Global trends and projections of tracheal, bronchial, and lung (TBL) cancers associated with occupational exposure to diesel engine exhaust (DEE): insights from the Global Burden of Disease (GBD) 2021 Study for 1990 to 2021 and projections to 2035

Introduction

On a global scale, malignant tumors affecting the respiratory system, specifically the trachea, bronchus, and lung (TBL) cancers, constitute a higher proportion of cancer-related morbidity and mortality. Data from recent epidemiological studies show that these malignant neoplasms constitute approximately one-eighth of newly diagnosed cancers (incidence rate of 12.4%) and nearly one-fifth of all cancer-related deaths worldwide (18.7%) (1). The 2019 Global Burden of Disease (GBD) study utilized three key metrics to quantify this impact. The global burden of TBL cancers is characterized by 2.04 million mortalities, 2.26 million new cases, and an aggregate loss of 45.9 million disability-adjusted life years (DALYs) (2). As a non-communicable disease, cancer seems to influence human health. According to World Health Organization (WHO) statistics, at least 19 million people died from cancer in 2021. Among the various neoplastic diseases, pulmonary malignancies maintain their position as the leading driver of global disease burden metrics in terms of the incidence, mortality, and disability parameters (3). TBL cancer has been strongly associated with several factors, such as genetic variation, smoking, environmental influences, and occupational exposures. Occupational exposures is a significant and preventable cause of TBL cancer, contributing to one in four deaths globally (4). Statistics show that the mortality rate caused by occupational exposure to diesel engine exhaust (DEE) increased from 0.05 per 100,000 people in 1990 to 0.07 in 2021 (5). Considering the widespread use of diesel-powered machinery across industries such as transportation, construction, mining, and manufacturing, occupational DEE exposure remains a persistent and under-recognized health threat.

DEE, produced through the incomplete combustion of hydrocarbon fuels, is a major source of occupational and environmental pollution due to its complex mixture of combustion by-products (6). These emissions consist of a heterogeneous mixture of particulate matter (PM2.5) and gaseous components, specifically polycyclic aromatic hydrocarbons (PAHs), benzene derivatives, aldehydes (e.g., formaldehyde), and nitrogen oxides (NOx), a profile containing multiple the International Agency for Research on Cancer (IARC)-classified carcinogenic agents (7). Of particular toxicological concern is the PM2.5 fraction, with its aerodynamic properties enabling deep respiratory penetration and hematogenous dissemination, promoting diverse pathological processes such as chronic inflammatory responses and subsequent systemic complications (8,9). The toxicological profile of DEE was formally recognized in 2008 when the German Research Foundation’s Commission for Hazardous Substances (DFG) categorized these emissions under Category 2: substances exerting definitive carcinogenic potential in experimental models (10). This regulatory decision indicates the convergence of empirical evidence from multidisciplinary toxicological investigations, including controlled animal exposure studies and population-based epidemiological analyses. Subsequently, IARC performed a systematic review in 2012, which led to the designation of DEE as a Group 1 agent with unequivocal carcinogenic potential in humans (11). This designation categorizes DEE in the same category as tobacco smoke and asbestos, supporting the urgent need for stricter regulations and protective measures for workers. In 2022, following the analysis of air quality test data from 2010 to 2019, the WHO demonstrated that nitrogen dioxide (NO₂), PM_2.5 with a diameter equal to or less than 10 µm (PM₁₀) or equal to or less than 2.5 µm (PM_2.5) represent the average values for the entire city or town, rather than the values from individual monitoring stations. Although DEE exposure is widespread in the general population, occupational exposure poses the greatest health risk due to its higher intensity and prolonged duration.

The development of TBL cancer is driven by several multifactorial processes, involving both genetic predisposition and environmental exposures (12). Prolonged occupational exposure to DEE, which contains known carcinogens such as PAHs, fine PM2.5, and elemental carbon, can enhance the risk of TBL cancer. Epidemiological evidence confirms a significant association between DEE exposure and increased lung cancer incidence, with tumor registry analyses revealing a pronounced predilection for certain histological subtypes, particularly squamous cell carcinoma (SCC) and large cell carcinoma (LCC) (13). Occupational cohort studies have also identified dose-dependent associations, wherein populations with prolonged DEE exposure demonstrate elevated risk of pulmonary malignancies. Notably, this correlation persists in multivariate models that adjust for confounding factors such as tobacco use. This conclusion is further corroborated by longitudinal surveillance data from high-risk occupational populations (14,15).

The burden of TBL cancer induced by DEE is not fully understood, and there are significant gaps in understanding its global impact and epidemiological trends. This present study employed the GBD 2021 dataset to systematically evaluate temporal patterns in mortality and DALYs associated with DEE-related TBL malignancies from 1990 to 2021. Application of joinpoint regression analysis can help to delineate significant inflection points in epidemiological trajectories, while also assessing the spatial heterogeneity and socio-demographic determinants that impact the burden distribution across populations. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1003/rc).

Methods

Data resource

This study is based on epidemiological metrics from the GBD 2021 study, a multinational epidemiological repository that harbors a comprehensive number of 288 etiological categories, 371 disease/injury entities, and 88 modifiable risk exposures spanning 204 countries and regions across three decades (1990–2021). The standardized metric system and methodological framework are publicly accessible via the Global Health Data Exchange platform (GHDx 2021; https://vizhub.healthdata.org/gbd-results/, accessed 1 January 2025), which acts as the primary data curation interface for GBD-derived parameters. This platform serves as a source of mortality rates and DALYs for TBL cancers associated with occupational DEE exposure from 1990 to 2021. The study also provided further details such as sex, age, location, etc., for descriptive analysis and visualization.

Statistical analysis

Core indicators and quantification of uncertainty

This study utilized two core epidemiological indicators to determine the risk of death in specific populations and time periods: crude mortality counts and age-standardized mortality rates (ASMRs). Moreover, DALYs are utilized to evaluate the aggregate health loss resulting from exposure to DEE, particularly concerning malignant tumors of the trachea, bronchi, and lungs. To account for uncertainties in data sources, modeling processes, and parameter estimates, all mortality figures (such as crude death counts and ASMR) and epidemiological indicators [including DALYs and age-standardized DALY rates (ASDR)] were calculated and presented with 95% uncertainty intervals (UIs).

Longitudinal trend analysis

This study utilized the estimated annual percentage change (EAPC) model to analyze the long-term longitudinal trends of disease burden indicators (ASMR, ASDR, crude death rates, DALYs) from 1990 to 2021. The EAPC model is a quantitative model that effectively quantifies the exponential growth or decline of indicators over time. It is particularly ideal for describing the average annual relative change rate of disease burden indicators over a long time span.

To clarify the overall trends (net drift) and local trend changes within specific time periods (local drift), we first performed preliminary explorations using an online tool based on the age-period-cohort (APC) model provided by the National Cancer Institute (NCI). Subsequently, the Joinpoint regression software (version 5.4.0, NCI) was utilized to calculate the average annual percentage change (AAPC) and to identify significant turning points in trends. For the Joinpoint model, statistical significance of AAPC deviations from the null hypothesis (i.e., no change) was measured using the Monte Carlo permutation test (significance level α=0.05), to clarify the observed changes in trends.

Disease burden prediction

This study employed a Bayesian hierarchical model using the integrated nested Laplace approximation (INLA) to forecast the distribution of disease burden in 2035 and to quantify the associated prediction uncertainty the INLA. The model employs a poisson likelihood function to model mortality rates and incorporates age groups, periods (years), and birth cohort effects to include complex patterns of disease burden changes with age, time, and generational shifts. INLA is an efficient method that can estimate the posterior distribution of Bayesian hierarchical models (especially latent Gaussian models). It is applied in handling large-scale spatial or spatiotemporal data, and effectively quantifying the UIs of predictions. The model aims to estimate population-wide mortality rates for 2035, providing both point estimates and corresponding UIs.

Data processing and visualization

All data preprocessing, statistical analysis [including EAPC calculation, joinpoint regression analysis, and Bayesian APC (BAPC) modelling], and visualization of results was performed using R software (version 4.4.2) and its associated packages (such as joinpointR, INLA, ggplot2, tidyverse, etc.).

Ethical information

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Results

Global burden

The number of fatal cases of TBL associated with occupational exposure to DEE in the global population increased markedly from 1990–2021, from 7,896.05 (95% UI: 6,827.28–9,174.69) to 21,619.90 (95% UI: 18,060.68–25,544.34). However, the ASMR showed a marginal decline, with a decrease from 0.31 (95% UI: 0.26–0.36) to 0.24 (95% UI: 0.20–0.29) per 100,000 population. Similarly, the number of DALYs rose from 249,939.49 (95% UI: 216,263.73–288,715.59) to 630,161.15 (95% UI: 526,089.80–740,423.19). At the same time, the ASDR estimate exhibited an upward trajectory, rising from 5.83 (95% UI: 5.04–6.73) to 7.09 (95% UI: 5.93–6.73) per 100,000 population. To understand alterations in mortality and DALYs rates from 1990 to 2021, the EAPC for ASMR and ASDR for the disease were determined. It was confirmed that the EAPC were 0.80 [95% confidence interval (CI): 0.74–0.85] for ASMR and 0.59 (95% CI: 0.53–0.64) for ASDR, both of which showed an increasing trend, evidenced by the global increased disease burden of TBL due to occupational DEE exposure (Tables 1,2).

Figure 1 illustrates that the global ASMR for TBL linked to occupational DEE exposure initially rose, then experienced a slight decline, before ultimately following a marked upward trajectory over the observed period 1990–2021 (AAPC =0.2%, P<0.05). A downward trend was observed between 2012 and 2016 (AAPC =−4.3%, P>0.05), but the difference was not statistically significant. Subsequently, the ASDR for TBL associated with occupational DEE exposure was analyzed, and a trend analogous to the ASMR was identified (AAPC =4.2%, P<0.05).

Figure 1 Joinpoint regression analysis of the burden of ASMR and ASDR for global occupational exposure to diesel engine exhaust-related TBL. (A) ASMR. (B) ASDR. ASDR, age-standardized DALYs rate; ASMR, age-standardized mortality rate; DALYs, disability-adjusted life years.

Regional and national levels

In 2021, East Asia showed the highest ASMR [0.51 (95% UI: 0.40–0.64) and ASDR (95% UI: 11.53–18.46) per 100,000 population] and ASDR for occupational DEE exposure-related TBL. Conversely, the lowest ASMR and ASDR values [0.04 (95% UI: 0.03–0.05) and 1.22 (95% UI: 0.93–1.55) per 100,000 population, respectively] were recorded in the western part of sub-Saharan Africa (Tables 1,2 and Figure 2).

Figure 2 ASMR and ASDR for global occupational exposure to diesel engine exhaust-related TBL in 204 countries and regions worldwide, 2021. (A) ASMR. (B) ASDR. ASDR, age-standardized DALYs rate; ASMR, age-standardized mortality rate; DALYs, disability-adjusted life years; TBL, tracheal, bronchial, and lung.

Differences in the epidemiologic trajectories of ASMR and ASDR indicators were revealed through a spatiotemporal analysis of occupational diesel exhaust-related TBL across 21 regions from 1990 to 2021. The region of western sub-Saharan Africa displayed the most significant increase in EAPC for ASMR [1.54 (95% CI: 1.46–1.62)] and ASDR [1.46 (95% CI: 1.39–1.54)] (Tables 1,2). In contrast, Eastern Europe revealed the maximum decline in ASMR [−2.59 (95% CI: −2.75–2.42)] (Tables 1,2), concurrent with the predominance of Central Asia in ASDR decline. Taken together, these observations highlight the geographical polarization in the evolution of disease burden.

Distinct geographic clustering of EAPC trajectories has emerged through longitudinal analysis of epidemiologic transitions. Negative ASMR/ASDR trends were predominant in 12 regions, including high-income zones (North America, Asia-Pacific), post-Soviet states (Central Asia, Eastern Europe), and Mediterranean-Near East territories. These trends were inconsistent with positive growth patterns in 10 developing regions spanning tropical Latin America to South/Southeast Asia. Of note, Western Sub-Saharan Africa retained its status as a region of dual extremity, demonstrating both maximal ASMR surge (β=+1.54) and functioning as the sole overlap zone between declining Oceania clusters and ascending tropical disease belts (Figure 2).

Socio-demographic development index (SDI) quintile level

Among the five SDI regions, the middle SDI region recorded the highest number of fatal TBL cases and DALYs related to occupational DEE exposure in 2021, contributing approximately 43% to the global total. The middle SDI region exhibited an ASMR and an ASDR of approximately 0.33 per 100,000 (95% UI: 0.26–0.39) and 9.53 (95% UI: 7.69–11.49), respectively. Between 1990 and 2021, the high SDI region experienced a notable decline in ASMR, reflected by an EAPC of −0.56 (95% CI: −0.62 to −0.50), whereas the remaining four regions showed a gradual increase. For ASDR, the High SDI region was the only one to demonstrate a downward trend, with an EAPC of −0.77 (95% CI: −0.84 to −0.70). There was significant growth in other regions. The trend is most evident in the High SDI region for both ASMR and ASDR (Tables 1,2).

Gender trends

Analysis of gender variations in occupational diesel exhaust exposure-related TBL was conducted, which may be potentially attributed to occupational distinctiveness. The prevalence of occupational diesel exhaust exposure-related TBL in males is nearly twofold higher compared to females. Furthermore, the number of deaths linked to occupational diesel exhaust exposure-related TBL in 2021 among males is estimated at approximately 15,053.85 (95% UI: 11,951.48–18,768.64) with an ASDR of 0.35 (95% UI: 0.28–0.44) per 100,000 population, while the number of female deaths was 6,566.05 (95% UI: 5,244.82–8,267.07) with an ASDR of 0.14 (95% UI: 0.11–0.18) per 100,000 population. Between 1990 and 2021, the estimated EAPC in ASDR was 0.45 (95% CI: 0.38–0.51) for males and 1.84 (95% CI: 1.76–1.92) for females—potentially reflecting the higher representation of female workers in the associated occupations. An analysis was performed on the burden of DALYs for TBL associated with occupational exposure to DEE by sex. The results were comparable to those for death (Tables 1,2 and Figure 3).

Figure 3 Global sex-age trends in occupational exposure to diesel engine exhaust-related TBL deaths and DALYs and ASMR and ASDR. (A) Death numbers and ASMR. (B) DALYs numbers and ASDR. ASDR, age-standardized DALYs rate; ASMR, age-standardized mortality rate; DALYs, disability-adjusted life years; TBL, tracheal, bronchial, and lung; UI, uncertainty interval.

Decomposition analysis

To explore the effect of the three determinants of ageing, epidemiological change and population growth on the burden of TBL deaths associated with occupational DEE exposure, a decomposition analysis was carried out using the available data. These three determinants were found to contribute significantly to the burden of TBL deaths linked to occupational DEE exposure, both at the global level and across SDI quintiles. The findings further demonstrate that, globally, population growth, epidemiological changes, and aging independently increase the burden of TBL deaths linked to occupational DEE exposure, with population growth accounting for 47.91%, epidemiological changes contributing 5.78%, and aging accounting for 46.31% of the total burden. Further analysis identified ageing as the leading contributor across the five SDI regions (Figure 4). While epidemiological changes in the high SDI region contributed to a decrease in disease burden, the effects of ageing and population growth drove an overall increase. However, the aggregate effect of these changes was towards an escalation. The alterations in DALYs were consistent with those in deaths. However, globally, epidemiological change and population growth accounted for 39.8% and 53.11%, respectively, while ageing accounted for only 7.09%.

Figure 4 Decomposition analysis of occupational exposure to diesel engine exhaust-related TBL ASMR and ASDR globally and in the SDI region. (A) ASMR. (B) ASDR. ASDR, age-standardized DALYs rate; ASMR, age-standardized mortality rate; DALYs, disability-adjusted life years; SDI, socio-demographic development index; TBL, tracheal, bronchial, and lung.

Frontier analysis

To develop strategies for developing strategies to improve the burden of TBL associated with occupational diesel exhaust exposure, we performed frontier analyses from 1990 to 2021 based on age-standardized DALYs as well as SDI levels (Figure 5). In Figure 5, the boundary line marks the region with the lowest (best performing) ASDR for a given SDI. A country’s effective distance from this boundary line quantifies the gap between its actual ASDR performance and its potential optimal performance. To determine this distance, we combined SDI with ASDR data for each country. In general, effective distance decreased as SDI increased, indicating an inverse relationship between the two variables. The position of the boundary line stabilizes when the SDI reaches 0.34 or more (Figure 5). The figure also demonstrates the movement of ASDR between 1990 and 2021. The Republic of Palau, Uruguay, and Nauru are among the countries furthest away from the theoretical optimal level, suggesting that there is room for improvement in developing interventions for reducing the burden of disease. Notably, all of the top ten countries ranked by effective distance have SDI values exceeding 0.6, highlighting a significant pattern.

Figure 5 Frontier analysis based on SDI and age-standardized TBL DALY rate in 2021. (A) The effective difference from the frontier for each country or territory by all years (from 1990 to 2021). (B) The effective difference from the frontier for each country or territory by single year (2021 vs. 1990). ASDR, age-standardized DALYs rate; DALYs, disability-adjusted life years; SDI, socio-demographic development index; TBL, tracheal, bronchial, and lung.

The burden of TBL associated with occupational DEE exposure in relation to SDI

To investigate the association of TBL with occupational DEE exposure and SDI, we explored the relationship between ASDR and SDI in this disease. From 1990 to 2021, the ASDR for the burden of TBL associated with occupational DEE exposure increased with the SDI, reaching the peak when the SDI was approximately 0.6, and decreased afterwards. A significant finding is the elevated ASDR ratios in Central Europe and East Asia, which exceed expectations based on their levels of development. Moreover, the ASDR ratio for TBL linked to occupational DEE exposure peaks at an SDI of around 0.8 before declining. It is also observed that Palau, Uruguay, Nauru, and the Northern Mariana Islands have significantly higher disease burdens than the anticipated (Figure 6). Notably, there was a positive correlation between EAPC and ASDR in 2021 (R=0.17, P<0.05). Conversely, SDI and EAPC for ASDR in 2021 exhibited a significant negative correlation (R=−0.462, P<0.001).

Figure 6 The association between SDI and age-standardized DALY rates in 21 global disease burden regions and 204 countries and regions’ TBL. (A) 21 global disease burden regions. (B) 204 countries and regions. DALYs, disability-adjusted life years; SDI, socio-demographic development index; TBL, tracheal, bronchial, and lung.

Prediction analysis

The projection analysis demonstrated that the number of all-age deaths will increase from 20,763 in 2022 to 23,100 in 2035. Furthermore, the ASMR is likely to decrease from 0.434 per 100,000 deaths in 2022 to 0.410 per 100,000 deaths in 2035 (Figure 7).

Figure 7 Temporal trends in global occupational exposure to diesel engine exhaust-related TBL deaths and ASMR from 1990 to 2035. (A) Death numbers. (B) ASMR. ASMR, age-standardized mortality rate; TBL, tracheal, bronchial, and lung.

Discussion

Since 2013, all WHO member states (194 countries) have developed policies to improve the implementation of the WHO Global Action Plan on Noncommunicable Diseases. Therefore, implementation of this plan at the national level may be instrumental in achieving the United Nations Sustainable Development Goals (SDGs) by the year 2030, which include reducing premature mortality from noncommunicable diseases (including lung cancer) by one-third through prevention and treatment (SDG 3.4). Air pollution control is one of the key risk factors prioritized in the formulation of public health policies by WHO member states.

Here, we comprehensively analyzed the global health burden of TBL cancers associated with occupational DEE exposure between 1990 and 2021. Two countervailing trends: a progressive reduction in ASMR accompanied by a significant increase in absolute mortality figures and DALYs. Notably, ASDR exhibited an upward trajectory, suggesting an increase in disease severity improvement despite the mortality rate.

Geospatial analysis revealed marked regional disparities, with populations in lower-SDI territories experiencing faster ASMR growth relative to those in high-SDI counterparts. Comparison across genders demonstrated consistent male predominance, with male mortality burden doubling female rates across all metrics. Using decomposition analysis, population growth and demographic aging were identified as the primary drivers of rising mortality, together accounting for more than 70% of the observed increase. Projections for the year 2035 indicated a continued growth in absolute mortality counts as well as ASMR declines. This epidemiological paradox highlights the need for dual-focused interventions addressing targeting occupational exposure control and demographic transition management.

A study by Zhang et al. found that occupational exposure to DEE ranks as the third largest contributor to the TBL cancer (4). Notably, diesel engines are widely adopted in many industries such as transportation, construction, agriculture, and mining, where they power vehicles, machinery, and tools (16). To obtain acceptable levels of DEE exposure, appropriate policy reforms and practical changes in fleet management are needed. Given the growing awareness of DEE’s health risks, governments and regulatory bodies worldwide have developed stricter emission standards to limit harmful diesel pollutants. The introduction of stringent DEE standards in the U.S., the European Union, and other countries has led to marked reductions in the environmental and health effects of diesel exhaust (17). Despite recent advancements, many industries, especially in developing countries, continue to depend heavily on diesel-powered equipment, where limited regulatory enforcement and restricted access to cleaner technologies hinder progress toward reducing emissions. To address household air pollution and its negative implications on health, WHO has formulated indoor air quality and household fuel guidelines, providing health-based recommendations on cleaner fuels and technologies and appropriate strategies aimed at stimulating their adoption. Through consultations and workshops, it builds capacity at national and regional levels; it also maintains a global household energy database for tracking progress toward SDG 7.1.2 and contributes to assessing the disease burden linked to indoor air pollution from polluting fuels. The WHO has created tools such as the Clean Household Energy Solutions Toolkit (CHEST) to help countries identify stakeholders, design and monitor health-focused energy policies, and estimate the costs and benefits of interventions. Through the Health and Energy Platform of Action (HEPA), WHO encourages collaboration between health and energy sectors to ensure universal access to clean, sustainable household and healthcare energy. Specifically, the WHO coordinates planning and evaluation methods among countries, researchers, and partners, strengthening the establishment of national surveys to examine the health risks and gender effects, thereby providing guidance and decision-support tools to help integrate clean household energy into global health and climate agendas.

Our results show a marked gender disparity in the global occupational carcinogen-associated TBL cancer burden, which is consistent with the changes in established epidemiological patterns (18). Notably, the risk of DEE-related TBL cancer morbidity is higher in men than in their female counterparts. This disproportionate burden is rooted in historical socio-industrial stratification, characterized by male occupational dominance in high-exposure sectors such as mining, construction, and heavy manufacturing. Exposure in these environments is driven by high levels of carcinogenic particulates, notably diesel particles, crystalline silica, and remnants of asbestos. This has enhanced the incidence of TBL cancer among men in many studies. Although women are poorly represented in traditional heavy industries, they may be exposed in certain sectors like healthcare, textiles, or cleaning, where carcinogens such as formaldehyde, disinfectants, or solvents are present (19). However, women in certain industries exhibit elevated risks compared to women in lower-exposure occupations (20). Thus, mitigating this disparity requires the formulation of targeted interventions in male-dominated industries, coupled with stricter enforcement of occupational health and safety standards. Ensuring that policies are inclusive is essential for protecting all workers from the adverse health effects associated with DEE exposure.

Moreover, significant regional differences were recorded in TBL cancer associated with occupational DEE exposure. For instance, East Asia, especially countries like China, has undergone rapid industrial growth, characterized by the widespread use of diesel-powered machinery in manufacturing, transportation, and construction (21). Due to prolonged and intense exposure to diesel exhaust, workers in these sectors face elevated health risks. In East Asia, stricter regulations have only been introduced recently; prior to these policy changes, emission controls were considerably less stringent than in regions like the EU or the U.S. (22). Compared to East Asia, sub-Saharan Africa has a less industrialized economy, with fewer diesel-powered machines and vehicles in widespread use (23). The relatively low occupational DEE exposure observed today is likely to change, as industrialization accelerates across many African nations. Therefore, stricter enforcement of emissions regulations is advocated, such as retrofitting older diesel engines with filters and transitioning to cleaner energy sources. It is also important to create awareness about potential long-term risks of diesel exhaust exposure to preempt future increases in TBL cancer cases as industrialization progresses.

The significant decline in ASMR and ASDR in high SDI regions demonstrates the success of comprehensive regulatory and health measures, while the slow increases in other SDI regions reveal ongoing challenges. To enhance worker safety, high SDI regions have introduced stricter regulations, which mandate the use of personal protective equipment (PPE), improve ventilation systems, and require regular health screenings for high-risk employees. Strict emissions standards such as US 2010, Euro 5, and Euro 6 significantly suppressed diesel particulate matter (DPM) and NOx emissions in high SDI regions (7,22). The geographic redistribution of high-pollution industries under globalized economic frameworks has precipitated parallel migration patterns of occupational TBL carcinogens toward low-income nations (24,25). Disproportionate increases in disease burden have been observed in regions receiving industrial realignments, further widening health disparities and placing unprotected labor forces at elevated risk. To mitigate these transboundary health consequences, it is imperative to implement equitable risk mitigation protocols through multinational governance frameworks.

The global burden of TBL cancer related to occupational DEE is influenced by population growth, epidemiological changes, and aging, exhibiting distinct patterns across regions. As the global population increases, the number of individuals exposed to occupational DEE also rises, especially in industrializing and densely populated regions (26). The increased vulnerability of aging populations to TBL cancer, particularly in high SDI regions, can be attributed to both prolonged lifetime exposure to DEE and age-related declines in physiological resilience (27). As occupational health advancements extend life expectancy, the long-term effects of early-career exposures become more pronounced, suggesting the need for continuous health monitoring, early detection programs, and stricter workplace exposure limits.

For lung cancer, interventions may appear to be absolutely more effective because the pool of potential cases is larger (28). Strategies that prevent and minimize occupational exposure to DEE can reduce the associated risks of lung cancer and other health conditions. To manage and eliminate DEE exposure, the hierarchy of control measures offers a systematic framework (29). While the most effective long-term solution involves eliminating or substituting diesel-powered equipment, engineering and administrative controls serve as essential interim strategies.

Although the decline in ASMR suggests continued progress, the increase in absolute deaths is seen. High SDI regions are expected to witness ASMR improvements, while low- and middle-income countries (LMICs) may struggle with increasing absolute deaths and stagnant or worsening ASMRs due to delayed implementation of controls. However, the decline in ASMR suggests that technological and regulatory advancements are achieving good effects. To sustain this progress and control the rising absolute burden, there is a need for a global, equitable approach to emission controls and occupational health protections.

This study has several limitations that need to be mentioned. Several TBL cancer cases caused by occupational exposure might either be misclassified or not reported as work-related due to a lack of systematic documentation in the GBD database. High-income regions with well-established cancer registries provide more accurate data, unlike their low-income counterparts, creating geographic disparities in reporting. This can skew global estimates toward regions with better reporting systems. Moreover, although a comprehensive approach was adopted in this study, there are some inherent limitations regarding data quality, modeling assumptions, and the complexity of attributing TBL cancer to occupational carcinogens. The use of GBD counterfactual risk model and linear dose-response assumption may weaken regional differences. However, the Poisson distribution in Bayesian predictions does not address the excessive dispersion of mortality data. Notably, 78% of LMICs are based on cross-national exposure assessment models, which leads to missing data for informal industries. The occupational exposure record rate for pathologically diagnosed lung cancer is estimated at 12%, and the smoking-DEE synergistic effect has not been fully controlled, thereby creating an increasing attribution bias. Moreover, cigarette smoking may serve as a significant confounder or effect modifier in the association between environmental DEE exposure and lung cancer risk. Individuals with occupational DEE exposure often exhibit higher smoking prevalence, complicating efforts to distinguish the independent carcinogenic effects of DEE from those attributable to tobacco use. Moreover, smoking may synergistically amplify the harmful effects of DEE, further complicating exposure attribution. Therefore, we recommend that researchers incorporate more refined analytical models that account for these interactions to improve the accuracy of risk estimations. To resolve these limitations, it is imperative to enhance occupational exposure surveillance, improving data harmonization across regions and refining exposure assessment methodologies. Obtaining a more nuanced understanding of these factors will strengthen the available evidence regarding the formulation of targeted interventions and policy measures aimed at reducing the burden of occupational DEE-related TBL cancer.

Conclusions

This study provides quantitative evidence supporting the significant global effects of occupational DEE-associated TBL malignancies, revealing increasing mortality and DALYs trajectory between 1990 and 2021, despite modest reductions in age-standardized epidemiological metrics. The current disease burden shows marked heterogeneity across geographic strata, socioeconomic development tiers, and gender groups, with a higher prevalence among male populations and low-SDI territories. Notably, the increase in populations (population growth) and structural ageing are the key accelerators of disease burden. Furthermore, predictive models predict a continued growth in absolute mortality by the year 2035. These epidemiological patterns call for the initiation of precision public health initiatives that include enhanced regulatory frameworks to mitigate exposure risks, optimized neoplasm surveillance systems, and multinational cooperation to counteract occupational DEE-associated oncological risks. A coordinated global response is crucial to mitigate occupational exposure to DEE and reduce its associated health risks. This will involve enhancing international collaboration to promote the utilization of cleaner technologies, to ensure equitable policy implementation, and resolve occupational health disparities. By prioritizing these measures, the burden of DEE-related TBL cancer worldwide can be alleviated.

Acknowledgments

We appreciate our friends for their invaluable contributions in data collection and for assisting to utilize the JD_GBDR software.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1003/rc

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1003/prf

Funding: This study was supported by the Key Support Project of Regional Innovation and Development Joint Fund of National Natural Science Foundation of China (No. U20A20398), the National Natural Science Foundation of China (Nos. 82104454 and 82374399), the Clinical Medical Research Transformation Project of Anhui Provincial Science and Technology Department (No. 202204295107020045), the Clinical Medical Research Transformation Project of Anhui Province (No. 202304295107020111) and the Natural Science Research Key Project of Anhui Provincial Department of Education (No. KJ2021A0542). The funders of the study did not have any involvement in the design of this study, data collection, analysis, interpretation, or in writing the report.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1003/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. Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2024;74:229-63. [Crossref] [PubMed]
2. Global, regional, and national burden of respiratory tract cancers and associated risk factors from 1990 to 2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Respir Med 2021;9:1030-49. [Crossref] [PubMed]
3. Yuan J, Sun Y, Bu X, et al. Global, regional and national burden of lung cancer and its attributable risk factors in 204 countries and territories, 1990-2019. Eur J Cancer Prev 2022;31:253-9. [Crossref] [PubMed]
4. Zhang Y, Mi M, Zhu N, et al. Global burden of tracheal, bronchus, and lung cancer attributable to occupational carcinogens in 204 countries and territories, from 1990 to 2019: results from the global burden of disease study 2019. Ann Med 2023;55:2206672. [Crossref] [PubMed]
5. Zou B, Wu P, Chen J, et al. The global burden of cancers attributable to occupational factors, 1990-2021. BMC Cancer 2025;25:503. [Crossref] [PubMed]
6. Wichmann HE. Diesel exhaust particles. Inhal Toxicol 2007;19:241-4. [Crossref] [PubMed]
7. Greim H. Diesel engine emissions: are they no longer tolerable? Arch Toxicol 2019;93:2483-90. [Crossref] [PubMed]
8. Latifovic L, Villeneuve PJ, Parent MÉ, et al. Bladder cancer and occupational exposure to diesel and gasoline engine emissions among Canadian men. Cancer Med 2015;4:1948-62. [Crossref] [PubMed]
9. Xu M, Siemiatycki J, Lavoué J, et al. Occupational exposures to leaded and unleaded gasoline engine emissions and lung cancer risk. Occup Environ Med 2018;75:303-9. [Crossref] [PubMed]
10. Garshick E, Laden F, Hart JE, et al. Lung cancer and vehicle exhaust in trucking industry workers. Environ Health Perspect 2008;116:1327-32. [Crossref] [PubMed]
11. Benbrahim-Tallaa L, Baan RA, Grosse Y, et al. Carcinogenicity of diesel-engine and gasoline-engine exhausts and some nitroarenes. Lancet Oncol 2012;13:663-4. [Crossref] [PubMed]
12. 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]
13. Villeneuve PJ, Parent MÉ, Sahni V, et al. Occupational exposure to diesel and gasoline emissions and lung cancer in Canadian men. Environ Res 2011;111:727-35. [Crossref] [PubMed]
14. Ilar A, Plato N, Lewné M, et al. Occupational exposure to diesel motor exhaust and risk of lung cancer by histological subtype: a population-based case-control study in Swedish men. Eur J Epidemiol 2017;32:711-9. [Crossref] [PubMed]
15. Olsson AC, Gustavsson P, Kromhout H, et al. Exposure to diesel motor exhaust and lung cancer risk in a pooled analysis from case-control studies in Europe and Canada. Am J Respir Crit Care Med 2011;183:941-8. [Crossref] [PubMed]
16. Taxell P, Santonen T. Diesel Engine Exhaust: Basis for Occupational Exposure Limit Value. Toxicol Sci 2017;158:243-51. [Crossref] [PubMed]
17. Scheepers PT, Vermeulen RC. Diesel engine exhaust classified as a human lung carcinogen. How will this affect occupational exposures? Occup Environ Med 2012;69:691-3. [Crossref] [PubMed]
18. Scarselli A, Corfiati M, Di Marzio D, et al. Gender differences in occupational exposure to carcinogens among Italian workers. BMC Public Health 2018;18:413. [Crossref] [PubMed]
19. McDiarmid MA, Gucer PW. The "GRAS" status of women's work. J Occup Environ Med 2001;43:665-9. [Crossref] [PubMed]
20. Xu M, Ho V, Siemiatycki J. Role of occupational exposures in lung cancer risk among women. Occup Environ Med 2021;78:98-104. [Crossref] [PubMed]
21. Guo X, Wu H, Chen D, et al. Estimation and prediction of pollutant emissions from agricultural and construction diesel machinery in the Beijing-Tianjin-Hebei (BTH) region, China Environ Pollut 2020;260:113973. [Crossref] [PubMed]
22. Khalek IA, Blanks MG, Merritt PM, et al. Regulated and unregulated emissions from modern 2010 emissions-compliant heavy-duty on-highway diesel engines. J Air Waste Manag Assoc 2015;65:987-1001. [Crossref] [PubMed]
23. Ngo NS, Gatari M, Yan B, et al. Occupational exposure to roadway emissions and inside informal settlements in sub-Saharan Africa: A pilot study in Nairobi, Kenya. Atmos Environ 1994;2015:179-84. [Crossref] [PubMed]
24. Mao Y, Yang D, He J, et al. Epidemiology of Lung Cancer. Surg Oncol Clin N Am 2016;25:439-45. [Crossref] [PubMed]
25. Wang Z, Hu L, Li J, et al. Magnitude, temporal trends and inequality in global burden of tracheal, bronchus and lung cancer: findings from the Global Burden of Disease Study 2017. BMJ Glob Health 2020;5:e002788. [Crossref] [PubMed]
26. Mihankhah T, Saeedi M, Karbassi A. Contamination and cancer risk assessment of polycyclic aromatic hydrocarbons (PAHs) in urban dust from different land-uses in the most populated city of Iran. Ecotoxicol Environ Saf 2020;187:109838. [Crossref] [PubMed]
27. Chen X, Mo S, Yi B. The spatiotemporal dynamics of lung cancer: 30-year trends of epidemiology across 204 countries and territories. BMC Public Health 2022;22:987. [Crossref] [PubMed]
28. Carey RN, Fritschi L, Driscoll TR, et al. Interventions to Reduce Future Cancer Incidence from Diesel Engine Exhaust: What Might Work? Cancer Prev Res (Phila) 2019;12:13-20. [Crossref] [PubMed]
29. Connor TH, McDiarmid MA. Preventing occupational exposures to antineoplastic drugs in health care settings. CA Cancer J Clin 2006;56:354-65. [Crossref] [PubMed]