BACKGROUND: Non-medical use (NMU) of prescription opioids in youth is of concern since they may continue this pattern into adulthood and become addicted or divert medications to others. Research into risk factors for NMU can help target interventions to prevent non-medical use of opioids in youth. METHOD: The National Monitoring of Adolescent Prescription Stimulants Study (N-MAPSS) was conducted from 2008 to 2011. Participants 10-18years of age were recruited from entertainment venues in urban, rural and suburban areas of 10 US cities. Participants completed a survey including questions on their use of prescription opioids. NMU was defined as a non-labeled route of administration or using someone else's prescription. Information on age, gender, alcohol, marijuana and tobacco use was also collected. Summary descriptive, chi-square statistics and logistic regression were conducted using SAS 9.4. RESULTS: Of the 10,965 youth who provided information about past 30day prescription opioid use, prevalence of reported opioid use was 4.8% with 3.2% reported as NMU (n=345) and 1.6% as medical use (MU) only (n=180). More males than females (55.7% vs. 44.4%) reported opioid NMU (p<0.0001). Logistic regression revealed that among males (comparing NMU to MU only), current smokers were 4.4 times more likely to report opioid NMU than non-smokers (95% CI: 1.8, 10.7). Among females (comparing NMU to MU only), current smokers and alcohol users were more likely to report opioid NMU than those who had never smoked or used alcohol (OR=3.2, 95% CI: 1.4, 7.0 and OR=4.1, 95% CI: 1.7, 10.4, respectively). CONCLUSIONS: These results suggest that further research on gender differences in opioid NMU is needed; interventions for opioid NMU may need to be gender specific to obtain the best results.
BACKGROUND: Non-medical use (NMU) of prescription opioids in youth is of concern since they may continue this pattern into adulthood and become addicted or divert medications to others. Research into risk factors for NMU can help target interventions to prevent non-medical use of opioids in youth. METHOD: The National Monitoring of Adolescent Prescription Stimulants Study (N-MAPSS) was conducted from 2008 to 2011. Participants 10-18years of age were recruited from entertainment venues in urban, rural and suburban areas of 10 US cities. Participants completed a survey including questions on their use of prescription opioids. NMU was defined as a non-labeled route of administration or using someone else's prescription. Information on age, gender, alcohol, marijuana and tobacco use was also collected. Summary descriptive, chi-square statistics and logistic regression were conducted using SAS 9.4. RESULTS: Of the 10,965 youth who provided information about past 30day prescription opioid use, prevalence of reported opioid use was 4.8% with 3.2% reported as NMU (n=345) and 1.6% as medical use (MU) only (n=180). More males than females (55.7% vs. 44.4%) reported opioid NMU (p<0.0001). Logistic regression revealed that among males (comparing NMU to MU only), current smokers were 4.4 times more likely to report opioid NMU than non-smokers (95% CI: 1.8, 10.7). Among females (comparing NMU to MU only), current smokers and alcohol users were more likely to report opioid NMU than those who had never smoked or used alcohol (OR=3.2, 95% CI: 1.4, 7.0 and OR=4.1, 95% CI: 1.7, 10.4, respectively). CONCLUSIONS: These results suggest that further research on gender differences in opioid NMU is needed; interventions for opioid NMU may need to be gender specific to obtain the best results.
Authors: Sean Esteban McCabe; Brady T West; James A Cranford; Paula Ross-Durow; Amy Young; Christian J Teter; Carol J Boyd Journal: Arch Pediatr Adolesc Med Date: 2011-08
Authors: Joseph J Palamar; Jenni A Shearston; Eric W Dawson; Pedro Mateu-Gelabert; Danielle C Ompad Journal: Drug Alcohol Depend Date: 2015-11-21 Impact factor: 4.492
Authors: Magdalena Cerdá; Julián Santaella; Brandon D L Marshall; June H Kim; Silvia S Martins Journal: J Pediatr Date: 2015-06-06 Impact factor: 4.406
Authors: Mark J Edlund; Valerie L Forman-Hoffman; Cherie R Winder; David C Heller; Larry A Kroutil; Rachel N Lipari; Lisa J Colpe Journal: Drug Alcohol Depend Date: 2015-04-22 Impact factor: 4.492
Authors: Mirsada Serdarevic; Catherine W Striley; Kelly K Gurka; Robert F Leeman; Linda B Cottler Journal: Drug Alcohol Depend Date: 2019-09-20 Impact factor: 4.492
Authors: Ju Nyeong Park; Saba Rouhani; Leo Beletsky; Louise Vincent; Brendan Saloner; Susan G Sherman Journal: Milbank Q Date: 2020-08-18 Impact factor: 4.911
Authors: Hestia Moningka; Sarah Lichenstein; Patrick D Worhunsky; Elise E DeVito; Dustin Scheinost; Sarah W Yip Journal: Neuropsychopharmacology Date: 2018-10-03 Impact factor: 7.853