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Journal Article

Citation

Vaidya V, Gabriel MH, Gangan N, Borse M. Popul. Health Manag. 2014; 17(6): 345-350.

Affiliation

University of Toledo College of Pharmacy , Toledo, Ohio.

Copyright

(Copyright © 2014, Mary Ann Liebert Publishers)

DOI

10.1089/pop.2013.0124

PMID

25075610

Abstract

Sleep deprivation and disturbances can result in lowered productivity and increased errors/accidents. Little is known about population characteristics associated with the use of sleep medications. The objective of this study was to investigate the association of sociodemographic factors with the use of sleep medications in the US population. This was a retrospective, cross-sectional study using data from the 2010 Medical Expenditure Panel Survey, which contains nationally representative data from the US population. The study population included all respondents older than 18 years of age. A multiple logistic regression model was built to analyze the odds of reporting use of prescription or nonprescription sleep medication. In 2010, an estimated 19 million survey respondents (10%) used some type of medication to fall asleep. The odds of reporting use of sleep medication were significantly lower among males (odds ratio [OR]=0.695, 95% confidence interval [CI]=0.599-0.808), and the uninsured (OR=0.613, 95% CI=0.439-0.855). The odds of sleep medication use were significantly higher among age groups 24-44 years and 44-64 years as compared with 18-24 years (OR=1.868, 95% CI=1.254-2.781 and OR=1.936, 95% CI=1.309-2.865, respectively), whites (OR=2.003, 95% CI=1.597-2.512) compared with African Americans, or non-Hispanics (OR=1.609, 95% CI=1.316-1.967), the unemployed (OR=1.773, 95% CI=1.496-2.101), and respondents with depression (OR=2.077, 95% CI=1.463-2.951) or anxiety (OR=6.855, 95% CI=4.998-9.403). Differences in sleep medication use were seen among specific subpopulations. Further research into why such differences exist is necessary. The factors identified in this study should be investigated further to identify vulnerable populations to determine the underlying causes of sleep disorders. (Population Health Management 2014;17:xxx-xxx).


Language: en

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