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Short Name<\/strong><\/u>
\nNeonatal mortality rate
<\/p>\n

Full Name<\/strong><\/u>
\nProbability of dying in the first month of life (in the five years preceding the survey) per 1,000 live births
<\/p>\n

Domain<\/strong><\/u>
\nSexual and reproductive health
<\/p>\n

Sub-domain<\/strong><\/u>
\nMaternal and newborn health
<\/p>\n

Tags<\/strong><\/u>
\nEnd preventable maternal deaths, SDG Target 3.2
<\/p>\n

Definition<\/strong><\/u>
\nThe probability that a child born in a specific year or period will die during the first 28 completed days of life, if subject to age-specific mortality rates of that period, expressed per 1000 live births.
<\/p>\n

Method of Calculation<\/strong><\/u>
\n
Data source specific method of calculation:<\/em>
\n
Global database:<\/strong>
The UN Inter-agency Group for Child Mortality Estimation (UN IGME) estimates are derived from nationally representative data from censuses, surveys or vital registration systems. The UN IGME does not use any covariates to derive its estimates (except in the case of neonatal mortality estimation, which incorporates the relatively more data-rich under-five mortality rate estimates in the modelling). It only applies a curve fitting method to good-quality empirical data to derive trend estimates after data quality assessment. In most cases, the UN IGME estimates are close to the underlying data. The UN IGME aims to minimize the errors for each estimate, harmonize trends over time and produce up-to-date and properly assessed estimates. The UN IGME produces neonatal mortality rate estimates with a Bayesian spline regression model which models the ratio of neonatal mortality rate / (under-five mortality rate - neonatal mortality rate). Estimates of NMR are obtained by recombining the estimates of the ratio with the UN IGME-estimated under-five mortality rate.\nFor the underlying data mentioned above, the most frequently used methods are as follows:\nCivil registration: The neonatal mortality rate can be calculated from the number of children who died during the first 28 days of life and the number of live births.\nCensuses and surveys: Censuses and surveys often include questions on household deaths in the last 12 months, which can be used to calculate mortality estimates.\nSurveys: A direct method is used based on a full birth history, a series of detailed questions on each child a woman has given birth to during her lifetime. Neonatal, post-neonatal, infant, child and under-five mortality estimates can be derived from the full birth history.\n
DHS:<\/strong>
the probability of a child exposed in a specific period dying before reaching the age of 1 month.\n
Numerator:<\/em>
Number of deaths at ages 0 to 30 days, including deaths reported at age zero months.\n
Denominator:<\/em>
Number of surviving children at beginning of specified age range during the specified time period.\n
Calculation:<\/em>
Component death probabilities are first tabulated. Then the component death probabilities are combined into the mortality rates. The component death probabilities are calculated for age segments 0, 1-2, 3-5, 6-11, 12-23, 24-35, 36-47, and 48-59 months of completed age. Each component death probability is defined by a time period and an age interval.
<\/p>\n

Expected Frequency of Data Dissemination<\/strong><\/u>
\nAnnual
<\/p>\n

Geospatial Dimension Availability<\/strong><\/u>
\nCountry (geolev0), Landlocked developing countries (LLDCs), Least Developed Countries (LDCs), SDG Regions, SDG Sub-Regions, Small island developing States (SIDS), Sub-national level 1 (geolev1), World
<\/p>\n

Time Dimension Availability<\/strong><\/u>
\n1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021
<\/p>\n

Disaggregation Dimension Availability<\/strong><\/u>
\nBirth order: 1, 2, 3, 4<\/em>
Education level: Higher, No education, No education or primary education, Primary education, Secondary education, Secondary education or higher<\/em>
Mother's age at birth: <20 years old, 20 to 29 years old, 30 to 39 years old, 40 to 49 years old<\/em>
Number of decisions woman has final say: Three or more decisions woman has final say, Woman has no final say<\/em>
Number of reasons for which wife-beating is justified: 0, 1-2, 3-4, 5<\/em>
Place of residence: Rural, Urban<\/em>
Previous birth interval: <2 years, 2 years, 3 years, 4+ years<\/em>
Sex: Female, Male<\/em>
Size at birth: Average or larger, Small or very small<\/em>
Wealth index: Middle, Poorer, Poorest, Richer, Richest<\/em>
<\/p>\n

References<\/strong><\/u>
\nSDG Indicator 3.2.2 metadata: Link<\/a>
<\/p>", "mapName": "hv_i67_gl3", "description": "Short Name\nNeonatal mortality rate\nFull Name\nProbability of dying in the first month of life (in the five years preceding the survey) per 1,000 live births \nDomain\nSexual and reproductive health\nSub-domain\nMaternal and newborn health\nTags\nEnd preventable maternal deaths, SDG Target 3.2\nDefinition\nThe probability that a child born in a specific year or period will die during the first 28 completed days of life, if subject to age-specific mortality rates of that period, expressed per 1000 live births.\nMethod of Calculation\nData source specific method of calculation:\nGlobal database: The UN Inter-agency Group for Child Mortality Estimation (UN IGME) estimates are derived from nationally representative data from censuses, surveys or vital registration systems. The UN IGME does not use any covariates to derive its estimates (except in the case of neonatal mortality estimation, which incorporates the relatively more data-rich under-five mortality rate estimates in the modelling). It only applies a curve fitting method to good-quality empirical data to derive trend estimates after data quality assessment. In most cases, the UN IGME estimates are close to the underlying data. The UN IGME aims to minimize the errors for each estimate, harmonize trends over time and produce up-to-date and properly assessed estimates. The UN IGME produces neonatal mortality rate estimates with a Bayesian spline regression model which models the ratio of neonatal mortality rate / (under-five mortality rate - neonatal mortality rate). Estimates of NMR are obtained by recombining the estimates of the ratio with the UN IGME-estimated under-five mortality rate.\nFor the underlying data mentioned above, the most frequently used methods are as follows:\nCivil registration: The neonatal mortality rate can be calculated from the number of children who died during the first 28 days of life and the number of live births.\nCensuses and surveys: Censuses and surveys often include questions on household deaths in the last 12 months, which can be used to calculate mortality estimates.\nSurveys: A direct method is used based on a full birth history, a series of detailed questions on each child a woman has given birth to during her lifetime. Neonatal, post-neonatal, infant, child and under-five mortality estimates can be derived from the full birth history.\nDHS: the probability of a child exposed in a specific period dying before reaching the age of 1 month.\nNumerator: Number of deaths at ages 0 to 30 days, including deaths reported at age zero months.\nDenominator: Number of surviving children at beginning of specified age range during the specified time period.\nCalculation: Component death probabilities are first tabulated. Then the component death probabilities are combined into the mortality rates. The component death probabilities are calculated for age segments 0, 1-2, 3-5, 6-11, 12-23, 24-35, 36-47, and 48-59 months of completed age. Each component death probability is defined by a time period and an age interval.\nExpected Frequency of Data Dissemination\nAnnual\nGeospatial Dimension Availability\nCountry (geolev0), Landlocked developing countries (LLDCs), Least Developed Countries (LDCs), SDG Regions, SDG Sub-Regions, Small island developing States (SIDS), Sub-national level 1 (geolev1), World\nTime Dimension Availability\n1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021\nDisaggregation Dimension Availability\nBirth order: 1, 2, 3, 4Education level: Higher, No education, No education or primary education, Primary education, Secondary education, Secondary education or higherMother's age at birth: <20 years old, 20 to 29 years old, 30 to 39 years old, 40 to 49 years oldNumber of decisions woman has final say: Three or more decisions woman has final say, Woman has no final sayNumber of reasons for which wife-beating is justified: 0, 1-2, 3-4, 5Place of residence: Rural, UrbanPrevious birth interval: <2 years, 2 years, 3 years, 4+ yearsSex: Female, MaleSize at birth: Average or larger, Small or very smallWealth index: Middle, Poorer, Poorest, Richer, Richest\nReferences\nSDG Indicator 3.2.2 metadata: Link", "copyrightText": "", "supportsDynamicLayers": true, "layers": [ { "id": 0, "name": "hv_i67_gl3", "parentLayerId": -1, "defaultVisibility": false, "subLayerIds": null, "minScale": 0, "maxScale": 0, "type": "Feature Layer", "geometryType": "esriGeometryPolygon", "supportsDynamicLegends": true } ], "tables": [], "spatialReference": { "wkid": 4326, "latestWkid": 4326, "xyTolerance": 8.983152841195215E-9, "zTolerance": 0.001, "mTolerance": 0.001, "falseX": -400, "falseY": -400, "xyUnits": 9.999999999999999E8, "falseZ": -100000, "zUnits": 10000, "falseM": -100000, "mUnits": 10000 }, "singleFusedMapCache": false, "initialExtent": { "xmin": -328.0378378378379, "ymin": -182.19386385839192, "xmax": 328.037837837838, "ymax": 208.98991992539203, "spatialReference": { "wkid": 4326, "latestWkid": 4326, "xyTolerance": 8.983152841195215E-9, "zTolerance": 0.001, "mTolerance": 0.001, "falseX": -400, "falseY": -400, "xyUnits": 9.999999999999999E8, "falseZ": -100000, "zUnits": 10000, "falseM": -100000, "mUnits": 10000 } }, "fullExtent": { "xmin": -180, "ymin": -90, "xmax": 180, "ymax": 90, "spatialReference": { "wkid": 4326, "latestWkid": 4326, "xyTolerance": 8.983152841195215E-9, "zTolerance": 0.001, "mTolerance": 0.001, "falseX": -400, "falseY": -400, "xyUnits": 9.999999999999999E8, "falseZ": -100000, "zUnits": 10000, "falseM": -100000, "mUnits": 10000 } }, "timeInfo": { "timeExtent": [ 946684800000, 1609459260000 ], "timeReference": null, "timeRelation": "esriTimeRelationOverlaps", "defaultTimeInterval": 1, "defaultTimeIntervalUnits": "esriTimeUnitsMonths", "defaultTimeWindow": 0, "defaultTimeWindowUnits": "esriTimeUnitsYears", "hasLiveData": false, "liveModeOffsetDirection": "past" }, "datesInUnknownTimezone": false, "minScale": 0, "maxScale": 0, "units": "esriDecimalDegrees", "supportedImageFormatTypes": "PNG32,PNG24,PNG,JPG,DIB,TIFF,EMF,PS,PDF,GIF,SVG,SVGZ,BMP", "documentInfo": { "Title": "template", "Author": "", "Comments": "", "Subject": "", "Category": "", "Version": "3.2.0", "AntialiasingMode": "None", "TextAntialiasingMode": "Force", "Keywords": "End preventable maternal deaths,SDG Target 3.2" }, "supportsQueryDomains": true, "capabilities": "Map,Query,Data", "supportedQueryFormats": "JSON, geoJSON, PBF", "exportTilesAllowed": false, "referenceScale": 0.0, "supportsDatumTransformation": true, "archivingInfo": {"supportsHistoricMoment": false}, "supportsClipping": true, "supportsSpatialFilter": true, "supportsTimeRelation": true, "supportsQueryDataElements": true, "mapUnits": {"uwkid": 9102}, "maxRecordCount": 2000, "maxImageHeight": 4096, "maxImageWidth": 4096, "supportedExtensions": "FeatureServer", "serviceItemId": "2fa0c8237fd04a5580eea9d7f725f158" }