Mexico faces a significant obesity and overweight problem, affecting 75% of its population. This epidemic is linked to a dietary and food retail transition marked by increased availability of high-calorie, dense foods and beverages. The North American Free Trade Agreement (NAFTA), implemented in 1994, significantly influenced this transition, leading to the introduction of global fast-food chains and increased imports of low-cost, ultra-processed foods. This influx of less healthy food options, combined with factors like decreased physical activity and the industrialization of food production, has contributed to the rise in obesity rates. While individual factors like diet and physical activity play a role, a broader understanding of the environmental context, particularly the retail food environment, is crucial. Existing research on the retail food environment's impact on obesity is largely concentrated in high-income countries, with limited studies in middle-income countries like Mexico. This study aimed to analyze the association between individual food outlet densities and adult BMI in urban Mexico, identifying obesogenic aspects of the retail food environment to inform policy recommendations. The research specifically addressed the question of whether the retail food environment is a risk factor for higher BMI in a middle-income country setting.

The literature review highlights the significant role of the food environment in shaping dietary choices and overall health outcomes. The community nutrition environment, or retail food environment, encompassing the type, location, and accessibility of food outlets, is a key determinant of health, especially concerning obesity. While much research exists on high-income countries, studies in low- and middle-income countries (LMICs) are less common, especially those directly assessing the relationship with obesity. The introduction of NAFTA into Mexico is presented as a critical event that shaped the retail food environment, facilitating the proliferation of global fast-food chains and affordable ultra-processed foods. This transition coincided with a steep increase in obesity prevalence in Mexico, indicating a potential link between environmental changes and health outcomes. The complexity of obesity is acknowledged; it's not solely attributable to individual behaviors, necessitating broader environmental and policy interventions.

This study used secondary analysis of cross-sectional data, combining spatial distribution of overweight and obesity in Mexico with an analysis of the retail food environment and its association with BMI. Sociodemographic and anthropometric data came from the 2012 Mexican National Survey of Health and Nutrition (ENSANUT), while retail data originated from the 2014 economic census by the National Institute of Statistics, Geography, and Informatics (INEGI). The study focused on urban areas (CTAs) with populations of 2500 or more. The sample included 22,219 adult participants after exclusions for pregnancy, age under 18, invalid weight/height data, and BMI values more than three standard deviations from the mean. Food outlets were categorized into convenience stores, restaurants, fast-food outlets, supermarkets, and fruit and vegetable stores based on INEGI data and website information. Geocoding of participants and food outlets was performed using ArcGIS. Density was calculated as the number of food outlets per CTA divided by the CTA's area. Statistical analysis involved multilevel linear regression models, accounting for state or CTA as random effects to address individual nesting within larger geographic units. Models incorporated BMI as the dependent variable and various sociodemographic, economic, and health variables as potential confounders. Sensitivity analyses utilized waist circumference as the outcome, and interaction tests explored the relationship between socioeconomic position (SEP) and food outlet density. The study accounted for the survey design's characteristics in all analyses.

Convenience stores exhibited the highest density among all food outlets in Mexico, particularly in metropolitan areas. Multilevel linear regression models revealed a statistically significant association between higher convenience store density and higher mean BMI. Specifically, a one-unit increase in convenience store density was associated with a 0.003 kg/m² increase in BMI (p=0.011). This translates to an estimated 0.34 kg weight increase for a 1.60 m tall adult for every 10% increase in convenience store density. In metropolitan areas, this association was even stronger, with a 10% increase in convenience store density potentially resulting in a 1 kg weight gain for a 1.60 m adult. These associations persisted after adjusting for age, gender, SEP, and other potential confounders, and remained significant even after accounting for selection bias. In contrast, there was no statistically significant association found between the density of other food outlets (supermarkets, fruit and vegetable stores, and restaurants) and BMI. The study also found that many urban CTAs lacked access to supermarkets and fruit and vegetable stores. Model A, which included age, gender, and household SEP, demonstrated the highest intraclass correlation coefficient (0.11), suggesting a reliable measurement scale.

The findings support the hypothesis that the retail food environment, specifically the high density of convenience stores, is associated with higher BMI in Mexican adults. This association underscores the obesogenic potential of an environment characterized by readily available, inexpensive, calorie-dense foods while lacking sufficient access to healthier options. The study's national scope and use of robust statistical models provide strong evidence for this association, even after controlling for several confounding factors, including socio-economic status. The concentration of convenience stores in metropolitan areas suggests a need for targeted interventions in these higher-density areas. The limitations of using cross-sectional data, which prevents definitive causal inferences, are acknowledged. The study's implications for public health policy in Mexico include the need for strategies to regulate the density and placement of food outlets and to promote healthier food access in underserved areas.

This study provides the first national-level evidence in Mexico linking convenience store density to higher BMI in adults. The high availability of unhealthy food choices and limited access to healthy alternatives in many areas contribute to this issue. Future research should focus on longitudinal studies to establish causality and explore the effectiveness of policy interventions aiming to improve the retail food environment and promote healthier dietary choices in Mexico. Targeted policies and interventions are needed, particularly in metropolitan areas where the obesogenic effects of the current food environment are most pronounced. These interventions might include regulations on the density and location of unhealthy food outlets and measures to increase access to affordable and nutritious food sources.

This study employed cross-sectional data, thus limiting the ability to establish definitive causal relationships between convenience store density and BMI. The reliance on census tract-level data for food outlet density and individual-level data for BMI could introduce ecological fallacy. Further, the assessment of food outlets was based on available secondary data and did not involve direct store assessments which may affect the accuracy of the food categorization. The sample excluded individuals from rural areas, potentially limiting the generalizability of the findings to the entire Mexican population.