variables: 959820

This table contains all the variables of all the datasets we have at Our World In Data. Note that this includes only the information about the variables like name and default display settings, not the data itself.

This data as json

id name unit description createdAt updatedAt code coverage timespan datasetId sourceId shortUnit display columnOrder originalMetadata grapherConfigAdmin shortName catalogPath dimensions schemaVersion processingLevel processingLog titlePublic titleVariant attributionShort attribution descriptionShort descriptionFromProducer descriptionKey descriptionProcessing licenses license grapherConfigETL type sort dataChecksum metadataChecksum
959820 Estimated live births births   2024-07-29 15:05:38 2024-07-29 15:05:39     1985-2020 6642     
{
    "unit": "births",
    "numDecimalPlaces": 0
}
 0     births grapher/un/2024-07-08/maternal_mortality/maternal_mortality#births   2             The estimated number of live births in a given year. - Data on maternal mortality and other relevant variables are obtained through databases maintained by WHO, UNPD, UNICEF, and the World Bank Group. Data available from countries varies in terms of the source and methods. Given the variability of the sources of data, different methods are used for each data source in order to arrive at country estimates that are comparable and permit regional and global aggregation. The current methodology employed by the Maternal Mortality Estimation Inter-Agency Group (MMEIG) in this round followed an improved approach that built directly upon methods used to produce the previous rounds of estimates published by the MMEIG since 2008. Estimates for this round were generated using a Bayesian approach, referred to as the Bayesian maternal mortality estimation model, or BMat model. This enhanced methodology uses the same core estimation method as in those previous rounds, but adds refinements to optimize the use of country-specific data sources and excludes late maternal deaths. It therefore provides more accurate estimates, and a more realistic assessment of certainty about those estimates. The new model still incorporates the same covariates which are; - the Gross Domestic Product per capita based on purchasing power parity conversion (GDP), - the general fertility rate (GFR) - proportion of births attended by a skilled health worker (SAB). The MMEIG has developed a method to adjust existing data in order to take into account these data quality issues and ensure the comparability of different data sources. This method involves assessment of data for underreporting and, where necessary, adjustment for incompleteness and misclassification of deaths as well as development of estimates through statistical modelling for countries with no reliable national level data. 
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 - The data shown is the UN MMEIG point estimate - this means there is a 50% chance that the true measure lies above this point, and a 50% chance that the true value lies below this point.       float 
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 3515a2177839b0499c893bd3a3f3ba0e f628041030a8b54c8c69e79b42bbd8bb

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