Geographic Distribution and Epidemiology of Lung Cancer During 2011 in Zhejiang Province of China

Lin, Xiaohui; Chen, Yan; Gong, Weiwei; Wu, Zhaofan; Zou, Baobo; Zhao, Jiayuan; Gu, Hua; Jiang, Jianmin

doi:10.7314/apjcp.2014.15.13.5299

Cited by 7 publications

(6 citation statements)

References 20 publications

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“…Soil with high sand content is more likely to produce dust, which is the largest source of PM 2.5 in Zhengzhou (S. Wang et al., 2017 ). NDVI is related to the vegetation cover and greening level of a region, and previous studies have shown that it may affect the occurrence of lung cancer (Lin et al., 2014 ). However, the results of this study showed that the correlation between NDVI and the incidence of lung cancer was not strong.…”

Section: Discussionmentioning

confidence: 99%

Identifying the Environmental Determinants of Lung Cancer: A Case Study of Henan, China

Liu

et al. 2023

GeoHealth

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Lung cancer has become one of the most prevalent cancers in the last several decades. Studies have documented that most cases of lung cancer are caused by inhaling environmental carcinogens while how external environmental factors lead to individual lung cancer is still an open issue as the pathogenesis may come from the combined action of multiple environmental factors, and such pathogenic mechanism may vary from region to region. Based on the data of lung cancer cases from hospitals at the county level in Henan from 2016 to 2020, we analyzed the response relationship between lung cancer incidence and physical ambient factors (air quality, meteorological conditions, soil vegetation) and socioeconomic factors (occupational environment, medical level, heating mode, smoking behavior). We used a Bayesian spatio‐temporal interaction model to evaluate the relative risk of disease in different regions. The results showed that smoking was still the primary determinant of lung cancer, but the influence of air quality was increasing year by year, with meteorological conditions and occupational environment playing a synergistic role in this process. The high‐risk areas were concentrated in the plains of East and Central Henan and the basin of South Henan, while the low‐risk areas were concentrated in the hilly areas of North and West Henan, which were related to the topography of Henan. Our study provides a better understanding of the environmental determinants of lung cancer which will help refine existing prevention strategies and recognize the areas where actions are required to prevent environment and occupation related lung cancer.

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Section: Discussionmentioning

confidence: 99%

Identifying the Environmental Determinants of Lung Cancer: A Case Study of Henan, China

Liu

et al. 2023

GeoHealth

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“…The study discovered significant variety among different geographic areas and identified areas that were impacted the most by cervical cancer. In another study [27], the investigators used a geographic map to uncover the distribution patterns and risk factors of lung cancer in China. The study discovered two most significant factors contributing to diagnoses of lung cancer, including the poor quality of air and the associated low annual precipitation.…”

Section: Discussionmentioning

confidence: 99%

Systematic data ingratiation of clinical trial recruitment locations for geographic-based query and visualization

Luo

Chen

et al. 2017

International Journal of Medical Informatics

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Background Prior studies of clinical trial planning indicate that it is crucial to search and screen recruitment sites before starting to enroll participants. However, currently there is no systematic method developed to support clinical investigators to search candidate recruitment sites according to their interested clinical trial factors. Objective In this study, we aim at developing a new approach to integrating the location data of over one million heterogeneous recruitment sites that are stored in clinical trial documents. The integrated recruitment location data can be searched and visualized using a map-based information retrieval method. The method enables systematic search and analysis of recruitment sites across a large amount of clinical trials. Methods The location data of more than 1.4 million recruitment sites of over 183,000 clinical trials was normalized and integrated using a geocoding method. The integrated data can be used to support geographic information retrieval of recruitment sites. Additionally, the information of over 6000 clinical trial target disease conditions and close to 4000 interventions was also integrated into the system and linked to the recruitment locations. Such data integration enabled the construction of a novel map-based query system. The system will allow clinical investigators to search and visualize candidate recruitment sites for clinical trials based on target conditions and interventions. Results The evaluation results showed that the coverage of the geographic location mapping for the 1.4 million recruitment sites was 99.8%. The evaluation of 200 randomly retrieved recruitment sites showed that the correctness of geographic information mapping was 96.5%. The recruitment intensities of the top 30 countries were also retrieved and analyzed. The data analysis results indicated that the recruitment intensity varied significantly across different countries and geographic areas. Conclusion This study contributed a new data processing framework to extract and integrate the location data of heterogeneous recruitment sites from clinical trial documents. The developed system can support effective retrieval and analysis of potential recruitment sites using target clinical trial factors.

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“…Han et al confirmed that NO 2 emerges as the primary environmental factor influencing lung cancer incidence [ 26 ]. Lin et al discovered that the air quality index and annual precipitation levels affect lung cancer, with high incidence seemingly associated with poor air quality and low yearly precipitation [ 28 ]. Merrill et al observed a reduced risk of developing lung cancer and improved patient survival at high altitudes [ 29 ].…”

Section: Introductionmentioning

confidence: 99%

Influence of the atmospheric environment on spatial variation of lung cancer incidence in China

Yu,

Wang,

Yue

et al. 2024

PLoS ONE

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Conducting this research contributes to a deeper understanding of the correlation between atmospheric environmental quality and lung cancer incidence, and provides the scientific basis for formulating effective environmental protection and lung cancer prevention and control strategies. Lung cancer incidence in China has strong spatial variation. However, few studies have systematically revealed the characteristics of the spatial variation in lung cancer incidence, and have explained the causes of this spatial variation in lung cancer incidence from the perspectives of multiple components of the atmospheric environment to explain this spatial variation in lung cancer incidence. To address research limitations, we first analyze the spatial variation and spatial correlation characteristics of lung cancer incidence in China. Then, we build a spatial regression model using GeoDa software with lung cancer incidence as the dependent variable, five atmospheric environment factors—particulate matter 2.5 (PM2.5) concentration, temperature, atmospheric pressure, and elevation as explanatory variables, and four socio-economic characteristics as control variables to systematically analyze the influence and intensity of these factors on lung cancer incidence. The results show that lung cancer incidence in China has apparent changes in geographical and spatial unevenness, and spatial autocorrelation characteristics. In China, the lung cancer incidence is relatively high in Northeast China, while some areas of high lung cancer incidence still exist in Central China, Southwest China and South China, although the overall lung cancer incidence is relatively low. The atmospheric environment significantly affects lung cancer incidence. Different elements of the atmospheric environment vary in the direction and extent of their influence on the development of lung cancer. A 1% increase in PM2.5 concentration is associated with a level of 0.002975 increase in lung cancer incidence. Atmospheric pressure positively affects lung cancer incidence, and an increase in atmospheric pressure by 1% increases lung cancer incidence by a level of 0.026061. Conversely, a 1% increase in temperature is linked to a level of 0.006443 decreases in lung cancer incidence, and a negative correlation exists between elevation and lung cancer incidence, where an increase in elevation by 1% correlates with a decrease in lung cancer incidence by a level of 0.000934. The core influencing factors of lung cancer incidence in the seven geographical divisions of China exhibit variations. This study facilitates our understanding of the spatial variation characteristics of lung cancer incidence in China on a finer scale, while also offering a more diverse perspective on the impact of the atmospheric environment on lung cancer incidence.

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Geographic Distribution and Epidemiology of Lung Cancer During 2011 in Zhejiang Province of China

Cited by 7 publications

References 20 publications

Identifying the Environmental Determinants of Lung Cancer: A Case Study of Henan, China

Identifying the Environmental Determinants of Lung Cancer: A Case Study of Henan, China

Systematic data ingratiation of clinical trial recruitment locations for geographic-based query and visualization

Influence of the atmospheric environment on spatial variation of lung cancer incidence in China

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