{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T06:35:52Z","timestamp":1790231752169,"version":"4.1.0"},"reference-count":62,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,12,16]],"date-time":"2024-12-16T00:00:00Z","timestamp":1734307200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100011350","name":"State Key Laboratory of Remote Sensing Science","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100011350","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"\n Background<\/jats:title>\n \n Despite examining the role of an association between particulate matter and lung cancer in low-income countries, studies on the association between long-term exposure to particulate matter and lung cancer risk are still contradictory. This study investigates the spatiotemporal distribution patterns of lung cancer incidence and potential association with particulate matter (PM\n 2.5<\/jats:sub>\n ) in Bagmati province, Nepal.\n <\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n We performed a spatiotemporal study to analyze the LC \u2013 PM\n 2.5<\/jats:sub>\n association, using LC and annual mean PM\n 2.5<\/jats:sub>\n concentration data from 2012 to 2021. The study assessed the global spatial autocorrelation test using global Moran's I, applied hotspot analysis. A bivariate statistical analysis was performed to evaluate the association, we also applied the geographically weighted regression model (GWR) to look for possible relationships.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n The annual mean crude incidence rate (CIR) and standardized incidence rate (SIR) were 5.16, and 6.09 respectively. The study reveals an increasing trend with notable municipal-level spatial variations. Bhaktapur municipality exhibits the highest CIR (243.88), followed by Panchkhal and Sunapati. Males consistently exhibit higher rates, particularly in middle-aged and older adult populations. Bhaktapur displayed the highest CIR in males (171.9) but very low in females (72). The spatial analysis identified concentration trends and hotspots developed in the Bhaktapur, Panchkhal, and Sunapati municipalities. The SIR showed fluctuating patterns of continuous rise until 2019, decrease in 2020, and rise again thereafter. Similar fluctuation association patterns were observed with PM\n 2.5<\/jats:sub>\n , the\n r<\/jats:italic>\n -squared value consistently fluctuated during the study period.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n \n In this study, we found an association between PM\n 2.5<\/jats:sub>\n exposure and lung cancer incidence. The findings underscore the need for targeted public health interventions, highlighting the role of PM\n 2.5<\/jats:sub>\n . Future research is suggested to explore the relationship between lung cancer distribution and various environmental risk factors for effective control and prevention. Addressing air pollution could potentially reduce future lung cancer risk.\n <\/jats:p>\n <\/jats:sec>","DOI":"10.3389\/fpubh.2024.1490973","type":"journal-article","created":{"date-parts":[[2024,12,16]],"date-time":"2024-12-16T01:19:33Z","timestamp":1734311973000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Lung cancer risk and its potential association with PM2.5 in Bagmati province, Nepal\u2014A spatiotemporal study from 2012 to 2021"],"prefix":"10.3389","volume":"12","author":[{"given":"Basanta Kumar","family":"Neupane","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bipin 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