Socioeconomic, demographic and geographic determinants of food consumption in Mexico.

What people eat affects public health and human wellbeing, agricultural production, and environmental sustainability. This paper explores the heterogeneity of food consumption patterns in an ecologically and culturally diverse country. Using a latent class approach (which creates clusters of individuals with homogeneous characteristics), we analyse a food questionnaire (from the National Health and Nutrition Survey) applied across Mexico. We identify four clusters of food consumption (staple, prudent, high meat and low fruit) and find that belonging to these clusters is determined by socioeconomic, demographic (age, sex) and geographic (region, urban/rural) characteristics. Maize and pulses tend to constitute a larger proportion of the diet of poor, rural populations living in the south, while urban populations eat more varied foods, including ingredients whose production systems tend to exert more pressure on natural resources (for instance, meat). Despite the importance given in the literature to the Mexican gastronomy and its diverse traditional regional diets, we find that only 6% of the population adopts a food consumption pattern resembling the traditional Mexican diet. Instead, most of the Mexican population has a food consumption pattern resembling a western diet, which is problematic in terms of public health and environmental sustainability.

An Entropy-Based Approach to Measuring Diet Adherence.

The aim of this study is to put forward an approach designed to calculate and sum up discrepancies between the actual food acquisition or intake and any standard or norm. Based on secondary analysis of cross-sectional data from the Mexican National Survey of Household Income and Expenditure, our proposed method to produce classes of entropy-based Diet Adherence Indices generates a Food Basket Adherence Index (FBAI) for Mexico City (2129 households). Findings suggest that it is possible to measure and decompose diet adherence using a cross entropy measure. Using food expenditure data and a normative food basket for Mexico City results, we show households' deviations from the suggested norm for different food groups. The average FBAI was 0.44, far above the minimum score of 0 which would indicate full adherence to the normative food basket. Our measure has a distribution wide enough to detect meaningful changes and distinguish between groups with known differences, providing important new insights on the linkages between home food environments and income distribution, and food insecurity and household distribution.

Association between density of convenience and small grocery stores with diet quality in adults living in Mexico City: A cross sectional study.

There is evidence of the association between different retail stores and food consumption, yet research is still limited in low- and medium-income countries, where the context of the food retail environment is different from that observed in high-income countries. Specifically, less is known about how convenience and small grocery stores, which offer products with immediate access, are associated with the diet as a whole. The present study assessed the association between density of convenience and small grocery stores and diet quality in adults from the Mexico City Representative Diabetes Survey 2015. A final sample size of 1,023 adults aged 20-69 years was analyzed. The density of stores was measured using Euclidean buffers within 500 meters of each participant's home. The Mexican Alternate Healthy Eating Index (MxAHEI) was used to assess diet quality. Multivariable Poisson models were used to test the association of convenience and small grocery stores densities with the MxAHEI. Although our results were not statistically significant, we observed a lower diet quality score among adults from Mexico City living in areas with a higher density of small grocery and convenience stores. More research is needed on the influence of environmental food retail on food consumption.

Health and Institutional Risk Factors of COVID-19 Mortality in Mexico, 2020.

INTRODUCTION: Several studies in developed and developing countries have analyzed the health risk factors associated with COVID-19 mortality. Comorbid diseases are a key explanatory factor behind COVID-19 mortality, but current studies treat comorbidities in isolation, at average-population values, and rarely assess how death risk varies for different health profiles across institutions. Estimating death risk variations for different interactions between comorbid diseases and across healthcare institutions is crucial to gaining a significant depth of understanding in relation to mortality during the pandemic. METHODS: This study relies on data from approximately half a million people in Mexico (of all recorded cases through August 15, 2020) and on Bayesian estimation to provide a more robust estimate of the combined effect of several comorbidities and institutional inequalities on COVID-19 mortality. RESULTS: The findings of the study illustrate the additive effects of several comorbid diseases, with the presence of obesity, diabetes, hypertension, and chronic kidney disease increasing the mortality risk of COVID-19. There are also variations in the risk of death across the heterogeneous Mexican health system. CONCLUSIONS: This study shows that COVID-19 mortality risk sharply increases in patients with 2 or more comorbid diseases (obesity, diabetes, hypertension, and cardiovascular diseases) in Mexico. However, death risk varied significantly across institutions for patients with the same comorbidity profile.

Precision non-implantable neuromodulation therapies: a perspective for the depressed brain

Current first-line treatments for major depressive disorder (MDD) include pharmacotherapy and cognitive-behavioral therapy. However, one-third of depressed patients do not achieve remission after multiple medication trials, and psychotherapy can be costly and time-consuming. Although non-implantable neuromodulation (NIN) techniques such as transcranial magnetic stimulation, transcranial direct current stimulation, electroconvulsive therapy, and magnetic seizure therapy are gaining momentum for treating MDD, the efficacy of non-convulsive techniques is still modest, whereas use of convulsive modalities is limited by their cognitive side effects. In this context, we propose that NIN techniques could benefit from a precision-oriented approach. In this review, we discuss the challenges and opportunities in implementing such a framework, focusing on enhancing NIN effects via a combination of individualized cognitive interventions, using closed-loop approaches, identifying multimodal biomarkers, using computer electric field modeling to guide targeting and quantify dosage, and using machine learning algorithms to integrate data collected at multiple biological levels and identify clinical responders. Though promising, this framework is currently limited, as previous studies have employed small samples and did not sufficiently explore pathophysiological mechanisms associated with NIN response and side effects. Moreover, cost-effectiveness analyses have not been performed. Nevertheless, further advancements in clinical trials of NIN could shift the field toward a more "precision-oriented" practice.

Precision non-implantable neuromodulation therapies: a perspective for the depressed brain.

Current first-line treatments for major depressive disorder (MDD) include pharmacotherapy and cognitive-behavioral therapy. However, one-third of depressed patients do not achieve remission after multiple medication trials, and psychotherapy can be costly and time-consuming. Although non-implantable neuromodulation (NIN) techniques such as transcranial magnetic stimulation, transcranial direct current stimulation, electroconvulsive therapy, and magnetic seizure therapy are gaining momentum for treating MDD, the efficacy of non-convulsive techniques is still modest, whereas use of convulsive modalities is limited by their cognitive side effects. In this context, we propose that NIN techniques could benefit from a precision-oriented approach. In this review, we discuss the challenges and opportunities in implementing such a framework, focusing on enhancing NIN effects via a combination of individualized cognitive interventions, using closed-loop approaches, identifying multimodal biomarkers, using computer electric field modeling to guide targeting and quantify dosage, and using machine learning algorithms to integrate data collected at multiple biological levels and identify clinical responders. Though promising, this framework is currently limited, as previous studies have employed small samples and did not sufficiently explore pathophysiological mechanisms associated with NIN response and side effects. Moreover, cost-effectiveness analyses have not been performed. Nevertheless, further advancements in clinical trials of NIN could shift the field toward a more "precision-oriented" practice.

Exploring perceptions of the Mexican sugar-sweetened beverage tax among adolescents in north-west Mexico: a qualitative study.

OBJECTIVE: To explore awareness and perceptions of the sugar-sweetened beverage (SSB) tax implemented in Mexico in 2014 among a sample of Mexican adolescents, and to investigate how the tax has affected their purchases and intake of SSB. DESIGN: Qualitative. SETTING: Semi-structured interviews were conducted in April-May 2016. The data were analysed using thematic analysis. SUBJECTS: Adolescents residing in north-west Mexico (n 29, 55·2 % females), aged 15-19 years. RESULTS: Four main themes emerged: awareness of taxation; perceptions of how the tax has affected SSB intake; reasons why the tax was not perceived to have affected SSB intake; and preferences for substitution of the taxed SSB. Participants were mostly unaware of the tax and perceived that it would not cause reductions in their intake of SSB; they felt that the price increase was low and insufficient to affect intake. Taste preferences and 'addiction' to SSB were highlighted as the main reasons why participants perceived taxation would not affect intake. If SSB prices were to increase further via a higher tax, participants would consider substituting SSB with other beverages, namely home-made drinks (e.g. 100 % fruit juices), non-caloric, instant-flavoured drinks and water. CONCLUSIONS: These findings provide important insights into the views of this sample of Mexican adolescents regarding the taxation of SSB, by pointing out several possible limitations of the tax policy in Mexico. These results could inform the design of future interventions directed at Mexican youth that would complement and strengthen the current SSB taxation.