57 datasets found
  1. f

    Threshold Levels of Infant and Under-Five Mortality for Crossover between...

    • plos.figshare.com
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    Updated Jun 1, 2023
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    Manisha Dubey; Usha Ram; Faujdar Ram (2023). Threshold Levels of Infant and Under-Five Mortality for Crossover between Life Expectancies at Ages Zero, One and Five in India: A Decomposition Analysis [Dataset]. http://doi.org/10.1371/journal.pone.0143764
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    pdfAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Manisha Dubey; Usha Ram; Faujdar Ram
    License

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

    Description

    ObjectivesUnder the prevailing conditions of imbalanced life table and historic gender discrimination in India, our study examines crossover between life expectancies at ages zero, one and five years for India and quantifies the relative share of infant and under-five mortality towards this crossover.MethodsWe estimate threshold levels of infant and under-five mortality required for crossover using age specific death rates during 1981–2009 for 16 Indian states by sex (comprising of India’s 90% population in 2011). Kitagawa decomposition equations were used to analyse relative share of infant and under-five mortality towards crossover.FindingsIndia experienced crossover between life expectancies at ages zero and five in 2004 for menand in 2009 for women; eleven and nine Indian states have experienced this crossover for men and women, respectively. Men usually experienced crossover four years earlier than the women. Improvements in mortality below ages five have mostly contributed towards this crossover. Life expectancy at age one exceeds that at age zero for both men and women in India except for Kerala (the only state to experience this crossover in 2000 for men and 1999 for women).ConclusionsFor India, using life expectancy at age zero and under-five mortality rate together may be more meaningful to measure overall health of its people until the crossover. Delayed crossover for women, despite higher life expectancy at birth than for men reiterates that Indian women are still disadvantaged and hence use of life expectancies at ages zero, one and five become important for India. Greater programmatic efforts to control leading causes of death during the first month and 1–59 months in high child mortality areas can help India to attain this crossover early.

  2. Life expectancy in Africa from 1950 to 2020

    • statista.com
    • ai-chatbox.pro
    Updated Aug 12, 2024
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    Statista (2024). Life expectancy in Africa from 1950 to 2020 [Dataset]. https://www.statista.com/statistics/1076271/life-expectancy-africa-historical/
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    Dataset updated
    Aug 12, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Africa
    Description

    Life expectancy from birth in Africa was just over 36 years in 1950. As a wave of independence movements and decolonization swept the continent between the 1950s and early 1970s, life expectancy rose greatly in Africa; particularly due to improvements and control over medical services, better sanitation and the widespread promotion of vaccinations in the country resulted in a sharp decrease in child mortality; one of the most significant reasons for Africa’s low life expectancy rates. Life expectancy in the continent would continue to steadily increase for much of the second half of the 20th century, however, life expectancy would flatline at around 52 years in the latter half of the 1980s, as the HIV/AIDS epidemic quickly grew to become one of the leading causes of death in the continent. After hovering around the low-fifties in the 1980s to and 1990s, life expectancy would begin to rise again at the turn of the millennium, and is estimated to be over 64 years in 2020.

  3. f

    Under-five mortality rate convergence results.

    • plos.figshare.com
    xls
    Updated Oct 15, 2024
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    Ariane Ephemia Ndzignat Mouteyica; Nicholas Nwanyek Ngepah (2024). Under-five mortality rate convergence results. [Dataset]. http://doi.org/10.1371/journal.pone.0312089.t005
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    xlsAvailable download formats
    Dataset updated
    Oct 15, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Ariane Ephemia Ndzignat Mouteyica; Nicholas Nwanyek Ngepah
    License

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

    Description

    Progress in health outcomes across Africa has been uneven, marked by significant disparities among countries, which not only challenges the global health security but impede progress towards achieving the United Nations’ Sustainable Development Goals 3 and 10 (SDG 3 and SDG 10) and Universal Health Coverage (UHC). This paper examines the progress of African countries in reducing intra-country health outcome disparities between 2000 and 2019. In other words, the paper investigates the convergence hypothesis in health outcome using a panel data from 40 African countries. Data were sourced from the World Development Indicators, the World Governance Indicators, and the World Health Organization database. Employing a non-linear dynamic factor model, the study focused on three health outcomes: infant mortality rate, under-5 mortality rate, and life expectancy at birth. The findings indicate that while the hypothesis of convergence is not supported for the selected countries, evidence of convergence clubs is observed for the three health outcome variables. The paper further examine the factors contributing to club formation by using the marginal effects of the ordered logit regression model. The findings indicate that the overall impact of the control variables aligns with existing research. Moreover, governance quality and domestic government health expenditure emerge as significant determinants influencing the probability of membership in specific clubs for the child mortality rate models. In the life expectancy model, governance quality significantly drives club formation. The results suggest that there is a need for common health policies for the different convergence clubs, while country-specific policies should be implemented for the divergent countries. For instance, policies and strategies promoting health prioritization in national budget allocation and reallocation should be encouraged within each final club. Efforts to promote good governance policies by emphasizing anti-corruption measures and government effectiveness should also be encouraged. Moreover, there is a need to implement regional monitoring mechanisms to ensure progress in meeting health commitments, while prioritizing urbanization plans in countries with poorer health outcomes to enhance sanitation access.

  4. f

    Life expectancy at birth convergence results.

    • plos.figshare.com
    xls
    Updated Oct 15, 2024
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    Ariane Ephemia Ndzignat Mouteyica; Nicholas Nwanyek Ngepah (2024). Life expectancy at birth convergence results. [Dataset]. http://doi.org/10.1371/journal.pone.0312089.t006
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    xlsAvailable download formats
    Dataset updated
    Oct 15, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Ariane Ephemia Ndzignat Mouteyica; Nicholas Nwanyek Ngepah
    License

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

    Description

    Progress in health outcomes across Africa has been uneven, marked by significant disparities among countries, which not only challenges the global health security but impede progress towards achieving the United Nations’ Sustainable Development Goals 3 and 10 (SDG 3 and SDG 10) and Universal Health Coverage (UHC). This paper examines the progress of African countries in reducing intra-country health outcome disparities between 2000 and 2019. In other words, the paper investigates the convergence hypothesis in health outcome using a panel data from 40 African countries. Data were sourced from the World Development Indicators, the World Governance Indicators, and the World Health Organization database. Employing a non-linear dynamic factor model, the study focused on three health outcomes: infant mortality rate, under-5 mortality rate, and life expectancy at birth. The findings indicate that while the hypothesis of convergence is not supported for the selected countries, evidence of convergence clubs is observed for the three health outcome variables. The paper further examine the factors contributing to club formation by using the marginal effects of the ordered logit regression model. The findings indicate that the overall impact of the control variables aligns with existing research. Moreover, governance quality and domestic government health expenditure emerge as significant determinants influencing the probability of membership in specific clubs for the child mortality rate models. In the life expectancy model, governance quality significantly drives club formation. The results suggest that there is a need for common health policies for the different convergence clubs, while country-specific policies should be implemented for the divergent countries. For instance, policies and strategies promoting health prioritization in national budget allocation and reallocation should be encouraged within each final club. Efforts to promote good governance policies by emphasizing anti-corruption measures and government effectiveness should also be encouraged. Moreover, there is a need to implement regional monitoring mechanisms to ensure progress in meeting health commitments, while prioritizing urbanization plans in countries with poorer health outcomes to enhance sanitation access.

  5. m

    Data for: The Role of Institutions in Environment-Health Outcomes Nexus:...

    • data.mendeley.com
    Updated Jun 18, 2020
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    Olorunfemi Alimi (2020). Data for: The Role of Institutions in Environment-Health Outcomes Nexus: Empirical Evidence from Sub-Saharan Africa [Dataset]. http://doi.org/10.17632/wj5wngc52s.1
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    Dataset updated
    Jun 18, 2020
    Authors
    Olorunfemi Alimi
    License

    Attribution-NonCommercial 3.0 (CC BY-NC 3.0)https://creativecommons.org/licenses/by-nc/3.0/
    License information was derived automatically

    Area covered
    Sub-Saharan Africa, Africa
    Description

    lep Life expectancy at birth, total (years) lepf Life expectancy at birth, female (years) lepm Life expectancy at birth, male (years) mmat Maternal mortality ratio (modeled estimate, per 100,000 live births) minf Mortality rate, infant (per 1,000 live births) mun5 Mortality rate, under-5 (per 1,000 live births) hep Current health expenditure per capita, PPP (current international $) ghep Domestic general government health expenditure per capita, PPP (current international $) phep Domestic private health expenditure per capita, PPP (current international $) hout Health outcomes co2 Carbon emission kt per capita ecft Ecological footprint ccn Control of Corruption: Estimate ge Government Effectiveness: Estimate rqv Regulatory Quality: Estimate insq Institutional Quality

  6. f

    Descriptive statistics of variables of the full sample.

    • plos.figshare.com
    xls
    Updated Oct 15, 2024
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    Ariane Ephemia Ndzignat Mouteyica; Nicholas Nwanyek Ngepah (2024). Descriptive statistics of variables of the full sample. [Dataset]. http://doi.org/10.1371/journal.pone.0312089.t003
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    xlsAvailable download formats
    Dataset updated
    Oct 15, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Ariane Ephemia Ndzignat Mouteyica; Nicholas Nwanyek Ngepah
    License

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

    Description

    Descriptive statistics of variables of the full sample.

  7. Fertility rate in Hungary 2023

    • statista.com
    Updated Mar 15, 2025
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    Statista (2025). Fertility rate in Hungary 2023 [Dataset]. https://www.statista.com/statistics/332502/fertility-rate-in-hungary/
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    Dataset updated
    Mar 15, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Hungary
    Description

    The total fertility rate in Hungary decreased to 1.51 children per woman compared to the previous year. Nevertheless, the last two years recorded a significantly higher fertility rate than the preceding years.The total fertility rate is the average number of children that a woman of childbearing age (generally considered 15 to 44 years) is expected to have throughout her reproductive years. Unlike birth rates, which are based on the actual number of live births in a given population, fertility rates are estimates (similar to life expectancy) that apply to a hypothetical woman, as they assume that current patterns in age-specific fertility will remain constant throughout her reproductive years.Find more statistics on other topics about Hungary with key insights such as infant mortality rate, total life expectancy at birth, and death rate.

  8. H

    ASSESSING THE DEVELOPMENTAL EFFECTS OF ABORTION LIBERALIZATION IN SUB-SAHARA...

    • dataverse.harvard.edu
    Updated Mar 8, 2025
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    Percy Taabazuing; Komla Koumi (2025). ASSESSING THE DEVELOPMENTAL EFFECTS OF ABORTION LIBERALIZATION IN SUB-SAHARA AFRICA: THE CASE OF MOZAMBIQUE [Dataset]. http://doi.org/10.7910/DVN/ZUQU5Z
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 8, 2025
    Dataset provided by
    Harvard Dataverse
    Authors
    Percy Taabazuing; Komla Koumi
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Mozambique, Africa, Sub-Saharan Africa
    Description

    This dataset contains empirical data used in the study that examined the impact of abortion liberalization in Mozambique on key health indicators and its immense implications for economic growth and development. It includes variables such as adolescent fertility, fertility rates, life expectancy, infant mortality, and adult female mortality, along with relevant control variables covering the period from 1997 to 2020. The dataset also includes synthetic control estimates used to construct a counterfactual Mozambique, derived from a pool of Sub-Saharan African countries that did not liberalize abortion during this timeframe. The data was solely sourced from the World Bank Development Indicators.

  9. Crude birth rate in Gambia 2013-2023

    • statista.com
    • ai-chatbox.pro
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    Statista (2025). Crude birth rate in Gambia 2013-2023 [Dataset]. https://www.statista.com/statistics/976904/crude-birth-rate-in-gambia/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    The Gambia
    Description

    In 2023, the crude birth rate in Gambia remained nearly unchanged at around 30.43 live births per 1,000 inhabitants. But still, the rate reached its lowest value of the observation period in 2023. The crude birth rate is the annual number of live births in a given population, expressed per 1,000 people. When looked at in unison with the crude death rate, the rate of natural increase can be determined.Find more statistics on other topics about Gambia with key insights such as total fertility rate, infant mortality rate, and total life expectancy at birth.

  10. Countries with the highest fertility rates 2025

    • statista.com
    • ai-chatbox.pro
    Updated Apr 3, 2025
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    Statista (2025). Countries with the highest fertility rates 2025 [Dataset]. https://www.statista.com/statistics/262884/countries-with-the-highest-fertility-rates/
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    Dataset updated
    Apr 3, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Worldwide
    Description

    In 2025, there are six countries, all in Sub-Saharan Africa, where the average woman of childbearing age can expect to have between 5-6 children throughout their lifetime. In fact, of the 20 countries in the world with the highest fertility rates, Afghanistan and Yemen are the only countries not found in Sub-Saharan Africa. High fertility rates in Africa With a fertility rate of almost six children per woman, Chad is the country with the highest fertility rate in the world. Population growth in Chad is among the highest in the world. Lack of healthcare access, as well as food instability, political instability, and climate change, are all exacerbating conditions that keep Chad's infant mortality rates high, which is generally the driver behind high fertility rates. This situation is common across much of the continent, and, although there has been considerable progress in recent decades, development in Sub-Saharan Africa is not moving as quickly as it did in other regions. Demographic transition While these countries have the highest fertility rates in the world, their rates are all on a generally downward trajectory due to a phenomenon known as the demographic transition. The third stage (of five) of this transition sees birth rates drop in response to decreased infant and child mortality, as families no longer feel the need to compensate for lost children. Eventually, fertility rates fall below replacement level (approximately 2.1 children per woman), which eventually leads to natural population decline once life expectancy plateaus. In some of the most developed countries today, low fertility rates are creating severe econoic and societal challenges as workforces are shrinking while aging populations are placin a greater burden on both public and personal resources.

  11. f

    Principal component analysis of governance indicators.

    • plos.figshare.com
    xls
    Updated Oct 15, 2024
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    Ariane Ephemia Ndzignat Mouteyica; Nicholas Nwanyek Ngepah (2024). Principal component analysis of governance indicators. [Dataset]. http://doi.org/10.1371/journal.pone.0312089.t002
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    xlsAvailable download formats
    Dataset updated
    Oct 15, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Ariane Ephemia Ndzignat Mouteyica; Nicholas Nwanyek Ngepah
    License

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

    Description

    Principal component analysis of governance indicators.

  12. Deeply phenotyped sepsis patients within hospital: onset, treatments &...

    • healthdatagateway.org
    unknown
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    "This work was supported by PIONEER, the Health Data Research Hub in acute care". If publishing using PIONEER overarching ethics, state "This research was conducted under the ethical approvals of PIONEER, a Health data research hub in acute care (East Midlands – Derby Research ethics committee, reference 20/EM/0158)"., Deeply phenotyped sepsis patients within hospital: onset, treatments & outcomes [Dataset]. https://healthdatagateway.org/en/dataset/155
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    unknownAvailable download formats
    Dataset provided by
    Health Data Research Uk
    Authors
    "This work was supported by PIONEER, the Health Data Research Hub in acute care". If publishing using PIONEER overarching ethics, state "This research was conducted under the ethical approvals of PIONEER, a Health data research hub in acute care (East Midlands – Derby Research ethics committee, reference 20/EM/0158)".
    License

    https://www.pioneerdatahub.co.uk/data/data-request-process/https://www.pioneerdatahub.co.uk/data/data-request-process/

    Description

    Deeply phenotyped sepsis patients within hospital: onset, treatments & outcomes

    Sepsis is life-threatening organ dysfunction due to a dysregulated host response to infection & is a global health challenge. In 2017, 48•9 million incident cases of sepsis were recorded worldwide with 11million sepsis-related deaths, representing 19•7% of all global deaths. There are >123,000 sepsis cases diagnosed in Engl& each year with an estimated 36,800 sepsis-associated deaths. Sepsis is treatable, & timely, targeted interventions improve outcomes. The World Health Assembly identified sepsis as a global health priority.

    PIONEER geography The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix. There is a higher than average percentage of minority ethnic groups. WM has a large number of elderly residents but is the youngest population in the UK. Birmingham has the highest birth rate in England. It also has the highest infant mortality rate. WM life expectancy is 1.8 years less than in London. There are particularly high rates of physical inactivity, obesity, smoking & diabetes. Each day >100,000 people are treated in hospital, see their GP or are cared for by the NHS.

    EHR. University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & 100 ITU beds. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”.

    Scope: All hospitalised patients to UHB from 2000 – current day. Updated monthly. Longitudinal & individually linked, so that the preceding & subsequent health journey can be mapped & healthcare utilisation prior to & after sepsis understood. The dataset includes ICD-10 & SNOMED-CT codes pertaining to sepsis & suspected sepsis. Serial, structured data pertaining to process of care (timings, staff grades, specialty review, wards), presenting complaint, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations), all blood results, microbiology, all prescribed & administered treatments (fluids, antibiotics, inotropes, vasopressors, organ support), all outcomes. Linked images available (radiographs, CT, MRI, ultrasound). Includes COVID-19 wave 1 and wave 2 data.

    Available supplementary data: Matched “non-sepsis” controls; ambulance, 111, 999 data, synthetic data.

    Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

  13. Wallis and Futuna Islands - Health Indicators

    • data.humdata.org
    csv
    Updated Jun 16, 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(38703), csv(1540), csv(34999), csv(3126), csv(143)Available download formats
    Dataset updated
    Jun 16, 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.

  14. Georgia - Health Indicators

    • data.humdata.org
    • cloud.csiss.gmu.edu
    csv
    Updated Jun 16, 2025
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    World Health Organization (2025). Georgia - Health Indicators [Dataset]. https://data.humdata.org/dataset/who-data-for-geo
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    csv(24672), csv(14968), csv(173025), csv(106465), csv(9089), csv(1480868), csv(1280929), csv(5994), csv(4296813), csv(87667), csv(5200), csv(6172), csv(14404), csv(71308), csv(348233), csv(6720), csv(514426), csv(1444681), csv(505536), csv(91486), csv(117200), csv(12599), csv(45459), csv(70175), csv(242584), csv(1211267), csv(101856), csv(1366195), csv(4629), csv(1328706), csv(12065), csv(6801027), csv(30830), csv(1755), csv(2226)Available download formats
    Dataset updated
    Jun 16, 2025
    Dataset provided by
    World Health Organizationhttps://who.int/
    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.

  15. Guadeloupe - Health Indicators

    • data.humdata.org
    csv
    Updated Apr 15, 2025
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    World Health Organization (2025). Guadeloupe - Health Indicators [Dataset]. https://data.humdata.org/dataset/who-data-for-glp
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    csv(8916), csv(143)Available download formats
    Dataset updated
    Apr 15, 2025
    Dataset provided by
    World Health Organizationhttps://who.int/
    Area covered
    Guadeloupe
    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.

  16. Peru - Health Indicators

    • data.amerigeoss.org
    csv
    Updated Mar 26, 2025
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    UN Humanitarian Data Exchange (2025). Peru - Health Indicators [Dataset]. https://data.amerigeoss.org/dataset/who-data-for-peru
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    csv(102376), csv(1452176), csv(138115), csv(1762), csv(10616), csv(3353), csv(6682), csv(1291524), csv(14904), csv(72319), csv(7039), csv(10868833), csv(62997), csv(352465), csv(305547), csv(1422647), csv(45237), csv(20224), csv(2823), csv(13182), csv(14926), csv(29004), csv(1135661), csv(4620), csv(36728), csv(5810317), csv(5973), csv(7496525), csv(34215), csv(89895), csv(393749), csv(206751), csv(94326), csv(1374390), csv(87387)Available download formats
    Dataset updated
    Mar 26, 2025
    Dataset provided by
    United Nationshttp://un.org/
    Area covered
    Peru
    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.

  17. Cayman Islands - Health Indicators

    • data.humdata.org
    csv
    Updated Jun 16, 2025
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    World Health Organization (2025). Cayman Islands - Health Indicators [Dataset]. https://data.humdata.org/dataset/who-data-for-cym
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    csv(45411), csv(3414), csv(143), csv(42489), csv(3403), csv(1391)Available download formats
    Dataset updated
    Jun 16, 2025
    Dataset provided by
    World Health Organizationhttps://who.int/
    Area covered
    Cayman Islands
    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.

  18. A

    Andorra - Health Indicators

    • data.amerigeoss.org
    • cloud.csiss.gmu.edu
    • +1more
    csv
    Updated Jun 18, 2025
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    UN Humanitarian Data Exchange (2025). Andorra - Health Indicators [Dataset]. https://data.amerigeoss.org/fi/dataset/who-data-for-andorra
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    csv(44088), csv(159556), csv(224166), csv(6661), csv(218666), csv(643), csv(101895), csv(2194), csv(2694955), csv(3722866), csv(7862), csv(1225039), csv(87341), csv(1056989), csv(336799), csv(2406), csv(9484), csv(1066280), csv(153876), csv(85325), csv(8185), csv(59016), csv(14802), csv(1147), csv(3822), csv(108956), csv(713718), csv(40258), csv(50756)Available download formats
    Dataset updated
    Jun 18, 2025
    Dataset provided by
    UN Humanitarian Data Exchange
    Area covered
    Andorra
    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.

  19. Population of Pakistan 1800-2020

    • statista.com
    Updated Aug 8, 2024
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    Statista (2024). Population of Pakistan 1800-2020 [Dataset]. https://www.statista.com/statistics/1067011/population-pakistan-historical/
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    Dataset updated
    Aug 8, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Pakistan
    Description

    In 1800, the population of the area of modern-day Pakistan was estimated to be just over 13 million. Population growth in the 19th century would be gradual in the region, rising to just 19 million at the turn of the century. In the early 1800s, the British Empire slowly consolidated power in the region, eventually controlling the region of Pakistan from the mid-19th century onwards, as part of the British Raj. From the 1930s on, the population's growth rate would increase as improvements in healthcare (particularly vaccination) and sanitation would lead to lower infant mortality rates and higher life expectancy. Independence In 1947, the Muslim-majority country of Pakistan gained independence from Britain, and split from the Hindu-majority country of India. In the next few years, upwards of ten million people migrated between the two nations, during a period that was blemished by widespread atrocities on both sides. Throughout this time, the region of Bangladesh was also a part Pakistan (as it also had a Muslim majority), known as East Pakistan; internal disputes between the two regions were persistent for over two decades, until 1971, when a short but bloody civil war resulted in Bangladesh's independence. Political disputes between Pakistan and India also created tension in the first few decades of independence, even boiling over into some relatively small-scale conflicts, although there was some economic progress and improvements in quality of life for Pakistan's citizens. The late 20th century was also characterized by several attempts to become democratic, but with intermittent periods of military rule. Between independence and the end of the century, Pakistan's population had grown more than four times in total. Pakistan today Since 2008, Pakistan has been a functioning democracy, with an emerging economy and increasing international prominence. Despite the emergence of a successful middle-class, this is prosperity is not reflected in all areas of the population as almost a quarter still live in poverty, and Pakistan ranks in the bottom 20% of countries according to the Human Development Index. In 2020, Pakistan is thought to have a total population of over 220 million people, making it the fifth-most populous country in the world.

  20. Martinique - Health Indicators

    • data.humdata.org
    csv
    Updated Apr 15, 2025
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    World Health Organization (2025). Martinique - Health Indicators [Dataset]. https://data.humdata.org/dataset/who-data-for-mtq
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    csv(10464), csv(143)Available download formats
    Dataset updated
    Apr 15, 2025
    Dataset provided by
    World Health Organizationhttps://who.int/
    Area covered
    Martinique
    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.

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Manisha Dubey; Usha Ram; Faujdar Ram (2023). Threshold Levels of Infant and Under-Five Mortality for Crossover between Life Expectancies at Ages Zero, One and Five in India: A Decomposition Analysis [Dataset]. http://doi.org/10.1371/journal.pone.0143764

Threshold Levels of Infant and Under-Five Mortality for Crossover between Life Expectancies at Ages Zero, One and Five in India: A Decomposition Analysis

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6 scholarly articles cite this dataset (View in Google Scholar)
pdfAvailable download formats
Dataset updated
Jun 1, 2023
Dataset provided by
PLOS ONE
Authors
Manisha Dubey; Usha Ram; Faujdar Ram
License

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

Description

ObjectivesUnder the prevailing conditions of imbalanced life table and historic gender discrimination in India, our study examines crossover between life expectancies at ages zero, one and five years for India and quantifies the relative share of infant and under-five mortality towards this crossover.MethodsWe estimate threshold levels of infant and under-five mortality required for crossover using age specific death rates during 1981–2009 for 16 Indian states by sex (comprising of India’s 90% population in 2011). Kitagawa decomposition equations were used to analyse relative share of infant and under-five mortality towards crossover.FindingsIndia experienced crossover between life expectancies at ages zero and five in 2004 for menand in 2009 for women; eleven and nine Indian states have experienced this crossover for men and women, respectively. Men usually experienced crossover four years earlier than the women. Improvements in mortality below ages five have mostly contributed towards this crossover. Life expectancy at age one exceeds that at age zero for both men and women in India except for Kerala (the only state to experience this crossover in 2000 for men and 1999 for women).ConclusionsFor India, using life expectancy at age zero and under-five mortality rate together may be more meaningful to measure overall health of its people until the crossover. Delayed crossover for women, despite higher life expectancy at birth than for men reiterates that Indian women are still disadvantaged and hence use of life expectancies at ages zero, one and five become important for India. Greater programmatic efforts to control leading causes of death during the first month and 1–59 months in high child mortality areas can help India to attain this crossover early.

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