Estimating the spatial distribution of environmental suitability for female lung cancer mortality in China based on a novel statistical method

Effect of forest cover on lung cancer incidence: a case study in Southwest China

Introduction

Forests are closely linked to human health, particularly about lung cancer incidence. However, there is currently limited research on how forest coverage and different types of forests influence lung cancer rates. This study aims to address this gap by examining how the coverage of various forest types impacts lung cancer incidence in Southwest China, thereby providing theoretical support for health-oriented forest structure planning.

Methods

We focused on 438 counties in Southwest China, employing spatial autocorrelation analysis (Moran's I) and spatial regression models [including Spatial Lag Model (SLM), Spatial Error Model (SEM), and Spatial Durbin Model (SDM)] to explore the effects of forest coverage and internal forest structure on lung cancer incidence. We used ArcGIS to visualize lung cancer incidence and forest coverage rates across the study area.

Results

The study found a significant negative correlation between forest coverage and lung cancer incidence. Specifically, for every 1% increase in forest coverage, lung cancer incidence decreased by 0.017 levels. Evergreen forests and mixed forests showed a significant negative impact on lung cancer rates, with evergreen forests having a particularly strong effect; a 1% increase in evergreen forest coverage was associated with a 0.027 level decrease in lung cancer incidence. In contrast, deciduous forests had no significant impact. Additionally, the study revealed a marked spatial heterogeneity in lung cancer incidence and forest coverage across Southwest China: higher lung cancer rates were observed in the eastern regions, while forest coverage was predominantly concentrated in the western and southern regions.

Discussion

This study demonstrates that increasing forest coverage, particularly of evergreen and mixed forests, can help reduce lung cancer incidence. This effect may be related to the ability of forests to absorb harmful gasses and particulate matter from the air. Furthermore, the spatial heterogeneity in lung cancer incidence suggests that regional economic development levels and urbanization processes may also play significant roles in the spatial distribution of lung cancer rates. The findings provide empirical support for the development of targeted forest conservation and development policies aimed at optimizing regional forest structures to reduce the risk of lung cancer.

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

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.

Spatial pattern and environmental drivers of breast cancer incidence in Chinese women

Breast cancer (BC) had the highest incidence of all cancers in Chinese women. However, studies on spatial pattern and environmental drivers of BC were still lacked as they were either limited in a small area or few considered the comprehensive impact of multiple risk factors. In this study, we firstly performed spatial visualization and the spatial autocorrelation analysis based on Chinese women breast cancer incidence (BCI) data of 2012-2016. Then, we explored the environmental drivers related to BC by applying univariate correlation analysis and geographical detector model. We found that the BC high-high clusters were mainly distributed in the eastern and central regions, such as Liaoning, Hebei, Shandong, Henan, and Anhui Provinces. The BCI in Shenzhen was significantly higher than other prefectures. Urbanization rate (UR), per capita GDP (PGDP), average years of school attainment (AYSA), and average annual wind speed (WIND) had higher explanatory power on spatial variability of the BCI. PM10, NO2, and PGDP had significant nonlinear enhanced effect on other factors. Besides, normalized difference vegetation index (NDVI) was negatively associated with BCI. Therefore, high socioeconomic status, serious air pollution, high wind speed, and low vegetation cover were the risk factors for BC. Our study may able to provide evidence for BC etiology research and precise identification of areas requiring focused screening.

Comparative study on the gastrointestinal- and immune- regulation functions of Hedysari Radix Paeparata Cum Melle and Astragali Radix Praeparata cum Melle in rats with spleen-qi deficiency, based on fuzzy matter-element analysis

CONTEXT

Hedysari Radix Praeparata Cum Melle (HRPCM) and Astragali Radix Praeparata Cum Melle (ARPCM) are used interchangeably in clinics to treat spleen-qi deficiency (SQD) symptom mainly including gastrointestinal dysfunction and decreased immunity, which has unknown differences in efficacy.

OBJECTIVE

To investigate the differences between HRPCM and ARPCM on intervening gastrointestinal- and immune-function with SQD syndrome.

MATERIALS AND METHODS

After the SQD model was established, the Sprague-Dawley (SD) rats were randomly divided into nine groups (n = 10): normal; model; Bu-Zhong-Yi-Qi Pills; 18.9, 12.6 and 6.3 g/kg dose groups of HRPCM and ARPCM. Gastrointestinal function including d-xylose, gastrin, amylase vasoactive intestinal peptide, motilin, pepsin, H⁺/K⁺-ATPase, Na⁺/K⁺-ATPase, sodium-glucose cotransporter 1 (SGLT1), glucose transporter 2 (GLUT2) and immune function including spleen and thymus index, blood routine, interleukin (IL)-2, IL-6, interferon-γ (IFN-γ), tumour necrosis factor-α (TNF-α), immunoglobulin (Ig) M, IgA, IgG and delayed-type hypersensitivity (DTH) were detected. Finally, the efficacy differences were analysed comprehensively by the fuzzy matter-element method.

RESULTS

In regulating immune, the doses differences in efficacy between HRPCM and ARPCM showed in the high-dose (18.9 g/kg), but there were no differences in the middle- and low- dose (12.6 and 6.37 g/kg); the efficacy differences were primarily reflected in levels of IL-6, IFN-γ, TNF-α and IgM in serum, and the mRNA expression of IL-6 and IFN-γ in the spleen. In regulating gastrointestinal, the efficacy differences were primarily reflected in the levels of D-xylose, MTL, and GAS in serum, and the mRNA and protein expression of SGLT1 and GLUT2 in jejunum and ileum.

DISCUSSION AND CONCLUSIONS

HRPCM is more effective than ARPCM on regulating gastrointestinal function and immune function with SQD syndrome. Therefore, we propose that HRPCM should be mainly used to treat SQD syndrome in the future.

Clinical characteristics of non-small cell lung cancer patients with EGFR mutations and ALK&ROS1 fusions

OBJECTIVE

To study the relationship between clinical characteristics and anaplastic lymphoma kinase (ALK) fusions, c-ros oncogene 1, receptor tyrosine kinase (ROS1) gene fusions, and epidermic growth factor receptor (EGFR) mutations in non-small cell lung cancer (NSCLC) patients to distinguish these different types.

METHODS

Both ALK, ROS1 gene rearrangements and EGFR mutations testing were performed. The clinical characteristics and associated pulmonary abnormalities were investigated.

RESULTS

Four hundred fifty-three NSCLC patients were included for analysis. One hundred seventy (37.5%), 32 (7.1%), and 9 cases (2.0%) with EGFR mutations, ALK gene fusions, and ROS1 gene fusions were identified, respectively. The EGFR-positive and ALK&ROS1-positive were more common in female (χ2  = 61.934, P < 0.001 and χ2  = 28.152, P < 0.001), non-smoking (χ2  = 59.315, P < 0.001 and χ2  = 11.080, P = 0.001), and adenocarcinoma (χ2  = 44.864, P < 0.001 and χ2  = 12.318, P = 0.002) patients; proportion of patients with emphysema was lower (χ2  = 35.494, P < 0.001 and χ2  = 15.770, P < 0.001) than the wild-type patients. The results of logistic regression analysis indicated that female (adjusted odds ratio [OR] 1.834, 95% confidence interval [CI] 1.069-3.144, P = 0.028), non-smoking (adjusted OR 2.504, 95% CI 1.456-4.306, P = 0.001), lung adenocarcinoma (adjusted OR 4.512, 95% CI 2.465-8.260, P < 0.001), stage III-IV (adjusted OR 2.232, 95% CI 1.066-4.676, P = 0.033), and no symptoms of emphysema (adjusted OR 2.139, 95% CI 1.221-3.747, P = 0.008) were independent variables associated with EGFR mutations. Young (adjusted OR 3.947, 95% CI 1.873-8.314, P < 0.001) and lung adenocarcinoma (adjusted OR 2.950, 95% CI 0.998-8.719, P = 0.050) were associated with ALK/ROS1 fusions.

CONCLUSIONS

EGFR mutations were more likely to occur in non-smoking, stage III-IV, and female patients with lung adenocarcinoma, whereas ALK&ROS1 gene fusions were more likely to occur in young patients with lung adenocarcinoma. Emphysema was less common in patients with EGFR mutations.

Using Multisource Data to Assess PM2.5 Exposure and Spatial Analysis of Lung Cancer in Guangzhou, China

Elevated air pollution, along with rapid urbanization, have imposed higher health risks and a higher disease burden on urban residents. To accurately assess the increasing exposure risk and the spatial association between PM_2.5 and lung cancer incidence, this study integrated PM_2.5 data from the National Air Quality Monitoring Platform and location-based service (LBS) data to introduce an improved PM_2.5 exposure model for high-precision spatial assessment of Guangzhou, China. In this context, the spatial autocorrelation method was used to evaluate the spatial correlation between lung cancer incidence and PM_2.5. The results showed that people in densely populated areas suffered from higher exposure risk, and the spatial distribution of population exposure risk was highly consistent with the dynamic distribution of the population. In addition, areas with PM_2.5 roughly overlapped with areas with high lung cancer incidence, and the lung cancer incidence in different locations was not randomly distributed, confirming that lung cancer incidence was significantly associated with PM_2.5 exposure. Therefore, dynamic population distribution has a great impact on the accurate assessment of environmental exposure and health burden, and it is necessary to use LBS data to improve the exposure assessment model. More mitigation controls are needed in highly populated and highly polluted areas.

Distance to highway and factory density related to lung cancer death and associated spatial heterogeneity in effects in Jiading District, Shanghai

This study aimed to determine the spatial effects of traffic- and industrial-related pollution on the mortality for lung cancer (LC). We conducted a retrospective cohort study by using the data from LC registry in Jiading District for the period from 2002 to 2012. Standard parametric model with Weibull distribution was used for spatial survival analysis. Shorter distance to highway (adjusted odds ratio (aOR) = 1.15, 95% confidence interval (CI): 1.03-1.30) and higher factory density (aOR = 1.20, 95% CI: 1.05-1.37) were significantly associated with an increased risk of LC death, and there was a spatial difference in the associations between northern and southern areas of Jiading District. The risk was high in suburbs as compared with urban areas. Traffic- and industrial-related pollution were significantly associated with an increased risk of LC death, which showed a spatial variation. Further studies are needed to better understand the current LC status in the suburbs and to reduce health disparities.