Although it also conflicts with prior evidence of disparities in nicotine and cannabis product use observed among lesbian and gay adolescents and young adults , it does align with two recent studies in which bisexual-identified, but not lesbian- or gay-identified adults, reported higher current use of some tobacco products relative to heterosexual-identified adults . The findings of the current study should be considered in the context of its limitations. One limitation is the relatively low representation of sexual minority young adults in our sample. While the percentage of sexual minority participants in the current report is comparable to other studies of sexual orientation and young adult substance use , a judicious interpretation of our findings is therefore encouraged, particularly for prevalence estimates that had wide confidence intervals. The small sample size also limited our ability to examine sexual identity differences in poly-substance use of nicotine and cannabis products, which we would expect to be high among sexual minority young adults . An additional study limitation relates to our inability to assess all three dimensions of sexual orientation , a practice that is increasingly normative in research with young adults, who may still be establishing their sexual identity. Although the data that correspond with the current analyses did not include items assessing sexual behavior or sexual attraction, these items will be administered to participants at the next wave of data collection for the Southern California Children’s Health Study. Our assessment of sexual identity is further limited by our inability to assess sexual minority identity labels that are non-traditional but increasingly common among sexual minority individuals, which will also be assessed in subsequent waves of the study.
There are also several limitations to the generalizability of our findings to sexual minority young adults outside of the current study. First, school-based studies necessarily exclude high school dropouts,home schooled students, and adolescents not in attendance at the time of survey administration. Given that sexual minority adolescents are more likely to drop out of school, face housing instability, and have poor school attendance , the school-based design of initial enrollment into the Southern California Children’s Health Study may be a source of sampling bias. Additionally, our findings may not generalize to sexual minority young adults outside of the Southern California region. Many of the prevalence estimates for nicotine and pot for growing marijuana product use for bisexual young adults reported here are larger than estimates observed for sexual minority young adults in similar cross-sectional studies , particularly with respect to cannabis use. This may be attributable to the unique legal landscape in California on issues that likely impact nicotine and cannabis product use among sexual minority young adults relative to other areas of the country . Future replication in U.S. settings that differ from California on these dimensions is warranted to better understand the role that contextual factors specific to California may have played in the current study. While the appeal of e-cigarettes and cannabis is on the rise among young adults in general, our data suggest that bisexual young adults may be especially at risk. Although gender-stratified results of the interaction analysis suggest that this risk may be compounded among female– relative to male—bisexual young adults, these findings warrant cautious interpretation given that the interactive effect of sexual identity and gender on lifetime product use only reached statistical significance for cigarette use. Nevertheless, future research examining substance use trends among young adult sexual minority populations should further explore the potentially moderating role of gender within this relationship. The prevalence of bisexual self-identification appears to be increasing rapidly relative to other sexual minority identities in the U. S.—especially among younger populations . Thus, the already disproportionate public health burden that bisexual individuals face will likely grow wider yet in the coming years, particularly if concerning trends around bisexual young adults’ substance use persist unchecked. The results reported here underscore the urgent need to prioritize this population as among the highest risk subgroup in need of enhanced substance use prevention efforts across the domains of research, policy, and clinical practice.
It is also imperative that future research elucidate why existing substance use screening, prevention, and intervention services continue to fall short for bisexual adolescents and young adults and how such programming can be tailored to address factors that play a unique role in motivating their substance use. To this end, identifying risk or protective factors that may influence the disproportionate nicotine and cannabis use observed in this vulnerable population is warranted. In the cannabis industry, be it medicinal or recreational, there is an abundance of control measures in place to ensure product safety and efficacy. Contamination of cannabis plants with toxic heavy metals such as arsenic, cadmium, lead etc. can result from numerous origins. Sources of contamination include environmental pollution such as emissions from factories and automobiles, contaminated water, some pesticides, and naturally occurring metals in soil and fertilisers. The contamination of the herbal material ultimately leads to contamination of the products during various stages of the manufacturing process. During growth, metals accumulate in the biomass of specific plants. Studies conducted on industrial hemp show that the cannabis plant bio-accumulates heavy metals from the soil, and thus is readily employed for phytoremediation of contaminated soils. There have been reported cases of post processing adulteration of cannabis buds, adding heavy metals to increase the weight of the product to purposely increase the street value. Pesticides that contain arsenic and mercury as part of their structures were commonly utilised until a few years ago, and are still employed to date. These toxic substances are likely to be present in many foods due to their abundance in nature, and it is important to note that associated ingestion or inhalation of these cannabis products would add to the accumulation of heavy metals consumed by people, even if best practice guidelines are followed. As a result of the new regulation imposed by the USP in collaboration with the ICH, the detection limits for certain metals have been lowered. Heavy metal residues in pharmaceutical end products, active pharmaceutical ingredients and excipients need to be controlled and should be at a certain limit for safe human consumption. Furthermore it can be noted in the somewhat unique case of cannabis based products, that an alternative route of administration of these products does occur, namely inhalation. The pharmacopeial guideline stipulates three routes of administration namely: Parenteral, Oral and Inhalation.ICP-MS is employed to detect heavy metal contamination. As a result low residue limits can be imposed by USP 232. Heavy metals are classified into different classes according to their toxic potential, class 1 being the most dangerous, class 2 less toxic and class 3 having the highest limits and being the least toxic. This study will focus on Class 1 and 2 metal residues given they present the greatest health risk to consumers. It is the aim of this study to analyse a segment of the South African cannabis-based products in circulation and provide a detailed overview of the elemental impurities/heavy metal residues contained in these products. Furthermore, the adherence of these samples to the imposed inhalation as well as oral limits by the ICH and USP will also be evaluated.
To date no data of this kind exist in South Africa. With these data, regulators, medical doctors and the public can gain a better sense of the dangers currently being faced regarding cannabis based products in South Africa. A total of 310 samples were submitted to a South African contract laboratory for analysis. Manufacturers are defined as any type of user, retailer, reseller, producer, or importer of cannabis-based products. Whether these manufacturers maintain the full value chain or only a portion thereof they are defined as manufacturers for the purpose of this study. Manufacturers may include cultivators of plants, producers of products, importers, resellers, and pharmaceutical manufacturers. Sample data will be presented anonymously. It should be noted that samples were analysed as received by the laboratory irrespective of whether plant material was dry or wet. Dry plant material will have a larger portion of elemental impurities as a result of the moisture mass loss during the drying process. The moisture content of the sample may influence results significantly since they are reported in a mass per mass unit. All samples were analysed in duplicate. Class 1 and 2 heavy metal test panels were analysed . It should be noted that the majority of samples were cannabis-based products, with very few samples submitted for the analysis of soil and water. Consent was provided to employ the data for research purposes. The samples were categorised into seven different types and are shown in Table 2, the same as reported by a potency study conducted by the same laboratory. Approximately 200 mg of each sample was weighed, digested in 10% HNO3 for 1 h at 100◦C and diluted 35 times to a total volume of 7 mL. Internal Standard Y and In was used for matrix interference correction. Since large isolate as well as extract sample quantities are scarce, a method needed to be developed to be able to employ as small as possible sample quantity while still being able to reach the USP232/ICHQ3D limits. Analysis started with a blank run, then a 5 point calibration curve, followed by a control standard every 10 duplicates, to avoid instrumental drift. Sample sets were ended by analysing a control standard to ensure all samples within a sample set adhered to bias and variation limits as per USP232/ICHQ3D. The data were grouped into two major groups containing categories applicable to either the inhalation limits and/or categories applicable to the oral specification limits as per USP232/ICHQ3D. All categories were included in the oral specification limit, since all samples needed to be compared to a specification. As for the inhalation specification,container for growing weed the following categories were grouped together for comparison; Extract, Liquid and Plant Material. Since it is not known by the laboratory what the final intended use of the products were, these three categories posed the highest likelihood being dosed in inhalation form. The two major dosage form groups were also subdivided into two different categories. Tabulated results of the data are shown in Appendix A, Tables A1–A4. Individual elemental data are grouped within categories according to specification as mentioned above. It should be noted that the applicable categories together with metal residues that failed will be displayed. If a metal was present in the test method but had no failures it will not be displayed on the figures.
The presence of each residue is also displayed for the analysed 310 samples, together with the limit of detection for each residue in Table A3. Additionally, Appendix A, Table A4, shows the number of samples that failed when they are evaluated against the different specification limits. Furthermore, the table also shows the number of samples for which heavy metal residues could be detected, irrespective of the concentration. A visual representation of the data is given in Figs. 1, 2 and 3. Represented in this data set is a small portion of samples obtained from the South African market. It is by no means a representative sample of the entire South African market, but inferences can be made nonetheless. The dataset will be discussed in two sections, relating to individual heavy metal residues as well as relating to samples. When comparing the individual heavy metal residues that are presented in Fig. 1 against the oral limit, it is evident that the following 3 metals are responsible for most failures: lead , arsenic and nickel . Detection of Class 1 residues above the USP/ICH oral specification limits were responsible for 91% of all residue failures identified in this study. It is further interesting to note, that only four of the seven categories contained heavy metals at concentrations high enough to cause a failure. The categories that did not contain residues at concentrations high enough to fail could be as result of the concentration dilution being performed or alternatively the process removes metal residues to some degree. For example, when Infusions are considered a dilution of concentration cannabinoids is prepared and consequently other residues like heavy metals and solvents are also diluted.