Inequality and adolescent cannabis use: A qualitative comparative analysis of the link at national level

Long-Term Impact of Medical Marijuana Laws on the Burden of Cannabis Use Disorders in US Male and Female Adolescents and Young Adults

Deregulation of cannabis use has raised concerns regarding its potential effects on health, particularly in adolescents and young adults. Here, we extracted data from the Global Burden of Disease database to estimate the long-term effect (> 5 years) of medical marijuana laws (MML) on 2019 cannabis use disorders Disability Adjusted Life Years (2019 CUD DALYs) in US male and female adolescents (15-19 years old) and young adults (20-24 years old). Socio-cultural, demographic and economic characteristics were used as baseline covariates. To improve the robustness of estimation, we took advantage of machine learning techniques. We found no significant effect of MML on 2019 CUD DALYS in each of our four age/sex groups. Estimates from a marginal structural model taking into account age and sex strata in the same model were also non-significant. Our findings suggest that MML may have a negligible effect (if any) on cannabis use disorders in this population group.

The impact of state cannabis legislation, county-level socioeconomic and dog-level characteristics on reported cannabis poisonings of companion dogs in the USA (2009-2014)

With current trends in cannabis legalization, large efforts are being made to understand the effects of less restricted legislation on human consumption, health, and abuse of these products. Little is known about the effects of cannabis legalization and increased cannabis use on vulnerable populations, such as dogs. The objective of this study was to examine the effects of different state-level cannabis legislation, county-level socioeconomic factors, and dog-level characteristics on dog cannabis poisoning reports to an animal poison control center (APCC). Data were obtained concerning reports of dog poisoning events, county characteristics, and state cannabis legislation from the American Society for the Prevention of Cruelty to Animals’ (ASPCA) APCC, the US Census Bureau, and various public policy-oriented and government websites, respectively. A multilevel logistic regression model with random intercepts for county and state was fitted to investigate the associations between the odds of a call to the APCC being related to a dog being poisoned by a cannabis product and the following types of variables: dog characteristics, county-level socioeconomic characteristics, and the type of state-level cannabis legislation. There were significantly higher odds of a call being related to cannabis in states with lower penalties for cannabis use and possession. The odds of these calls were higher in counties with higher income variability, higher percentage of urban population, and among smaller, male, and intact dogs. These calls increased throughout the study period (2009–2014). Reporting of cannabis poisonings were more likely to come from veterinarians than dog owners. Reported dog poisonings due to cannabis appear to be influenced by dog-level and community-level factors. This study may increase awareness to the public, public health, and veterinary communities of the effects of recreational drug use on dog populations. This study highlights the need to educate dog owners about safeguarding cannabis products from vulnerable populations.

A fuzzy set qualitative comparative analysis of 131 countries: which configuration of the structural conditions can explain health better?

Background

According to the recommendations of the World Health Organization Commission On Social Determinants of Health (CSDH) for intersectoral action on health, the well-being of and equity in health within a population are achieved via a complex fusion of policies and actions. In this study, following the CSDH’s approach and considering set-theoretic relations, we aimed to unravel this complexity and answer the kinds of questions that are outside the scope of conventional variable-oriented approach.

Methods

A fuzzy-set qualitative comparative analysis of 131 countries was conducted to examine the configurational effects of five macro-level structural conditions on life expectancy at birth. The potential causal conditions were level of country wealth, income inequality, quality of governance, education, and health system. The data collected from different international data sources were recorded during 2004–2015.

Results

The intermediate solution of the truth table analysis indicated a configuration of conditions including high level of governance, education, wealth, and affluent health system to be consistently sufficient for high life expectancy. On the other hand, four configurations, each containing two or three conditions, were consistent with being usually sufficient to cause low life expectancy.

Conclusions

We were able to configurationally explore the cases and specify the combinations of potentially causal conditions which were usually sufficient to explain high or low life expectancy in different countries. As a result, particular cases were identified for further research. In addition, research may provide support for the CSDH’s recommendations emphasizing the importance of intersectoral action for health.

Electronic supplementary material

The online version of this article (10.1186/s12939-018-0724-1) contains supplementary material, which is available to authorized users.