ASDR: −70.62%) than males (ASMR: −75.93%; ASDR: −74.62%) (Figure 8A).

Figure 8 Analyses of SHS- and HAP-associated ASDR and ASMR for both COPD (A) and LRIs (B). ASDR, age-standardized DALYs rate; ASMR, age-standardized mortality rate; COPD, chronic obstructive pulmonary disease; HAP, household air pollution; LRI, lower respiratory infection; SHS, secondhand smoke.

Analyses of SHS- and HAP-associated burdens for LRIs revealed that, with the exception of higher female ASDR attributable to SHS in 1990, all other ASDR and ASMR demonstrated consistently elevated burdens in males compared with females throughout 1990–2021. Between 1990 and 2021, SHS-associated LRIs burden demonstrated substantial declines in both ASMR and ASDR, with great reductions observed in females (ASMR: −70.77%; ASDR: −79.85%) than males (ASMR: −64.84%; ASDR: −76.68%). HAP-associated LRIs burden demonstrated similar declines in both ASMR and ASDR, with reductions observed both in females (ASMR: −72.67%; ASDR: −77.17%) and males (ASMR: −71.11%; ASDR: −74.91%) (Figure 8B).

Prediction of the ASIR for COPD and LRIs

ARIMA model was applied to analyze and project the potential global burden of incidence and mortality rates for COPD and LRIs over a future 19-year period [2022–2040]. The ASMR of COPD has been showing a continuous downward trend in both male and female patients. However, while the ASIR has been decreasing year by year in male patients, it has remained largely unchanged in female patients since 2024 (Figure 9A). For LRIs, both the ASIR and ASMR have shown a consistent declining trend in both males and females (Figure 9B).

Figure 9 Sex-specific impact on future disease burden of COPD (A) and LRIs (B) by ARIMA model. ARIMA, Autoregressive Integrated Moving Average; ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate; COPD, chronic obstructive pulmonary disease; LRI, lower respiratory infection.

Globally, ASMR of COPD exhibits a year-on-year decline across almost the whole age groups in the BAPC projection period. ASIR of COPD exhibits a gradual year-on-year decline across most age groups. In the extremely elderly age groups (80–84, 85–89, 90–94, and ≥95 years), the ASIR curve of COPD patients demonstrated an initial gradual increase followed by a subsequent slow decline (Figure 10A). By 2044, ASMR of LRIs globally demonstrates a slight upward trend among patients aged ≥95 years, while generally exhibiting declining trends in other age groups, stabilizing after 2024. The ASIR of LRIs in individuals aged ≥90 years shows a modest increase after 2024, whereas ASIR remains stable in other age groups during this period (Figure 10B).

Figure 10 Age-specific impact on future disease burden of COPD (A) and LRIs (B) by BAPC model. ASIR, age-standardized incidence rate; ASMR, age-standardized mortality rate; BAPC, Bayesian age-period-cohort; COPD, chronic obstructive pulmonary disease; LRI, lower respiratory infection.

Twenty-year projection of global COPD and LRI burden attributable to SHS and HAP using ARIMA modeling

During 2022–2040 under SHS exposure, ASDR for female COPD patients declines before stabilizing, while ASDR in males demonstrates a continuing downward trend. Female ASDR and ASMR are projected to approach and exceed male levels in 2030 and 2032, respectively. However, SHS exposure does not show significant gender disparities in ASDR or ASMR among LRI patients, with both rates demonstrating sustained year-on-year reductions (Figure 11A). Considering the influence of HAP, the ASDR and ASMR for COPD maintains a declining trend over time. Male patients exhibit a more pronounced year-on-year reduction, whereas female patients stabilize after 2030. Around or after 2030, female COPD patients are projected to approach and exceed males in both ASDR and ASMR under persistent HAP exposure. However, under persistent HAP exposure, both ASDR and ASMR for LRIs demonstrates sustained year-on-year reductions without significant gender disparities (Figure 11B).

Figure 11 Projection of global COPD (A) and LRIs (B) burden attributable to SHS and HAP using ARIMA modeling. ARIMA, Autoregressive Integrated Moving Average; ASDR, age-standardized DALYs rate; ASMR, age-standardized mortality rate; COPD, chronic obstructive pulmonary disease; HAP, household air pollution; LRI, lower respiratory infection; SHS, secondhand smoke.

Discussion

This study utilized the GBD2021 database to provide comprehensive estimates of the disease burden for COPD. Meanwhile, it presents corresponding burden estimates for LRIs, the major factor closely associated with COPD exacerbation. Notably, several burden indicators of COPD, including prevalence rates, the absolute number of DALYs, and death counts, have increased. While the age-standardized disease burden rate of COPD demonstrated a declining trend over time, the ASPR continued to rise in some regions, particularly in Western Asia and North Africa. All the prevalence, DALYs, mortality counts and ASRs of LRIs have been demonstrated a consistent downward trend. Both COPD and LRIs exhibited significant inverse correlations with socioeconomic development levels, as evidenced by a consistent decline in their ASDR with increasing SDI. GOLD2025 Report explicitly emphasizes that COPD is currently the third leading cause of death globally, with approximately 90% of COPD-related deaths concentrated in LMICs (36). As a primary trigger for acute exacerbations of COPD, our findings further demonstrate low SDI is also significantly associated with heavy disease burden of LRIs. This association might be largely contributed to by suboptimal healthcare infrastructure, inadequate social security systems, and low vaccine coverage for respiratory diseases in low-SDI countries (37,38). Our observation aligns with several studies substantiating that lower socioeconomic status correlates with an elevated burden of COPD acute exacerbations (39). In the advanced-age population (≥75 years), the increasing disease burden of COPD is primarily driven by ASPR and ASIR, suggesting that the growing aging population worldwide might be a major contributing factor to the heavier disease burden of COPD (40). Although the age-standardized burden of COPD (including ASPR, ASDR, and ASMR) demonstrates a broad declining trend overall and is consistently lower in females than in males, a marked increase in this burden is observed specifically among females aged ≥75 years, where it became markedly heavier than in their male counterparts. This phenomenon has historically been attributed to the increased overall life expectancy, reduced mortality rates from other diseases, such as cardiovascular disease, among elderly females, and changes in smoking behavior within the female population (41,42), For LRIs, the age-standardized disease burden demonstrates a progressive decline over time in both males and females. Furthermore, unlike the pattern seen in COPD, no discernible increase in burden has been observed among female patients within the oldest age (≥75 years). These interesting findings may prompt consideration of factors beyond LRIs contributing to the increased disease burden observed in advanced-age COPD patients, particularly among females (43).

In most cases, smoking, exposure to indoor and ambient air pollution, and occupational pollutants have been established as the principal risk factors for COPD (44). Despite the persistent primacy of tobacco smoking in COPD etiology, non-active smoking exposure has emerged as significant contributors to the rising COPD burden in LMICs (45). According to GBD2021, HAP has surpassed occupational exposure as the third leading risk factor for COPD, accounting for 19.5% of COPD DALYs (46). As COPD disproportionately impacts elderly populations, activity limitations from the disease extend indoor residence time. This behavior change precipitates significant underestimation of HAP-attributable burden, with particularly pronounced biases in LMICs (47). While smoking cessation interventions occupy a well-established position in COPD policy frameworks, our study specifically focused on the disease burden associated with HAP and SHS exposure in COPD and its exacerbation-critical comorbidity, LRIs.

Our study showed that the DALYs rate for COPD attributable to HAP decreased from 661.17 per 100,000 in 1990 to 181.17 per 100,000 in 2021. Similarly, the DALYs rate for COPD attributable to SHS exposure declined from 129.21 per 100,000 to 66.78 per 100,000 over the same period. Our findings also demonstrated that the DALYs rate for LRIs attributable to HAP declined from 1,154.57 per 100,000 in 1990 to 276.63 per 100,000 in 2021. Meanwhile, the rate attributable to SHS decreased from 406.81 per 100,000 to 88.26 per 100,000 over the same period. Therefore, for both COPD and LRIs, HAP imposes a greater disease burden than SHS as a risk factor. The widespread adoption of clean energy and modern cooking technologies, now covering nearly 70% of the global population, has led to a progressive reduction in the burden of respiratory diseases associated with HAP (48). Therefore, the disparity in the impact on COPD DALYs between HAP and SHS narrows significantly, from HAP being 5.1 times that of SHS in 1990 to merely 2.7 times by 2021. In contrast, for LRIs DALYs, the burden attributable to HAP remains consistently about 3-times that of SHS throughout the period, from 1990 to 2021. Despite HAP consistently conferring a higher burden of COPD and LRIs than SHS, especially in LMICs where it is a leading cause, the attributable burden from SHS demands increased focus amidst the widespread adoption of clean energy (49). A sex disparity has been also observed in the DALYs attributable to SHS and HAP. For SHS, the burden shifts from being slightly higher among females in 1990 to being greater among males in 2021. Conversely, HAP consistently imposed a higher burden on males across the entire study period.

In this study, the ARIMA was employed to predict sex-specific temporal trends, while the BAPC model was used to analyze age-specific temporal cohorts for disease burden projection. Overall, the global burden of both COPD and LRIs exhibits a declining trend. However, a modest upward trend in the ASIR for both COPD and LRIs is observed after 2024 within specific demographic subgroups, notably among the elderly population (≥75 years). The rise in ASIR in the elderly population, despite the overall favorable trend, is probably driven by demographic shifts toward an aging population and gains in average life expectancy.

The trends observed for COPD and LRI burden should be interpreted within the broader setting of social transformation. Over the past three decades, accelerated urban growth across Asia and Africa has fundamentally reshaped patterns of environmental exposure. Although this transition has, in certain contexts, diminished dependence on traditional biomass fuels, it has concurrently elevated exposure to ambient air pollutants in expanding metropolitan areas—where inadequate urban planning, elevated population density, and the juxtaposition of industrial and residential zones serve to concentrate pollution sources (5). Adding further complexity, the shift from solid fuels to cleaner energy sources has unfolded unevenly across LMICs. A substantial number of households engage in what is termed “energy stacking”—the simultaneous use of clean and traditional solid fuels—driven by economic limitations, cultural norms, or unreliable fuel supply (50). Such behavioral patterns lead to a slower reduction in HAP exposure than would otherwise be expected, because even partial and intermittent combustion of polluting fuels maintains considerable exposure levels. A nuanced appreciation of these social and behavioral determinants is therefore essential for correctly interpreting the burden trajectories documented here and for crafting effective public health interventions.

The epidemiological transition framework offers a useful perspective for making sense of the seemingly contradictory trends observed in our study: declining ASRs alongside persistently elevated absolute burdens. As this framework posits, societies typically move from an era of pestilence and famine (dominated by infectious diseases) through a phase of receding pandemics (with improved infection control) to a stage of degenerative and human-induced diseases (dominated by non-communicable diseases, NCDs) (51). At present, many LMICs occupy an intermediate position within this transition, facing a “dual burden” whereby improvements in child survival from infectious illnesses are progressively counterbalanced by an increasing load of CRDs among aging populations (52). Our findings reflect this duality: although ASMRs for both COPD and LRI have fallen substantially—owing to advances in sanitation, vaccination programs, and broader access to antibiotics—the absolute number of cases continues to rise as a result of population expansion and demographic aging. Furthermore, healthcare systems in many LMICs remain better adapted to managing acute infectious conditions than to addressing chronic diseases that demand long-term follow-up, consistent medication adherence, and pulmonary rehabilitation services (53). This disconnect between the prevailing epidemiological profile and the existing capacity of health systems highlights the pressing need for integrated, life-course approaches to respiratory health.

Additionally, several methodological considerations related to data processing should be acknowledged. The GBD study applies a standardized ‘garbage code’ redistribution algorithm to reclassify non-specific or intermediate causes of death (e.g., heart failure, unspecified LRI) into plausible underlying causes such as COPD. While this process improves the consistency and comparability of cause-specific mortality estimates across regions and time, it relies on empirical algorithms and assumptions about disease patterns. These assumptions may introduce bias, particularly in settings where diagnostic coding practices vary or where specific underlying causes are systematically underdocumented (31). Therefore, the burden estimates for COPD attributable to HAP and SHS should be interpreted with awareness of this potential non‑differential misclassification.

In this study, the application of the ARIMA model to predict the impact of HAP and SHS on the burden of COPD, reveals a certain degree of sex-based heterogeneity in the effects of both risk factors. Over the future 20 years, the COPD burden attributable to HAP and SHS is expected to follow a distinct sex-specific pattern: a gradual decline in males contrasted with a relatively stable trend in females, leading to an eventual crossover where the burden in females surpasses that in males. This narrowing disparity, improvements in household ventilation, and gender-based divisions in cooking responsibilities (54). Some studies have also proposed a hypothesis that females exhibit greater susceptibility to air pollutants (55). However, the exact mechanisms warrant further investigation to be substantiated.

Another notable finding is the COVID-19 pandemic substantially altered the epidemiology of LRI and the clinical management of COPD. During the pandemic period, non-pharmaceutical interventions globally altered respiratory virus circulation patterns. Similar disruptions have been observed for other respiratory viruses, with altered seasonal patterns and delayed peaks in southwestern China (56). For COPD, the pandemic led to delays in diagnosis and follow-up visits, reduced access to pulmonary rehabilitation, and overall disruption of routine care (15). These factors likely introduced non-stationary volatility into the time series data for both LRI and COPD during 2020–2021.

To translate our findings into actionable public health measures, we propose the following interventions based on the observed burden patterns. First, expand vaccine coverage in high-burden areas. Pneumonia remains a major driver of LRI mortality, yet effective vaccines against Streptococcus pneumoniae [pneumococcal conjugate vaccine (PCV)] and influenza remain underused in LMICs. In 2022, global PCV stood at only 60.0%, with marked cross-country inequalities. Moreover, 83% of influenza-related respiratory deaths occur in LMICs, whereas these regions receive just 24% of the world’s vaccine doses (57). Closing these coverage gaps could avert millions of LRI episodes and COPD exacerbations each year. Second, use economic incentives to promote clean cooking technologies. The persistent HAP burden in LMICs, despite the known health benefits of clean fuels, reflects market failures and affordability constraints. Policy tools with proven effectiveness include targeted subsidies for clean cooking fuels, tax breaks for clean stove manufacturers, and carbon credits that capture the climate benefits of reduced biomass burning. Notably, subsidies for transitional fuels like LPG could help over 400 million marginalized households avoid the health costs of traditional biomass cooking, while also supporting longterm pathways to fully clean technologies. However, clean fuel subsidies alone are insufficient; complementary efforts addressing information gaps, supply chain reliability, and cultural preferences are essential for sustained adoption (58). Third, make indoor air quality improvement a strategic priority in national health plans. The sex-specific patterns we identified—especially the projected crossover around 2030 where the female COPD burden attributable to HAP and SHS overtakes that of males—suggest that indoor air quality should be elevated to a priority on par with tobacco control. Achieving this will require multisectoral coordination across health, energy, housing, and environmental regulation.

Limitations

There are several limitations in this study that should be acknowledged. These include potential biases in data sources, variations in definitions and diagnostic criteria for LRIs across different studies, and the possible incomplete capture of the complexity of risk factors. Further research is needed to address these knowledge gaps and to better understand the dynamic nature of the burden and risk factors of both COPD and LRIs.

Conclusions

Despite the overall global decline in the burden of COPD and LRIs, our study identified persistently high disease burdens among elderly populations and in LMICs. Importantly, HAP and SHS, as major indoor air pollution sources, contribute to the disease burden partially in a sex-specific manner. Moreover, our projections indicate that the future burden of COPD attributable to both HAP and SHS will be greater in females, particularly those aged ≥75 years, and is expected to surpass that in males around 2030. To address this emerging trend, priority interventions should include reducing indoor HAP exposure (e.g., promoting clean cooking fuels and improving ventilation), implementing smoke-free home environments, and establishing early screening and management programs for COPD in older women. These observations might influence the design and prioritization of public health interventions.

Acknowledgments

We would like to express our gratitude to everyone who contributed to the GBD 2021 study.

Footnote

Reporting Checklist: The authors have completed the GATHER reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0284/rc

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0284/prf

Funding: This work was supported by National Natural Science Foundation of China, Youth Program (No. 82200095), Chongqing Natural Science Foundation (No. CSTB2023NSCQ-MSX0389), Chongqing Medical Scientific Research Project (Joint Project of Chongqing Health Commission and Science and Technology Bureau) (No. 2026KFXM011), and the First batch of key Disciplines on Public Health in Chongqing (No. CMHC [2022] No. 71).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0284/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Lozano R, Naghavi M, Foreman K, et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012;380:2095-128. [Crossref] [PubMed]
2. Global burden of chronic respiratory diseases and risk factors, 1990-2019: an update from the Global Burden of Disease Study 2019. EClinicalMedicine 2023;59:101936.
3. Zhao M, Zhai H, Li H, et al. Age-standardized incidence, prevalence, and mortality rates of autoimmune diseases in adolescents and young adults (15-39 years): an analysis based on the global burden of disease study 2021. BMC Public Health 2024;24:1800. [Crossref] [PubMed]
4. GBD 2021 Forecasting Collaborators. Burden of disease scenarios for 204 countries and territories, 2022-2050: a forecasting analysis for the Global Burden of Disease Study 2021. Lancet 2024;403:2204-56. [Crossref] [PubMed]
5. Global, regional, and national incidence and mortality burden of non-COVID-19 lower respiratory infections and aetiologies, 1990-2021: a systematic analysis from the Global Burden of Disease Study 2021. Lancet Infect Dis 2024;24:974-1002.
6. Torres A, Cilloniz C, Niederman MS, et al. Pneumonia. Nat Rev Dis Primers 2021;7:25. [Crossref] [PubMed]
7. Guerrero M, Crisafulli E, Liapikou A, et al. Readmission for Acute Exacerbation within 30 Days of Discharge Is Associated with a Subsequent Progressive Increase in Mortality Risk in COPD Patients: A Long-Term Observational Study. PLoS One 2016;11:e0150737. [Crossref] [PubMed]
8. Patel S, Marchant J, Bhatt SP, et al. Rural versus urban living and COPD: a systematic review. Eur Respir Rev 2026;35:250290. [Crossref] [PubMed]
9. Adeloye D, Chua S, Lee C, et al. Global and regional estimates of COPD prevalence: Systematic review and meta-analysis. J Glob Health 2015;5:020415. [Crossref] [PubMed]
10. Cui Y, Yan Y. Effect of water and sanitation, PM pollution and climate change of COPD and LRIs under different sociodemographic transitions. Public Health 2024;237:150-9. [Crossref] [PubMed]
11. Herbst K, Juvekar S, Jasseh M, et al. Health and demographic surveillance systems in low- and middle-income countries: history, state of the art and future prospects. Glob Health Action 2021;14:1974676. [Crossref] [PubMed]
12. Wamai RG, Kengne AP, Levitt N. Non-communicable diseases surveillance: overview of magnitude and determinants in Kenya from STEPwise approach survey of 2015. BMC Public Health 2018;18:1224. [Crossref] [PubMed]
13. Stoner O, Lewis J, Martínez IL, et al. Household cooking fuel estimates at global and country level for 1990 to 2030. Nat Commun 2021;12:5793. [Crossref] [PubMed]
14. Tauras JA. Tobacco control in low-income and middle-income countries: findings from WHO FCTC investment cases. Tob Control 2024;33:s1-s2. [Crossref] [PubMed]
15. Fekadu G, Bekele F, Tolossa T, et al. Impact of COVID-19 pandemic on chronic diseases care follow-up and current perspectives in low resource settings: a narrative review. Int J Physiol Pathophysiol Pharmacol 2021;13:86-93.
16. Basille D, Soriot L, Weppe F, et al. Association between acute exacerbation of chronic obstructive pulmonary disease and short-term exposure to ambient air pollutants in France. Environ Health 2024;23:107. [Crossref] [PubMed]
17. Yatera K, Nishida C. Contemporary Concise Review 2023: Environmental and occupational lung diseases. Respirology 2024;29:574-87. [Crossref] [PubMed]
18. Thurston GD, Kipen H, Annesi-Maesano I, et al. A joint ERS/ATS policy statement: what constitutes an adverse health effect of air pollution? An analytical framework. Eur Respir J 2017;49:1600419.
19. Viegi G, Simoni M, Scognamiglio A, et al. Indoor air pollution and airway disease. Int J Tuberc Lung Dis 2004;8:1401-15.
20. Aithal SS, Sachdeva I, Kurmi OP. Air quality and respiratory health in children. Breathe (Sheff) 2023;19:230040. [Crossref] [PubMed]
21. GBD 2015 Risk Factors Collaborators. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet 2016;388:1659-724. [Crossref] [PubMed]
22. Agustí A, Celli BR, Criner GJ, et al. Global Initiative for Chronic Obstructive Lung Disease 2023 Report: GOLD Executive Summary. Eur Respir J 2023;61:2300239. [Crossref] [PubMed]
23. Chu MT, Gillooly SE, Levy JI, et al. Real-time indoor PM(2.5) monitoring in an urban cohort: Implications for exposure disparities and source control. Environ Res 2021;193:110561. [Crossref] [PubMed]
24. Levy JI, Kibilko K. Indoor Air Quality in Multi-Family Housing: Drivers and Interventions. Curr Environ Health Rep 2025;12:4. [Crossref] [PubMed]
25. Alupo P, Baluku J, Bongomin F, et al. Overcoming challenges of managing chronic obstructive pulmonary disease in low- and middle-income countries. Expert Rev Respir Med 2024;18:873-82. [Crossref] [PubMed]
26. Rossaki FM, Hurst JR, van Gemert F, et al. Strategies for the prevention, diagnosis and treatment of COPD in low- and middle- income countries: the importance of primary care. Expert Rev Respir Med 2021;15:1563-77. [Crossref] [PubMed]
27. Jackson P, Muyanja SZ, Siddharthan T. Health Equity and Respiratory Diseases in Low- and Middle-Income Countries. Clin Chest Med 2023;44:623-34. [Crossref] [PubMed]
28. Tabyshova A, Hurst JR, Soriano JB, et al. Gaps in COPD Guidelines of Low- and Middle-Income Countries: A Systematic Scoping Review. Chest 2021;159:575-84. [Crossref] [PubMed]
29. Boutros P, Kassem N, Boudo V, et al. Understanding the Risk Factors, Burden, and Interventions for Chronic Respiratory Diseases in Low- and Middle-Income Countries: A Scoping Review. Public Health Rev 2024;45:1607339. [Crossref] [PubMed]
30. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet 2024;403:2133-61.
31. Johnson SC, Cunningham M, Dippenaar IN, et al. Public health utility of cause of death data: applying empirical algorithms to improve data quality. BMC Med Inform Decis Mak 2021;21:175. [Crossref] [PubMed]
32. Zhou M, Wang H, Zhu J, et al. Cause-specific mortality for 240 causes in China during 1990-2013: a systematic subnational analysis for the Global Burden of Disease Study 2013. Lancet 2016;387:251-72. [Crossref] [PubMed]
33. Liu S, Wu X, Lopez AD, et al. An integrated national mortality surveillance system for death registration and mortality surveillance, China. Bull World Health Organ 2016;94:46-57. [Crossref] [PubMed]
34. GBD 2019 Australia Collaborators. Pre-COVID life expectancy, mortality, and burden of diseases for adults 70 years and older in Australia: a systematic analysis for the Global Burden of Disease 2019 Study. Lancet Reg Health West Pac 2024;47:101092. [Crossref] [PubMed]
35. Deng Y, Zhao P, Zhou L, et al. Epidemiological trends of tracheal, bronchus, and lung cancer at the global, regional, and national levels: a population-based study. J Hematol Oncol 2020;13:98. [Crossref] [PubMed]
36. Meghji J, Mortimer K, Agusti A, et al. Improving lung health in low-income and middle-income countries: from challenges to solutions. Lancet 2021;397:928-40. [Crossref] [PubMed]
37. Wahl B, O’Brien KL, Greenbaum A, et al. Burden of Streptococcus pneumoniae and Haemophilus influenzae type b disease in children in the era of conjugate vaccines: global, regional, and national estimates for 2000-15. Lancet Glob Health 2018;6:e744-57. [Crossref] [PubMed]
38. Li J, Xu L, Zuo AF, et al. The global burden of Klebsiella pneumoniae-associated lower respiratory infection in 204 countries and territories, 1990-2021: Findings from the global burden of disease study 2021. PLoS One 2025;20:e0324151. [Crossref] [PubMed]
39. Zhou JX, Peng ZX, Zheng ZY, et al. Big picture thinking of global PM(2.5)-related COPD: Spatiotemporal trend, driving force, minimal burden and economic loss. J Hazard Mater 2025;488:137321. [Crossref] [PubMed]
40. Guo B, Gan H, Xue M, et al. The Changing and Predicted Trends in Chronic Obstructive Pulmonary Disease Burden in China, the United States, and India from 1990 to 2030. Int J Chron Obstruct Pulmon Dis 2024;19:695-706. [Crossref] [PubMed]
41. Jenkins C. Differences Between Men and Women with Chronic Obstructive Pulmonary Disease. Clin Chest Med 2021;42:443-56. [Crossref] [PubMed]
42. Chen X, Goh N, Dunn S, et al. Gender Disparities in Advanced Lung Diseases: do They Persist Towards the End of Life? Am J Hosp Palliat Care 2025;42:1128-35. [Crossref] [PubMed]
43. Ryu MH, Yun JH, Morrow JD, et al. Blood Gene Expression and Immune Cell Subtypes Associated with Chronic Obstructive Pulmonary Disease Exacerbations. Am J Respir Crit Care Med 2023;208:247-55. [Crossref] [PubMed]
44. Viegi G, Maio S, Fasola S, et al. Global Burden of Chronic Respiratory Diseases. J Aerosol Med Pulm Drug Deliv 2020;33:171-7. [Crossref] [PubMed]
45. Cioboata R, Balteanu MA, Mitroi DM, et al. Beyond Smoking: Emerging Drivers of COPD and Their Clinical Implications in Low- and Middle-Income Countries: A Narrative Review. J Clin Med 2025;14:4633. [Crossref] [PubMed]
46. Wu Y, Zhang S, Zhuo B, et al. Global burden of chronic obstructive pulmonary disease attributable to ambient particulate matter pollution and household air pollution from solid fuels from 1990 to 2019. Environ Sci Pollut Res Int 2022;29:32788-99. [Crossref] [PubMed]
47. Thawanaphong S, Nair P. Contemporary Concise Review 2024: Chronic Obstructive Pulmonary Disease. Respirology 2025;30:574-86. [Crossref] [PubMed]
48. Byaro M, Dimoso P, Rwezaula A. Are clean energy technologies a panacea for environmental sustainability in sub-Saharan African countries? Environ Sci Pollut Res Int 2024;31:67171-86. [Crossref] [PubMed]
49. Wang Y, Jin L, Dong Y, et al. Global burden of disease study on COPD in the older adult: comprehensive analysis of environmental factors and interaction effects. Front Public Health 2025;13:1597793. [Crossref] [PubMed]
50. Iuliano AD, Roguski KM, Chang HH, et al. Estimates of global seasonal influenza-associated respiratory mortality: a modelling study. Lancet 2018;391:1285-300. [Crossref] [PubMed]
51. Konkor I, Kuuire VZ. Epidemiologic transition and the double burden of disease in Ghana: What do we know at the neighborhood level? PLoS One 2023;18:e0281639. [Crossref] [PubMed]
52. Bygbjerg IC. Double burden of noncommunicable and infectious diseases in developing countries. Science 2012;337:1499-501. [Crossref] [PubMed]
53. Puzzolo E, Pope D, Stanistreet D, et al. Clean fuels for resource-poor settings: A systematic review of barriers and enablers to adoption and sustained use. Environ Res 2016;146:218-34. [Crossref] [PubMed]
54. Shupler M, Tawiah T, Nix E, et al. Household concentrations and female and child exposures to air pollution in peri-urban sub-Saharan Africa: measurements from the CLEAN-Air(Africa) study. Lancet Planet Health 2024;8:e95-e107. [Crossref] [PubMed]
55. Li C, Qiu P, Guo H, et al. Air Pollution, Genetic Susceptibility, and Risk of Symptomatic Peripheral Arterial Disease: A Cohort Study of the UK Biobank. Eur J Vasc Endovasc Surg 2026;71:125-34. [Crossref] [PubMed]
56. Ye C, Tian Y, Huo D, et al. Changes in Epidemics of Respiratory Viral Infections Resulted From the COVID-19 Pandemic in Shanghai. J Med Virol 2024;96:e70034. [Crossref] [PubMed]
57. Gill-Wiehl A, Gould CF, Jeuland M, et al. Beyond access: clean energy use in low-income and middle-income countries. Lancet Glob Health 2026;14:e598-611. [Crossref] [PubMed]
58. Gould CF, Bailis R, Balakrishnan K, et al. In praise of cooking gas subsidies: transitional fuels to advance health and equity. Environ Res Lett 2024;19:081002. [Crossref] [PubMed]