Open Access. Powered by Scholars. Published by Universities.®

Medicine and Health Sciences Commons

Open Access. Powered by Scholars. Published by Universities.®

External Link

Diseases

Richard Crespo

Articles 1 - 2 of 2

Full-Text Articles in Medicine and Health Sciences

Age At Diagnosis Of Diabetes In Appalachia, Lawrence Barker, Robert Gerzoff, Richard Crespo, Molly Shrewsberry Nov 2012

Age At Diagnosis Of Diabetes In Appalachia, Lawrence Barker, Robert Gerzoff, Richard Crespo, Molly Shrewsberry

Richard Crespo

Background Appalachia is a region of the United States noted for the poverty and poor health outcomes of its residents. Residents of the poorest Appalachian counties have a high prevalence of diabetes and risk factors (obesity, low income, low education, etc.) for type 2 diabetes. However, diabetes prevalence exceeds what these risk factors alone explain. Based on this, the history of poor health outcomes in Appalachia, and personally observed high rates of childhood obesity and lack of concern about prediabetes, we speculated that people in Appalachia with diagnosed diabetes might tend to be diagnosed younger than their non-Appalachian counterparts. Methods …


Residence In A Distressed County In Appalachia As A Risk Factor For Diabetes, Behavioral Risk Factor Surveillance System, 2006-2007, Lawrence Barker, Richard Crespo, Robert Gerzoff, Sharon Denham, Molly Shrewsberry, Darrlyn Cornelius-Averhart Nov 2012

Residence In A Distressed County In Appalachia As A Risk Factor For Diabetes, Behavioral Risk Factor Surveillance System, 2006-2007, Lawrence Barker, Richard Crespo, Robert Gerzoff, Sharon Denham, Molly Shrewsberry, Darrlyn Cornelius-Averhart

Richard Crespo

Introduction We compared the risk of diabetes for residents of Appalachian counties to that of residents of non-Appalachian counties after controlling for selected risk factors in states containing at least 1 Appalachian county. Methods We combined Behavioral Risk Factor Surveillance System data from 2006 and 2007 and conducted a logistic regression analysis, with self-reported diabetes as the dependent variable. We considered county of residence (5 classifications for Appalachian counties, based on economic development, and 1 for non-Appalachian counties), age, sex, race/ethnicity, education, household income, smoking status, physical activity level, and obesity to be independent variables. The classification “distressed” refers to …