Socioeconomic and demographic factors associated with anaemia among women of reproductive age in Zimbabwe: a supervised machine learning approach

Socioeconomic and demographic factors associated with anaemia among women of reproductive age in Zimbabwe: a supervised machine learning approach

Abstract Anaemia affects approximately one-third of women of reproductive age globally, with the highest burden observed in resource-limited countries. Therefore, this study aimed to determine the socioeconomic and demographic factors associated with anaemia and predict anaemia among women in Zimbab...

Full description

Saved in:
Bibliographic Details
Main Authors: Garikayi Chemhaka, Elliot Mbunge, Tafadzwa Dzinamarira, Godfrey Musuka, John Batani, Benhildah Muchemwa, Stephen Fashoto, Munyaradzi Mapingure, Rutendo Birri Makota, Ester Petrus
Format: Article
Language:English
Published: Springer 2025-04-01
Series:Discover Public Health
Subjects:
Anaemia
Machine learning
Survey
Socioeconomic
Demographic
Logistic regression
Online Access:https://doi.org/10.1186/s12982-025-00524-7
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1186/s12982-025-00524-7

Similar Items