Biomass Burning, PM2.5 Peaks, and Trends in Lung Adenocarcinoma Incidence: An Ecological Study in São Paulo State, Brazil

Biomass Burning, PM2.5 Peaks, and Trends in Lung Adenocarcinoma Incidence: An Ecological Study in São Paulo State, Brazil | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Biomass Burning, PM2.5 Peaks, and Trends in Lung Adenocarcinoma Incidence: An Ecological Study in São Paulo State, Brazil Saulo Silva, Henrique Larssen, Leandro Colli This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8681500/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Lung adenocarcinoma incidence has increased globally despite declining tobacco exposure, raising questions about non–tobacco-related contributors. The role of fine particulate matter (PM2.5) peaks related to biomass burning in shaping population-level lung cancer patterns remains unexplored. A population-based ecological analysis was conducted across the Regional Health Divisions of São Paulo State, Brazil, from 2000 to 2023. Histologically confirmed lung cancer cases were obtained from the state cancer registry. Temporal trends in the adenocarcinoma-to-total lung cancer ratio (ATR) were evaluated alongside annual mean and maximum PM2.5 concentrations and wildfire counts derived from satellite data. Among 51,580 lung cancer cases, adenocarcinoma accounted for 36%. Regions with a significant increase in ATR demonstrated annual increases ranging from 0.39% to 0.72%. With the exception of the São Paulo metropolitan area, which showed high mean PM2.5 levels despite low wildfire activity, all other regions with increasing ATR exhibited substantially higher wildfire occurrence (311 vs. 207 annual hotspots; p = 0.04), which strongly correlated with PM2.5 peaks (ρ = 0.928, p = 0.007). Periods of elevated PM2.5 peaks consistently coincided with increased wildfire activity. These findings suggest that biomass-burning–related PM2.5 peaks may be relevant to population-level patterns of lung cancer epidemiology. Lung adenocarcinoma PM2.5 Air pollution Environmental exposure Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Lung cancer remains one of the most commonly diagnosed cancers and the leading cause of cancer-related mortality worldwide, accounting for over 1.8 million deaths annually 1 . Despite a global decline in smoking rates, lung cancer incidence—particularly the adenocarcinoma subtype—has not followed the same downward trend. Indeed, lung adenocarcinoma has emerged as the predominant histological subtype, with a notable increase among never-smokers 2 . This epidemiological shift has sparked growing interest in alternative etiological factors, particularly environmental exposures such as fine particulate matter with a diameter ≤ 2.5 µm (PM2.5) 3 . PM2.5, classified as a Group 1 carcinogen by the International Agency for Research on Cancer (IARC) 4 , originates largely from combustion processes, including industrial emissions, vehicular traffic, fossil fuel burning, and increasingly, biomass combustion 4 . While long-term exposure to PM2.5 from urban-industrial sources has been linked to lung adenocarcinoma 5 , episodic exposures from biomass burning—common in agricultural regions and areas prone to wildfires—may carry underrecognized carcinogenic risks. Such acute yet recurrent exposures can generate peaks of PM2.5 that superimpose on chronic pollution and potentially exacerbate lung carcinogenesis. With climate change intensifying the frequency and severity of biomass fires, this source of PM2.5 is becoming increasingly relevant to public health 6 , 7 . Early evidence linking PM2.5 with lung adenocarcinoma has largely emerged from analyses of large metropolitan areas in East Asia, particularly among never-smokers, often highlighting associations with adenocarcinoma harboring EGFR mutations 9 . However, less is known about lung adenocarcinoma trends in in large metropolitan areas outside of East Asia and in the surrounding rural areas, particularly in low- and middle income (LMIC) settings. The potential carcinogenic impact of such PM2.5 peaks remains underexplored, despite their intensity and recurrence. This ecological study aims to assess the association between lung adenocarcinoma incidence, PM2.5 levels, and biomass burning activity across São Paulo State, Brazil, a region characterized both by a major metropolitan area and by extensive rural area with environmental pollution from deforestation, sugarcane harvesting, and climate-related wildfires. By integrating population-based cancer registry data with satellite-derived environmental metrics of air pollution and wildfire activity, we seek to clarify the role of biomass burning in lung cancer risk and address a critical knowledge gap in a middle-income setting. 2. Material and Methods 2.1 Study Design and Population This is a retrospective ecological analysis conducted across the 17 Regional Health Divisions (RHDs) of São Paulo State, Brazil. RHDs are state administrative areas for better reference and treatment care for population. Each RHD has their own health structure for diagnosis and treatment of patients of all diseases, including cancer. For analytical purposes, RHD 4 was combined with RHD 1 due to its small geographic area and proximity, resulting in 16 effective regions. The study period spanned from January 2000 to December 2023. All histologically confirmed primary lung cancer cases were included, as reported in the publicly available at Fundação Oncocentro de São Paulo (Hospital Cancer Registry of São Paulo State, FOSP, https://fosp.saude.sp.gov.br/ ). The state registry contains information on primary tumor site, histological subtype, age at diagnosis, sex, educational level, clinical and/or pathological stage (grouped as I–II vs III–IV), municipality of residence, and vital status. Each RHD contributes monthly data to the centralized database, ensuring systematic and continuous collection of cancer cases treated within the region. Patients were assigned to the RHD corresponding to their municipality of residence, consistent with the standard referral structure in São Paulo. To minimize biases due to temporal fluctuations in case reporting, we calculated the annual adenocarcinoma-to-total histology ratio (ATR) per RHD. The primary outcome was temporal trends in the adenocarcinoma-to-total lung cancer ratio (ATR) across RHDs. Secondary analyses included demographic and clinical variables to evaluate whether changes in adenocarcinoma prevalence were accompanied by shifts in patient characteristics. Environmental exposures, including wildfire activity and PM2.5 concentrations (both mean and peak levels), were assessed to explore potential associations with ATR trends. The use of aggregated RHD-level data allowed investigation of regional patterns while preserving patient confidentiality. 2.2 Environmental Exposure Data Air pollution data were obtained from publicly available sources. Annual mean and maximum PM2.5 concentrations were derived from representative monitoring stations in major cities within each RHD, as reported by the Companhia Ambiental do Estado de São Paulo (Environmental Agency of the State of São Paulo, CETESB, http://www.cetesb.sp.gov.br ). Stations provide hourly measurements, typically aggregated monthly, which were then averaged to obtain annual values. Mean annual PM2.5 values capture chronic exposure, whereas maximum annual values represent peak pollution levels. Wildfire activity was quantified using the Instituto Nacional de Pesquisas Espaciais (National Institute for Space Research, INPE, http://queimadas.dgi.inpe.br ) satellite fire hotspot product. Fires are detected by multiple satellites including NOAA-18, NOAA-19, NOAA-20, METOP-B, TERRA, AQUA, and Suomi-NPP, with spatial resolution ranging from 375 m × 375 m to 5 km × 4 km depending on the satellite. Each hotspot corresponds to a fire detection at a pixel; multiple hotspots may represent a single fire event. For each RHD, the mean annual number of hotspots was calculated over the study period. This approach allowed integration of environmental exposures with regional lung cancer trends and facilitated evaluation of potential associations between wildfire activity, PM2.5 peaks, and adenocarcinoma incidence. 2.3 3Statistical Analysis Continuous variables are reported as means ± standard deviation (SD) or medians with interquartile ranges (IQR), as appropriate, and categorical variables as counts and percentages. Temporal trends in the ATR were assessed using linear regression models and correlation analyses with time (Pearson or Spearman, depending on normality). In addition, average annual percent change (AAPC) was calculated for each RHD to quantify the magnitude of long-term trends and provide a confirmatory measure alongside regression slopes. Correlations between wildfire hotspot frequency, PM2.5 peak concentrations, and ATR trends were evaluated using Pearson or Spearman correlation. PM2.5 peaks were defined as the annual maximum daily PM2.5 value recorded within each monitoring station. Two complementary analyses were performed for PM2.5 peaks: one considering all individual annual data points across RHDs, and another considering the maximum PM2.5 value per RHD to highlight extreme exposure events. Comparisons between RHDs with and without a significant increase in ATR were performed using independent t-tests or non-parametric Mann–Whitney tests, as appropriate. A p-value < 0.05 was considered statistically significant, while p-values between 0.05 and 0.10 were interpreted as trend-level effects. All analyses were conducted in R (version 4.3.1). 3. Results 3.1 Lung Cancer Trends Across São Paulo State A total of 51,580 cases of lung cancer were identified during the study period across the 16 geographic regions. Among these, adenocarcinoma accounted for 36% of cases, representing the most frequent histological subtype. Temporal trend analyses in the ATR from 2000 to 2023 demonstrated varying patterns across regions (Fig. 1 A), with significant linear trend-level effect increases observed in RHDs 1, 2, 6, 7, 8, 14, and 15, underscoring an upward trend. Correlation analyses supported these observations, with coefficients ranging from moderate to very strong (r = 0.441–0.823, p < 0.05), and estimates of average annual percent change (AAPC) demonstrating annual increases in ATR ranging from 0.39% to 0.72% across these regions (Supplementary Tables 1 and 2). Taken together, these seven RHDs (1, 2, 6, 7, 8, 14, and 15) were classified as regions with an increasing ATR. Temporal trends in sex distribution revealed a pronounced increase in the proportion of female lung cancer cases across São Paulo State (Fig. 1 B), with thirteen of the 16 RHDs demonstrating positive annual increases in female proportion and moderate to strong correlations over time (r = 0.568–0.944, p < 0.05), indicating a consistent upward shift in female incidence. Similarly, the young-to-adult ratio (< 50/≥50 years) demonstrated a consistent declining pattern across regions (Fig. 1 C), with annual decreases ranging from 0.54% to 1.35%. Regarding stage distribution, the proportion of early-stage (I–II) versus advanced-stage (III–IV) adenocarcinomas exhibited heterogeneous patterns, although most regions remained stable overall (Supplementary Table 1). 3.2 Wildfire Activity and PM2.5 Between 2000 and 2023, a total of 90,149 wildfire events were recorded across the 17 RHDs, with mean annual counts for each RHD ranging from 84.3 to 452 events/year (Supplementary Fig. 1). Among the RHDs exhibiting significant increases in the ATR (RHDs 1, 2, 6, 7, 8, 14, 15), a pattern of higher wildfire activity was observed, with mean annual wildfire counts of 257.3, 427, 218, 263, 206, and 389.5 events/year in RHDs 2, 6, 7, 8, 14, and 15, respectively, with the exception of the São Paulo metropolitan area (RHD 1), which had a substantially lower mean of 130 events/year (Fig. 2 ). Regarding PM2.5 measurements, a total of 286 observations were recorded during the same period across seven RHDs, with concentrations ranging from 8 to 26 µg/m³ (overall mean ± SD: 15.93 ± 3.15 µg/m³) (Supplementary Fig. 2). Among the RHDs with increases in the ATR, the São Paulo metropolitan region (RHD 1) exhibited the highest regional mean PM2.5 concentration (16.8 µg/m³), despite having comparatively low wildfire activity. Taken together with the markedly lower number of wildfire events in this region, these findings suggest that the increase in the ATR observed in RHD 1 may be influenced by a chronic urban pollution profile that differs from the patterns seen in the other RHDs. A total of 79 PM2.5 peak measurements were recorded between 2000 and 2023 (Supplementary Fig. 3), with values ranging from 25 to 121 µg/m³ (mean ± SD: 47.7 ± 14.4 µg/m³). Considering all individual annual data points, a moderate positive correlation was observed between wildfire activity and PM2.5 peaks (ρ = 0.34, p = 0.005). When only the maximum PM2.5 value per RHD was considered, a strong correlation was observed (ρ = 0.928, p = 0.007) (Fig. 3 ), indicating that regions with more intense wildfire activity tend to experience higher PM2.5 peak concentrations. Given the observed association between annual wildfire activity and PM2.5 peaks, we further analyzed the monthly dynamics to explore seasonal patterns. Monthly PM2.5 data were extracted along with corresponding monthly wildfire counts for the same period, considering the entire state of São Paulo. These monthly averages revealed a clear temporal synchrony, with PM2.5 concentrations peaking in the same months as fire outbreaks. Spearman correlation analysis confirmed a very strong positive association between monthly PM2.5 and wildfire counts (ρ = 0.965, p < 0.001), supporting the visual impression of coinciding peaks and highlighting the potential contribution of wildfires to elevated PM2.5 episodes (Fig. 4 ). Building on the previous analyses, we next compared the mean number of wildfire hotspots between RHDs with and without a significant increase in the ATR. RHD 1 was excluded from this comparison due to its unique profile, including its megacity status and elevated mean PM2.5, which could confound the relationship. Among the six RHDs showing a significant ATR increase (2, 6, 7, 8, 14, and 15), the mean wildfire count was 311.3 hotspots (SD = 92.3), while the nine RHDs without an ATR increase had a lower mean of 206.8 hotspots (SD = 65.5). A Mann–Whitney test indicated a statistically significant difference (p = 0.049), showing that regions with increasing ATR have higher wildfire activity. Boxplots were generated to illustrate the distribution of wildfire counts across groups, showing higher medians and interquartile ranges in the “Increased ATR” group compared with the “No increase” group (Fig. 5 ) 4. Discussion By analyzing a state-level cancer registry comprising more than 51,000 lung cancer cases, we demonstrated that the proportion of adenocarcinoma increased in the last decade compared with the preceding one in Brazil’s most populous state. This finding aligns with multiple reports worldwide showing a steady global rise in lung adenocarcinoma 2 . Notably, the two-decade trend analysis revealed that this increase was not homogeneous across São Paulo State but instead concentrated in specific geographic microregions. Such spatial heterogeneity raises the hypothesis that local geographic context may act as a modulator of carcinogenic risk for lung adenocarcinoma, potentially through distinct environmental exposures. Chronic exposure to fine particulate matter (PM2.5) has recently been recognized as a contributor to lung adenocarcinoma risk, particularly in large metropolitan areas 9 . In line with this, the São Paulo metropolitan region exhibited a marked rise in the ATR, alongside the highest mean PM2.5 level (16.8 µg/m³) among all regions. Notably, other regions characterized by lower mean PM2.5 exposure also showed significant increases in ATR. Geographic analyses indicated that these areas overlapped with regions experiencing higher wildfire activity. In addition, when grouped, these regions exhibited substantially higher mean wildfire counts compared with those without an ATR increase. Correlation analyses showed that regions with more intense wildfire activity also exhibited higher PM2.5 peak levels, suggesting a dose-dependent–like pattern in which greater fire activity corresponded to higher maximum concentrations. Furthermore, the temporal synchrony between monthly wildfire counts and monthly PM2.5 peaks indicates that periods of heightened fire activity coincide with sharper pollution spikes. Taken together, these findings underscore the hypothesis that environmental biomass burning may act as a key driver of episodic PM2.5 peaks. At the mechanistic level, PM2.5 exposure has been linked to lung adenocarcinoma development, particularly in EGFR-mutated tumors 10 . These cancers occur predominantly in older women, a pattern that may reflect both lower smoking prevalence and a longer cumulative exposure window to environmental pollutants that can foster EGFR-dependent carcinogenic pathways. Mechanistic studies indicate that PM2.5 triggers inflammatory and oxidative stress responses in the alveolar lining, providing a biologically plausible link to tumor initiation 10 . Although short-term PM2.5 peaks have not been directly examined in these mechanistic models, their capacity to generate acute and amplified inflammatory responses suggests a meaningful potential to further heighten risk among susceptible populations. Importantly, our study documented a pronounced and consistent rise in the proportion of women over 50 years diagnosed with lung adenocarcinoma, underscoring the relevance of environmental exposure profiles in shaping the observed epidemiologic patterns. This study faces inherent limitations related to the challenges of conducting an ecological analysis in which multiple individual-level characteristics cannot be controlled, restricting the strength of any inferred association between wildfire events, peak PM2.5 exposure, and the increasing ATR of lung adenocarcinoma over time. The absence of individual-level exposure information in the São Paulo state cancer registry—including smoking status—limits our ability to assess and adjust for major determinants of lung cancer risk, thereby weakening the capacity to substantiate a hypothesis of environmentally driven carcinogenesis. Additionally, we were unable to account for other potential sources of PM2.5 beyond biomass burning, although the consistent observation that regions with higher wildfire activity exhibited more pronounced increases in ATR remains noteworthy. Overall, our results highlight the potential of PM2.5 peaks and environmental exposures related to wildfires and biomass burning as possible contributors to lung adenocarcinoma risk. This opens avenues for translational research addressing previously unexplored areas, such as carcinogenesis in non-EGFR-mutated adenocarcinomas among non-smoking populations. Furthermore, our findings have implications for public health policy, emphasizing the importance of integrating air quality monitoring, land management strategies, and cancer surveillance. They also support the idea that incorporating environmental risks into assessments can improve the identification of vulnerable populations, who may be candidates for targeted screening or prevention strategies. Future studies could leverage remote sensing, spatiotemporal modeling, and individual-level epidemiology to better elucidate the mechanistic links between PM2.5 peaks, wildfire- and biomass burning–associated exposures, and lung adenocarcinoma development. Declarations Acknowledgements This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Author contributions Saulo Brito Silva contributed to the conceptualization, data curation, formal analysis, methodology, software, validation, visualization, and writing of the original draft. Henrique Goldhart Larssen contributed to investigation, methodology, visualization, and manuscript review and editing. Leandro Machado Colli contributed to conceptualization, data curation, formal analysis, methodology, project administration, supervision, validation, and manuscript review and editing. Competing interest The authors declare no competing financial or non-financial interests. Data availability The environmental exposure data used in this study are publicly available. Air pollution data, including annual mean and maximum PM2.5 concentrations, were obtained from the Environmental Agency of the State of São Paulo (CETESB) for the period 2000–2023. Wildfire activity data were derived from satellite-based fire hotspot records provided by the Brazilian National Institute for Space Research (INPE) for the same period. Cancer incidence data were obtained from the Fundação Oncocentro de São Paulo (FOSP) and were analyzed in aggregated and deidentified form. Individual-level data cannot be shared due to data protection regulations and institutional restrictions. Aggregated datasets and the statistical code supporting the findings of this study will be made available upon reasonable request to the corresponding author for academic, non-commercial research purposes, subject to approval by the data-holding institution. Data will be available from the date of publication, with no planned end date. References 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(3):229–263. doi:10.3322/caac.21834. Luo G, Zhang Y, Rumgay H, et al. Estimated worldwide variation and trends in incidence of lung cancer by histological subtype in 2022 and over time: a population-based study. Lancet Respir Med. 2025;13(4):348–363. doi:10.1016/S2213-2600(24)00428-4. Hill W, Lim EL, Weeden CE, et al. Lung adenocarcinoma promotion by air pollutants. Nature. 2023;616(7955):159–167. doi:10.1038/s41586-023-05874-3. IARC. Air pollution and cancer. IARC Scientific Publication No. 161. Lyon: International Agency for Research on Cancer; 2013. Available from: https://www.iarc.who.int/wp-content/uploads/2018/07/AirPollutionandCancer161.pdf. Zhu M, Han Y, Mou Y, et al. Effect of long-term fine particulate matter exposure on lung cancer incidence and mortality in Chinese nonsmokers. Am J Respir Crit Care Med. 2025;211(4):600–609. doi:10.1164/rccm.202408-1661OC. Zhong Q, Shen G, Wang B, Ma J, Tao S, et al. Climate-driven escalation of global PM2.5 health burden from wildland fires. Environ Sci Technol. 2025;59(6):3131–3142. doi:10.1021/acs.est.4c10320. Yim SHL, Li Y, Huang T, et al. Global health impacts of ambient fine particulate pollution associated with climate variability. Environ Int. 2024;186:108587. doi:10.1016/j.envint.2024.108587. Lillini R, Tittarelli A, Bertoldi M, et al. Water and soil pollution: ecological environmental study methodologies useful for public health projects. A literature review. Rev Environ Contam Toxicol. 2021;256:179–214. doi:10.1007/398_2020_58. Berg CD, Schiller JH, Boffetta P, et al.; IASLC Early Detection and Screening Committee. Air pollution and lung cancer: a review by International Association for the Study of Lung Cancer Early Detection and Screening Committee. J Thorac Oncol. 2023;18(10):1277–1289. doi:10.1016/j.jtho.2023.05.024. PMID:37277094. Hill W, Lim EL, Weeden CE, Lee C, Augustine M, Chen K, et al.; TRACERx Consortium. Lung adenocarcinoma promotion by air pollutants. Nature. 2023;616(7955):159–167. doi:10.1038/s41586-023-05874-3. PMID:37020004; PMCID:PMC7614604. Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial.pdf Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 03 Apr, 2026 Reviews received at journal 03 Apr, 2026 Reviews received at journal 11 Mar, 2026 Reviewers agreed at journal 26 Feb, 2026 Reviewers agreed at journal 25 Feb, 2026 Reviewers invited by journal 09 Feb, 2026 Editor assigned by journal 03 Feb, 2026 Submission checks completed at journal 03 Feb, 2026 First submitted to journal 23 Jan, 2026 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-8681500","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":588507108,"identity":"f8104479-4e3e-48ee-a303-a46abfb09b81","order_by":0,"name":"Saulo Silva","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIiWNgGAWjYDACCQaGAwwMNvxwAQOitBxgSJNsIEkL0JrDJGiRn9378PCHivMSurPPHmDm+XOHwVz6AH4tBneOGxw4cOa2hNm5vARm3rZnDJZ9CQS0SKQxHDjYdrvO7AyPATNvw2EGgzOEHDYDrOWcBFgLzx8itDDcAGs5ANXCRoQWgzvHGA6cOZMM1MKXcHBu2zMeyx5CDpvdxvyhosIOqIX34IM3f+7ImfMQchgC8ICSwQESNIC0MIATzygYBaNgFIwCNAAAaFxG/NU6+ioAAAAASUVORK5CYII=","orcid":"","institution":"Universidade de São Paulo","correspondingAuthor":true,"prefix":"","firstName":"Saulo","middleName":"","lastName":"Silva","suffix":""},{"id":588507109,"identity":"8a2bd472-a0c2-4a38-a783-d54d39cd5e82","order_by":1,"name":"Henrique Larssen","email":"","orcid":"","institution":"Universidade de São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Henrique","middleName":"","lastName":"Larssen","suffix":""},{"id":588507110,"identity":"f0a2be92-e257-4daa-a738-ee58963c5fea","order_by":2,"name":"Leandro Colli","email":"","orcid":"","institution":"Universidade de São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Leandro","middleName":"","lastName":"Colli","suffix":""}],"badges":[],"createdAt":"2026-01-23 17:23:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8681500/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8681500/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102747493,"identity":"43317454-b993-4b7d-84ee-16ea2127703e","added_by":"auto","created_at":"2026-02-16 09:04:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1293482,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrends of adenocarcinoma-related ratios across Regional Health Departments (RHDs) over time. \u003c/strong\u003eThis combined figure presents three key indicators across multiple RHDs: (A) Adenocarcinoma / Total cases, showing varying trends across regions; (B) Female / Male ratio (Adenocarcinoma), indicating a generally increasing pattern across most RHDs; (C) Young / Adult (\u0026lt;50 ≥50 years) ratio (Adenocarcinoma), demonstrating a consistent declining pattern. Each point represents the observed value for a given year in a specific RHD, and the lines correspond to linear regression trends. Colors indicate the different RHDs, with consistent coding across all panels. Panels allow visual comparison of temporal trends across regions and ratios.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8681500/v1/68552d24e08f0e6b9ecd09af.png"},{"id":102747745,"identity":"9e62abc3-caf3-4129-9fe3-79cc0bcc3df6","added_by":"auto","created_at":"2026-02-16 09:05:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":361909,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpatial distribution of wildfire intensity and temporal trends in lung adenocarcinoma in São Paulo State, 2000–2023.\u003c/strong\u003e The left panel shows the mean number of wildfires per Regional Health Department (RHD) from 2000 to 2023, with color intensity representing the average annual fire incidence (0–500). The right panel illustrates the correlation between time and the adenocarcinoma-to-total lung cancer ratio (ATR) for each RHD, with color intensity indicating the correlation coefficient (ρ). Higher correlation values correspond to regions where ATR increased more consistently over the 24-year period. Negative correlation values were set to zero for visualization.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8681500/v1/786f0f0fdceb02dd36f322bd.png"},{"id":102596563,"identity":"6f0442f2-6478-46ef-adc4-015df7a1e2fb","added_by":"auto","created_at":"2026-02-13 12:22:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":182917,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWildfire activity is positively associated with PM2.5 peaks across Regional Health Departments (RHDs) in São Paulo State, 2000–2023.\u003c/strong\u003e Scatter plot showing the correlation between wildfire hotspot frequency and annual PM2.5 peaks across Regional Health Divisions (RHDs) in São Paulo State (2000–2023). A strong positive association was observed (Spearman ρ = 0.928; p = 0.008), suggesting that biomass burning substantially contributes to acute pollution episodes.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8681500/v1/d430d948c0fa9d468b3fdeef.png"},{"id":102596564,"identity":"1513daa5-0fce-401b-91fc-15bf033349fc","added_by":"auto","created_at":"2026-02-13 12:22:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":180850,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMonthly averages of PM2.5 concentrations and fire outbreaks in São Paulo State (2021–2025).\u003c/strong\u003ePeaks of air pollution coincide with peaks of biomass burning, showing a strong positive correlation (Spearman’s ρ = 0.97, p \u0026lt; 0.001). Left panels: PM2.5 trends (top: line chart; bottom: bar chart). Right panels: fire outbreaks (top: line chart; bottom: bar chart).\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8681500/v1/a401589ea676ddb053bb81dc.png"},{"id":102747992,"identity":"686dd571-80a8-4ff8-bec7-cad679e17d1d","added_by":"auto","created_at":"2026-02-16 09:05:43","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":81439,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRegions with increasing adenocarcinoma-to-total lung cancer ratios experienced higher wildfire activity, São Paulo State, 2000–2023.\u003c/strong\u003e Distribution of the adenocarcinoma-to-total lung cancer ratio across Regional Health Departments (RHDs) in São Paulo State, Brazil, from 2000 to 2023. The boxplots (red: RHDs with significant increase; blue: RHDs with no significant increase) represent the median, interquartile range, and variability of the ratios.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8681500/v1/5383edaf1cd9d74bece7826a.png"},{"id":102750932,"identity":"6f4de83f-1231-4aa8-a582-c4830f429e2f","added_by":"auto","created_at":"2026-02-16 09:22:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2738098,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8681500/v1/fc7eedcf-87a7-4e16-8f40-ad7dd2cf3e1e.pdf"},{"id":102596566,"identity":"014ce31d-c3f2-40f4-96c4-7e1bd2a1a7a6","added_by":"auto","created_at":"2026-02-13 12:22:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":887290,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8681500/v1/87a020d7a3ce94658f02430b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Biomass Burning, PM2.5 Peaks, and Trends in Lung Adenocarcinoma Incidence: An Ecological Study in São Paulo State, Brazil","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eLung cancer remains one of the most commonly diagnosed cancers and the leading cause of cancer-related mortality worldwide, accounting for over 1.8\u0026nbsp;million deaths annually\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Despite a global decline in smoking rates, lung cancer incidence\u0026mdash;particularly the adenocarcinoma subtype\u0026mdash;has not followed the same downward trend. Indeed, lung adenocarcinoma has emerged as the predominant histological subtype, with a notable increase among never-smokers\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. This epidemiological shift has sparked growing interest in alternative etiological factors, particularly environmental exposures such as fine particulate matter with a diameter\u0026thinsp;\u0026le;\u0026thinsp;2.5 \u0026micro;m (PM2.5)\u003csup\u003e3\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePM2.5, classified as a Group 1 carcinogen by the International Agency for Research on Cancer (IARC)\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, originates largely from combustion processes, including industrial emissions, vehicular traffic, fossil fuel burning, and increasingly, biomass combustion\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. While long-term exposure to PM2.5 from urban-industrial sources has been linked to lung adenocarcinoma\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, episodic exposures from biomass burning\u0026mdash;common in agricultural regions and areas prone to wildfires\u0026mdash;may carry underrecognized carcinogenic risks. Such acute yet recurrent exposures can generate peaks of PM2.5 that superimpose on chronic pollution and potentially exacerbate lung carcinogenesis. With climate change intensifying the frequency and severity of biomass fires, this source of PM2.5 is becoming increasingly relevant to public health\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eEarly evidence linking PM2.5 with lung adenocarcinoma has largely emerged from analyses of large metropolitan areas in East Asia, particularly among never-smokers, often highlighting associations with adenocarcinoma harboring EGFR mutations\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. However, less is known about lung adenocarcinoma trends in in large metropolitan areas outside of East Asia and in the surrounding rural areas, particularly in low- and middle income (LMIC) settings. The potential carcinogenic impact of such PM2.5 peaks remains underexplored, despite their intensity and recurrence.\u003c/p\u003e \u003cp\u003eThis ecological study aims to assess the association between lung adenocarcinoma incidence, PM2.5 levels, and biomass burning activity across S\u0026atilde;o Paulo State, Brazil, a region characterized both by a major metropolitan area and by extensive rural area with environmental pollution from deforestation, sugarcane harvesting, and climate-related wildfires. By integrating population-based cancer registry data with satellite-derived environmental metrics of air pollution and wildfire activity, we seek to clarify the role of biomass burning in lung cancer risk and address a critical knowledge gap in a middle-income setting.\u003c/p\u003e"},{"header":"2. Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Design and Population\u003c/h2\u003e \u003cp\u003eThis is a retrospective ecological analysis conducted across the 17 Regional Health Divisions (RHDs) of S\u0026atilde;o Paulo State, Brazil. RHDs are state administrative areas for better reference and treatment care for population. Each RHD has their own health structure for diagnosis and treatment of patients of all diseases, including cancer. For analytical purposes, RHD 4 was combined with RHD 1 due to its small geographic area and proximity, resulting in 16 effective regions. The study period spanned from January 2000 to December 2023. All histologically confirmed primary lung cancer cases were included, as reported in the publicly available at Funda\u0026ccedil;\u0026atilde;o Oncocentro de S\u0026atilde;o Paulo (Hospital Cancer Registry of S\u0026atilde;o Paulo State, FOSP, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://fosp.saude.sp.gov.br/\u003c/span\u003e\u003cspan address=\"https://fosp.saude.sp.gov.br/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The state registry contains information on primary tumor site, histological subtype, age at diagnosis, sex, educational level, clinical and/or pathological stage (grouped as I\u0026ndash;II vs III\u0026ndash;IV), municipality of residence, and vital status. Each RHD contributes monthly data to the centralized database, ensuring systematic and continuous collection of cancer cases treated within the region. Patients were assigned to the RHD corresponding to their municipality of residence, consistent with the standard referral structure in S\u0026atilde;o Paulo. To minimize biases due to temporal fluctuations in case reporting, we calculated the annual adenocarcinoma-to-total histology ratio (ATR) per RHD.\u003c/p\u003e \u003cp\u003eThe primary outcome was temporal trends in the adenocarcinoma-to-total lung cancer ratio (ATR) across RHDs. Secondary analyses included demographic and clinical variables to evaluate whether changes in adenocarcinoma prevalence were accompanied by shifts in patient characteristics. Environmental exposures, including wildfire activity and PM2.5 concentrations (both mean and peak levels), were assessed to explore potential associations with ATR trends. The use of aggregated RHD-level data allowed investigation of regional patterns while preserving patient confidentiality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Environmental Exposure Data\u003c/h2\u003e \u003cp\u003eAir pollution data were obtained from publicly available sources. Annual mean and maximum PM2.5 concentrations were derived from representative monitoring stations in major cities within each RHD, as reported by the \u003cem\u003eCompanhia Ambiental do Estado de S\u0026atilde;o Paulo\u003c/em\u003e (Environmental Agency of the State of S\u0026atilde;o Paulo, CETESB, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.cetesb.sp.gov.br\u003c/span\u003e\u003cspan address=\"http://www.cetesb.sp.gov.br\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Stations provide hourly measurements, typically aggregated monthly, which were then averaged to obtain annual values. Mean annual PM2.5 values capture chronic exposure, whereas maximum annual values represent peak pollution levels.\u003c/p\u003e \u003cp\u003eWildfire activity was quantified using the \u003cem\u003eInstituto Nacional de Pesquisas Espaciais\u003c/em\u003e (National Institute for Space Research, INPE, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://queimadas.dgi.inpe.br\u003c/span\u003e\u003cspan address=\"http://queimadas.dgi.inpe.br\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) satellite fire hotspot product. Fires are detected by multiple satellites including NOAA-18, NOAA-19, NOAA-20, METOP-B, TERRA, AQUA, and Suomi-NPP, with spatial resolution ranging from 375 m \u0026times; 375 m to 5 km \u0026times; 4 km depending on the satellite. Each hotspot corresponds to a fire detection at a pixel; multiple hotspots may represent a single fire event. For each RHD, the mean annual number of hotspots was calculated over the study period. This approach allowed integration of environmental exposures with regional lung cancer trends and facilitated evaluation of potential associations between wildfire activity, PM2.5 peaks, and adenocarcinoma incidence.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 3Statistical Analysis\u003c/h2\u003e \u003cp\u003eContinuous variables are reported as means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) or medians with interquartile ranges (IQR), as appropriate, and categorical variables as counts and percentages. Temporal trends in the ATR were assessed using linear regression models and correlation analyses with time (Pearson or Spearman, depending on normality). In addition, average annual percent change (AAPC) was calculated for each RHD to quantify the magnitude of long-term trends and provide a confirmatory measure alongside regression slopes.\u003c/p\u003e \u003cp\u003eCorrelations between wildfire hotspot frequency, PM2.5 peak concentrations, and ATR trends were evaluated using Pearson or Spearman correlation. PM2.5 peaks were defined as the annual maximum daily PM2.5 value recorded within each monitoring station. Two complementary analyses were performed for PM2.5 peaks: one considering all individual annual data points across RHDs, and another considering the maximum PM2.5 value per RHD to highlight extreme exposure events.\u003c/p\u003e \u003cp\u003eComparisons between RHDs with and without a significant increase in ATR were performed using independent t-tests or non-parametric Mann\u0026ndash;Whitney tests, as appropriate. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant, while p-values between 0.05 and 0.10 were interpreted as trend-level effects. All analyses were conducted in R (version 4.3.1).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Lung Cancer Trends Across S\u0026atilde;o Paulo State\u003c/h2\u003e \u003cp\u003eA total of 51,580 cases of lung cancer were identified during the study period across the 16 geographic regions. Among these, adenocarcinoma accounted for 36% of cases, representing the most frequent histological subtype. Temporal trend analyses in the ATR from 2000 to 2023 demonstrated varying patterns across regions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), with significant linear trend-level effect increases observed in RHDs 1, 2, 6, 7, 8, 14, and 15, underscoring an upward trend. Correlation analyses supported these observations, with coefficients ranging from moderate to very strong (r\u0026thinsp;=\u0026thinsp;0.441\u0026ndash;0.823, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and estimates of average annual percent change (AAPC) demonstrating annual increases in ATR ranging from 0.39% to 0.72% across these regions (Supplementary Tables\u0026nbsp;1 and 2). Taken together, these seven RHDs (1, 2, 6, 7, 8, 14, and 15) were classified as regions with an increasing ATR.\u003c/p\u003e \u003cp\u003eTemporal trends in sex distribution revealed a pronounced increase in the proportion of female lung cancer cases across S\u0026atilde;o Paulo State (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), with thirteen of the 16 RHDs demonstrating positive annual increases in female proportion and moderate to strong correlations over time (r\u0026thinsp;=\u0026thinsp;0.568\u0026ndash;0.944, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating a consistent upward shift in female incidence. Similarly, the young-to-adult ratio (\u0026lt;\u0026thinsp;50/\u0026ge;50 years) demonstrated a consistent declining pattern across regions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), with annual decreases ranging from 0.54% to 1.35%. Regarding stage distribution, the proportion of early-stage (I\u0026ndash;II) versus advanced-stage (III\u0026ndash;IV) adenocarcinomas exhibited heterogeneous patterns, although most regions remained stable overall (Supplementary Table\u0026nbsp;1).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Wildfire Activity and PM2.5\u003c/h2\u003e \u003cp\u003eBetween 2000 and 2023, a total of 90,149 wildfire events were recorded across the 17 RHDs, with mean annual counts for each RHD ranging from 84.3 to 452 events/year (Supplementary Fig.\u0026nbsp;1). Among the RHDs exhibiting significant increases in the ATR (RHDs 1, 2, 6, 7, 8, 14, 15), a pattern of higher wildfire activity was observed, with mean annual wildfire counts of 257.3, 427, 218, 263, 206, and 389.5 events/year in RHDs 2, 6, 7, 8, 14, and 15, respectively, with the exception of the S\u0026atilde;o Paulo metropolitan area (RHD 1), which had a substantially lower mean of 130 events/year (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eRegarding PM2.5 measurements, a total of 286 observations were recorded during the same period across seven RHDs, with concentrations ranging from 8 to 26 \u0026micro;g/m\u0026sup3; (overall mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: 15.93\u0026thinsp;\u0026plusmn;\u0026thinsp;3.15 \u0026micro;g/m\u0026sup3;) (Supplementary Fig.\u0026nbsp;2). Among the RHDs with increases in the ATR, the S\u0026atilde;o Paulo metropolitan region (RHD 1) exhibited the highest regional mean PM2.5 concentration (16.8 \u0026micro;g/m\u0026sup3;), despite having comparatively low wildfire activity. Taken together with the markedly lower number of wildfire events in this region, these findings suggest that the increase in the ATR observed in RHD 1 may be influenced by a chronic urban pollution profile that differs from the patterns seen in the other RHDs.\u003c/p\u003e \u003cp\u003eA total of 79 PM2.5 peak measurements were recorded between 2000 and 2023 (Supplementary Fig.\u0026nbsp;3), with values ranging from 25 to 121 \u0026micro;g/m\u0026sup3; (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD: 47.7\u0026thinsp;\u0026plusmn;\u0026thinsp;14.4 \u0026micro;g/m\u0026sup3;). Considering all individual annual data points, a moderate positive correlation was observed between wildfire activity and PM2.5 peaks (ρ\u0026thinsp;=\u0026thinsp;0.34, p\u0026thinsp;=\u0026thinsp;0.005). When only the maximum PM2.5 value per RHD was considered, a strong correlation was observed (ρ\u0026thinsp;=\u0026thinsp;0.928, p\u0026thinsp;=\u0026thinsp;0.007) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), indicating that regions with more intense wildfire activity tend to experience higher PM2.5 peak concentrations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eGiven the observed association between annual wildfire activity and PM2.5 peaks, we further analyzed the monthly dynamics to explore seasonal patterns. Monthly PM2.5 data were extracted along with corresponding monthly wildfire counts for the same period, considering the entire state of S\u0026atilde;o Paulo. These monthly averages revealed a clear temporal synchrony, with PM2.5 concentrations peaking in the same months as fire outbreaks. Spearman correlation analysis confirmed a very strong positive association between monthly PM2.5 and wildfire counts (ρ\u0026thinsp;=\u0026thinsp;0.965, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), supporting the visual impression of coinciding peaks and highlighting the potential contribution of wildfires to elevated PM2.5 episodes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBuilding on the previous analyses, we next compared the mean number of wildfire hotspots between RHDs with and without a significant increase in the ATR. RHD 1 was excluded from this comparison due to its unique profile, including its megacity status and elevated mean PM2.5, which could confound the relationship. Among the six RHDs showing a significant ATR increase (2, 6, 7, 8, 14, and 15), the mean wildfire count was 311.3 hotspots (SD\u0026thinsp;=\u0026thinsp;92.3), while the nine RHDs without an ATR increase had a lower mean of 206.8 hotspots (SD\u0026thinsp;=\u0026thinsp;65.5). A Mann\u0026ndash;Whitney test indicated a statistically significant difference (p\u0026thinsp;=\u0026thinsp;0.049), showing that regions with increasing ATR have higher wildfire activity. Boxplots were generated to illustrate the distribution of wildfire counts across groups, showing higher medians and interquartile ranges in the \u0026ldquo;Increased ATR\u0026rdquo; group compared with the \u0026ldquo;No increase\u0026rdquo; group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eBy analyzing a state-level cancer registry comprising more than 51,000 lung cancer cases, we demonstrated that the proportion of adenocarcinoma increased in the last decade compared with the preceding one in Brazil\u0026rsquo;s most populous state. This finding aligns with multiple reports worldwide showing a steady global rise in lung adenocarcinoma\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Notably, the two-decade trend analysis revealed that this increase was not homogeneous across S\u0026atilde;o Paulo State but instead concentrated in specific geographic microregions. Such spatial heterogeneity raises the hypothesis that local geographic context may act as a modulator of carcinogenic risk for lung adenocarcinoma, potentially through distinct environmental exposures.\u003c/p\u003e \u003cp\u003eChronic exposure to fine particulate matter (PM2.5) has recently been recognized as a contributor to lung adenocarcinoma risk, particularly in large metropolitan areas\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. In line with this, the S\u0026atilde;o Paulo metropolitan region exhibited a marked rise in the ATR, alongside the highest mean PM2.5 level (16.8 \u0026micro;g/m\u0026sup3;) among all regions. Notably, other regions characterized by lower mean PM2.5 exposure also showed significant increases in ATR. Geographic analyses indicated that these areas overlapped with regions experiencing higher wildfire activity. In addition, when grouped, these regions exhibited substantially higher mean wildfire counts compared with those without an ATR increase.\u003c/p\u003e \u003cp\u003eCorrelation analyses showed that regions with more intense wildfire activity also exhibited higher PM2.5 peak levels, suggesting a dose-dependent\u0026ndash;like pattern in which greater fire activity corresponded to higher maximum concentrations. Furthermore, the temporal synchrony between monthly wildfire counts and monthly PM2.5 peaks indicates that periods of heightened fire activity coincide with sharper pollution spikes. Taken together, these findings underscore the hypothesis that environmental biomass burning may act as a key driver of episodic PM2.5 peaks.\u003c/p\u003e \u003cp\u003eAt the mechanistic level, PM2.5 exposure has been linked to lung adenocarcinoma development, particularly in EGFR-mutated tumors\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. These cancers occur predominantly in older women, a pattern that may reflect both lower smoking prevalence and a longer cumulative exposure window to environmental pollutants that can foster EGFR-dependent carcinogenic pathways. Mechanistic studies indicate that PM2.5 triggers inflammatory and oxidative stress responses in the alveolar lining, providing a biologically plausible link to tumor initiation\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Although short-term PM2.5 peaks have not been directly examined in these mechanistic models, their capacity to generate acute and amplified inflammatory responses suggests a meaningful potential to further heighten risk among susceptible populations. Importantly, our study documented a pronounced and consistent rise in the proportion of women over 50 years diagnosed with lung adenocarcinoma, underscoring the relevance of environmental exposure profiles in shaping the observed epidemiologic patterns.\u003c/p\u003e \u003cp\u003eThis study faces inherent limitations related to the challenges of conducting an ecological analysis in which multiple individual-level characteristics cannot be controlled, restricting the strength of any inferred association between wildfire events, peak PM2.5 exposure, and the increasing ATR of lung adenocarcinoma over time. The absence of individual-level exposure information in the S\u0026atilde;o Paulo state cancer registry\u0026mdash;including smoking status\u0026mdash;limits our ability to assess and adjust for major determinants of lung cancer risk, thereby weakening the capacity to substantiate a hypothesis of environmentally driven carcinogenesis. Additionally, we were unable to account for other potential sources of PM2.5 beyond biomass burning, although the consistent observation that regions with higher wildfire activity exhibited more pronounced increases in ATR remains noteworthy.\u003c/p\u003e \u003cp\u003eOverall, our results highlight the potential of PM2.5 peaks and environmental exposures related to wildfires and biomass burning as possible contributors to lung adenocarcinoma risk. This opens avenues for translational research addressing previously unexplored areas, such as carcinogenesis in non-EGFR-mutated adenocarcinomas among non-smoking populations. Furthermore, our findings have implications for public health policy, emphasizing the importance of integrating air quality monitoring, land management strategies, and cancer surveillance. They also support the idea that incorporating environmental risks into assessments can improve the identification of vulnerable populations, who may be candidates for targeted screening or prevention strategies. Future studies could leverage remote sensing, spatiotemporal modeling, and individual-level epidemiology to better elucidate the mechanistic links between PM2.5 peaks, wildfire- and biomass burning\u0026ndash;associated exposures, and lung adenocarcinoma development.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSaulo Brito Silva contributed to the conceptualization, data curation, formal analysis, methodology, software, validation, visualization, and writing of the original draft. Henrique Goldhart Larssen contributed to investigation, methodology, visualization, and manuscript review and editing. Leandro Machado Colli contributed to conceptualization, data curation, formal analysis, methodology, project administration, supervision, validation, and manuscript review and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing financial or non-financial interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe environmental exposure data used in this study are publicly available. Air pollution data, including annual mean and maximum PM2.5 concentrations, were obtained from the Environmental Agency of the State of S\u0026atilde;o Paulo (CETESB) for the period 2000\u0026ndash;2023. Wildfire activity data were derived from satellite-based fire hotspot records provided by the Brazilian National Institute for Space Research (INPE) for the same period. Cancer incidence data were obtained from the Funda\u0026ccedil;\u0026atilde;o Oncocentro de S\u0026atilde;o Paulo (FOSP) and were analyzed in aggregated and deidentified form. Individual-level data cannot be shared due to data protection regulations and institutional restrictions. Aggregated datasets and the statistical code supporting the findings of this study will be made available upon reasonable request to the corresponding author for academic, non-commercial research purposes, subject to approval by the data-holding institution. Data will be available from the date of publication, with no planned end date.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. \u003cem\u003eCA Cancer J Clin.\u003c/em\u003e 2024;74(3):229\u0026ndash;263. doi:10.3322/caac.21834.\u003c/li\u003e\n\u003cli\u003eLuo G, Zhang Y, Rumgay H, et al. Estimated worldwide variation and trends in incidence of lung cancer by histological subtype in 2022 and over time: a population-based study. \u003cem\u003eLancet Respir Med.\u003c/em\u003e 2025;13(4):348\u0026ndash;363. doi:10.1016/S2213-2600(24)00428-4.\u003c/li\u003e\n\u003cli\u003eHill W, Lim EL, Weeden CE, et al. Lung adenocarcinoma promotion by air pollutants. \u003cem\u003eNature.\u003c/em\u003e 2023;616(7955):159\u0026ndash;167. doi:10.1038/s41586-023-05874-3.\u003c/li\u003e\n\u003cli\u003eIARC. Air pollution and cancer. IARC Scientific Publication No. 161. Lyon: International Agency for Research on Cancer; 2013. Available from: https://www.iarc.who.int/wp-content/uploads/2018/07/AirPollutionandCancer161.pdf.\u003c/li\u003e\n\u003cli\u003eZhu M, Han Y, Mou Y, et al. Effect of long-term fine particulate matter exposure on lung cancer incidence and mortality in Chinese nonsmokers. \u003cem\u003eAm J Respir Crit Care Med.\u003c/em\u003e 2025;211(4):600\u0026ndash;609. doi:10.1164/rccm.202408-1661OC.\u003c/li\u003e\n\u003cli\u003eZhong Q, Shen G, Wang B, Ma J, Tao S, et al. Climate-driven escalation of global PM2.5 health burden from wildland fires. \u003cem\u003eEnviron Sci Technol.\u003c/em\u003e 2025;59(6):3131\u0026ndash;3142. doi:10.1021/acs.est.4c10320.\u003c/li\u003e\n\u003cli\u003eYim SHL, Li Y, Huang T, et al. Global health impacts of ambient fine particulate pollution associated with climate variability. \u003cem\u003eEnviron Int.\u003c/em\u003e 2024;186:108587. doi:10.1016/j.envint.2024.108587.\u003c/li\u003e\n\u003cli\u003eLillini R, Tittarelli A, Bertoldi M, et al. Water and soil pollution: ecological environmental study methodologies useful for public health projects. A literature review. \u003cem\u003eRev Environ Contam Toxicol.\u003c/em\u003e 2021;256:179\u0026ndash;214. doi:10.1007/398_2020_58.\u003c/li\u003e\n\u003cli\u003eBerg CD, Schiller JH, Boffetta P, et al.; IASLC Early Detection and Screening Committee. Air pollution and lung cancer: a review by International Association for the Study of Lung Cancer Early Detection and Screening Committee. \u003cem\u003eJ Thorac Oncol.\u003c/em\u003e 2023;18(10):1277\u0026ndash;1289. doi:10.1016/j.jtho.2023.05.024. PMID:37277094.\u003c/li\u003e\n\u003cli\u003e Hill W, Lim EL, Weeden CE, Lee C, Augustine M, Chen K, et al.; TRACERx Consortium. Lung adenocarcinoma promotion by air pollutants. \u003cem\u003eNature.\u003c/em\u003e 2023;616(7955):159\u0026ndash;167. doi:10.1038/s41586-023-05874-3. PMID:37020004; PMCID:PMC7614604.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bjc-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [BJC Reports](https://www.springer.com/journal/44276) ","snPcode":"44276","submissionUrl":"https://submission.springernature.com/new-submission/44276/3","title":"BJC Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Lung adenocarcinoma, PM2.5, Air pollution, Environmental exposure","lastPublishedDoi":"10.21203/rs.3.rs-8681500/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8681500/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLung adenocarcinoma incidence has increased globally despite declining tobacco exposure, raising questions about non\u0026ndash;tobacco-related contributors. The role of fine particulate matter (PM2.5) peaks related to biomass burning in shaping population-level lung cancer patterns remains unexplored. A population-based ecological analysis was conducted across the Regional Health Divisions of S\u0026atilde;o Paulo State, Brazil, from 2000 to 2023. Histologically confirmed lung cancer cases were obtained from the state cancer registry. Temporal trends in the adenocarcinoma-to-total lung cancer ratio (ATR) were evaluated alongside annual mean and maximum PM2.5 concentrations and wildfire counts derived from satellite data. Among 51,580 lung cancer cases, adenocarcinoma accounted for 36%. Regions with a significant increase in ATR demonstrated annual increases ranging from 0.39% to 0.72%. With the exception of the S\u0026atilde;o Paulo metropolitan area, which showed high mean PM2.5 levels despite low wildfire activity, all other regions with increasing ATR exhibited substantially higher wildfire occurrence (311 vs. 207 annual hotspots; p\u0026thinsp;=\u0026thinsp;0.04), which strongly correlated with PM2.5 peaks (ρ\u0026thinsp;=\u0026thinsp;0.928, p\u0026thinsp;=\u0026thinsp;0.007). Periods of elevated PM2.5 peaks consistently coincided with increased wildfire activity. These findings suggest that biomass-burning\u0026ndash;related PM2.5 peaks may be relevant to population-level patterns of lung cancer epidemiology.\u003c/p\u003e","manuscriptTitle":"Biomass Burning, PM2.5 Peaks, and Trends in Lung Adenocarcinoma Incidence: An Ecological Study in São Paulo State, Brazil","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-13 12:22:20","doi":"10.21203/rs.3.rs-8681500/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-03T15:27:02+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-03T12:10:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-11T21:58:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"261438483955483623405592346242123743195","date":"2026-02-26T18:30:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"261579215657986252922067767638022729320","date":"2026-02-25T10:49:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-09T18:24:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-03T10:55:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-03T10:54:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"BJC Reports","date":"2026-01-23T17:09:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bjc-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [BJC Reports](https://www.springer.com/journal/44276) ","snPcode":"44276","submissionUrl":"https://submission.springernature.com/new-submission/44276/3","title":"BJC Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3f16d634-0bed-4f7f-acea-6049b8528e29","owner":[],"postedDate":"February 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-07T20:38:14+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-13 12:22:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8681500","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8681500","identity":"rs-8681500","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}