The 1996 Zambia Demographic and Health Survey (ZDHS) is a nationally representative survey conducted by the Central Statistical Office at the request of the Ministry of Health, with the aim of gathering reliable information on fertility, childhood and maternal mortality rates, maternal and child health indicators, contraceptive knowledge and use, and knowledge and prevalence of sexually transmitted diseases (STDs) including AIDS. The survey is a follow-up to the Zambia DHS survey carried out in 1992.
The primary objectives of the ZDHS are:
- To collect up-to-date information on fertility, infant and child mortality and family planning;
- To collect information on health-related matters such as breastfeeding, antenatal care, children's immunisations and childhood diseases;
- To assess the nutritional status of mothers and children; iv) To support dissemination and utilisation of the results in planning, managing and improving family planning and health services in the country; and
- To enhance the survey capabilities of the institutions involved in order to facilitate the implementation of surveys of this type in the future.
SUMMARY OF FINDINGS
- Fertility Trends. The 1996 ZDHS survey results indicate that the level of fertility in Zambia is continuing to decline.
- Fertility Differentials. Some women are apparently leading the fertility decline. Moreover, women who have received some secondary education have the lowest level of fertility.
- Age at First Birth. Childbearing begins early in Zambia, with over one-third of women becoming mothers by the time they reach age 18 and around two-thirds having had a child by the time they reach age 20.
- Birth Intervals. The majority of Zambian children (81 percent) are born after a "safe" birth interval (24 or more months apart), with 36 percent born at least 36 months after a prior birth. Nevertheless, 19 percent of non-first births occur less than 24 months after the preceding birth. The overall median birth interval is 32 months.
- Fertility Preferences. Survey data indicate that there is a strong desire for children and a preference for large families in Zambian society.
- Unplanned Fertility. Despite the increasing level of contraceptive use, ZDHS data indicate that unplanned pregnancies are still common.
- Increasing Use of Contraception. The contraceptive prevalence rate in Zambia has increased significantly over the past five years, rising from 15 percent in 1992 to 26 percent in 1996.
- Differentials in Family Planning Use. Differentials in current use of family planning by province are large.
- Source of Contraception. Six in ten users obtain their methods from public sources, while 24 percent use non-governmental medical sources and shops and friends account for the remaining 13 percent. Government health centres (41 percent) and government hospitals (16 percent) are the most common sources of contraceptive methods.
- Knowledge of Contraceptive Methods. Knowledge of contraceptive methods is nearly universal, with 96 percent of all women and men knowing at least one method of family planning.
- Family Planning Messages. One reason for the increase in level of contraceptive awareness is that family planning messages are prevalent.
- Unmet Need for Family Planning. ZDHS data show that there is a considerable unmet need for family planning services in Zambia.
MATERNAL AND CHILD HEALTH
- Maternal Health Care. ZDHS data show some encouraging results regarding maternal health care, as well as to some areas in which improvements could be made. Results show that most Zambian mothers receive antenatal care, 3 percent from a doctor and 93 percent from a nurse or trained midwife.
- High Childhood Mortality. One of the more disturbing findings from the survey is that child survival has not improved over the past few years.
- Childhood Vaccination Coverage. Vaccination coverage against the most common childhood illnesses has increased recently.
- Childhood Health. ZDHS data indicate that Zambian mothers are reasonably well-informed about childhood illnesses and that a high proportion are treated appropriately.
- Breastfeeding Practices. The ZDHS results indicate that breastfeeding is almost universally practised in Zambia, with a median duration of 20 months.
- Knowledge and Behaviour Regarding AIDS. Survey results indicate that virtually all respondents had heard of AIDS. Common sources of information were friends/relatives, the radio, and health workers. The vast majority of respondents--80 percent of women and 94 percent of men--say they have changed their behaviour in order to avoid contracting AIDS, mostly by restricting themselves to one sexual partner.
Kind of data
Sample survey data
The 1996 Zambia Demographic and Health Survey (ZDHS) is a nationally representative survey. The sample was designed to produce reliable estimates for the country as a whole, for the urban and the rural areas separately, and for each of the nine provinces in the country.
Unit of analysis
- women age 15-49
- Men age 15-59
- Children under five years
The survey covered all de jure household members (usual residents), all women of reproductive age, aged 15-49 years in the total sample of households, men aged 15-59 and Children under age 5 resident in the household.
Producers and sponsors
Central Statistical Office
Macro International Inc.
Ministry of Health
Agency for International Development
United Nations Population Fund
Swedish International Development Agency
Government of Zambia
United Nations Children's Fund
The 1996 ZDHS covered the population residing in private households in the country. The design for the ZDHS called for a representative probability sample of approximately 8,000 completed individual interviews with women between the ages of 15 and 49. It is designed principally to produce reliable estimates for the country as a whole, for the urban and the rural areas separately, and for each of the nine provinces in the country. In addition to the sample of women, a sub-sample of about 2,000 men between the ages of 15 and 59 was also designed and selected to allow for the study of AIDS knowledge and other topics.
Zambia is divided administratively into nine provinces and 57 districts. For the Census of Population, Housing and Agriculture of 1990, the whole country was demarcated into census supervisory areas (CSAs). Each CSA was in turn divided into standard enumeration areas (SEAs) of approximately equal size. For the 1992 ZDHS, this frame of about 4,200 CSAs and their corresponding SEAs served as the sampling frame. The measure of size was the number of households obtained during a quick count operation carried out in 1987. These same CSAs and SEAs were later updated with new measures of size which are the actual numbers of households and population figures obtained in the census. The sample for the 1996 ZDHS was selected from this updated CSA and SEA frame.
CHARACTERISTICS OF THE AMPLE
The sample for ZDHS was selected in three stages. At the first stage, 312 primary sampling units corresponding to the CSAs were selected from the frame of CSAs with probability proportional to size, the size being the number of households obtained from the 1990 census. At the second stage, one SEA was selected, again with probability proportional to size, within each selected CSA. An updating of the maps as well as a complete listing of the households in the selected SEAs was carried out. The list of households obtained was used as the frame for the third-stage sampling in which households were selected for interview. Women between the ages of 15 and 49 were identified in these households and interviewed. Men between the ages of 15 and 59 were also interviewed, but only in one-fourth of the households selected for the women's survey.
The provinces, stratified by urban and rural areas, were the sampling strata. There were thus 18 strata. The proportional allocation would result in a completely self-weighting sample but would not allow for reliable estimates for at least three of the nine provinces, namely Luapula, North-Western and Western. Results of other demographic and health surveys show that a minimum sample of 800-1,000 women is required in order to obtain estimates of fertility and childhood mortality rates at an acceptable level of sampling errors. It was decided to allocate a sample of 1,000 women to each of the three largest provinces, and a sample of 800 women to the two smallest provinces. The remaining provinces got samples of 850 women. Within each province, the sample was distributed approximately proportionally to the urban and rural areas.
STRATIFICATION AND SYSTEMATIC SELECTION OF CLUSTERS
A cluster is the ultimate area unit retained in the survey. In the 1992 ZDHS and the 1996 ZDHS, the cluster corresponds exactly to an SEA selected from the CSA that contains it. In order to decrease sampling errors of comparisons over time between 1992 and 1996--it was decided that as many as possible of the 1992 clusters be retained. After carefully examining the 262 CSAs that were included in the 1992 ZDHS, locating them in the updated frame and verifying their SEA composition, it was decided to retain 213 CSAs (and their corresponding SEAs). This amounted to almost 70 percent of the new sample. Only 99 new CSAs and their corresponding SEAs were selected.
As in the 1992 ZDHS, stratification of the CSAs was only geographic. In each stratum, the CSAs were listed by districts ordered geographically. The procedure for selecting CSAs in each stratum consisted of:
(1) calculating the sampling interval for the stratum:
(2) calculating the cumulated size of each CSA;
(3) calculating the series of sampling numbers R, R+I, R+21, .... R+(a-1)l, where R is a random number between 1 and 1;
(4) comparing each sampling number with the cumulated sizes.
The reasons for not retaining the remaining 49 CSAs are as followed:
(1) the urban sample of Copperbelt Province is smaller in the 1996 ZDHS than in the 1992 ZDHS so that all clusters in urban Copperbelt are not needed;
(2) the SEA composition of certain CSAs was changed during the actual census; and
(3) there were errors in the old frame concerning the urban/rural specifications.
The CSA to be selected was the first CSA whose cumulated size was greater or equal to the sampling number. In each CSA, only one SEA was selected at random (using a random number between 1 and the number of SEAs in the CSA.) The final sample of CSAs (and their corresponding SEAs) shows that of the 57 districts that exist in the country, 55 will be covered by ZDHS.
The results indicate that of the 8,016 households selected in the survey, 91 percent were successfully interviewed. Four percent of the dwellings were found vacant or destroyed, 4 percent of the households were not at home, and in one percent of the households there was no competent respondent. The response rate at the household level is 99 percent. In these households, there were 8,298 women age 15-49, 97 percent of whom were successfully interviewed. The response rate for the women survey is 96 percent. There is some variation in response rate by province and urban/rural areas. The rate is 95 percent or lower in Northern, Copperbelt, Noah-Western, Lusaka, and Central Provinces, and 98 percent or higher in Eastern and Luapula Provinces.
For the men's survey, the overall response rate is lower than that for women (90 percent). The rates range from 80 percent in Lusaka to 95 percent in Eastern province.
Dates of collection
Mode of data collection
Data collection supervision
From among those selected, candidates suitable as field editors and supervisors were selected. The supervisors and field editors were given additional training in coordination of fieldwork, methods of field editing and data quality control procedures.
Three types of questionnaires were used for the ZDHS:
a) the Household Questionnaire,
b) the Women's Questionnaire
c) the Men's Questionnaire.
The contents of these questionnaires were based on the DHS Model "B" Questionnaire, which is designed for use in countries with low levels of contraceptive use. Additions and modifications to the model questionnaires were made after consultation with a number of institutions, including the University of Zambia, the Ministry of Health, the Planned Parenthood Association of Zambia (PPAZ), and the National Commission for Development Planning. The questionnaires were developed in English and then translated into and printed in seven of the most widely spoken languages (Bemba, Kaonde, Lozi, Lunda, Luvale, Nyanja and Tonga).
a) The Household Questionnaire was used to list all the usual members and visitors of a selected household. Some basic information was collected on the characteristics of each person listed, including his/her age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. In addition, information was collected on the household itself, such as the source of water, type of toilet facilities, material used for the floor of the house, and ownership of various consumer goods.
b) The Women's Questionnaire was used to collect information from women age 15-49 about the following topics:
Background characteristics (education, religion, etc.); Reproductive history; Knowledge and use of family planning methods; Antenatal and delivery care; Breastfeeding and weaning practices; Vaccinations and health of children under age five; Marriage; Fertility preferences; Husband' s background and respondent' s work; Awareness of AIDS; and Maternal mortality.
c) The Men's Questionnaire was used to collect information from men age 15-59 years in every fourth household about the following topics:
Background characteristics (education, religion, etc.); Reproductive history; Knowledge and use of family planning methods; Marriage; Fertility preferences; and Awareness of AIDS.
In addition, the interviewing teams measured the height and weight of all children under age five and their mothers.
Central Statistical Office
The completed questionnaires were returned to the CSO headquarters for data processing. The data processing staff first checked whether all household and individual questionnaires for selected households and eligible women and men were indeed present for all clusters, along with field control forms. Missing information was relayed to the respective team. They then edited the questionnaires, coded open-ended questions, entered the data, and ran the secondary editing program. The data were processed by a team consisting of five data entry clerks, three office editors, and one data entry supervisor. Data processing was accomplished using a computer program developed for DHS surveys, Integrated System for Survey Analysis (ISSA).
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the ZDHS 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 ZDHS 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 ZDHS is the ISSA Sampling Error Module. This module used 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 ZDHS 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 nine provinces. 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.13 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 3.037 and its standard error is .038. Therefore, to obtain the 95 percent confidence limits, one adds and subtracts twice the standard error to the sample estimate, i.e., 3.037+2x.038. 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 2.961 and 3.113.
Sampling errors are analyzed 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 0.2 percent and 20 percent with an average of 3.5 percent; the highest relative standard errors are for estimates of very low values (e.g., currently using injections among women who were currently using a contraceptive method). If estimates of very low values (less than 10 percent) were removed, than the average drops to 2.1 percent. So in general, the relative standard errors 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 percent. However, for the mortality rates, the average relative standard error is somewhat higher, 4.6 percent.
There are differentials in the relative standard error for the estimates of sub-populations. For example, for the variable 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 Northern Province are 4 percent, 7.8 percent, and 13.5 percent, respectively.
For the total sample, the value of the design effect (DEFT), averaged over all variables, is 1.27 which means that, due to multi-stage clustering of the sample, variance is increased by a factor of 1.6 over that in an equivalent simple random sample.
Finally, the 1996 ZDHS sample consisted mostly of the same enumeration areas selected for the 1992 ZDHS; therefore, there was a strong interest in the calculation of sampling errors for the change in rates between the two surveys. Because the two samples were not independent, it is possible to detect change in a particular rate during the period between the two surveys with a smaller sample than if the two samples had been independent. To obtain a measure of the sampling error of the difference in rates between the two surveys, say, for example, the contracepfve prevalence rate, it is necessary to calculate the correlation between the values of the contraceptive prevalence rate for the two surveys at the cluster level and then apply the following formula to calculate the corresponding sampling error:
se(p , -P 2) =~se 2(p l ) + se 2(p2) -2 *p , ~se 2(pl) * se 2(p2)
Other forms of data appraisal
Nonsampling errors am the results of mistakes made in implementing 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 ZDHS to minimize this type of error, nonsampling errors are impossible to 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.