variables: 905841

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.

Data license: CC-BY

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
905841 Maternal mortality ratio (modeled estimate, per 100,000 live births) modeled estimate, per 100,000 live births   2024-05-31 06:52:19 2024-07-08 16:51:18     2000-2020 6543   modeled estimate, 
{
    "unit": "modeled estimate, per 100,000 live births",
    "shortUnit": "modeled estimate,"
}
 0     sh_sta_mmrt grapher/worldbank_wdi/2024-05-20/wdi/wdi#sh_sta_mmrt   2               Maternal mortality ratio is the number of women who die from pregnancy-related causes while pregnant or within 42 days of pregnancy termination per 100,000 live births. The data are estimated with a regression model using information on the proportion of maternal deaths among non-AIDS deaths in women ages 15-49, fertility, birth attendants, and GDP measured using purchasing power parities (PPPs). Limitations and exceptions: The methodology differs from that used for previous estimates, so data should not be compared historically. Maternal mortality ratios are generally of unknown reliability, as are many other cause-specific mortality indicators. The ratios cannot be assumed to provide an exact estimate of maternal mortality. Statistical concept and methodology: Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. Means of achieving reproductive health include education and services during pregnancy and childbirth, safe and effective contraception, and prevention and treatment of sexually transmitted diseases. Complications of pregnancy and childbirth are the leading cause of death and disability among women of reproductive age in developing countries. Maternal mortality is generally of unknown reliability, as are many other cause-specific mortality indicators. Household surveys such as Demographic and Health Surveys attempt to measure maternal mortality by asking respondents about survivorship of sisters. The main disadvantage of this method is that the estimates of maternal mortality that it produces pertain to any time within the past few years before the survey, making them unsuitable for monitoring recent changes or observing the impact of interventions. In addition, measurement of maternal mortality is subject to many types of errors. Even in high-income countries with reliable vital registration systems, misclassification of maternal deaths has been found to lead to serious underestimation. The estimates are based on an exercise by the Maternal Mortality Estimation Inter-Agency Group (MMEIG) which consists of World Health Organization (WHO), United Nations Children's Fund (UNICEF), World Bank, and United Nations Population Fund (UNFPA), and include country-level time series data. For countries without complete registration data but with other types of data and for countries with no data, maternal mortality is estimated with a regression model using available national maternal mortality data and socioeconomic information. Notes from original source: Estimates of maternal mortality are presented along with upper and lower limits of intervals (see footnote) designed to depict the uncertainty of estimates. The intervals are the product of a detailed probabilistic evaluation of the uncertainty attributable to the various components of the estimation process. For estimates derived from the multilevel regression model, the components of uncertainty were divided into two groups: those reflected within the regression model (internal sources), and those due to assumptions or calculations that occur outside the model (external sources). Estimates of the total uncertainty reflect a combination of these various sources. 
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 54fe404b4c7a396a1619d0a77a2be854 c37e9e03631c13f21bd3697c63006889

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