Processed ENDES 2007–2025 dataset for childhood stunting prediction in Peru

Analysis dataset used in the article "Machine Learning Model for Predicting the Risk of Childhood Stunting in Peru". It contains one row per child under five years of age with valid anthropometry (n = 304,271) from the 2007–2025 rounds of Peru's Demographic and Family Health Survey (ENDES), with 79...

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Guardado en:
Autores principales: Abel Is-Boset Guevara-Huasco, Zulin Pamela Vallejos-Cotrina, Verónica Lisseth Vergara-Rojas, Ferdinand Pineda, Nemías Saboya
Formato: Conjunto de datos
Lenguaje:inglés
Publicado: 2026
Materias:
child stunting
children under five
anthropometry
height-for-age z-score
Peru
machine learning
child nutrition
Child Nutrition and Water Access
Public Health and Nutrition
Artificial Intelligence in Healthcare
Acceso en línea:Enlace permanente (DOI o Handle)

Registro tomado de OpenAlex, que lo atribuye a la UPeU. Aún no está en el CRIS de la universidad.

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Sumario:Analysis dataset used in the article "Machine Learning Model for Predicting the Risk of Childhood Stunting in Peru". It contains one row per child under five years of age with valid anthropometry (n = 304,271) from the 2007–2025 rounds of Peru's Demographic and Family Health Survey (ENDES), with 79 harmonized variables, the stunting outcome (height-for-age Z-score below −2 SD) and the survey expansion factor. It contains no household or person identifiers and no geographic coordinates; the finest geographic level is the department. Source: Instituto Nacional de Estadística e Informática (INEI), https://proyectos.inei.gob.pe/microdatos/. The README describes the variables, preprocessing and known issues; data_dictionary.csv lists every variable.

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