{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T16:07:54Z","timestamp":1785859674865,"version":"3.56.0"},"reference-count":33,"publisher":"American Medical Association (AMA)","issue":"11","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"Importance<\/jats:title>In 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.<\/jats:p><\/jats:sec>Objective<\/jats:title>To examine the variation between smaller areas within districts in the quality of maternal and newborn care in India.<\/jats:p><\/jats:sec>Design, Setting, and Participants<\/jats:title>This 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).<\/jats:p><\/jats:sec>Exposures<\/jats:title>Maternal and newborn care in 36 states and union territories (UTs), 707 districts, and 28\u202f113 clusters (small areas) in India.<\/jats:p><\/jats:sec>Main Outcomes and Measures<\/jats:title>The 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\u2013small area SD were calculated.<\/jats:p><\/jats:sec>Results<\/jats:title>The final analytic sample for the composite score was composed of 123\u202f257 births nested in 28\u202f113 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 \u03c1\u2009=\u2009\u22120.981 to \u22120.886). Low-quality scores and large between\u2013small 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).<\/jats:p><\/jats:sec>Conclusions and Relevance<\/jats:title>The 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\u2013small 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.<\/jats:p><\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2022.42666","type":"journal-article","created":{"date-parts":[[2022,11,28]],"date-time":"2022-11-28T16:32:47Z","timestamp":1669653167000},"page":"e2242666","source":"Crossref","is-referenced-by-count":14,"title":["Small Area Variation in the Quality of Maternal and Newborn Care in India"],"prefix":"10.1001","volume":"5","author":[{"given":"Hwa-Young","family":"Lee","sequence":"first","affiliation":[{"name":"Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts"},{"name":"Institute of Convergence Science, Convergence Science Academy, Yonsei University, Seoul, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Md Juel","family":"Rana","sequence":"additional","affiliation":[{"name":"Korea University Research and Business Foundation, Seoul, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rockli","family":"Kim","sequence":"additional","affiliation":[{"name":"Division of Health Policy and Management, College of Health Science, Korea University, Seoul, South Korea"},{"name":"Interdisciplinary Program in Precision Public Health, Department of Public Health Sciences, Graduate School of Korea University, Seoul, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S. 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