Adolescents (n = 18) |
Banks et al., 2017
|
Cross-sectional |
|
Concurrent:
past 30-day A + Ca, Ca + T, A + T, A + Ca + T, coded as yes/no for each combination
|
Sex
|
Age, income |
Compared with girls, boys were more likely to belong to the typologies A + Ca, Ca + T, A + T, A + Ca + T (vs. A only)
|
Banks et al., 2019
|
Cross-sectional |
238 detained youth
19.6% girls
77.3% non-White
M
age = 15.5
|
Concurrent:
past-year Ca + A, Ca + Oth, Ca + A + Oth, coded as yes/no for each combination
Oth included e.g. spice, NPM, E, Meth
|
Gender |
None |
|
Collins et al., 1998
|
Longitudinal |
|
Simultaneous:
past year A + D, A + U, A + Ca, Co + Oth on the same occasion, coded as yes/no for each combination
|
Gender
|
Model 1: none Model 2: age; race/ethnicity; income; parent education/ occupation; social influences; family, school and church factors; problem behavior/lifestyle factors |
Model 1:
Compared with girls, boys were more likely to use A + Ca
No gender differences in illicit drug use (excluding Ca) + A/Ca
Model 2:
Compared with girls, boys were more likely to use A + Ca (vs. no PSU)
No gender differences in illicit drug use (excluding Ca) + Oth (compared with A + Ca)
|
Epstein et al., 1999
|
Longitudinal |
2354 6th and 7th graders
52% girls
84% White
M
age = 12.6
|
Concurrent: - lifetime and past month A, T, Ca, each coded as 0–3 total substances
|
Gender
|
Ethnicity |
|
Evans et al., 2020
a
|
Repeated cross-sectional |
Young in Värmland (YiV) study, 1988–2011
20,057 Swedish adolescents
49% girls
Race NR
Age = 15 to 16
|
Concurrent:
|
Sex
|
None |
- Compared with girls, boys were more likely to be in the PSU class (lifetime A + Ci, drunkenness+I) versus no/low use class (no substance use or lifetime A only) for first 3 cohorts (1988–1991, 1995–1998, 2002–2005) - No significant sex differences in the 2008–2011 cohort |
Font-Mayolas et al., 2013
|
Cross-sectional |
|
Concurrent:
past 6-month T, A, Ca, Co, ≥2 substances used coded as yes/no
|
Gender
|
None |
No gender differences in PSU when whole sample included
When only drug users included, girls were more likely to report PSU
|
Göbel et al., 2016
a
|
Cross-sectional |
Second International Self-Report Delinquency Study (ISRD-2), 2006
33,566 European adolescents
50.6% girls
Race NR
M
age = 13.9
|
Concurrent:
lifetime and past-month A, Ca, and E/speed/ /LSD/H/Co coded as yes/no and frequency of past-month use coded as never, 1–2 times, or ≥ 3 times; subjected to LCA
|
Gender
|
None |
|
Hoffman et al., 2000
|
Repeated cross-sectional |
|
Simultaneous:
|
Gender
|
Model 1: none Model 2: demographics and survey year Model 3: individual substance use rates: average daily A, past 30-day use frequency of Ca/Co respectively and product of A and drug use frequency |
Model 1: Probabilities of simultaneous use greater for boys versus girls
Model 2: A + Co was higher for boys
Model 3: Controlling for the individual substance rates of use, girls were more likely to use A + Ca and A + Co in combination than boys
|
Kokkevi et al., 2014
|
Cross-sectional |
European School Survey Project on Alcohol and Other Drugs (ESPAD) survey, 2011 wave
101,401 16-year-old students in 36 European countries
41.9% girls
Race NR
M
age = 16
|
Concurrent:
past 30-day use of ‘risky’ substance combinations: ≥6 T/day, A use ≥10 times, any Ca, and any lifetime use of S and Oth, coded as yes/no, and past 30-day ‘risky’ use defined total number of substances used at a ‘risky’ level
|
Gender
|
None |
More boys (vs. girls) used 2 and 3+ substances
Compared with girls, more boys endorsed substance combinations: T + A, Ca + Oth, A + Ca, T + A + Ca, T + A + Ca + Oth, A+ O, A + Ca + Oth, A + Ca + S + Oth
Compared with boys, more girls endorsed the substance combinations: S + Oth, T + S, T + S + Oth, T + Ca + S + Oth, Ca + S, T + Ca + S, T + A + Ca + S, A + Ca + S
|
Merrin and Leadbeater, 2018
a
|
Longitudinal |
|
Concurrent:
past year use of T, HED, Ca, Oth, coded as yes/no; subjected to LCA
|
Sex |
None |
Similar proportions of boys and girls in poly-use class (highest probabilities of T, HED, Ca, Oth) and co-use class (high probabilities of HED and Ca, low probabilities of T and Oth)
Low-use class (low probabilities of T, HED, Ca, Oth) had more girls than boys
|
Patrick et al., 2018
a
|
Cross-sectional |
|
Concurrent and Simultaneous:
A use coded as: no A past year, past-year A but no BA past 2 weeks, or A past year and BA past 2 weeks; Ca coded as: no Ca past year, Ca past year but not past 30 days, or Ca past year and past 30 days; past-year A + Ca (overlapping drug effects) coded as yes/no, subjected to LCA
|
Gender |
Race/ethnicity, parent education, high school grades, whether the student had definite plans to graduate from a 4-year college, frequency of evenings out with friends, truancy, past year use of any illicit drugs other than Ca |
Compared with girls, boys were more likely to be in simultaneous A + Ca-heavier use group (high probabilities for: simultaneous A + Ca, A, BA and past 30-day Ca) versus simultaneous A + Ca-lighter use (high probabilities of A + Ca, past-month Ca, A without BA), concurrent use (high probabilities of Ca and A without B), or A-only (high probabilities of A without BA, Ca, A + Ca)
No gender differences in risk of being in A-only class versus either simultaneous A + Ca-lighter use or concurrent classes
|
Patrick et al., 2019
|
Cross-sectional |
|
Simultaneous:
|
Gender
|
Model 1: none Model 2: race/ethnicity, college plans, grades, parents in the home, religiosity, parental education, geographic region, cohort and A, T, Ca use |
|
Petrou and Kupek, 2018
|
Cross-sectional |
Scottish Schools Adolescent Lifestyle and Substance Use Survey (SALSUS), 2002–2013
134,387 Scottish students
Gender NR
Race NR
2 classes, Mage = 13 and 15, respectively
|
Concurrent:
regular PSU, coded as yes/no; defined as having: Avg of ≥1 T/week, A ≥ 1 times/week, and past-month illicit drug use
heavy PSU coded as yes/no defined as engaging in ≥2 out of 3: ≥60 T past week, ≥21 units of A past week, illicit drugs most days
|
Gender
|
School year, ethnicity and socioeconomic quintile |
|
Purcell et al., 2020
|
Cross-sectional |
|
Concurrent:
past 30-day A + Ca, A + T, and T + Ca, A + Ca + T, coded as yes/no
|
Sex
|
Model 1: none Model 2: age, parental education, parental marital status, household income |
Model 1: no sex differences in A + Ca, A + T, T + Ca; boys more likely to use A + T + Ca
Model 2: no sex differences
|
Rose et al., 2018
a
|
Cross-sectional |
|
Concurrent:
lifetime A, T, Ca, prescription drugs NP, I, coded on 7-point frequency scale, subjected to LCA
|
Gender |
Race/ethnicity, free/reduced lunch, number of parents living at home |
|
Smit et al., 2002
b
|
Cross-sectional |
|
Concurrent:
past month use of ≥2 substances: A, T, Ca, E, Am, Op, H, and Co, coded as yes/no, entered into HOMALS
|
Gender
|
None |
No gender difference in risk of becoming ordinary PSU (user of A + T)
Compared with girls, boys had greater risk of becoming user of Ca + A/T or a user of E/Co/Am or H + A/T/Ca
|
Terry-McElrath et al., 2013
|
Cross-sectional |
Monitoring the Future, 1976–2011
34,850 nationally represented American students
Gender NR
Race NR
12th grade students
|
Simultaneous:
|
Gender
|
Model 1: none Model 2: year, psychosocial and demographic variables Model 3: year, all psychosocial, demographic and substance use measures |
Model 1: Compared with girls, boys had higher odds of reporting any simultaneous A + Ca
Model 2: Boys had higher odds of any simultaneous A + Ca use
Model 3: Controlling for substance use frequency, girls showed higher odds of simultaneous A + Ca use than boys
|
Zuckermann et al., 2019
|
Cross-sectional |
|
Concurrent:
past year use of ≥2 substances: A, T, Ca, e-cig, coded as number of substances used
|
Gender |
Model 1: none Model 2: study year/sample and race |
Model 1: Compared with girls, boys were more likely to report PSU at all levels (i.e. 2, 3 and 4 substances), AY 2013/2014–2016/2017 until 2017/2018 when more girls reported PSU
Model 2: Compared with girls, boys were more likely to report PSU; difference increased with each substance used
|
Adults (n = 37) |
Back et al., 2010
c
|
Cross-sectional |
|
Concurrent:
|
Gender
|
None |
|
Bassiony and Seleem, 2020
|
Cross-sectional |
|
Concurrent:
positive urine screen of ≥2: Ca, codeine, hypnotics, A, opium, tramadol, Hal, H, coded as yes/no
|
Sex
|
None |
|
Beswick et al., 2001
|
Cross-sectional |
|
Simultaneous:
|
Gender
|
None |
|
Bunting et al., 2020
a
|
Cross-sectional |
Criminal Justice Kentucky Treatment Outcome Study (CJKTOS), 2015–2017
6569 justice-involved individuals
18.1% women
60.7% White
M
age = 32.7
|
Concurrent:
use days 30 days prior to incarceration of: A, Co, Ca, H, prescription Op, Am, T, subjected to LPA
|
Gender
|
Age, years of education, race, unemployment, homelessness, county lived in, financial strain, injection drug use, physical health, anxiety symptoms, depression symptoms, stress-related health consequences |
Compared with women, men were more likely to be in primary A group (~daily A + Ca, prescription Op ~50% of month) and primary Bup group (daily Bup + Ca, prescription Op, Am and S-Op), compared with those in group with no drug use >15 days/month
No gender differences in odds of being in primarily H class (~daily use of H, co-use of Ca + prescription Op) or T PSU group (frequent prescription Op and ~ daily T; co-use of Ca + Am) compared with those in group with no drug use >15 days/month
|
Byqvist, 2006
|
Cross-sectional |
|
Concurrent:
past 12-month CNS + Op, CNS + Ca, Op+Ca, CNS + Op+Ca, CNS + Op+ ≥ 1 narcotics, Op+other narcotics; predominant substance was used as a basal point of reference
|
Gender
|
None |
Compared with women, men had greater prevalence of PSU, with Ca appearing more often in drug combinations; for women Op was more common
Combinations of narcotics were somewhat more prevalent among men
No gender differences in use of another substance for those with A as primary
For those with CNS as primary: more women used Op+S; more men used Ca + A
For those with Op as primary: more men used Ca
For those with Ca as primary: more women misused CNS + E
|
Chan et al., 2019
a
|
Cross-sectional |
National Drug Strategy Household Surveys (NDSHS), 2004, 2007, 2010, 2013, 2016
20,350 nationally representative sample of Australians
58% women
Race NR
M
age = 24.5
|
Concurrent:
past-year use of T (ordinal variable based on frequency), A (ordinal variable based on AUDIT-C), and yes/no variables of Tr/sleeping pills, meth/Am, Ca, H, Co, E, Hal, and ketamine, subjected to LCA
|
Gender
|
Age, sexuality, psychological distress, language, income, socio-economic index for area |
Compared with women, men were more likely to be categorized as Class 2 (high probability of A risk and T, and moderate probability of Ca, minimal Oth) and as Class 3 (high probability of A risk and Ca and higher probability of Oth)
|
Earleywine and Newcomb, 1997
|
Longitudinal |
470 community sample
73.2% women
67% White
M
age = 29.9
|
Concurrent:
Simultaneous:
|
Sex
|
None |
Compared with women, men had more simultaneous use of A + T
No sex differences on any other measure of drug use
|
Egan et al., 2013
|
Cross-sectional |
Study to Prevent Alcohol Related Consequences, College Drinking Survey, 2009
4090 undergraduate students
63.5% women
81.4% White
M
age = 20
|
Simultaneous:
Concurrent:
|
Gender |
Model 1: none Model 2: academic classification, race, parents’ education level, GPA, sensation seeking, past 30-day A, past 30-day HED, past 30-day T, past 30-day, Ca, past 30-day illicit drug use, past-year prescription drug use (excluding Stim) |
Model 1: men had greater odds of reporting simultaneous NMPS+A past-year; no gender differences in simultaneous versus concurrent A + NMPS
Model 2: no gender difference in simultaneous A + NMPS versus past-year A or in simultaneous versus concurrent A + NMPS
|
Evans et al., 2017d
|
Cross-sectional |
|
Concurrent:
|
Gender
|
None |
|
Evans et al., 2017e
|
Cross-sectional |
|
Concurrent:
|
Gender
|
None |
|
Falk et al., 2008
|
Cross-sectional |
|
Concurrent:
past-year A + drugs (Ca, Co, Op, Hal, Am, S, H, I, O), each coded as yes/no
Past year AUD and DUD, coded as yes/no
|
Gender
|
None |
Compared with women, men more likely to use A + O
Men more likely to have past-year AUD + DUD
Men more likely to have past-year AUD + CUD
|
Fernández-Calderón et al., 2015
a
|
Cross-sectional |
|
Concurrent:
diagnoses of abuse/dep of: A, Ca, Co, Op, Am and derivatives, S, Benz, each coded as Abuse vs. Dep vs. Absence of SUD, subjected to LCA
|
Gender |
None |
No gender differences between membership in Class 1 versus 2, Class 1 versus 4 or Class 2 versus 4
Gender differences between membership in Class 1 versus 3, Class 2 versus 3 and Class 3, versus 4 identified in table but directionality not discernible and not discussed
|
Fernández-Calderón et al., 2020
a
|
Cross-sectional |
|
Simultaneous:
substance use at last party attended: A, Ca, Co, E, Am, Meth, ketamine, GHB, magic mushrooms, LSD, Benz, H, poppers, each coded as yes/no; subjected to LCA
|
Sex |
Model 1: none Model 2: age, sexual orientation, education, employment, socioeconomic status, country of residence, last recreational setting attended |
Model 1: Sex differences between class membership identified in table but directionality not discernible and not discussed
Model 2: Compared with participants in the low PSU class (high use of A + Ca, mean of 2.3 substances used), those in the extensive PSU/Stim class (E + A + Am+ Ca, mean of 4.7 substances used) were at lower odds of being men
|
Grant & Harford, 1990f
|
Cross-sectional |
|
Concurrent:
Simultaneous:
|
Sex
|
None |
|
Grant & Harford, 1990g
|
Cross-sectional |
|
Concurrent:
Simultaneous
|
Sex
|
None |
No sex differences in percentage of S users who used A + S concurrently
Concurrent users of A + S who reported simultaneous use were more likely to be men versus women
A greater percentage of men versus women reported both concurrent and simultaneous use of A + Tr
|
Griesler et al., 2019
|
Cross-sectional |
|
Concurrent:
past-year prescription Op (misused without prescription, misused own prescription, misused both without a prescription and with one’s own prescription) + past-month nicotine use and dep, past-year A, Ca, Co, H, Benz, Stim, coded as no use, use only, or dep/ disorder for each substance
|
Gender |
None |
Across all prescription Op user and misuser groups, men had higher rates of Co than women
Women were more likely to use prescription Op+Benz
Men who were Op users or who misused without a prescription only were more likely to report nicotine dep
Men who were Op users, who misused without a prescription only or who misused with and without a prescription were more likely to report AUD
Men who were Op users and who misused without a prescription only were more likely to report CUD
Men who were Op users or who misused without and with a prescription were more likely to report H
Men who were Op users, who misused without a prescription only, or who misused with and without a prescription were more likely to report Stim misuse
|
Grigsby and Howard, 2019
c
|
Cross-sectional |
|
Concurrent:
past month use of Op, Op+licit drugs (T/A), Op+illicit drugs (Ca, Co, H, LSD, PCP, E, ketamine, DMT/AMT/ FOXY, salvia, Meth, I), Op+ > 1 recreational drug, drug use only
|
Gender
|
None |
|
Husky et al., 2007
|
Cross-sectional |
NESARC, Wave 1, 2001–2002
42,565 nationally represented American adults
57.1% women
Race NR
M
age NR
|
Concurrent:
current T status (daily, occasional, previous), current A and drug abuse and dep (past year); drug diagnoses included abuse and dep for Op, Stim, Ca, Hal, S, Tr, I, and solvents, coded as A Abuse/Dep vs No Current A Abuse/Dep and Current Drug Abuse/Dep vs No Current Drug Abuse/Dep
|
Gender
|
Race, education, marital status and age |
Women with a current AUD had greater odds of being a daily or occasional T user compared with men
Women with DUD had greater odds of being daily T user versus men and similar odds of being an occasional T user
|
Jackson et al., 2020
|
Cross-sectional |
|
Concurrent:
Simultaneous:
|
Gender |
None |
|
John et al., 2018
a
|
Cross-sectional |
National Drug Abuse Treatment Clinical Trials Network, TAPS Tool Study (CTN-0059)
2000 adult primary care patients
56.2% women
28.9% White
M
age = 46
|
Concurrent: - past-year SUD variables: T, A, Ca, Co, prescription Op/H, and Oth (i.e. S, Meth, prescription Stim/Am, Hal, I, other nonspecific drugs), coded as yes/no, subjected to LCA |
Sex
|
Model 1: none Model 2: age, race/ethnicity, education, employment, marital status, study site |
Model 1: Men had increased odds of having multiple SUDs (≥2)
Model 2: Men had increased odds of having multiple SUDs (≥2) compared with having a single SUD
Model 2: Men were at increased odds of being in the Medium SUD Class (high prevalence of TUD), moderate prevalence of AUD, CaUD and CoUD, and low prevalence of Op and Oth DUD) and high SUD class (high prevalence of SUD for Op, T and Co and moderate prevalence of Oth SUDs) compared with low SUD class (low prevalence of all SUD)
|
Linden-Carmichael et al., 2019
|
Cross-sectional |
|
Simultaneous:
|
Sex |
None |
|
Maffli and Astudillo, 2018
|
Cross-sectional |
Swiss national monitoring system (act-info), 2013–2015
10,009 patients in substance-related treatment in Switzerland
Sex NR
Race NR
M
age NR
|
Concurrent:
all combinations of A, Ca, T, Co, Op, hypnotics-S, and Oth, each combination coded as yes/no
|
Sex |
None |
|
McCabe and West, 2017
|
Longitudinal |
NESARC, Wave 1 and Wave 2, 2001–2002 and 2004–2005
34,653 non-institutionalized US adults
Sex NR
Race NR
M
age NR
|
Concurrent:
≥2 past year SUDs, coded as yes/no for each substance: A, Ca, Co, H, Hal, I, prescription Op, S, Stim, and Tr
|
Sex
|
Model 1: none Model 2: race, age, marital status, income, geographical region, sexual identity, past-year nicotine dep, past-year anxiety disorders, past-year mood disorders, lifetime personality disorders |
Model 1 and Model 2: In all models, men were at increased odds of developing multiple SUDs and having 3-year persistence of multiple SUDs |
McCabe et al., 2017
|
Cross-sectional |
|
Concurrent:
past-year, prior to past year, and lifetime use of each substance: A, Ca, Co, H, Hal, I, prescription Op, S or Tr, Stim, and Oth (e.g. E and ketamine)
|
Sex
|
Model 1: none Model 2: age, race, anxiety disorder, mood disorder, personality disorder, eating disorder, posttraumatic stress disorder |
Model 1 and Model 2:
|
Meshesha et al., 2018
|
Cross-sectional |
|
Concurrent:
past-month HD, Ca, and PSU, coded as HD + Ca, or HD + PSU (≥2 illicit drugs)
|
Gender |
None |
|
Midanik et al., 2007
|
Cross-sectional |
|
Concurrent:
past-year A, Ca, and Co/Hal/H/NM use of U/D/painkillers; users categorized as either A-only, A + Ca, or A + Oth Simultaneous:
past-year frequency of A+(‘a specific’) DRUG at the same time, categorized as: A + Ca or A + Oth (Co, Hal, H, or NM use of U, D, or painkillers)
|
Gender
|
Model 1: none Model 2: age, ethnicity, education, income, relationship status, days drinking 5+ drinks |
Model 1: Being a man was associated with simultaneous Ca + A, and simultaneous use of Oth + A
Model 2: No gender difference in concurrent use of Ca + A or Oth + A
|
Morley et al., 2015
a
|
Cross-sectional |
Median age = 27 |
Concurrent:
past-year drug use, coded as yes/no for each substance: Ca, E, Co, Stim, Nitrous oxide, Ketamine, Benz, Op painkillers, subjected to LCA
|
Sex |
Age, country of residence, sexual orientation, qualifications, occupational status, living status, past-year T, past-year A, AUDIT score, desire to use drugs less, treatment for anxiety and/or depression, personality disorder, involvement in violent incident, sexual risk-taking, emergency treatment |
|
Orsini et al., 2018
|
Cross-sectional |
|
Concurrent:
|
Gender
|
None |
|
Pakula et al., 2009
|
Cross-sectional |
|
Simultaneous:
|
Gender
|
None |
Compared with women, men were more likely to be simultaneous users of A + Ca
There were no gender differences likelihood of reporting A + Co
|
Roche et al., 2019
|
Event-level |
|
Simultaneous:
|
Sex
|
Age, ethnicity, source study, and person-means for each predictor variable |
Compared with women, men were more likely to report same-day A + Ca
There was a synergistic effect of A + T for women, but not men
Effects of singular A and T had effect on Ca for men but not women
The synergistic effect of combining T + Ca was greater among women compared with men
No other sex differences observed
|
Ruglass et al., 2020
|
Cross-sectional |
|
Concurrent and Simultaneous:
past 3-month use of Ca and T, categorized as either concurrent Ca + T, (same time period, not simultaneously), and simultaneous Ca + T (at same time so effects overlapped)
|
Sex
|
Model 1: none Model 2: Ca, race, SES, age, health rating, anxiety, stress level, simultaneous A and cig use, days A consumed, other substance use |
Model 1: Simultaneous Ca + T group had a larger proportion of men relative to all other groups
Model 2: Relative to Ca-only group, men (compared with women) were more likely to belong to concurrent or simultaneous Ca + T groups
When compared with simultaneous users, concurrent users were more likely to be women versus men
|
Sadeh et al., 2020
a
|
Cross-sectional |
|
Concurrent and Simultaneous:
lifetime use of: Op Co, Ca, psychedelics, BA, prescription drug misuse and use of ‘multiple drugs at once,’ subjected to LCA
|
Gender |
None |
Women were more likely than men to be in recreational Ca group (occasional Ca and BA)
Men had greater representation in the heavy substance use profiles (heavy Ca Group: high Ca with low levels Oth; heavy multidrug intoxication group: highest levels of simultaneous PSU, and heavy BA, moderate Ca, Co, prescription drug misuse and low levels of H; Heavy Op+PSU, high H, prescription drug misuse and Co)
|
Saha et al., 2018
|
Cross-sectional |
|
Concurrent:
past-year: A + T only, A + Ca only; A + T + Ca only; and A + other drug use (T/Ca/Sed/ Op/Co/Am/club drugs/Hal/I/H/Oth
Past-year AUD only; AUD + TUD only; AUD + CaUD only; AUD + TUD + CaUD only; and AUD + other DUDs (that might include TUD or CaUD in addition to other DUDs)
|
Sex
|
Race/ethnicity, age, marital status, education, income, Urbanicity, region |
Men more likely to report concurrent A + drugs and AUD-DUD
Compared with respondents in A-only group, those using A + T more likely to be men
Men more likely to be in A + Ca Group versus A-only
Compared with those in AUD-only group, respondents in A + T + Ca Group more likely to be men
Odds of using A + other drugs greater among men
Compared with those in AUD-only Group, those in AUD + TUD Group more likely to be men
Compared with those in AUD-only group, those in AUD + CaUD group more likely to be men
Odds of being in AUD + TUD + CaUD group greater among men
|
Schauer et al., 2015
|
Cross-sectional |
|
Concurrent:
|
Sex |
Year, age and race/ethnicity |
|
Subbaraman and Kerr, 2015
|
Cross-sectional |
|
Concurrent and Simultaneous:
|
Gender |
Age, race/ethnicity, education, employment, relationship status, 5+ in a day, avg daily number drinks |
|
Tucker et al., 2020
a
|
Cross-sectional |
|
Concurrent:
past-month use of A, heavy A, T, e-cig with nicotine, Ca, e-cig with hash oil, prescription M without prescription, coded as no days, non-daily use, and daily/near daily use, subjected to LCA
|
Gender
|
Race, ethnicity, marital status, education, age, income, social functioning, mental functioning, physical functioning |
The HD with T/Ca Class (high likelihood of HD, moderate likelihood of daily/almost daily T, and non-daily Ca use) versus to Abstinent Class (slightly elevated daily/near daily T use) was associated with being a man
No gender differences in likelihood of being in T with Prescription Drugs/Ca Class (moderate likelihood of non-daily and daily/near daily T, and non-daily prescription drug misuse and Ca use, but low likelihood of A) versus Abstinent Class
|
Votaw et al., 2020
a
|
Cross-sectional |
|
Concurrent:
past-month BA, prescription Op, Stim, and S (e.g. zolpidem, eszopiclone, zaleplon, temazepam, triazolam, barbiturates) misuse, subjected to LCA
|
Gender
|
Age, race/ethnicity, total number of motives for misuse of Tr, misuse behaviors and past month psychological distress score |
Men had greater odds of expected membership in BA and Ca Use Class (high probabilities of BA and Ca, moderate probabilities of Co, Hal, prescription Op and prescription Stim misuse) and the Op Use Class (high probability of prescription Op use; moderate probabilities of BA, Ca, Co, H, prescription Stim, and Meth use), as compared with the limited PSU Class (moderate BA, Ca and prescription Op misuse; near-zero probabilities of other substance use)
|
Sexual and gender minorities (n = 8) |
Coulter et al., 2019
a
|
Cross-sectional |
Youth Risk Behavior Survey (YRBS), 2015
119,437 adolescents in the US
50.1% girls
49.7% White
85.7% heterosexual
M
age NR
|
Concurrent:
lifetime and past-month A and HED (coded as never A, A in lifetime but not past month, past-month A, but no past-month HED, 1 to 5 HED days past month, ≥6 HED), lifetime and past-month T (cigarette and cigars measured separately), coded as never T, T but not in past month, T 1–5 days past month, ≥6 past-month T, and lifetime and past-month Ca (coded as never, 1–2 times past month, 3–9 times past month, 10–19 times past month, ≥20 past month); subjected to LCA
|
Sex
|
None |
Women were more likely than men to be in the Experimental Users Class (lifetime A, Ca and T but no current use) and Ca-A Users Class (past-month Ca/A, and majority engaged in past month HED) compared with the nonusers class (mostly abstinent from A, T, Ca in lifetime)
Men were more likely than women to be T-A users, medium-frequency 3-substance users and high frequency 3-substance users compared with Nonusers
Youth who identified as heterosexual were less likely than those who identified as gay/lesbian or bisexual to be classified as any use class compared with the Nonusers Class
Sexual minority girls had greatest propensity to be classified in PSU Classes relative to Nonusers Class
|
Day et al., 2017
|
Cross-sectional |
Biennial Statewide California Student survey, 2013–2015
32,072 California middle and high school students
51.2% girls
1% transgender
33.5% White
M
age = 14.74
|
Simultaneous:
past-month use of ≥2 drugs at same time: A, T, Ca, I/NP pain medication, any other drug, pill, or medicine to get ‘high’ or NP, coded as yes/no
|
Gender and sex
|
Model 1: none Model 2: sexual identity, race and ethnicity, and age Model 3: victimization, depressive symptoms, perceived risk of substance use |
Models 1, 2 and 3: transgender youth are at heightened risk for PSU compared with nontransgender peers Model 3: men reported higher odds of PSU |
Dermody, 2018
a
|
Cross-sectional |
Youth Risk Behavior Surveillance System (YRBS), 2015
15,624 nationally representative American students in grades 9–12
49.7% girls
83% heterosexual
43.9% White
M
age NR
|
Concurrent:
past-month A, BA, e-cig, Ca, T (cigarettes measured separately from chewing tobacco/snus/snuff, cigars/cigarillos/little cigars), coded as 0 = none, 1 = at least once; subjected to latent mixture modeling
|
Sex
|
race/ethnicity, sex and age |
Relative to heterosexual youth, gay/lesbian-identified youth were at risk of being T + Ca Co-Users (elevated T + Ca), bisexual youth at risk of being in all 4 substance-using classes, and ‘not sure’ sexuality youth at risk of being PSU/T Users (elevated on all substances except T)
Among boys, no association between sexual minority status and likelihood of being classified in Ca/T Co-Users Group relative to the Non-Users Group (low probabilities of all substances)
Girls who identified as sexual minorities had greater likelihood of being classified in Ca/T Co-Users Group and PSU/T Group than Non-Users Group relative to heterosexual girls
No additional sex differences in sexual minority-related disparities were supported
|
Jun et al., 2019
|
Longitudinal |
Growing Up Today Study (GUTS), Cohorts 1 and 2
12,428 participants assessed 20–35 yo
55.2% women
Race NR
M
age NR
|
Concurrent:
|
Gender
|
Model 1: sexual orientation, gender identity, age, race/ethnicity, region of residence |
Compared with completely heterosexuals, sexual minority (i.e. mostly heterosexual, bisexual, lesbian/gay) participants were generally more likely to 2+ SUDs
Differences in likelihood of ≥2 SUDs between completely heterosexual individuals and those who are mostly heterosexual and lesbian/gay were greater among women than men; no significant gender differences in likelihood of ≥2 SUDs between bisexual and completely heterosexual individuals
No differences in likelihood of having ≥2 SUDs between cisgender and gender minority individuals
|
Kecojevic et al., 2017
|
Longitudinal |
|
Concurrent:
past-year use of ≥3 substances: T, HED, Ca, E, Co, H, LSD, Meth/Am, misuse of prescription Tr, prescription Op, prescription sleeping pills, prescription Stim
|
Gender
|
race/ethnicity, region of residence, report of an adult or sibling living in the household who drinks A |
Compared with their same-gender completely heterosexual peers, sexual minorities evidenced higher risk for concurrent PSU over all repeated measures
Differences between sexual minorities and completely heterosexuals were larger among women than men
|
Nguyen et al., 2021
|
Event-level |
147 young adult smokers
51.7% women
41.5% sexual minority
40.8% White
M
age = 22.7
|
Simultaneous:
|
sex |
age, sex, education, race, psychological distress |
No sex differences in same-day PSU compared with no use or single substance use between women and men
Compared with heterosexual peers, sexual minorities had higher odds of same-day T + Ca and T + Ca + A compared with no PSU
No significant associations for same-day T + A and A + Ca
No interaction between sexual identity and sex
|
Schauer et al., 2013
|
Cross-sectional |
|
Concurrent:
|
Sex
|
Depressive symptoms, perceived stress, satisfaction with life, sensation seeking, Big 5 personality traits |
Among men, no association between sexual orientation and number of substances used
Homosexually and bisexually identified women were more likely to report using greater number of substances than heterosexually identified women
|
Silveira et al., 2019
a
|
Cross-sectional |
Population Assessment of Tobacco and Health (PATH) Study, Wave 1, 2013–2014
6127 nationally represented American youth 15–17 yo
Gender NR
Race NR
M
age NR
|
Concurrent: -past year T, A, Ca, NP Stim, Sed, and Tr, Co, Meth, speed, H, I, solvents, Hal, coded as yes/no; subjected to LCA |
Gender
|
Class proportions, sensation seeking, age, race/ethnicity, urban, grade, parent education, past year internalizing problems, past year externalizing problems, sexual orientation |
Compared with women, men had lower likelihood of membership in A + Ca + T Predominant AM Class (higher probabilities of A + Ca than T), but a higher likelihood of membership in
A + Ca + T Predominant T Class (higher probabilities of T than A + Ca) relative to Abstainer Class (low probabilities of T, A and drugs)
Compared with those of straight sexual orientation, those identifying as lesbian, gay, bisexual or something else had higher likelihood of membership in A + Ca + T Predominant T Class and A + Ma + T + Oth (high probabilities of A, Ca, T, non-prescribed painkillers/Sed and Oth) relative to Abstainer Class
|