Assessing the association between tourism and the alcohol urban environment in Barcelona: a cross-sectional study

Ex ante evaluation of the impact of tobacco control policy measures aimed at the point of sale in the Netherlands

INTRODUCTION

The Netherlands aims to implement stricter tobacco control policies targeting the retail environment. This paper is an ex ante policy evaluation of the potential impact of the current tobacco display and advertising ban as well as future tobacco sales bans on tobacco outlet visibility and availability.

METHODS

Between September 2019 and June 2020, all potential tobacco retailers in four Dutch cities (Amsterdam, Eindhoven, Haarlem and Zwolle) were visited and mapped using Global Positioning System. For each retailer selling tobacco, we completed a checklist on the visibility of tobacco products and advertising. Expected reductions in tobacco outlet visibility and availability were calculated per policy measure in absolute numbers (percentage or percentage point decrease) as well as density and proximity.

RESULTS

Out of 870 tobacco outlets, 690 were identified with visible tobacco products/advertising. The display ban in supermarkets and small outlets (respectively) is expected to decrease the number (-15; -42 percentage points), outlet density per 10 000 capita (-0.9; -2.6) and proximity in metres (+27 m; +400 m) of outlets with visible products/advertising. The upcoming bans on vending machines and sales in supermarkets are expected to decrease the number (-12%; -31%), density (-0.7; -1.9) and proximity (+12 m; +68 m) of tobacco outlets. Further changes in the number, density and proximity (respectively) of tobacco outlets may be achieved with future sales bans in petrol stations (-7%; -0.4; +60 m) and particularly with a ban on sales in small outlets (-43%; -2.7; +970 m).

CONCLUSION

A display ban and a sales ban in small outlets will contribute most to reducing tobacco outlet visibility and availability, assuming that no market shift towards other tobacco outlets will take place.

Leading consumption patterns of psychoactive substances in Colombia: A deep neural network-based clustering-oriented embedding approach

The number of health-related incidents caused using illegal and legal psychoactive substances (PAS) has dramatically increased over two decades worldwide. In Colombia, the use of illicit substances has increased up to 10.3%, while the consumption alcohol and tobacco has increased to 84% and 12%, respectively. It is well-known that identifying drug consumption patterns in the general population is essential in reducing overall drug consumption. However, existing approaches do not incorporate Machine Learning and/or Deep Data Mining methods in combination with spatial techniques. To enhance our understanding of mental health issues related to PAS and assist in the development of national policies, here we present a novel Deep Neural Network-based Clustering-oriented Embedding Algorithm that incorporates an autoencoder and spatial techniques. The primary goal of our model is to identify general and spatial patterns of drug consumption and abuse, while also extracting relevant features from the input data and identifying clusters during the learning process. As a test case, we used the largest publicly available database of legal and illegal PAS consumption comprising 49,600 Colombian households. We estimated and geographically represented the prevalence of consumption and/or abuse of both PAS and non-PAS, while achieving statistically significant goodness-of-fit values. Our results indicate that region, sex, housing type, socioeconomic status, age, and variables related to household finances contribute to explaining the patterns of consumption and/or abuse of PAS. Additionally, we identified three distinct patterns of PAS consumption and/or abuse. At the spatial level, these patterns indicate concentrations of drug consumption in specific regions of the country, which are closely related to specific geographic locations and the prevailing social and environmental contexts. These findings can provide valuable insights to facilitate decision-making and develop national policies targeting specific groups given their cultural, geographic, and social conditions.