Reduced Lung Cancer Mortality With Lower Atmospheric Pressure

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.

Exploring the Link between Altitude of Residence and Smoking Patterns in the United States

INTRODUCTION

Smoking-related diseases affect 16 million Americans, causing approximately 480,000 deaths annually. The prevalence of cigarette smoking varies regionally across the United States, and previous research indicates that regional rates of smoking-related diseases demonstrate a negative association with altitude. The purpose of this study was to determine the relationship between altitude and the prevalence of cigarette smoking by county (N = 3106) in the United States. We hypothesized that smoking prevalence among adults would be negatively associated with mean county altitude.

METHODS

A multivariate linear regression was performed to examine the relationship between county-level mean altitude and county smoking rate. Covariates were individually correlated with 2020 smoking data, and significant associations were included in the final model.

RESULTS

The multivariate linear regression indicated that the county-level smoking rates are significantly reduced at high altitudes (p < 0.001). The model accounted for 89.5% of the variance in smoking prevalence, and for each 1000-foot increase in altitude above sea level, smoking rates decreased by 0.143%. Based on multivariate linear regression, the following variables remained independently and significantly associated: race, sex, educational attainment, socioeconomic status, unemployment, physical inactivity, drinking behavior, mental distress, and tobacco taxation.

CONCLUSIONS

Our results indicate that smoking rates are negatively associated with altitude, which may suggest that altitude affects the pharmacokinetics, pharmacodynamics, and mechanistic pathways involved in cigarette use. Further research is needed to explore the relationship between altitude and smoking and how altitude may serve as a protective factor in the acquisition and maintenance of tobacco use disorders.

Geographical distinctions of longevity indicators and their correlation with climatic factors in the area where most Chinese Yao are distributed

Longevity research is a hot topic in the health field. Considerable research focuses on longevity phenomenon in Bama Yao Autonomous County, which has a typical karst landform and is located in Southwest China. This study aims to illustrate the spatial feature of longevity indicators in other Yao areas, to analyze the correlation between climatic factors and longevity indicators, and to provide new clues and targets for further longevity studies. We collect and integrate population, climate, and terrain data into a spatial database. The main analysis methods include spatial autocorrelation, high/low clustering, and multiscale geographically weighted regression (MGWR). Two longevity clusters are identified in Guijiang River Basin (longevity index (LI%): 2.49 ± 0.63) and Liujiang River Basin (LI%: 2.13 ± 0.60). The spatial distribution of longevity indicators is autocorrelative (Moran's I = 0.652, p < 0.001) and clustered significantly (Z score = 4.268, p < 0.001). MGWR shows that the atmospheric pressure significantly affects the spatial distribution of LI% (estimate value (EV) =  - 0.566, p = 0.012), centenarity index (CI%) (EV =  - 0.425, p = 0.007), UC (EV =  - 0.502, p = 0.006), and CH (EV =  - 0.497, p = 0.007). Rainfall significantly affects the spatial distribution of LI% (EV = 0.300, p = 0.003) and CI% (EV =  - 0.191, p = 0.016). The spatial distribution of the main longevity indicators shows significant heterogeneity and autocorrelation, and they cluster in the Guijiang River and Liujiang River basins. Atmospheric pressure and rainfall may contribute to the longevity phenomenon through complex mechanisms. The longevity phenomenon in the Yao nationality in Guijiang River Basin requires further study to improve our understanding of the health effect of meteorological, environmental, and social conditions on longevity.

The Oxygen Transport Triad in High-Altitude Pulmonary Edema: A Perspective from the High Andes

Acute high-altitude illnesses are of great concern for physicians and people traveling to high altitude. Our recent article "Acute Mountain Sickness, High-Altitude Pulmonary Edema and High-Altitude Cerebral Edema, a View from the High Andes" was questioned by some sea-level high-altitude experts. As a result of this, we answer some observations and further explain our opinion on these diseases. High-Altitude Pulmonary Edema (HAPE) can be better understood through the Oxygen Transport Triad, which involves the pneumo-dynamic pump (ventilation), the hemo-dynamic pump (heart and circulation), and hemoglobin. The two pumps are the first physiologic response upon initial exposure to hypobaric hypoxia. Hemoglobin is the balancing energy-saving time-evolving equilibrating factor. The acid-base balance must be adequately interpreted using the high-altitude Van Slyke correction factors. Pulse-oximetry measurements during breath-holding at high altitude allow for the evaluation of high altitude diseases. The Tolerance to Hypoxia Formula shows that, paradoxically, the higher the altitude, the more tolerance to hypoxia. In order to survive, all organisms adapt physiologically and optimally to the high-altitude environment, and there cannot be any "loss of adaptation". A favorable evolution in HAPE and pulmonary hypertension can result from the oxygen treatment along with other measures.