| Title |
Is employment status in adults over 25 years old associated with nonmedical prescription opioid and stimulant use?
|
|---|---|
| Published in |
Social Psychiatry and Psychiatric Epidemiology, November 2016
|
| DOI | 10.1007/s00127-016-1312-6 |
| Pubmed ID | |
| Authors |
Alexander S. Perlmutter, Sarah C. Conner, Mirko Savone, June H. Kim, Luis E. Segura, Silvia S. Martins |
| Abstract |
Nonmedical use of prescription opioid and stimulants (NMUPO and NMUPS, respectively) has declined in recent years, but remains an important public health problem. Evidence regarding their relationships with employment status remains unclear. We determined the relationship between employment status and NMUPO and NMUPS. We analyzed a cross-sectional, nationally representative, weighted sample of 58,486 adults, ages 26 years and older, using combined 2011-2013 data from the National Survey on Drug Use and Health (NSDUH). We fit two crude and two adjusted multivariable logistic regression models to assess the relationship between our two different outcomes of interest: (1) past-year NMUPO and (2) past-year NMUPS, and our exposure of interest: employment status, categorized as (1) full time, (2) part time, (3) unemployed, and (4) not in the workforce. Our adjusted models featured the following covariates: sex, race, age, marital status, and psychological distress, and other nonmedical use. Prevalence of NMUPO was higher than NMUPS (3.48 vs. 0.72%). Unemployed participants had the highest odds of NMUPO [aOR 1.45, 95% CI (1.15-1.82)], while those not in the workforce had the highest odds of NMUPS [aOR 1.71, 95% CI (1.22-2.37)]. Additionally, part-time and unemployed individuals had increased odds of NMUPS [aORs, 95% CI 1.59 (1.09-2.31) and 1.67 (1.11-2.37) respectively], while those not in the workforce had decreased odds of NMUPO [aOR 0.82, 95% CI (0.68-0.99)] relative to full-time participants. There is a need for adult prevention and deterrence programs that target nonmedical prescription drug use, especially among those unemployed or not in the workforce. |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 67% |
| Ireland | 1 | 11% |
| Unknown | 2 | 22% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 89% |
| Scientists | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 61 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 18% |
| Researcher | 10 | 16% |
| Student > Master | 9 | 15% |
| Other | 6 | 10% |
| Student > Doctoral Student | 3 | 5% |
| Other | 9 | 15% |
| Unknown | 13 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 11 | 18% |
| Psychology | 8 | 13% |
| Medicine and Dentistry | 8 | 13% |
| Economics, Econometrics and Finance | 5 | 8% |
| Nursing and Health Professions | 3 | 5% |
| Other | 9 | 15% |
| Unknown | 17 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 26. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 January 2017.
All research outputs
#1,476,416
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Outputs from Social Psychiatry and Psychiatric Epidemiology
#267
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Outputs of similar age
#29,327
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Outputs of similar age from Social Psychiatry and Psychiatric Epidemiology
#11
of 42 outputs
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