Using cross-sectional data from 6348 chronically infected HCV patients, we found that current cannabis use was associated with a 55% lower likelihood of central obesity (elevated waist circumference), a 73% lower likelihood of obesity (BMI ≥ 30 kg/m²), and a 53% lower likelihood of overweight (BMI between 25 and 30 kg/m²), when compared with no lifetime cannabis use. To our knowledge, this is the first time that such associations have been highlighted for HCV-infected patients.

Our results are in line with those found in general populations in different countries (Meier et al. 2019; Alshaarawy and Anthony 2019; Sidney 2016; Ngueta et al. 2015; Clark et al. 2018). For instance, Ngueta et al., among Inuit adults, found an OR of 0.56 for obesity (BMI ≥ 30 kg/m²) for past-year cannabis use as compared to non-users (Ngueta et al. 2015). They also found a similar association between frequent cannabis use (but not former nor infrequent use) and concurrent elevated triglycerides and waist circumference (Ngueta 2020). However, causal association was not found in a recent Mendelian randomization study (Alayash et al. 2021). Our results are also in line with what we found in a previous study for patients with chronic hepatitis B virus from the same cohort (Barré et al. 2021a).

One possible explanation for the relationship between cannabis use and corpulence is that such frequent use may downregulate cannabinoid receptor 1 (CB1)—which regulates appetite and body weight, thereby reducing energy storage and increasing metabolic rates (Clark et al. 2018; Spindle et al. 2021). In two preclinical studies, CB1 antagonists and peripherally restricted CB1 antagonists (i.e., with no effect on the central nervous system) showed some efficacy on obesity and metabolic syndrome (O’Sullivan et al. 2021; Lopez Trinidad et al. 2021).

However, assuming that the effects of cannabis are solely attributable to the most abundant phytocannabinoid Δ9-tetrahydrocannabinol (THC) (Cluny et al. 2015) and/or are only mediated through CB1 may be reductive. Cannabis exposes users to a large number of phytocannabinoids, as well as to non-cannabinoid molecules, such as terpenoids (Russo 2018). The most abundant phytocannabinoids in cannabis are THC, cannabidiol (CBD), and Δ9-tetrahydrocannabivarin (THCV). Beside their varying affinity for CB1 and CB2, these cannabinoids also interact with other targets such as transient receptor potential channels, GPR55 receptor, or peroxisome proliferator activated receptors, which in turn may impact energy metabolism (Bielawiec et al. 2020; Abioye et al. 2020). Moreover, cannabis compounds may have anti-oxidant and anti-inflammatory properties (Atalay et al. 2019; Bielawiec et al. 2021; Henshaw et al. 2021; Graczyk et al. 2021), inflammation being a major element in chronic diseases, especially metabolic and obesity-related disorders (Cavalheiro et al. 2022; Ellulu et al. 2017). Non-cannabinoid cannabis compounds such as limonene, β-caryophyllene, and other terpenes may also play a role in the corpulence lowering effect of cannabis use (Hashiesh et al. 2021; Jing et al. 2013; Scandiffio et al. 2020). Finally, a synergetic effect, resulting from the interactions between those compounds, cannot be excluded (Russo 2018).

By lowering body weight, cannabis use may have an indirect beneficial effect on liver disease and metabolic disorders in patients with chronic HCV infection. Cannabis and/or cannabis compounds may also have a direct beneficial effect on these problems. More specifically, a growing body of research, including observational, preclinical, and clinical data, suggests that phytocannabinoids may play a role in the prevention or treatment of hepatic steatosis (Berk et al. 2021; Barré et al. 2021b). As modulators of the endocannabinoid system, which is a main therapeutic target for treating diabetes mellitus (Veilleux et al. 2019), cannabis compounds may exert a beneficial role on the development of diabetes in different populations (Bielawiec et al. 2020; Wargent et al. 2013; Jadoon et al. 2016; Meah et al. 2021), including HCV-infected people (Barré et al. 2020). Observational studies have also highlighted a potential role of cannabis compounds in liver disease prevention in this population (Adejumo et al. 2018; Santos et al. 2020).

We adjusted our analyses for tobacco use, which is common in European cannabis users (Hindocha et al. 2016) and is associated with lower body weight (Audrain-McGovern and Benowitz 2011). Accordingly, the effect of cannabis use we found cannot be imputed to tobacco use.

The other factors associated with both definitions of obesity in our study were socioeconomic status, African origin, and history of HCV treatment. The inverse relationship between socioeconomic status and elevated body weight/obesity is multifactorial and has been widely documented (Newton et al. 2017; Vieira et al. 2019; Wang and Beydoun 2007; Pigeyre et al. 2016; Hruby et al. 2016). A higher BMI and/or risk of obesity in African-Americans, as well as immigrants from Africa in Europe, has also been reported (Shai et al. 2006; Agyemang et al. 2016; Toselli et al. 2014; Min et al. 2021; Abraham et al. 2013). This is a complex phenomenon and involves socio-cultural, economic, and genetic factors.

We found that a history of HCV treatment (interferon-based and 1^st/2^nd generation DAA) was associated with a higher risk of obesity. This may seem counter-intuitive given the documented weight loss-inducing effect of interferon (Alam et al. 2013). Elsewhere, elevated BMI/obesity was an independent risk factor for nonresponse to previous antiviral treatment (Bressler et al. 2003; Asselah et al. 2010). Therefore, as HCV-cured patients were not included in our analyses, participants with a history of HCV treatment were more likely to have risk factors for nonresponses (i.e., obesity) than those with no such history.

The main strength of the present study is its large sample size. The inclusion of socio-behavioral factors is another strength, as it is widely recognized that these factors greatly impact body weight. The assessment of corpulence through two distinct markers (waist circumference and BMI) and the consistency of our results across the different models suggest they are robust. It has previously been highlighted that a measure of waist circumference provides both independent and complementary information to the BMI value when predicting morbidity and mortality. This is likely to be at least partly due to its ability to identify adults with increased visceral adipose tissue mass (Ross et al. 2020).

Some study limitations need to be acknowledged. First, cannabis use was self-declared, and we therefore cannot exclude potential desirability bias, which was however equally likely in people with and without obesity. Second, data on frequency of cannabis use were not collected, preventing the possibility of conducting dose-response analyses. Similarly, cannabinoid content of cannabis products was unknown. However, most recent data indicated that THC levels are increasing in both herb and resin in France and other European countries, reaching around 11 and 18% THC in France, respectively (Freeman et al. 2021; Gandilhon et al. 2019). Third, data for some of the most important determinants of elevated body weight (i.e., dietary intakes and physical activity) were not available. However, we can assume that socioeconomic variables captured part of these effects.