74 datasets found
  1. Countries with the highest infant mortality rate 2024

    • statista.com
    • ai-chatbox.pro
    Updated Apr 16, 2025
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    Statista (2025). Countries with the highest infant mortality rate 2024 [Dataset]. https://www.statista.com/statistics/264714/countries-with-the-highest-infant-mortality-rate/
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    Dataset updated
    Apr 16, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Worldwide
    Description

    This statistic shows the 20 countries* with the highest infant mortality rate in 2024. An estimated 101.3 infants per 1,000 live births died in the first year of life in Afghanistan in 2024. Infant and child mortality Infant mortality usually refers to the death of children younger than one year. Child mortality, which is often used synonymously with infant mortality, is the death of children younger than five. Among the main causes are pneumonia, diarrhea – which causes dehydration – and infections in newborns, with malnutrition also posing a severe problem. As can be seen above, most countries with a high infant mortality rate are developing countries or emerging countries, most of which are located in Africa. Good health care and hygiene are crucial in reducing child mortality; among the countries with the lowest infant mortality rate are exclusively developed countries, whose inhabitants usually have access to clean water and comprehensive health care. Access to vaccinations, antibiotics and a balanced nutrition also help reducing child mortality in these regions. In some countries, infants are killed if they turn out to be of a certain gender. India, for example, is known as a country where a lot of girls are aborted or killed right after birth, as they are considered to be too expensive for poorer families, who traditionally have to pay a costly dowry on the girl’s wedding day. Interestingly, the global mortality rate among boys is higher than that for girls, which could be due to the fact that more male infants are actually born than female ones. Other theories include a stronger immune system in girls, or more premature births among boys.

  2. Leading causes of death among children aged 5-9 years in the United States...

    • statista.com
    • ai-chatbox.pro
    Updated Dec 13, 2024
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    Statista (2024). Leading causes of death among children aged 5-9 years in the United States 2020-2022 [Dataset]. https://www.statista.com/statistics/1017949/distribution-of-the-10-leading-causes-of-death-among-children-five-to-nine/
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    Dataset updated
    Dec 13, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The leading causes of death among children aged 5 to 9 years in the United States in 2022 were unintentional injuries, cancer, and congenital malformations, deformations and chromosomal abnormalities. At that time, unintentional injuries accounted for around 28 percent of all deaths among this age group. Child abuse in the U.S. Sadly, assault or homicide, was the fourth leading cause of death among those aged 5 to 9 years in the United States in 2022, accounting for around 9.4 percent of all deaths. That year, there were around 113,259 cases of child abuse in the U.S. among children aged 6 to 9 years and 129,846 cases among children aged 2 to 5 years. In 2022, there were around 5.36 child deaths per day in the United States due to abuse and neglect. Suicide among children Assault or homicide was also among the top five leading causes of death among children aged 10 to 14 years, but perhaps even more troubling is that suicide is the second leading cause of death among this age group. As with younger children, unintentional injuries are the leading cause of death among those aged 10 to 14 years, however, suicide accounts for around 13 percent of all deaths among this age group. Comparatively, suicide is not among the ten-leading causes of death among children from the age 1 to 9 years.

  3. Leading causes of death, total population, by age group

    • www150.statcan.gc.ca
    • open.canada.ca
    Updated Feb 19, 2025
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    Government of Canada, Statistics Canada (2025). Leading causes of death, total population, by age group [Dataset]. http://doi.org/10.25318/1310039401-eng
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    Dataset updated
    Feb 19, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

  4. Countries with the highest child mortality rates worldwide 2022

    • statista.com
    Updated Jan 23, 2025
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    Statista (2025). Countries with the highest child mortality rates worldwide 2022 [Dataset]. https://www.statista.com/statistics/1458360/countries-highest-child-mortality-rate-world/
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    Dataset updated
    Jan 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Worldwide
    Description

    19 of the 20 countries worldwide with the highest number of children under the age of five dying per 1,000 live births were found in Sub-Saharan Africa, with Niger, Nigeria, and Somalia topping the list. This made it the world region with the significantly highest child mortality rate in 2022.

  5. Global deaths of children under five in 2015, by cause

    • statista.com
    • ai-chatbox.pro
    Updated Apr 16, 2018
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    Statista (2018). Global deaths of children under five in 2015, by cause [Dataset]. https://www.statista.com/statistics/221052/causes-of-global-child-death/
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    Dataset updated
    Apr 16, 2018
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2015
    Area covered
    Worldwide
    Description

    This statistic shows the global causes of death of children under five in 2015. Malaria was responsible for five percent of global deaths of children aged under five, while pneumonia accounted for 13 percent of all such deaths.

  6. Leading causes of child death in refugee camps/settlements worldwide in 2022...

    • statista.com
    Updated Sep 9, 2024
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    Statista (2024). Leading causes of child death in refugee camps/settlements worldwide in 2022 [Dataset]. https://www.statista.com/statistics/1445726/leading-causes-of-child-death-refugee-camps-settlements-worldwide/
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    Dataset updated
    Sep 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Worldwide
    Description

    According to data from 2022 from 172 refugee camps/settlements hosting over five million refugees in 21 countries, the leading cause of death among child refugees under five years of age in such places were neonatal conditions, lower respiratory tract infections, and malaria. That year, neonatal conditions accounted for around 27 percent of all deaths among children in refugee camps/settlements. This statistic shows the leading causes of death among children under five years in refugee camps/settlements worldwide in 2022.

  7. Leading global causes of death among children under 5 as of 2015

    • statista.com
    Updated Jul 6, 2017
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    Statista (2017). Leading global causes of death among children under 5 as of 2015 [Dataset]. https://www.statista.com/statistics/720065/global-death-causes-for-children-under-5/
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    Dataset updated
    Jul 6, 2017
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2015
    Area covered
    Worldwide
    Description

    This statistic displays the distribution of the leading global causes of death for children under five as of 2015. According to the statistic, 18 percent of child deaths were due to prematurity and around 15 percent were due to pneumonia as of 2015.

  8. f

    Comparison of Maternal Mortality Estimates: Zambia, Bangladesh, Mozambique.

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Siân L. Curtis; Robert G. Mswia; Emily H. Weaver (2023). Comparison of Maternal Mortality Estimates: Zambia, Bangladesh, Mozambique. [Dataset]. http://doi.org/10.1371/journal.pone.0135062.t006
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    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Siân L. Curtis; Robert G. Mswia; Emily H. Weaver
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Bangladesh
    Description

    Sources:a National Institute for Population Research and Training, MEASURE Evaluation, International Centre for Diarrhoeal Disease Research (2012) Bangladesh Maternal Mortality and Health Care Survey 2010. Available: http://www.cpc.unc.edu/measure/publications/tr-12-87. Accessed October 15, 2012.b World Health Organization (ND) WHO Maternal Mortality Country Profiles. Available: www.who.int/gho/maternal_health/en/#M. Accessed 1 March 2015.c Lozano R, Wang H, Foreman KJ, Rajaratnam JK, Naghavi M, Marcus JR, et al. (2011) Progress towards Millennium Development Goals 4 and 5 on maternal and child mortality: an updated systematic analysis. Lancet 378(9797): 1139–65. 10.1016/S0140-6736(11)61337-8d UNFPA, UNICEF, WHO, World Bank (2012) Trends in maternal mortality: 1990–2010. Available: http://www.unfpa.org/public/home/publications/pid/10728. Accessed 7 October 2012.e Bangladesh Bureau of Statistics, Statistics Informatics Division, Ministry of Planning (December 2012) Population and Housing Census 2011, Socio-economic and Demographic Report, National Series–Volume 4. Available at: http://203.112.218.66/WebTestApplication/userfiles/Image/BBS/Socio_Economic.pdf. Accessed 15 February, 2015.f Mozambique National Institute of Statistics, U.S. Census Bureau, MEASURE Evaluation, U.S. Centers for Disease Control and Prevention (2012) Mortality in Mozambique: Results from a 2007–2008 Post-Census Mortality Survey. Available: http://www.cpc.unc.edu/measure/publications/tr-11-83. Accessed 6 October 2012.g Ministerio da Saude (MISAU), Instituto Nacional de Estatística (INE) e ICF International (ICFI). Moçambique Inquérito Demográfico e de Saúde 2011. Calverton, Maryland, USA: MISAU, INE e ICFI.h Mudenda SS, Kamocha S, Mswia R, Conkling M, Sikanyiti P, et al. (2011) Feasibility of using a World Health Organization-standard methodology for Sample Vital Registration with Verbal Autopsy (SAVVY) to report leading causes of death in Zambia: results of a pilot in four provinces, 2010. Popul Health Metr 9:40. 10.1186/1478-7954-9-40i Central Statistical Office (CSO), Ministry of Health (MOH), Tropical Diseases Research Centre (TDRC), University Teaching Hospital Virology Laboratory, University of Zambia, and ICF International Inc. 2014. Zambia Demographic and Health Survey 2013–14: Preliminary Report. Rockville, Maryland, USA. Available: http://dhsprogram.com/pubs/pdf/PR53/PR53.pdf. Accessed February 26, 2015.j Centers for Disease Control and Prevention (2014) Saving Mothers, Giving Life: Maternal Mortality.Phase 1 Monitoring and Evaluation Report. Atlanta, GA: Centers for Disease Control and Prevention, US Dept of Health and Human Services. Available at: http://www.savingmothersgivinglife.org/doc/Maternal%20Mortality%20(advance%20copy).pdf. Accessed 26 February 2015.k Central Statistical Office (CSO), Ministry of Health (MOH), Tropical Diseases Research Centre (TDRC), University of Zambia, and Macro International Inc. 2009. Zambia Demographic and Health Survey 2007. Calverton, Maryland, USA: CSO and Macro International Inc.Comparison of Maternal Mortality Estimates: Zambia, Bangladesh, Mozambique.

  9. B

    Etiology of hospital mortality in children living in low-and middle-income...

    • borealisdata.ca
    • search.dataone.org
    Updated Jun 12, 2024
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    Teresa B Kortz; Rishi Mediratta; Audrey M Smith; Katie R Nielsen; Asya Agulnik; Stephanie Gordon Rivera; Hailey Reeves; Nicole F O'Brien; Jan Hau Lee; Qalab Abbas; Jonah E Attebery; Tigist Bacha; Emaan G Bhutta; Carter Biewen; Jhon Camacho-Cruz; Alvaro Coronado Munoz; Mary L DeAlmeida; Larko Domeryo Owusu; Yudy Fonseca; Shubhada Hooli; Mara Leimanis-Laurens; Deogratisu Nicholaus Mally; Amanda M McCarthy; Andrew Mutekanga; Carol Pineda; Kenneth E Remy; Sara C. Sanders; Erica Tabor; Adriana Rodrigues Teixeira; Justin Qi Jyuee Want; Niranjan Kissoon; Yemisi Takwoingi; Matthew O Wiens; Adnan Bhutta (2024). Etiology of hospital mortality in children living in low-and middle-income countries: a systematic review and meta-analysis [Dataset]. http://doi.org/10.5683/SP3/2UKUKW
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 12, 2024
    Dataset provided by
    Borealis
    Authors
    Teresa B Kortz; Rishi Mediratta; Audrey M Smith; Katie R Nielsen; Asya Agulnik; Stephanie Gordon Rivera; Hailey Reeves; Nicole F O'Brien; Jan Hau Lee; Qalab Abbas; Jonah E Attebery; Tigist Bacha; Emaan G Bhutta; Carter Biewen; Jhon Camacho-Cruz; Alvaro Coronado Munoz; Mary L DeAlmeida; Larko Domeryo Owusu; Yudy Fonseca; Shubhada Hooli; Mara Leimanis-Laurens; Deogratisu Nicholaus Mally; Amanda M McCarthy; Andrew Mutekanga; Carol Pineda; Kenneth E Remy; Sara C. Sanders; Erica Tabor; Adriana Rodrigues Teixeira; Justin Qi Jyuee Want; Niranjan Kissoon; Yemisi Takwoingi; Matthew O Wiens; Adnan Bhutta
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Dataset funded by
    National Institute of General Medical Sciences
    National Medical Research Council, Singapore
    ational Institute of Allergy and Infectious Diseases
    Fogarty International Center
    Eunice Kennedy Shriver National Institute of Child Health and Human Development
    National Institute for Health Research, Birmingham Biomedical Research Centre of the National Health Services
    American Lung Association
    National Institutes of Health (NIH), the Conquer Cancer Foundation (AA), the National Cancer Institute
    Description

    Background: In 2019, 80% of the 7.4 million global child deaths occurred in low- and middle-income countries (LMICs). Global and regional estimates of cause of hospital death and admission in LMIC children are needed to guide global and local priority setting and resource allocation but are currently lacking. The study objective was to estimate global and regional prevalence for common causes of pediatric hospital mortality and admission in LMICs. Methods: We performed a systematic review and meta-analysis to identify LMIC observational studies published January 1, 2005-February 26, 2021. Eligible studies included: a general pediatric admission population, a cause of admission or death, and total admissions. We excluded studies with data before 2000 or without a full text. Two authors independently screened and extracted data. We performed methodological assessment using domains adapted from the Quality in Prognosis Studies tool. Data were pooled using random-effects models where possible. We reported prevalence as a proportion of cause of death or admission per 1000 admissions with 95% confidence intervals (95%CI). Findings: ur search identified 29,637 texts. After duplicate removal and screening, we analyzed 253 studies representing 21.8 million pediatric hospitalizations in 59 LMICs. All-cause pediatric hospital mortality was 4.1% [95%CI 3.4-4.7%]. The most common causes of mortality (deaths/1000 admissions) were infectious (12 [95%CI 9-14]); respiratory (9 [95%CI 5-13]); and gastrointestinal (9 [95%CI 6-11]). Common causes of admission (cases/1000 admissions) were respiratory (255 [95%CI 231-280]); infectious (214 [95%CI193-234]); and gastrointestinal (166 [95%CI 143-190]). We observed regional variation in estimates. Pediatric hospital mortality remains high in LMICs. Implications: Global child health efforts must include measures to reduce hospital mortality including basic emergency and critical care services tailored to the local disease burden. Resources are urgently needed to promote equity in child health research, support researchers, and collect high-quality data in LMICs to further guide priority setting and resource allocation. NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days. Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at sepsiscolab@bcchr.ca or visit our website.

  10. Rates of death for the leading causes of death in low-income countries in...

    • statista.com
    Updated Aug 23, 2024
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    Statista (2024). Rates of death for the leading causes of death in low-income countries in 2021 [Dataset]. https://www.statista.com/statistics/311934/top-ten-causes-of-death-in-low-income-countries/
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    Dataset updated
    Aug 23, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    Worldwide
    Description

    The leading cause of death in low-income countries worldwide in 2021 was lower respiratory infections, followed by stroke and ischemic heart disease. The death rate from lower respiratory infections that year was 59.4 deaths per 100,000 people. While the death rate from stroke was around 51.6 per 100,000 people. Many low-income countries suffer from health issues not seen in high-income countries, including infectious diseases, malnutrition and neonatal deaths, to name a few. Low-income countries worldwide Low-income countries are defined as those with per gross national incomes (GNI) per capita of 1,045 U.S. dollars or less. A majority of the world’s low-income countries are located in sub-Saharan Africa and South East Asia. Some of the lowest-income countries as of 2023 include Burundi, Sierra Leone, and South Sudan. Low-income countries have different health problems that lead to worse health outcomes. For example, Chad, Lesotho, and Nigeria have some of the lowest life expectancies on the planet. Health issues in low-income countries Low-income countries also tend to have higher rates of HIV/AIDS and other infectious diseases as a consequence of poor health infrastructure and a lack of qualified health workers. Eswatini, Lesotho, and South Africa have some of the highest rates of new HIV infections worldwide. Likewise, tuberculosis, a treatable condition that affects the respiratory system, has high incident rates in lower income countries. Other health issues can be affected by the income of a country as well, including maternal and infant mortality. In 2023, Afghanistan had one of the highest rates of infant mortality rates in the world.

  11. Child mortality in the United States 1800-2020

    • statista.com
    Updated Aug 9, 2024
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    Statista (2024). Child mortality in the United States 1800-2020 [Dataset]. https://www.statista.com/statistics/1041693/united-states-all-time-child-mortality-rate/
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    Dataset updated
    Aug 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    1800 - 2020
    Area covered
    United States
    Description

    The child mortality rate in the United States, for children under the age of five, was 462.9 deaths per thousand births in 1800. This means that for every thousand babies born in 1800, over 46 percent did not make it to their fifth birthday. Over the course of the next 220 years, this number has dropped drastically, and the rate has dropped to its lowest point ever in 2020 where it is just seven deaths per thousand births. Although the child mortality rate has decreased greatly over this 220 year period, there were two occasions where it increased; in the 1870s, as a result of the fourth cholera pandemic, smallpox outbreaks, and yellow fever, and in the late 1910s, due to the Spanish Flu pandemic.

  12. Wallis and Futuna Islands - Health Indicators

    • data.humdata.org
    csv
    Updated May 15, 2025
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    World Health Organization (2025). Wallis and Futuna Islands - Health Indicators [Dataset]. https://data.humdata.org/dataset/who-data-for-wlf
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    csv(3126), csv(1540), csv(38703), csv(143), csv(34999)Available download formats
    Dataset updated
    May 15, 2025
    Dataset provided by
    World Health Organizationhttps://who.int/
    Area covered
    Wallis and Futuna
    Description

    This dataset contains data from WHO's data portal covering the following categories:

    Adolescent, Ageing, Air pollution, Assistive technology, Child, Child mortality, Cross-cutting, Dementia diagnosis, treatment and care, Environment and health, Foodborne Diseases Estimates, Global Dementia Observatory (GDO), Global Health Estimates: Life expectancy and leading causes of death and disability, Global Information System on Alcohol and Health, Global Patient Safety Observatory, Global strategy, HIV, Health financing, Health systems, Health taxes, Health workforce, Hepatitis, Immunization coverage and vaccine-preventable diseases, Malaria, Maternal and newborn, Maternal and reproductive health, Mental health, Neglected tropical diseases, Noncommunicable diseases, Nutrition, Oral Health, Priority health technologies, Resources for Substance Use Disorders, Road Safety, SDG Target 3.8 | Achieve universal health coverage (UHC), Sexually Transmitted Infections, Tobacco control, Tuberculosis, Vaccine-preventable communicable diseases, Violence prevention, Water, sanitation and hygiene (WASH), World Health Statistics.

    For links to individual indicator metadata, see resource descriptions.

  13. M

    Montenegro ME: Number of Death: Under-5

    • ceicdata.com
    Updated Jun 30, 2018
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    CEICdata.com (2018). Montenegro ME: Number of Death: Under-5 [Dataset]. https://www.ceicdata.com/en/montenegro/health-statistics
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    Dataset updated
    Jun 30, 2018
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2005 - Dec 1, 2016
    Area covered
    Montenegro
    Description

    ME: Number of Death: Under-5 data was reported at 25.000 Person in 2017. This records a decrease from the previous number of 27.000 Person for 2016. ME: Number of Death: Under-5 data is updated yearly, averaging 101.000 Person from Dec 1989 (Median) to 2017, with 29 observations. The data reached an all-time high of 184.000 Person in 1989 and a record low of 25.000 Person in 2017. ME: Number of Death: Under-5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Montenegro – Table ME.World Bank: Health Statistics. Number of children dying before reaching age five.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum;

  14. o

    Global, Regional, And National Under-5 Mortality, Adult Mortality,...

    • explore.openaire.eu
    Updated Jan 1, 2017
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    Haidong Wang; Amanuel Alemu Abajobir; Kalkidan Hassen Abate; Burcu Küçük Biçer (2017). Global, Regional, And National Under-5 Mortality, Adult Mortality, Age-Specific Mortality, And Life Expectancy, 1970-2016: A Systematic Analysis For The Global Burden Of Disease Study 2016 [Dataset]. https://explore.openaire.eu/search/other?orpId=od_4268::9ad8f2b350836bbb05bbd2b5e29d6abb
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    Dataset updated
    Jan 1, 2017
    Authors
    Haidong Wang; Amanuel Alemu Abajobir; Kalkidan Hassen Abate; Burcu Küçük Biçer
    Description

    Background Detailed assessments of mortality patterns, particularly age-specific mortality, represent a crucial input that enables health systems to target interventions to specific populations. Understanding how all-cause mortality has changed with respect to development status can identify exemplars for best practice. To accomplish this, the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) estimated age-specific and sex-specific all-cause mortality between 1970 and 2016 for 195 countries and territories and at the subnational level for the five countries with a population greater than 200 million in 2016. Methods We have evaluated how well civil registration systems captured deaths using a set of demographic methods called death distribution methods for adults and from consideration of survey and census data for children younger than 5 years. We generated an overall assessment of completeness of registration of deaths by dividing registered deaths in each location-year by our estimate of all-age deaths generated from our overall estimation process. For 163 locations, including subnational units in countries with a population greater than 200 million with complete vital registration (VR) systems, our estimates were largely driven by the observed data, with corrections for small fluctuations in numbers and estimation for recent years where there were lags in data reporting (lags were variable by location, generally between 1 year and 6 years). For other locations, we took advantage of different data sources available to measure under-5 mortality rates (U5MR) using complete birth histories, summary birth histories, and incomplete VR with adjustments; we measured adult mortality rate (the probability of death in individuals aged 15-60 years) using adjusted incomplete VR, sibling histories, and household death recall. We used the U5MR and adult mortality rate, together with crude death rate due to HIV in the GBD model life table system, to estimate age-specific and sex-specific death rates for each location-year. Using various international databases, we identified fatal discontinuities, which we defined as increases in the death rate of more than one death per million, resulting from conflict and terrorism, natural disasters, major transport or technological accidents, and a subset of epidemic infectious diseases; these were added to estimates in the relevant years. In 47 countries with an identified peak adult prevalence for HIV/AIDS of more than 0.5% and where VR systems were less than 65% complete, we informed our estimates of age-sex-specific mortality using the Estimation and Projection Package (EPP)-Spectrum model fitted to national HIV/AIDS prevalence surveys and antenatal clinic serosurveillance systems. We estimated stillbirths, early neonatal, late neonatal, and childhood mortality using both survey and VR data in spatiotemporal Gaussian process regression models. We estimated abridged life tables for all location-years using age-specific death rates. We grouped locations into development quintiles based on the Sociodemographic Index (SDI) and analysed mortality trends by quintile. Using spline regression, we estimated the expected mortality rate for each age-sex group as a function of SDI. We identified countries with higher life expectancy than expected by comparing observed life expectancy to anticipated life expectancy on the basis of development status alone. Findings Completeness in the registration of deaths increased from 28% in 1970 to a peak of 45% in 2013; completeness was lower after 2013 because of lags in reporting. Total deaths in children younger than 5 years decreased from 1970 to 2016, and slower decreases occurred at ages 5-24 years. By contrast, numbers of adult deaths increased in each 5-year age bracket above the age of 25 years. The distribution of annualised rates of change in age-specific mortality rate differed over the period 2000 to 2016 compared with earlier decades: increasing annualised rates of change were less frequent, although rising annualised rates of change still occurred in some locations, particularly for adolescent and younger adult age groups. Rates of stillbirths and under-5 mortality both decreased globally from 1970. Evidence for global convergence of death rates was mixed; although the absolute difference between age-standardised death rates narrowed between countries at the lowest and highest levels of SDI, the ratio of these death rates-a measure of relative inequality-increased slightly. There was a strong shift between 1970 and 2016 toward higher life expectancy, most noticeably at higher levels of SDI. Among countries with populations greater than 1 million in 2016, life expectancy at birth was highest for women in Japan, at 86.9 years (95% UI 86.7-87.2), and for men in Singapore, at 81.3 years (78.8-83.7) in 2016. Male life expectancy was generally lower than female life expectancy between 1970 and 2016, and the gap be...

  15. f

    Aetiology-Specific Estimates of the Global and Regional Incidence and...

    • plos.figshare.com
    docx
    Updated May 30, 2023
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    Sara M. Pires; Christa L. Fischer-Walker; Claudio F. Lanata; Brecht Devleesschauwer; Aron J. Hall; Martyn D. Kirk; Ana S. R. Duarte; Robert E. Black; Frederick J. Angulo (2023). Aetiology-Specific Estimates of the Global and Regional Incidence and Mortality of Diarrhoeal Diseases Commonly Transmitted through Food [Dataset]. http://doi.org/10.1371/journal.pone.0142927
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    docxAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Sara M. Pires; Christa L. Fischer-Walker; Claudio F. Lanata; Brecht Devleesschauwer; Aron J. Hall; Martyn D. Kirk; Ana S. R. Duarte; Robert E. Black; Frederick J. Angulo
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    BackgroundDiarrhoeal diseases are major contributors to the global burden of disease, particularly in children. However, comprehensive estimates of the incidence and mortality due to specific aetiologies of diarrhoeal diseases are not available. The objective of this study is to provide estimates of the global and regional incidence and mortality of diarrhoeal diseases caused by nine pathogens that are commonly transmitted through foods.Methods and FindingsWe abstracted data from systematic reviews and, depending on the overall mortality rates of the country, applied either a national incidence estimate approach or a modified Child Health Epidemiology Reference Group (CHERG) approach to estimate the aetiology-specific incidence and mortality of diarrhoeal diseases, by age and region. The nine diarrhoeal diseases assessed caused an estimated 1.8 billion (95% uncertainty interval [UI] 1.1–3.3 billion) cases and 599,000 (95% UI 472,000–802,000) deaths worldwide in 2010. The largest number of cases were caused by norovirus (677 million; 95% UI 468–1,153 million), enterotoxigenic Escherichia coli (ETEC) (233 million; 95% UI 154–380 million), Shigella spp. (188 million; 95% UI 94–379 million) and Giardia lamblia (179 million; 95% UI 125–263); the largest number of deaths were caused by norovirus (213,515; 95% UI 171,783–266,561), enteropathogenic E. coli (121,455; 95% UI 103,657–143,348), ETEC (73,041; 95% UI 55,474–96,984) and Shigella (64,993; 95% UI 48,966–92,357). There were marked regional differences in incidence and mortality for these nine diseases. Nearly 40% of cases and 43% of deaths caused by these nine diarrhoeal diseases occurred in children under five years of age.ConclusionsDiarrhoeal diseases caused by these nine pathogens are responsible for a large disease burden, particularly in children. These aetiology-specific burden estimates can inform efforts to reduce diarrhoeal diseases caused by these nine pathogens commonly transmitted through foods.

  16. f

    Effect of Investment in Malaria Control on Child Mortality in Sub-Saharan...

    • plos.figshare.com
    doc
    Updated Jun 2, 2023
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    Yoko Akachi; Rifat Atun (2023). Effect of Investment in Malaria Control on Child Mortality in Sub-Saharan Africa in 2002–2008 [Dataset]. http://doi.org/10.1371/journal.pone.0021309
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    docAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Yoko Akachi; Rifat Atun
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Sub-Saharan Africa
    Description

    BackgroundAround 8.8 million children under-five die each year, mostly due to infectious diseases, including malaria that accounts for 16% of deaths in Africa, but the impact of international financing of malaria control on under-five mortality in sub-Saharan Africa has not been examined. Methods and FindingsWe combined multiple data sources and used panel data regression analysis to study the relationship among investment, service delivery/intervention coverage, and impact on child health by observing changes in 34 sub-Saharan African countries over 2002–2008. We used Lives Saved Tool to estimate the number of lives saved from coverage increase of insecticide-treated nets (ITNs)/indoor residual spraying (IRS). As an indicator of outcome, we also used under-five mortality rate. Global Fund investments comprised more than 70% of the Official Development Assistance (ODA) for malaria control in 34 countries. Each $1 million ODA for malaria enabled distribution of 50,478 ITNs [95%CI: 37,774–63,182] in the disbursement year. 1,000 additional ITNs distributed saved 0.625 lives [95%CI: 0.369–0.881]. Cumulatively Global Fund investments that increased ITN/IRS coverage in 2002–2008 prevented an estimated 240,000 deaths. Countries with higher malaria burden received less ODA disbursement per person-at-risk compared to lower-burden countries ($3.90 vs. $7.05). Increased ITN/IRS coverage in high-burden countries led to 3,575 lives saved per 1 million children, as compared with 914 lives in lower-burden countries. Impact of ITN/IRS coverage on under-five mortality was significant among major child health interventions such as immunisation showing that 10% increase in households with ITN/IRS would reduce 1.5 [95%CI: 0.3–2.8] child deaths per 1000 live births. ConclusionsAlong with other key child survival interventions, increased ITNs/IRS coverage has significantly contributed to child mortality reduction since 2002. ITN/IRS scale-up can be more efficiently prioritized to countries where malaria is a major cause of child deaths to save greater number of lives with available resources.

  17. w

    Demographic and Health Survey 2006 - Nepal

    • microdata.worldbank.org
    • dev.ihsn.org
    • +2more
    Updated Jun 16, 2017
    + more versions
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    New ERA (2017). Demographic and Health Survey 2006 - Nepal [Dataset]. https://microdata.worldbank.org/index.php/catalog/1465
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    Dataset updated
    Jun 16, 2017
    Dataset authored and provided by
    New ERA
    Time period covered
    2006
    Area covered
    Nepal
    Description

    Abstract

    The principal objective of the 2006 Nepal Demographic and Health Survey (NDHS) is to provide current and reliable data on fertility and family planning behavior, child mortality, adult and maternal mortality, children’s nutritional status, the utilization of maternal and child health services, and knowledge of HIV/AIDS. For the first time, the 2006 NDHS conducted anemia testing at the household level for the country as a whole to provide information on the prevalence of anemia at the population level. The specific objectives of the survey are to:

    • collect data at the national level which will allow the calculation of key demographic rates;
    • analyze the direct and indirect factors which determine the level and trends of fertility;
    • measure the level of contraceptive knowledge and practice among women and men by method, urban-rural residence and region,
    • collect high-quality data on family health including immunization coverage among children, prevalence and treatment of diarrhea and other diseases among children under five, and maternity care indicators including antenatal visits, assistance at delivery, and postnatal care;
    • collect data on infant and child mortality, and maternal and adult mortality;
    • obtain data on child feeding practices including breastfeeding, and collect anthropometric measures to use in assessing the nutritional status of women and children;
    • collect data on knowledge and attitudes of women and men about sexually transmitted infections and HIV/AIDS and evaluate patterns of recent behavior regarding condom use;
    • conduct hemoglobin testing on women age 15-49 and children age 6-59 months in the households selected for the survey to provide information on the prevalence of anemia among women in the reproductive ages and young children.

    This information is essential for informed policy decisions, planning, monitoring, and evaluation of programs on health in general and reproductive health in particular at both the national and regional levels. A long-term objective of the survey is to strengthen the technical capacity of government organizations to plan, conduct, process, and analyze data from complex national population and health surveys. Moreover, the 2006 NDHS provides national, regional and subregional estimates on population and health that are comparable to data collected in similar surveys in other developing countries. The first Demographic and Health Survey (DHS) in Nepal was the 1996 Nepal Family Health Survey (NFHS) conducted as part of the worldwide DHS program, and was followed five years later by the 2001 Nepal Demographic and Health Survey (NDHS). Data from the 2006 NDHS survey, the third such survey, allow for comparison of information gathered over a longer period of time and add to the vast and growing international database on demographic and health variables.

    Wherever possible, the 2006 NDHS data are compared with data from the two earlier DHS surveys—the 2001 NDHS and the 1996 NFHS—which also sampled women age 15-49. Additionally, men age 15-59 were interviewed in the 2001 NDHS and the 2006 NDHS to provide comparable data for men over the last five years.

    Geographic coverage

    National

    Analysis unit

    • Household
    • Children under five years
    • Women age 15-49
    • Men age 15-59

    Kind of data

    Sample survey data

    Sampling procedure

    The primary focus of the 2006 NDHS was to provide estimates of key population and health indicators, including fertility and mortality rates, for the country as a whole and for urban and rural areas separately. In addition, the sample was designed to provide estimates of most key indicators for the 13 domains obtained by cross-classifying the three ecological zones (mountain, hill and terai) with the five development regions (East, Central, West, Mid-west, and Far-west).

    The 2006 NDHS used the sampling frame provided by the list of census enumeration areas with population and household information from the 2001 Population Census. Each of the 75 districts in Nepal is subdivided into Village Development Committees (VDCs), and each VDC into wards. The primary sampling unit (PSU) for the 2006 NDHS is a ward, subward, or group of wards in rural areas, and subwards in urban areas. In rural areas, the ward is small enough in size for a complete household listing, but in urban areas the ward is large. It was therefore necessary to subdivide each urban ward into subwards. Information on the subdivision of the urban wards was obtained from the updated Living Standards Measurement Survey. The sampling frame is representative of 96 percent of the noninstitutional population.

    The sample for the survey is based on a two-stage, stratified, nationally representative sample of households. At the first stage of sampling, 260 PSUs (82 in urban areas and 178 in rural areas) were selected using systematic sampling with probability proportional to size. A complete household listing operation was then carried out in all the selected PSUs to provide a sampling frame for the second stage selection of households. At the second stage of sampling, systematic samples of about 30 households per PSU on average in urban areas and about 36 households per PSU on average in rural areas were selected in all the regions, in order to provide statistically reliable estimates of key demographic and health variables. However, since Nepal is predominantly rural, in order to obtain statistically reliable estimates for urban areas, it was necessary to oversample the urban areas. As such, the total sample is weighted and a final weighting procedure was applied to provide estimates for the different domains, and for the urban and rural areas of the country as a whole.

    The survey was designed to obtain completed interviews of 8,600 women age 15-49. In addition, males age 15-59 in every second household were interviewed. To take nonresponse into account, a total of 9,036 households nationwide were selected.

    Mode of data collection

    Face-to-face

    Research instrument

    Three questionnaires were administered for the 2006 NDHS: the Household Questionnaire, the Women’s Questionnaire, and the Men’s Questionnaire. These questionnaires were adapted to reflect the population and health issues relevant to Nepal at a series of meetings with various stakeholders from government ministries and agencies, NGOs and international donors. The final draft of the questionnaires was discussed at a questionnaire design workshop organized by MOHP in September 2005 in Kathmandu. The survey questionnaires were then translated into the three main local languages—Nepali, Bhojpuri and Maithili and pretested from November 16 to December 13, 2005.

    The Household Questionnaire was used to list all the usual members and visitors in the selected households and to identify women and men who were eligible for the individual interview. Some basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. For children under age 18, the survival status of the parents was determined. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor of the house, ownership of various durable goods, and ownership of mosquito nets. Additionally, the Household Questionnaire was used to record height, weight, and hemoglobin measurements of women age 15-49 and children age 6-59 months. The Women’s Questionnaire was used to collect information from all women age 15-49.

    These women were asked questions on the following topics: - respondent’s characteristics such as education, residential history, media exposure, - pregnancy history, childhood mortality, - knowledge and use of family planning methods, - fertility preferences, - antenatal, delivery, and postnatal care, - breastfeeding and infant feeding practices, - immunization and childhood illnesses, - marriage and sexual activity, - woman’s work and husband’s background characteristics, - awareness and behavior regarding AIDS and other sexually transmitted infections (STIs), and - maternal mortality.

    The Men’s Questionnaire was administered to all men age 15-59 living in every second household in the 2006 NDHS sample. The Men’s Questionnaire collected much of the same information found in the Women’s Questionnaire, but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health or nutrition.

    In addition, the Verbal Autopsy Module into the causes of under-five mortality was administered to all women age 15-49 (and anyone else who remembered the circumstances surrounding the reported death) who reported a death or stillbirth in the five years preceding the survey to children under five years of age.

    Response rate

    A total of 9,036 households were selected, of which 8,742 were found to be occupied during data collection. Of these existing households, 8,707 were successfully interviewed, giving a household response rate of nearly 100 percent.

    In the selected households, 10,973 women were identified as eligible for the individual interview. Interviews were completed for 10,793 women, yielding a response rate of 98 percent. Of the 4,582 eligible men identified in the selected subsample of households, 4,397 were successfully interviewed, giving a 96 percent response rate. Response rates were higher in rural than urban areas, especially for eligible men.

    Sampling error estimates

    The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2)

  18. M

    Pakistan Infant Mortality Rate 1950-2025

    • macrotrends.net
    csv
    Updated Apr 30, 2025
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    MACROTRENDS (2025). Pakistan Infant Mortality Rate 1950-2025 [Dataset]. https://www.macrotrends.net/global-metrics/countries/PAK/pakistan/infant-mortality-rate
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    csvAvailable download formats
    Dataset updated
    Apr 30, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1950 - May 5, 2025
    Area covered
    Pakistan
    Description
    Pakistan infant mortality rate for 2025 is 53.54, a 2.05% decline from 2024.
    <ul style='margin-top:20px;'>
    
    <li>Pakistan infant mortality rate for 2024 was <strong>54.66</strong>, a <strong>2.01% decline</strong> from 2023.</li>
    <li>Pakistan infant mortality rate for 2023 was <strong>55.78</strong>, a <strong>1.95% decline</strong> from 2022.</li>
    <li>Pakistan infant mortality rate for 2022 was <strong>56.89</strong>, a <strong>1.91% decline</strong> from 2021.</li>
    </ul>Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 live births in a given year.
    
  19. Countries with highest mortality rate among children aged under five 2021

    • statista.com
    • ai-chatbox.pro
    Updated May 22, 2024
    + more versions
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    Statista (2024). Countries with highest mortality rate among children aged under five 2021 [Dataset]. https://www.statista.com/statistics/281580/countries-with-highest-mortality-rate-among-children-aged-under-five/
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    Dataset updated
    May 22, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    Worldwide
    Description

    In 2021, Niger had the highest mortality rate among children aged under five years, with an average of around 115 children dying, per one thousand live births, under five years of age. This statistic shows the countries with the highest mortality rate among children aged under five years as of 2021.

  20. f

    Table 2_Global, regional, and national epidemiology of congenital heart...

    • figshare.com
    • frontiersin.figshare.com
    docx
    Updated May 16, 2025
    + more versions
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    Jiaoli Xu; Qinhong Li; Lili Deng; Jingxuan Xiong; Zugen Cheng; Caixia Ye (2025). Table 2_Global, regional, and national epidemiology of congenital heart disease in children from 1990 to 2021.docx [Dataset]. http://doi.org/10.3389/fcvm.2025.1522644.s002
    Explore at:
    docxAvailable download formats
    Dataset updated
    May 16, 2025
    Dataset provided by
    Frontiers
    Authors
    Jiaoli Xu; Qinhong Li; Lili Deng; Jingxuan Xiong; Zugen Cheng; Caixia Ye
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    BackgroundCongenital heart disease (CHD) is a leading cause of morbidity and mortality in children globally, with significant variations in outcomes across different regions.ObjectiveTo provide comprehensive estimates of CHD prevalence, mortality, and disability-adjusted life years (DALYs) among children under five years old globally from 1990 to 2021.MethodsUsing data from the Global Burden of Disease (GBD) study, trends in CHD prevalence, mortality, and DALYs were analyzed. Mortality estimates were generated using Cause of Death Ensemble modeling, while prevalence and DALYs were estimated using DisMod-MR 2.1. Systematic literature reviews informed the disability estimates.ResultsIn 2021, the global prevalence of CHD in children under five years was over 4.18 million, reflecting a 3.4% increase since 1990. CHD-associated mortality decreased by 56.2%, and DALYs declined by 55.7% from 1990 to 2021. Low and low-middle Socio-Demographic Index (SDI) regions experienced the highest prevalence and mortality rates. South Asia had the highest number of CHD cases, while Oceania had the highest mortality and DALY rates. India had the highest number of cases, while Afghanistan had the highest mortality and DALY rates.ConclusionsCHD remains a significant global health challenge, with substantial disparities in disease burden across regions. Targeted interventions are needed to improve survival and quality of life, particularly in high-burden areas.

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Statista (2025). Countries with the highest infant mortality rate 2024 [Dataset]. https://www.statista.com/statistics/264714/countries-with-the-highest-infant-mortality-rate/
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Countries with the highest infant mortality rate 2024

Explore at:
Dataset updated
Apr 16, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2023
Area covered
Worldwide
Description

This statistic shows the 20 countries* with the highest infant mortality rate in 2024. An estimated 101.3 infants per 1,000 live births died in the first year of life in Afghanistan in 2024. Infant and child mortality Infant mortality usually refers to the death of children younger than one year. Child mortality, which is often used synonymously with infant mortality, is the death of children younger than five. Among the main causes are pneumonia, diarrhea – which causes dehydration – and infections in newborns, with malnutrition also posing a severe problem. As can be seen above, most countries with a high infant mortality rate are developing countries or emerging countries, most of which are located in Africa. Good health care and hygiene are crucial in reducing child mortality; among the countries with the lowest infant mortality rate are exclusively developed countries, whose inhabitants usually have access to clean water and comprehensive health care. Access to vaccinations, antibiotics and a balanced nutrition also help reducing child mortality in these regions. In some countries, infants are killed if they turn out to be of a certain gender. India, for example, is known as a country where a lot of girls are aborted or killed right after birth, as they are considered to be too expensive for poorer families, who traditionally have to pay a costly dowry on the girl’s wedding day. Interestingly, the global mortality rate among boys is higher than that for girls, which could be due to the fact that more male infants are actually born than female ones. Other theories include a stronger immune system in girls, or more premature births among boys.

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