Multidimensional analysis of health in Mexico: implementation of fuzzy sets

Abstract

Abstract Background The national health and nutrition survey allows to know the state of health of the Mexican population, it provides data for the analysis of different factors and / or indicators of health, diseases and nutritional conditions, such as chronic degenerative diseases and depressive symptoms, which, in turn, if both occur simultaneously, they will have a negative impact on health. This article studies the four factors involved in the overall health of the population in Mexico: excess weight, diabetes, high blood pressure, and depressive symptoms, which are used to conduct a multidimensional characterization and analysis. Methods Two methodological resources are applied, a descriptive statistical characterization and the construction of a multidimensional health index with the use of fuzzy sets, through the National Health and Nutrition Survey (ENSANUT 2018–19 - for its acronym in Spanish) in Mexico. Results The results reveal a growing percentage of individuals who experience detriments to their health, that is, the factors being studied have had a negative impact and tend to follow international projections. The construction of a multidimensional index enables the interaction between the factors being studied, thus allowing for an adequate modeling for the identification of health in Mexico. Conclusion This study aims to elucidate the current state of health throughout the population in Mexico by using the most current data provided by the autonomous public body of statistics and geography to build a multidimensional panorama using four elementary public health indicators (diabetes, obesity, high blood pressure, and depressive symptoms).