A1C Testing and its Sociodemographic Predictors: Implications for Diabetes Self-management Programs. (5th September 2014)

• Record Type: Journal Article
• Authors: Nepal, Vishnu; Banerjee, Deborah
• Is Part Of: Health services research and managerial epidemiology. Volume 1(2014)
• Publication Date: 2014-09-05
• Subjects: A1C -- diabetes -- Texas -- self-management -- demographics; Medical care -- Periodicals; Health services administration -- Periodicals; Epidemiology -- Periodicals; 362.1
• DOI: 10.1177/2333392814547129
• Languages: English
• ISSNs: 2333-3928

Abstract

Background: One of the Healthy People (2020) goals related to the glycated hemoglobin (HbA1C) test is to increase the percentage of adults (aged 18 years and older) with diabetes who have had an HbA1C test at least twice in the past 12 months from 64.6% percent in 2008 to 71.1% by 2020. However, Texas has historically trailed behind several other states in achieving this goal. Targeted interventions for demographic subgroups of population could be a strategy to increase testing. However, little is known about the sociodemographic predictors of A1C test. Method: Texas Behavioral Risk Factor Surveillance System (BRFSS) data (2011 and 2012) were used to identify sociodemographic predictors of having had at least one A1C test in the past 12 months among diabetic patients. The sociodemographic predictors examined included age, sex, race/ethnicity, marital status, educational attainment, insurance status, whether or not the respondents had a primary care physician, and age when diabetes was diagnosed. A logistic model was developed to predict the membership. Results: Multivariate logistic regression indicated that insurance status and educational attainment are predictors of adherence to an annual A1C test. Those with insurance were nearly 3 times more likely than those without insurance to report adherence to annual A1C test (odds ratio [OR] = 2.82, 95% confidence interval [CI], 1.47-5.42, P = .002), when controlled for all other sociodemographic variables. Likewise, those with more than college-level education were also nearly 3 times more likely than those with less than high school level education to report adherence (OR = 2.74, 95% CI, 1.27-5.89, P = .010). Conclusion: Population-based diabetes management programs should consider educational attainment level and insurance status of individuals when developing interventions to increase the rate of adherence to A1C testing recommendation among diabetic patients. Targeting interventions toward individuals with less than high school education and ensuring that diabetic individuals have some form of health insurance coverage may be helpful.