The 1998 Kenya Demographic and Health Survey (KDHS) is a nationally representative survey of 7,881 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.
OBJECTIVES OF THE SURVEY
The principal aim of the 1998 KDHS project is to provide up-to-date information on fertility and childhood mortality levels, nuptiality, fertility preferences, awareness and use of family planning methods, use of maternal and child health services, and knowledge and behaviours related to HIV/AIDS and other sexually-transmitted diseases. It was designed as a follow-on to the 1989 KDHS and 1993 KDHS, national-level surveys of similar size and scope. Ultimately, the 1998 KDHS project seeks to:
- Assess the overall demographic situation in Kenya;
- Assist in the evaluation of the population and reproductive health programmes in Kenya;
- Advance survey methodology; and
- Assist the NCPD to strengthen its capacity to conduct demographic and health surveys.
The 1998 KDHS was specifically designed to:
- Provide data on the family planning and fertility behaviour of the Kenyan population, and to thereby 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, desire for children, availability of contraception, breastfeeding habits, and 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, and use of immunisation services;
- Describe levels and patterns of knowledge and behaviour related to the prevention of AIDS and other sexually transmitted infection;
- Measure adult and maternal mortality at the national level; and
- Ascertain the extent and pattern of female circumcision in the country.
Fertility. The survey results demonstrate a continuation of the fertility transition in Kenya. Marriage. The age at which women and men first marry has risen slowly over the past 20 years. Fertility Preferences. Fifty-three percent of women and 46 percent of men in Kenya do not want to have any more children. Family Planning. Knowledge and use of family planning in Kenya has continued to rise over the last several years. Early Childhood Mortality. Results from the 1998 KDHS data make clear that childhood mortality conditions have worsened in the early-mid 1990s;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). Childhood Immunisation. The KDHS found that 65 percent of children age 12-23 months are fully vaccinated: this includes BCG and measles vaccine, and at least 3 doses of both DPT and polio vaccines. Infant Feeding. Almost all children (98 percent) are breastfed for some period of time; however, only 58 percent are breastfed within the first hour of life, and 86 percent within the first day after birth. Nutritional Status The results indicate that one-third of children in Kenya are stunted (i.e., too short for their age), a condition reflecting chronic malnutrition; and 1 in 16 children are wasted (i.e., very thin), a problem indicating acute or short-term food deficit.
Knowledge, Attitudes and Behaviour regarding HIV/AIDS and Other Sexually Transmitted Infections. As a measure of the increasing toll taken by AIDS on Kenyan society, the percentage of respondents who reported “personally knowing someone who has AIDS or has died from AIDS” has risen from about 40 percent of men and women in the 1993 KDHS to nearly three-quarters of men and women in 1998. Female Circumcision. The results indicate that 38 percent of women age 15-49 in Kenya have been circumcised. The prevalence of FC has however declined significantly over the last 2 decades from about one-half of women in the oldest age cohorts to about one-quarter of women in the youngest cohorts (including daughters age 15+).
Kind of data
Sample survey data
The 1998 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
Unit of analysis
- Women age 15-49
- Men age 20-54
- Children under five
The population covered by the 1998 KDHS is defined as the universe of all women age 15-49 in Kenya and all husband age 20-54 living in the household.
Producers and sponsors
National Council for Population Development (NCPD)
Central Bureau of Statistics (CBS)
Office of the Vice President and Ministry of Planning and National Development
Macro International Inc.
U.S. Agency for International Development
The 1998 Kenya Demographic and Health Survey (KDHS) covered the population residing in private households1 throughout the country, with the exception of sparsely-populated areas in the north of the country that together comprise about 4 percent of the national population. Like the 1993 KDHS, the 1998 KDHS was designed to produce reliable national estimates as well as urban and rural estimates of fertility and childhood mortality rates, contraceptive prevalence, and various other health and population indicators. The design also allows for estimates of selected variables for the rural parts of 15 oversampled districts. Because of the relative rarity of maternal death, the maternal mortality ratio is estimated only at the national level.
In addition to the KDHS principal sample of women, a sub-sample of men age 15-54 were also interviewed to allow for the study of HIV/AIDS, family planning, and other selected topics.
SAMPLING FRAME AND FIRST-STAGE SELECTION
The KDHS utilised a two-stage, stratified sampling approach. The first step involved selecting sample points or "clusters"; the second stage involved selecting households within sample points from a list compiled during a special KDHS household listing exercise.
The 1998 KDHS sample points were the same as those used in the 1993 KDHS, and were selected from a national master sample (i.e., sampling frame) maintained by the Central Bureau of Statistics. From this master sample, called NASSEP-3,3 were drawn 536 sample points: 444 rural and 92 urban.
Selected districts were oversampled in the 1998 KDHS in order to produce reliable estimates for certain variables at the district level. Fifteen districts were thus targeted in both the 1993 and 1998 KDHS: Bungoma, Kakamega, Kericho, Kilifi, Kisii, Machakos, Meru, Murang'a, Nakuru, Nandi, Nyeri, Siaya, South Nyanza, Taita-Taveta, and Uasin Gishu. In addition, Nairobi and Mombasa were targeted. Due to this oversampling, the 1998 KDHS is not self-weighting (i.e., sample weights are needed to produce national estimates). Within each of the 15 oversampled (rural) districts, about 400 households were selected. In all other rural areas combined, about 1,400 households were selected, and 2,000 households were selected in urban areas. The total number of households targeted for selection was thus approximately 9,400 households. Within each sampling stratum, implicit stratification was introduced by ordering the sample points geographically within the hierarchy of administrative units (i.e., sublocation, location, and district within province).
SELECTION OF HOUSEHOLDS AND INDIVIDUALS
The Central Bureau of Statistics began a complete listing of households in all sample points during November 1997 and finished the exercise in February 1998. In the end, listing in 6 of 536 sample points4 could not be completed (and were thus not included in the survey) due to problems of inaccesibility. From these 530 household lists, a systematic sample of households was drawn, with a "take" of 22 households in urban clusters and 17 households in the rural clusters for a total of 9,465 households. All women age 15-49 were targeted for interview in the selected households. Every second household was identified for inclusion in the male survey; in those households, all men age 15-54 were identified and considered eligible for individual interview.
Deviations from sample design
The main reason for individual men and women not being interviewed is their absense from the household over an extended period (i.e., during the days when the survey teams were operating in those sample points). The lower response rates among men (especially in Nairobi) were due to the greater time they spend on trips or otherwise away from the household (e.g., work, social activity).
A total of 9,465 households were selected for inclusion in the 1998 KDHS, of which 8,661 were occupied and thus eligible for interview. Of the eligible households, 8,380 were successfully interviewed, giving a response rate of 97 percent. The main reason for eligible households not being interviewed was that a competent member of the household could not be found and interviewed during the course of work in the cluster. In interviewed households, 8,233 eligible women (age 15-49) were identified and 7,881 were successfully interviewed, yielding a response rate of 96 percent.
Of the 4,747 households subsampled for inclusion in the KDHS male survey, 4,337 households were occupied and therefore eligible for interview. About 97 percent of these households were successfully interviewed. A total of 3,845 men (age 15-54) were identified in the surveyed households and 3,407 of these were interviewed, yielding a response rate of 89 percent. Response rates for male and female individual interviews were higher in rural areas than in urban areas. The main reason for nonresponse was failure to find the individuals despite repeated visits to the household and place of work.
Dates of collection
Mode of data collection
Three types of questionnaires were used in the 1998 KDHS: the Household Questionnaire, the Women's Questionnaire, and the Men's Questionnaire. The Women's and Men's questionnaires were based on the DHS Model A Questionnaire, which is designed for use in countries with relatively high levels of contraceptive use. A series of meetings were held with policy experts, programme managers, and other professionals to review, adapt, and revise the questionnaires. This process culminated in a set of English-language questionnaires, which were translated into Kiswahili and nine of the most widely spoken local languages: Kalenjin, Kamba, Kikuyu, Kisii, Luhya, Luo, Masai, Meru, and Mijikenda.
a )The Household Questionnaire was used to list all of the usual members and visitors in the selected households. Basic information on each person listed was collected including age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify all of the women age 15-49 and men age 15-54 eligible for the individual interview. In addition, information was collected about characteristics of the household, such as the source of water, type of toilet facilities, materials used to construct the household's dwelling, and ownership of various consumer goods.
b) The Women's Questionnaire was used to collect information from women age 15-49, and included questions on the following topics:
- Background characteristics (age, education, religion, etc.),
- Reproductive history (to arrive at fertility and childhood mortality rates),
- Knowledge and use of family planning methods,
- Antenatal and delivery care,
- Infant feeding practices including patterns of breastfeeding,
- Childhood vaccinations,
- Recent episodes of childhood illness and responses to illness,
- Marriage and sexual activity,
- Fertility preferences,
- Husband's background and respondent's work status,
- Mortality of adults, including maternal mortality,
- AIDS-related knowledge, attitudes, and behaviour,
- Female circumcision, and
- Nutritional status of children and mothers.
c) The Men's Questionnaire covered many of the same topics but excluded the detailed reproductive history and sections dealing with maternal and child health, maternal mortality, and female circumcision. The Men's Questionnaire is consequently much shorter than the Women's Questionnaire.
The questionnaires were pretested by language-specific teams of one woman and one man who had been trained for two weeks at the Machakos Technical Training Institute. During the pretest fieldwork, supervised by NCPD staff, 200 Household, Women's, and Men's Questionnaires were completed in locations around Kenya where interviews could be carried out in the various local languages. Based on observations in the field and suggestions made by the pretest field teams and trainers, revisions were made in the wording and translation of the questionnaires.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 1998 KDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.
A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.
If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 1998 KDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 1998 Kenya Demographic and Health Survey (KDHS) is the ISSA Sampling Error Module. This module uses the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.
In addition to the standard error, ISSA computes the design effect (DEFT) for each estimate, which is defined as the ratio between the standard error using the given sample design and the standard error that would result if a simple random sample had been used. A DEFT value of 1.0 indicates that the sample design is as efficient as a simple random sample, while a value greater than 1.0 indicates the increase in the sampling error due to the use of a more complex and less statistically efficient design. ISSA also computes the relative error and confidence limits for the estimates.
Sampling errors for the 1998 KDHS are calculated for selected variables considered to be of primary interest. The results are presented in an appendix to the Final Report for the country as a whole, for urban and rural areas, and for the seven surveyed provinces. For each variable, the type of statistic (mean, proportion, or rate) and the base population are given in Table B.1 of the appendix in the Final Report. Tables B.2 to B.11 present the value of the statistic (R), its standard error (SE), the number of unweighted (N) and weighted (WN) cases, the design effect (DEFT), the relative standard error (SE/R), and the 95 percent confidence limits (R±2SE), for each variable. The DEFT is considered undefined when the standard error considering simple random sample is zero (when the estimate is close to 0 or 1). In the case of the total fertility rate, the number of unweighted cases is not relevant, as there is no known unweighted value for woman-years of exposure to child-bearing.
The confidence interval (e.g., as calculated for Children ever born to women aged 15-49) can be interpreted as follows: the overall average from the national sample is 2.895 and its standard error is 0.034. Therefore, to obtain the 95 percent confidence limits, one adds and subtracts twice the standard error to the sample estimate, i.e., 2.895±2×0.034. There is a high probability (95 percent) that the true average number of children ever born to all women aged 15 to 49 is between 2.827 and 2.962. (The confidence interval should not be interpreted to mean that all values between 2.827 and 2.962 are equally likely to be the true value. Indeed, based on the assumption that the sample design is unbiased, the estimated value of 2.895 is the best estimate (most likely single value) of the average number of children ever born that can be inferred from the KDHS data.)
Sampling errors are analyzed for the national woman sample and for two separate groups of estimates: (1) means and proportions, and (2) complex demographic rates. The relative standard errors (SE/R) for the means and proportions range between 0.2 percent and 22.5 percent with an average of 4.2 percent. The highest relative standard errors are for estimates of very low values (e.g., Women currently using contraceptive implants, or Norplant). If estimates of very low values (less than 1 percent) were removed, than the average would drop to 2.4 percent. So in general, the relative standard errors for most estimates for the country as a whole are small, except for estimates of very small proportions (i.e. rare occurences). The relative standard error for the total fertility rate is small, 2.3 percent. However, for the childhood mortality rates, the average relative standard error is much higher, 5.5 to 8.0 percent.
There are differentials in subnational estimates of the relative standard error. For example, for the variable With Secondary Education or higher, the relative standard errors (i.e., as a percentage of the estimated proportion) for the whole country, for the urban areas, and for the Coast region are 3 percent, 3.9 percent, and 10.4 percent, respectively.
For the total sample, the value of the design effect (DEFT), averaged over all variables, is 1.26. This which means that, due to the sample design which involves multi-stage clustering, the average standard error is increased by 26 percent over that in an equivalent simple random sample.
Other forms of data appraisal
Nonsampling (measurement) errors are the results of shortcomings in the implemention of data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 1998 Kenya Demographic and Health Survey (KDHS) to minimize this type of error, nonsampling errors are impossible to entirely avoid and difficult to evaluate statistically.
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Data and Data Related Resources
National Co-ordination Agency for Population & Development (NCPD)