Racial differences in sleep medication use: a cross-sectional study of the Johnston County Osteoarthritis Project

Allen KD, Renner JB, DeVellis B, Helmick CG, Jordan JM. Racial differences in sleep medication use: a cross-sectional study of the Johnston County Osteoarthritis Project. The Annals of pharmacotherapy. 2008 Sep 1; 42(9):1239-46.

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Abstract:

BACKGROUND: Little is known about racial differences in the use of sleep medications. OBJECTIVES: To compare sleep medication use among African Americans and whites with self-reported current sleep problems. METHODS: Participants were 1910 individuals (69% female, 34% African American, 66% white) from the Johnston County Osteoarthritis Project. We examined racial differences in self-reported current use of prescription, nonprescription, herbal, and other medications for sleep. Multivariable logistic regression models controlled for age, sex, education, health insurance, symptomatic hip or knee osteoarthritis, depressive symptoms, obesity, fair or poor general health, and self-reported annual days of sleep problems. Models were conducted separately for the whole sample and for men and women. RESULTS: Among participants with current sleep problems, 31% were using one or more types of sleep medication: 17% prescription, 12% nonprescription, 1% herbal, and 3% other products. African Americans were less likely than whites to be using any sleep medication (25% vs 35%; p < 0.001), prescription sleep medication (14% vs 19%; p = 0.003), and nonprescription sleep medication (10% vs 13%; p = 0.048). These racial differences persisted in multivariable models. In sex-stratified analyses, there were significant racial differences in sleep medication use only among women. CONCLUSIONS: African Americans were less likely than whites to report current use of prescription and nonprescription sleep medications; these results appeared to be largely driven by racial differences among women. Additional research should study possible underlying factors and determine whether these racial differences impact clinical outcomes.