Objective: To evaluate the morbidity due to diabetes mellitus type 2 within the State of San Luis Potosí, México, through a strong methodology, through which the multivariate relations were identified of the...Objective: To evaluate the morbidity due to diabetes mellitus type 2 within the State of San Luis Potosí, México, through a strong methodology, through which the multivariate relations were identified of the main social and environmental determiners in the disease, thus managing to quantify their respective levels of responsibility. Material and Methods: This evaluation began as a hypothesis of a multicasual theoretical model on diabetes mellitus and its main determining factors, which was analyzed through the application of multivariate exploratory statistical methodologies and confirmed as it is the case of the principal components analysis and the structural equation models. Results: Three components were extracted that explain the 96% of the total variance of the indicators;the main risk factors which were identified in the first component were, the use of the car, age, homes with TV use, urban life and feminine population;the indicators from the second and third component have little influence in the impact of the disease. Conclusions: the study shows the usefulness of the model for the analysis and prioritization of the environmental and social determiners of the disease, information that could sustain the design of public guidelines for the prevention and control of the analyzed disease.展开更多
文摘Objective: To evaluate the morbidity due to diabetes mellitus type 2 within the State of San Luis Potosí, México, through a strong methodology, through which the multivariate relations were identified of the main social and environmental determiners in the disease, thus managing to quantify their respective levels of responsibility. Material and Methods: This evaluation began as a hypothesis of a multicasual theoretical model on diabetes mellitus and its main determining factors, which was analyzed through the application of multivariate exploratory statistical methodologies and confirmed as it is the case of the principal components analysis and the structural equation models. Results: Three components were extracted that explain the 96% of the total variance of the indicators;the main risk factors which were identified in the first component were, the use of the car, age, homes with TV use, urban life and feminine population;the indicators from the second and third component have little influence in the impact of the disease. Conclusions: the study shows the usefulness of the model for the analysis and prioritization of the environmental and social determiners of the disease, information that could sustain the design of public guidelines for the prevention and control of the analyzed disease.
