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Assessing the impact of social determinants of health on diabetes severity and management
by
Kharrazi, Hadi
, Nishimura, Akihiko
, Ding, Xiyu
in
Analysis
/ Blood sugar
/ Brief Communications
/ Diabetes
/ Diabetes therapy
/ Disease management
/ Electronic records
/ Glycosylated hemoglobin
/ Health care industry
/ Medical records
/ Observational studies
/ Prevention
/ Type 2 diabetes
2024
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Assessing the impact of social determinants of health on diabetes severity and management
by
Kharrazi, Hadi
, Nishimura, Akihiko
, Ding, Xiyu
in
Analysis
/ Blood sugar
/ Brief Communications
/ Diabetes
/ Diabetes therapy
/ Disease management
/ Electronic records
/ Glycosylated hemoglobin
/ Health care industry
/ Medical records
/ Observational studies
/ Prevention
/ Type 2 diabetes
2024
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Do you wish to request the book?
Assessing the impact of social determinants of health on diabetes severity and management
by
Kharrazi, Hadi
, Nishimura, Akihiko
, Ding, Xiyu
in
Analysis
/ Blood sugar
/ Brief Communications
/ Diabetes
/ Diabetes therapy
/ Disease management
/ Electronic records
/ Glycosylated hemoglobin
/ Health care industry
/ Medical records
/ Observational studies
/ Prevention
/ Type 2 diabetes
2024
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Assessing the impact of social determinants of health on diabetes severity and management
Journal Article
Assessing the impact of social determinants of health on diabetes severity and management
2024
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Overview
Objective
Adverse Social Determinants of Health (SDoH) are considered major obstacles to effective management of type-2 diabetes. This study aims to quantify the impact of SDoH factors on diabetes management outcomes.
Materials and Methods
We quantified the joint impact of multiple SDoH by applying a self-control case series method—which accounts for confounding by using individuals as their own control—to electronic health record data from an academic health system in Maryland.
Results
We found a consistent increase in HbA1c levels associated with SDoH across alternative study designs. The estimated total contributions of SDoH ranged 0.014–0.065 across the alternative designs. Transportation issues demonstrated particularly significant contributions, with estimates of 0.077–0.144. When assuming SDoH’s risk window to be ±45 days, for example, the total contribution was estimated to be 0.065 (95% CI [0.010, 0.120]) increase in HbA1c and the transportation issues’ contribution 0.134 (95% CI [0.020, 0.249]).
Discussion and Conclusion
Our result suggests that reducing transportation barriers may be an effective SDoH intervention strategy for diabetes management; however, the clinical impact of such interventions warrants further investigation.
Lay Summary
Did you know where you live impacts your life expectancy more than your genetic makeup? It affects your access to healthy food, healthcare services, exercise facilities, economic opportunities, and so forth. The Centers for Disease Control and Prevention (CDC) defines these non-medical factors affecting health as Social Determinants of Health (SDoH). Many with diabetes struggle to manage their disease, despite the availability of effective treatments, due to SDoH-related difficulties. Our study attempts to quantify the impact of SDoH on poor diabetes management by using electronic health records (EHRs) and examining how an individual’s blood sugar levels change over time as he/she encounters adverse SDoH. Our analysis shows the lack of reliable transportation to be a significant contributor to worse diabetes control, manifested by higher levels of hemoglobin A1c. While our study identifies no other SDoH factors as significant contributors, this finding could simply be an artifact of the poor recording of SDoH issues in EHRs despite their sizable roles in individuals’ health. More careful documentation of SDoH by healthcare providers will help us quantify their true health impacts and thus identify the most effective interventions.
Publisher
Oxford University Press
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