drsunday-ade/CS-risk-prediction-modelling

Nationally representative NDHS 2024 study developing and internally validating a survey-weighted risk model for caesarean delivery in Nigeria, quantifying geographic inequality and operative-birth burden using weighted ridge logistic regression and zonal burden stratification. # CS-risk-prediction-modelling Nationally representative NDHS 2024 study developing and internally validating a survey-weighted risk model for caesarean delivery in Nigeria, quantifying geographic inequality and operative-birth burden using weighted ridge logistic regression and zonal burden stratification. # Geographic inequality in caesarean delivery in Nigeria This repository contains the analytic code and reproducibility materials for a nationally representative NDHS 2024 study developing and internally validating a survey-weighted risk model for caesarean delivery in Nigeria, with emphasis on geographic inequality and operative-birth burden. ## Study status **Manuscript under review:** *International Journal of Gynecology & Obstetrics (IJGO)* ## Data source Nigeria Demographic and Health Survey (NDHS) 2024 Birth Recode dataset. Access to DHS data requires registration and approval through the DHS Program. ## Reproducibility This repository contains code for data preparation, variable engineering, survey-weighted descriptive analysis, weighted ridge logistic regression, internal validation, calibration assessment, and geographic burden stratification. ## Suggested citation Adetunji SA, Adewuyi RO. Geographic inequality in caesarean delivery in Nigeria: development and internal validation of a nationally representative NDHS 2024 risk model. Under review at *International Journal of Gynecology & Obstetrics*. ## Links - Code and reproducibility: github.com - Data access: dhsprogram.com - ORCID: orcid.org