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Evaluating Spatial Relationships Between Environmental Factors and Contextual Sociodemographic Burden and Associations with Respiratory Morbidity Among Young Children : = An Indicator-Based Approach.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Evaluating Spatial Relationships Between Environmental Factors and Contextual Sociodemographic Burden and Associations with Respiratory Morbidity Among Young Children :/
其他題名:	An Indicator-Based Approach.
作者:	Muscatiello, Neil A.
面頁冊數:	1 online resource (129 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-10, Section: B.
Contained By:	Dissertations Abstracts International84-10B.
標題:	Environmental health. -
電子資源:	click for full text (PQDT)
ISBN:	9798379423995

Evaluating Spatial Relationships Between Environmental Factors and Contextual Sociodemographic Burden and Associations with Respiratory Morbidity Among Young Children : = An Indicator-Based Approach.
Muscatiello, Neil A.

Evaluating Spatial Relationships Between Environmental Factors and Contextual Sociodemographic Burden and Associations with Respiratory Morbidity Among Young Children :An Indicator-Based Approach. - 1 online resource (129 pages)

Source: Dissertations Abstracts International, Volume: 84-10, Section: B.

Thesis (Ph.D.)--State University of New York at Albany, 2023.

Includes bibliographical references

The body of public health literature related to air pollution epidemiology is extensive. Similarly, the body of literature related to social epidemiology has also expanded greatly in recent years. While studies in these sub-disciplines of epidemiology sometimes seek to control for variables more commonly studied in one or the other, fewer studies report on their combined effects. Studies which do attempt to summarize how the combined air pollution burden and contextual sociodemographic burden differentially effect health outcomes beyond their individual effects could be beneficial in understanding links between the environment and certain health outcomes such as childhood asthma. The proposed work is novel in that while many studies of asthma and the environment have focused on outdoor or sociodemographic exposure indicators, fewer studies have linked data from the indoor and outdoor environment with sociodemographic data to explore interrelationships between these factors. In the work that follows, Chapter 1 provides a more detailed background for the studies and analyses conducted in Chapters 2, 3, and 4. Chapter 5 summarizes the findings collectively and suggests additional analyses that could be done. In addition, the analyses in Chapters 3 and 4 study focus on areas of NYS excluding NYC, large parts of which are rural and which have been studied less frequently.Chapter 2 explored different methods for combining multiple indicators to create a summary composite index representing outdoor air pollution and contextual sociodemographic burden, while not necessarily having a particular health outcome in mind. Geographic locations where increased concentrations of air pollutants overlap with areas of social vulnerability are important in understanding the intersection between air pollution epidemiology and social determinants of health. Three statistical methods were evaluated to develop combined outdoor air pollution and contextual sociodemographic burden classifications, and the results were compared and contrasted. Two methods used clustering techniques and one method used ranked quantiles. The three methods were consistent in creating outdoor air pollution categories or clusters that separate urban and rural areas of NYS. There was more variation in how urban areas were classified. The results may be useful in environmental health surveillance and research, including situational awareness for community investigations and screening to identify areas with disadvantaged and disproportionally impacted populations. Further analysis of cluster results could identify statistical associations unique to particular clusters and health outcomes of interest, while analysis of ranked results might more likely ask whether there are associations between increasing ranks and health outcomes of interest.The study detailed in Chapter 3 explored associations between maternal reporting of exposure to indoor air pollutant hazards and wheeze through age 1. This census tract-based ecologic study found significant associations between counts of respiratory morbidity among children 0-4 and indicators of outdoor air pollution and contextual sociodemographic burden. Despite this finding, a substantial proportion of the variance in census tract respiratory morbidity counts was not explained by the variables included in the models. This is not necessarily unexpected, given that respiratory morbidities have complex and multifactorial etiologies that include genetic and environmental risk factors, some of which among the latter are more associated with indoor air quality which was not considered in this study. Understanding community level associations can be helpful in identifying and implementing interventions.The analyses in Chapter 4 explored associations between maternal reporting of exposure to indoor air pollutant hazards and wheeze through age 1. The study found an association between parental asthma and reports of persistent wheeze through age 1 among children of the Upstate KIDS Study. Individual level variables characterizing indoor environmental hazards and sociodemographic factors were not significant in final multivariate models. Community level outdoor air pollution and sociodemographic burden index variable was not significant in final models, nor did the addition of this variable substantial impact associations for the individual level variables.As outlined in Chapter 5, better characterization of both environmental exposures and sociodemographic variables to be helpful to better inform analyses. However, these results can assist in identifying small areas that experience a greater burden from outdoor air pollutants and which may also be disadvantaged socioeconomically. Existing efforts in NYS and in other states already provide examples of potential applications, including use in the development of effective policies. Next steps can include discussions with public health partners as a resource for interventions at the local level.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798379423995Subjects--Topical Terms:

569475
Environmental health.
Subjects--Index Terms:

Sociodemographic burdenIndex Terms--Genre/Form:

554714
Electronic books.

Evaluating Spatial Relationships Between Environmental Factors and Contextual Sociodemographic Burden and Associations with Respiratory Morbidity Among Young Children : = An Indicator-Based Approach.
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In the work that follows, Chapter 1 provides a more detailed background for the studies and analyses conducted in Chapters 2, 3, and 4. Chapter 5 summarizes the findings collectively and suggests additional analyses that could be done. In addition, the analyses in Chapters 3 and 4 study focus on areas of NYS excluding NYC, large parts of which are rural and which have been studied less frequently.Chapter 2 explored different methods for combining multiple indicators to create a summary composite index representing outdoor air pollution and contextual sociodemographic burden, while not necessarily having a particular health outcome in mind. Geographic locations where increased concentrations of air pollutants overlap with areas of social vulnerability are important in understanding the intersection between air pollution epidemiology and social determinants of health. Three statistical methods were evaluated to develop combined outdoor air pollution and contextual sociodemographic burden classifications, and the results were compared and contrasted. Two methods used clustering techniques and one method used ranked quantiles. The three methods were consistent in creating outdoor air pollution categories or clusters that separate urban and rural areas of NYS. There was more variation in how urban areas were classified. The results may be useful in environmental health surveillance and research, including situational awareness for community investigations and screening to identify areas with disadvantaged and disproportionally impacted populations. Further analysis of cluster results could identify statistical associations unique to particular clusters and health outcomes of interest, while analysis of ranked results might more likely ask whether there are associations between increasing ranks and health outcomes of interest.The study detailed in Chapter 3 explored associations between maternal reporting of exposure to indoor air pollutant hazards and wheeze through age 1. This census tract-based ecologic study found significant associations between counts of respiratory morbidity among children 0-4 and indicators of outdoor air pollution and contextual sociodemographic burden. Despite this finding, a substantial proportion of the variance in census tract respiratory morbidity counts was not explained by the variables included in the models. This is not necessarily unexpected, given that respiratory morbidities have complex and multifactorial etiologies that include genetic and environmental risk factors, some of which among the latter are more associated with indoor air quality which was not considered in this study. Understanding community level associations can be helpful in identifying and implementing interventions.The analyses in Chapter 4 explored associations between maternal reporting of exposure to indoor air pollutant hazards and wheeze through age 1. The study found an association between parental asthma and reports of persistent wheeze through age 1 among children of the Upstate KIDS Study. Individual level variables characterizing indoor environmental hazards and sociodemographic factors were not significant in final multivariate models. Community level outdoor air pollution and sociodemographic burden index variable was not significant in final models, nor did the addition of this variable substantial impact associations for the individual level variables.As outlined in Chapter 5, better characterization of both environmental exposures and sociodemographic variables to be helpful to better inform analyses. However, these results can assist in identifying small areas that experience a greater burden from outdoor air pollutants and which may also be disadvantaged socioeconomically. Existing efforts in NYS and in other states already provide examples of potential applications, including use in the development of effective policies. Next steps can include discussions with public health partners as a resource for interventions at the local level.
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