Small Area Variation in the Quality of Maternal and Newborn Care in India

Abstract

ImportanceIn India, the district serves as the primary policy unit for implementing and allocating resources for various programs aimed at improving key developmental and health indicators. Recent evidence highlights that high-quality care for mothers and newborns is critical to reduce preventable mortality. However, the geographic variation in maternal and newborn health service quality has never been investigated.ObjectiveTo examine the variation between smaller areas within districts in the quality of maternal and newborn care in India.Design, Setting, and ParticipantsThis cross-sectional study assessed data from women aged 15 to 49 years on the most recent birth (singleton or multiples) in the 5 years that preceded the fifth National Family Health Survey (June 17, 2019, to April 30, 2021).ExposuresMaternal and newborn care in 36 states and union territories (UTs), 707 districts, and 28 113 clusters (small areas) in India.Main Outcomes and MeasuresThe composite quality score of maternal and newborn care was defined as the proportion of components of care received of the total 11 essential components of antenatal and postnatal care. Four-level logistic and linear regression was used for analyses of individual components of care and composite score, respectively. Precision-weighted prevalence of each component of care and mean composite score across districts as well as their between–small area SD were calculated.ResultsThe final analytic sample for the composite score was composed of 123 257 births nested in 28 113 small areas, 707 districts, and 36 states/UTs. For the composite score, 58.3% of the total geographic variance was attributable to small areas, 29.3% to states and UTs, and 12.4% to districts. Of 11 individual components of care, the small areas accounted for the largest proportion of geographic variation for 6 individual components of care (ranging from 42.3% for blood pressure taken to 73.0% for tetanus injection), and the state/UT was the largest contributor for 4 components of care (ranging from 41.7% for being weighed to 52.3% for ultrasound test taken). District-level composite score and prevalence of individual care components and their variation across small areas within the districts showed a consistently strong negative correlation (Spearman rank correlation ρ = −0.981 to −0.886). Low-quality scores and large between–small area disparities were not necessarily concentrated in aspirational districts (mean district composite score [SD within districts], 92.7% [2.1%] among aspirational districts and 93.7% [1.8%] among nonaspirational districts).Conclusions and RelevanceThe findings of this cross-sectional study suggest that the policy around maternal and child health care needs to be designed more precisely to consider district mean and between–small area heterogeneity in India. This study may have implications for other low- and middle-income countries seeking to improve maternal and newborn outcomes, particularly for large countries with geographic heterogeneity.

Multilevel analysis of determinants in postnatal care utilisation among mother-newborn pairs in India, 2019–21

“…We also found that cluster variation was substantial across all selected states. A recent study that attempted to partition the geographic variation in a composite score of maternal health care quality in India had similar results (VPC for clusters = 58.3%, states/union territories = 29.3%, and districts = 12.4%), indicating the relative importance of clusters in reducing geographic inequalities for overall maternal health care quality in India [ 18 ]. Although the Indian government adopted the Reproductive, Maternal, Newborn, Child, and Adolescent Health (RMNCH + A) framework to improve maternal and child health since 2013 [ 46 ], the intervention undertaken within have mainly been focussed at the district level [ 29 , 47 , 48 ].…”

“…To further advance the accumulating literature quantifying small area variation in various health outcomes in India [ 15 – 18 , 49 ], we assessed the extent to which total contextual variation in PNC utilisation at each geographic level can be explained by different compositional factors. When we simultaneously considered various demographic, socioeconomic, and pregnancy-related characteristics, we found maternal education, household wealth, health insurance, ANC visits, and delivery at private facilities to be statistically significant factors associated with maternal and newborn PNC utilisation.…”

“…According to a recent study evaluating the geographic variations in a composite score of maternal health care quality, including PNC utilisation, more than half (58.3%) of the total geographic variance in India was attributed to clusters [ 18 ], indicating the importance of smaller geographic levels for addressing inequalities in maternal and newborn health. However, this study did not assess the extent to which the observed geographic variation at multiple levels can be explained by various known risk factors.…”

Small Area Geographic Estimates of Cardiovascular Disease Risk Factors in India

“…A 4-level logistic regression was estimated for each outcome using standard multilevel modeling [6][7][8][9][10][11][12][13][14] (eEquation 1 in Supplement 1), and variance partitioning coefficient (VPC) was calculated for each level (eEquation 2 in Supplement 1). In this study, we focused on the total geographic variability as opposed to total variability (including 3.29 as level 1 variance) to assess the relative importance of geographic levels.…”

“…4 For example, states are principal macro policy units, and districts are subdivisions of states that serve as central policy units for the development, administration, and implementation of programs. 5 However, prior studies have consistently demonstrated considerable variability across small areas for various development and health outcomes, [6][7][8][9][10][11][12][13][14] underscoring the significant inequality within any given district and raising concerns about the potential limitations of a one-size-fits-all approach based on district averages. These findings are primarily restricted to child-related issues, such as poor nutrition [8][9][10] and birth outcomes, [11][12][13] and there remains limited knowledge about small area variability in CVD risk factors among adults.…”