Dataset Information

Predictive MERRA-2 aerosol diagnostic model for oral, oropharyngeal and laryngeal cancer caused by air pollution in Thai population.

ABSTRACT:

Introduction

Head and neck cancers were generally characterized with many possible causes. Exposure to outdoor particulate matter affected to multiple organ systems but it was unknown whether which species in PM was an association with cancer incidence.

Objectives

The study aimed to examine the oral- oropharyngeal- laryngeal cancer incidence and accumulated air pollution-related cancers in the spatial patterns.

Methods

Observational study was conducted, and the Poisson log-linear models were used which were analyzed on subgroups-specific incidence rates by national references of Thailand and NASA's database of aerosol diagnostics model (MERRA-2).

Results

With a signiﬁcant inﬂuence on increasing of 1 μg/m³ black carbon, organic carbon, Dust-PM_2.5, and SO₄ were associated with increased cancer risk in 1.433 times (95%CI: 1.215-1.690), 1.272 times (95%CI: 1.139-1.420), 3.640 times (95%CI: 2.011-6.589), and 1.704 times (95%CI: 1.334-2.177), respectively.

Conclusion

This study indicated that oral-oropharyngeal-laryngeal cancer incidence could worsen because of adverse air pollution conditions. These issues should be addressed and the importance of the monitoring procedure for dust-PM_2.5, sulfate, black carbon, and organic carbon should be emphasized.

SUBMITTER: Jenwitheesuk K

PROVIDER: S-EPMC9742832 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Predictive MERRA-2 aerosol diagnostic model for oral, oropharyngeal and laryngeal cancer caused by air pollution in Thai population.

Jenwitheesuk Kriangsak K Peansukwech Udomlack U Jenwitheesuk Kamonwan K

Toxicology reports 20220422

<h4>Introduction</h4>Head and neck cancers were generally characterized with many possible causes. Exposure to outdoor particulate matter affected to multiple organ systems but it was unknown whether which species in PM was an association with cancer incidence.<h4>Objectives</h4>The study aimed to examine the oral- oropharyngeal- laryngeal cancer incidence and accumulated air pollution-related cancers in the spatial patterns.<h4>Methods</h4>Observational study was conducted, and the Poisson log- ...[more]

PMID: 36518436

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Project description:BackgroundDermatitis caused by insects and mites, diagnosed as papular urticaria or scabies, is a common skin disease. However, there is still a lack of studies about the effects of weather and air pollution on outpatient visits for this disease. This study aims to explore the impacts of meteorological and environmental factors on daily visits of dermatitis outpatients.MethodsAnalyses are conducted on a total of 43,101 outpatient visiting records during the years 2015-2020 from the largest dermatology specialist hospital in Guangzhou, China. Hierarchical cluster models based on Pearson correlation between risk factors are utilized to select regression variables. Linear regression models are fitted to identify the statistically significant associations between the risk factors and daily visits, taking into account the short-term effects of temperatures. Permutation importance is adopted to evaluate the predictive ability of these factors.ResultsShort-term temperatures have positive associations with daily visits and exhibit strong predictive abilities. In terms of total outpatients, the one-day lagged temperature not only has a significant impact on daily visits, but also has the highest median value of permutation importance. This conclusion is robust across most subgroups except for subgroups of summer and scabies, wherein the three-day lagged temperature has a negative effect. By contrast, air pollution has insignificant associations with daily visits and exhibits weak predictive abilities. Moreover, weekdays, holidays and trends have significant impacts on daily visits, but with weak predictive abilities.ConclusionsOur study suggests that short-term temperatures have positive associations with daily visits and exhibit strong predictive abilities. Nevertheless, air pollution has insignificant associations with daily visits and exhibits weak predictive abilities. The results of this study provide a reference for local authorities to formulate intervention measures and establish an environment-based disease early warning system.

Project description:BackgroundSeveral studies have shown the health effects of air pollutants, especially in China, North American and Western European countries. But longitudinal cohort studies focused on health effects of long-term air pollution exposure are still limited in Southeast Asian countries where sources of air pollution, weather conditions, and demographic characteristics are different. The present study examined the association between long-term exposure to air pollution and self-reported morbidities in participants of the Thai cohort study (TCS) in Bangkok metropolitan region (BMR), Thailand.MethodsThis longitudinal cohort study was conducted for 9 years from 2005 to 2013. Self-reported morbidities in this study included high blood pressure, high blood cholesterol, and diabetes. Air pollution data were obtained from the Thai government Pollution Control Department (PCD). Particles with diameters ≤10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO) exposures were estimated with ordinary kriging method using 22 background and 7 traffic monitoring stations in BMR during 2005-2013. Long-term exposure periods to air pollution for each subject was averaged as the same period of person-time. Cox proportional hazards models were used to examine the association between long-term air pollution exposure with self-reported high blood pressure, high blood cholesterol, diabetes. Results of self-reported morbidity were presented as hazard ratios (HRs) per interquartile range (IQR) increase in PM10, O3, NO2, SO2, and CO.ResultsAfter controlling for potential confounders, we found that an IQR increase in PM10 was significantly associated with self-reported high blood pressure (HR = 1.13, 95% CI: 1.04, 1.23) and high blood cholesterol (HR = 1.07, 95%CI: 1.02, 1.12), but not with diabetes (HR = 1.05, 95%CI: 0.91, 1.21). SO2 was also positively associated with self-reported high blood pressure (HR = 1.22, 95%CI: 1.08, 1.38), high blood cholesterol (HR = 1.20, 95%CI: 1.11, 1.30), and diabetes (HR = 1.21, 95%CI: 0.92, 1.60). Moreover, we observed a positive association between CO and self-reported high blood pressure (HR = 1.07, 95%CI: 1.00, 1.15), but not for other diseases. However, self-reported morbidities were not associated with O3 and NO2.ConclusionsLong-term exposure to air pollution, especially for PM10 and SO2 was associated with self-reported high blood pressure, high blood cholesterol, and diabetes in subjects of TCS. Our study supports that exposure to air pollution increases cardiovascular disease risk factors for younger population.

Dataset Information

Predictive MERRA-2 aerosol diagnostic model for oral, oropharyngeal and laryngeal cancer caused by air pollution in Thai population.

Introduction

Objectives

Methods

Results

Conclusion

Publications

Predictive MERRA-2 aerosol diagnostic model for oral, oropharyngeal and laryngeal cancer caused by air pollution in Thai population.

Similar Datasets

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