The assessment and identification of spatial distribution patterns associated with uncommonly high or low relative risks of mortality and morbidity are crucial for informing effective public health policies. However, conventional methodologies, although straightforward and efficient, often overlook the inherent spatial interdependence among geographical units [36]. Acknowledging the significance of addressing this relationship, we examined the spatial patterns of T2DM mortality across municipalities in Mexico and explored the main contextual factors linked to this cause of death in 2020.

Overall, the Standardized Mortality Ratio (SMR) results (Fig. 2) revealed notable geographic and age-specific patterns. Central Mexico and Yucatán Peninsula exhibited the highest excess mortality rates. For the population under 50 years of age, municipalities in Oaxaca had the highest T2DM mortality rates, while those 50 years old and older experienced the highest rates in Tlaxcala and Puebla. Socioeconomic factors, such as low levels of educational attainment, lack of health services, dietary deficiency, and marginalization, were positively associated with increased T2DM mortality risk. In contrast, GDP per capita showed a negative association (Tables 1 and 2). High-risk areas for T2DM mortality were prominent along the south of the Pacific Coast, The Bajío, Central Mexico, and southern Yucatán for the younger population, and along a central strip extending to the Yucatán Peninsula for the older population. Significant uncertainties in mortality risk were identified, with Central Mexico, Oaxaca, Chiapas, and Tabasco showing high probabilities of excess risk for those under 50 years of age and extended risk areas along the Gulf of Mexico for those 50 years old and older (Figs. 3 and 4).

One of the main findings was that the high-risk areas for T2DM mortality were in municipalities in the states of Chiapas, Tabasco, Oaxaca, Puebla, Guerrero, Tlaxcala, and Veracruz. According to CONAPO [33], these states are characterized by high levels of marginalization. Furthermore, most of these states are characterized by low levels of overall educational attainment, high levels of food insecurity, and low levels of access to health services [38]. We also observed a relatively similar distribution of T2DM mortality risk among individuals under 50 years old and those 50 years old and older across municipalities in Mexico, although with a more homogeneous spatial pattern for the first age-group. This suggests that these states may harbor environments conducive to obesity and T2DM development, characterized by various factors that promote unhealthy lifestyles and elevated disease risk. These include high levels of marginalization, substandard diet quality, and limited access to healthcare services. Such conditions contribute to higher rates of obesity, a key risk factor for T2DM, leading to more severe disease progression and higher mortality rates owing to complications associated with poorly controlled diabetes.

We found that low levels of educational attainment are associated with higher risks of T2DM mortality. This finding aligns with existing research demonstrating that higher levels of education are associated with a reduced risk of developing T2DM and experiencing its complications [12, 14]. Lower levels of education may limit health literacy, which can lead to a poorer understanding of preventive measures, management strategies, and healthcare utilization related to T2DM [14]. This lower awareness may result in a delayed diagnosis, inadequate self-management, and higher mortality rates. Educational attainment also influences lifestyle behaviors that affect diabetes risk and mortality, such as diet quality, physical activity levels, and adherence to medical recommendations. Therefore, it is crucial to provide more educational resources to populations in high-risk regions to improve T2DM control [39].

We also found that a higher percentage of the population with dietary deficiencies had increased T2DM mortality. This finding aligns with other studies demonstrating that food availability [10] and food insecurity [25] are also associated with diabetes. Food insecurity often forces individuals to depend on low-cost, calorie-dense, nutrient-poor foods that are typically high in sugars, refined carbohydrates, and unhealthy fats [25]. These diets contribute to obesity and insulin resistance, which are primary risk factors for the development of T2DM. Poor access to healthy foods makes it difficult to maintain a healthy diet and has an adverse impact on diabetes care [12], which helps manage blood sugar levels. This can lead to poor glycemic control, increased complications, and higher mortality rates. Food availability, or lack thereof, is a significant source of chronic stress, which can contribute to the development of insulin resistance and T2DM. Chronic stress can lead to unhealthy eating behaviors, further increasing the risk of T2DM [40]. Moreover, heightened food insecurity impedes effective self-management diabetes. Stress associated with food insecurity may be related to a greater burden of diabetes [12].

An increase in municipal GDP per capita is associated with a decrease in the risk of T2DM mortality. As stated previously, GDP per capita is one of the most widely used socioeconomic predictors of mortality and health. This finding aligns with other studies that show that gross national per capita income is inversely linked to a rapidly growing trend of type 2 diabetes burden [5], that is, low- and middle-GDP areas have higher prevalence rates of T2DM [41, 42]. In areas with lower GDP, poor health awareness among diabetes patients often leads to significant delays in diagnosis and treatment, resulting in a severe burden of diabetes-related disability and complications [5]. People in these areas tend to have restricted access to high-quality nutritious foods, and instead consume high-calorie foods (often western-style), with low intake of fruits and vegetables, and high intake of sugar-sweetened beverages [43]. This can lead to obesity, accumulation of abdominal fat, and insulin resistance, which are strong risk factors for T2DM. In contrast, a higher GDP per capita usually correlates with better access to nutritious foods and positively impacts various health determinants crucial for the prevention and management of type 2 diabetes [42]. This leads to lower prevalence and better health outcomes in individuals with T2DM.

Finally, the results indicate that marginalization increases the risk of T2DM mortality. These outcomes align with those of other studies conducted in Mexico, which found that socioeconomic inequalities and higher rates of poverty are associated with a higher T2DM prevalence [44], and that the inequality gap in DM mortality between states has recently widened [45]. Marginalized populations often have reduced access to healthcare services, leading to delayed diagnosis and treatment of T2DM [46], and poorer compliance with diabetes treatment. This delay can result in more severe disease progression and higher mortality rates [47]. Economic constraints and limited access to healthy foods and recreational facilities can contribute to unhealthy diets and sedentary lifestyles, which are significant risk factors for T2DM [46]. Marginalized populations often face higher levels of stress owing to financial instability, unsafe living conditions, and social exclusion. Chronic stress can exacerbate the development of T2D [48], whereas financial barriers limit the ability to afford medications and regular medical check-ups, resulting in poor glycemic control and higher complication rates.

The findings of this study should be interpreted with caution in light of these limitations. The first limitation concerns data quality and availability. We used municipal-level data that may suffer from underreporting or misreporting in death certificates, leading to underestimation of T2DM mortality rates. Advanced and chronic type 2 diabetes mellitus leads to complications such as renal and coronary diseases, which are often the direct causes of death. Consequently, these conditions may ultimately be recorded as the primary cause of death [13]. To minimize underreporting, it is essential to emphasize the importance of physicians accurately completing death certificates [49]. Second, working with smaller populations can lead to a higher variability in mortality rates, making it difficult to detect significant trends or differences. Third, the associations analyzed in this study are based on aggregated data. We were unable to infer all identified associations at the individual or local level, as we used municipal-level variables. Thus, while our findings align with other spatial-epidemiological studies on T2DM, it is important that future research confirms whether the associations observed at the ecological level also hold true at the individual level [24]. Fourth, the analyses were conducted for 2020, an exceptional year for overall mortality due to the impact of the COVID-19 pandemic. As a result, it is important to interpret our findings within this context. We also recommend that future studies revisit this analysis in the coming years.