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Light at Night and Cancer Incidence:...

Lyu, Linshuoshuo.

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Light at Night and Cancer Incidence: A GIS-Based Study in the US.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Light at Night and Cancer Incidence: A GIS-Based Study in the US./
作者:	Lyu, Linshuoshuo.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2024,
面頁冊數:	45 p.
附註:	Source: Masters Abstracts International, Volume: 85-11.
Contained By:	Masters Abstracts International85-11.
標題:	Epidemiology. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31243285
ISBN:	9798382456355

Light at Night and Cancer Incidence: A GIS-Based Study in the US.
Lyu, Linshuoshuo.

Light at Night and Cancer Incidence: A GIS-Based Study in the US. - Ann Arbor : ProQuest Dissertations & Theses, 2024 - 45 p.

Source: Masters Abstracts International, Volume: 85-11.

Thesis (M.P.H.)--Yale University, 2024.

Aims: Light at night (LAN) can cause circadian disruption and was found to be a potential risk factor for several cancers. This study aims to confirm the adverse effect of LAN on hormone-related cancers and explore the association between LAN and the prevalence of various cancer types under an ecological study design. Methods: County-level age-adjusted cancer incidence data was obtained from the CDC Cancer Statistics (2016 to 2020), while LAN data (1996 to 2000) was obtained from the satellite imagery of Version 4 Defense Meteorological Satellite Program. Linear mixed effect regression models (LMMs) were performed to assess the relationship of LAN with 25 individual cancer types and cancer of all sites. Both univariable and multivariable regression analysis were conducted. In addition to modeling the continuous LAN exposure, the LAN level was categorized into three groups and modeled to assess the potential non-linear relationship with cancers. Results: Through LMMs analysis, I found that prevalence cancer of all sites and hormone-related cancer, especially female breast (correlation coefficient = 0.42; crude beta = 0.04, p after correction = 3.99E-13) and prostate cancer (correlation coefficient = 0.5; crude beta = 0.05, p after correction =1.61E-06), were positively associated with LAN. Some cancers in the digestive system (colon and rectum, esophagus) and urogenital system (cervix, corpus and uterus, ovary, kidney and renal pelvis, testis, and urinary bladder) were negatively associated with LAN. Similar results were detected in categorical models, while the most significant associations were observed in the highest LAN exposure level. Conclusions: The study evaluates LAN in relation to various cancer types based on large populations, providing clues for future epidemiological and experimental studies. It also indicated different directions of associations of LAN and cancer across different tumor sites. Further studies are warranted to reveal the complex mechanism of LAN on different cancer types.

ISBN: 9798382456355Subjects--Topical Terms:

568544
Epidemiology.
Subjects--Index Terms:

Cancers

Light at Night and Cancer Incidence: A GIS-Based Study in the US.
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500 $a Source: Masters Abstracts International, Volume: 85-11.
500 $a Advisor: Deziel, Nicole.
502 $a Thesis (M.P.H.)--Yale University, 2024.
520 $a Aims: Light at night (LAN) can cause circadian disruption and was found to be a potential risk factor for several cancers. This study aims to confirm the adverse effect of LAN on hormone-related cancers and explore the association between LAN and the prevalence of various cancer types under an ecological study design. Methods: County-level age-adjusted cancer incidence data was obtained from the CDC Cancer Statistics (2016 to 2020), while LAN data (1996 to 2000) was obtained from the satellite imagery of Version 4 Defense Meteorological Satellite Program. Linear mixed effect regression models (LMMs) were performed to assess the relationship of LAN with 25 individual cancer types and cancer of all sites. Both univariable and multivariable regression analysis were conducted. In addition to modeling the continuous LAN exposure, the LAN level was categorized into three groups and modeled to assess the potential non-linear relationship with cancers. Results: Through LMMs analysis, I found that prevalence cancer of all sites and hormone-related cancer, especially female breast (correlation coefficient = 0.42; crude beta = 0.04, p after correction = 3.99E-13) and prostate cancer (correlation coefficient = 0.5; crude beta = 0.05, p after correction =1.61E-06), were positively associated with LAN. Some cancers in the digestive system (colon and rectum, esophagus) and urogenital system (cervix, corpus and uterus, ovary, kidney and renal pelvis, testis, and urinary bladder) were negatively associated with LAN. Similar results were detected in categorical models, while the most significant associations were observed in the highest LAN exposure level. Conclusions: The study evaluates LAN in relation to various cancer types based on large populations, providing clues for future epidemiological and experimental studies. It also indicated different directions of associations of LAN and cancer across different tumor sites. Further studies are warranted to reveal the complex mechanism of LAN on different cancer types.
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