Central African Republic CF: Mortality Rate: Under-5: Male: per 1000 Live Births data was reported at 103.400 Ratio in 2022. This records a decrease from the previous number of 106.100 Ratio for 2021. Central African Republic CF: Mortality Rate: Under-5: Male: per 1000 Live Births data is updated yearly, averaging 184.300 Ratio from Dec 1960 (Median) to 2022, with 63 observations. The data reached an all-time high of 285.000 Ratio in 1960 and a record low of 103.400 Ratio in 2022. Central African Republic CF: Mortality Rate: Under-5: Male: per 1000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Central African Republic – Table CF.World Bank.WDI: Social: Health Statistics. Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male age-specific mortality rates of the specified year.;Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.;Weighted average;Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys. Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation. This is a sex-disaggregated indicator for Sustainable Development Goal 3.2.1 [https://unstats.un.org/sdgs/metadata/].

The maternal mortality ratio in the Middle East and North Africa (MENA) region has drastically decreased, reaching 56 deaths per 100,000 live births in 2020 compared to 2000. However, improvement in the region's female mortality rate slowed down from 2014 to 2020.

In 2021, the maternal mortality rate amounted to nine to 10 women per one hundred thousands live births in South Korea. Overall, there was a decrease in the maternal mortality ratio over the considered timespan.

In 2022, the infant mortality rate in the United States was 5.4 out of every 1,000 live births. This is a significant decrease from 1960, when infant mortality was at around 26 deaths out of every 1,000 live births. What is infant mortality? The infant mortality rate is the number of deaths of babies under the age of one per 1,000 live births. There are many causes for infant mortality, which include birth defects, low birth weight, pregnancy complications, and sudden infant death syndrome. In order to decrease the high rates of infant mortality, there needs to be an increase in education and medicine so babies and mothers can receive the proper treatment needed. Maternal mortality is also related to infant mortality. If mothers can attend more prenatal visits and have more access to healthcare facilities, maternal mortality can decrease, and babies have a better chance of surviving in their first year. Worldwide infant mortality rates Infant mortality rates vary worldwide; however, some areas are more affected than others. Afghanistan suffered from the highest infant mortality rate in 2024, and the following 19 countries all came from Africa, with the exception of Pakistan. On the other hand, Slovenia had the lowest infant mortality rate that year. High infant mortality rates can be attributed to lack of sanitation, technological advancements, and proper natal care. In the United States, Massachusetts had the lowest infant mortality rate, while Mississippi had the highest in 2022. Overall, the number of neonatal and post neonatal deaths in the United States has been steadily decreasing since 1995.

Maternal mortality ratio shown by province from 2001 to 2018*Number of maternal deaths per 10,000 live births.The maternal mortality rate for every one hundred thousand live births is 38 according to 2016 data. Its fluctuations during the last decades demonstrate the need to focus on access and care by qualified professionals to reduce the causes of preventable deaths.Source: https://www.ossyr.org.ar/indicadores.php#Raz%C3%B3n-de-mortalidad-materna

Calculation Of Mortality Rates From Respiratory And Circulatory Diseases
This dataset falls under the category Environmental Data Other.
It contains the following data: Mortality rates according to respiratory and circulatory diseases calculated in the project "Air quality and its effects on the health of the population of the ten municipalities of the Aburra Valley, 2008 - 2015".
This dataset was scouted on 2022/01/18 as part of a data sourcing project conducted by TUMI. License information might be outdated: Check original source for current licensing. The data can be accessed using the following URL / API Endpoint: https://datosabiertos.metropol.gov.co/dataset/c%C3%A1lculo-tasas-de-mortalidad-de-enfermedades-respiratorias-y-circulatoriasSee URL for data access and license information.

In 2024, the mortality rate in China ranged at approximately 7.76 deaths per 1,000 inhabitants. The mortality rate in China displayed an uneven development over the last two decades. This is mainly related to the very uneven sizes of Chinese age groups, improvements in health care, and the occurrence of epidemics. However, an overall growing trend is undisputable and related to China's aging population. As the share of the population aged 60 and above will be growing significantly over the upcoming two decades, the mortality rate will further increase in the years ahead. Population in China China was the second most populous country in the world in 2024. However, due to several mechanisms put into place by the Chinese government as well as changing circumstances in the working and social environment of the Chinese people, population growth has subsided over the past decades and finally turned negative in 2022. The major factor for this development was a set of policies introduced by the Chinese government in 1979, including the so-called one-child policy, which was intended to improve people’s living standards by limiting the population growth. However, with the decreasing birth rate and slower population growth, China nowadays is facing the problems of a rapidly aging population. Birth control in China According to the one-child policy, a married couple was only allowed to have one child. Only under certain circumstances were parents allowed to have a second child. As the performance of family control had long been related to the assessment of local government’s achievements, violations of the rule were severely punished. The birth control in China led to a decreasing birth rate and a more skewed gender ratio of new births due to a widely preference for male children in the Chinese society. Nowadays, since China’s population is aging rapidly, the one-child policy has been re-considered as an obstacle for the country’s further economic development. Since 2014, the one-child policy has been gradually relaxed and fully eliminated at the end of 2015. In May 2021, a new three-child policy has been introduced. However, many young Chinese people today are not willing to have more children due to high costs of raising a child, especially in urban areas.

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.

Mali ML: Mortality Rate: Infant: per 1000 Live Births data was reported at 68.000 Ratio in 2016. This records a decrease from the previous number of 69.600 Ratio for 2015. Mali ML: Mortality Rate: Infant: per 1000 Live Births data is updated yearly, averaging 131.200 Ratio from Dec 1963 (Median) to 2016, with 54 observations. The data reached an all-time high of 213.400 Ratio in 1963 and a record low of 68.000 Ratio in 2016. Mali ML: Mortality Rate: Infant: per 1000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank: Health Statistics. Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 live births in a given year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted Average; Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys.

In 2023, the maternal mortality ratio in Malaysia was at 25.7 maternal deaths per 100,000 live births, a slight decrease compared to the previous year. The maternal mortality ratio refers to the annual number of female deaths caused by or related to pregnancy per one hundred thousand live births.

These indicators are designed to accompany the SHMI publication. Information on the main condition the patient is in hospital for (the primary diagnosis) is used to calculate the expected number of deaths used in the calculation of the SHMI. A high percentage of records with an invalid primary diagnosis may indicate a data quality problem. A high percentage of records with a primary diagnosis which is a symptom or sign may indicate problems with data quality or timely diagnosis of patients, but may also reflect the case-mix of patients or the service model of the trust (e.g. a high level of admissions to acute admissions wards for assessment and stabilisation). Contextual indicators on the percentage of provider spells with an invalid primary diagnosis and the percentage of provider spells with a primary diagnosis which is a symptom or sign are produced to support the interpretation of the SHMI. Notes: 1. There is a shortfall in the number of records for East Lancashire Hospitals NHS Trust (trust code RXR), Guy’s and St Thomas’ NHS Foundation Trust (trust code RJ1), and King’s College Hospital NHS Foundation Trust (trust code RJZ). Values for these trusts are based on incomplete data and should therefore be interpreted with caution. 2. Frimley Health NHS Foundation Trust (trust code RDU) stopped submitting data to the Secondary Uses Service (SUS) during June 2022 and did not start submitting data again until April 2023 due to an issue with their patient records system. This is causing a large shortfall in records and values for this trust should be viewed in the context of this issue. 3. A number of trusts are now submitting Same Day Emergency Care (SDEC) data to the Emergency Care Data Set (ECDS) rather than the Admitted Patient Care (APC) dataset. The SHMI is calculated using APC data. Removal of SDEC activity from the APC data may impact a trust’s SHMI value and may increase it. More information about this is available in the Background Quality Report. 4. Further information on data quality can be found in the SHMI background quality report, which can be downloaded from the 'Resources' section of this page.

This dataset of U.S. mortality trends since 1900 highlights childhood mortality rates by age group for age at death. Age-adjusted death rates (deaths per 100,000) after 1998 are calculated based on the 2000 U.S. standard population. Populations used for computing death rates for 2011–2017 are postcensal estimates based on the 2010 census, estimated as of July 1, 2010. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years between 2000 and 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Data on age-adjusted death rates prior to 1999 are taken from historical data (see References below). Age groups for childhood death rates are based on age at death. SOURCES CDC/NCHS, National Vital Statistics System, historical data, 1900-1998 (see https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm); CDC/NCHS, National Vital Statistics System, mortality data (see http://www.cdc.gov/nchs/deaths.htm); and CDC WONDER (see http://wonder.cdc.gov). REFERENCES National Center for Health Statistics, Data Warehouse. Comparability of cause-of-death between ICD revisions. 2008. Available from: http://www.cdc.gov/nchs/nvss/mortality/comparability_icd.htm. National Center for Health Statistics. Vital statistics data available. Mortality multiple cause files. Hyattsville, MD: National Center for Health Statistics. Available from: https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. Kochanek KD, Murphy SL, Xu JQ, Arias E. Deaths: Final data for 2017. National Vital Statistics Reports; vol 68 no 9. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_09-508.pdf. Arias E, Xu JQ. United States life tables, 2017. National Vital Statistics Reports; vol 68 no 7. Hyattsville, MD: National Center for Health Statistics. 2019. Available from: https://www.cdc.gov/nchs/data/nvsr/nvsr68/nvsr68_07-508.pdf. National Center for Health Statistics. Historical Data, 1900-1998. 2009. Available from: https://www.cdc.gov/nchs/nvss/mortality_historical_data.htm.

Forecast: Total Maternal Mortality Ratio in Norway 2023 - 2027 Discover more data with ReportLinker!

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.

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.

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.

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.

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.

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.

Laos LA: Mortality Rate: Under-5: per 1000 Live Births data was reported at 63.400 Ratio in 2017. This records a decrease from the previous number of 65.600 Ratio for 2016. Laos LA: Mortality Rate: Under-5: per 1000 Live Births data is updated yearly, averaging 121.450 Ratio from Dec 1978 (Median) to 2017, with 40 observations. The data reached an all-time high of 214.400 Ratio in 1978 and a record low of 63.400 Ratio in 2017. Laos LA: Mortality Rate: Under-5: per 1000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Laos – Table LA.World Bank: Health Statistics. Under-five mortality rate is the probability per 1,000 that a newborn baby will die before reaching age five, if subject to age-specific mortality rates of the specified year.; ; Estimates Developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys.