The 1999 Nigeria Demographic and Health Survey (NDHS) is a nationally representative survey of 8,199 women age 15-49 and 3,082 men age 15-64, designed to provide information on levels and trends of fetility, family planning practice, maternal and child health, infant and child mortality, and maternal mortality, as well as awareness of HIV/AIDS and other sexually transmitted diseases (STDs) and female circumcision. Fieldwork for the survey took place between March and May 1999.
The main objective of the 1999 Nigeria Demographic and Health Survey (NDHS) is to provide up-to-date information on reality and childhood mortality levels; nuptiality; fertility preferences; awareness, approval, and use of family planning methods; breastfeeding practices; nutrition levels; and maternal and child health. This information is intended to assist policymakers and administrators in evaluating and designing programmes and strategies for improving health and family planning services in Nigeria.
The total fertility rate during the five years before the survey is 5.2 births per woman. This shows a drop from the level of 6.0 births per woman as reported in the 1990 NDHS and 5.4 from the 1994 Sentinel Survey. The total fertility rate may, however be higher due to evidence that some births were probably omitted in the data. Fertility is substantially higher in the Northeast and Northwest regions and lower in the Southeast, Southwest, and Central regions. Fertility rates are also lower for more educated women.
Childbearing begins early in Nigeria, with about half of women 25 years and above becoming mothers before reaching the age of 20. The median age at first birth is 20.
The level of teenage childbearing has declined somewhat, with the proportion of girls age 15-19 who have either given birth or are pregnant with their first child declining from 28 percent in 1990 to 22 percent in 1999.
Teenage childbearing is higher in rural than urban areas and for those with no education than those with education.
The data from the survey indicate that there is a strong desire for children and a preference for large families with 66 percent of married women and 71 percent of married men indicating a desire to have more children. Even among those with six or more children, 30 percent of married women and 55 percent of married men want to have more children. This indicates a decline for women from the 35 percent reported in the 1990 NDHS. Overall, women report a mean ideal number of children of 6.2, compared with 7.8 children for men.
Despite the increasing level of contraceptive use, the 1999 NDHS data show that unplanned pregnancies are common, with almost one in five births reported to be unplanned. Most of these (16 percent of births) are mistimed (wanted later), while 3 percent were unwanted at all.
Knowledge about family planning methods is increasing in Nigeria, with about 65 percent of all women and 82 percent of all men having heard of at least one method of contraception.
Among women, the pill is the best known method (53 percent) while among men, the condom is the best known method (70 percent). Radio is a main source of information about family planning, with 35 percent of women and 61 percent of men reporting that they heard a family planning message on the radio in the few months before interview. The proportions of women and men who have seen a television message are 23 and 40 percent, respectively. Only 17 percent of women had seen a family planning message in the print media.
The contraceptive prevalence rate in Nigeria has also increased, with 15 percent of married women and 32 percent of married men now using some method of family planning. The use of modem methods is lower at 9 percent for married women and 14 percent for men. Although traditional contraceptive methods are not actively promoted, their use is relatively high with about 6 percent of married women and 17 percent of married men reporting that they are using periodic abstinence or withdrawal. In 1990, only 6 percent of married women were using any method, with only 4 percent using a modern method.
There are significant differentials in levels of family planning use. Urban women and men are much more likely to be using a method than rural respondents. Current use among married women is higher in the Southwest regions (26 percent), Southeast (24 percent), and Central (18 percent) regions than in the Northwest and Northeast (3 percent each). The largest differences occur by educational attainment. Only 6 percent of married women with no education are using a method of contraception, compared with 45 percent of those with more than secondary school.
Users of modern contraception are almost as likely to obtain their methods from government as private sources. Forty-three percent of users obtain their methods from the public sector--mostly government hospitals and health centres--while 43 percent use private medical sources such as pharmacies and private hospitals and clinics; 8 percent get their methods from other private sources like friends, relatives, shops and non-governmental organisations.
The results of the survey show that antenatal care is not uncommon in Nigeria, with mothers receiving antenatal check-ups from either a doctor, nurse or midwife for two out of three births in the three years preceding the survey. However, the content of antenatal care visits appears to be lacking in at least one respect: survey data indicate deficiencies in tetanus toxoid coverage during pregnancy. Mothers reported receiving the recommended two doses of tetanus toxoid for only 44 percent of births and one dose for I 1 percent of births. Almost 40 percent of births occurred without the benefit of a tetanus vaccination.
In Nigeria, home deliveries are still very common, with almost three in five births delivered at home. Compared with 1990, the proportion of home deliveries has declined, with more births now taking place in health facilities. Increasing the proportion of births occurring in facilities is important since they can be attended by medically trained personnel which can result in fewer maternal deaths and delivery complications. Currently, 42 percent of births are attended by doctors, nurses or midwives.
The 1999 NDHS data show that about one in four Nigerian women age 15-49 reported being circumcised. The practice of female genital cutting is more prevalent in the south and central parts of the country and is almost non-existent in the north.
The 1999 NDHS data indicate a decline in childhood vaccination coverage, with the proportion of children fully immunised dropping from 30 percent of children age 12-23 months in 1990 to only 17 percent in 1999. Only a little over half of young children receive the BCG vaccine and the first doses of DPT and polio vaccines. Almost 40 percent of children have not received any vaccination.
Diarrhoea and respiratory illness are common causes of childhood death. In the two weeks before the survey, 11 percent of children under three years of age were ill with acute respiratory infections (ARI) and 15 percent had diarrhoea. Half of children with ARI and 37,percent of those with diarrhoea were taken to a health facility for treatment. Of all the children with diarrhoea, 34 percent were given fluid prepared from packets of oral rehydralion salts (ORS) and 38 percent received a home-made sugar-salt solution.
The infant mortality rate for the five-year period before the survey (early 1994 to early 1999) is 75 per thousand live births. The under-five mortality is 140 deaths per 1,000 births, which means that one in seven children born in Nigeria dies before reaching his/her fifth birthday. However, both these figures are probably considerably higher in reality since an in-depth examination of the data from the birth histories reported by women in the NDHS shows evidence of omission of births and deaths. For this reason, the dramatic decline observed in childhood mortality between the 1990 and 1999 NDHS surveys needs to be viewed with considerably skepticism. Based on the reported birth history information, the infant mortality rate fell from 87 to 75 deaths per 1,000 births, while the under-five mortality rate dropped from 192 to 140.
Problems with the overall levels of reported mortality are unlikely to severely affect differentials in childhood mortality. As expected, mother's level of education has a major effect on infant and child mortality. Whereas the lowest infant mortality rate was reported among children of mothers with post- secondary education (41 per thousand live births), the corresponding figure among infants of mothers with no schooling is 77 per thousand live births.
Data were also collected in the NDHS on the availability of various health services. The data indicate that the vast majority of Nigerian households live within five kilometres of a health facility, with health centres being the closest, followed by clinics and hospitals.
Breasffeeding and Nutrition
Breastfeeding is widely practiced in Nigeria, with 96 percent of children being breastfed. The median duration of breastfeeding is 19 months. Although it is recommended that children be exclusively breastfed with no supplements for the first 4 to 6 months, only 20 percent of children 0-3 months are exclusively breasffed, as are 8 percent of children 4-6 months. Two-thirds of children 4-6 months are being given supplements in addition to breast milk.
In the NDHS, interviewers weighed and measured children under three born to women who were interviewed. Unfortunately, data were either missing or implausible for more than half of these children. Of the half with plausible data, 46 percent of children under 3 are classified as stunted (low height-for-age), 12 percent are wasted (low weight-for-height) and 27 percent are underweight (low weight-for-age).
The 1999 NDHS also collected information on the nutritional status of women who had a birth in the three years prior to the survey. Sixteen percent of these women are considered to be too thin, with a body mass index of less than 18.5. Women of short stature (height less than 145 cm) comprise 7 percent of the women measured.
HIV/AIDS and Other Sexually Transmitted Diseases
Survey data indicate that awareness of HIWAIDS is becoming more widespread. Three-quarters of women and 90 percent of men in Nigeria have heard of AIDS. The radio and relatives and friends are the most commonly cited sources of information about HIV/AIDS among both women and men. However, knowledge of ways to avoid HIV/AIDS is not so widespread. More than a quarter of women and 14 percent of men say they do not know of any way to avoid HIV/AIDS and 6 percent of women and 3 percent of men say there is no way to avoid it. Only 14 percent of women and 29 percent of men say that using condoms is a means of avoiding the disease. On the other hand, three in five men and women who have heard of AIDS know that ahealthy-looking person can be infected with the AIDS virus and over 80 percent know that AIDS is a fatal disease that cannot be cured.
Two-thirds of Nigerian women and men believe that they have no chance of contracting HIV/AIDS, while almost all the rest believe their chances are small. Perhaps one reason is that many Nigerians say they have changed their sexual behavior to avoid getting AIDS. For example, 37 percent of women and 42 percent of men say they restrict themselves to only one pamler; one-fourth of the women say they asked their partners to remain faithful. Condoms are acknowledged by a large majority of respondents to be a way of preventing HIV/AIDS and other sexually-transmitted diseases. Men are almost twice as likely (38 percent) as women (20 percent) to have ever used condoms either for family planning or disease prevention. However, only 7 percent of women and 15 percent of men reported having used a condom the last time they had sexual intercourse. The most widely known sexually transmitted disease apart from AIDS is gonorrhoea.
Kind of data
Sample survey data
The 1999 Nigeria Demographic and Health Survey (NDHS) is a nationally representative survey. The sample was stratified into rural and urban areas and was selected in two stages. It was designed to produce reliable estimates of most of the variables for the rural and urban segments of the country as well as each of five statistical regions, namely, the Northeast region, the Northwest region, the Central region, the Southeast region, and the Southwest region.
Unit of analysis
- Women age 10-49
- Men age 15-64
- Children under 5 years
The population covered by the 1999 DHS is defined as the universe of all women age 10-49 who were either permanent residents of the households in the 1999 NDHS sample or visitors present in the household on the night before the survey were eligible to be interviewed. In addition, in a subsample of one-third of all households selected for the survey, all men age 15-64 were eligible to be interviewed if they were either permanent residents or visitors present in the household on the night before the survey.
Producers and sponsors
National Population Commission
United Nations Population Fund
U.S. Agency for International Development
The 1999 Nigeria Demographic and Health Survey (NDHS) is a nationally representative probability sample of women age 10-49 living in households. The sampling frame used for the survey was constructed from the enumeration areas (EAs) into which the country was delineated for the 1991 population census. Currently, the frame contains 212,079 EAs.
The sample was stratified into rural and urban areas and was selected in two stages. It was designed to produce reliable estimates of most of the variables for the rural and urban segments of the country as well as each of five statistical regions, namely, the Northeast region, the Northwest region, the Central region, the Southeast region, and the Southwest region. Each of these five regions was treated as a sampling domain. The distribution of the states across these regions is shown fully in Appendix A. The regions used for this survey differ from the six geopolitical zones of the country and the seven administrative zones of the National Population Commission.
The primary sampling unit was the EA. Altogether, 400 EAs were selected with equal probability. In all, 119 urban EAs and 281 rural EAs were selected. To ensure data quality, the selection of the EAs was done centrally by trained statisticians at the Liaison Office of the National Population Commission (NPC) in Lagos. The list of selected EAs was sent to the NPC offices in each state to identify the EAs, draw sketch maps, and conduct a listing of all households in each selected EA. NPC's comptrollers at the local government offices thereafter cross-checked the work of the state officers to ensure no omission of any building within the EA.
At the second sampling stage, one in every five households listed was selected for interview. The combination of equal probability selection at the first stage and a fixed sampling rate at the second stage yielded a roughly self-weighting sample design. However, while the returns from the rural stratum showed an appreciable level of self-weighting, the returns from the urban stratum showed a significant level of deviation from self-weighting. The deviation in the urban stratum was due to under listing of dwellings in some EAs because of changes in EA boundaries over time. Therefore, in processing and estimating the population parameters, the sample returns were weighted by considering the selection probabilities of the primary sampling units, the expected and eventual field returns, and the differential response rate among the domains. The weights were standardised and entered with the individual data records. Thus, all the tables presented in this report are based on weighted data.
In the selected households, all women age 10-49 were eligible for interview with the Women's Questionnaire. In every third household, men age 15-64 were eligible for interview with the Men's Questionnaire.
A total of 7,919 households were sampled, of which 7,736 were determined in the field to be valid households and 7,647 were successfully interviewed, giving a response rate of 99 percent.
Of the 8,918 eligible women age 15-49 in these households, 8,199 were interviewed for a response rate of 92 percent. Every third household was selected for coverage with the Men's Questionnaire. Thus, 2,620 households were sampled, of which 2,571 were found and 2,550 were successfully interviewed. In these households, a total of 3,082 men age 15-64 were identified and 2,680 were interviewed for a response rate of 87 percent.
Dates of collection
Mode of data collection
Data collection supervision
The NPC Comptroller of the local government who is a very senior staff thereafter cross checked the work of the technical staff to ensure no omission of any building within the EA or inclusion of a building outside the boundaries of the EA. After approval of the building numbering and listing, the technical staff who did not serve as interviewers in the EA identified and listed all households within the EA in the Household Listing Form -NDHS-07. The Comptroller again was supposed to spot check the listed households by re-listing all households in one of five residential buildings listed by the technical staff.
The following quality control procedure was adopted:
i) If no error was found in the re-listing (sample), then the listing was accepted for enumeration,
ii) if 2 or more percent error was found then, the entire EA was re-listed
iii) if errors were found but less than 2 percent, a second independent sample was drawn, the cumulative errors were found, if 2 or more percent error was obtained (from the two samples), the entire households in the EA will be re-listed, otherwise correction was to be made on the Household Listing Form (NDHS-07). (Note that in an EA, where there are less than 10 residential buildings the comptroller is expected to quality check one of every five households listed in the EA).
Four questionnaires were used for the main fieldwork: the Service Availability Questionnaire, the Household Questionnaire, the Women's Questionnaire, and the Men's Questionnaire.
a) The Service Availability Questionnaire was implemented at an early stage of the fieldwork and was designed to assess the availability (or supply) of health and family planning services. It was administered at the community level (enumeration area) by interviewing knowledgeable informants in the selected community.
b) The household questionnaire was used to identify both men and women who were eligible for the individual questionnaire and to collect data on housing characteristics. name, sex, age, and education.
c) The Women's Questionnaire was administered to all women age 10-49 who were listed on the Household Questionnaire. The decision to interview women age 10-14 was influenced by pretest findings on teenage pregnancy, motherhood, and the age at commencement of sexual activities. Since most of the variables presented in this report are not relevant for the youngest women, the analysis has been restricted to women age 15-49. Women were asked questions on the following topics:
- Background characteristics (age, education, religion, etc.)
- Female genital cutting practices
- Fertility preferences
- Husband's background and respondent's work
- Knowledge of AIDS
- Maternal mortality
- Height and weight of respondents and their children under three.
d) The Men's Questionnaire was used to interview men age 15-64 living in every third household. It was similar to that for women except that it omitted the sections on antenatal and delivery care, breastfeeding, vaccinations, causes of death, female genital cutting, and height and weight.
National Population Commission
The personnel who took part in the processing of NDHS data consisted of 20 data entry operators, two supervisors, and six coders/editors, all of whom are staff of the NPC. Before data processing began, the data entry operators were trained intensively for two weeks by staff from Macro International Inc. (USA).
Data were processed on microcomputers and printers that were provided by Macro International Inc., with funding from USAID. The computers were used to establish the nucleus of a demographic laboratory at the NPC. Data were processed using programmes written by Macro International Inc. with the Integrated System for Survey Analysis (ISSA), which was designed for processing DHS data.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the NDHS 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 NDHS sample is the result of a two-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the NDHS is the ISSA Sampling Error Module. This module used the Taylor linearisation 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.
The Jackknife repeated replication method derives estimates of complex rates from each of several replications of the parent sample, and calculates standard errors for these estimates using simple formulae. Each replication considers all but one clusters in the calculation of the estimates. Pseudo-independent replications are thus created. In the NDHS, there were 399 non-empty clusters. Hence, 399 replications were created.
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 DEbT 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 NDHS 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 five regions. For each variable, the type of statistic (mean, proportion, or rate) and the base population are given in Table B.1 of the Final report. Tables B.2 to B.9 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 since there is no known unweighted value for woman-years of exposure to childbearing.
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 2.848 and its standard error is .04. Therefore, to obtain the 95 percent confidence limits, one adds and subtracts twice the standard error to the sample estimate, i.e., 3.848-+2x.04. There is a high probability (95 percent) that the true average number of children ever bona to all women aged 15 to 49 is between 2.771 and 2.925.
Sampling errors are analysed for the national 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 percent and 50.7 percent with an average of 6.6 percent; the highest relative standard errors are for estimates of very low values (e.g., currently using implants among currently married women who were currently using a contraceptive method). If estimates of very low values (less than 10 percent) were removed, then the average drops considerably. So in general, the relative standard error for most estimates for the country as a whole is small, except for estimates of very small proportions. The relative standard error for the total fertility rate is small, 2.2 percent. However, for the mortality rates, the average relative standard errors are somewhat higher, e.g., 4.8 percent for under-five mortality.
There are differentials in the relative standard error for the estimates of sub-populations. For example, for the variable with secondary education or higher, the relative standard errors as a percent of the estimated mean for the whole country, for the rural areas, and for the Northeast region are 3. I percent, 4.4 percent, and 17.5 percent, respectively.
For the total sample, the value of the design effect (DEFT) averaged over all variables is 1.46, which means that due to multi-stage clustering of the sample variance is increased by a factor of 1.46 over that in an equivalent simple random sample.
Other forms of data appraisal
Any assessment of the quality of survey-based data will find internal and external inconsistencies. Sampling variability can contribute to such findings especially when considering data at the regional as opposed to the national level. So, a data quality assessment often requires a judgement as to whether the degree of the inconsistency indicates acceptable departures from expected patterns or severe data problems.
There are a number of problems with the data of the 1999 NDHS. There is clear evidence of underreporting of events for the time period 1984-89. The magnitude of the mortality decline implied by the estimates from the 1990 and 1999 surveys ranks among the largest observed in high-mortality African countries. Yet, the health indicators for Nigeria indicate a deterioration of immunisation coverage for children over the last decade. The neonatal mortality rate for the Northeast Region is unrealistically low and inconsistent with the postneonatal mortality rate. Both the mortality and the fertility data for the Central Region appear particularly flawed.
The weight of evidence indicates that the mortality rates based on the data are most probably underestimates. Moreover, the nature and scope of the data defects leading to this conclusion suggest that the possibility of repairing these data so that they would form the basis for reliable mortality estimates for Nigeria is not good. This review is useful because of the implications for future surveys that attempt to estimate mortality in the Nigerian setting. It is not the purpose here to specify the design parameters that are necessary to ensure that reliable data are collected. Such design features are well known and it should be a high priority of the next survey to put them in place.
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.