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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Organización Panamericana de la Salud
2017
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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 |
Sumario: | 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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