26 datasets found
  1. Total fertility rate of Kenya 1930-2024

    • statista.com
    Updated Jun 3, 2025
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    Statista (2025). Total fertility rate of Kenya 1930-2024 [Dataset]. https://www.statista.com/statistics/1069664/fertility-rate-kenya-historical/
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    Dataset updated
    Jun 3, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Kenya
    Description

    In 1930, the average woman of childbearing age in Kenya would have had just under seven children over the course of their reproductive years. This rate would steadily increase until the end of the 1960s, peaking at just over eight children per woman in 1970. Following this peak, a combination of strong national and international promotion of family planning in Kenya and an expansion of contraceptive use would lead to a sharp decrease in the fertility rate, resulting in an average of 3.19 children in 2024. Teenage fertility in Kenya In 2022, most teenage pregnancies occurred among 19-year-olds. There is a strong correlation between adolescents who had ever been pregnant and those who had no education. Additionally, those who form part of the highest wealth quintile in the country were less likely to have ever been pregnant. Overall decreasing trends in Kenya’s fertility ratesAlthough fertility rates in Kenya have dropped considerably since 1989, the global fertility rate is significantly lower. Kenyans living in rural areas have a higher total fertility rate compared to those living in urban areas. This is reportedly due to differences in the level of education, the use of contraception, and the desire to live a quality life. Between 1995 and 2000, the decline in fertility rates in Kenya slowed somewhat, partly due to the government prioritizing and reallocating healthcare resources towards combatting the then-emerging HIV/AIDS epidemic. However, resources for contraceptives and family planning commenced once more around 2003, and as a result, the total fertility rate began to fall steadily again.

  2. M

    Kenya Fertility Rate (1950-2025)

    • macrotrends.net
    csv
    Updated May 31, 2025
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    MACROTRENDS (2025). Kenya Fertility Rate (1950-2025) [Dataset]. https://www.macrotrends.net/global-metrics/countries/ken/kenya/fertility-rate
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    csvAvailable download formats
    Dataset updated
    May 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

    Area covered
    Kenya
    Description
    Kenya fertility rate for 2025 is 3.17, a 1.37% decline from 2024.
    <ul style='margin-top:20px;'>
    
    <li>Kenya fertility rate for 2024 was <strong>3.21</strong>, a <strong>0.19% increase</strong> from 2023.</li>
    <li>Kenya fertility rate for 2023 was <strong>3.21</strong>, a <strong>1.66% decline</strong> from 2022.</li>
    <li>Kenya fertility rate for 2022 was <strong>3.26</strong>, a <strong>1.51% decline</strong> from 2021.</li>
    </ul>Total fertility rate represents the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with age-specific fertility rates of the specified year.
    
  3. Crude birth rate of Kenya 1930-2020

    • statista.com
    Updated Jul 31, 2024
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    Statista (2024). Crude birth rate of Kenya 1930-2020 [Dataset]. https://www.statista.com/statistics/1070600/crude-birth-rate-kenya-historical/
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    Dataset updated
    Jul 31, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Kenya
    Description

    In 1930, the crude birth rate in Kenya was 47.9 births per thousand people, meaning that approximately 4.8% of the population was born in that given year. The birth rate would continue to increase for several decades, peaking at 51.3 births per thousand people in 1960. Following this, the crude birth rate would remain somewhat stable in Kenya until the late-1970s, when strong national and international promotion of family planning services and an increased use of contraceptives would lead to a sharp decrease in the birth rate. The crude birth rate would see a rapid decrease over the next two decades, falling from 51 births in 1975 to just over 40 births in 1995.

    However, the birth rate would see a brief increase from 1995 to 2000, an increase attributed in part to a prioritizing of government healthcare resources away from contraceptives and family planning towards combatting the emerging HIV/AIDS epidemic. Resources for contraceptives and family planning from the Kenyan government would begin to return around 2003, and as a result, the crude birth rate began to fall again. In 2020, the crude birth rate in Kenya is estimated to be 28.9 births per thousand people.

  4. M

    Kenya Birth Rate (1950-2025)

    • macrotrends.net
    csv
    Updated May 31, 2025
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    MACROTRENDS (2025). Kenya Birth Rate (1950-2025) [Dataset]. https://www.macrotrends.net/global-metrics/countries/ken/kenya/birth-rate
    Explore at:
    csvAvailable download formats
    Dataset updated
    May 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

    Area covered
    Kenya
    Description
    Kenya birth rate for 2025 is 26.79, a 1.05% decline from 2024.
    <ul style='margin-top:20px;'>
    
    <li>Kenya birth rate for 2024 was <strong>27.07</strong>, a <strong>0.13% decline</strong> from 2023.</li>
    <li>Kenya birth rate for 2023 was <strong>27.11</strong>, a <strong>0.86% decline</strong> from 2022.</li>
    <li>Kenya birth rate for 2022 was <strong>27.34</strong>, a <strong>0.97% decline</strong> from 2021.</li>
    </ul>Crude birth rate indicates the number of live births occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.
    
  5. Number of births in Kenya 2016-2022

    • statista.com
    Updated Jun 3, 2025
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    Statista (2025). Number of births in Kenya 2016-2022 [Dataset]. https://www.statista.com/statistics/1227189/number-of-births-in-kenya/
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    Dataset updated
    Jun 3, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Kenya
    Description

    In 2022, over 1.22 million births were registered in Kenya, increasing from 1.20 million births in the previous year. The birth rate in Kenya grew exponentially from 2016, with a slight drop occurring in 2020.

  6. i

    Demographic and Health Survey 1988-1989 - Kenya

    • dev.ihsn.org
    • datacatalog.ihsn.org
    • +2more
    Updated Apr 25, 2019
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    National Council for Population Development (NCPD) (2019). Demographic and Health Survey 1988-1989 - Kenya [Dataset]. https://dev.ihsn.org/nada/catalog/73315
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    Dataset updated
    Apr 25, 2019
    Dataset authored and provided by
    National Council for Population Development (NCPD)
    Time period covered
    1988 - 1989
    Area covered
    Kenya
    Description

    Abstract

    The Kenya Demographic and Health Survey (KDHS) was conducted between December 1988 and May 1989 to collect data regarding fertility, family planning and maternal and child health. The survey covered 7,150 women aged 15-49 and a subsample of 1,116 husbands of these women, selected from a sample covering 95 percent of the population. The purpose of the survey was to provide planners and policymakers with data useful in making informed programme decisions.

    OBJECTIVES

    On March 1, 1988, 'on behalf of the Government of Kenya, the National Council for Population and Development (NCPD) signed an agreement with the Institute for Resource Development (IRD) to carry out the Kenya Demographic and Health Survey (KDHS).

    The KDHS is intended to serve as a source of population and health data for policymakers and for the research community. In general, the objectives of the KDHS are to: assess the overall demographic situation in Kenya, assist in the evaluation of the population and health programmes in Kenya, advance survey methodology, and assist the NCPD strengthen and improve its technical skills to conduct demographic and health surveys.

    The KDHS was specifically designed to: - provide data on the family planning and fertility behaviour of the Kcnyan population to enable the NCPD to evaluate and enhance the National Family Planning Programme, - measure changes in fertility and contraceptive prevalence and at the same time study the factors which affect these changes, such as marriage patterns, urban/rural residence, availability of contraception, breastfeeding habits and other socioeconomic factors, and - examine the basic indicators of maternal and child health in Kenya.

    SUMMARY OF FINDINGS

    The survey data can also be used to evaluate Kenya's efforts to reduce fertility and the picture that emerges shows significant strides have been made toward this goal. KDHS data provide the first evidence of a major decline in fertility. If young women continue to have children at current rates, they will have an average of 6.7 births in their lifetime. This is down considerably from the average of 7.5 births for women now at the end of their childbearing years. The fertility rate in 1984 was estimated at 7.7 births per woman.

    A major cause of the decline in fertility is increased use of family pIanning. Twenty-seven percent of married women in Kenya are currcntly using a contraceptive method, compared to 17 percent in 1984. Although periodic abstinence continues to he the most common method (8 percent), of interest to programme planners is the fact that two-thirds of marricd women using contraception have chosen a modern method--either the pill (5 percent) or female sterilisation (5 percent). Contraccptive use varies by province, with those closest to Nairobi having the highest levels. Further evidence of the success in promoting family planning is the fact that more than 90 percent of married women know at least one modern method of contraception (and where to obtain it), and 45 percent have used a contraceptive method at some time in their life.

    The survey indicates a high level of knowledge, use and approval of family planning by husbands of interviewed women. Ninety-three percent of husbands know a modern method of family planning. Sixty-five percent of husbands have used a method at some time and almost 49 percent are currently using a method, half of which are modern methods. Husbands in Kenya are strongly supportive of family planning. Ninety-one percent of those surveyed approve of family planning use by couples, compared to 88 percent of married women.

    If couples are able to realise their childbearing preferences, fertility may continue to decline in the future. One half of married women say that they want no more children; another 26 percent want to wait at least two years before having another child. Husbands report similar views on limiting births--one-half say they want no more children. The desire to limit childbearing appears to be greater in Kenya than in other subSaharan countries. In Botswana and Zimbabwe, for example, only 33 percent of married women want no more children. Another indicator of possible future decline in fertility in Kenya is the decrease in ideal family size. According to the KDHS, the mean ideal family size declined from 5.8 in 1984 to 4.4 in 1989.

    The KDHS indicates that in the area of health, government programmes have been effective in providing health services for womcn and children. Eight in ten births benefit from ante-natal care from a doctor, nurse, or midwife and one-half of births are assisted at delivery by a doctor, nurse, or midwife. At least 44 percent of children 12-23 months of age are fully immunised against the major childhood diseases, Almost all children benefit from an extended period of breastfeeding. The average duration of breastfeeding is 19 months and the practice does not appear to be waning among either younger women or urban women. Another encouraging piece of information is the high level of ORT (oral rehydration therapy) use for treating childhood diarrhoea. Among children under five reported to have had an episode of diarrhoea in the two weeks before the survey, half were treated with a homemade solution and almost one-quarter were given a solution prepared from commercially prepared packets.

    The survey indicates several areas where there is room for improvement. Although young women are marrying later, many are still having births at young ages. More than 20 percent of teen-age girls have had at least one child and 7 percent were pregnant at the time of the survey. There is also evidence of an unmet need for family planning services. Of the births occurring in the 12 months before the survey, over half were either mistimed or unwanted; one fifth occurred less than 24 months after a previous birth.

    Geographic coverage

    The 1989 KDHS sample is national in scope, with the exclusion of all three districts in North Eastern Province and four other northern districts (Samburu and Turkana in Rift Valley Province and Isiolo and 4 Marsabit in Eastern Province). Together the excluded areas account for less than 4 percent of Kenya's population.

    Analysis unit

    • Household
    • Women age 15-49
    • Men age not specified

    Universe

    The population covered by the 1989 KDHS is defined as the universe of all women age 15-49 in Kenya and all husband living in the household.

    Kind of data

    Sample survey data

    Sampling procedure

    The sample for the KDHS is based on the National Sample Survey and Ewduation Programme (NASSEP) master sample maintained by the CBS. The KDHS sample is national in coverage, with the exclusion of North Eastern Province and four northern districts which together account for only about five percent of Kenya's population. The KDHS sample was designed to produce completed interviews with 7,500 women aged 15-49 and with a subsample of 1,000 husbands of these women.

    The NASSEP master sample is a two-stage design, stratified by urban-rural residence, and within the rural stratum, by individual district. In the first stage, 1979 census enumeration areas (EAs) were selected with probability proportional to size. The selected EAs were segmented into the expected number of standard-sized clusters, one of which was selected at random to form the NASSEP cluster. The selected clusters were then mapped and listed by CBS field staff. In rural areas, household listings made betwecn 1984 and 1985 were used to select the KDHS households, while KDHS pretest staff were used to relist households in the selected urban clusters.

    Despite the emphasis on obtaining district-level data for phoning purposes, it was decided that reliable estimates could not be produced from the KDHS for all 32 districts in NASSEP, unless the sample were expanded to an unmanageable size. However, it was felt that reliable estimates of certain variables could be produced lbr the rural areas in the 13 districts that have been initially targeted by the NCPD: Kilifi, Machakos, Meru, Nyeri, Murang'a, Kirinyaga, Kericho, Uasin Gishu, South Nyanza, Kisii, Siaya, Kakamega, and Bungoma. Thus, all 24 rural clusters in the NASSEP were selected for inclusion in the KDHS sample in these 13 districts. About 450 rural households were selected in each of these districts, just over 1000 rural households in other districts, and about 3000 households in urban areas, for a total of almost 10,000 households. Sample weights were used to compensate for the unequal probability of selection between strata, and weighted figures are used throughout the remainder of this report.

    Mode of data collection

    Face-to-face

    Research instrument

    The KDHS utilised three questionnaires: a household questionnaire, a woman's questionnaire, and a husband's questionnaire. The first two were based on the DHS Programme's Model "B" Questionnaire that was designed for low contraceptive prevalence countries, while the husband's questionnaire was based on similar questionnaires used in the DHS surveys in Ghana and Burundi. A two-day seminar was held in Nyeri in November 1987 to develop the questionnaire design. Participants included representatives from the Central Bureau of Statistics (CBS), the Population Studies Research Institute at the University of Nairobi, the Community Health Department of Kenyatta Hospital, and USAID. The decision to include a survey of husbands was based on the recommendation of the seminar participants. The questionnaires were subsequently translated into eight local languages (Kalenjin, Kamba, Kikuyu, Kisii, Luhya, Luo, Meru and Mijikenda), in addition to Kiswahili.

    Cleaning operations

    Data

  7. 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

  8. Kenya Demographic and Health Survey 2014 - Kenya

    • statistics.knbs.or.ke
    Updated Feb 15, 2023
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    Kenya National Bureau of Statistics (KNBS) (2023). Kenya Demographic and Health Survey 2014 - Kenya [Dataset]. https://statistics.knbs.or.ke/nada/index.php/catalog/65
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    Dataset updated
    Feb 15, 2023
    Dataset provided by
    Kenya National Bureau of Statistics
    Authors
    Kenya National Bureau of Statistics (KNBS)
    Time period covered
    2014
    Area covered
    Kenya
    Description

    Abstract

    The 2014 Kenya Demographic and Health Survey (KDHS) provides information to help monitor and evaluate population and health status in Kenya. The survey, which follows up KDHS surveys conducted in 1989, 1993, 1998, 2003, and 2008-09, is of special importance for several reasons. New indicators not collected in previous KDHS surveys, such as noncommunicable diseases, fistula, and men's experience of domestic violence, are included. Also, it is the first national survey to provide estimates for demographic and health indicators at the county level. Following adoption of a constitution in Kenya in 2010 and devolution of administrative powers to the counties, the new 2014 KDHS data should be valuable to managers and planners. The 2014 KDHS has specifically collected data to estimate fertility, to assess childhood, maternal, and adult mortality, to measure changes in fertility and contraceptive prevalence, to examine basic indicators of maternal and child health, to estimate nutritional status of women and children, to describe patterns of knowledge and behaviour related to the transmission of HIV and other sexually transmitted infections, and to ascertain the extent and pattern of domestic violence and female genital cutting. Unlike the 2003 and 2008-09 KDHS surveys, this survey did not include HIV and AIDS testing. HIV prevalence estimates are available from the 2012 Kenya AIDS Indicator Survey (KAIS), completed prior to the 2014 KDHS. Results from the 2014 KDHS show a continued decline in the total fertility rate (TFR). Fertility decreased from 4.9 births per woman in 2003 to 4.6 in 2008-09 and further to 3.9 in 2014, a one-child decline over the past 10 years and the lowest TFR ever recorded in Kenya. This is corroborated by the marked increase in the contraceptive prevalence rate (CPR) from 46 percent in 2008-09 to 58 percent in the current survey. The decline in fertility accompanies a marked decline in infant and child mortality. All early childhood mortality rates have declined between the 2003 and 2014 KDHS surveys. Total under-5 mortality declined from 115 deaths per 1,000 live births in the 2003 KDHS to 52 deaths per 1,000 live births in the 2014 KDHS. The maternal mortality ratio is 362 maternal deaths per 100,000 live births for the seven-year period preceding the survey; however, this is not statistically different from the ratios reported in the 2003 and 2008-09 KDHS surveys and does not indicate any decline over time. The proportion of mothers who reported receiving antenatal care from a skilled health provider increased from 88 percent to 96 percent between 2003 and 2014. The percentage of births attended by a skilled provider and the percentage of births occurring in health facilities each increased by about 20 percentage points between 2003 and 2014. The percentage of children age 12-23 months who have received all basic vaccines increased slightly from the 77 percent observed in the 2008-09 KDHS to 79 percent in 2014. Six in ten households (59 percent) own at least one insecticide-treated net, and 48 percent of Kenyans have access to one. In malaria endemic areas, 39 percent of women received the recommended dosage of intermittent preventive treatment for malaria during pregnancy. Awareness of AIDS is universal in Kenya; however, only 56 percent of women and 66 percent of men have comprehensive knowledge about HIV and AIDS prevention and transmission. The 2014 KDHS was conducted as a joint effort by many organisations. The Kenya National Bureau of Statistics (KNBS) served as the implementing agency by providing guidance in the overall survey planning, development of survey tools, training of personnel, data collection, processing, analysis, and dissemination of the results. The Bureau would like to acknowledge and appreciate the institutions and agencies for roles they played that resulted in the success of this exercise: Ministry of Health (MOH), National AIDS Control Council (NACC), National Council for Population and Development (NCPD), Kenya Medical Research Institute (KEMRI), Ministry of Labour, Social Security and Services, United States Agency for International Development (USAID/Kenya), ICF International, United Nations Fund for Population Activities (UNFPA), the United Kingdom Department for International Development (DfID), World Bank, Danish International Development Agency (DANIDA), United Nations Children's Fund (UNICEF), German Development Bank (KfW), World Food Programme (WFP), Clinton Health Access Initiative (CHAI), Micronutrient Initiative (MI), US Centers for Disease Control and Prevention (CDC), Japan International Cooperation Agency (JICA), Joint United Nations Programme on HIV/AIDS (UNAIDS), and the World Health Organization (WHO). The management of such a huge undertaking was made possible through the help of a signed memorandum of understanding (MoU) by all the partners and the creation of active Steering and Technical Committees.

    Geographic coverage

    County, Urban, Rural and National

    Analysis unit

    Households

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sample for the 2014 KDHS was drawn from a master sampling frame, the Fifth National Sample Survey and Evaluation Programme (NASSEP V). This is a frame that the KNBS currently operates to conduct household-based surveys throughout Kenya. Development of the frame began in 2012, and it contains a total of 5,360 clusters split into four equal subsamples. These clusters were drawn with a stratified probability proportional to size sampling methodology from 96,251 enumeration areas (EAs) in the 2009 Kenya Population and Housing Census. The 2014 KDHS used two subsamples of the NASSEP V frame that were developed in 2013. Approximately half of the clusters in these two subsamples were updated between November 2013 and September 2014. Kenya is divided into 47 counties that serve as devolved units of administration, created in the new constitution of 2010. During the development of the NASSEP V, each of the 47 counties was stratified into urban and rural strata; since Nairobi county and Mombasa county have only urban areas, the resulting total was 92 sampling strata. The 2014 KDHS was designed to produce representative estimates for most of the survey indicators at the national level, for urban and rural areas separately, at the regional (former provincial1) level, and for selected indicators at the county level. In order to meet these objectives, the sample was designed to have 40,300 households from 1,612 clusters spread across the country, with 995 clusters in rural areas and 617 in urban areas. Samples were selected independently in each sampling stratum, using a two-stage sample design. In the first stage, the 1,612 EAs were selected with equal probability from the NASSEP V frame. The households from listing operations served as the sampling frame for the second stage of selection, in which 25 households were selected from each cluster. The interviewers visited only the preselected households, and no replacement of the preselected households was allowed during data collection. The Household Questionnaire and the Woman's Questionnaire were administered in all households, while the Man's Questionnaire was administered in every second household. Because of the non-proportional allocation to the sampling strata and the fixed sample size per cluster, the survey was not self-weighting. The resulting data have, therefore, been weighted to be representative at the national, regional, and county levels.

    Sampling deviation

    Not available

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The 2014 KDHS used a household questionnaire, a questionnaire for women age 15-49, and a questionnaire for men age 15-54. These instruments were based on the model questionnaires developed for The DHS Program, the questionnaires used in the previous KDHS surveys, and the current information needs of Kenya. During the development of the questionnaires, input was sought from a variety of organisations that are expected to use the resulting data. A two-day workshop involving key stakeholders was held to discuss the questionnaire design. Producing county-level estimates requires collecting data from a large number of households within each county, resulting in a considerable increase in the sample size from 9,936 households in the 2008-09 KDHS to 40,300 households in 2014. A survey of this magnitude introduces concerns related to data quality and overall management. To address these concerns, reduce the length of fieldwork, and limit interviewer and respondent fatigue, a decision was made to not implement the full questionnaire in every household and, in so doing, to collect only priority indicators at the county level. Stakeholders generated a list of these priority indicators. Short household and woman's questionnaires were then designed based on the full questionnaires; the short questionnaires contain the subset of questions from the full questionnaires required to measure the priority indicators at the county level. Thus, a total of five questionnaires were used in the 2014 KDHS: (1) a full Household Questionnaire, (2) a short Household Questionnaire, (3) a full Woman's Questionnaire, (4) a short Woman's Questionnaire, and (5) a Man's Questionnaire. The 2014 KDHS sample was divided into halves. In one half, households were administered the full Household Questionnaire, the full Woman's Questionnaire, and the Man's Questionnaire. In the other half, households were administered the short Household Questionnaire and the short Woman's Questionnaire. Selection of these subsamples was done at the household level-within a cluster, one in every two

  9. w

    Kenya - Demographic and Health Survey 1993 - Dataset - waterdata

    • wbwaterdata.org
    Updated Mar 16, 2020
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    (2020). Kenya - Demographic and Health Survey 1993 - Dataset - waterdata [Dataset]. https://wbwaterdata.org/dataset/kenya-demographic-and-health-survey-1993
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    Dataset updated
    Mar 16, 2020
    License

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

    Area covered
    Kenya
    Description

    The 1993 Kenya Demographic and Health Survey (KDHS) was a nationally representative survey of 7,540 women age 15-49 and 2,336 men age 20-54. The KDHS was designed to provide information on levels and trends of fertility, infant and child mortality, family planning knowledge and use, maternal and child health, and knowledge of AIDS. In addition, the male survey obtained data on men's knowledge and attitudes towards family planning and awareness of AIDS. The data are intended for use by programme managers and policymakers to evaluate and improve family planning and matemal and child health programmes. Fieldwork for the KDHS took place from mid-February until mid-August 1993. All areas of Kenya were covered by the survey, except for seven northem districts which together contain less than four percent of the country's population. The KDHS was conducted by the National Council for Population and Development (NCPD) and the Central Bureau of Statistics of the Government of Kenya. Macro International Inc. provided financial and technical assistance to the project through the intemational Demographic and Health Surveys (DHS) contract with the U.S. Agency for International Development. OBJECTIVES The KDHS is intended to serve as a source of population and health data for policymakers and the research community. It was designed as a follow-on to the 1989 KDHS, a national-level survey of similar size that was implemented by the same organisations. In general, the objectives of KDHS are to: assess the overall demographic situation in Kenya, assist in the evaluation of the population and health programmes in Kenya, advance survey methodology, and assist the NCPD to strengthen and improve its technical skills to conduct demographic and health surveys. The KDHS was specifically designed to: provide data on the family planning and fertility behaviour of the Kenyan population to enable the NCPD to evaluate and enhance the National Family Planning Programme, measure changes in fertility and contraceptive prevalence and at the same time study the factors which affect these changes, such as marriage patterns, urban/rural residence, availability of contraception, breastfeeding habits and other socioeconomic factors, and examine the basic indicators of maternal and child health in Kenya. KEY FINDINGS The 1993 KDHS reinforces evidence of a major decline in fertility which was first revealed by the findings of the 1989 KDHS. Fertility continues to decline and family planning use has increased. However, the disparity between knowledge and use of family planning remains quite wide. There are indications that infant and under five child mortality rates are increasing, which in part might be attributed to the increase in AIDS prevalence.

  10. H

    Education, HIV, and Early Fertility: Experimental Evidence from Kenya

    • dataverse.harvard.edu
    Updated Nov 13, 2019
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    Esther Duflo; Pascaline Dupas; Michael Kremer (2019). Education, HIV, and Early Fertility: Experimental Evidence from Kenya [Dataset]. http://doi.org/10.7910/DVN/TZG4WJ
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 13, 2019
    Dataset provided by
    Harvard Dataverse
    Authors
    Esther Duflo; Pascaline Dupas; Michael Kremer
    License

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

    Area covered
    Kenya, Butere-Mumias, Western Province, Bungoma
    Dataset funded by
    MacArthur Foundation
    National Institute of Health
    Partnership for Child Developmenthttp://www.imperial.ac.uk/partnership-for-child-development
    World Bank
    Hewlett Foundation
    Nike Foundation
    Description

    A seven-year randomized evaluation suggests education subsidies reduce adolescent girls’ dropout, pregnancy, and marriage but not sexually transmitted infection (STI). The government’s HIV curriculum, which stresses abstinence until marriage, does not reduce pregnancy or STI. Both programs combined reduce STI more, but cut dropout and pregnancy less, than education subsidies alone. These results are inconsistent with a model of schooling and sexual behavior in which both pregnancy and STI are determined by one factor (unprotected sex), but consistent with a two-factor model in which choices between committed and casual relationships also affect these outcomes

  11. d

    Kenya - Demographic and Health Survey 2008-2009 - Dataset - waterdata

    • waterdata3.staging.derilinx.com
    Updated Mar 16, 2020
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    (2020). Kenya - Demographic and Health Survey 2008-2009 - Dataset - waterdata [Dataset]. https://waterdata3.staging.derilinx.com/dataset/kenya-demographic-and-health-survey-2008-2009
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    Dataset updated
    Mar 16, 2020
    License

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

    Area covered
    Kenya
    Description

    The 2008-09 Kenya Demographic and Health Survey (KDHS) is a population and health survey that Kenya conducts every five years. It was designed to provide data to monitor the population and health situation in Kenya and also to be used as a follow-up to the previous KDHS surveys in 1989, 1993, 1998, and 2003. From the current survey, information was collected on fertility levels; marriage; sexual activity; fertility preferences; awareness and use of family planning methods; breastfeeding practices; nutritional status of women and young children; childhood and maternal mortality; maternal and child health; and awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections. The 2008-09 KDHS is the second survey to collect data on malaria and the use of mosquito nets, domestic violence, and HIV testing of adults. The specific objectives of the 2008-09 KDHS were to: Provide data, at the national and provincial levels, that allow the derivation of demographic rates, particularly fertility and childhood mortality rates, to be used to evaluate the achievements of the current national population policy for sustainable development Measure changes in fertility and contraceptive prevalence use and study the factors that affect these changes, such as marriage patterns, desire for children, availability of contraception, breastfeeding habits, and other important social and economic factors Examine the basic indicators of maternal and child health in Kenya, including nutritional status, use of antenatal and maternity services, treatment of recent episodes of childhood illness, use of immunisation services, use of mosquito nets, and treatment of children and pregnant women for malaria Describe the patterns of knowledge and behaviour related to the transmission of HIV/AIDS and other sexually transmitted infections Estimate adult and maternal mortality ratios at the national level Ascertain the extent and pattern of domestic violence and female genital cutting in the country Estimate the prevalence of HIV infection at the national and provincial levels and by urban-rural residence, and use the data to corroborate the rates from the sentinel surveillance system The 2008-09 KDHS information provides data to assist policymakers and programme implementers as they monitor and evaluate existing programmes and design new strategies for demographic, social, and health policies in Kenya. The data will be useful in many ways, including the monitoring of the country’s achievement of the Millennium Development Goals. As in 2003, the 2008-09 KDHS survey was designed to cover the entire country, including the arid and semi-arid districts, and especially those areas in the northern part of the country that were not covered in the earlier KDHS surveys. The survey collected information on demographic and health issues from a sample of women at the reproductive age of 15-49 and from a sample of men age 15-54 years in a one-in-two subsample of households.

  12. Demographic and Health Survey 2008-2009 - Kenya

    • datacatalog.ihsn.org
    • dev.ihsn.org
    • +2more
    Updated Mar 29, 2019
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    Kenya National Bureau of Statistics (KNBS) (2019). Demographic and Health Survey 2008-2009 - Kenya [Dataset]. https://datacatalog.ihsn.org/catalog/1465
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    Dataset updated
    Mar 29, 2019
    Dataset provided by
    Kenya National Bureau of Statistics
    Authors
    Kenya National Bureau of Statistics (KNBS)
    Time period covered
    2008 - 2009
    Area covered
    Kenya
    Description

    Abstract

    The 2008-09 Kenya Demographic and Health Survey (KDHS) is a population and health survey that Kenya conducts every five years. It was designed to provide data to monitor the population and health situation in Kenya and also to be used as a follow-up to the previous KDHS surveys in 1989, 1993, 1998, and 2003.

    From the current survey, information was collected on fertility levels; marriage; sexual activity; fertility preferences; awareness and use of family planning methods; breastfeeding practices; nutritional status of women and young children; childhood and maternal mortality; maternal and child health; and awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections. The 2008-09 KDHS is the second survey to collect data on malaria and the use of mosquito nets, domestic violence, and HIV testing of adults.

    The specific objectives of the 2008-09 KDHS were to: - Provide data, at the national and provincial levels, that allow the derivation of demographic rates, particularly fertility and childhood mortality rates, to be used to evaluate the achievements of the current national population policy for sustainable development - Measure changes in fertility and contraceptive prevalence use and study the factors that affect these changes, such as marriage patterns, desire for children, availability of contraception, breastfeeding habits, and other important social and economic factors - Examine the basic indicators of maternal and child health in Kenya, including nutritional status, use of antenatal and maternity services, treatment of recent episodes of childhood illness, use of immunisation services, use of mosquito nets, and treatment of children and pregnant women for malaria - Describe the patterns of knowledge and behaviour related to the transmission of HIV/AIDS and other sexually transmitted infections - Estimate adult and maternal mortality ratios at the national level - Ascertain the extent and pattern of domestic violence and female genital cutting in the country - Estimate the prevalence of HIV infection at the national and provincial levels and by urban-rural residence, and use the data to corroborate the rates from the sentinel surveillance system

    The 2008-09 KDHS information provides data to assist policymakers and programme implementers as they monitor and evaluate existing programmes and design new strategies for demographic, social, and health policies in Kenya. The data will be useful in many ways, including the monitoring of the country’s achievement of the Millennium Development Goals.

    As in 2003, the 2008-09 KDHS survey was designed to cover the entire country, including the arid and semi-arid districts, and especially those areas in the northern part of the country that were not covered in the earlier KDHS surveys. The survey collected information on demographic and health issues from a sample of women at the reproductive age of 15-49 and from a sample of men age 15-54 years in a one-in-two subsample of households.

    Geographic coverage

    National

    Analysis unit

    • Household
    • Children under five years
    • Women age 15-49
    • Men age 15-54

    Kind of data

    Sample survey data

    Sampling procedure

    The survey is household-based, and therefore the sample was drawn from the population residing in households in the country. A representative sample of 10,000 households was drawn for the 2008-09 KDHS. This sample was constructed to allow for separate estimates for key indicators for each of the eight provinces in Kenya, as well as for urban and rural areas separately. Compared with the other provinces, fewer households and clusters were surveyed in North Eastern province because of its sparse population. A deliberate attempt was made to oversample urban areas to get enough cases for analysis. As a result of these differing sample proportions, the KDHS sample is not self-weighting at the national level; consequently, all tables except those concerning response rates are based on weighted data.

    The KNBS maintains master sampling frames for household-based surveys. The current one is the fourth National Sample Survey and Evaluation Programme (NASSEP IV), which was developed on the platform of a two-stage sample design. The 2008-09 KDHS adopted the same design, and the first stage involved selecting data collection points ('clusters') from the national master sample frame. A total of 400 clusters-133 urban and 267 rural-were selected from the master frame. The second stage of selection involved the systematic sampling of households from an updated list of households. The Bureau developed the NASSEP frame in 2002 from a list of enumeration areas covered in the 1999 population and housing census. A number of clusters were updated for various surveys to provide a more accurate selection of households. Included were some of the 2008-09 KDHS clusters that were updated prior to selection of households for the data collection.

    All women age 15-49 years who were either usual residents or visitors present in sampled households on the night before the survey were eligible to be interviewed in the survey. In addition, in every second household selected for the survey, all men age 15-54 years were also eligible to be interviewed. All women and men living in the households selected for the Men's Questionnaire and eligible for the individual interview were asked to voluntarily give a few drops of blood for HIV testing.

    Note: See detailed description of the sample design in Appendix A of the survey final report.

    Mode of data collection

    Face-to-face

    Research instrument

    Three questionnaires were used to collect the survey data: the Household, Women’s, and Men’s Questionnaires. The contents of these questionnaires were based on model questionnaires developed by the MEASURE DHS programme that underwent only slight adjustments to reflect relevant issues in Kenya. Adjustment was done through a consultative process with all the relevant technical institutions, government agencies, and local and international organisations. The three questionnaires were then translated from English into Kiswahili and 10 other local languages (Kalenjin, Kamba, Kikuyu, Kisii, Luhya, Luo, Maasai, Meru, Mijikenda, and Somali). The questionnaires were further refined after the pretest and training of the field staff.

    In each of the sampled households, the Household Questionnaire was the first to be administered and was used to list all the usual members and visitors. Basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women age 15-49 and men age 15-54 who were eligible for the individual interviews. The questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor, walls, and roof of the house, ownership of various durable goods, ownership of agricultural land, ownership of domestic animals, and ownership and use of mosquito nets. In addition, this questionnaire was used to capture information on height and weight measurements of women age 15-49 years and children age five years and below, and, in households eligible for collection of blood samples, to record the respondents’ consent to voluntarily give blood samples. A detailed description of HIV testing procedures is given in Section 1.10 below.

    The Women’s Questionnaire was used to capture information from all women age 15-49 years and covered the following topics: - Respondent’s background characteristics (e.g., education, residential history, media exposure) - Reproductive history - Knowledge and use of family planning methods - Antenatal, delivery, and postnatal care - Breastfeeding - Immunisation, nutrition, and childhood illnesses - Fertility preferences - Husband’s background characteristics and woman’s work - Marriage and sexual activity - Infant and child feeding practices - Childhood mortality - Awareness and behaviour about HIV/AIDS and other sexually transmitted diseases - Knowledge of tuberculosis - Health insurance - Adult and maternal mortality - Domestic violence - Female genital cutting

    The set of questions on domestic violence sought to obtain information on women’s experience of violence. The questions were administered to one woman per household. In households with more eligible women, special procedures (use of a ‘Kish grid’) were followed to ensure that the woman interviewed about domestic violence was randomly selected.

    The Men’s Questionnaire was administered to all men age 15-54 years living in every second household in the sample. The Men’s Questionnaire collected information similar to that collected in the Women’s Questionnaire, but it was shorter because it did not contain questions on reproductive history, maternal and child health, nutrition, maternal mortality, and domestic violence.

    Two pilot projects were conducted in 12 districts for the KDHS, the first from July 1-7, 2008, and the second from October 13-17, 2008, to test the questionnaires, which were written in English and then translated into eleven other languages. The pilot was repeated because the first pilot did not include the HIV blood testing component. Twelve teams (one for each language) were formed, each with one female interviewer, one male interviewer, and one health worker. A total of 260 households were covered in the pilots. The lessons learnt from the pilot surveys were used to finalise the survey instruments and set up strong, logistical arrangements to ensure the success of the survey.

    Response

  13. Kenya Demographic and Health Survey 2022 - Kenya

    • statistics.knbs.or.ke
    Updated Sep 10, 2024
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    Kenya National Bureau of Statistics (2024). Kenya Demographic and Health Survey 2022 - Kenya [Dataset]. https://statistics.knbs.or.ke/nada/index.php/catalog/128
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    Dataset updated
    Sep 10, 2024
    Dataset authored and provided by
    Kenya National Bureau of Statistics
    Time period covered
    2022
    Area covered
    Kenya
    Description

    Abstract

    The 2022 Kenya Demographic and Health Survey (2022 KDHS) is the seventh DHS survey implemented in Kenya. The Kenya National Bureau of Statistics (KNBS) in collaboration with the Ministry of Health (MoH) and other stakeholders implemented the survey. Survey planning began in late 2020 with data collection taking place from February 17 to July 19, 2022. ICF provided technical assistance through The DHS Program, which is funded by the United States Agency for International Development (USAID) and offers financial support and technical assistance for population and health surveys in countries worldwide. Other agencies and organizations that facilitated the successful implementation of the survey through technical or financial support were the Bill & Melinda Gates Foundation, the World Bank, the United Nations Children's Fund (UNICEF), the United Nations Population Fund (UNFPA), Nutrition International, the World Food Programme (WFP), the United Nations Entity for Gender Equality and the Empowerment of Women (UN Women), the World Health Organization (WHO), the Clinton Health Access Initiative, and the Joint United Nations Programme on HIV/AIDS (UNAIDS).

    SURVEY OBJECTIVES The primary objective of the 2022 KDHS is to provide up-to-date estimates of demographic, health, and nutrition indicators to guide the planning, implementation, monitoring, and evaluation of population and health-related programs at the national and county levels. The specific objectives of the 2022 KDHS are to: Estimate fertility levels and contraceptive prevalence Estimate childhood mortality Provide basic indicators of maternal and child health Estimate the Early Childhood Development Index (ECDI) Collect anthropometric measures for children, women, and men Collect information on children's nutrition Collect information on women's dietary diversity Obtain information on knowledge and behavior related to transmission of HIV and other sexually transmitted infections (STIs) Obtain information on noncommunicable diseases and other health issues Ascertain the extent and patterns of domestic violence and female genital mutilation/cutting

    Geographic coverage

    National coverage

    Analysis unit

    Household, individuals, county and national level

    Universe

    The survey covered sampled households

    Sampling procedure

    The sample for the 2022 KDHS was drawn from the Kenya Household Master Sample Frame (K-HMSF). This is the frame that KNBS currently operates to conduct household-based sample surveys in Kenya. In 2019, Kenya conducted a Population and Housing Census, and a total of 129,067 enumeration areas (EAs) were developed. Of these EAs, 10,000 were selected with probability proportional to size to create the K-HMSF. The 10,000 EAs were randomized into four equal subsamples. The survey sample was drawn from one of the four subsamples. The EAs were developed into clusters through a process of household listing and geo-referencing. To design the frame, each of the 47 counties in Kenya was stratified into rural and urban strata, resulting in 92 strata since Nairobi City and Mombasa counties are purely urban.

    The 2022 KDHS was designed to provide estimates at the national level, for rural and urban areas, and, for some indicators, at the county level. Given this, the sample was designed to have 42,300 households, with 25 households selected per cluster, resulting into 1,692 clusters spread across the country with 1,026 clusters in rural areas and 666 in urban areas.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    Eight questionnaires were used for the 2022 KDHS: 1. A full Household Questionnaire 2. A short Household Questionnaire 3. A full Woman's Questionnaire 4. A short Woman's Questionnaire 5. A Man's Questionnaire 6. A full Biomarker Questionnaire 7. A short Biomarker Questionnaire 8. A Fieldworker Questionnaire.

    The Household Questionnaire collected information on: o Background characteristics of each person in the household (for example, name, sex, age, education, relationship to the household head, survival of parents among children under age 18) o Disability o Assets, land ownership, and housing characteristics o Sanitation, water, and other environmental health issues o Health expenditures o Accident and injury o COVID-19 (prevalence, vaccination, and related deaths) o Household food consumption

    The Woman's Questionnaire was used to collect information from women age 15-49 on the following topics: o Socioeconomic and demographic characteristics o Reproduction o Family planning o Maternal health care and breastfeeding o Vaccination and health of children o Children's nutrition o Woman's dietary diversity o Early childhood development o Marriage and sexual activity o Fertility preferences o Husbands' background characteristics and women's employment activity o HIV/AIDS, other sexually transmitted infections (STIs), and tuberculosis (TB) o Other health issues o Early Childhood Development Index 2030 o Chronic diseases o Female genital mutilation/cutting o Domestic violence

    The Man's Questionnaire was administered to men age 15-54 living in the households selected for long Household Questionnaires. The questionnaire collected information on: o Socioeconomic and demographic characteristics o Reproduction o Family planning o Marriage and sexual activity o Fertility preferences o Employment and gender roles o HIV/AIDS, other STIs, and TB o Other health issues o Chronic diseases o Female genital mutilation/cutting o Domestic violence

    The Biomarker Questionnaire collected information on anthropometry (weight and height). The long Biomarker Questionnaire collected anthropometry measurements for children age 0-59 months, women age 15-49, and men age 15-54, while the short questionnaire collected weight and height measurements only for children age 0-59 months.

    The Fieldworker Questionnaire was used to collect basic background information on the people who collected data in the field. This included team supervisors, interviewers, and biomarker technicians.

    All questionnaires except the Fieldworker Questionnaire were translated into the Swahili language to make it easier for interviewers to ask questions in a language that respondents could understand.

    Cleaning operations

    Data were downloaded from the central servers and checked against the inventory of expected returns to account for all data collected in the field. SyncCloud was also used to generate field check tables to monitor progress and flag any errors, which were communicated back to the field teams for correction.

    Secondary editing was done by members of the central office team, who resolved any errors that were not corrected by field teams during data collection. A CSPro batch editing tool was used for cleaning and tabulation during data analysis.

    Response rate

    A total of 42,022 households were selected for the sample, of which 38,731 (92%) were found to be occupied. Among the occupied households, 37,911 were successfully interviewed, yielding a response rate of 98%. The response rates for urban and rural households were 96% and 99%, respectively. In the interviewed households, 33,879 women age 15-49 were identified as eligible for individual interviews. Interviews were completed with 32,156 women, yielding a response rate of 95%. The response rates among women selected for the full and short questionnaires were the similar (95%). In the households selected for the male survey, 16,552 men age 15-54 were identified as eligible for individual interviews and 14,453 were successfully interviewed, yielding a response rate of 87%.

  14. o

    2014 Kenya Demographic and Health Survey - Dataset - openAFRICA

    • open.africa
    Updated Mar 27, 2016
    + more versions
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    (2016). 2014 Kenya Demographic and Health Survey - Dataset - openAFRICA [Dataset]. https://open.africa/dataset/2014-kenya-demographic-and-health-survey
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    Dataset updated
    Mar 27, 2016
    Area covered
    Kenya
    Description

    The 2014 Kenya Demographic and Health Survey (2014 KDHS) samples over 40,000 households on their composition and health issues. It covers household characteristics, education and employment, marriage and sexual activity, fertility levels and preferences, awareness and use of family planning methods, maternal and child health and survival, nutritional status, ownership and use of mosquito nets, knowledge and behaviours regarding HIV, domestic violence, female circumcision, and fistula. Carried our every five years this edition carried out the survey at county levels and additionally added key insights into new health related conditions. The Objective of the study is to provide information to monitor and evaluate population and health status in Kenya.

  15. East Africa preterm birth initiative birth register data (March 2016 -...

    • zenodo.org
    • explore.openaire.eu
    • +1more
    bin
    Updated Jun 2, 2022
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    Lara Miller; Lara Miller (2022). East Africa preterm birth initiative birth register data (March 2016 - October 2016) [Dataset]. http://doi.org/10.7272/q6833q63
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    binAvailable download formats
    Dataset updated
    Jun 2, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Lara Miller; Lara Miller
    License

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

    Area covered
    Africa
    Description

    Abstract

    Objective: Preterm birth is the primary driver of neonatal mortality worldwide, but it is defined by gestational age (GA) which is challenging to accurately assess in low-resource settings. In a commitment to reducing preterm birth while reinforcing and strengthening facility, routine data sources, the East Africa Preterm Birth Initiative (PTBi-EA) chose eligibility criteria that combined GA and birth weight. This analysis evaluated the quality of the GA data as recorded in maternity registers in PTBi-EA study facilities and the validity of the PTBi-EA eligibility criteria.

    Methods: We conducted a retrospective analysis of maternity register data from March – September 2016. GA data from 23 study facilities in Migori, Kenya and the Busoga Region of Uganda were evaluated for completeness (variable present), consistency (recorded versus calculated GA), and plausibility (falling within the 3rd and 97th birth weight percentiles for GA of the INTERGROWTH-21st Newborn Birth Weight Standards). Preterm birth rates were calculated using: 1) recorded GA <37 weeks, 2) recorded GA <37 weeks, excluding implausible GAs, 3) birth weight <2500g, and 4) PTBi-EA eligibility criteria of <2500g and between 2500g and 3000g if the recorded GA is <37 weeks.

    Results: In both countries, GA was the least recorded variable in the maternity register (77.6%). Recorded and calculated GA (Kenya only) were consistent in 29.5% of births. Implausible GAs accounted for 11.7% of births. The four preterm birth rates were 1) 14.5%, 2) 10.6%, 3) 9.6%, 4) 13.4%.

    Conclusions: Maternity register GA data presented quality concerns in PTBi-EA study sites. The PTBi-EA eligibility criteria of <2500g and between 2500g and 3000g if the recorded GA is <37 weeks adjusted for these concerns by using both birth weight and GA, balancing issues of accuracy and completeness with practical applicability.

  16. M

    Kenya Maternal Mortality Rate

    • macrotrends.net
    csv
    Updated May 31, 2025
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    MACROTRENDS (2025). Kenya Maternal Mortality Rate [Dataset]. https://www.macrotrends.net/global-metrics/countries/ken/kenya/maternal-mortality-rate
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    csvAvailable download formats
    Dataset updated
    May 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, 1985 - Dec 31, 2023
    Area covered
    Kenya
    Description

    Historical chart and dataset showing Kenya maternal mortality rate by year from 1985 to 2023.

  17. f

    Characteristics of women who were married/in-union and completed the...

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Linnea A. Zimmerman; Celia Karp; Mary Thiongo; Peter Gichangi; Georges Guiella; Alison Gemmill; Caroline Moreau; Suzanne O. Bell (2023). Characteristics of women who were married/in-union and completed the baseline and COVID-19 follow-up surveys in Kenya, PMA 2020 (N = 3,095). [Dataset]. http://doi.org/10.1371/journal.pgph.0000147.t002
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Linnea A. Zimmerman; Celia Karp; Mary Thiongo; Peter Gichangi; Georges Guiella; Alison Gemmill; Caroline Moreau; Suzanne O. Bell
    License

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

    Area covered
    Kenya
    Description

    Characteristics of women who were married/in-union and completed the baseline and COVID-19 follow-up surveys in Kenya, PMA 2020 (N = 3,095).

  18. Life expectancy in Kenya from 1870 to 2020

    • statista.com
    Updated Aug 9, 2024
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    Statista (2024). Life expectancy in Kenya from 1870 to 2020 [Dataset]. https://www.statista.com/statistics/1072206/life-expectancy-kenya-historical/
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    Dataset updated
    Aug 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Kenya
    Description

    In 1870, it is estimated that Kenyan life expectancy from birth was just 25.5 years. This low rate was in part the result of several famines and epidemics which ravaged the region throughout the late 1800s, including an epidemic in 1898, which, when combined with the coinciding famine, was estimated to have resulted in the death of over half the population of the country. The life expectancy would further drop in the late 1910s, the result of the 1918 Spanish Flu epidemic, which is estimated to have claimed the lives of over 5.5 percent of Kenya’s population.

    Life expectancy would increase only marginally for much of the late 19th and early 20th centuries, but saw a significant increase in the years following the end of the Second World War. Kenyan life expectancy rose by almost ten years in the late 1940s. Life expectancy would continue to steadily rise for much of the 20th century, particularly so with the implementation of universal healthcare in 1965, before peaking at almost 59 years in 1985. However, beginning in the late-1980s, Kenya would see life expectancy fall significantly until the early 2010s, as the HIV/AIDS epidemic led to a significant increase in mortality across the population. After bottoming out at under 52 years in 2005, life expectancy was able to recover to pre-HIV/AIDS levels by the 2010s. In 2020, Kenya is estimated to have a life expectancy from birth of more than 66 years.

  19. 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
    Zenodohttp://zenodo.org/
    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.

  20. f

    Description and operationalization of fertility intention dimensions.

    • plos.figshare.com
    xls
    Updated Jun 16, 2023
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    Linnea A. Zimmerman; Celia Karp; Mary Thiongo; Peter Gichangi; Georges Guiella; Alison Gemmill; Caroline Moreau; Suzanne O. Bell (2023). Description and operationalization of fertility intention dimensions. [Dataset]. http://doi.org/10.1371/journal.pgph.0000147.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 16, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Linnea A. Zimmerman; Celia Karp; Mary Thiongo; Peter Gichangi; Georges Guiella; Alison Gemmill; Caroline Moreau; Suzanne O. Bell
    License

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

    Description

    Description and operationalization of fertility intention dimensions.

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Statista (2025). Total fertility rate of Kenya 1930-2024 [Dataset]. https://www.statista.com/statistics/1069664/fertility-rate-kenya-historical/
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Total fertility rate of Kenya 1930-2024

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Dataset updated
Jun 3, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Kenya
Description

In 1930, the average woman of childbearing age in Kenya would have had just under seven children over the course of their reproductive years. This rate would steadily increase until the end of the 1960s, peaking at just over eight children per woman in 1970. Following this peak, a combination of strong national and international promotion of family planning in Kenya and an expansion of contraceptive use would lead to a sharp decrease in the fertility rate, resulting in an average of 3.19 children in 2024. Teenage fertility in Kenya In 2022, most teenage pregnancies occurred among 19-year-olds. There is a strong correlation between adolescents who had ever been pregnant and those who had no education. Additionally, those who form part of the highest wealth quintile in the country were less likely to have ever been pregnant. Overall decreasing trends in Kenya’s fertility ratesAlthough fertility rates in Kenya have dropped considerably since 1989, the global fertility rate is significantly lower. Kenyans living in rural areas have a higher total fertility rate compared to those living in urban areas. This is reportedly due to differences in the level of education, the use of contraception, and the desire to live a quality life. Between 1995 and 2000, the decline in fertility rates in Kenya slowed somewhat, partly due to the government prioritizing and reallocating healthcare resources towards combatting the then-emerging HIV/AIDS epidemic. However, resources for contraceptives and family planning commenced once more around 2003, and as a result, the total fertility rate began to fall steadily again.

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