Neupane Basanta Kumar, Acharya Bipin Kumar, Cao Chunxiang, Xu Min, Taylor Pornpimol Kodsup, Wang Shaohua, Yang Yujie
State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China.
University of Chinese Academy of Sciences, Beijing, China.
Front Public Health. 2024 Dec 16;12:1490973. doi: 10.3389/fpubh.2024.1490973. eCollection 2024.
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) in Bagmati province, Nepal.
We performed a spatiotemporal study to analyze the LC - PM association, using LC and annual mean PM 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.
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, the -squared value consistently fluctuated during the study period.
In this study, we found an association between PM exposure and lung cancer incidence. The findings underscore the need for targeted public health interventions, highlighting the role of PM. 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.
尽管对低收入国家中颗粒物与肺癌之间的关联作用进行了研究，但关于长期接触颗粒物与肺癌风险之间的关联研究仍存在矛盾之处。本研究调查了尼泊尔巴格马蒂省肺癌发病率的时空分布模式以及与颗粒物（PM）的潜在关联。
我们进行了一项时空研究，以分析肺癌与颗粒物的关联，使用了2012年至2021年的肺癌和年平均颗粒物浓度数据。该研究使用全局莫兰指数评估全局空间自相关检验，并应用热点分析。进行了双变量统计分析以评估这种关联，我们还应用地理加权回归模型（GWR）来寻找可能的关系。
年平均粗发病率（CIR）和标准化发病率（SIR）分别为5.16和6.09。该研究揭示了一种上升趋势，且存在显著的市级空间差异。巴克塔普尔市的CIR最高（243.88），其次是潘奇哈尔和苏纳帕蒂。男性的发病率一直较高，尤其是在中年及老年人群中。巴克塔普尔市男性的CIR最高（171.9），但女性的CIR非常低（72）。空间分析确定了巴克塔普尔、潘奇哈尔和苏纳帕蒂市的浓度趋势和热点。SIR呈现出波动模式，直到2019年持续上升，2020年下降，此后再次上升。与颗粒物观察到类似的波动关联模式，在研究期间，R平方值持续波动。
在本研究中，我们发现了颗粒物暴露与肺癌发病率之间的关联。这些发现强调了有针对性的公共卫生干预措施的必要性，突出了颗粒物的作用。建议未来的研究探索肺癌分布与各种环境风险因素之间的关系，以进行有效的控制和预防。解决空气污染问题可能会潜在地降低未来的肺癌风险。
