Lifetime nonmedical use of prescription medications and socioeconomic status among young adults in the United States

Abstract

Background: Despite decreases in the use of illicit drugs in the United States, prescription medications have become a major category of substances used by young adults. Objective: This study examines the relationship between the socioeconomic status (SES) of young adult respondents (ages 24–32) and their history of nonmedical use of prescription medications (NUPM). Method: A secondary analysis was conducted with nationally representative data gathered from several waves (n = 15 701) of the National Longitudinal Study of Adolescent Health (Add Health). Four categories of NUPM were examined: (i) sedatives; (ii) tranquilizers; (iii) stimulants; and (iv) pain killers. SES was defined by several measures in the Add Health survey. Given the complex sampling plan of the Add Health, all analyses were weighted appropriately. Results: Results indicated higher levels of personal SES, such as having health insurance or not experiencing a financial hardship in the past year, decreased the likelihood of reporting lifetime NUPM. In contrast higher levels of parent SES (e.g. parental education) were associated with an increased likelihood of reporting lifetime use of NUPM tranquilizers and stimulants. Conclusions: The results of this study suggest parental SES may have a stronger influence over NUPM than personal levels of SES, particularly for the categories of tranquilizers and stimulants. Furthermore, these findings indicate more research is needed on this subject to better understand the NUPM epidemic in order to effectively develop comprehensive clinical, public health, and policy-related intervention and prevention approaches.

• Drug use
• NUPM
• prescription
• SES
• young adult

Acknowledgements

This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website (http://www.cpc.unc.edu/addhealth). No direct support was received from grant P01-HD31921 for this analysis.

Declaration of interest

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of this paper.