Decomposing low birth weight inequality in Lesotho: A distributional analysis using hybrid Fairlie and recentred influence function methods on multiple indicator cluster survey 2018

Background: Low birth weight (LBW) is a major public health concern in Lesotho, linked to higher infant mortality, long-term morbidity and intergenerational poverty. Despite expanded maternal and child health services, socio-economic disparities in birth outcomes persist. Aim: This study investigates the drivers of LBW inequality, quantifying and decomposing socio-economic and geographic disparities to inform equity-oriented health policy. Setting: The study used nationally representative data from the 2018 Lesotho Multiple Indicator Cluster Survey, covering all 10 districts. Methods: A hybrid econometric framework was applied. Low birth weight inequality was first assessed by using the Concentration Index (CI), Erreygers Index (EI) and Wagstaff Index (WI). Fairlie decomposition was then used to compare LBW probabilities between poor vs. rich and rural vs. urban households. Finally, recentred influence function regressions examined the distributional impact of maternal and household factors across the 28th, 50th and 75th birth weight percentiles. Results: Maternal education, antenatal care (ANC) attendance, maternal disability and digital connectivity were key determinants of LBW, with effects varying across the birth weight distribution. Only 20.5% of the poor-rich LBW gap was explained by observable characteristics, primarily education and ANC. Recentred influence function regressions revealed stronger protective effects of education and ANC at lower percentiles, while maternal disability and Internet access were more relevant at higher percentiles. Conclusion: LBW in Lesotho reflects both structural barriers and compositional disadvantages. Addressing these requires equity-focused, distribution-sensitive maternal health interventions. Contribution: This study provides evidence-based insights to inform targeted policies to reduce LBW among vulnerable populations.