Frontiers in public health · 2026
Inequality atop excess: a nonlinear decomposition of wealth-related inequality in caesarean section delivery in Punjab, Pakistan.
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Nadeem Muhammad, Adil Shahid, Bashatah Adel, Arifi Mohamed N Al, Syed Wajid, Iqbal Ayesha
Аннотация
BACKGROUND: Caesarean section (CS) rates are rising rapidly across South Asia, and Pakistan combines over-use among advantaged groups with historically limited access among the poor. Quantifying and decomposing wealth-related inequality in CS delivery is essential for equitable obstetric policy. Decomposed by the Wagstaff-van Doorslaer method; the rich-poor gap was decomposed using a two-fold nonlinear (Yun) Oaxaca-Blinder decomposition. All estimates applied survey weights with PSU-cluster-robust inference; analyses used Python 3.12 (statsmodels 0.14). Because service-use variables lie on the causal pathway between wealth and CS, hierarchical models are reported and all decomposition results are descriptive, not causal.
METHODS: A cross-sectional analysis of 6,832 ever-married women with recorded last pregnancy delivery from the Punjab Health and Population Survey (PHPS) 2024-25 was done. The aim was to measure inequality by wealth in the rates of cesarean section (CS) delivery and identify the channels responsible for the inequality. The dependent variable CS delivery was binary, with the primary explanatory variable being a principal-component analysis (PCA) based household wealth index, with maternal, service use and clinical covariates. Inequality was measured using concentration curves, standard concentration index, Wagstaff-normalised concentration index, Erreygers concentration index and decomposed by Wagstaff-van Doorslaer method. The rich-poor gap was decomposed by a two-fold nonlinear (Yun) Oaxaca-Blinder decomposition. Survey weights were employed in all estimates, which were derived using PSU-cluster-robust inference; analyses were conducted in Python 3.12 (statsmodels 0.14). Because service-use variables lie on the causal pathway between wealth and CS, hierarchical models are reported and all decomposition results are descriptive, not causal.
RESULTS: The weighted CS rate was 43.3% (21.0% poorest to 64.6% richest quintile). CS delivery was concentrated among the wealthy (standard CI = 0.195, 95% CI 0.173-0.215; Erreygers = 0.337, 95% CI 0.301-0.373). In the fully adjusted model the richest quintile (OR 2.07, 95% CI 1.50-2.85), private-facility delivery (OR 3.50, 2.90-4.23) and lady-doctor attendance (OR 13.10, 9.65-17.80) showed the strongest associations. There was no multicollinearity (all VIF < 2.45) and model discrimination was good (AUC 0.824). Excluding proximate service-use variables, observed characteristics accounted for 66.9% of the 28.4-percentage-point rich-poor gap; adding service use raised this to 87.3%, with lady-doctor attendance (44.7%) and private-facility delivery (20.9%) the largest components.
CONCLUSION: Wealth-related inequality in caesarean delivery in Punjab is predominantly associated with differential access to private, physician-led obstetric care. These associations are descriptive and cannot establish causation. Policy should pair clinical audit of elective CS indications in the private sector with financial protection for medically necessary CS among poorer women.
METHODS: A cross-sectional analysis of 6,832 ever-married women with recorded last pregnancy delivery from the Punjab Health and Population Survey (PHPS) 2024-25 was done. The aim was to measure inequality by wealth in the rates of cesarean section (CS) delivery and identify the channels responsible for the inequality. The dependent variable CS delivery was binary, with the primary explanatory variable being a principal-component analysis (PCA) based household wealth index, with maternal, service use and clinical covariates. Inequality was measured using concentration curves, standard concentration index, Wagstaff-normalised concentration index, Erreygers concentration index and decomposed by Wagstaff-van Doorslaer method. The rich-poor gap was decomposed by a two-fold nonlinear (Yun) Oaxaca-Blinder decomposition. Survey weights were employed in all estimates, which were derived using PSU-cluster-robust inference; analyses were conducted in Python 3.12 (statsmodels 0.14). Because service-use variables lie on the causal pathway between wealth and CS, hierarchical models are reported and all decomposition results are descriptive, not causal.
RESULTS: The weighted CS rate was 43.3% (21.0% poorest to 64.6% richest quintile). CS delivery was concentrated among the wealthy (standard CI = 0.195, 95% CI 0.173-0.215; Erreygers = 0.337, 95% CI 0.301-0.373). In the fully adjusted model the richest quintile (OR 2.07, 95% CI 1.50-2.85), private-facility delivery (OR 3.50, 2.90-4.23) and lady-doctor attendance (OR 13.10, 9.65-17.80) showed the strongest associations. There was no multicollinearity (all VIF < 2.45) and model discrimination was good (AUC 0.824). Excluding proximate service-use variables, observed characteristics accounted for 66.9% of the 28.4-percentage-point rich-poor gap; adding service use raised this to 87.3%, with lady-doctor attendance (44.7%) and private-facility delivery (20.9%) the largest components.
CONCLUSION: Wealth-related inequality in caesarean delivery in Punjab is predominantly associated with differential access to private, physician-led obstetric care. These associations are descriptive and cannot establish causation. Policy should pair clinical audit of elective CS indications in the private sector with financial protection for medically necessary CS among poorer women.