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Research Article Open access CC BY 4.0

Separating the Temporal Dynamics and Wealth Inequalities in Early Childbearing: Multilevel Statistical Analysis

Francis Ayiah-Mensah, Cynthia Ama Mensah, Francis Eyiah-Bediako, Emmanuel Asare Ayim, Anthony Joe Turkson

Advances in Research · pp. 144–155 · Published 23 Jan 2026

10.9734/air/2026/v27i11575

Abstract

Early childbearing remains a persistent global public health challenge, yet existing evidence is largely derived from cross-sectional or pooled analyses that ignore hierarchical data structures and within-country dependence. The study aims to quantify the temporal dynamics and socio-economic inequalities in national proportions of child, sexual, and early childbearing (CSEC) while addressing key statistical limitations in prior research. This study used a quantitative, longitudinal research design with secondary country-level data from the UNICEF global maternal and adolescent health data repository. The analytic dataset comprises 555 observations of countries and survey years 2000-2023. Analysis of the results indicates no statistically significant trend over time after accounting for the hierarchical relationship (β = 0.017, p = 0.254), suggesting irregular progress. Significantly positive relationships were found in both rural (β = 2.238, CI: 1.529-2.947) and urban (β = 2.069, CI: 1.462-2.677) settings. Wealth effects were non-linear, with the largest coefficients in the middle (β = 2.941) and fourth (β = 2.340) quintiles, challenging conventional poor-rich dichotomies. A substantial proportion of variance was attributable to between-country differences, confirming the inadequacy of pooled models. The novelty of this research lies in its equity-aware longitudinal multilevel framework, which overcomes independence and aggregation biases in earlier studies. Actionable recommendations include adopting hierarchical monitoring for SDG reporting, strengthening adolescent reproductive health services in both rural and urban settings, and targeting socio-economically transitional populations often overlooked in policy design.

Global maternal and adolescent health socio-economic rural and urban health disparities linear mixed-effects models cross-country comparative analysis

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