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Factors related to undiagnosed diabetes and prediabetes in Asian Americans: A cross-sectional analysis of NHANES 2011-2016
Descriptive
TitleInfo
Title
Factors related to undiagnosed diabetes and prediabetes in Asian Americans: A cross-sectional analysis of NHANES 2011-2016
Name
(type = personal)
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(type = family)
Lee
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(type = given)
Euny C.
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(type = date)
1979-
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Euny C. Lee
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author
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Coffman
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Frederick
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Frederick Coffman
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Advisory Committee
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chair
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Srinivasan
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Shankar
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Shankar Srinivasan
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Advisory Committee
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internal member
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Arniella
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Guedy
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Guedy Arniella
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Advisory Committee
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outside member
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Rubinstein
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Pesha
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Pesha Rubinstein
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Advisory Committee
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outside member
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Rutgers University
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degree grantor
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School of Health Professions
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school
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Text
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theses
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2019
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2019-08
Language
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(type = text)
English
Abstract
(type = abstract)
OBJECTIVES: Asian Americans, the fastest-growing race in the U.S., are disproportionately affected by diabetes (DM), particularly undiagnosed DM (51% of all diabetes cases) and prediabetes. The goal of this study was to examine differences and identify predictors in social determinants of health factors and health-related factors associated with undiagnosed diabetes, diagnosed diabetes, prediabetes, and no diabetes/prediabetes among Asian Americans.
METHODS: Three cycles of National Health and Nutrition Examination Survey (NHANES) from 2011-2016 were analyzed for exploratory and inferential statistics—using the chi-square test of independence, linear regression and multinomial logistic regression models—to assess the associations and predictive factors (i.e., Social Determinants of Health, obesity, HbA1c, and sleep) in those with undiagnosed diabetes, diagnosed diabetes, prediabetes, and no diabetes/prediabetes among Asian Americans (n=1,685).
RESULTS: Diabetes estimates—both undiagnosed and diagnosed—were different when stratifying by nativity (U.S.-born vs. foreign-born). Differences in age (p<.001), marital status (p<.001), education(p<.001), acculturation (p=0.010), poverty (p=0.009), regular healthcare provider (p<.001), overweight/obese body mass index (BMI) (p<.001), and sleep duration (p=0.033) were observed. Education was a significant predictor especially when comparing those who attained college degrees or higher to high school graduates; they are 3.3 times more likely to have no diabetes or prediabetes compared to undiagnosed diabetes (p=0.0031) OR: 3.337, (CI: 1.534 to 7.261). In addition, those who had some college or an Associate’s degree when compared to high school graduates were 2.5 times more likely to not have diabetes/prediabetes compared to having undiagnosed diabetes (p=0.0453), OR: 2.497 (CI:1.020 to 6.112).
CONCLUSIONS: This study suggests that BMI is an inadequate predictor of diabetes—either diagnosed or undiagnosed—and prediabetes. Nativity, gender, education, regular healthcare provider and sleep duration are potential factors that need to be considered when developing interventions, preventive strategies, and clinical guidelines for Asian Americans.
METHODS: Three cycles of National Health and Nutrition Examination Survey (NHANES) from 2011-2016 were analyzed for exploratory and inferential statistics—using the chi-square test of independence, linear regression and multinomial logistic regression models—to assess the associations and predictive factors (i.e., Social Determinants of Health, obesity, HbA1c, and sleep) in those with undiagnosed diabetes, diagnosed diabetes, prediabetes, and no diabetes/prediabetes among Asian Americans (n=1,685).
RESULTS: Diabetes estimates—both undiagnosed and diagnosed—were different when stratifying by nativity (U.S.-born vs. foreign-born). Differences in age (p<.001), marital status (p<.001), education(p<.001), acculturation (p=0.010), poverty (p=0.009), regular healthcare provider (p<.001), overweight/obese body mass index (BMI) (p<.001), and sleep duration (p=0.033) were observed. Education was a significant predictor especially when comparing those who attained college degrees or higher to high school graduates; they are 3.3 times more likely to have no diabetes or prediabetes compared to undiagnosed diabetes (p=0.0031) OR: 3.337, (CI: 1.534 to 7.261). In addition, those who had some college or an Associate’s degree when compared to high school graduates were 2.5 times more likely to not have diabetes/prediabetes compared to having undiagnosed diabetes (p=0.0453), OR: 2.497 (CI:1.020 to 6.112).
CONCLUSIONS: This study suggests that BMI is an inadequate predictor of diabetes—either diagnosed or undiagnosed—and prediabetes. Nativity, gender, education, regular healthcare provider and sleep duration are potential factors that need to be considered when developing interventions, preventive strategies, and clinical guidelines for Asian Americans.
Subject
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Topic
Biomedical Informatics
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Title
Rutgers University Electronic Theses and Dissertations
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ETD
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ETD_10173
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application/pdf
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text/xml
Extent
1 onlione resource (104 pages) : illustrations
Note
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Ph.D.
Note
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Includes bibliographical references
Subject
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Topic
EHR
Subject
(authority = LCSH)
Topic
Diabetes -- Diagnosis
Subject
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Topic
Asian Americans -- Health and hygiene
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TitleInfo
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School of Health Professions ETD Collection
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rucore10007400001
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NjNbRU
Identifier
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doi:10.7282/t3-fjv3-ec38
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ETD doctoral
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Rights
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The author owns the copyright to this work.
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Name
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Lee
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Euny
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Permission or license
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2019-08-19 13:23:17
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Euny Lee
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Rutgers University. School of Health Professions
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Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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RULTechMD
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windows xp
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2019-08-19T13:15:45
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2019-08-19T13:15:45
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