Objective:Health consequences of commercializing nonmedical cannabis remain unclear, but data suggest that youth may encounter unintended risks. This study examined whether cannabis marketing expos...

There is limited information about the potential individual-level and contextual drivers of heavy drinking in South Africa. This study aimed to identify risk factors for heavy drinking in Tshwane, South Africa. A household survey using a multi-stage stratified cluster random sampling design. Complete consumption and income data were available on 713 adults. Heavy drinking was defined as consuming ≥120 ml (96 g) of absolute alcohol (AA) for men and ≥ 90 ml (72 g) AA for women at any location at least monthly. 53% of the sample were heavy drinkers. Bivariate analyses revealed that heavy drinking differed by marital status, primary drinking location, and container size. Using simple logistic regression, only cider consumption was found to lower the odds of heavy drinking. Persons who primarily drank in someone else’s home, nightclubs, and sports clubs had increased odds of heavy drinking. Using multiple logistic regression and adjusting for marital status and primary container size, single persons were found to have substantially higher odds of heavy drinking. Persons who drank their primary beverage from above average-sized containers at their primary location had 7.9 times the odds of heavy drinking as compared to persons who drank from average-sized containers. Some significant associations between heavy drinking and age, race, and income were found for certain beverages. Rates of heavy drinking were higher than expected giving impetus to various alcohol policy reforms under consideration in South Africa. Better labeling of the alcohol content of different containers is needed together with limiting production, marketing and serving of alcohol in large containers.

Background Intimate partner violence (IPV) victims and perpetrators often report suicidal ideation, yet there is no comprehensive national dataset that allows for an assessment of the connection between IPV and suicide. The National Violent Death Reporting System (NVDRS) captures IPV circumstances for homicide-suicides (98% of suicides). Objective To facilitate a more comprehensive understanding of the co-occurrence of IPV and suicide, we developed and validated a tool that detects mentions of IPV circumstances (yes/no) for single suicides in NVDRS death narratives. Methods We used 10 000 hand-labelled single suicide cases from NVDRS (2010–2018) to train (n=8500) and validate (n=1500) a classification model using supervised machine learning. We used natural language processing to extract relevant information from the death narratives within a concept normalisation framework. We tested numerous models and present performance metrics for the best approach. Results Our final model had robust sensitivity (0.70), specificity (0.98), precision (0.72) and kappa values (0.69). False positives mostly described other family violence. False negatives used vague and heterogeneous language to describe IPV, and often included abusive suicide threats. Implications It is possible to detect IPV circumstances among singles suicides in NVDRS, although vague language in death narratives limited our tool’s sensitivity. More attention to the role of IPV in suicide is merited both during the initial death investigation processes and subsequent NVDRS reporting. This tool can support future research to inform targeted prevention.