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Estimating the Population Prevalence of Diagnosed and Undiagnosed Diabetes
OBJECTIVE: Health administrative data are frequently used for diabetes surveillance, but validation studies are limited, and undiagnosed diabetes has not been considered in previous studies. We compared the test properties of an administrative definition with self-reported diabetes and estimated pre...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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American Diabetes Association
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3781536/ https://www.ncbi.nlm.nih.gov/pubmed/23656982 http://dx.doi.org/10.2337/dc12-2543 |
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author | Leong, Aaron Dasgupta, Kaberi Chiasson, Jean-Louis Rahme, Elham |
author_facet | Leong, Aaron Dasgupta, Kaberi Chiasson, Jean-Louis Rahme, Elham |
author_sort | Leong, Aaron |
collection | PubMed |
description | OBJECTIVE: Health administrative data are frequently used for diabetes surveillance, but validation studies are limited, and undiagnosed diabetes has not been considered in previous studies. We compared the test properties of an administrative definition with self-reported diabetes and estimated prevalence of undiagnosed diabetes by measuring glucose levels in mailed-in capillary blood samples. RESEARCH DESIGN AND METHODS: A stratified random sample of 6,247 individuals (Quebec province) was surveyed by telephone and asked to mail in fasting blood samples on filter paper to a central laboratory. An administrative definition was applied (two physician claims or one hospitalization for diabetes within a 2-year period) and compared with self-reported diabetes alone and with self-reported diabetes or elevated blood glucose level (≥7 mmol/L). Population-level prevalence was estimated with the use of the administrative definition corrected for its sensitivity and specificity. RESULTS: Compared with self-reported diabetes, sensitivity and specificity were 84.3% (95% CI 79.3–88.5%) and 97.9% (97.4–98.4%), respectively. Compared with diabetes by self-report and/or glucose testing, sensitivity was lower at 58.2% (52.2–64.6%), whereas specificity was similar at 98.7% (98.0–99.3%). Adjusted for sampling weights, population-level prevalence of physician-diagnosed diabetes was 7.2% (6.3–8.0%). Prevalence of total diabetes (physician-diagnosed and undiagnosed) was 13.4% (11.7–15.0%), indicating that ∼40% of diabetes cases are undiagnosed. CONCLUSIONS: A substantial proportion of diabetes cases are missed by surveillance methods that use health administrative databases. This finding is concerning because individuals with undiagnosed diabetes are likely to have a delay in treatment and, thus, a higher risk for diabetes-related complications. |
format | Online Article Text |
id | pubmed-3781536 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | American Diabetes Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-37815362014-10-01 Estimating the Population Prevalence of Diagnosed and Undiagnosed Diabetes Leong, Aaron Dasgupta, Kaberi Chiasson, Jean-Louis Rahme, Elham Diabetes Care Original Research OBJECTIVE: Health administrative data are frequently used for diabetes surveillance, but validation studies are limited, and undiagnosed diabetes has not been considered in previous studies. We compared the test properties of an administrative definition with self-reported diabetes and estimated prevalence of undiagnosed diabetes by measuring glucose levels in mailed-in capillary blood samples. RESEARCH DESIGN AND METHODS: A stratified random sample of 6,247 individuals (Quebec province) was surveyed by telephone and asked to mail in fasting blood samples on filter paper to a central laboratory. An administrative definition was applied (two physician claims or one hospitalization for diabetes within a 2-year period) and compared with self-reported diabetes alone and with self-reported diabetes or elevated blood glucose level (≥7 mmol/L). Population-level prevalence was estimated with the use of the administrative definition corrected for its sensitivity and specificity. RESULTS: Compared with self-reported diabetes, sensitivity and specificity were 84.3% (95% CI 79.3–88.5%) and 97.9% (97.4–98.4%), respectively. Compared with diabetes by self-report and/or glucose testing, sensitivity was lower at 58.2% (52.2–64.6%), whereas specificity was similar at 98.7% (98.0–99.3%). Adjusted for sampling weights, population-level prevalence of physician-diagnosed diabetes was 7.2% (6.3–8.0%). Prevalence of total diabetes (physician-diagnosed and undiagnosed) was 13.4% (11.7–15.0%), indicating that ∼40% of diabetes cases are undiagnosed. CONCLUSIONS: A substantial proportion of diabetes cases are missed by surveillance methods that use health administrative databases. This finding is concerning because individuals with undiagnosed diabetes are likely to have a delay in treatment and, thus, a higher risk for diabetes-related complications. American Diabetes Association 2013-10 2013-09-14 /pmc/articles/PMC3781536/ /pubmed/23656982 http://dx.doi.org/10.2337/dc12-2543 Text en © 2013 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details. |
spellingShingle | Original Research Leong, Aaron Dasgupta, Kaberi Chiasson, Jean-Louis Rahme, Elham Estimating the Population Prevalence of Diagnosed and Undiagnosed Diabetes |
title | Estimating the Population Prevalence of Diagnosed and Undiagnosed Diabetes |
title_full | Estimating the Population Prevalence of Diagnosed and Undiagnosed Diabetes |
title_fullStr | Estimating the Population Prevalence of Diagnosed and Undiagnosed Diabetes |
title_full_unstemmed | Estimating the Population Prevalence of Diagnosed and Undiagnosed Diabetes |
title_short | Estimating the Population Prevalence of Diagnosed and Undiagnosed Diabetes |
title_sort | estimating the population prevalence of diagnosed and undiagnosed diabetes |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3781536/ https://www.ncbi.nlm.nih.gov/pubmed/23656982 http://dx.doi.org/10.2337/dc12-2543 |
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