Demographic and Health Survey (standard) - DHS III
The 1994 Zimbabwe Demographic and Health Survey (ZDHS) is the second DHS survey carried out in Zimbabwe. The first one was conducted in 1988.
The 1994 Zimbabwe Demographic and Health Survey (ZDHS) is a nationally representative survey of 6,128 women age 15-49 and 2,141 men age 15-54. The ZDHS was implemented by the Central Statistical Office (CSO), with significant technical guidance provided by the Ministry of Health and Child Welfare (MOH&CW) and the Zimbabwe National Family Planning Council (ZNFPC). Macro International Inc. (U.S.A.) provided technical assistance throughout the course of the project in the context of the Demographic and Health Surveys (DHS) programme, while financial assistance was provided by the U.S, Agency for International Development (USAID/Harare). Data collection for the ZDHS was conducted from July to November 1994.
As in the 1988 ZDHS, the 1994 ZDHS was designed to provide information on levels and trends in fertility, family planning knowledge and use, infant and child mortality, and maternal and child health. How- ever, the 1994 ZDHS went further, collecting data on: compliance with contraceptive pill use, knowledge and behaviours related to AIDS and other sexually transmitted diseases, and mortality related to pregnancy and childbearing (i.e., maternal mortality). The ZDHS data are intended for use by programme managers and policymakers to evaluate and improve family planning and health programmes in Zimbabwe.
The primary objectives of the 1994 ZDHS were to provide up-to-date information on: fertility levels; nuptiality; sexual activity; fertility preferences; awareness and use of family planning methods; breastfeeding practices; nutritional status of mothers and young children; early childhood mortality and maternal mortality; maternal and child health, and awareness and behaviour regarding AIDS and other sexually transmitted diseases.
The 1994 ZDHS is a follow-up of the 1988 ZDHS, also implemented by CSO. While significantly expanded in scope, the 1994 ZDHS provides updated estimates of basic demographic and health indicators covered in the earlier survey.
Survey results show that Zimbabwe has experienced a fairly rapid decline in fertility over the past decade.
Despite the decline in fertility, childbearing still begins early for many women. One in five women age 15-19 has begun childbearing (i.e., has already given birth or is pregnant with her first child). More than half of women have had a child before age 20.
Births that occur too soon after a previous birth face higher risks of undemutrition, illness, and death. The 1994 ZDHS indicates that 12 percent of births in Zimbabwe take place less than two years after a prior birth.
Marriage. The age at which women and men marry has risen slowly over the past 20 years. Nineteen percent of currently married women are in a polygynous union (i.e., their husband has at least one other wife). This represents a small rise in polygyny since the 1988 ZDHS when 17 percent of married women were in polygynous unions.
Fertility Preferences. Around one-third of both women and men in Zimbabwe want no more children. The survey results show that, of births in the last three years, 1 in 10 was unwanted and in 1 in three was mistimed. If all unwanted births were avoided, the fertility rate in Zimbabwe would fall from 4.3 to 3.5 children per woman.
Knowledge and use of family planning in Zimbabwe has continued to rise over the last several years. The 1994 ZDHS shows that virtually all married women (99 percent) and men (100 percent) were able to cite at least one modem method of contraception. Contraceptive use varies widely among geographic and socioeconomic subgroups. Fifty-eight per- cent of married women in Harare are using a modem method versus 28 percent in Manicaland. Government-sponsored providers remain the chief source of contraceptive methods in Zimbabwe. Survey results show that 15 percent of married women have an unmet need for family planning (either for spacing or limiting births).
One of the main objectives of the ZDHS was to document the levels and trends in mortality among children under age five. The 1994 ZDHS results show that child survival prospects have not improved since the late 1980s. The ZDHS results show that childhood mortality is especially high when associated with two factors: short preceding birth interval and low level of maternal education.
MATERNAL AND CHILD HEALTH
Utilisation of antenatal services is high in Zimbabwe; in the three years before the survey, mothers received antenatal care for 93 percent of births. About 70 percent of births take place in health facilities; however, this figure varies from around 53 percent in Manicaland and Mashonaland Central to 94 percent in Bulawayo. It is important for the health of both the mother and child that trained medical personnel are available in cases of prolonged or obstructed delivery, which are major causes of maternal morbidity and mortality. Twenty-four percent of children under age three were reported to have had diarrhoea in the two weeks preceding the survey.
Nutrition. Almost all children (99 percent) are breastfed for some period of time; When food supplementation begins, wide disparity exists in the types of food received by children in different geographic and socioecoaomic groups. Generally, children living in urban areas (Harare and Bulawayo, in particular) and children of more educated women receive protein-rich foods (e.g., meat, eggs, etc.) on a more regular basis than other children.
AIDS-related Knowledge and Behaviour. All but a fraction of Zimbabwean women and men have heard of AIDS, but the quality of that knowledge is sometimes poor. Condom use and limiting the number of sexual partners were cited most frequently by both women and men as ways to avoid the AIDS Virus. While general knowledge of condoms is nearly universal among both women and men, when asked where they could get a condom, 30 Percent of women and 20 percent of men could not cite a single source.
Kind of Data
Sample survey data
Unit of Analysis
- Women age 15-49
- Men age 15-54
- Children under five years
The 1994 Zimbabwe Demographic and Health Survey covers the following topics:
- HIV Behavior
- HIV Knowledge–Questions assess knowledge/sources of knowledge/ways to avoid HIV
- Maternal Mortality
- Men's Survey
- Reproductive Calendar
- Service Availability
- Social Marketing
- Women's Status–Questions: women's autonomy (household decisionmaking/free movement/access money) & Dom. violence
The 1994 Zimbabwe Demographic and Health Survey (ZDHS) is a nationally representative survey.
The population covered by the 1994 ZDHS is defined as the universe of all women age 15-49 in Zimbabwe and all men age 15-54 living in the household.
Producers and sponsors
Central Statistical Office
Macro International lnc
U.S. Agency for International Development
Ministry of Health and Child Welfare
Zimbabwe National Family
The area sampling frame for the ZDHS was the 1992 Zimbabwe Master Sample (ZMS92), which was developed by the Central Statistical Office (CSO) following the 1992 Population Census for use in demographic and socio-economic surveys. The sample for ZMS92 was designed to be almost nationally representative: people residing on state land (national parks, safari areas, etc.) and in institutions, which account for less than one percent of the total population, were not included. The sample was stratified and selected in two stages. With the exception of Harare and Bulawayo, each of the other eight provinces in the country was stratified into four groups according to land use: communal land, large-scale farming, urban and semi-urban areas, and small scale fanning and resettlement areas. In Harare and Bulawayo, only an urban stratum was formed.
The primary sampling unit (PSU) was the enumeration area (EA), as defined in the 1992 Population Census. A total of 395 EAs were selected with probability proportional to size, the size being the number of households enumerated in the 1992 Population Census. The selection of the EAs was a systematic, one- stage operation, carried out independently for each of 34 strata. In each stratum, implicit stratification was introduced by ordering the EAs geographically within the hierarchy of administrative units (wards and districts within provinces).
An evaluation of the ZMS92 showed that it oversampled urban areas: in the ZMS92 the proportion of urban households is about 36 percent while, according to the preliminary results of the 1992 Population Census, this proportion is about 32 percent.
CHARACTERISTICS OF THE ZDHS SAMPLE
The sample for the ZDHS was selected from the ZMS92 master sample in two stages. In the first stage, 230 EAs were selected with equal probabilities. Since the EAs in the ZMS92 master sample were selected with probability proportional to size from the sampling frame, equal probability selection of a subsample of these EAs for the ZDHS was equivalent to selection with probability proportional to size from the entire sampling frame. A complete listing of the households in the selected EAs was carried out. The list of households obtained was used as the frame for the second-stage sampling, which was the selection of the households to be visited by the ZDHS interviewing teams during the main survey fieldwork. Women between the ages of 15 and 49 were identified in these households and interviewed. In 40 percent of the households selected for the main survey, men between the ages of 15 and 54 were interviewed with a male questionnaire.
Stratification in the ZDHS consisted of grouping the ZMS92 strata into two main strata only: urban and rural. Thus the ZDHS rural stratum consists of communal land, large scale farming, and small scale farming and resettlement areas, while the ZDHS urban stratum corresponds exactly to the urban/semi-urban stratum of the ZMS92.
The proportional allocation would result in a completely self-weighting sample but did not allow for reliable estimates for provinces. Results of other demographic and health surveys show that a minimum sample of 1,000 women i:; required in order to obtain estimates of fertility and childhood mortality rates at an acceptable level of sampling errors. Given that the total sample size for the ZDHS could not be increased for the provinces so as to achieve the required level of sampling errors, it was decided that estimates of complex rates would not be produced at the provincial level. Furthermore, since some of the provinces are quite small and would be allocated small sample size, it was decided that the total sample would be allocated equally to the 10 provinces for estimates of selected variables other than complex rates The following sample allocation was adopted after taking into account three factors: (1) a minimum sample of 600 completed interviews for each province; (2) close to proportional allocation for urban and rural areas in each province---except when the resulting stratum size was less than 40, in which case the minimum stratum size was 40--and (3) the number of EAs available in the ZMS92 master sample. According to this sampling scheme, stratum weights would be necessary for data analysis.
A total of 6,483 households were selected, of which 6,075 were found to be occupied. Of the occupied households, 5,984 were successfully interviewed, yielding a household response rate of 98.5 percent. The household response rate shows only moderate variation between provinces. The lowest household response rate was recorded in Harare (95 percent).
Of all eligible women, 95.6 percent were successfully interviewed. Only 0.3 percent of women refused to be interviewed, and 2.4 percent were not at home. A very small percentage (0.2 percent) of interviews with eligible women were incomplete.
Of the eligible men, 91.5 percent were successfully interviewed. The percentage of incomplete inter- views for men is lower than for women because, although only a small percentage (0.6 percent) refused to be interviewed, approximately 4 percent were not at home. The percentage of male interviews completed is higher in rural areas (92.8 percent) than in urban areas (88.9 percent).
Dates of Data Collection
Data Collection Mode
Six permanent senior CSO staff coordinated and supervised fieldwork activities.
Data Collection Notes
The ZDHS questionnaires were pretested in April 1994. Twenty qualified nurses were trained to implement the pretest during a three-week training period. Three language versions of the questionnaires were produced: Shona, Ndebele, and English. The pretest fieldwork was conducted over a one-week period in areas surrounding Gweru, where both Shona and Ndebele households could easily be identified. Approxi-mately 150 pretest interviews were conducted, debriefing sessions were subsequently held with the pretest field staff, and modifications to the questionnaire were made based on lessons drawn from the exercise. Pretest interviewers were retained to serve as field editors and team supervisors during the main survey.
Training of field staff for the main survey was conducted over a four-week period, June-July 1994. Permanent CSO staff trained 70 incoming interviewer trainees, most of whom were trained nurses. The training course consisted of instruction in general interviewing techniques, field procedures, a detailed review of items on the questionnaires, instruction and practice in weighing and measuring children, mock interviews between participants in the classroom, and practice interviews with real respondents in areas outside ZDHS sample points. Trainees who performed satisfactorily in the training programme were selected as interviewers, while the remainder were retained to assist in office operations. During this period, field editors and team supervisors were provided with additional training in methods of field editing, data quality control procedures, and coordination of fieldwork.
The fleldwork for the ZDHS was carried out by 10 interviewing teams, one designated for each province. Each team consisted of one team supervisor, one field editor, five to six female interviewers, one or two male interviewers and one driver. Thus, in total, there were 10 team supervisors, 10 field editors, 54 female interviewers, 12 male interviewers and 10 drivers. Six permanent senior CSO staff coordinated and supervised fieldwork activities. Data collection took place over a four-month period, 20 July to 28 November 1994.
Central Statistical Office
Four types of questionnaires were used for the ZDHS: a) the Household Questionnaire, b) the Women's Questionnaire, c) the Men's Questionnaire, and d) the community-level Service Availability Questionnaire. The contents of these questionnaires were based on the DHS Model "A" Questionnaire, which is designed for use in countries with moderate to high levels of contraceptive use.
a) The Household Questionnaire was used to list all the usual members and visitors of selected households. Some basic information was collected on 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, the Household Questionnaire collected information on characteristics of the household's dwelling units, such as the source of water, type of toilel facilities, materials used for the floor of the house, and ownership of various consumer and durable good.
b) The Women's Questionnaire,. was used to collect information on women age 15-49. These women were asked questions on the following topics:
Background characteristics (education, residential history, etc.) Reproductive history Knowledge and use of family planning methods, including compliance with pill use Fertility preference.,:
- Antenatal and delivery care Breastfeeding and weaning practices
- Vaccinations and health of children under age three
- Marriage and sexual activity Woman's status and husband's occupation
- Awareness and behaviour regarding AIDS and other sexually transmitted diseases
- Adult mortality including maternal mortality.
Unlike the 1988 ZDHS, a "calendar" was used in the 1994 ZDHS to collect information on the respondent' s history since January 1989 concerning reproduction, contraceptive use, reasons for discontinuation of contraception, marriage, anti migration. In addition, interviewing teams measured the height and weight of all children under the age of three years and women who had a birth since January 1991.
c) The Men's Questionnaire was administered to all men age 15-54 living in every 2.5 households in the ZDHS sample (i.e., a 40 percent subsample). The Men's Questionnaire collected much of the same information found in the Women's questionnaire, but was shorter because it did not contain questions on reproductive history and maternal and child health.
d) The Service Availability Questionnaire was administered to community leaders during the household listing operations in March 1994. Community-level information was collected on the nearest health and family planning services available to residents of each of the 230 clusters of households included in the ZDHS sample.
All questionnaires for the ZDHS were returned to the CSO for data processing, which consisted of office editing, coding of open-ended questions, data entry, and editing computer identified errors. The data were processed on five microcomputers. Data entry and editing were accomplished using the computer program ISSA (Integrated System for Survey Analysis). Data processing commenced on I August 1994 and was completed on 14 December 1994.
Estimates of Sampling Error
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 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.
In addition to the standard error, ISSA computes the design effect (DEFT) for each estimate, which is defined as the ratio between the s:andard error using the given sample design and the standard error that would result ifa simple random sample had been used. A DEFT value of t .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 samphng 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. 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. Sampling errors for selected variables are shown for the 10 provinces. Tables B.2 to B.14 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 DEFY 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 childbearing.
In general, the relative standard error for most estimates for the country as a whole is small, except for estimates of very small proportions. There are some differentials in the relative standard error for the estimates of subpopulations. For example, for the variable with secondary education or higher, the relative standard errors as a percent of the e~,;timated mean for the whole country, for urban areas, and for Manicaland are 2.4 percent, 2.9 percent, and 7.4 percent, respectively.
The confidence interval (e.g., as calculated for children ever born ro women age 15-49) can be interpreted as follows: the overall average from the national sample is 2.7 and its standard error is .04. Therefore, to obtain the 95 percent confidence hmits, one adds and subtracts twice the standard error to the sample estimate, i.e., 2.7±.04. There is a high probability (95 percent) that the true average number of children ever born to all women age 15 to 49 is between 2.6 and 2.8.
Nonsampling errors are 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 minimise this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.
Data and Data Related Resources
Central Statistical Office (CSO)
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