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

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.

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

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.

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.

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.

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.

Actual value and historical data chart for Kenya Mortality Rate Infant Per 1 000 Live Births

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.

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.

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.

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.

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.

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.

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.

39.9 (deaths per 1,000 live births) in 2023. Under-five mortality rate is the probability per 1,000 that a newborn baby will die before reaching age five, if subject to current age-specific mortality rates.

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.

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;

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.

Background: Sexual and Reproductive Health and Rights (SRHR) investments are critical to people's well-being. However, despite the demonstrated returns on investments, underfunding of SRHR still persists. The objective of this study was to characterize donor commitments and disbursements to SRH aid in four sub-Saharan countries of Kenya, Tanzania, Uganda and Zambia and to compare trends in donor aids with SRH outcome and impact indicators for each of these countries.Methods: The study is a secondary analysis of data from the Organization for Economic Co-operation and Development's Assistance creditor reporting system and SRH indicator data from the Global Health Observatory and country demographic health surveys for a 16-year period (2002–2017). We downloaded and compared commitments to disbursements of all donors for population policies, programs and reproductive health for the four African countries. SRH indicators were stratified into health facility level process/outcome indicators (modern contraceptive prevalence rate, unmet need for family planning, antenatal care coverage and skilled birth attendance) and health impact level indicators (maternal mortality ratio, newborn mortality rate, infant mortality rate and under five mortality rate).Results: Donor commitments for SRH aid grew on average by 20% while disbursements grew by 21% annually between 2002 and 2017. The overall disbursement rate was 93%. Development Assistance Cooperation (DAC) countries donated the largest proportion (79%) of aid. Kenya took 33% of total aid, followed by Tanzania 26%, Uganda 23% and then Zambia (18%). There was improvement in all SRH outcome and impact indicators, but not enough to meet targets.Conclusion: Donor aid to SRH grew over time and in the same period indicators improved, but improvement remained slow. Unpredictability and insufficiency of aid may be disruptive to recipient country planning. Donors and low- and middle-income countries should increase funding in order to meet global SRHR targets.