Demographic and Health Survey 2004
Malawi, 2004 - 2005
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MWI_2004_DHS_v01_M
Demographic and Health Survey 2004
| Name | Country code |
|---|---|
| Malawi | MWI |
Demographic and Health Survey (standard) - DHS IV
The Malawi Demographic and Health Survey 2004 is the third survey of its kind to be conducted in Malawi. The first one was carried out in 1992 and the second one in 2000.
The 2004 MDHS survey was implemented by the National Statistical Office (NSO). The Ministry of Health and Population, the National AIDS Commission (NAC), the National Economic Council, and the Ministry of Gender contributed to the development of the questionnaires for the survey. Most of the funds for the local costs of the survey were provided by multiple donors through the NAC. The United States Agency for International Development (USAID) provided additional funds for the technical assistance through ORC Macro. The Department for International Development (DfID) of the British Government, the United Nations Children's Fund (UNICEF), and the United Nations Population Fund (UNFPA) also provided funds for the survey. The Centers of Disease Control and Prevention provided technical assistance in HIV testing.
The survey used a two-stage sample based on the 1998 Census of Population and Housing and was designed to produce estimates for key indicators for ten large districts in addition to estimates for national, regional, and urban-rural domains. Fieldwork for the 2004 MDHS was carried out by 22 mobile interviewing teams. Data collection commenced on 4 October 2004 and was completed on 31 January 2005.
The principal aim of the 2004 MDHS project was 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 infections. It was designed as a follow-on to the 2000 MDHS survey, a national-level survey of similar scope. The 2004 MDHS survey, unlike the 2000 MDHS, collected blood samples which were later tested for HIV in order to estimate HIV prevalence in Malawi.
In broad terms, the 2004 MDHS survey aimed to:
- Assess trends in Malawi's demographic indicators, principally fertility and mortality
- Assist in the monitoring and evaluation of Malawi's health, population, and nutrition programmes
- Advance survey methodology in Malawi and contribute to national and international databases
- Provide national-level estimates of HIV prevalence for women age 15-49 and men age 15-54.
In more specific terms, the 2004 MDHS survey was designed to:
- Provide data on the family planning and fertility behaviour of the Malawian population and thereby enable policymakers to evaluate and enhance family planning initiatives in the country
- Measure changes in fertility and contraceptive prevalence and analyse the factors that affect these changes, such as marriage patterns, desire for children, availability of contraception, breastfeeding habits, and important social and economic factors
- Examine basic indicators of maternal and child health and welfare in Malawi, including nutritional status, use of antenatal and maternity services, treatment of recent episodes of childhood illness, and use of immunisation services. Particular emphasis was placed on malaria programmes, including malaria prevention activities and treatment of episodes of fever.
- Provide levels and patterns of knowledge and behaviour related to the prevention of HIV/AIDS and other sexually transmitted infections
- Provide national estimates of HIV prevalence
- Measure the level of infant and adult mortality including maternal mortality at the national level
- Assess the status of women in the country.
MAIN FINDINGS
Fertility - Fertility Levels and Trends. While there has been a significant decline in fertility in the past two decades from 7.6 children in the early 1980s to 6.0 children per woman in the early 2000s, compared with selected countries in Eastern and Southern Africa, such as Zambia, Tanzania, Mozambique, Kenya, and Uganda, the total fertility rate (TFR) in Malawi is high, lower only than Uganda (6.9).
Family planning - Knowledge of Contraception. Knowledge of family planning is nearly universal, with 97 percent of women age 15-49 and 97 percent of men age 15-54 knowing at least one modern method of family planning. The most widely known modern methods of contraception among all women are injectables (93 percent), the pill and male condom (90 percent each), and female sterilisation (83 percent).
Maternal health - Antenatal Care. There has been little change in the coverage of antenatal care (ANC) from a medical professional since 2000 (93 percent in 2004 compared with 91 percent in 2000). Most women receive ANC from a nurse or a midwife (82 percent), although 10 percent go to a doctor or a clinical officer. A small proportion (2 percent) receives ANC from a traditional birth attendant, and 5 percent do not receive any ANC. Only 8 percent of women initiated ANC before the fourth month of pregnancy, a marginal increase from 7 percent in the 2000 MDHS.
Adult and Maternal Mortality. Comparison of data from the 2000 and 2004 MDHS surveys indicates that mortality for both women and men has remained at the same levels since 1997 (11-12 deaths per 1,000).
Child health - Childhood Mortality. Data from the 2004 MDHS show that for the 2000-2004 period, the infant mortality rate is 76 per 1,000 live births, child mortality is 62 per 1,000, and the under-five mortality rate is 133 per 1,000 live births.
Nutrition - Breastfeeding Practices. Breastfeeding is nearly universal in Malawi. Ninety-eight percent of children are breastfed for some period of time. The median duration of breastfeeding in Malawi in 2004 is 23.2 months, one month shorter than in 2000.
HIV/AIDS - Awareness of AIDS. Knowledge of AIDS among women and men in Malawi is almost universal. This is true across age group, urban-rural residence, marital status, wealth index, and education. Nearly half of women and six in ten men can identify the two most common misconceptions about the transmission of HIV-HIV can be transmitted by mosquito bites, and HIV can be transmitted by supernatural means-and know that a healthy-looking person can have the AIDS virus.
Sample survey data
- Household
- Women age 15-49
- Men age 15-54
Scope
The Malawi Demographic and Health Survey 2004 covers the following topics:
- Anemia Questions–Questions or testing assessing prevalence/severity of iron-def. anemia among women or children
- Anemia Testing
- Anthropometry
- Child Labor
- Domestic Violence
- Fistula Questions
- GPS/Georeferenced–Global Positioning System or Georeferenced Data
- HIV Behavior
- HIV Knowledge–Questions assess knowledge/sources of knowledge/ways to avoid HIV
- HIV Testing
- Malaria Module (bednets)
- Male circumcision
- Maternal Mortality
- Men's Survey
- Micronutrients
- Reproductive Calendar
- Social Marketing
- Tobacco Use
- Vitamin A Questions
Coverage
The 2004 MDHS is designed to present important characteristics for Malawi as a whole, urban and rural areas separately, and each of ten large districts. These districts are: Blantyre, Kasungu, Machinga, Mangochi, Mzimba, Salima, Tyolo, Zomba, Lilongwe, and Mulanje.
The population covered by the 2004 MDHS is defined as the universe of all women age 15-49 in malawi and all men age 15-54 living in the household.
Producers and sponsors
| Name |
|---|
| National Statistical Office (NSO) |
| Name | Role |
|---|---|
| ORC Macro | Technical assistance |
| Name | Role |
|---|---|
| United States Agency for International Development | Funding |
| Department for International Development of the British Government | Funding |
| United Nations Children’s Fund | Funding |
| United Nations Population Fund | Funding |
| National AIDS Commission | Channel of delivery |
| Name | Role |
|---|---|
| Centers for Disease Control and Prevention (CDC) | Technical assistance on HIV testing |
Sampling
The primary objective of the 2004 Malawi Demographic and Health Survey (MDHS) is to provide estimates with acceptable precision for important population characteristics such as fertility, contraceptive prevalence, selected health indicators, and infant mortality rates.
Administratively, Malawi is divided into twenty-seven districts. In turn, each district is subdivided into smaller administrative units. In 1998, the National Statistical Office (NSO) carried out a Housing and Population Census. In the census, each administrative unit was sub-divided into enumeration areas (EAs), which is totally classified as urban or rural. For each EA, a sketch map was drawn. The sketch shows the EA boundaries, location of buildings, and other landmarks. The list of EAs serves as the frame for the 2004 MDHS sample.
The 2004 MDHS is designed to present important characteristics for Malawi as a whole, urban and rural areas separately, and each of ten large districts. These districts are: Blantyre, Kasungu, Machinga, Mangochi, Mzimba, Salima, Tyolo, Zomba, Lilongwe, and Mulanje. In the interest of presenting estimates for the remaining 17 districts in Malawi in as much breakdown as possible, these districts are grouped as follows:
- Group 1: The rest of the Northern region (Chitipa, Karonga, Rumphi, Likoma, and Nkhata Bay)
- Group 2: Dowa, Dedza, and Nkhotakota
- Group 3: Mchinji and Ntchisi
- Group 4: Mwanza, Chikwawa, and Nsanje
- Group 5: Phalombe and Chiradzulu
- Group 6: Balaka and Ntcheu
SAMPLE ALOCATION
The target sample for the 2004 MDHS sample is about 15,140 households. Based on the level of non-response found in the 2000 MDHS, approximately 13,000 women with completed interviews are expected to be obtained. A sample of households will be selected from each EA, and all women age 15 to 49 identified in these households were interviewed. One in every three sampled households was selected for the male survey and HIV testing. All men age 15-54 in these households are eligible for individual interview. The selected households will be distributed in 522 EAs, 64 in the urban and 458 in the rural areas.
SAMPLE SELECTION
The 2004 MDHS sample will be selected using a stratified two-stage cluster design. In each domain, the clusters are selected with a probability proportional to household size (based on the 1998 census). An average of 29 households will be selected in each cluster.
A total of 15,041 households were selected in the MDHS sample, of which 13,965 were occupied. Of the occupied households, 13,664 were interviewed, yielding a household response rate of 98 percent. The household response rate is higher in rural areas.
In the 13,664 interviewed households, 12,229 women age 15-49 were identified as eligible for the individual interview, and interviews were completed for 11,698, for a 96 percent response rate. Of the 3,797 men age 15-54 who were identified as eligible for individual interview, 3,261 were interviewed, resulting in an 86 percent response rate. For both women and men, the main reason for nonresponse in the MDHS was failure to find the respondents despite repeated visits to the household. Compared with the 2000 MDHS, the response rate for women declined from 98 to 96 percent and the response rate for men declined from 97 to 95 percent.
Survey instrument
Three types of questionnaires were used in the 2004 MDHS survey: a) the Household Questionnaire, b) the Women's Questionnaire, and c) the Men's Questionnaire. The contents of the questionnaires were based on the MEASURE DHS model questionnaires, which were adapted for use in Malawi in collaboration with a wide range of stakeholders. The MDHS survey instruments were translated into and printed in Chichewa and Tumbuka for pretesting.
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. Height and weight measurements were taken for all women age 15-49 and all children under the age of five. Respondents to the Household Questionnaire were asked questions on child labour for each child ages 5-14 living in the household or who spent the preceding night in the household. In addition, information was collected about the dwelling itself such as the source of water, type of toilet facilities, materials used to construct the house, ownership of various consumer goods, and use of bed nets. The Household Questionnaire was also used to identify persons eligible for individual interview: women age 15-49 and men age 1554. One woman in each household was selected for the interview on domestic violence.
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, delivery, and postnatal care
- Infant feeding practices, including patterns of breastfeeding
- Vaccinations
- Episodes of childhood illness and responses to illness, with a focus on treatment of fevers in the last two weeks
- Marriage and sexual activity
- Fertility preferences
- Husband's background and the woman's work status
- Woman's status and decisionmaking
- Mortality of adults, including maternal mortality
- AIDS-related knowledge, attitudes, and behaviour
- Domestic violence
c) The Men's Questionnaire was much shorter than the Women's Questionnaire, but covered many of the same topics, excluding the detailed reproductive history and sections dealing with maternal and child health and adult and maternal mortality.
Data collection
| Start | End |
|---|---|
| 2004-10 | 2005-01 |
| Name |
|---|
| National Statistical Office (NSO) |
Four senior NSO staff and one from Ministry of Health and Population supervised and coordinated fieldwork activities. In addition, three health technicians were assigned to supervise the blood collection for anaemia and HIV testing. Fieldwork commenced on 4 October 2004 and was completed by 31 January 2005.
PRETEST
Twelve NSO permanent staff were recruited as interviewers for the DHS pretest of the questionnaires, which was conducted in June and July 2004. The 12 interviewers were trained in conducting interviews and taking blood samples for anaemia and HIV testing. The training took place at the NSO offices for a period of two weeks. The interviewers were split into three teams to conduct interviews in the Northern Region, Central Region, and Southern Region, respectively. During the pretest fieldwork, 206 Household Questionnaires, 160 Women's Questionnaires, and 154 Men's Questionnaires were completed. Based on the observations in the field and suggestions made by the pretest field teams, revisions were made in some skip patterns, wording, and translations of the questionnaires.
RECRUITMENT OF FIELD STAFF
NSO recruited the field staff through its regional offices in Mzuzu, Lilongwe, and Blantyre. The candidates were interviewed and selection of successful applicants was done at NSO Headquarters in Zomba by the Survey Director assisted by the human resource personnel. A total of 180 people were recruited for the survey; 30 were NSO permanent staff and the remaining 150 were temporary workers. Of the temporary workers, 40 have medical background.
TRAINING
A total of 180 people were recruited by NSO for the main training. Training was held for five weeks at Magomero College, south of Zomba town. The first week of training was devoted to the collection of blood samples. Sixty persons were trained to collect blood samples, 34 of whom had medical training and 26 with no medical training. These participants were joined in subsequent weeks by 120 persons who were trained as interviewers only.
The second phase of training focused on interviewing the respondents and taking height and weight measurements. Initially, training consisted of lectures on the underlying rationale of the questionnaires' content and how to complete the questionnaires. Guest lecturers were invited to give talks on specific subjects such as family planning and gender issues, in particular domestic violence. Mock interviews were conducted between participants to allow practice in proper interviewing techniques and the use of local language questionnaires. Throughout the training, participants were given tests to evaluate their understanding and skills in the survey procedures. Toward the end of training, participants spent several days practicing interviews near the training centre.
DATA COLLECTION
Prior to the visit of the interviewing teams to the selected EAs, NSO sent listing teams whose main task was to list all households residing in these EAs. The listing teams were also instructed to draw a sketch map which include the EA boundaries and all structures found in the EA.
In addition to listing households in the selected EAs, the listing teams were entrusted with two additional tasks; 1) informing local authorities about the implementation of MDHS, including the drawing blood samples for anemia and HIV testing and 2) to obtain information on the estimate the transportation cost from the EA to the nearest VCT facility. Data was collected by 22 mobile teams. Each team comprises one supervisor, one field editor, four female interviewers, one male interviewer, and a driver. Quality control was assured through supervision and monitoring of teams during fieldwork. The supervisor and field editor held work sessions frequently with their team, with the goal of reinforcing the training received and correcting all data collection errors.
Five senior NSO staff and one senior MOH staff coordinated and supervised the field activities. The three laboratory technicians supervised the blood sample collection to assure that collection of blood samples was done properly.
Specially designed tables were run once a week by NSO during fieldwork to check the data that were entered. Any problems that appear from review of these tables were discussed with the appropriate teams, and attempts will be made to ensure that they do not persist. The field checks tables included data necessary to monitor the response rates for anemia and HIV testing.
SOCIAL MOBILIZATION
In order to ensure a successful survey, the public was informed about the survey, particularly because for the first time the survey includes taking blood samples from the respondents. Social mobilization started with the household listers who were instructed to meet with Districts Commissioners, Traditional Authorities and other local community leaders to inform them about the survey, particularly about the collection of blood samples for HIV testing.
Publicity of the survey during data collection included using the mass media: press releases in daily newspapers, radio slots, radio drama (Pamajiga). In addition, meetings were held with district assembly staff, chiefs of the areas, and representatives of the local governments of areas that had been selected in the survey.
Data processing
All questionnaires for the MDHS were returned to the NSO central office in Zomba for data processing. The processing operation consisted of office editing, coding of open-ended questions, data entry, double entry verification, and editing inconsistencies found by computer programs developed for the MDHS. The MDHS data entry and editing programs used CSPro, a computer software package specifically designed for processing survey data such as that produced by DHS surveys. About 39 people working in two shifts were involved in the data process activities that include registry, editing and data keying, and secondary editing. Data processing commenced one month after fieldwork and was completed in May 2005. Testing of blood samples started in May 2005 and was completed in June 2005.
Data appraisal
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2004 MDHS 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 2004 MDHS 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 2004 MDHS 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 2004 MDHS are calculated for selected variables considered to be of primary interest for woman's survey and for man's surveys, respectively. The results are presented in an appendix of the Final Report for the country as a whole, for urban and rural areas, and for each of the 11 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.18 present the value of the statistic (R), its standard error (SE), the number of unweighted (N-UNWE) and weighted (N-WEIG) 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 40-49) can be interpreted as follows: the overall average from the national sample is 6.550 and its standard error is 0.080. Therefore, to obtain the 95 percent confidence limits, one adds and subtracts twice the standard error to the sample estimate, i.e., 6.550 ± 2×0.080. There is a high probability (95 percent) that the true average number of children ever born to all women aged 40 to 49 is between 6.391 and 6.709.
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 34.2 percent with an average of 3.47 percent; the highest relative standard errors are for estimates of very low values (e.g., currently using IUD). If estimates of very low values (less than 10 percent) were removed, then the average drops to 1.81 percent. 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, 1.7 percent. However, for the mortality rates, the average relative standard error is much higher, 5.16 percent.
There are differentials in the relative standard error for the estimates of sub-populations. For example, for the variable want no more children, the relative standard errors as a percent of the estimated mean for the whole country and for the urban areas are 1.7 percent and 5.0 percent, respectively.
For the total sample, the value of the design effect (DEFT), averaged over all variables, is 1.351 which means that, due to multi-stage clustering of the sample, the average standard error is increased by a factor of 1.351 over that in an equivalent simple random sample.
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 2004 Malawi Demographic and Health Survey (MDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.
Data Access
| Name | Affiliation | URL | |
|---|---|---|---|
| MEASURE DHS | ICF International | www.measuredhs.com | archive@measuredhs.com |
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.
Contacts
| Name | URL | |
|---|---|---|
| Data and Data Related Resources | archive@measuredhs.com | www.measuredhs.com |
| General Inquiries | info@measuredhs.com | www.measuredhs.com |
| Demography and Social Statistics Division, National Statistical Office | enquiries@statistics.gov.mw | www.nso.malawi.net |
Metadata production
DDI_MWI_2004_DHS_v01_M
| Name | Role |
|---|---|
| World Bank, Development Economics Data Group | Generation of DDI documentation |
2012-04-04