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. 2022 Mar 12;57(3):292–321. doi: 10.1093/alcalc/agac006

Table 1.

Characteristics and gender/sex difference and sexuality difference results of included studies (N = 63)

Author (Year) Design Sample Polysubstance use measurement Sex/ gender Covariates in sex/gender model Gender/sex differences results
Adolescents (n = 18)
Banks et al., 2017 Cross-sectional
  • National Survey on Drug Use and Health (NSDUH), 2011–2014

  • 14,667 American students

  • 47.4% girls

  • 61.9% White

  • M age = 16.6

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
  • No gender differences between Ca-use typology: Ca + A, Ca + Oth, Ca + A + Oth (vs. Ca only)

Collins et al., 1998 Longitudinal
  • RAND Adolescent Panel Study

  • 4070 12th graders

  • 54% girls

  • 75% White

  • M age = 15.4

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
 
  • composite PSU frequency index

Gender Ethnicity
  • Compared with girls, boys engaged in more PSU according to the composite frequency and past month variables

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:
  • lifetime A + T, and past school year drunkenness+I, each coded as yes/no; subjected to LCA

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
  • 1501 Spanish high school students

  • 50.6% girls

  • Race NR

  • M age = 14.0

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
  • Compared with girls, boys were more likely to be classified as PSU (recent use of A, Ca and Oth) compared with non-users

Hoffman et al., 2000 Repeated cross-sectional
  • 70,516 7th and 12th graders in New York State

  • Gender NR

  • Race NR

  • M age NR

Simultaneous:
  • past 6-month A + Ca, A + Co coded as yes/no

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
  • Victoria Healthy Youth Survey (V-HYS), 2003–2013

  • 662 Canadian youth

  • 41.9% girls

  • Race NR

  • M age = 15

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
  • Monitoring the Future (MTF), 1976–2016

  • 84,805 US 12th graders

  • 48.4% girls

  • 70.9% White

  • M age NR

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
  • Monitoring the Future, 2005–2015

  • 1719 nationally representative 12-graders

  • 53.2% girls

  • 61.8% White

  • M age NR

Simultaneous:
  • past-year A + Ca, coded as yes/no

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
  • In Models 1 and 2, the odds of A + Ca were higher for boys (vs. girls)

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
  • Compared with girls, boys had higher odds of use of regular and heavy PSU

Purcell et al., 2020 Cross-sectional
  • Healthy Passages, Wave 3, 2009–2011

  • 4129 US adolescents

  • 51% girls

  • 25% White

  • M age = 16.10

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
  • Rural Adaptation Projects, fourth year

  • 7074 low-income rural adolescents

  • 51.8% girls

  • 29% White

  • M age = 14.8

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
  • Compared with girls, boys had higher odds of being at risk for more types of substances used

Smit et al., 2002 b Cross-sectional
  • Dutch National School Survey on Substance Use, 1999

  • 6236 nationally surveyed Dutch students

  • Gender NR

  • 76.2% Dutch origin

  • M age = 14

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:
  • past-year A + Ca; 2 variables created: any simultaneous use coded as yes/no, and simultaneous use most or every time, coded as yes/no

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
  • COMPASS (2013–2018)

  • 79,879 Canadian 9-12th graders (43,312 included in PSU analyses)

  • 46.1% girls

  • 80.2% White

  • M age NR

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
  • NSDUH, 2006

  • 55,279 non-institutionalized civilians

  • 51.6% women

  • 64,1% White

  • M age NR (majority >35yo)

Concurrent:
  • current use or abuse/dep of prescription Op and past-year A or T, each coded as yes/no

Gender None
  • No gender differences in the number of current prescription Op users who endorsed past-year A or T

Bassiony and Seleem, 2020 Cross-sectional
  • 100 treatment seeking adults diagnosed with SUDs

  • 7% women

  • Race NR

  • M age = 30.7

Concurrent:
  • positive urine screen of ≥2: Ca, codeine, hypnotics, A, opium, tramadol, Hal, H, coded as yes/no

Sex None
  • Compared with women, men were more likely to report PSU

Beswick et al., 2001 Cross-sectional
  • 116 treatment seeking Op users

  • 29% women

  • Race NR

  • M age = 35.5

Simultaneous:
  • Benz+H, Cr + H (timeframe NR) each coded as yes/no

Gender None
  • Compared with women, men were more likely to use Benz+H

  • Women were more likely to use Cr + H

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
  • MAX-98 Project, 1998

  • 5539 Swedish heavy drug users (past-year narcotic injection or drug use daily/nearly daily for the past month)

  • 23% women

  • Race NR

  • M age NR

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:
  • frequency of past 6-month use of T, A, Ca, and Oth

Simultaneous:
  • frequency of past 6-month: T + A, Ci + Ca, A + Oth, Ca + Oth

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:
  • past-year NMPS+A at same time, coded as yes/no

Concurrent:
  • past-year NMPS+A coded as yes/no

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
  • National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), Wave 2, 2004–2005

  • 33,107 adults

  • 58% women

  • 75.7% White

  • M age NR

Concurrent:
  • lifetime presence of drug+A abuse and/or dep, coded as yes/no

Gender None
  • Compared with women, men were more likely to have ever had a PSU-related disorder

Evans et al., 2017e Cross-sectional
  • NESARC Waves 1 and 2, 2001–2002 and 2004–2005

  • 2860 non-institutionalized US adults

  • 35.7% women

  • 66.6% White

  • M age NR

Concurrent:
  • past 12-month PSU SUD, coded yes/no

Gender None
  • Compared with women, men had a higher probability of poly-SUD persistence

Falk et al., 2008 Cross-sectional
  • NESARC, Wave 1, 2001–2002

  • 43,093 adults

  • Gender NR

  • Race NR

  • M age NR

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
  • 4102 patients in public therapeutic communities in Spain

  • 13.2% women

  • Race NR

  • M age = 36.6

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
  • 1345 partygoers who reported past-year use of ≥1 substance

  • 32.5% women

  • 54.1% Spain country of residence

  • M age = 26.9

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
  • National Household Survey on Drug Abuse, 1985

  • 9630 respondents of national US survey

  • 46.9% women

  • Race NR

  • M age NR

Concurrent:
  • past-month or past year A + Co

Simultaneous:
 
  • past-year or past-month A + Co at same time

Sex None
  • Compared with women, men had higher prevalence of both concurrent and simultaneous past-year and past-month A + Co use

Grant & Harford, 1990g Cross-sectional
  • National Household Survey on Drug Abuse, 1985

  • 9630 respondents of national US survey

  • 46.9% women

  • Race NR

  • M age NR

Concurrent:
  • past-year A, S, and Tr

Simultaneous
  • past-year A + S and A + Tr at the same time (or within a couple of hours)

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
  • NSDUH, 2016–2017

  • 29,241 past-year prescription Op users in the US

  • Gender NR

  • Race NR

  • M age NR

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
  • NSDUH, 2016

  • 26,033 civilian non-institutionalized US, 12+ yo, reporting past month substance use

  • 51.5% women

  • 63.4% White

  • M age NR

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
  • Men had a higher risk of past-month prescription Op misuse with illicit drug or PSU

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
  • 1360 past-year A and Ca using college students

  • 62% women

  • 69% White

  • M age = 19.8

Concurrent:
  • past 3-month A + Ca, but not simultaneously, coded 0 = no use past 3 months, to 7 = ≥daily

Simultaneous:
  • past 3-month frequency of A + Ca at same time so effects overlapped, recoded ordinal frequencies to days

Gender None
  • Simultaneous A + Ca users were more likely to be men (compared with A-only users)

  • No gender differences in concurrent A + Ca users and A-only users

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
  • 1017 young adults with past-month A use

  • 32.2% women

  • 71.5% White

  • M age = 21.66

Simultaneous:
  • past-year A + Ca (occurring within a few hours of each other), coded as yes/no

Sex None
  • Compared with women, men were more likely to be A + Ca users (versus A-only users)

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
  • All subgroups showed majority of men except the combination A/hypnotics-S, which showed majority women

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
  • NESARC-III, 2012–2013

  • 36,309 nationally representative American adults

  • Sex NR

  • Race NR

  • M age NR

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:
  • Compared with women, men had a higher prevalence of multiple SUD in lifetime, before past year and past year

Meshesha et al., 2018 Cross-sectional
  • 358 college students who reported ≥2 past-month HD episodes

  • 60% women

  • 79% White

  • M age = 18.76

Concurrent:
  • past-month HD, Ca, and PSU, coded as HD + Ca, or HD + PSU (≥2 illicit drugs)

Gender None
  • Women were less likely to be in the drug-using groups compared with men

Midanik et al., 2007 Cross-sectional
  • National Alcohol Survey (NAS), 2000

  • 7612 US adults

  • 50% women

  • Race NR

  • M age NR

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
  • Global Drug Survey, 2012

  • 14,869 adults living in UK, Australia, and US

  • 31.5% women

  • Race NR

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
  • Compared with the PSU classes, participants in the Non-PSU Class (no PSU; moderate probability of Ca-only) were more likely to be women (vs. men)

Orsini et al., 2018 Cross-sectional
  • 5131 NCAA college athletes

  • 50.8% women

  • 79.7% White

  • M age = 18.84

Concurrent:
  • 2+ substances (A/T/ Ca/prescription drugs) in the last month, coded as yes/no

Gender None
  • Compared with women, men were more likely to report PSU

Pakula et al., 2009 Cross-sectional
  • 874 clients in treatment in Ontario, Canada reporting past-year Ca or Co use

  • Gender NR

  • Race NR

  • M age = 33.5

Simultaneous:
  • past-year combined use of Ca + A and Co + A, each coded as yes/no

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
  • 179 non-treatment seeking regular drinkers from the Los Angeles area

  • 27.53% women

  • 31.07% White

  • M age = 29.02

Simultaneous:
  • Past-month use of A, T, Ca; use of each drug each day coded as yes/no; same-day effects examined

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
  • 3-Campus Alcohol and Marijuana Study (3CAM)

  • 1390 Past-year Ca using US college students

  • 62.4% women

  • 63.8% White

  • M age = 19.8

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
  • 1106 adults recruited from forensic and community samples who endorsed illicit drug use and/or misuse of prescription drugs

  • 43.4% women

  • 72.9% White

  • M age = 32.99

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
  • NESARC-III

  • 36,309 US non- institutionalized civilian population

  • Sex NR

  • Race NR

  • M age NR

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
  • NSDUH, 2003–2012

  • 378,459 nationally representative adults

  • Sex NR

  • Race NR

  • M age NR

Concurrent:
  • Past-month T, Ca, coded as yes/no for each combination of use

Sex Year, age and race/ethnicity
  • Compared with Ca-only and T-only users, a higher percentage of co-users of Ca + T were men

Subbaraman and Kerr, 2015 Cross-sectional
  • National Alcohol Survey (NAS), 2005 and 2010

  • 8626 nationally represented American adults

  • 52.4% women

  • Race NR

  • M age NR

Concurrent and Simultaneous:
  • past-year Ca + A (separately always) and simultaneous Ca + A, categorized as mutually exclusive groups

Gender Age, race/ethnicity, education, employment, relationship status, 5+ in a day, avg daily number drinks
  • Risk of simultaneous and concurrent use (relative to only use) did not differ by gender

Tucker et al., 2020 a Cross-sectional
  • RAND American Life Panel (ALP)

  • 1877 national sample of US adults ages 30–80

  • 48% women

  • 69% White

  • M age = 56

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
  • NSDUH, 2015–2017

  • 1253 national survey of adults with past-month Tr misuse

  • Gender NR

  • Race NR

  • M age NR

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:
  • past-year probable T dependence, A abuse and Dep, and drug abuse and Dep; co-occurring multiple SUDs (≥2) coded as yes/no

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
  • GUTS, Cohort 1

  • 13,519 sexual minority and heterosexual participants followed 12–29 yo

  • 58% girls/women

  • 93% White

  • baseline Mage = 14.6

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:
  • 30-day record of same-day use of each of the following: T + Ca, T + A, Ca + A, T + Ca + A

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
  • 4840 American students from 6 southeastern colleges

  • 71.2% women

  • 93.7% heterosexual

  • 46.7% White

  • M age = 23.5

Concurrent:
  • past 30-day T, Ca, A, coded as 0–3 according to the number of substances used

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

Note. A = alcohol, Am = amphetamines, AUD = alcohol use disorder, AUDIT-C = Alcohol Use Disorder Identification Test-Consumption, AY = academic year, BA = binge alcohol/drinking, Benz = benzodiazepines, Bup = buprenorphine, Ca = cannabis, Co = cocaine/crack, CNS = central nervous system drugs, primarily amphetamines, D = downers, Dep = dependence, DUD = drug use disorder, E = ecstasy, e-cig = electronic cigarette, H = heroin, Hal = hallucinogens, HD = heavy drinking, HED = heavy episodic drinking, I = inhalant, LCA = latent class analysis, LPA = latent profile analysis, LSD = lysergic acid diethylamide, M = medication, Meth = methamphetamine, NM = non-medical, NR = not reported, NP = not as prescribed/not prescribed, Oth = other drug/other illicit drug, Op = Opioids/opiates, PS = prescription stimulants, PSP = Phencyclidine, PSU = polysubstance use/user, S = sedatives, Stim = stimulants, SUD = substance use disorder, T = tobacco/cigarette, Tr = tranquilizers, U = uppers, UD = use disorder, yo = years old.

Sex/Gender column refers to whether sex and/or gender were included in the analysis examining its association with polysubstance use. The term(s) is written in boldface italicized text if it was a primary aim of the study analyses (vs. secondary aim). Study type is specific to how the gender/sex differences were analyzed.

aStudy used LCA/LPA or latent mixture modeling to identify classes of substance use/PSU; for details regarding classes, see original article.

bStudy used homogeneity analysis through alternating least squares (HOMALS) to identify Clusters of substance users who resemble each other.

cStudy includes participants under the age of 18, but Mage > 18; therefore, article included in adult section of table.

dArticle title is: Gender differences in the effects of childhood adversity on alcohol, drug and polysubstance-related disorders.

eArticle title is: Gender and race/ethnic differences in the persistence of alcohol, drug and poly-substance use disorders.

fArticle title is: Concurrent and simultaneous use of alcohol with cocaine: results of national survey.

gArticle title is: Concurrent and simultaneous use of alcohol with sedatives and with tranquilizers: results of a national survey.