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. Author manuscript; available in PMC: 2023 Aug 10.
Published in final edited form as: Subst Use Misuse. 2022 Aug 10;57(11):1663–1672. doi: 10.1080/10826084.2022.2107670

Differential associations between weight status (obesity, overweight, underweight) and substance use in young adulthood

H Isabella Lanza a, Monica Orozco a, Gabriella Motlagh b
PMCID: PMC9582253  NIHMSID: NIHMS1837590  PMID: 35946172

Abstract

Background:

Past evidence suggests obesity co-occurs with tobacco/nicotine, cannabis, and alcohol use in young adulthood, but whether this relationship extends to nicotine or cannabis vaping is unclear. Furthermore, differential relationships between substance use and specific weight status categories (obesity, overweight, underweight) have not been assessed. The current study assessed prevalence of tobacco/nicotine, cannabis, and alcohol use by weight status categories in young adulthood.

Methods:

1,322 young adults (18–29 years; 20.5±2.3 years; 63% female; 42% Hispanic/Latino/a/x, 30% Asian-American/Asian, 18% Caucasian/White, 7% Multiracial, and 2% African-American/Black) from a public, urban university were surveyed on their health-risk behaviors in the spring and fall of 2021.

Results:

Multinomial logistic regression models assessed six-month follow-up substance use prevalence (never, lifetime but no past 30-day use, past 30-day use) by baseline weight status (obese, overweight, underweight; reference: healthy weight). Obesity predicted lower odds of past 30-day nicotine vaping (aOR[95% CI]=.27[.08-.92]). Overweight predicted higher odds of lifetime combustible cannabis (aOR[95% CI]=1.58[1.08–2.30]) and past 30-day binge drinking (aOR[95% CI]=1.79[1.12–2.85]). Underweight was associated with lower odds of lifetime cannabis vaping (aOR[95% CI]=.35[.12-.99]) and combustible cannabis (aOR[95% CI]=.38[.16-.87]).

Conclusions:

Differential relationships between obesity and overweight on tobacco/nicotine, cannabis, and alcohol use suggest greater specificity is needed when evaluating relationships between higher weight status and substance use. It appears that overweight young adults may be at higher risk of substance use than obese young adults. Greater efforts to consider multiple weight status groups, not just obese, may have significant implications for tobacco/nicotine prevention and intervention efforts targeting vulnerable populations.

Keywords: binge drinking, cannabis/marijuana, vaping, obesity, tobacco/nicotine, weight status

Introduction

Obesity and substance use among adolescents and young adults remain two of the most pressing public health concerns in the U.S.; both are linked to pervasive health declines across the lifespan, including earlier mortality risk, mental health deficits, and physical impairments (Stewart et al., 2009; Zheng et al., 2017; Shulte & Hser, 2013). After unsurpassed growth in the 1980s and 1990s, obesity rates have plateaued but remain high; recent estimates report 40% of young adults meet obesity status (body mass index ≥ 95th percentile; Fryar et al. 2020). Undoubtedly, the popularity of vaping use has led to a renormalization of tobacco/nicotine use and increase in cannabis use among younger populations (Fairchild et al., 2014; Pearson & Villanti, 2020; Walley et al., 2019). According to recent Monitoring the Future (MTF) reports on young adults aged 19–30 (Schulenberg et al., 2021), sizeable growth in past 30-day nicotine vaping (6.2% to 13.7%) and cannabis vaping (6.1% to 10.8%) occurred between 2017 and 2020. Alongside these increases in vaping, combustible cannabis has increased steadily in the past decade (15.3% to 26.8%), whereas past 30-day cigarette smoking (14.8% to 9.5%), and past 30-day alcohol use/being drunk (38.2% to 30.8%) has declined. The transition from adolescence to young adulthood – emerging adulthood - presents a critical period for examining the co-occurrence of these health-risks. Obesity status during this period is predictive of chronic obesity and metabolic-related diseases through adulthood (Gordon-Larsen et al., 2010; Nelson et al., 2008; Zheng et al., 2017), and problematic substance use often arises during this developmental stage (Palmer et al., 2009; Sussman & Arnett, 2014; Wood, 2018). Though the past decade has seen increasing attention to the relationship between obesity and substance use, with multiple studies highlighting positive relationships between obesity and substance use in young adulthood (e.g., Daw et al., 2017; Fazzino et al., 2017; Hussaini et al., 2011; Lanza et al., 2014), empirical work has yet to evaluate whether prevalence of nicotine and cannabis vaping significantly differs by weight status, or address differential relationships between weight status categories (obese, overweight, underweight) and tobacco/nicotine, cannabis, and alcohol use in young adulthood.

Given the marked neuro-cognitive and socio-contextual challenges occurring in emerging adulthood, examining co-occurring health-risks during this developmental period has been at the forefront of much research (Park et al., 2014; Peters et al., 2012; Small et al., 2012); however, relatively less research has cut across health-risk dimensions of higher weight status and substance use. There is a growing consensus that obesity or higher body mass index (BMI) predicts cigarette smoking in young adulthood (Hussaini et al., 2011; Koval et al., 2008; Lanza et al., 2014), but whether links between obesity and cigarette smoking extend to nicotine vaping is unclear, as no study has yet examined the direct association between obesity or higher BMI and e-cigarette/vaping use in young adulthood. Though focused on adolescence, two recent large-scale, epidemiological studies have reported mixed findings: Delk et al. (2019) indicated a positive relationship between obesity and e-cigarette/vaping use among a sample of close to 3,000 Texas middle- and high-school boys, while Cho et al. (2018) reported null findings between higher BMI and e-cigarette/vaping use using high school data from the Youth Risk Behavior Survey (YRBS). These findings should be taken with some caution as both studies analyzed data from 2015 to early 2016, just prior to the emergence of pod-based devices linked to a surge in nicotine vaping and cannabis vaping use (Huang et al., 2019; Spindle & Eissenberg, 2018). Additionally, these studies were cross-sectional, thus limiting knowledge as to whether obesity/high BMI predicts e-cigarette/vaping use. Considering strong evidence that cigarette smoking and e-cigarette/vaping use significantly co-occur in young adulthood (Kenne et al., 2016; Khouja et al., 2021; Sutfin et al., 2015), it is likely that the relationship between obesity and cigarette smoking extends to nicotine vaping in young adulthood.

Compared to studies evaluating the relationship between obesity or higher BMI and tobacco/nicotine use in young adulthood, less attention has been paid to cannabis. In a review of the literature on marijuana use and cardiovascular risk factors and outcomes, Ravi et al. (2018) argued that lack of prospective studies significantly limit our ability to accurately understand the relationship between cardiovascular risk factors and outcomes, including obesity, and cannabis use. Moreover, available cross-sectional studies have reported mixed findings on higher weight status and cannabis use. For example, while Hu et al. (2020) found a lower risk of marijuana dependence in obese adolescents and adults using cross-sectional data from the National Survey of Drug Use and Health (NSDUH), Muniyappa and colleagues (2013) reported significant positive associations between visceral adiposity and chronic combustible cannabis use in their cross-sectional, control-case study of 30 adults. In addition to their cross-sectional nature, current studies do not draw conclusions specific to young adults, particularly during the emerging adulthood period that is known for its specific contexts and challenges (e.g., transitioning to college, workforce, increased autonomy, and financial responsibility, etc.; Arnett, 2011; Wood, 2018). Furthermore, these studies have not included prevalence of cannabis vaping, which has grown considerably in the past few years (Schulenberg et al., 2021). Thus, there is a clear need for longitudinal studies addressing higher weight status and multiple cannabis product use in young adulthood.

Past research on higher weight status and alcohol use has generally indicated positive associations between obesity and binge or heavy drinking among young adults (Daw et al., 2017; Fazzino et al., 2017). In a prospective analysis from adolescence to adulthood using data from the National Longitudinal Study of Adolescent Health (Add Health), Daw and colleagues (2017) indicated that participants categorized as ‘least healthy’ had a high likelihood of obesity, binge drinking, and cigarette smoking across adolescence and young adulthood, but prediction from obesity status to substance use was not tested. Using the same sample (Add Health), but specifically across young adult and adulthood waves, Fazzino et al. (2017) tested the direction from heavy episodic drinking to higher weight status and reported higher risk of overweight and obesity status among heavy episodic drinkers, but the direction from higher weight status to problematic drinking was not assessed. Beyond the need for longitudinal analyses evaluating whether higher weight status predicts problematic substance use in young adulthood, the current literature on higher weight status and substance use highlights another limitation of existing literature; the lack of knowledge as to whether substance use prevalence differs between healthy weight young adults and multiple non-normative weight status categories (i.e., obese, overweight, underweight). Though there is speculation that a U-shaped relationship between BMI and substance use exists (Amiri & Behnezhad, 2018), there is a dearth of substance use research incorporating assessment of obese, overweight, and underweight status. Understanding whether young adults from specific weight status categories are at higher or lower risk of various types of substance use (tobacco/nicotine, cannabis, alcohol) can potentially inform more tailored prevention and intervention addition health services.

The current prospective study sought to identify differences in substance use prevalence (including nicotine vaping, cigarette smoking, cannabis vaping, combustible cannabis, and binge drinking) across multiple weight status categories (e.g., obese vs. healthy weight) in young adulthood. The study advances previous work on obesity and substance use by considering multiple weight status categories (obese, overweight, underweight, healthy weight) alongside popular forms of substance use (e.g., nicotine and cannabis vaping) in a longitudinal cohort of emerging adults attending college. With close to two-thirds (61.8%) of U.S. high school graduates attending college (U.S. Bureau of Labor Statistics, 2022), college students are an increasingly valuable population for understanding substance use trends (Buu et al., 2020; Lanier & Farley, 2011), especially as they have similar rates of substance use compared to other young adults (Schulenberg et al., 2020) and experience major life transitions that leave them vulnerable to risky behavior (Stone, et al. 2012; Willoughby et al., 2014). Given the high co-occurrence between cigarette smoking and e-cigarette/vaping use and growing consensus that obesity or higher BMI significantly co-occurs with cigarette smoking, we expected that belonging to higher weight status categories (obesity and overweight) would predict higher likelihood of cigarette smoking and nicotine vaping compared to healthy weight and underweight. The mixed and comparatively small literature on weight status-cannabis associations in young adulthood suggest there may be more nuance in weight status categories and cannabis use. Due to weaker relationships previously reported for obesity, we hypothesized that overweight would specifically predict higher likelihood of combustible cannabis or cannabis vaping compared to healthy weight and underweight. Finally, past findings indicating positive relationships between obesity and alcohol use resulted in the expectation that higher weight status categories (obesity and overweight) would predict higher likelihood of binge drinking vs. healthy weight and underweight.

2. Methods

Participants and procedure

The study included data from a prospective cohort study of 1,322 young adults attending a large, urban public university. During Spring 2021, 93 classes were randomly selected for participant recruitment from all non-asynchronous undergraduate classes. The PI sought approval from course instructors to present study information and recruit participants during class time (which took place online due to COVID-19 restrictions). Of the 93 randomly selected classes, 67 (72.0%) instructors agreed to a 10-minute class visit (20.4% of instructors did not respond and 7.5% declined to participate). Study presentations and recruitment during class time were conducted by the PI from late January to late April 2021 (Spring 2021). The aim of the class visit was to build rapport between participants and the study, which could ultimately reduce attrition in this longitudinal (two-year, 5 assessment waves) online survey study. Following the study presentation, eligible (≥ 18 years, currently enrolled undergraduate) and interested participants were able to review the informed consent online by either clicking a link shared on the class chat or through a study information email forwarded by the instructor to students. Once a student completed and submitted the informed consent form online, the PI individually emailed the participant with the online survey link, as well as an individual verification code. Participants completed a 15-minute health behavior survey that included questions on eating habits, exercise, weight status, substance use, mood, personality, and social relationships. To avoid identifying information being collected within the online survey, the unique verification code was used to link a participant’s survey with their informed consent, which was used to email participant incentives for completing the survey ($15 Amazon egiftcard). Six months after baseline (Fall 2021), participants were contacted by email to complete a follow-up survey via the same procedure and incentive. All study protocol was approved institution removed for blind review.

Of 2,651 students targeted in 67 randomly selected classes, 1,381 students (52.1%) participated in the study. Participants between 18–29 years were selected for current study analyses (N=1,322; 95.7% of total sample). The average age of participants at baseline was M = 20.53 (SD = 2.30) years. The sample closely aligned with the gender and race/ethnicity composition of the institution’s undergraduate population. Participants in the sample included (university Fall 2020 statistics in parentheses): 62.7% (59.4%) female, 34.9% (40.6%) male; 2.4% transgender or gender variant/non-binary/non-conforming; 41.5% (47.9%) Hispanic/Latino/a/x, 30.3% (25.3%) Asian-American/Asian, 17.9% (16.1%) Caucasian/White, 2.0% (3.7%) African-American/Black, 7.4% (4.6%) Multiracial; 0.8% (0.2%) Pacific Islander/Native Hawaiian, 0.1% (0.1%) Native American/Alaskan Native. About two-thirds (63.8%) reported their parents attending some college or a higher level of education.

Measures

Weight status

Participants self-reported height and weight at baseline (Wave 1), which was used to calculate body mass index (BMI; weight(lbs)/[height(in)2 × 703). Based on U.S. Centers for Disease Control (CDC) recommendations (https://www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/), participants were categorized into one of four weight status categories: obese (BMI ≥ 30.0); overweight (BMI 25.0–29.9); underweight (BMI < 18.5); and healthy weight (BMI 18.5–24.9).

Substance use prevalence

Lifetime and past 30-day use of nicotine vaping, cigarette smoking, cannabis vaping, combustible cannabis, and binge drinking were assessed with participant self-report at baseline (Wave 1) and six-month follow-up (Wave 2). For each type of substance, participants were asked about lifetime use: “Have you ever used a vaporizer to vape nicotine (e.g., Puff Bar, JUUL, Box mod)?”; “Have you ever smoked a cigarette?”; “Have you ever used a vaporizer to vape cannabis (e.g., Pax Era, Heavy Hitters, Dosist, Kandypens)?”; “Have you ever smoked cannabis (marijuana, weed, pot)?”; “Have you ever consumed more than 5 alcoholic drinks in one sitting (if you are a man) or 4 alcoholic drinks in one sitting (if you are a woman)?”. If participants reported lifetime use for a specific substance, they were asked a corresponding question on past 30-day use: “In the past 30 days have you vaped nicotine?”; “In the past 30 days have you smoked a cigarette?”; “In the past 30 days have you vaped cannabis?”; “In the past 30 days have you smoked cannabis?”; “In the past 30 days have you consumed more than 5 drinks in one sitting (if you are a man) or 4 drinks in one sitting (if you are a woman)?”. Due to low cell counts for high-frequency use patterns resulting in large standard errors, dichotomous responses (0=no past 30-day use, 1=past 30-day use) were used to measure past 30-day substance use prevalence. For each substance, responses for lifetime use (0=no ever use, 1=ever use) and past 30-day use (0=no past 30-day use, 1=past 30-day use) were recoded for multinomial logistic regression analyses (0=never use, 1=lifetime use (without past 30-day use), 2=past 30-day use).

Sociodemographic covariates

Sociodemographic characteristics including age, gender, ethnicity/race, and parent highest education were self-reported at baseline (Wave 1). Participants reported their age in years, gender (female, male, transgender female, transgender male, gender variant/non-binary/non-conforming), race/ethnicity (African-American/Black, Asian-American/Asian, Caucasian/White, Hispanic/Latino/a/x, Native American/Alaskan Native, Pacific Islander/Native Hawaiian, Multi-racial, and other), and highest parent education (less than some high school, some high school, graduated from high school, some college, graduated from college, earned graduate degree). Gender was recoded into two dummy variables (female vs. non-female, male vs. non-male) to account for the 2.5% of participants reporting transgender or gender variant/non-binary/non-conforming status (a sole dummy variable, female vs. male, would exclude this group from analyses). Race/ethnicity was recoded into dummy variables (Asian American/Asian vs. non-Asian American/Asian) for racial/ethnic groups representing ≥10% of the sample (89.7% of total sample was comprised of Hispanic/Latino/a/x: 41.5%, Asian American/Asian: 30.3%; and Caucasian/White: 17.9%). Highest parent education was recoded into a binary variable (≥ some college vs. < some college).

Analysis plan

Following descriptive analyses, a series of multinomial logistic regression models assessed substance use prevalence at six-month follow-up by baseline weight status for five substance use variables (nicotine vaping, cigarette smoking, cannabis vaping, cannabis smoking, binge drinking). Obese, overweight, and underweight weight status categories were compared to the reference group, healthy weight, on substance use prevalence. Multinomial substance use outcomes included current (past 30-day) use, lifetime (without past 30-day) use, and never use (as the reference group). Following unadjusted models, sociodemographic covariates (age, gender, race/ethnicity, parent education) and baseline lifetime (ever) substance use were included in adjusted models to determine the odds of lifetime (without past 30-day) and past 30-day use at six-month follow-up based on obesity, overweight, or underweight status at baseline. A Bonferroni multiple-comparison test correction was applied to reduce the chance of type I error; the alpha was set to .01. Analyses were conducted using Stata Version 17 (StataCorp, 2021). Of the 1,322 participants in the study, 1097 (83.0%) completed the six-month follow-up survey. Compared to young adults with available follow-up data, young adults without follow-up data did not significantly differ on demographics, but they were less likely to report binge drinking (t(1289)=−3.00, p<.01) and combustible cannabis (t(1287)=−3.30, p<.001) at baseline.

Results

Descriptive characteristics

Table 1 presents sociodemographic characteristics of the total sample (N=1322) and by weight status category (obese, overweight, underweight, healthy weight) at baseline. Approximately 14% (13.8%) of participants were classified as obese (BMI > 30); 21.0% were identified as overweight (BMI 25.0–29.9); 6.2% were classified as underweight (BMI < 18.5); and 59.0% were within the healthy weight range (BMI 18.5–24.9). A one-way ANOVA indicated significant differences in age by weight status, F (3, 1276) = 15.72, p<.001. Post-hoc contrasts indicated those in the obese category were significantly older (p < .001) compared to young adults in the underweight and healthy weight categories; similarly, young adults in the overweight category were significantly older compared to the underweight (p < .01) and healthy weight (p < .01) categories. Chi-square tests of independence (χ2) were conducted to test whether other sociodemographics and substance use significantly differed by weight status at baseline; significant pairwise comparisons were identified using a Bonferroni correction. Significant differences across weight status categories were identified for ethnicity/race χ2=119.67, p<.001, but not for gender or parent education (African-American/Black more likely in obese vs. overweight, underweight, and healthy weight; Asian-American/Asian more likely in underweight and healthy weight vs. obese and overweight; Caucasian/White more likely in healthy weight vs. obese and overweight; Hispanic/Latino/a/x more likely in obese and overweight vs. underweight and healthy weight).

Table 1.

Sociodemographic characteristics (N = 1322)

Total Sample Obese (n=176; BMI > 30.0) Overweight (n=268; BMI 25.0–29.9) Underweight (n=79; BMI < 18.5) Healthy Weight (n=754; BMI 18.5–24.9)
Demographics N(%) or Mean ± SD
Age (years)***a 20.53 ± 2.30 21.27 ± 2.81 20.96 ± 2.45 19.85 ± 1.96 20.25 ± 2.05
Gender
 Female 829 (62.7%) 108 (61.4%) 149 (55.6%) 54 (68.4%) 489 (64.9%)
 Male 461 (34.9%) 62 (35.2%) 107 (39.9%) 23 (29.1%) 254 (33.7%)
 Non-Binary 27 (2.0%) 5 (2.8%) 10 (3.7%) 2 (2.5%) 9 (1.2%)
 Transgender 5 (0.4%) 1 (0.6%) 2 (0.8%) 0 (0.0%) 2 (0.3%)
Ethnicity/Race***
 African-American/Blackb 26 (2.0%) 11 (6.3%) 3 (1.1%) 0 (0.0%) 10 (1.3%)
 Asian-American/Asianc 401 (30.3%) 27 (15.3%) 62 (23.1%) 36 (45.6%) 265 (35.1%)
 Caucasian/Whited 236 (17.9%) 17 (9.7%) 36 (13.4%) 15 (19.0%) 158 (21.0%)
 Hispanic/Latino/a/xe 549 (41.5%) 106 (60.2%) 148 (55.2%) 22 (27.8%) 251 (33.3%)
 Native American/Alaska Native 1 (0.1%) 1 (0.6%) 0 (0.0%) 0 (0.0%) 0 (0.0%)
 Pacific Islander/Native American 11 (0.8%) 0 (0.0%) 2 (0.7%) 2 (2.5%) 7 (0.9%)
 Multiracial 98 (7.4%) 14 (8.0%) 17 (6.3%) 4 (5.1%) 63 (8.4%)
Parent Highest Education Level
 ≥ some college 844 (63.8%) 99 (56.3%) 165 (61.6%) 48 (60.8%) 498 (66.%)
 < some college 476 (36.0%) 77 (43.8%) 103 (38.4) 31 (39.2%) 753 (33.8%)
 Unknown 2 (0.2%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 (0.1%)
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***

p < .001 for omnibus Chi-square test of independence.

a

Older participants more likely (p < .001) in obese or overweight vs. underweight or healthy weight categories.

b

African-American/Black more likely (p < .05) in obese vs. overweight, underweight and healthy weight categories.

c

Asian-American/Asian more likely (p < .05) in underweight and healthy weight vs. obese and overweight categories.

d

Caucasian/White more likely (p < .05) in healthy weight vs. obese or underweight category.

e

Hispanic/Latino/a/x more likely (p < .05) in obese and overweight vs. underweight and healthy weight categories.

As shown in Figures 1 and 2, significant differences across baseline weight status on lifetime use (with or without past 30-day use) and/or past 30-day use at six-month follow-up was observed for each type of substance use (except cigarette smoking): lifetime (χ2=9.20, p<.05) and past 30-day (χ2=13.67, p<.01) nicotine vaping (obese < overweight, healthy weight); lifetime cannabis vaping χ2=10.95, p<.05 (overweight > underweight, healthy weight; healthy weight > underweight); lifetime combustible cannabis χ2=19.07, p<.001 (overweight > obese, underweight, healthy weight; obese and healthy weight > underweight); and both lifetime (χ2=20.90, p<.001; overweight > obese, underweight, healthy weight; obese and healthy weight > underweight) and past 30-day (χ2=9.49, p<.05) binge drinking (overweight > obese, underweight, healthy weight). Across the entire sample, lifetime and past 30-day substance use at baseline was highest for binge drinking (lifetime: 47.1%; past 30-day: 20.0%) and lowest for cigarette smoking (lifetime: 18.0%; past 30-day: 3.4%). Lifetime (31.0%) and past 30-day (12.7%) cannabis vaping rates were higher than lifetime (28.2%) and past 30-day (10.0%) nicotine vaping rates, respectively.

Figure 1.

Figure 1.

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Prevalence Rate of Lifetime Use (With or Without Past 30-day Use) by Weight Status Categories at Baseline

* p < .05; *** p < .001 for omnibus Chi-square test of independence.

Shared superscripts between weight status categories indicates significant (p < .05) difference on the specified substance use variable; aObese vs. Overweight; bObese vs. Underweight; cObese vs. Healthy Weight; dOverweight vs. Underweight; eOverweight vs. Healthy Weight; fUnderweight vs. Healthy Weight.

Figure 2.

Figure 2.

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Prevalence Rate of Past 30-Day Use by Weight Status Categories at Baseline

* p < .05; ** p < .01 for omnibus Chi-square test of independence.

Shared superscripts between weight status categories indicates significant (p < .05) difference on the specified substance use variable; aObese vs. Overweight; cObese vs. Healthy Weight; dOverweight vs. Underweight; eOverweight vs. Healthy Weight.

Unadjusted models of substance use by weight status categories

First, unadjusted multinomial regression analyses were conducted to determine odds of six-month follow-up lifetime (without past 30-day use) vs. never use and past 30-day use vs. never use of nicotine vaping, cigarette smoking, cannabis vaping, combustible cannabis, and binge drinking by weight status (obese, overweight, underweight; reference group: healthy weight) at baseline. Compared to the healthy weight group, young adults meeting obesity status had lower odds of past 30-day nicotine vaping (aOR [95% CI]=.20[.07-.54]). Young adults meeting overweight status had higher odds of lifetime cigarette smoking (aOR [95% CI]=1.67[1.11–2.50]) and combustible cannabis (aOR [95% CI]=1.68[1.20–2.37]), and higher odds of both lifetime (aOR [95% CI]=1.54 [1.07–2.21]) and past 30-day (aOR [95% CI]=1.77[1.20–2.61]) binge drinking vs. the healthy weight group. Compared to healthy weight peers, young adults meeting underweight status had lower odds of lifetime cannabis vaping (aOR [95% CI]=.28[.10-.79]), combustible cannabis (aOR [95% CI]=.31[.14-.70]), and binge drinking (aOR [95% CI]=.40[.19-.84]).

Adjusted models of substance use by weight status categories

Following unadjusted models, covariates were added to model adjusted multinominal regressions. Table 2 presents adjusted odds ratios for lifetime (without past 30-day use) and past 30-day use (reference: never use) of each type of substance at six-month follow-up by baseline weight status category (reference: healthy weight). Young adults meeting obesity status had lower odds of past 30-day nicotine vaping aOR[95% CI]=.27[.08-.92]) vs. the healthy weight group. Compared to the healthy weight group, young adults meeting overweight status had higher odds of lifetime combustible cannabis (aOR [95% CI]=1.58[1.08–2.30]), and higher odds of past 30-day binge drinking (aOR [95% CI]=1.79[1.12–2.85]). Young adults meeting underweight status had lower odds of lifetime cannabis vaping (aOR [95% CI]=.35[.12-.99]) and combustible cannabis (aOR[95% CI]=.38[.16-.87]) compared to healthy weight peers.

Table 2.

Estimated Adjusted Odds Ratios (aOR) of Lifetime (without past 30-day use) and Past 30-day Substance Use by Weight Status Categories

Lifetime use (without past 30-day use) vs. never use Past 30-day use vs. never use
Reference group: Healthy Weight (BMI 18.5–24.9) aOR(95%CI) aOR(95%CI)
Nicotine Vaping
 Obese (BMI > 30.0) .70(.41–1.21) .27(.08–.92)**
 Overweight (BMI 25.0–29.9) 1.12(.74–1.72) 58(.27–1.23)
 Underweight (BMI < 18.5) .77(.35–1.69) .85(.26–2.80)
Cigarette Smoking
 Obese (BMI > 30.0) .76(.43–1.33) .66(.16–2.67)
 Overweight (BMI 25.0–29.9) 1.18(.76–1.83) .84(.29–2.45)
 Underweight (BMI < 18.5) 1.04(.44–2.43) .44(.05–4.23)
Cannabis Vaping
 Obese (BMI > 30.0) .76(.45–1.30) .98(.47–.2.07)
 Overweight (BMI 25.0–29.9) 1.24(.82–1.89) 1.43(.78–2.64)
 Underweight (BMI < 18.5) .35(.12–.99)** 1.24(.42–3.62)
Combustible Cannabis
 Obese (BMI > 30.0) .68(.42–1.10) 1.09(.50–.2.34)
 Overweight (BMI 25.0–29.9) 1.58(1.08–2.30)** 1.59(.83–3.02)
 Underweight (BMI < 18.5) .38(.16–.87)** 1.03(.33–3.17)
Binge Drinking
 Obese (BMI > 30.0) .77(.48–1.24) .76(.42–1.40)
 Overweight (BMI 25.0–29.9) 1.34(.90–1.99) 1.79(1.12–2.85)**
 Underweight (BMI < 18.5) .52(.24–1.11) .88(.39–2.00)
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**

p < .01.

Multinomial substance use outcome models (lifetime without past 30-day use vs. never use, past 30-day use vs. never use) include a weight status category regressor variable (reference group: healthy weight) adjusted for age, gender, race/ethnicity, parent education, and baseline lifetime (ever) use for the corresponding substance.

Discussion

The current study advanced knowledge of the relationship between weight status and substance use in emerging adulthood by assessing lifetime and current prevalence of common types of substance use (tobacco/nicotine, cannabis, alcohol) across multiple weight status categories. The study not only extended prior knowledge by evaluating the relationship longitudinally in young adulthood and incorporating both nicotine and cannabis vaping, but also better informed the literature by examining substance use prevalence among multiple weight status categories: obese, overweight, and underweight vs. healthy weight. These more nuanced weight status comparisons resulted in distinct differences in substance use by weight status category. Obese and overweight young adults, often viewed as more similar than different in relation to physical and psychosocial consequences, reported unique associations with substance use; while obese young adults had lower odds of nicotine vaping vs. healthy weight peers, overweight young adults had higher odds of both combustible cannabis and binge drinking compared to healthy weight counterparts. These distinct differences between weight status categories and substance use prevalence are likely to have significant implications for prevention and intervention efforts aimed at decreasing co-occurring health-risks in young adults. Though obese status earns significantly more research and clinical attention than overweight status, overweight young adults’ significantly higher risk of cannabis use and binge drinking compared to healthy weight young adults suggests they may be a key target group for anti-cannabis and anti-binge drinking public health initiatives.

Given growing consensus that higher weight status is associated with higher risk of cigarette smoking in young adulthood (Hussaini et al., 2011; Koval et al., 2008; Lanza et al., 2014), and strong evidence that e-cigarette use and cigarette smoking significantly co-occur in young adults (Kenne et al., 2016; Khouja et al., 2021; Sutfin et al., 2015), we hypothesized that previously observed associations between higher weight status and cigarette smoking would extend to nicotine vaping. However, the expected positive association between higher weight status (obesity and overweight) and nicotine vaping was not observed in this study. In contrast, obese young adults reported lower odds of past 30-day nicotine vaping compared to healthy weight young adults. This unexpected finding underscores the importance of examining heterogeneity of tobacco/nicotine product use among vulnerable populations. Though not reported in this current study, past research linking obesity to cigarette smoking in young adulthood suggests that there may be different risk and protective processes underlying cigarette smoking vs. nicotine vaping use among obese young adults. We speculate that obese young adults may be less likely to nicotine vape compared to healthy weight peers due to perceptions that e-cigarette/vaping use is primarily for “cool” young adults and used for peer socialization (Kong et al., 2015; Saddleson et al., 2016; Sutfin et al., 2013, 2015); potentially the social stigma and marginalization obese individuals commonly experience (Puhl & Heuer, 2010; Puhl & King, 2013) may decrease opportunities for nicotine vaping. Future work examining the underlying mechanisms resulting in lower risk of nicotine vaping among obese young adults is warranted, especially to determine whether tobacco/nicotine prevention and intervention efforts targeting obese young adults need to focus more specifically on cigarette smoking or expend significant resources to nicotine vaping.

The current study also added to the limited literature on weight status and cannabis use in young adulthood. Considering past research on weight status-cannabis associations has resulted in mixed findings (Hu et al., 2020; Muniyappa et al., 2013; Ravi et al., 2018), including null or negative relationships between obesity and cannabis use, we expected overweight, but not obese, young adults to report higher likelihood of cannabis use compared to healthy weight peers. Notable differences across non-normative weight status categories partially supported our hypothesis. Overweight young adults had higher odds of lifetime combustible cannabis use (vs. healthy weight), while underweight young adults had lower odds of both lifetime cannabis vaping and combustible cannabis (vs. healthy weight). Though previous physiological and neuroscience studies have shown that acute vs. chronic cannabis use may explain differential relationships between cannabis use and weight status outcome (acute use is associated with weight gain while chronic use is associated with weight loss; Farokhnia et al., 2020; Sansone & Sansone, 2014), there is currently a dearth of studies examining how weight status influences cannabis use.

In addition to higher likelihood of combustible cannabis, overweight young adults also had higher odds of past 30-day binge drinking compared to healthy weight young adults. However, the expected positive relationship between obesity and binge drinking, identified in previous studies on young adults (Daw et al., 2017; Fazzino et al., 2017), was not found. Though we did not compare obese and overweight young adults directly to each other in this study, the differences in combustible cannabis and binge drinking risk when compared to healthy weight peers highlights the need for future studies to identify underlying risk and protective processes that can inform why substance use risk may differ across weight status categories. One promising direction for future empirical work is examining social behavior or context that may differ between obese and overweight young adults. For example, the greater deviation from the peer group norm obese vs. overweight individuals experience may limit obese young adults’ opportunities to engage in cannabis and alcohol use, which often takes place at social events with peers during the college years (Chauvin et al., 2012; Gunn et al., 2021’ White et al., 2016). On the other hand, overweight status may reflect a group that more recently shifted from healthy to unhealthy weight during the transition to college (Vadeboncoeur et al., 2015), and are using cannabis and/or alcohol as a coping mechanism (Espinosa et al., 2022; Krieger et al., 2018).

Limitations of this study should be considered when interpreting findings. The use of a sample specific to the Southern California region limits generalizability of findings to other regions; however, a regionally-specific sample increases the likelihood participants were experiencing similar regulatory tobacco, cannabis, and alcohol policies, as well as trends in vaping use. During the time period survey data was collected (over the course of 2021), COVID-19 restrictions in California that limited capacity for most businesses, including bars, vape shops, and cannabis dispensaries were gradually lifted. The dynamic academic and social context college students experienced during this year may explain why significant weight status-substance use relationships were either identified for lifetime (without past 30-day use) or past 30-day use, but not both for a given substance; unique contextual differences during assessment periods may have resulted in less alignment between past 30-day and lifetime prevalence findings. As the social context stabilizes post-pandemic, it will be critical to examine whether the current study findings are replicated. We also recognize that the use of dichotomous substance use measures limited the variability in the sample, thus preventing a comprehensive analysis on the impact weight status has on frequency of use. Though notable large epidemiological studies have also relied on dichotomous lifetime and past 30-day substance use measures (e.g., Cohn et al., 2019; Grucza et al., 2018; Nguyen et al, 2019), prioritizing the use of more heterogenous data is imperative going forward. Furthermore, the focus on college students precludes generalizability to all young adults, but the high rate (61.8%) of U.S high school students enrolling directly into college suggests that college students are becoming increasingly representative of the U.S. young adult population (U.S. Bureau of Labor Statistics, 2021). The study also relied on self-reported vs. directly measured BMI. Although directly measured vs. self-reported height and weight is ideal, self-reported height and weight is still of value when direct measurement is unfeasible (e.g., online surveys); past research has indicated that self-reported BMI has high concordance with directly measured BMI among adolescents and young adults (Field et al., 2007; Davies et al., 2020; Lipsky et al., 2019). That said, it is important to recognize that BMI, whether directly measured or self-reported, is not as accurate an indicator as anthropometric measures (e.g., visceral adiposity) for evaluating healthy vs. unhealthy status (Camhi et al., 2011; Nuttall, 2015).

The differential associations observed across tobacco/nicotine, cannabis, and alcohol use by weight status – lower likelihood of nicotine vaping among obese young adults, higher likelihood of combustible cannabis use and binge drinking among overweight young adults, and lower likelihood of combustible cannabis and cannabis vaping among underweight young adults (compared to healthy weight peers) - highlights the importance of considering weight status in substance use prevalence in emerging adulthood. Past literature linking weight status to behavioral health outcomes, like substance use, has heavily focused on obesity status, but findings from the current study suggest overweight status may be a better predictor of cannabis or binge drinking in young adulthood. Future research, particularly using nationally representative epidemiological studies, would benefit from incorporating the three non-normative weight status categories in analyses to better inform which groups are in most need of addiction health services. If these studies replicate the findings reported in this study, the effectiveness of public health initiatives and clinical prevention/intervention efforts will likely improve by targeting messages, education, and treatment to overweight young adults. A more nuanced view of the role weight status plays on substance use prevalence in younger populations is likely to improve current efforts to reduce co-occurring health-risks earlier in the lifespan.

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