Patterns and correlates of use of evidence-based interventions to control diabetes by local health departments across the USA. Issue 1 (5th September 2018)

• Record Type: Journal Article
• Authors: Tabak, Rachel G; Parks, Renee G; Allen, Peg; Jacob, Rebekah R; Mazzucca, Stephanie; Stamatakis, Katherine A; Poehler, Allison R; Chin, Marshall H; Dobbins, Maureen; Dekker, Debra; Brownson, Ross C
• Is Part Of: BMJ open diabetes research and care. Volume 6:Issue 1(2018)
• Publication Date: 2018-09-05
• Subjects: public health -- prevention -- chronic disease prevention and treatment; Diabetes -- Periodicals; 616.462005
• DOI: 10.1136/bmjdrc-2018-000558
• Languages: English
• ISSNs: 2052-4897

Abstract

Abstract : Objective: The nearly 3000 local health departments (LHDs) nationwide are the front line of public health and are positioned to implement evidence-based interventions (EBIs) for diabetes control. Yet little is currently known about use of diabetes-related EBIs among LHDs. This study used a national online survey to determine the patterns and correlates of the Centers for Disease Control and Prevention Community Guide-recommended EBIs for diabetes control in LHDs. Research design and methods: A cross-sectional study was conducted to survey a stratified random sample of LHDs regarding department characteristics, respondent characteristics, evidence-based decision making within the LHD, and delivery of EBIs (directly or in collaboration) within five categories (diabetes-related, nutrition, physical activity, obesity, and tobacco). Associations between delivering EBIs and respondent and LHD characteristics and evidence-based decision making were explored using logistic regression models. Results: Among 240 LHDs there was considerable variation among the EBIs delivered. Diabetes prevalence in the state was positively associated with offering the Diabetes Prevention Program (OR=1.28 (95% CI 1.02 to 1.62)), diabetes self-management education (OR=1.32 (95% CI 1.04 to 1.67)), and identifying patients and determining treatment (OR=1.27 (95% CI 1.05 to 1.54)). Although all organizational supports for evidence-based decision making factors were related in a positive direction, the only significant association was between evaluation capacity and identifying patients with diabetes and determining effective treatment (OR=1.54 (95% CI 1.08 to 2.19)). Conclusion: Supporting evidence-based decision making and increasing the implementation of these EBIs by more LHDs can help control diabetes nationwide.