Predicting and identifying correlates of inequalities in breast cancer screening uptake using national level data from India.

ABSTRACT:

Background

Despite national screening initiatives, coverage of breast cancer screening is low, and late-stage diagnosis remains a major contributor to mortality among Indian women. Accurate, precise, and actionable prediction of socioeconomic and structural inequities in screening uptake is critical for formulating equitable cancer control policies. This study aimed to apply machine learning to predict determinants of screening uptake, estimate inequalities in uptake and their concentration indices, and identify contributing factors to inequity using concentration index decomposition across economic, educational, and caste gradients.

Methods

Cross-sectional National Family Health Survey (NFHS-5) 2019-2021 data, comprising 68,526 women aged 30-49 years, is used for the study.

SUBMITTER: Tanveer A 

PROVIDER: S-EPMC12820423 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature