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Escenario futuro de la diabetes mellitus tipo 2 estimado con un modelo de simulación dinámico predictivo

OBJECTIVE. Develop a predictive dynamic model to estimate future scenarios for the incidence rate of type 2 diabetes mellitus (T2DM). METHODS. A retrospective ecological study was conducted in 2013-2015 in the city of San Luis Potosí, Mexico. Secondary official data from the 58 municipalities making...

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Autores principales: Gaytán-Hernández, Darío, Gutiérrez-Enríquez, Sandra Olimpia, Díaz-Oviedo, Aracely, González-Acevedo, Claudia Elena, Miranda-Herrera, Magdalena, Hernández-Ibarra, Luis Eduardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Organización Panamericana de la Salud 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6645193/
https://www.ncbi.nlm.nih.gov/pubmed/29466528
http://dx.doi.org/10.26633/RPSP.2017.93
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author Gaytán-Hernández, Darío
Gutiérrez-Enríquez, Sandra Olimpia
Díaz-Oviedo, Aracely
González-Acevedo, Claudia Elena
Miranda-Herrera, Magdalena
Hernández-Ibarra, Luis Eduardo
author_facet Gaytán-Hernández, Darío
Gutiérrez-Enríquez, Sandra Olimpia
Díaz-Oviedo, Aracely
González-Acevedo, Claudia Elena
Miranda-Herrera, Magdalena
Hernández-Ibarra, Luis Eduardo
author_sort Gaytán-Hernández, Darío
collection PubMed
description OBJECTIVE. Develop a predictive dynamic model to estimate future scenarios for the incidence rate of type 2 diabetes mellitus (T2DM). METHODS. A retrospective ecological study was conducted in 2013-2015 in the city of San Luis Potosí, Mexico. Secondary official data from the 58 municipalities making up the state of San Luis Potosí were analyzed. Linear correlation, multiple linear regression, and structural equations were carried out, and four predictive dynamic submodels were developed: T2DM, urban population, inhabited private dwellings that have television, and population aged 45-49 years. A holistic model was also developed. RESULTS. The structural model explains 27.2% of total variance in type 2 diabetes mellitus. Percentage of inhabited dwellings that have television weighs 4.46 non-standard units on diabetes; that of urban population, 2.84; and that of population aged 45-49 years, 156.69. Estimated scenarios for T2DM per 100 000 population for the years 2015, 2020, 2025, and 2030 were 1,052.4, 1,413.7, 1,850.1, and 2,351.1 respectively. CONCLUSION. The T2DM scenario shows exponential growth from 2000 to 2030. Risk factors according to the weight they represent in occurrence of the disease were: population aged 45-49 years, inhabited private dwellings that have television, and urban population.
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spelling pubmed-66451932019-08-05 Escenario futuro de la diabetes mellitus tipo 2 estimado con un modelo de simulación dinámico predictivo Gaytán-Hernández, Darío Gutiérrez-Enríquez, Sandra Olimpia Díaz-Oviedo, Aracely González-Acevedo, Claudia Elena Miranda-Herrera, Magdalena Hernández-Ibarra, Luis Eduardo Rev Panam Salud Publica Investigación Original OBJECTIVE. Develop a predictive dynamic model to estimate future scenarios for the incidence rate of type 2 diabetes mellitus (T2DM). METHODS. A retrospective ecological study was conducted in 2013-2015 in the city of San Luis Potosí, Mexico. Secondary official data from the 58 municipalities making up the state of San Luis Potosí were analyzed. Linear correlation, multiple linear regression, and structural equations were carried out, and four predictive dynamic submodels were developed: T2DM, urban population, inhabited private dwellings that have television, and population aged 45-49 years. A holistic model was also developed. RESULTS. The structural model explains 27.2% of total variance in type 2 diabetes mellitus. Percentage of inhabited dwellings that have television weighs 4.46 non-standard units on diabetes; that of urban population, 2.84; and that of population aged 45-49 years, 156.69. Estimated scenarios for T2DM per 100 000 population for the years 2015, 2020, 2025, and 2030 were 1,052.4, 1,413.7, 1,850.1, and 2,351.1 respectively. CONCLUSION. The T2DM scenario shows exponential growth from 2000 to 2030. Risk factors according to the weight they represent in occurrence of the disease were: population aged 45-49 years, inhabited private dwellings that have television, and urban population. Organización Panamericana de la Salud 2017-09-29 /pmc/articles/PMC6645193/ /pubmed/29466528 http://dx.doi.org/10.26633/RPSP.2017.93 Text en https://creativecommons.org/licenses/by/4.0/  
spellingShingle Investigación Original
Gaytán-Hernández, Darío
Gutiérrez-Enríquez, Sandra Olimpia
Díaz-Oviedo, Aracely
González-Acevedo, Claudia Elena
Miranda-Herrera, Magdalena
Hernández-Ibarra, Luis Eduardo
Escenario futuro de la diabetes mellitus tipo 2 estimado con un modelo de simulación dinámico predictivo
title Escenario futuro de la diabetes mellitus tipo 2 estimado con un modelo de simulación dinámico predictivo
title_full Escenario futuro de la diabetes mellitus tipo 2 estimado con un modelo de simulación dinámico predictivo
title_fullStr Escenario futuro de la diabetes mellitus tipo 2 estimado con un modelo de simulación dinámico predictivo
title_full_unstemmed Escenario futuro de la diabetes mellitus tipo 2 estimado con un modelo de simulación dinámico predictivo
title_short Escenario futuro de la diabetes mellitus tipo 2 estimado con un modelo de simulación dinámico predictivo
title_sort escenario futuro de la diabetes mellitus tipo 2 estimado con un modelo de simulación dinámico predictivo
topic Investigación Original
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6645193/
https://www.ncbi.nlm.nih.gov/pubmed/29466528
http://dx.doi.org/10.26633/RPSP.2017.93
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