Global, regional and national burden of tracheal, bronchus, and lung cancer attributable to ambient particulate matter pollution. 1990-2021: An analysis of the Global Burden of Disease Study

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Up to now, far too little attention has been paid to TBL cancer attributable to ambient particulate matter pollution. This study aims to assess the disease burden of TBL cancer attributable to ambient particulate matter pollution in global, regional and national from 1990 to 2021 to update the epidemiology data of this disease. Methods Leveraging data from the Global Burden of Disease (GBD) 2021 study, we analyzed the worldwide burden of TBL cancer resulting from ambient particulate matter pollution using indices including disability-adjusted life years (DALYs), age-standardised rate of DALYs (ASDR). This burden was further segmented based on variables including geographical location, and socio-demographic index (SDI), age and sex. Results The ASDR per 100,000 population of TBL cancer attributable to ambient particulate matter pollution increased by 0.2%[95% UI 0.1 to 0.3] to 79.6[95% UI 49.0 to 111.2] from 1990 to 2021 Globally. Middle-aged and elderly individuals accounted for the majority of the disease burden, with the highest value at the 65–69 years. Most of the disease burden was concentrated in countries with High-middle SDI. There was a positive correlation between ASDR of TBL cancer due to particulate matter pollution and the SDI(ρ = 0.66, p < 0.001). East Asia and Central Europe exhibited higher observed values than the fitted curves, while such as Austraiasia South Asia and Western Sub-Saharan Africa had a lower observed values than the fitted curves. Decomposition analysis showed that population aging and growth were the two major drivers of the increase in DALYs. Conclusions The disease burden of TBL cancer attributable to ambient particulate matter pollution has increased, especially in regions and countries with High-middle SDI. Global regional and national global burden ambient particulate matter pollution trends Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Currently, tracheal, bronchial, and lung (TBL) cancer remains the highest in terms of global incidence and mortality rates among all types of cancers(1). In 2022, tracheal, bronchial, and lung cancer (TBL) ranked as the most prevalent malignancy, accounting for approximately 2,480,675 newly diagnosed cases, which represented 12.4% of all global cancer cases. Furthermore, TBL cancer was the leading cause of cancer mortality, with an estimated 1,817,469 fatalities, constituting 18.7% of total global cancer-related deaths(2, 3). This underscores the substantial burden TBL imposes on global public health(4). Particulate matter pollution primarily encompasses household particulate matter air pollution and ambient Particulate matter air pollution(5). Recently conducted studies have underscored the significance of ambient particulate matter pollution as a substantial contributor to TBL development, in addition to conventional risk factors like smoking(6–8). The data shows that the attributable DALYs due to ambient ambient ozone pollution and particulate matter pollution increased, from 2000 to 2021(9). However, the prevalence and impact of ambient particulate matter pollution vary widely across regions and populations(10). Understanding the latest trends and burdens associated with ambient particulate matter pollution is crucial for reducing the overall burden of TBL cancer . In this study, we aims to assess the changes of TBL cancer attributable to ambient particulate matter pollution by the age-standardized disability-adjusted life year rate (ASDR) of TBL cancer from 1990 to 2021 in 204 countries and territories, stratifying the data by age, sex, region, country, and socio demographic index (SDI) based on the latest data from the GBD 2021 study, offering insightful guidance for medical agencies, policymakers, and the general public. Materials and methods Data collection All the data in this study were obtained for free access from the Global Health Data 2021 ( https://ghdx.healthdata.org/gbd-2021/sources ), which is the largest and most recent assessment of the burden of 371 diseases and injuries and 88 risk factors in 204 countries or territories form 1990 to 2021(11). The burden of disease encompasses the overall socioeconomic and health impacts, leading to poor health, disability, and premature mortality. TBL cancer, succinctly defined as tumors within the trachea, bronchus, or lung, is classified in the International Classification of Diseases (ICD) 10 by codes C33 and C34-C34.92and in the ICD9 by codes 162–162.9, 209.21, V10.1-V10.20, V16.1-V16.2,and V16.4-V16.40(12). The International Classification of Diseases, Revision 10 (ICD-10), is the current diagnostic standard and contains the most exhaustive cause list. We extracted the data of incident patients, prevalent patients, deaths, and DALYs and calculated the incidence, prevalence, mortality, and DALYs rates of TBL caner due to ambient particulate matter pollution from 1990 to 2021. Significant Definitions The socio-demographic index(SDI) is a comprehensive indicator introduced by the Institute for Health Metrics and Evaluation (IHME) in 2015, which can assess the social and economic conditions that affect health outcomes in different development level of countries or regions. SDI is the geometric mean of indices ranging from 0 to 1 of total fertility rate (TFR) for those younger than 25 years old(TFU25), the mean education level for those aged 15 years old and above (EDU15+), and lag-distributed income (LDI) per-capita. In the GBD 2021 study, after computing SDI, the final values were multiplied by 100 to create a scale ranging from 0(the worst) to 100(the best)(12). The value 0 indicates the lowest income and the minimum years of education, and the highest fertility, Conversely, the value 100 indicates the highest income and the most years of education and the lowest fertility. In the GBD 2021, The 204 countries and territories were stratified into five SDI groups: low, low-middle, middle, high-middle, and high SDI. Disability-adjusted life years (DALYs), a standard metric for quantifying burden, represent the total years of healthy life lost from the onset of a disease to death, encompassing both years of life lost (YLLs) and years lived with disability (YLDs), as expressed by the formula(13): DALYs = YLLs + YLDs Age-standardized rates were used to evaluate and compare the incidence, prevalence, deaths, and DALYs rates among nations or regions with distinct age structures and demographic characteristics. The estimated annual percentage change (EAPC) (14)is a widely and effective used indicator which has been extensively utilized in other studies to track the trends of indicators such as prevalence, DALYs and incidence rates during specifc time periods, as expressed by the formula: ln(y) = α + βx + ε, the y is mortality (ASMR) or disability-adjusted life years (ASDR), and x is the calendar year. EAPC and its 95% confidence interval (CI) is calculated as expressed by the formula:100 × (exp (β)-1)(15). If the 95% CI of corresponding EAPC estimation > 0, ASDR was recognized to be in an increasing trend, on the contrary, if 95% CI of corresponding EAPC estimation < 0, ASDR was recognized to be a decreasing trend, but if the 95% CI of corresponding EAPC including 0, ASDR was recognized to be stable. Statistics We utilized decomposition analysis to study the change of DALYs in TBL cancer due to ambient particulate matter pollution, by three population-level drivers: population aging, population growth, and epidemiologic changes (epidemiologic changes is age-and population-standardized rates) to allow the quantification of the effect of each factor on the total change. The decomposition analysis could be investigated the effect of underlying factors on the epidemiology of TBL cancer due to ambient particulate matter pollution from 1990 to 2021(16) Smoothing spline models were fitted to determine the shapes of the correlations between age-standardized rates and the SDI. These models produced estimates of the average age-standardized rates expected for every level of SDI. In this study, all count and rates are presented with 95% uncertainty intervals (UIs) (17) (generated using the 2.5th and 97.5th percentile ordered 1000 draws of the posterior distribution). All the rates are reported per 100,000 population. R software (R core team, version 4.0.2, Vienna, Austria) conducted all data. Results Burden of TBL cancer due to ambient particulate matter pollution As shown in Table 1 , the EAPC ASDR of Global due to ambient particulate matter pollution was 0.2[95% UI 0.1 to 0.3], representing the ASDR per 100,000 population increased by 0.2% to 79.6[95% UI 49.0 to 111.2]. It was worth watching that the EAPC ASDR of male due to ambient particulate matter pollution was − 0.2[95% UI -0.3 to 0.0]. The highest ASDR was in China (190.9 [95% UI, 110.0 to 274.3]), whereas the lowest was in Africa Malawi (2.2 [95% UI,1.1 to 3.7]; Fig. 1 . There was more than 75-fold considerable global variation in ASDR among 204 countries. The trends of ASDR varied considerably among 204 countries, with the largest increase in Equatorial Guinea(EAPC 6.0[95% UI, 5.1 to 6.9]) and the largest decrease in the Estonia( EAPC − 6.4[95% UI,-6.8 to -6.0]). Table 1 The global ASDR of TBL cancer due to particulate matter pollution in 1990 and 2021 and percentage change by sex from 1990 to 2021 Variables ASDR per 100,000 no.in 1990(95%UI) ASDR per 100,000 no.in 2021(95%UI) EAPC in ASDR no.(95%UI) Global 81.4(47.8 to 119.2) 79.6(49.0 to 111.2) 0.2(0.1 to 0.3) Male 135.4(79.9 to 200.3) 116.9(71.4 to 165.5) -0.2(-0.3 to 0.0) Female 33.9(19.9 to 50.2) 46.5(26.9 to 67.1) 1.2(1.1 to 1.3) ASDR, age-standardized DALY rate; no. number; DALYs, disability-adjusted life-years; UI, uncertainty interval; EAPC, estimated annual percentage change; Age and Sex Patterns As shown in Fig. 2 , the distribution of trends was in a similar manner in male, female and both. The ASDR gradually increased with age (from 25 years old to 69 years old), with the highest value at the 65–69 years and followed by a gradual decline with age (from 70 years old to 95 + years old). As shown in Fig. 3 , the temporal patterns of distribution were similar for both and male, the ASDR gradually descended from 1990 to around 1998, slowly increased and reached the peak in around 2014, then declined gradually until a turning point in 2020. For female, the trend was steadily ascending from 1990 to 2014, culminating in its peak in 2014, followed by a gradual decline until it reaches an inflection point in 2020. Disease Burden by Socio demographic Index As shown in Fig. 4 , the temporal trends of ASDR was gradual decline from 1990 to 2021 in the high SDI. There were some small fluctuations at the beginning, but it gradually increase from 2000, peaked around 2014, and then gradually declined again, with an upward trend starting from 2020 in High middle SDI. The trends of Middle SDI was similar to the High middle SDI. The trends were remained stable with slight increase changes in Low-middle SDI and Low SDI. Burden trends associated with the SDI In 2021, there was a positive correlation between ASDR of TBL cancer attributable to particulate matter pollution and the SDI. With the improvement of the economy, the overall burden is on the rise. The ASDR increased with SDI, but decreased substantially at higher SDI levels(Fig. 5 ). Across 21 regions, the burden of TBL cancer due to particulate matter pollution remains the trend of steady rise when the SDI value less than 0.7. When the SDI value was around 0.7, the burden of TBL cancer due to particulate matter pollution reached its peak, therewith most rapid declined in the high SDI. East Asia and Central Europe exhibited higher observed values than the fitted curves, while such as Austraiasia, South Asia and Western Sub-Saharan Africa had a lower observed values than the fitted curves. Decomposition Analysis of Change in DALYs The Table 2 and Fig. 6 show the results of decomposition analysis in DALYS attributable to three population-level determinants, include aging, growth, and epidemiologic change, at the global level and five SDI. Globally, 80% of the DALYs increase was attributed to population growth, followed by population aging (24%) and epidemiologic changes (-4%). The contribution of population growth to the overall DALYs change was the most pronounced in the Low SDI quintile (84%), followed by the High-middle SDI (64%), Low-middle SDI (53%), Middle SDI (42%), and high SDI (42%). The contribution of population aging(24%) was more than the epidemiological Change(-4%) to the overall DALYs change at Global. But the contribution of epidemiological change to the overall DALYs change at Low-middle SDI(40%) and Middle SDI(39%) were significant. whereas epidemiological change played a relatively weak role in the High-middle SDI (4%), and nearly vanished in Global (-4%). The contribution of aging to the overall DALYs change played a significant role at High-middle SDI(32%) and Middle SDI(19%), but played a relatively weak role in Low-middle SDI(7%) and Low SDI(5%). Table 2 Change in the DALY of TBL cancer due to particulate matter pollution decomposed by three population-level determinants: population aging, population growth, and epidemiological change from 1990 to 2021 at the global level and different SDI. Location Overll difference Change due to Population-Level Determinants (% Contribution to the Total Change) Aging Growth Epidemiological Change Global 3619,793.1 895,245.0 (24) 2,890,868.6 (80) -166,320.5 (-4) High SDI -275,836.3 262,848.1 (95) 423,203.7 (153) -961,888.1 (-348) Low-middle SDI 345,726.0 25,654.9 (7) 182,307.1 (53) 137,764.0 (40) Low SDI 40,569.6 -2,263.3 (-5) 34,223.4 (84) 8,609.5 (21) High-middle SDI 1,334,758.4 431,819.1 (32) 853,116.6 (64) 49,822.8 (4) Middle SDI 2,174,499.6 406,554.3 (19) 918,325.6 (42) 849,619.7 (39) Discussion Most of previous GBD analyses have focused on the burden of TBL cancer globally, or in specific regions, while analyses on the TBL cancer burden attributable to specific risk factors are often infrequent. This study will be the first to assess the burden of TBL cancer attributable to particulate matter pollution using data from the post COVID-19 pandemic period. This study used the latest GBD 2021 data to summarize the epidemiological characteristics of the global burden of TBL cancer attributable to particulate matter pollution, included comparisons between different regions, countries, and age groups. The results showed that the absolute burden of TBL cancer attributable to particulate matter pollution had been increasing globally, of which males, middle-aged and elderly individuals were the high-risk groups. Moreover showed a strong association with SDI. The High-middle SDI region, East Asia and Central Europe exhibited higher observed values than the fitted curves. The highest ASDR was in China. China exhibited the highest TBL cancer burden attributable to particulate matter pollution. The burden of TBL cancer due to particulate matter pollution reached its peak, when the SDI value was 0.7, therewith most rapid declined in the high SDI. Decomposition analysis showed that population aging and growth were the two major drivers of the increase in DALYs. The incidence of TBL cancer carries numerous potential risks. The previous body of research has extensively demonstrated that smoking is a prominent risk factor in the development of TBL cancer. In recent years, there has been a general decline in smoking rates and the incidence of smoking-related lung cancer in most countries and territories following the implementation of the World Health Organization (WHO) Framework Convention on Tobacco Control (18, 19) . The attention of numerous articles has shifted towards other potential risk factors. According to the International Agency for Research on Cancer (IARC), outdoor air pollution is classified as a Group 1 human carcinogen and significantly contributes to the burden of diseases, including TBL (20) . Moreover, particulate matter pollution has been identified as a contributing factor in nearly 14.1% of TBL cancer deaths globally. Exposure to air pollution may contribute to the progression of TBL cancer by activating signal transduction pathways, inducing DNA damage, promoting inflammation, altering metabolism, and influencing epigenetic regulation (21) .Multivariable logistic regression analysis revealed a significant association with never-smoking patients with lung cancer and being Asian (OR Asian versus non−Asian = 6.48, 95% CI: 4.42–9.50, p < 0.001), and having greater exposure to air pollution (ORln_PM 2.5 =1.79, 95% CI: 1.10–7.2.90, p = 0.019) (20) . Environmental particulate matter pollution, specifically ambient fine particulate matter (PM 2.5 and PM 10 ), has been identified as a crucial factor contributing to the escalating prevalence of lung cancer, particularly among individuals who do not smoke (22) . The results showed that the absolute burden of TBL cancer attributable to particulate matter pollution had been increasing globally from 1990 to 2021. The ASDR per 100,000 was 81.4(47.8 to 119.2) in 1990 and was 79.6(49.0 to 111.2). From the perspective of these two years, the data for 2021 has experienced a slight decrease, however, with an EAPC in ASDR of 0.2(0.1 to 0.3), the annual average continues to exhibit an upward trend. The data for 2021 has slightly decreased, and the reason for this may be related to the COVID-19 pandemic in 2020, An analysis of the data post-COVID-19 revealed that during the peak of the COVID-19 pandemic in 2020, a sharp decline in the global burden was observed, followed by a sharp rise in 2021. Although this fluctuation was not directly attributed to COVID-19, it partially reflected the impact of the pandemic on global lung cancer care systems, highlighting resource constraints, delays in cancer screening, and disruptions in treatment during the initial phase of the COVID-19 outbreak (23) . The most significant aspect was that the various types of lockdowns implemented in each country were based on the severity of the COVID-19 pandemic, the implementation of various lockdown measures in each country was contingent upon the severity of the COVID-19 pandemic. Notably, there was a significant reduction observed in the concentrations of major air pollutants, particularly particulate matter (PM) and nitrogen dioxide (NO 2 ), across all countries (24) . The disease burden of TBL cancer attributable to particulate matter pollution has significantly increased from 1990 to 2021, albeit with minor fluctuations. The variation in SDI levels across different areas in this study can be attributed to the disparity in pollution levels within these regions. According to a study, approximately 7.3 billion individuals worldwide are exposed to annual average PM 2.5 concentrations that do not meet safety standards, with approximately 80% residing in low- and middle-income countries such as China, India, and Sub-Saharan Africa (25) . In this study, the High-middle SDI region, East Asia and Central Europe exhibited higher observed values than the fitted curves. The highest ASDR was in China. China exhibited the highest TBL cancer burden attributable to particulate matter pollution. In addition, the association between the burden of lung cancer attributable to ambient PM 2.5 and the SDI followed an inverted U-shaped pattern (26) , similar results were obtained in the present study. In this study, the burden of TBL cancer due to particulate matter pollution reached its peak, when the SDI value was 0.7, therewith most rapid declined in the high SDI. At the regional level, regions with a high SDI typically enforce more stringent environmental regulatory policies and maintain robust air quality monitoring systems, in addition to allocating ample resources and employing advanced technologies to mitigate pollutant emissions. These measures include promoting the adoption of clean energy sources and implementing enhanced industrial filtration technologies, which effectively contribute to controlling ambient PM 2.5 levels. The process of globalization and rapid economic development has brought about significant transformations in occupational exposures and environmental factors. This phenomenon is particularly pronounced in regions characterized by middle- to middle-high Socio-demographic Index (SDI) levels. These regions are currently experiencing a period of accelerated industrialization and urbanization, which often results in heightened levels of pollutant emissions (27) . Conclusions This study provided a comprehensive estimate the global TBL cancer burden. The disease burden of TBL cancer attributable to ambient particulate matter pollution has increased, especially in regions and countries with High-middle SDI. The findings of this study can serve as a foundation for the development of relevant policies and the efficient allocation of limited resources. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Funding Not applicable. Author Contribution LJG designed and supervised the study. LJG and GSY collected data and developed the database. ZXM conducted the analysis. LJG, ZXM and GSY were involved in manuscript writing. 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Nature communications. 2023;14(1):6491. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 09 Jan, 2025 Read the published version in BMC Public Health → Version 1 posted Editorial decision: Revision requested 10 Dec, 2024 Reviews received at journal 08 Dec, 2024 Reviewers agreed at journal 28 Nov, 2024 Reviewers agreed at journal 27 Nov, 2024 Reviews received at journal 26 Nov, 2024 Reviewers agreed at journal 19 Nov, 2024 Reviewers invited by journal 18 Nov, 2024 Editor invited by journal 18 Nov, 2024 Editor assigned by journal 17 Nov, 2024 Submission checks completed at journal 13 Nov, 2024 First submitted to journal 11 Nov, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5432219","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":388358565,"identity":"b1d6d66c-deee-41b4-a9a2-bed14a350b26","order_by":0,"name":"Jianguo Lu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYDCCA2DSgoGxGcKXY2NvP0BIC2MDA4MEXIsxH8+ZBOK0wEDiPAkHA7w6+I43P3/wcY9EYnM787OHX9ts0tskGBIYflRsw6lF8swxw8YZzyQSG5vZzI1l29Jy26QbDzD2nLmNU4vBjRzGZp4DIC0MZtKSbYdz22QOJDAzthGlhf0bSEs6m0SCAbFaeMwkP7YdTiCoBeSXmTMOSBgDtZRJM5xLM2wDBvJBfH4BhtiDDx8O2Mhu7D++TfJHmY28fHv7wQc/KnBrgQPDBgYGZh4o5wBh9UAgD8SMP4hSOgpGwSgYBSMNAADE5VsroMCJMwAAAABJRU5ErkJggg==","orcid":"","institution":"The First Affiliated Hospital of Xinxiang Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Jianguo","middleName":"","lastName":"Lu","suffix":""},{"id":388358566,"identity":"9acf8269-3304-44a4-ab2b-edeff2b38ce5","order_by":1,"name":"Xiangmei Zhao","email":"","orcid":"","institution":"The First Affiliated Hospital of Xinxiang Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiangmei","middleName":"","lastName":"Zhao","suffix":""},{"id":388358567,"identity":"67c48b0d-9edf-4a6b-9082-fa8aa5ac9cac","order_by":2,"name":"Shaoyin Gan","email":"","orcid":"","institution":"The First Affiliated Hospital of Xinxiang Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shaoyin","middleName":"","lastName":"Gan","suffix":""}],"badges":[],"createdAt":"2024-11-11 13:08:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5432219/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5432219/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12889-024-21226-w","type":"published","date":"2025-01-09T15:57:20+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":71171460,"identity":"c7dfc2fe-cb38-49fa-85cf-e29a8420fd09","added_by":"auto","created_at":"2024-12-11 19:40:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":293534,"visible":true,"origin":"","legend":"\u003cp\u003eWorldwide burden of TBL cancer due to particulate matter pollution in 2021. The ASDR per 100,000 population of TBL cancer due to particulate matter pollutionin 204 countries and territories in 2021.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5432219/v1/0ef7ea7425176f51042817d8.png"},{"id":71170863,"identity":"3e4fc005-88a1-4c2a-945b-f62e12f054c8","added_by":"auto","created_at":"2024-12-11 19:24:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":122018,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAge and sex patterns of the global burden of TBL cancer due to particulate matter pollution. \u003c/strong\u003eGlobal ASDR and their corresponding 95% uncertainty interval of TBL cancer due to particulate matter pollution by sex and age in 2021.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5432219/v1/a8dc50efc5b46c5afefe69ec.png"},{"id":71170864,"identity":"25aa2a93-4765-49c9-85cf-74655ef12489","added_by":"auto","created_at":"2024-12-11 19:24:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":80698,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSex patterns of the global burden of TBL cancer due to particulate matter pollution. \u003c/strong\u003eGlobal ASDR and their corresponding 95% uncertainty interval of TBL cancer due to particulate matter pollution by sex from 1990 to 2021.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-5432219/v1/fca475e039017232a82ee661.png"},{"id":71170866,"identity":"fa65fad4-a592-42ac-a5dc-ce8a65ef8e4a","added_by":"auto","created_at":"2024-12-11 19:24:59","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":76912,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBurden of TBL cancer due to particulate matter pollution in five socio demographic-index(SDI) quintiles. \u003c/strong\u003eThe temporal trends of global ASDR per 100,000 people from 1990 to 2021 of TBL cancer due to particulate matter pollution in different SDI.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-5432219/v1/e7ad1a7c3b0af8b74bfdabc8.png"},{"id":71170868,"identity":"020ab8d0-7bd6-4526-a210-3a0fd98dea7c","added_by":"auto","created_at":"2024-12-11 19:24:59","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":155517,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe associations between the SDI and ASDR per 100,000 population of TBL cancer due to particulate matter pollution \u0026nbsp;across 21 GBD regions in 2021. \u003c/strong\u003eSDI=Socio-Demographic Index, GBD=Global Burden of Disease ASDR, age-standardized DALY rate.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-5432219/v1/7a9e25cd04422ff510e99707.png"},{"id":71171087,"identity":"89cc78dc-27cf-4515-adda-5659fa57b038","added_by":"auto","created_at":"2024-12-11 19:32:59","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":55860,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChange in DALYs of TBL cancer due to particulate matter pollution decomposed by three population-level determinants: population aging, population growth, and epidemiological change from 1990 to 2021 at the global level and five SDI. \u003c/strong\u003eThe black dots indicate the total value of change attributable to all three components.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-5432219/v1/b32a907ce5405cf6dd221445.png"},{"id":73694737,"identity":"e21edead-e288-44c7-844d-7f89a265e33c","added_by":"auto","created_at":"2025-01-13 16:13:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1857796,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5432219/v1/1e03b2bb-3f1e-4e2a-9923-6942a9f43b02.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Global, regional and national burden of tracheal, bronchus, and lung cancer attributable to ambient particulate matter pollution. 1990-2021: An analysis of the Global Burden of Disease Study","fulltext":[{"header":"Background","content":"\u003cp\u003eCurrently, tracheal, bronchial, and lung (TBL) cancer remains the highest in terms of global incidence and mortality rates among all types of cancers(1). In 2022, tracheal, bronchial, and lung cancer (TBL) ranked as the most prevalent malignancy, accounting for approximately 2,480,675 newly diagnosed cases, which represented 12.4% of all global cancer cases. Furthermore, TBL cancer was the leading cause of cancer mortality, with an estimated 1,817,469 fatalities, constituting 18.7% of total global cancer-related deaths(2, 3). This underscores the substantial burden TBL imposes on global public health(4).\u003c/p\u003e \u003cp\u003eParticulate matter pollution primarily encompasses household particulate matter air pollution and ambient Particulate matter air pollution(5). Recently conducted studies have underscored the significance of ambient particulate matter pollution as a substantial contributor to TBL development, in addition to conventional risk factors like smoking(6\u0026ndash;8). The data shows that the attributable DALYs due to ambient ambient ozone pollution and particulate matter pollution increased, from 2000 to 2021(9). However, the prevalence and impact of ambient particulate matter pollution vary widely across regions and populations(10). Understanding the latest trends and burdens associated with ambient particulate matter pollution is crucial for reducing the overall burden of TBL cancer .\u003c/p\u003e \u003cp\u003eIn this study, we aims to assess the changes of TBL cancer attributable to ambient particulate matter pollution by the age-standardized disability-adjusted life year rate (ASDR) of TBL cancer from 1990 to 2021 in 204 countries and territories, stratifying the data by age, sex, region, country, and socio demographic index (SDI) based on the latest data from the GBD 2021 study, offering insightful guidance for medical agencies, policymakers, and the general public.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eAll the data in this study were obtained for free access from the Global Health Data 2021 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ghdx.healthdata.org/gbd-2021/sources\u003c/span\u003e\u003cspan address=\"https://ghdx.healthdata.org/gbd-2021/sources\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), which is the largest and most recent assessment of the burden of 371 diseases and injuries and 88 risk factors in 204 countries or territories form 1990 to 2021(11). The burden of disease encompasses the overall socioeconomic and health impacts, leading to poor health, disability, and premature mortality. TBL cancer, succinctly defined as tumors within the trachea, bronchus, or lung, is classified in the International Classification of Diseases (ICD) 10 by codes C33 and C34-C34.92and in the ICD9 by codes 162\u0026ndash;162.9, 209.21, V10.1-V10.20, V16.1-V16.2,and V16.4-V16.40(12). The International Classification of Diseases, Revision 10 (ICD-10), is the current diagnostic standard and contains the most exhaustive cause\u003c/p\u003e \u003cp\u003elist. We extracted the data of incident patients, prevalent patients, deaths, and DALYs and calculated the incidence, prevalence, mortality, and DALYs rates of TBL caner due to ambient particulate matter pollution from 1990 to 2021.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSignificant Definitions\u003c/h3\u003e\n\u003cp\u003eThe socio-demographic index(SDI) is a comprehensive indicator introduced by the Institute for Health Metrics and Evaluation (IHME) in 2015, which can assess the social and economic conditions that affect health outcomes in different development level of countries or regions. SDI is the geometric mean of indices ranging from 0 to 1 of total fertility rate (TFR) for those younger than 25 years old(TFU25), the mean education level for those aged 15 years old and above (EDU15+), and lag-distributed income (LDI) per-capita. In the GBD 2021 study, after computing SDI, the final values were multiplied by 100 to create a scale ranging from 0(the worst) to 100(the best)(12). The value 0 indicates the lowest income and the minimum years of education, and the highest fertility, Conversely, the value 100 indicates the highest income and the most years of education and the lowest fertility. In the GBD 2021, The 204 countries and territories were stratified into five SDI groups: low, low-middle, middle, high-middle, and high SDI.\u003c/p\u003e \u003cp\u003eDisability-adjusted life years (DALYs), a standard metric for quantifying burden, represent the total years of healthy life lost from the onset of a disease to death, encompassing both years of life lost (YLLs) and years lived with disability (YLDs), as expressed by the formula(13):\u003c/p\u003e \u003cp\u003eDALYs\u0026thinsp;=\u0026thinsp;YLLs\u0026thinsp;+\u0026thinsp;YLDs\u003c/p\u003e \u003cp\u003eAge-standardized rates were used to evaluate and compare the incidence, prevalence, deaths, and\u003c/p\u003e \u003cp\u003eDALYs rates among nations or regions with distinct age structures and demographic characteristics.\u003c/p\u003e \u003cp\u003eThe estimated annual percentage change (EAPC) (14)is a widely and effective used indicator which has been extensively utilized in other studies to track the trends of indicators such as prevalence, DALYs and incidence rates during specifc time periods, as expressed by the formula: ln(y) = α\u0026thinsp;+\u0026thinsp;βx\u0026thinsp;+\u0026thinsp;ε, the y is mortality (ASMR) or disability-adjusted life years (ASDR), and x is the calendar year. EAPC and its 95% confidence interval (CI) is calculated as expressed by the formula:100 \u0026times; (exp (β)-1)(15). If the 95% CI of corresponding EAPC estimation\u0026thinsp;\u0026gt;\u0026thinsp;0, ASDR was recognized to be in an increasing trend, on the contrary, if 95% CI of corresponding EAPC estimation\u0026thinsp;\u0026lt;\u0026thinsp;0, ASDR was recognized to be a decreasing trend, but if the 95% CI of corresponding EAPC including 0, ASDR was recognized to be stable.\u003c/p\u003e\n\u003ch3\u003eStatistics\u003c/h3\u003e\n\u003cp\u003eWe utilized decomposition analysis to study the change of DALYs in TBL cancer due to ambient particulate matter pollution, by three population-level drivers: population aging, population growth, and epidemiologic changes (epidemiologic changes is age-and population-standardized rates) to allow the quantification of the effect of each factor on the total change. The decomposition analysis could be investigated the effect of underlying factors on the epidemiology of TBL cancer due to ambient particulate matter pollution from 1990 to 2021(16)\u003c/p\u003e \u003cp\u003eSmoothing spline models were fitted to determine the shapes of the correlations between age-standardized rates and the SDI. These models produced estimates of the average age-standardized rates expected for every level of SDI.\u003c/p\u003e \u003cp\u003eIn this study, all count and rates are presented with 95% uncertainty intervals (UIs) (17) (generated using the 2.5th and 97.5th percentile ordered 1000 draws of the posterior distribution). All the rates are reported per 100,000 population. R software (R core team, version 4.0.2, Vienna, Austria) conducted all data.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eBurden of TBL cancer due to ambient particulate matter pollution\u003c/h2\u003e \u003cp\u003eAs shown in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the EAPC ASDR of Global due to ambient particulate matter pollution was 0.2[95% UI 0.1 to 0.3], representing the ASDR per 100,000 population increased by 0.2% to 79.6[95% UI 49.0 to 111.2]. It was worth watching that the EAPC ASDR of male due to ambient particulate matter pollution was \u0026minus;\u0026thinsp;0.2[95% UI -0.3 to 0.0].\u003c/p\u003e \u003cp\u003eThe highest ASDR was in China (190.9 [95% UI, 110.0 to 274.3]), whereas the lowest was in Africa Malawi (2.2 [95% UI,1.1 to 3.7]; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. There was more than 75-fold considerable global variation in ASDR among 204 countries. The trends of ASDR varied considerably among 204 countries, with the largest increase in Equatorial Guinea(EAPC 6.0[95% UI, 5.1 to 6.9]) and the largest decrease in the Estonia( EAPC \u0026minus;\u0026thinsp;6.4[95% UI,-6.8 to -6.0]).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe global ASDR of TBL cancer due to particulate matter pollution in 1990 and 2021 and percentage change by sex from 1990 to 2021\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eASDR per 100,000 no.in 1990(95%UI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eASDR per 100,000 no.in 2021(95%UI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEAPC in ASDR no.(95%UI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81.4(47.8 to 119.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.6(49.0 to 111.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2(0.1 to 0.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135.4(79.9 to 200.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116.9(71.4 to 165.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.2(-0.3 to 0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.9(19.9 to 50.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.5(26.9 to 67.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.2(1.1 to 1.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eASDR, age-standardized DALY rate; no. number; DALYs, disability-adjusted life-years; UI, uncertainty interval; EAPC, estimated annual percentage change;\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAge and Sex Patterns\u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the distribution of trends was in a similar manner in male, female and both. The ASDR gradually increased with age (from 25 years old to 69 years old), with the highest value at the 65\u0026ndash;69 years and followed by a gradual decline with age (from 70 years old to 95\u0026thinsp;+\u0026thinsp;years old). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the temporal patterns of distribution were similar for both and male, the ASDR gradually descended from 1990 to around 1998, slowly increased and reached the peak in around 2014, then declined gradually until a turning point in 2020. For female, the trend was steadily ascending from 1990 to 2014, culminating in its peak in 2014, followed by a gradual decline until it reaches an inflection point in 2020.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDisease Burden by Socio demographic Index\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the temporal trends of ASDR was gradual decline from 1990 to 2021 in the high SDI. There were some small fluctuations at the beginning, but it gradually increase from 2000, peaked around 2014, and then gradually declined again, with an upward trend starting from 2020 in High middle SDI. The trends of Middle SDI was similar to the High middle SDI. The trends were remained stable with slight increase changes in Low-middle SDI and Low SDI.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBurden trends associated with the SDI\u003c/h3\u003e\n\u003cp\u003eIn 2021, there was a positive correlation between ASDR of TBL cancer attributable to particulate matter pollution and the SDI. With the improvement of the economy, the overall burden is on the rise. The ASDR increased with SDI, but decreased substantially at higher SDI levels(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Across 21 regions, the burden of TBL cancer due to particulate matter pollution remains the trend of steady rise when the SDI value less than 0.7. When the SDI value was around 0.7, the burden of TBL cancer due to particulate matter pollution reached its peak, therewith most rapid declined in the high SDI. East Asia and Central Europe exhibited higher observed values than the fitted curves, while such as Austraiasia, South Asia and Western Sub-Saharan Africa had a lower observed values than the fitted curves.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eDecomposition Analysis of Change in DALYs\u003c/h3\u003e\n\u003cp\u003eThe Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e show the results of decomposition analysis in DALYS attributable to three population-level determinants, include aging, growth, and epidemiologic change, at the global level and five SDI. Globally, 80% of the DALYs increase was attributed to population growth, followed by population aging (24%) and epidemiologic changes (-4%). The contribution of population growth to the overall DALYs change was the most pronounced in the Low SDI quintile (84%), followed by the High-middle SDI (64%), Low-middle SDI (53%), Middle SDI (42%), and high SDI (42%). The contribution of population aging(24%) was more than the epidemiological Change(-4%) to the overall DALYs change at Global. But the contribution of epidemiological change to the overall DALYs change at Low-middle SDI(40%) and Middle SDI(39%) were significant. whereas epidemiological change played a relatively weak role in the High-middle SDI (4%), and nearly vanished in Global (-4%). The contribution of aging to the overall DALYs change played a significant role at High-middle SDI(32%) and Middle SDI(19%), but played a relatively weak role in Low-middle SDI(7%) and Low SDI(5%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChange in the DALY of TBL cancer due to particulate matter pollution decomposed by three population-level determinants: population aging, population growth, and epidemiological change from 1990 to 2021 at the global level and different SDI.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverll difference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eChange due to Population-Level Determinants\u003c/p\u003e \u003cp\u003e(% Contribution to the Total Change)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAging\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGrowth\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eEpidemiological Change\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3619,793.1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e895,245.0 (24)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,890,868.6 (80)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e-166,320.5 (-4)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHigh SDI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-275,836.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e262,848.1 (95)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e423,203.7 (153)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-961,888.1 (-348)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLow-middle SDI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e345,726.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e25,654.9 (7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e182,307.1 (53)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003e137,764.0 (40)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLow SDI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e40,569.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-2,263.3 (-5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e34,223.4 (84)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003e8,609.5 (21)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHigh-middle SDI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1,334,758.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e431,819.1 (32)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e853,116.6 (64)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003e49,822.8 (4)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMiddle SDI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2,174,499.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e406,554.3 (19)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e918,325.6 (42)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003e849,619.7 (39)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMost of previous GBD analyses have focused on the burden of TBL cancer globally, or in specific regions, while analyses on the TBL cancer burden attributable to specific risk factors are often infrequent. This study will be the first to assess the burden of TBL cancer attributable to particulate matter pollution using data from the post COVID-19 pandemic period. This study used the latest GBD 2021 data to summarize the epidemiological characteristics of the global burden of TBL cancer attributable to particulate matter pollution, included comparisons between different regions, countries, and age groups. The results showed that the absolute burden of TBL cancer attributable to particulate matter pollution had been increasing globally, of which males, middle-aged and elderly individuals were the high-risk groups. Moreover showed a strong association with SDI. The High-middle SDI region, East Asia and Central Europe exhibited higher observed values than the fitted curves. The highest ASDR was in China. China exhibited the highest TBL cancer burden attributable to particulate matter pollution. The burden of TBL cancer due to particulate matter pollution reached its peak, when the SDI value was 0.7, therewith most rapid declined in the high SDI. Decomposition analysis showed that population aging and growth were the two major drivers of the increase in DALYs.\u003c/p\u003e \u003cp\u003eThe incidence of TBL cancer carries numerous potential risks. The previous body of research has extensively demonstrated that smoking is a prominent risk factor in the development of TBL cancer. In recent years, there has been a general decline in smoking rates and the incidence of smoking-related lung cancer in most countries and territories following the implementation of the World Health Organization (WHO) Framework Convention on Tobacco Control\u003csup\u003e(18, 19)\u003c/sup\u003e. The attention of numerous articles has shifted towards other potential risk factors. According to the International Agency for Research on Cancer (IARC), outdoor air pollution is classified as a Group 1 human carcinogen and significantly contributes to the burden of diseases, including TBL\u003csup\u003e(20)\u003c/sup\u003e. Moreover, particulate matter pollution has been identified as a contributing factor in nearly 14.1% of TBL cancer deaths globally. Exposure to air pollution may contribute to the progression of TBL cancer by activating signal transduction pathways, inducing DNA damage, promoting inflammation, altering metabolism, and influencing epigenetic regulation\u003csup\u003e(21)\u003c/sup\u003e.Multivariable logistic regression analysis revealed a significant association with never-smoking patients with lung cancer and being Asian (OR\u003csub\u003eAsian versus non\u0026minus;Asian\u003c/sub\u003e = 6.48, 95% CI: 4.42\u0026ndash;9.50, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and having greater exposure to air pollution (ORln_PM\u003csub\u003e2.5\u003c/sub\u003e=1.79, 95% CI: 1.10\u0026ndash;7.2.90, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.019)\u003csup\u003e(20)\u003c/sup\u003e. Environmental particulate matter pollution, specifically ambient fine particulate matter (PM\u003csub\u003e2.5\u003c/sub\u003e and PM\u003csub\u003e10\u003c/sub\u003e), has been identified as a crucial factor contributing to the escalating prevalence of lung cancer, particularly among individuals who do not smoke\u003csup\u003e(22)\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe results showed that the absolute burden of TBL cancer attributable to particulate matter pollution had been increasing globally from 1990 to 2021. The ASDR per 100,000 was 81.4(47.8 to 119.2) in 1990 and was 79.6(49.0 to 111.2). From the perspective of these two years, the data for 2021 has experienced a slight decrease, however, with an EAPC in ASDR of 0.2(0.1 to 0.3), the annual average continues to exhibit an upward trend. The data for 2021 has slightly decreased, and the reason for this may be related to the COVID-19 pandemic in 2020, An analysis of the data post-COVID-19 revealed that during the peak of the COVID-19 pandemic in 2020, a sharp decline in the global burden was observed, followed by a sharp rise in 2021. Although this fluctuation was not directly attributed to COVID-19, it partially reflected the impact of the pandemic on global lung cancer care systems, highlighting resource constraints, delays in cancer screening, and disruptions in treatment during the initial phase of the COVID-19 outbreak\u003csup\u003e(23)\u003c/sup\u003e. The most significant aspect was that the various types of lockdowns implemented in each country were based on the severity of the COVID-19 pandemic, the implementation of various lockdown measures in each country was contingent upon the severity of the COVID-19 pandemic. Notably, there was a significant reduction observed in the concentrations of major air pollutants, particularly particulate matter (PM) and nitrogen dioxide (NO\u003csub\u003e2\u003c/sub\u003e), across all countries\u003csup\u003e(24)\u003c/sup\u003e. The disease burden of TBL cancer attributable to particulate matter pollution has significantly increased from 1990 to 2021, albeit with minor fluctuations.\u003c/p\u003e \u003cp\u003eThe variation in SDI levels across different areas in this study can be attributed to the disparity in pollution levels within these regions. According to a study, approximately 7.3\u0026nbsp;billion individuals worldwide are exposed to annual average PM\u003csub\u003e2.5\u003c/sub\u003e concentrations that do not meet safety standards, with approximately 80% residing in low- and middle-income countries such as China, India, and Sub-Saharan Africa\u003csup\u003e(25)\u003c/sup\u003e. In this study, the High-middle SDI region, East Asia and Central Europe exhibited higher observed values than the fitted curves. The highest ASDR was in China. China exhibited the highest TBL cancer burden attributable to particulate matter pollution. In addition, the association between the burden of lung cancer attributable to ambient PM\u003csub\u003e2.5\u003c/sub\u003e and the SDI followed an inverted U-shaped pattern\u003csup\u003e(26)\u003c/sup\u003e, similar results were obtained in the present study. In this study, the burden of TBL cancer due to particulate matter pollution reached its peak, when the SDI value was 0.7, therewith most rapid declined in the high SDI. At the regional level, regions with a high SDI typically enforce more stringent environmental regulatory policies and maintain robust air quality monitoring systems, in addition to allocating ample resources and employing advanced technologies to mitigate pollutant emissions. These measures include promoting the adoption of clean energy sources and implementing enhanced industrial filtration technologies, which effectively contribute to controlling ambient PM\u003csub\u003e2.5\u003c/sub\u003e levels. The process of globalization and rapid economic development has brought about significant transformations in occupational exposures and environmental factors. This phenomenon is particularly pronounced in regions characterized by middle- to middle-high Socio-demographic Index (SDI) levels. These regions are currently experiencing a period of accelerated industrialization and urbanization, which often results in heightened levels of pollutant emissions\u003csup\u003e(27)\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study provided a comprehensive estimate the global TBL cancer burden. The disease burden of TBL cancer attributable to ambient particulate matter pollution has increased, especially in regions and countries with High-middle SDI. The findings of this study can serve as a foundation for the development of relevant policies and the efficient allocation of limited resources.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eLJG designed and supervised the study. LJG and GSY collected data and developed the database. ZXM conducted the analysis. LJG, ZXM and GSY were involved in manuscript writing. All authors reviewed and approved the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eWe thank Zhao Xiangmei for her work in the GBD database. Her excellent sharing of GBD database analysis procedure and other public database, makes it easier for us to explore the GBD database.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eZhao J, Ren R, Beeraka NM, Pa M, Xue N, Lu P, et al. Correlation of time trends of air pollutants, greenspaces and tracheal, bronchus and lung cancer incidence and mortality among the adults in United States. Frontiers in oncology. 2024;14:1398679.\u003c/li\u003e\n\u003cli\u003eZhong R, Cai X, Li J, Chen P, Wang R, Li X, et al. 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Nature communications. 2023;14(1):6491.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Global, regional and national, global burden, ambient particulate matter pollution, trends","lastPublishedDoi":"10.21203/rs.3.rs-5432219/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5432219/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe ambient particulate matter pollution may play a critical role in the initiation and development of tracheal, bronchus, and lung (TBL) cancer. Up to now, far too little attention has been paid to TBL cancer attributable to ambient particulate matter pollution. This study aims to assess the disease burden of TBL cancer attributable to ambient particulate matter pollution in global, regional and national from 1990 to 2021 to update the epidemiology data of this disease.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eLeveraging data from the Global Burden of Disease (GBD) 2021 study, we analyzed the worldwide burden of TBL cancer resulting from ambient particulate matter pollution using indices including disability-adjusted life years (DALYs), age-standardised rate of DALYs (ASDR). This burden was further segmented based on variables including geographical location, and socio-demographic index (SDI), age and sex.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe ASDR per 100,000 population of TBL cancer attributable to ambient particulate matter pollution increased by 0.2%[95% UI 0.1 to 0.3] to 79.6[95% UI 49.0 to 111.2] from 1990 to 2021 Globally. Middle-aged and elderly individuals accounted for the majority of the disease burden, with the highest value at the 65\u0026ndash;69 years. Most of the disease burden was concentrated in countries with High-middle SDI. There was a positive correlation between ASDR of TBL cancer due to particulate matter pollution and the SDI(ρ\u0026thinsp;=\u0026thinsp;0.66, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). East Asia and Central Europe exhibited higher observed values than the fitted curves, while such as Austraiasia South Asia and Western Sub-Saharan Africa had a lower observed values than the fitted curves. Decomposition analysis showed that population aging and growth were the two major drivers of the increase in DALYs.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe disease burden of TBL cancer attributable to ambient particulate matter pollution has increased, especially in regions and countries with High-middle SDI.\u003c/p\u003e","manuscriptTitle":"Global, regional and national burden of tracheal, bronchus, and lung cancer attributable to ambient particulate matter pollution. 1990-2021: An analysis of the Global Burden of Disease Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-11 19:24:55","doi":"10.21203/rs.3.rs-5432219/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-12-10T05:28:18+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-08T20:19:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"186851105845194945877127875124160708690","date":"2024-11-28T17:05:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"147968068489560806675643597767241067179","date":"2024-11-27T05:01:21+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-26T06:03:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"72965841971403289711804623206653570451","date":"2024-11-19T05:01:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-11-19T04:59:16+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-11-18T06:30:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-11-18T02:58:12+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-11-14T04:15:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2024-11-11T12:52:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"05f68b59-b95e-4a6e-9745-7beb926d0c01","owner":[],"postedDate":"December 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-01-13T16:08:52+00:00","versionOfRecord":{"articleIdentity":"rs-5432219","link":"https://doi.org/10.1186/s12889-024-21226-w","journal":{"identity":"bmc-public-health","isVorOnly":false,"title":"BMC Public Health"},"publishedOn":"2025-01-09 15:57:20","publishedOnDateReadable":"January 9th, 2025"},"versionCreatedAt":"2024-12-11 19:24:55","video":"","vorDoi":"10.1186/s12889-024-21226-w","vorDoiUrl":"https://doi.org/10.1186/s12889-024-21226-w","workflowStages":[]},"version":"v1","identity":"rs-5432219","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5432219","identity":"rs-5432219","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}