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Diagnosed and Undiagnosed Diabetes Prevalence by County in the U.S., 1999–2012
Oleh:
Dwyer-Lindgren, Laura
;
Mackenbach, Johan P.
;
Lenthe, Frank J. van
;
Flaxman, Abraham D.
;
Mokdad, Ali H.
Jenis:
Article from Journal - ilmiah internasional
Dalam koleksi:
Diabetes Care vol. 39 no. 09 (Sep. 2016)
,
page 1556-1562.
Topik:
Diabetes Prevalence
Fulltext:
D05 v39 n9 p1556 kelik2017.pdf
(8.86MB)
Ketersediaan
Perpustakaan FK
Nomor Panggil:
D05.K
Non-tandon:
1 (dapat dipinjam: 0)
Tandon:
tidak ada
Lihat Detail Induk
Isi artikel
OBJECTIVE Previous analyses of diabetes prevalence in the U.S. have considered either only large geographic regions or only individuals in whom diabetes had been diagnosed. We estimated county-level trends in the prevalence of diagnosed, undiagnosed, and total diabetes as well as rates of diagnosis and effective treatment from 1999 to 2012. RESEARCH DESIGN AND METHODS We used a two-stage modeling procedure. In the first stage, self-reported and biomarker data from the National Health and Nutrition Examination Survey (NHANES) were used to build models for predicting true diabetes status, which were applied to impute true diabetes status for respondents in the Behavioral Risk Factor Surveillance System (BRFSS). In the second stage, small area models were fit to imputed BRFSS data to derive county-level estimates of diagnosed, undiagnosed, and total diabetes prevalence, as well as rates of diabetes diagnosis and effective treatment. RESULTS In 2012, total diabetes prevalence ranged from 8.8% to 26.4% among counties, whereas the proportion of the total number of cases that had been diagnosed ranged from 59.1% to 79.8%, and the proportion of successfully treated individuals ranged from 19.4% to 31.0%. Total diabetes prevalence increased in all counties between 1999 and 2012; however, the rate of increase varied widely. Over the same period, rates of diagnosis increased in all counties, while rates of effective treatment stagnated. CONCLUSIONS Our findings demonstrate substantial disparities in diabetes prevalence, rates of diagnosis, and rates of effective treatment within the U.S. These findings should be used to target high-burden areas and select the right mix of public health strategies.
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