Selected Risk Factors' Contribution to State-Level Incidence of Diagnosed Diabetes, 2005-2007
Lawrence Barker*, Edward Tierney, Andrew Lanza, Karen Kirtland
Identifiers and Pagination:Year: 2011
First Page: 123
Last Page: 130
Publisher Id: TODIAJ-4-123
Article History:Received Date: 24/06/2011
Revision Received Date: 22/08/2011
Acceptance Date: 23/08/2011
Electronic publication date: 29/11/2011
Collection year: 2011
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Introduction: Differences in incidence of diabetes and prevalence of risk factors for diabetes exist among states. It is unknown how much of this variability in incidence of diagnosed diabetes is due to variability in risk factor prevalence. We investigate the contribution of selected risk factors to state level incidence of diagnosed diabetes. Materials and Methods: Using 2005-2007 data from the Behavioral Risk Factor Surveillance System, we conducted two logistic regressions, both with incident case status as dependent variable. One model considered only state of residence as an independent variable. The other added: age; sex; race/ethnicity; education; inactive lifestyle; and obesity. We compared adjusted and unadjusted odds of incident diabetes among states, and calculated excess risk. Results: Adjusted and unadjusted odds of incident diabetes were similar. Sensitivity analyses showed that this differed little if we used data from earlier years or if we included income or insurance as a risk factor. In most states, the excess risk associated with risk factors was less than 30%. Discussion: Factors other than age, sex, race/ethnicity, education, inactivity, and obesity (i.e., established risk factors for diabetes) might substantially influence the differences in state incidence rates. These factors' identities are unknown. If these factors are identified and modifiable, states might use them to reduce between-state disparities in diabetes incidence.