Análisis de vulnerabilidad en el Perú a partir del desarrollo de modelos de regresión logísticos mediante la utilización del software Stata
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2024-09-03
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Pontificia Universidad Católica del Perú
Abstract
La presente investigación se orientó a determinar los factores que influyen en la vulnerabilidad
ante desastres naturales en el Perú, periodo 2021. En ese contexto, para responder a tal objetivo la
metodología contemplada fue de carácter cuantitativo, de nivel correlacional, de análisis documental
con información extraída del ENAHO – 2021 misma que fue procesada en el programa estadístico Stata
16 mediante la metodología del modelo logit, además, es de precisar que, la muestra total estuvo
conformada por 109,867 individuos. Los resultados de la regresión logística (Logit) indican que los
factores asociados con las características de la vivienda y del hogar, las características de los miembros
del hogar, la educación y el empleo e ingreso influyen significativamente en la probabilidad de ser
vulnerable o no a los desastres naturales, no obstante, los factores asociados con la salud no influyen
significativamente en la vulnerabilidad. Finalmente, se concluye que los factores correlacionados
significativamente con la vulnerabilidad ante desastres naturales son: Tipo de vivienda, material
predominante de las paredes, material predominante del piso, material predominante del techo,
construcción de vivienda con asistencia técnica de un ingeniero civil o arquitecto, edad, zona de
residencia, nivel educativo, disponibilidad de internet en la vivienda e ingreso bruto.
The present investigation was oriented to determine the factors that influence vulnerability to natural disasters in Peru, period 2021. In this context, to respond to this objective, the methodology contemplated was of a quantitative nature, of a correlational level, of documentary analysis with information extracted from ENAHO - 2021, which was processed in the Stata 16 statistical program using the logit model methodology, in addition, it must be specified that the total sample consisted of 109,867 individuals. The results of the logistic regression (Logit) indicate that the factors associated with the characteristics of the dwelling and the household, the characteristics of the household members, education and employment, and income significantly influence the probability of being vulnerable or not to natural disasters, however, factors associated with health do not significantly influence vulnerability. Finally, it is concluded that the factors significantly correlated with vulnerability to natural disasters are: Type of dwelling, predominant wall material, predominant floor material, predominant roof material, housing construction with technical assistance from a civil engineer or architect, age, area of residence, educational level, availability of internet in the home and gross income.
The present investigation was oriented to determine the factors that influence vulnerability to natural disasters in Peru, period 2021. In this context, to respond to this objective, the methodology contemplated was of a quantitative nature, of a correlational level, of documentary analysis with information extracted from ENAHO - 2021, which was processed in the Stata 16 statistical program using the logit model methodology, in addition, it must be specified that the total sample consisted of 109,867 individuals. The results of the logistic regression (Logit) indicate that the factors associated with the characteristics of the dwelling and the household, the characteristics of the household members, education and employment, and income significantly influence the probability of being vulnerable or not to natural disasters, however, factors associated with health do not significantly influence vulnerability. Finally, it is concluded that the factors significantly correlated with vulnerability to natural disasters are: Type of dwelling, predominant wall material, predominant floor material, predominant roof material, housing construction with technical assistance from a civil engineer or architect, age, area of residence, educational level, availability of internet in the home and gross income.
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Desastres naturales--Perú, Viviendas--Perú, Análisis de regresión logística
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