Evolution of the spatial distribution of alcohol consumption following alcohol control policies: a 25-year cross-sectional study in a Swiss urban population

BackgroundAlcohol consumption is a major risk factor for multiple chronic diseases and overall mortality. Consequently, multiple alcohol control policies have been implemented in Switzerland. Recent evidence shows that population-wide policies may have impacted some population subgroups and places differently. While the determinants of alcohol consumption are complex, understanding where interventions are needed is necessary for implementing targeted policies. Spatial statistics and modeling allow incorporating this spatial context into the analysis of alcohol consumption and its determinants. MethodsWe used the 1993-2018 Bus Sante annual population-based surveys including 18,515 participants aged 35-74 years residing in the canton of Geneva, Switzerland. We assessed the existence of spatial clustering of alcohol consumption the local Morans I spatial statistics. To evaluate how the spatial distribution of alcohol consumption may have changed over time, we subdivided the study sample into three subsamples according to periods of alcohol-control policies implementation: before (Period 1 (P1): 1993.01.01-1999.06.30), during (Period 2 (P2): 1999.07.01-2009.10.31), and after (Period 3 (P3): 2009.11.01-2018.12.31). We also investigated socio-demographic and built environment determinants of alcohol consumption across periods and provided a comparison of the performance and results of global ordinary least squares (OLS), local geographically weighted regression (GWR), and multiscale GWR (MGWR) models. ResultsWe found spatial clustering of alcohol consumption in the three analyzed periods. Alcohol consumption in local clusters markedly decreased across periods despite increasing alcohol outlet accessibility. The spatial distribution of higher alcohol consumption clusters (i.e., hot spots) and of lower alcohol consumption clusters (i.e., cold spots) changed slightly across periods. Alcohol consumption in hot spots remained above recommendations in P3 (26.0 g/day, SD {+/-} 17.2 g/day), particularly for women. Cold spots increased in size (4.6% of the participants in P1, 9.3% in P3), particularly in the period following the implementation of policies (P2 to P3) while hot spots remained stable (3.2% of the participants). Alcohol consumption was significantly higher in hot spots than cold spots in all three periods (p < 0.001). The MGWR model outperformed the OLS and GWR models in most cases and revealed that alcohol consumption was influenced by a mix of global and local relationships. Several of these relationships evolved across periods. Interestingly, in models adjusted for individual-level determinants, we found significant positive relationships between bar density and alcohol consumption in P1 and between density of off-premises alcohol outlets and alcohol consumption in P2. However, these two associations were not significant in P3 potentially due to alcohol control policies. ConclusionOur results reveal that certain areas and subgroups in need of public health intervention and show that a mix of global and local processes best model alcohol consumption. In addition, this study highlights the potential of geospatial approaches to provide a refined understanding of the determinants of alcohol consumption, and the spatial scales at which they vary.