Our study found significant differences in BMI prevalence in subjects enrolled in MAT programmes compared to state and national trends. We found a higher overall prevalence of overweight (26.5%) and obese (42.4%) individuals in our cohort compared to state surveillance data. Additionally, the overall underweight prevalence (4.6% of the study population) was significantly higher in our cohort compared to state and national data. These trends may provide insight for future physicians to assess high-risk factors for proper prevention and intervention.

We were surprised to find unexpected racial and ethnic trends that were strikingly different among these OUD than among state and national surveillance populations. National studies examining BMI show Black non-Hispanic adults have higher prevalence of overweight and obesity. In contrast, Black non-Hispanic cohort subjects were significantly more likely to be underweight than what was predicted by either NJBRFS (SPR=6.71, p=0.007) or NHIS data (SPR=7.36, p=0.005) [31, 32]. Additionally, half of the Hispanic subjects were obese. Hispanic subjects comprised a little over a fifth of the cohort population and although in our study the observed obesity prevalence in adult Hispanic subjects was not statistically significant, it was higher than reported in other studies done in the general adult Hispanic population of New Jersey (27.5%) and in the US (42.5%) [33].These findings highlight the need to screen and treat OUD as part of a strategy to manage the opioid and obesity epidemic. Age, race, and ethnicity should be used to stratify risk in individuals with OUD, especially considering their increased likelihood for more severe disease and mortality from contracting infections like COVID-19 and HIV.

Gender differences observed may be a result of different drug use history, age of initiation, duration, and type of drugs utilized. Our study found men tended to be more underweight than NJBRFS (SPR=7.44, p=0.016) or NHIS (SPR=7.69, p=0.015) rates, similar to a comparable study conducted among male drug addicts vs non-addicts in Dhaka, Bangladesh [34]. In contrast, females in our study had a higher prevalence of obesity than those calculated from NJBRFS data (SPR=1.44, p=0.026). This phenomenon could be due to the fact that older women are more likely to have a different drug use history than men, leading to a different set of health outcomes in the long term. For example, a 2014 study on the gender differences in self-reported BMI in drug users in Latin America found a positive BMI correlation with older women who were more likely to use over-the-counter analgesics and tranquilizers [35]. In the United States, which is a developed country, there is an inverse relationship between education and obesity observed especially for women [36]. Low education level is one of many socioeconomic factors that have been shown to be strong predictors for the risk of obesity [36, 37].

Persons who inject drugs (PWID) comprise 54.3% of our drug user cohort, all of whom have a history of opioid addiction. Previous studies have associated PWID using opioids with being underweight [34, 38, 39]. One plausible explanation may be that opioids may take precedence over seeking nutritional food, leading to long-term poor dietary patterns and nutritional deficiency [34, 38]. The combination of being a PWID and underweight poses a significant health risk. Nutritional deficiencies and malnourishment increase susceptibility to infections. Particularly with PWID, the risk and management of HIV is of great concern [34, 38, 40].

In drug cohort studies during the 1980s, the opioid epidemic was primarily manifested among PWID. However, the opioid epidemic has evolved, perhaps explaining the increase in non-PWID seen in our current cohort. Addiction to post-surgical pain medications has emerged as a common introduction to OUDs. Purity of street opioids has increased, minimizing the extent to which tolerance builds, and costs have plummeted. The introduction of fentanyl to the illegal drug markets has provided many with extreme highs and increasing mortality. In line with the changing demographics of the opioid epidemic, the younger group, who are more likely to have non-PWID patterns of use, showed increased tendency to be overweight (SPR=0.61, p=0.043) or obese (SPR=1.68, p=0.005) than the New Jersey population from NJBRFS. We found the older group (subjects > 50 years old), who tended to use more injection opioids than the younger group (subjects ≤ 50 years old). Older subjects were also more likely to be underweight than rates calculated from NJBRFS and NHIS data (SPR=4.03, p=0.037 and SPR=4.89, p=0.02 respectively). In our data persons who did not inject drugs (non-PWID), which are 45.7% of our cohort, were more likely to be overweight compared to general population calculated from NJBRFS data (SPR=0.58, p=0.027). This is a surprising result, since previous studies have not found a significant relationship between non-PWID and BMI [39].

Our study found that obese subjects were less likely to be regular cannabis users than subjects of normal weight (p=0.011). Cannabis is thought to be an appetite stimulant in low-weight individuals; a phenomenon colloquially termed as “the munchies” [41]. Overeating could be in competition with cannabis in brain reward sites [42]. Our finding suggests that the effect of regular cannabis use may not be a primary contributing factor to the increased obesity prevalence in this cohort; instead, the increased obesity prevalence observed in this cohort is likely multifactorial. Several studies have reported alcohol consumption to be associated with an increased BMI, however in our study we found obese individuals were less likely to be heavy drinkers (p=0.030) [38, 43]. Barry et al. found BMI is positively associated with a lifetime risk for alcohol abuse in men and inversely associated with the risk of drinking in the last year for women [43]. Patterns of drinking such as frequency and quantity (ex. binge drinking) must be key considerations in epidemiological research studying alcohol and BMI and illicit drug use [43].