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To estimate changes in taxed and untaxed beverages by volume of beverage purchased after a sugar-sweetened beverage (SSB) tax was introduced in 2014 in Mexico.
We used household purchase data from January 2012 to December 2015. We first classified the sample into four groups based on pre-tax purchases of beverages: (i) higher purchases of taxed beverages and lower purchases of untaxed beverages (HTLU-unhealthier); (ii) higher purchases of both types of beverages (HTHU); (iii) lower purchases of taxed and untaxed beverages (LTLU); and (iv) lower purchases of taxed beverages and higher purchases of untaxed beverages (LTHU-healthier). Next, we estimated differences in purchases after the tax was implemented for each group compared with a counterfactual based on pre-tax trends using a fixed-effects model.
Areas with more than 50 000 residents in Mexico.
Households (n 6089).
The HTLU-unhealthier and HTHU groups had the largest absolute and relative reductions in taxed beverages and increased their purchases of untaxed beverages. Households with lower purchases of untaxed beverages (HTLU-unhealthier and LTLU) had the largest absolute and relative increases in untaxed beverages. We also found that among households with higher purchases of taxed beverages, the group with lowest socio-economic status had the greatest reduction in purchases of taxed beverages.
Evidence associating the SSB tax with larger reductions among high purchasers of taxed beverages prior to the tax is relevant, as higher SSB purchasers have a greater risk of obesity, diabetes and other cardiometabolic outcomes.
To study the association between density of stores (food and beverage stores, stores selling only fruits and vegetables, and supermarkets) and the BMI of adults aged ≥20 years in Mexico.
A cross-sectional study was performed. Individual data came from the 2012 National Health and Nutrition Survey, while information on stores was taken from the National Institute of Geography and Statistics’ National Statistics Directory of Economic Units. A weighted least-squares model was estimated to test the association between density of stores and BMI of adults adjusting for sex, age, education, presence of hypertension, diabetes or both, household assets index and marginality index at the municipality level.
An additional 1 sd in the density of fruit and vegetable stores was associated with a reduction of 0·24 (95 % CI −0·37, −0·12) kg/m2 in BMI when the densities of the other stores were at their mean values. For food and beverage store density, a difference of 1 sd was associated with an increase of 0·50 (95 % CI 0·33, 0·67) kg/m2 in BMI, while for supermarkets the corresponding association was a reduction of 0·48 (95 % CI −1·52, 0·56) kg/m2 in BMI.
In places with a higher density of stores that offer unhealthy foods, the BMI of adults tends to be higher.
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