Nonmedical stimulant use among young Asian-Americans, Native Hawaiians/Pacific Islanders, and mixed-race individuals aged 12–34 years in the United States

Abstract

There are concerns over nonmedical use of prescription stimulants among youths, but little is known about the extent of use among young Asian-Americans, Native Hawaiians/Pacific Islanders (NHs/PIs), and mixed-race individuals—the fastest growing segments of the U.S. population. We examined prevalences and correlates of nonmedical stimulant use (NMSU) and disorder (StiUD) for these underrecognized groups. Whites were included as a comparison. Data were from young individuals aged 12–34 years in the 2005–2012 National Surveys on Drug Use and Health. We used logistic regression to estimate odds of past-year NMSU status. Significant yearly increases in lifetime NMSU prevalence were noted in Whites only. NHs/PIs (lifetime 7.33%, past-year 2.72%) and mixed-race individuals (10.20%, 2.82%) did not differ from Whites in NMSU prevalence (11.68%, 3.15%). Asian-Americans (lifetime 3.83%, past-year 0.90%) had lower prevalences than Whites. In each racial/ethnic group, “Methamphetamine/Desoxyn/Methedrine or Ritalin” was more commonly used than other stimulant groups; “got them from a friend/relative for free” and “bought them from a friends/relative” were among the most common sources. Females had greater odds than males of NMSU (among White, NH/PI, mixed-race individuals) and StiUD (among mixed-race individuals). Young adults (aged 18–25) had elevated odds of NMSU (White, NH/PI); adolescents had elevated odds of StiUD (White, mixed-race). Other substance use (especially marijuana, other prescription drugs) increased odds of NMSU and StiUD. NHs/PIs and mixed-race individuals were as likely as Whites to misuse stimulants. Research is needed to delineate health consequences of NMSU and inform prevention efforts for these understudied, rapidly-growing populations.

Annual review of Asian American Psychology, 2014.

“…This year’s review also found more studies that included bicultural or multiracial Asian-heritage populations compared to past reviews (e.g., L.-T. Wu et al, 2014). This is an encouraging trend, reflecting the fact that from 2000 to 2010, the multiple-race “White and Asian” population increased by a remarkable 87% in the United States (Jones & Bullock, 2012).…”

“…The majority of studies used quantitative-correlational designs with analytical methods such as analysis of variance, linear or logistic regression, and structural equation modeling ( n = 15; e.g., Mukherjea et al, 2014). Among the correlational studies, six used longitudinal designs ( n = 6; Bart et al, 2014; Blanco et al, 2014; Boyd, Corbin, & Fromme, 2014; Jimi Huh, Heesung Shin, et al, 2014; Luczak et al, 2014; L.-T. Wu et al, 2014), and the rest used cross-sectional designs. Other studies used quantitative-experimental designs ( n = 1; L.…”

Annual review of Asian American Psychology, 2013.

“…Little, Fagan, Muranaka, & Herzog, 2014;Tsang et al, 2014;Williams & Nigg, 2014) and drug/nonmedical stimulant use, resistance, and treatment (n = 3; Bart, Lenz, Straka, & Brundage, 2014;Okamoto, Pel, Helm, & Valdez, 2014;L.-T. Wu, Swartz, Brady, Blazer, & Hoyle, 2014). Other articles studied substance use more generally, covering cigarettes, alcohol, marijuana, or "hard" drugs (n = 8; L. Fang & Schinke, 2014;Helm, Okamoto, Kaliades, & Giroux, 2014;Okamoto, Kulis, Helm, Edwards, & Giroux, 2014;Savage & Mezuk, 2014;.…”

“…Articles mainly centered on alcohol use (n = 11; Banerjee et al, 2014;Blanco et al, 2014;Jimi Huh, Heesung Shin, et al, 2014;Jimi Huh, Thing, Abramova, Sami, & Unger, 2014;Lo, Cheng, & Howell, 2014;Mukherjea, Wackowski, Lee, & Delnevo, 2014;Pagano, Lee, & Sin, 2014;Pokhrel, Little, Fagan, Kawamoto, & Herzog, 2014;Pokhrel, Little, Fagan, Muranaka, & Herzog, 2014;Tsang et al, 2014;Williams & Nigg, 2014) and drug/nonmedical stimulant use, resistance, and treatment (n = 3; Bart, Lenz, Straka, & Brundage, 2014;Okamoto, Pel, Helm, & Valdez, 2014;L.-T. Wu, Swartz, Brady, Blazer, & Hoyle, 2014). Other articles studied substance use more generally, covering cigarettes, alcohol, marijuana, or "hard" drugs (n = 8; L. Fang & Schinke, 2014;Helm, Okamoto, Kaliades, & Giroux, 2014;Okamoto, Kulis, Helm, Edwards, & Giroux, 2014;Savage & Mezuk, 2014;.…”

“…The majority of studies used quantitative-correlational designs with analytical methods such as analysis of variance, linear or logistic regression, and structural equation modeling (n = 15; e.g., Mukherjea et al, 2014). Among the correlational studies, six used longitudinal designs (n = 6; Bart et al, 2014;Blanco et al, 2014;Boyd, Corbin, & Fromme, 2014;Jimi Huh, Heesung Shin, et al, 2014;Luczak et al, 2014;L.-T. Wu et al, 2014), and the rest used cross-sectional designs. Other studies used quantitative-experimental designs (n = 1; L. Fang & Schinke, 2014), qualitative designs using methods such as interviews and focus groups (n = 4; Banerjee et al, 2014;Hunt, Moloney, & Fazio, 2014;Tsang et al, 2014) and mixed-method designs (n = 1; Jimi Huh, James Paul Thing, et al, 2014).…”