{"componentChunkName":"component---src-templates-post-query-tsx","path":"/blog-post/30000-babies-in-up/","result":{"pageContext":{"post":{"slug":"/blog-post/30000-babies-in-up/","title":"30,000 babies in UP","date":"Feb 29, 2016","timeToRead":1,"description":"Neonatal mortality is the number of babies, per 1000 live births, that die in the first 28 days of life.Postneonatal mortality is the number of babies, per 1000 live births, that die between 29 days and a year.","body":"function _extends() { _extends = Object.assign || function (target) { for (var i = 1; i < arguments.length; i++) { var source = arguments[i]; for (var key in source) { if (Object.prototype.hasOwnProperty.call(source, key)) { target[key] = source[key]; } } } return target; }; return _extends.apply(this, arguments); }\n\nfunction _objectWithoutProperties(source, excluded) { if (source == null) return {}; var target = _objectWithoutPropertiesLoose(source, excluded); var key, i; if (Object.getOwnPropertySymbols) { var sourceSymbolKeys = Object.getOwnPropertySymbols(source); for (i = 0; i < sourceSymbolKeys.length; i++) { key = sourceSymbolKeys[i]; if (excluded.indexOf(key) >= 0) continue; if (!Object.prototype.propertyIsEnumerable.call(source, key)) continue; target[key] = source[key]; } } return target; }\n\nfunction _objectWithoutPropertiesLoose(source, excluded) { if (source == null) return {}; var target = {}; var sourceKeys = Object.keys(source); var key, i; for (i = 0; i < sourceKeys.length; i++) { key = sourceKeys[i]; if (excluded.indexOf(key) >= 0) continue; target[key] = source[key]; } return target; }\n\n/* @jsxRuntime classic */\n\n/* @jsx mdx */\nvar _frontmatter = {\n  \"title\": \"30,000 babies in UP\",\n  \"date\": \"2016-02-29\",\n  \"template\": \"post\",\n  \"slug\": \"30000-babies-in-up\",\n  \"postedLink\": \"https://riceinstitute.org/blog/30000-babies-in-up/\",\n  \"description\": \"Neonatal mortality is the number of babies, per 1000 live births, that die in the first 28 days of life.Postneonatal mortality is the number of babies, per 1000 live births, that die between 29 days and a year.\",\n  \"tags\": \"Blog Post\",\n  \"banner\": \"up-mortality-graph.jpg\"\n};\nvar layoutProps = {\n  _frontmatter: _frontmatter\n};\nvar MDXLayout = \"wrapper\";\nreturn function MDXContent(_ref) {\n  var components = _ref.components,\n      props = _objectWithoutProperties(_ref, [\"components\"]);\n\n  return mdx(MDXLayout, _extends({}, layoutProps, props, {\n    components: components,\n    mdxType: \"MDXLayout\"\n  }), mdx(\"p\", null, \"Neonatal mortality is the number of babies, per 1000 live births, that die in the first 28 days of life.Postneonatal mortality is the number of babies, per 1000 live births, that die between 29 days and a year.Infant mortality is the sum of these two rates, that is, the number of babies, per 1000 live births, who die in the first year.\\xA0\\xA0\"), mdx(\"p\", null, \"These numbers are considered good summary measures of population health.\"), mdx(\"p\", null, \"The graphs below\\xA0show state level differences in neonatal, postneonatal, and infant mortality from two of India\\u2019s most recent datasets - the Annual Health Survey (AHS) and the Sample Registration System (SRS.The results for most states, and most rates, are quite similar.\\xA0\\xA0The exception is neonatal mortality in Uttar Pradesh.\"), mdx(\"p\", null, \"SRS\\xA0reports UP\\u2019s neonatal mortality rate as 43.9 while the AHS reports it as 50.0.\\xA0 As stand-alone rates, these numbers do not seem so wildly different, but because Uttar Pradesh has such a large population, the discrepancy in neonatal deaths between the two sources is over 30,000 deaths!\\xA0\\xA0Perhaps another survey is in order.\"), mdx(\"p\", null, \"No matter which of the surveys you use, Uttar Pradesh has one of the highest neonatal mortality (NNM) rates in the country.\\xA0 That over 200,000 babies die in Uttar Pradesh every year is a tragedy.\\xA0 These are babies who have been loved by parents and grandparents and siblings and neighbors.\"), mdx(\"p\", null, \"Although the downward sloping lines in these graphs indicate that things are getting better across the eight states, including Uttar Pradesh, improvement is not happening fast enough.\\xA0\\xA0Uttar Pradesh\\u2019s especially high rates suggest the need pay more attention to understanding and addressing the causes of NNM there.\"), mdx(\"p\", null, mdx(\"span\", {\n    parentName: \"p\",\n    \"className\": \"gatsby-resp-image-wrapper\",\n    \"style\": {\n      \"position\": \"relative\",\n      \"display\": \"block\",\n      \"marginLeft\": \"auto\",\n      \"marginRight\": \"auto\",\n      \"maxWidth\": \"730px\"\n    }\n  }, \"\\n      \", mdx(\"span\", {\n    parentName: \"span\",\n    \"className\": \"gatsby-resp-image-background-image\",\n    \"style\": {\n      \"paddingBottom\": \"59.00000000000001%\",\n      \"position\": \"relative\",\n      \"bottom\": \"0\",\n      \"left\": 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