55 datasets found
  1. Infant mortality rate per 1,000 live births in Kenya 1960-2023

    • statista.com
    Updated Apr 25, 2014
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    Statista (2014). Infant mortality rate per 1,000 live births in Kenya 1960-2023 [Dataset]. https://www.statista.com/statistics/806963/infant-mortality-in-kenya/
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    Dataset updated
    Apr 25, 2014
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Kenya
    Description

    In 2023, the infant mortality rate in deaths per 1,000 live births in Kenya was 34.7. Between 1960 and 2023, the figure dropped by 78, though the decline followed an uneven course rather than a steady trajectory.

  2. Kenya - Demographics, Health and Infant Mortality Rates

    • data.unicef.org
    Updated Sep 29, 2016
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    UNICEF (2016). Kenya - Demographics, Health and Infant Mortality Rates [Dataset]. https://data.unicef.org/country/ken/
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    Dataset updated
    Sep 29, 2016
    Dataset authored and provided by
    UNICEFhttp://www.unicef.org/
    Description

    UNICEF's country profile for Kenya, including under-five mortality rates, child health, education and sanitation data.

  3. M

    Kenya Infant Mortality Rate | Historical Data | Chart | 1950-2025

    • macrotrends.net
    csv
    Updated Oct 31, 2025
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    MACROTRENDS (2025). Kenya Infant Mortality Rate | Historical Data | Chart | 1950-2025 [Dataset]. https://www.macrotrends.net/datasets/global-metrics/countries/ken/kenya/infant-mortality-rate
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    csvAvailable download formats
    Dataset updated
    Oct 31, 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 - Dec 31, 2025
    Area covered
    Kenya
    Description

    Historical dataset showing Kenya infant mortality rate by year from 1950 to 2025.

  4. K

    Kenya KE: Mortality Rate: Infant: per 1000 Live Births

    • ceicdata.com
    Updated Mar 15, 2018
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    CEICdata.com (2018). Kenya KE: Mortality Rate: Infant: per 1000 Live Births [Dataset]. https://www.ceicdata.com/en/kenya/health-statistics/ke-mortality-rate-infant-per-1000-live-births
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    Dataset updated
    Mar 15, 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
    Kenya
    Description

    Kenya KE: Mortality Rate: Infant: per 1000 Live Births data was reported at 33.600 Ratio in 2017. This records a decrease from the previous number of 34.300 Ratio for 2016. Kenya KE: Mortality Rate: Infant: per 1000 Live Births data is updated yearly, averaging 67.500 Ratio from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 117.400 Ratio in 1960 and a record low of 33.600 Ratio in 2017. Kenya KE: Mortality Rate: Infant: per 1000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank.WDI: Health Statistics. Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 live births in a given year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys.

  5. T

    Kenya Infant Mortality Rate

    • trendonify.com
    csv
    Updated Dec 31, 2023
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    Trendonify (2023). Kenya Infant Mortality Rate [Dataset]. https://trendonify.com/kenya/infant-mortality-rate
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    csvAvailable download formats
    Dataset updated
    Dec 31, 2023
    Dataset authored and provided by
    Trendonify
    License

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

    Time period covered
    Dec 31, 1960 - Dec 31, 2023
    Area covered
    Kenya
    Description

    Yearly (annual) dataset of the Kenya Infant Mortality Rate, including historical data, latest releases, and long-term trends from 1960-12-31 to 2023-12-31. Available for free download in CSV format.

  6. Infant mortality in Kenya 1950-2020

    • statista.com
    Updated Sep 22, 2020
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    Statista (2020). Infant mortality in Kenya 1950-2020 [Dataset]. https://www.statista.com/statistics/1073181/infant-mortality-rate-kenya-historical/
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    Dataset updated
    Sep 22, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Kenya
    Description

    In 1950, the infant mortality rate in Kenya was 187 deaths for every 1,000 live births. This means that just under 19 percent of all children born in 1950 were not expected to live past their first birthday. However, as the use of insecticides such as DDT and insecticide-treated nets (ITNs) became more widespread, and several anti-malarial drugs became more widely available, malaria and other insect-borne diseases (one of the major sources of infant mortality in the country) saw a sharp reduction in Kenya, leading to a large reduction in infant mortality from the 1950s to the mid-1980s.

    In the late 1980s, this downward trend would slow, as an economic depression and the spread of the HIV/AIDS epidemic would lead to both an increase in complications for children born with the disease, as well as increased strain on the Kenyan healthcare system as a whole. After remaining at 74 deaths per 1000 births through the remainder of the 20th century, infant mortality would continue to fall again, in part the result of significantly improved access to HIV counselling and treatments and progress in malaria eradication efforts. In 2020, it is estimated that for every 1,000 live births, there will be 36 deaths before the first birthday.

  7. K

    Kenya KE: Mortality Rate: Infant: Male: per 1000 Live Births

    • ceicdata.com
    Updated Sep 15, 2022
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    CEICdata.com (2022). Kenya KE: Mortality Rate: Infant: Male: per 1000 Live Births [Dataset]. https://www.ceicdata.com/en/kenya/health-statistics/ke-mortality-rate-infant-male-per-1000-live-births
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    Dataset updated
    Sep 15, 2022
    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, 1990 - Dec 1, 2016
    Area covered
    Kenya
    Description

    Kenya KE: Mortality Rate: Infant: Male: per 1000 Live Births data was reported at 36.900 Ratio in 2017. This records a decrease from the previous number of 38.500 Ratio for 2015. Kenya KE: Mortality Rate: Infant: Male: per 1000 Live Births data is updated yearly, averaging 43.700 Ratio from Dec 1990 (Median) to 2017, with 5 observations. The data reached an all-time high of 71.000 Ratio in 1990 and a record low of 36.900 Ratio in 2017. Kenya KE: Mortality Rate: Infant: Male: per 1000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank.WDI: Health Statistics. Infant mortality rate, male is the number of male infants dying before reaching one year of age, per 1,000 male live births in a given year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys.

  8. T

    Kenya Mortality Rate Infant Male Per 1000 Live Births

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 8, 2017
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    TRADING ECONOMICS (2017). Kenya Mortality Rate Infant Male Per 1000 Live Births [Dataset]. https://tradingeconomics.com/kenya/mortality-rate-infant-male-per-1000-live-births-wb-data.html
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    json, csv, excel, xmlAvailable download formats
    Dataset updated
    Jun 8, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    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, 1976 - Dec 31, 2025
    Area covered
    Kenya
    Description

    Actual value and historical data chart for Kenya Mortality Rate Infant Male Per 1000 Live Births

  9. Child mortality in Kenya 1900-2020

    • statista.com
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    Statista, Child mortality in Kenya 1900-2020 [Dataset]. https://www.statista.com/statistics/1072817/child-mortality-rate-kenya-historical/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Kenya
    Description

    In 1900, the child mortality rate in Kenya was just over 507 deaths for every 1,000 live births. This means that more than half of all children born in this years did not survive past their fifth birthday. This rate would remain relatively constant through the first thirty years of the 20th century. However, child mortality would begin to sharply fall beginning in the 1930s, in part the result of a rapid modernization campaign between the 1930s to 1950s. In the post-war years, as the use of insecticides such as DDT and insecticide-treated nets (ITNs) became more widespread, and several anti-malarial drugs became more widely available, malaria and other insect-borne diseases saw a sharp reduction in Kenya, which, when combined with an expansion of healthcare access throughout the country, led to a large reduction in child mortality from the 1950s to the mid-1980s.

    However, in the late 1980s, this downward trend would slow, as an economic depression and the spread of the HIV/AIDS epidemic would lead to both an increase in complications for children born with the disease, as well as place an increased strain on the Kenyan healthcare system as a whole. After reaching a record low of 106 deaths in 1990, child mortality would rise for the first time in 65 years in 1995 to 108 deaths per 1,000 births. However, thanks in part to significantly improved access to HIV counselling and treatments, progress in malaria eradication efforts, and overall improvement in the economy, child mortality would begin to fall again, and in 2020, it is estimated that for every 1,000 live births, over 95 percent of all children will make it past the age of five.

  10. T

    Kenya - Number Of Infant Deaths

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 3, 2017
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    TRADING ECONOMICS (2017). Kenya - Number Of Infant Deaths [Dataset]. https://tradingeconomics.com/kenya/number-of-infant-deaths-wb-data.html
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    excel, csv, json, xmlAvailable download formats
    Dataset updated
    Jun 3, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    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, 1976 - Dec 31, 2025
    Area covered
    Kenya
    Description

    Number of infant deaths in Kenya was reported at 51498 deaths in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kenya - Number of infant deaths - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

  11. K

    Kenya KE: Mortality Rate: Under-5: Male: per 1000 Live Births

    • ceicdata.com
    Updated Apr 15, 2018
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    CEICdata.com (2018). Kenya KE: Mortality Rate: Under-5: Male: per 1000 Live Births [Dataset]. https://www.ceicdata.com/en/kenya/health-statistics/ke-mortality-rate-under5-male-per-1000-live-births
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    Dataset updated
    Apr 15, 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, 1990 - Dec 1, 2016
    Area covered
    Kenya
    Description

    Kenya KE: Mortality Rate: Under-5: Male: per 1000 Live Births data was reported at 53.200 Ratio in 2016. This records a decrease from the previous number of 55.100 Ratio for 2015. Kenya KE: Mortality Rate: Under-5: Male: per 1000 Live Births data is updated yearly, averaging 66.600 Ratio from Dec 1990 (Median) to 2016, with 5 observations. The data reached an all-time high of 106.400 Ratio in 2000 and a record low of 53.200 Ratio in 2016. Kenya KE: Mortality Rate: Under-5: Male: per 1000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank: Health Statistics. Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male age-specific mortality rates of the specified year.; ; Estimates Developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted Average; Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys.

  12. m

    Infant_Mortality_Rate_Per_1000_Live_Births - Kenya

    • macro-rankings.com
    csv, excel
    Updated Dec 31, 2023
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    macro-rankings (2023). Infant_Mortality_Rate_Per_1000_Live_Births - Kenya [Dataset]. https://www.macro-rankings.com/selected-country-rankings/infant-mortality-rate-per-1000-live-births/kenya
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    excel, csvAvailable download formats
    Dataset updated
    Dec 31, 2023
    Dataset authored and provided by
    macro-rankings
    License

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

    Area covered
    Kenya
    Description

    Time series data for the statistic Infant_Mortality_Rate_Per_1000_Live_Births and country Kenya. Indicator Definition:Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 live births in a given year.The statistic "Infant Mortality Rate Per 1000 Live Births" stands at 34.70 per mille as of 12/31/2023, the lowest value at least since 12/31/1961, the period currently displayed. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -1.10 percentage points compared to the value the year prior.The 1 year change in percentage points is -1.10.The 3 year change in percentage points is -2.20.The 5 year change in percentage points is -3.10.The 10 year change in percentage points is -6.20.The Serie's long term average value is 65.22 per mille. It's latest available value, on 12/31/2023, is 30.52 percentage points lower, compared to it's long term average value.The Serie's change in percentage points from it's minimum value, on 12/31/2023, to it's latest available value, on 12/31/2023, is +0.0.The Serie's change in percentage points from it's maximum value, on 12/31/1960, to it's latest available value, on 12/31/2023, is -78.00.

  13. K

    Kenya KE: Mortality Rate: Under-5: Female: per 1000 Live Births

    • ceicdata.com
    Updated Mar 15, 2018
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    CEICdata.com (2018). Kenya KE: Mortality Rate: Under-5: Female: per 1000 Live Births [Dataset]. https://www.ceicdata.com/en/kenya/health-statistics/ke-mortality-rate-under5-female-per-1000-live-births
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    Dataset updated
    Mar 15, 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, 1990 - Dec 1, 2016
    Area covered
    Kenya
    Description

    Kenya KE: Mortality Rate: Under-5: Female: per 1000 Live Births data was reported at 41.500 Ratio in 2017. This records a decrease from the previous number of 44.500 Ratio for 2015. Kenya KE: Mortality Rate: Under-5: Female: per 1000 Live Births data is updated yearly, averaging 53.900 Ratio from Dec 1990 (Median) to 2017, with 5 observations. The data reached an all-time high of 98.400 Ratio in 2000 and a record low of 41.500 Ratio in 2017. Kenya KE: Mortality Rate: Under-5: Female: per 1000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank.WDI: Health Statistics. Under-five mortality rate, female is the probability per 1,000 that a newborn female baby will die before reaching age five, if subject to female age-specific mortality rates of the specified year.; ; Estimates Developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys.

  14. K

    Kenya KE: Mortality Rate: Under-5: per 1000 Live Births

    • ceicdata.com
    Updated Jan 15, 2018
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    CEICdata.com (2018). Kenya KE: Mortality Rate: Under-5: per 1000 Live Births [Dataset]. https://www.ceicdata.com/en/kenya/health-statistics/ke-mortality-rate-under5-per-1000-live-births
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    Dataset updated
    Jan 15, 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
    Kenya
    Description

    Kenya KE: Mortality Rate: Under-5: per 1000 Live Births data was reported at 45.600 Ratio in 2017. This records a decrease from the previous number of 47.100 Ratio for 2016. Kenya KE: Mortality Rate: Under-5: per 1000 Live Births data is updated yearly, averaging 107.350 Ratio from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 196.900 Ratio in 1960 and a record low of 45.600 Ratio in 2017. Kenya KE: Mortality Rate: Under-5: per 1000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank.WDI: Health Statistics. Under-five mortality rate is the probability per 1,000 that a newborn baby will die before reaching age five, if subject to age-specific mortality rates of the specified year.; ; Estimates Developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys.

  15. K

    Kenya KE: Mortality Rate: Infant per 1000 Births

    • ceicdata.com
    Updated Apr 15, 2018
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    CEICdata.com (2018). Kenya KE: Mortality Rate: Infant per 1000 Births [Dataset]. https://www.ceicdata.com/en/kenya/demographic-projection/ke-mortality-rate-infant-per-1000-births
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    Dataset updated
    Apr 15, 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
    Jun 1, 2039 - Jun 1, 2050
    Area covered
    Kenya
    Variables measured
    Population
    Description

    Kenya KE: Mortality Rate: Infant per 1000 Births data was reported at 12.300 NA in 2050. This records a decrease from the previous number of 12.700 NA for 2049. Kenya KE: Mortality Rate: Infant per 1000 Births data is updated yearly, averaging 40.050 NA from Jun 1979 (Median) to 2050, with 72 observations. The data reached an all-time high of 78.200 NA in 1979 and a record low of 12.300 NA in 2050. Kenya KE: Mortality Rate: Infant per 1000 Births data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s Kenya – Table KE.US Census Bureau: Demographic Projection.

  16. Age distribution, trends, and forecasts of under-5 mortality in 31...

    • plos.figshare.com
    docx
    Updated Jun 6, 2023
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    Iván Mejía-Guevara; Wenyun Zuo; Eran Bendavid; Nan Li; Shripad Tuljapurkar (2023). Age distribution, trends, and forecasts of under-5 mortality in 31 sub-Saharan African countries: A modeling study [Dataset]. http://doi.org/10.1371/journal.pmed.1002757
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    docxAvailable download formats
    Dataset updated
    Jun 6, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Iván Mejía-Guevara; Wenyun Zuo; Eran Bendavid; Nan Li; Shripad Tuljapurkar
    License

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

    Area covered
    Africa, Sub-Saharan Africa
    Description

    BackgroundDespite the sharp decline in global under-5 deaths since 1990, uneven progress has been achieved across and within countries. In sub-Saharan Africa (SSA), the Millennium Development Goals (MDGs) for child mortality were met only by a few countries. Valid concerns exist as to whether the region would meet new Sustainable Development Goals (SDGs) for under-5 mortality. We therefore examine further sources of variation by assessing age patterns, trends, and forecasts of mortality rates.Methods and findingsData came from 106 nationally representative Demographic and Health Surveys (DHSs) with full birth histories from 31 SSA countries from 1990 to 2017 (a total of 524 country-years of data). We assessed the distribution of age at death through the following new demographic analyses. First, we used a direct method and full birth histories to estimate under-5 mortality rates (U5MRs) on a monthly basis. Second, we smoothed raw estimates of death rates by age and time by using a two-dimensional P-Spline approach. Third, a variant of the Lee–Carter (LC) model, designed for populations with limited data, was used to fit and forecast age profiles of mortality. We used mortality estimates from the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME) to adjust, validate, and minimize the risk of bias in survival, truncation, and recall in mortality estimation. Our mortality model revealed substantive declines of death rates at every age in most countries but with notable differences in the age patterns over time. U5MRs declined from 3.3% (annual rate of reduction [ARR] 0.1%) in Lesotho to 76.4% (ARR 5.2%) in Malawi, and the pace of decline was faster on average (ARR 3.2%) than that observed for infant (IMRs) (ARR 2.7%) and neonatal (NMRs) (ARR 2.0%) mortality rates. We predict that 5 countries (Kenya, Rwanda, Senegal, Tanzania, and Uganda) are on track to achieve the under-5 sustainable development target by 2030 (25 deaths per 1,000 live births), but only Rwanda and Tanzania would meet both the neonatal (12 deaths per 1,000 live births) and under-5 targets simultaneously. Our predicted NMRs and U5MRs were in line with those estimated by the UN IGME by 2030 and 2050 (they overlapped in 27/31 countries for NMRs and 22 for U5MRs) and by the Institute for Health Metrics and Evaluation (IHME) by 2030 (26/31 and 23/31, respectively). This study has a number of limitations, including poor data quality issues that reflected bias in the report of births and deaths, preventing reliable estimates and predictions from a few countries.ConclusionsTo our knowledge, this study is the first to combine full birth histories and mortality estimates from external reliable sources to model age patterns of under-5 mortality across time in SSA. We demonstrate that countries with a rapid pace of mortality reduction (ARR ≥ 3.2%) across ages would be more likely to achieve the SDG mortality targets. However, the lower pace of neonatal mortality reduction would prevent most countries from achieving those targets: 2 countries would reach them by 2030, 13 between 2030 and 2050, and 13 after 2050.

  17. Morbidity and mortality in infants.

    • figshare.com
    • plos.figshare.com
    xls
    Updated Jun 4, 2023
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    Helen M. Nabwera; Dingmei Wang; Olukemi O. Tongo; Pauline E. A. Andang’o; Isa Abdulkadir; Chinyere V. Ezeaka; Beatrice N. Ezenwa; Iretiola B. Fajolu; Zainab O. Imam; Martha K. Mwangome; Dominic D. Umoru; Abimbola E. Akindolire; Walter Otieno; Grace M. Nalwa; Alison W. Talbert; Ismaela Abubakar; Nicholas D. Embleton; Stephen J. Allen (2023). Morbidity and mortality in infants. [Dataset]. http://doi.org/10.1371/journal.pone.0244109.t004
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    xlsAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Helen M. Nabwera; Dingmei Wang; Olukemi O. Tongo; Pauline E. A. Andang’o; Isa Abdulkadir; Chinyere V. Ezeaka; Beatrice N. Ezenwa; Iretiola B. Fajolu; Zainab O. Imam; Martha K. Mwangome; Dominic D. Umoru; Abimbola E. Akindolire; Walter Otieno; Grace M. Nalwa; Alison W. Talbert; Ismaela Abubakar; Nicholas D. Embleton; Stephen J. Allen
    License

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

    Description

    Morbidity and mortality in infants.

  18. z

    Data from: Pregnancy outcomes in facility deliveries in Kenya and Uganda: A...

    • zenodo.org
    • datadryad.org
    bin, txt
    Updated Jun 3, 2022
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    Peter Waiswa; Brennan V. Higgins; Paul Mubiri; Leah Kirumbi; Elizabeth Butrick; Rikita Merai; Nancy L. Sloan; Dilys Walker; Preterm Birth Initiative Kenya & Uganda Implementation Research Collaborative; Peter Waiswa; Brennan V. Higgins; Paul Mubiri; Leah Kirumbi; Elizabeth Butrick; Rikita Merai; Nancy L. Sloan; Dilys Walker; Preterm Birth Initiative Kenya & Uganda Implementation Research Collaborative (2022). Pregnancy outcomes in facility deliveries in Kenya and Uganda: A large cross-sectional analysis of maternity registers illuminating opportunities for mortality prevention [Dataset]. http://doi.org/10.7272/q6zg6qfc
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    txt, binAvailable download formats
    Dataset updated
    Jun 3, 2022
    Dataset provided by
    Zenodo
    Authors
    Peter Waiswa; Brennan V. Higgins; Paul Mubiri; Leah Kirumbi; Elizabeth Butrick; Rikita Merai; Nancy L. Sloan; Dilys Walker; Preterm Birth Initiative Kenya & Uganda Implementation Research Collaborative; Peter Waiswa; Brennan V. Higgins; Paul Mubiri; Leah Kirumbi; Elizabeth Butrick; Rikita Merai; Nancy L. Sloan; Dilys Walker; Preterm Birth Initiative Kenya & Uganda Implementation Research Collaborative
    License

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

    Area covered
    Uganda, Kenya
    Description

    Introduction

    As facility-based deliveries increase globally, maternity registers offer a promising way of documenting pregnancy outcomes and understanding opportunities for perinatal mortality prevention. This study aims to contribute to global quality improvement efforts by characterizing facility-based pregnancy outcomes in Kenya and Uganda including maternal, neonatal, and fetal outcomes at the time of delivery and neonatal discharge outcomes using strengthened maternity registers.

    Methods

    Cross sectional data were collected from previously strengthened maternity registers at 23 facilities over 18 months. Pregnancy outcomes were classified as live births, early stillbirths, late stillbirths, or spontaneous abortions according to birth weight or gestational age. Discharge outcomes were assessed for all live births. Outcomes were assessed by country and by infant, maternal, and facility characteristics. Maternal mortality was also examined.

    Results

    Among 50,981 deliveries, 91.3% were live born and, of those, 1.6% died before discharge. An additional 0.5% of deliveries were early stillbirths, 3.6% late stillbirths, and 4.7% spontaneous abortions. There were 64 documented maternal deaths (0.1%). Preterm and low birthweight infants represented a disproportionate number of stillbirths and pre-discharge deaths, yet very few were born at ≤1500g or <28w. More pre-discharge deaths and stillbirths occurred after maternal referral and with cesarean section. Half of maternal deaths occurred in women who had undergone cesarean section.

    Conclusion

    Maternity registers are a valuable data source for understanding pregnancy outcomes including those mothers and infants at highest risk of perinatal mortality. Strengthened register data in Kenya and Uganda highlight the need for renewed focus on improving care of preterm and low birthweight infants and expanding access to emergency obstetric care. Registers also permit enumeration of pregnancy loss <28 weeks. Documenting these earlier losses is an important step towards further mortality reduction for the most vulnerable infants.

  19. K

    Kenya KE: Number of Death: Infant

    • ceicdata.com
    Updated Aug 15, 2025
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    CEICdata.com (2025). Kenya KE: Number of Death: Infant [Dataset]. https://www.ceicdata.com/en/kenya/health-statistics/ke-number-of-death-infant
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    Dataset updated
    Aug 15, 2025
    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
    Kenya
    Description

    Kenya KE: Number of Death: Infant data was reported at 51,053.000 Person in 2017. This records a decrease from the previous number of 51,524.000 Person for 2016. Kenya KE: Number of Death: Infant data is updated yearly, averaging 55,663.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 79,090.000 Person in 1999 and a record low of 46,502.000 Person in 1963. Kenya KE: Number of Death: Infant data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank.WDI: Health Statistics. Number of infants dying before reaching one year of age.; ; 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;

  20. Kenya Demographic and Health Survey 1998 - Kenya

    • statistics.knbs.or.ke
    Updated Sep 20, 2022
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    Kenya National Bureau of Statistics (KNBS) (2022). Kenya Demographic and Health Survey 1998 - Kenya [Dataset]. https://statistics.knbs.or.ke/nada/index.php/catalog/64
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    Dataset updated
    Sep 20, 2022
    Dataset provided by
    Kenya National Bureau of Statistics
    Authors
    Kenya National Bureau of Statistics (KNBS)
    Time period covered
    1998
    Area covered
    Kenya
    Description

    Abstract

    The 1998 Kenya Demographic and Health Survey (KDHS) is a nationally representative survey of 7,881 wo 881 women age 15-49 and 3,407 men age 15-54. The KDHS was implemented by the National Council for Population and Development (NCPD) and the Central Bureau of Statistics (CBS), with significant technical and logistical support provided by the Ministry of Health and various other governmental and nongovernmental organizations in Kenya. Macro International Inc. of Calverton, Maryland (U.S.A.) provided technical assistance throughout the course of the project in the context of the worldwide Demographic and Health Surveys (DHS) programme, while financial assistance was provided by the U.S. Agency for International Development (USAID/Nairobi) and the Department for International Development (DFID/U.K.). Data collection for the KDHS was conducted from February to July 1998. Like the previous KDHS surveys conducted in 1989 and 1993, the 1998 KDHS was designed to provide information on levels and trends in fertility, family planning knowledge and use, infant and child mortality, and other maternal and child health indicators. However, the 1998 KDHS went further to collect more in-depth data on knowledge and behaviours related to AIDS and other sexually transmitted diseases (STDs), detailed “calendar” data that allows estimation of contraceptive discontinuation rates, and information related to the practice of female circumcision. Further, unlike earlier surveys, the 1998 KDHS provides a national estimate of the level of maternal mortality (i.e. related to pregnancy and childbearing).The KDHS data are intended for use by programme managers and policymakers to evaluate and improve health and family planning programmes in Kenya. Fertility. The survey results demonstrate a continuation of the fertility transition in Kenya. At current fertility levels, a Kenyan women will bear 4.7 children in her life, down 30 percent from the 1989 KDHS when the total fertility rate (TFR) was 6.7 children, and 42 percent since the 1977/78 Kenya Fertility Survey (KFS) when the TFR was 8.1 children per woman. A rural woman can expect to have 5.2 children, around two children more than an urban women (3.1 children). Fertility differentials by women's education level are even more remarkable; women with no education will bear an average of 5.8 children, compared to 3.5 children for women with secondary school education. Marriage. The age at which women and men first marry has risen slowly over the past 20 years. Currently, women marry for the first time at an average age of 20 years, compared with 25 years for men. Women with a secondary education marry five years later (22) than women with no education (17).The KDHS data indicate that the practice of polygyny continues to decline in Kenya. Sixteen percent of currently married women are in a polygynous union (i.e., their husband has at least one other wife), compared with 19 percent of women in the 1993 KDHS, 23 percent in the 1989 KDHS, and 30 percent in the 1977/78 KFS. While men first marry an average of 5 years later than women, men become sexual active about onehalf of a year earlier than women; in the youngest age cohort for which estimates are available (age 20-24), first sex occurs at age 16.8 for women and 16.2 for men. Fertility Preferences. Fifty-three percent of women and 46 percent of men in Kenya do not want to have any more children. Another 25 percent of women and 27 percent of men would like to delay their next child for two years or longer. Thus, about three-quarters of women and men either want to limit or to space their births. The survey results show that, of all births in the last three years, 1 in 10 was unwanted and 1 in 3 was mistimed. If all unwanted births were avoided, the fertility rate in Kenya would fall from 4.7 to 3.5 children per woman. Family Planning. Knowledge and use of family planning in Kenya has continued to rise over the last several years. The 1998 KDHS shows that virtually all married women (98 percent) and men (99 percent) were able to cite at least one modern method of contraception. The pill, condoms, injectables, and female sterlisation are the most widely known methods. Overall, 39 percent of currently married women are using a method of contraception. Use of modern methods has increased from 27 in the 1993 KDHS to 32 percent in the 1998 KDHS. Currently, the most widely used methods are contraceptive injectables (12 percent of married women), the pill (9 percent), female sterilisation (6 percent), and periodic abstinence (6 percent). Three percent of married women are using the IUD, while over 1 percent report using the condom and 1 percent use of contraceptive implants (Norplant). The rapid increase in use of injectables (from 7 to 12 percent between 1993 and 1998) to become the predominant method, plus small rises in the use of implants, condoms and female sterilisation have more than offset small decreases in pill and IUD use. Thus, both new acceptance of contraception and method switching have characterised the 1993-1998 intersurvey period. Contraceptive use varies widely among geographic and socioeconomic subgroups. More than half of currently married women in Central Province (61 percent) and Nairobi Province (56 percent) are currently using a method, compared with 28 percent in Nyanza Province and 22 percent in Coast Province. Just 23 percent of women with no education use contraception versus 57 percent of women with at least some secondary education. Government facilities provide contraceptives to 58 percent of users, while 33 percent are supplied by private medical sources, 5 percent through other private sources, and 3 percent through community-based distribution (CBD) agents. This represents a significant shift in sourcing away from public outlets, a decline from 68 percent estimated in the 1993 KDHS. While the government continues to provide about two-thirds of IUD insertions and female sterilisations, the percentage of pills and injectables supplied out of government facilities has dropped from over 70 percent in 1993 to 53 percent for pills and 64 percent for injectables in 1998. Supply of condoms through public sector facilities has also declined: from 37 to 21 percent between 1993 and 1998. The survey results indicate that 24 percent of married women have an unmet need for family planning (either for spacing or limiting births). This group comprises married women who are not using a method of family planning but either want to wait two year or more for their next birth (14 percent) or do not want any more children (10 percent). While encouraging that unmet need at the national level has declined (from 34 to 24 percent) since 1993, there are parts of the country where the need for contraception remains high. For example, the level of unmet need is higher in Western Province (32 percent) and Coast Province (30 province) than elsewhere in Kenya. Early Childhood Mortality. One of the main objectives of the KDHS was to document current levels and trends in mortality among children under age 5. Results from the 1998 KDHS data make clear that childhood mortality conditions have worsened in the early-mid 1990s; this after a period of steadily improving child survival prospects through the mid-to-late 1980s. Under-five mortality, the probability of dying before the fifth birthday, stands at 112 deaths per 1000 live births which represents a 24 percent increase over the last decade. Survival chances during age 1-4 years suffered disproportionately: rising 38 percent over the same period. Survey results show that childhood mortality is especially high when associated with two factors: a short preceding birth interval and a low level of maternal education. The risk of dying in the first year of life is more than doubled when the child is born after an interval of less than 24 months. Children of women with no education experience an under-five mortality rate that is two times higher than children of women who attended secondary school or higher. Provincial differentials in childhood mortality are striking; under-five mortality ranges from a low of 34 deaths per 1000 live births in Central Province to a high of 199 per 1000 in Nyanza Province. Maternal Health. Utilisation of antenatal services is high in Kenya; in the three years before the survey, mothers received antenatal care for 92 percent of births (Note: These data do not speak to the quality of those antenatal services). The median number of antenatal visits per pregnancy was 3.7. Most antenatal care is provided by nurses and trained midwives (64 percent), but the percentage provided by doctors (28 percent) has risen in recent years. Still, over one-third of women who do receive care, start during the third trimester of pregnancy-too late to receive the optimum benefits of antenatal care. Mothers reported receiving at least one tetanus toxoid injection during pregnancy for 90 percent of births in the three years before the survey. Tetanus toxoid is a powerful weapon in the fight against neonatal tetanus, a deadly disease that attacks young infants. Forty-two percent of births take place in health facilities; however, this figure varies from around three-quarters of births in Nairobi to around one-quarter of births in Western Province. It is important for the health of both the mother and child that trained medical personnel are available in cases of prolonged labour or obstructed delivery, which are major causes of maternal morbidity and mortality. The 1998 KDHS collected information that allows estimation of mortality related to pregnancy and childbearing. For the 10-year period before the survey, the maternal mortality ratio was estimated to be 590 deaths per 100,000 live births. Bearing on average 4.7 children, a Kenyan woman has a 1 in 36 chance of dying from maternal causes during her lifetime. Childhood Immunisation. The KDHS

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Statista (2014). Infant mortality rate per 1,000 live births in Kenya 1960-2023 [Dataset]. https://www.statista.com/statistics/806963/infant-mortality-in-kenya/
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Infant mortality rate per 1,000 live births in Kenya 1960-2023

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Dataset updated
Apr 25, 2014
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Kenya
Description

In 2023, the infant mortality rate in deaths per 1,000 live births in Kenya was 34.7. Between 1960 and 2023, the figure dropped by 78, though the decline followed an uneven course rather than a steady trajectory.

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