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Studying the Impact of Air Pollution and Pesticide Mixtures on Respiratory Health in Fresno and Tulare Counties of Central California.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Studying the Impact of Air Pollution and Pesticide Mixtures on Respiratory Health in Fresno and Tulare Counties of Central California./
作者:	Hughes, Matthew Lawrence.
面頁冊數:	1 online resource (101 pages)
附註:	Source: Masters Abstracts International, Volume: 83-12.
Contained By:	Masters Abstracts International83-12.
標題:	Environmental health. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29067341click for full text (PQDT)
ISBN:	9798438794479

Studying the Impact of Air Pollution and Pesticide Mixtures on Respiratory Health in Fresno and Tulare Counties of Central California.
Hughes, Matthew Lawrence.

Studying the Impact of Air Pollution and Pesticide Mixtures on Respiratory Health in Fresno and Tulare Counties of Central California. - 1 online resource (101 pages)

Source: Masters Abstracts International, Volume: 83-12.

Thesis (M.S.)--Colorado State University, 2022.

Includes bibliographical references

Residents of California's Central Valley are exposed to some of the worst air quality in the United States, as well as high levels of pesticides owing to the region's large agricultural economy. There is ample evidence that exposure to air pollution is associated with adverse respiratory health outcomes, and some evidence from occupational and community-based studies that exposure to pesticides has negative impacts on respiratory health as well. Epidemiologic research on air pollution and pesticides often considers these exposures one at a time in relation to health outcomes, but humans are exposed to pollutants simultaneously in mixtures. In this study we used multiple linear regression models to look at linear relationships of three criteria air pollutants and biomarkers of organophosphates (dialkyl-phosphates or DAPs) with urinary leukotriene E4 (LTE4), a biomarker of respiratory inflammation, in participants in four Central California communities (n=80). We then used Bayesian Kernel Machine Regression models to study these criteria air pollutants and DAPs as a mixture and determine if this mixture had a relationship with respiratory health in this population. We also studied these relationships at two different times of the year (January and June) to study whether and how this relationship between an air pollution-pesticide mixture and the respiratory health outcome changed seasonally. Our multiple linear regression models revealed that dimethyl-phosphates had a statistically significant association with respiratory health in January, which suggests that LTE4 can be used as a biomarker for respiratory inflammation in populations with low asthma prevalence. The results of our BKMR analysis were not statistically significant but did suggest interactions between the exposures in our air pollution-pesticide mixture. Despite a small sample size, this study adds to the limited research on environmental mixtures, and the effects of pesticide exposure on respiratory health.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798438794479Subjects--Topical Terms:

543032
Environmental health.
Subjects--Index Terms:

Air pollutionIndex Terms--Genre/Form:

542853
Electronic books.

Studying the Impact of Air Pollution and Pesticide Mixtures on Respiratory Health in Fresno and Tulare Counties of Central California.
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520 $a Residents of California's Central Valley are exposed to some of the worst air quality in the United States, as well as high levels of pesticides owing to the region's large agricultural economy. There is ample evidence that exposure to air pollution is associated with adverse respiratory health outcomes, and some evidence from occupational and community-based studies that exposure to pesticides has negative impacts on respiratory health as well. Epidemiologic research on air pollution and pesticides often considers these exposures one at a time in relation to health outcomes, but humans are exposed to pollutants simultaneously in mixtures. In this study we used multiple linear regression models to look at linear relationships of three criteria air pollutants and biomarkers of organophosphates (dialkyl-phosphates or DAPs) with urinary leukotriene E4 (LTE4), a biomarker of respiratory inflammation, in participants in four Central California communities (n=80). We then used Bayesian Kernel Machine Regression models to study these criteria air pollutants and DAPs as a mixture and determine if this mixture had a relationship with respiratory health in this population. We also studied these relationships at two different times of the year (January and June) to study whether and how this relationship between an air pollution-pesticide mixture and the respiratory health outcome changed seasonally. Our multiple linear regression models revealed that dimethyl-phosphates had a statistically significant association with respiratory health in January, which suggests that LTE4 can be used as a biomarker for respiratory inflammation in populations with low asthma prevalence. The results of our BKMR analysis were not statistically significant but did suggest interactions between the exposures in our air pollution-pesticide mixture. Despite a small sample size, this study adds to the limited research on environmental mixtures, and the effects of pesticide exposure on respiratory health.
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