MWI_2000_DHS_v01_M
Demographic and Health Survey 2000
Name | Country code |
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Malawi | MWI |
Demographic and Health Survey (standard) - DHS IV
The 2000 MDHS survey is the second survey of its kind to be conducted in Malawi; the first MDHS was conducted in 1992.
Sample survey data
The Malawi Demographic and Health Survey 2000 covers the following topics:
National
The population covered by the 2000 MDHS is defined as the universe of all women age 15-49 in malawi and all men age 15-54 living in the household.
Name |
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National Statistical Office (NSO) |
Name | Role |
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ORC Macro | Technical assistance |
Name | Role |
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United States Agency for International Development | Funding |
Department for International Development | Funding |
United Nations Children’s Fund | Funding |
A major objective of the 2000 MDHS sample design was to provide independent estimates with acceptable precision for important population and health indicators. The sample was designed to provide these estimates for different domains, including estimates for the country, for urban and rural areas, for each of the three regions, and for eleven selected districts (each as a separate domain). The selected districts were chosen based on the size of the district (the five largest) and for programmatic importance.
The population covered by the 2000 MDHS was all women age 15-49 living in the selected households. The initial target sample was 14,000 completed eligible women interviews, and the final sample was 13,220 completed interviews. Information on sampling errors for five selected variables from the MDHS 1992 was used to help determine the most efficient allocation of the target number of interviews by domain with a minimum allocation of 900 for each of the 11 district domain. Based on this objective and some adjustments to ensure that the sample size requirements for each domain were met, the target number of completed interviews was distributed by districts.
SAMPLE FRAME
Based on the 1998 census frame, the National Statistical Office developed an updated preliminary master sample to use during the intercensal period. In order to maintain an integrated household survey approach for future household surveys, it was decided that the 2000 MDHS sample should use the preliminary master sample as the sample frame. The 2000 MDHS sample of enumeration areas (EAs) is thus a sub-sample of NSO's preliminary master sample. NSO's preliminary master sample of EAs is stratified according to district designation and, within districts, by urban-rural designation.1 Since one objective of the master sample is to permit estimation at the district level, the total number of EAs per district was not allocated proportional to population size of the district. Instead, a minimum of 24 EAs were allocated to each district, with certain districts being allocated more EAs based on size and programmatic interest. For instance, Lilongwe and Blantyre districts were each allocated 48 EAs in the master sample. The master sample includes a total of 816 EAs out of the 9,213 EAs established in the 1998 census. A small number of EAs located in national parks and forest areas (representing less than 1 percent of the population of Malawi) were excluded from the master sample.
The design features and stratification of the master sample are implicit in the 2000 MDHS and all other subsamples.
SAMPLE SELECTION
Based on the 2000 MDHS sample design objectives of 36 EAs per "emphasis" district and adequate urban and rural representation, a total of 560 EAs were selected from the master sample: 489 in rural and 71 in urban areas. All districts are represented in the sample, but the sample is specifically designed to allow for estimation of certain parameters for the following "oversampled" districts: Lilongwe, Blantyre, Karonga, Mzimba, Kasungu, Salima, Mangochi, Machinga, Zomba, Thyolo, and Mulanje. A simple systematic sample of EAs was implemented district by district; Before the final household selection, a complete household listing operation was completed for each selected EA. Based on these household lists, the household selection was then implemented to maintain a self-weighted sample in each domain but the sampling rates differ between districts. Therefore, the total 2000 MDHS sample is weighted, and a final weighting adjustment is required to provide national estimates.
All women age 15-49 were targeted for interview in the selected households. Every fourth household was identified for inclusion in the male survey; in those households, all men age 15-54 were identified and considered eligible for individual interview.
A total of 15,421 households were selected in the MDHS sample, of which 14,352 were occupied. Of the occupied households, 14,213 were interviewed, yielding a household response rate of 99 percent. The household response rate was slightly higher in rural areas.
Within the interviewed households, 13,538 eligible women age 15-49 were identified, of which 13,220 were interviewed. The individual women's response rate to the 2000 MDHS survey was 98 percent. In the one-in-four subsample of households, 3,377 men age 15-54 were identified, of which 3,092 men were interviewed, giving a response rate of 92 percent. The main reason for nonresponse among both eligible men and women was the failure to find them at home despite repeated visits to the household. It is typical for male response rates to be lower than female response rates because men are more frequently absent from the household. Response rates for women were not influenced by urban-rural residence, but men's response rates were significantly better in rural areas than in urban areas.
In comparing response rates from the 1992 MDHS survey and the 2000 MDHS survey, the more recent survey performed slightly better. The women's response rate rose from 97 to 98 percent, and the men's response rate increased from 89 to 92 percent.
Three types of questionnaires were used in the 2000 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. A series of meetings were held with policy experts, programme managers, and other professionals in Malawi to review, adapt, and revise the questionnaires. This process culminated in English-version questionnaires that were then translated into Chichewa and Tumbuka.
a) The Household Questionnaire was used to list all of the usual members and visitors in the selected households1. Basic information on each person listed was collected, including age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify all of the eligible women (age 15-49) and men (age 15-54) for individual interviews. In addition, information was collected about characteristics of the household, such as the source of water, type of toilet facilities, materials used to construct the household's dwelling, and ownership of various consumer goods. Data on child labour practises, use of bednets (mosquito nets), and nutritional status of children and women were also collected in the Household Questionnaire.
b) The Women's Questionnaire was used to collect information from women age 15-49 and included questions on the following topics:
c) The Men's Questionnaire covered many of the same topics but excluded the detailed reproductive history and sections dealing with maternal and child health and adult and maternal mortality. The Men's questionnaire is consequently much shorter than the Women's Questionnaire.
The questionnaires were pretested in February 2000 in Mzimba, Ntcheu, and Blantyre City. More than 200 interviews were conducted over a one-week period. The questionnaires were produced in three language versions: Chichewa, Tumbuka, and English. However, interviews could be conducted in any of the languages spoken in Malawi if the respondent was not fluent in one of these three languages. Adjustments in language and content were made to the questionnaires based on the lessons drawn from the pretest interviews.
Start | End |
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2000-07 | 2000-11 |
Name |
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National Statistical Office (NSO) |
TRAINING
Training of field staff for the main survey was conducted over a three-week period in June and July 2000. The training took place at Chilema Ecumenical Lay Training Centre outside Zomba Municipality. A total of 200 field staff were trained.
The training course consisted of instruction in general interviewing techniques, and field procedures, a detailed review of items on the questionnaires, instruction and practice in weighing and measuring children and women, mock interviews between participants, and practical interviews in surrounding villages. In-depth discussions of the translations were an important part of the training programme. The trainees included 26 medically trained personnel who worked on the survey as health technicians. Of the trainees, 183 who performed satisfactorily in the training programme were selected to form the 22 teams for the fieldwork. The rest, if qualified, were employed as MDHS data entry and registry staff.
DATA COLLECTION
Twenty-two interviewing teams carried out the fieldwork for the MDHS survey, with each team consisting of one team leader, one field editor, four female interviewers, one health technician, one male interviewer, and one driver. On a few teams, an additional male interviewer was added. Additionally, six senior staff from NSO coordinated and supervised field activities. Data collection began on July 12 and was completed in early November 2000.
Complete, field-edited questionnaires were brought to the NSO headquarters in Zomba after collection during supervisory visits by NSO senior staff. Data entry began one week after data collection started and was completed in December 2000. Office editing, coding of open-ended questions, and editing based on computer identified inconsistencies in the data continued into January 2001. The questionnaires were entered, verified, and edited using a new version of ISSA (Integrated System for Survey Analysis) adapted by ORC Macro and the U.S. Bureau of Census for integrated use in censuses and surveys.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2000 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 2000 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 2000 MDHS is the ISSA Sampling Error Module (ISSAS). This module used the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jacknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.
The Jacknife 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 2000 MDHS, there were 559 non-empty clusters (one cluster contained no eligible women). Hence, 559 replications were created.
In addition to the standard error, ISSAS 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. ISSAS also computes the relative error and confidence limits for the estimates.
Sampling errors for the 2000 MDHS are calculated for selected variables considered to be of primary interest. The results are presented in an appendix of the Final Report for the country as a whole, for urban and rural areas, for north, central and south regions, and for each of 11 over-sampled district plus the rest of the country. 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) 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 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 sub-populations. For example, for the variable contraceptive use among currently married women age 15-49, the relative standard errors as a percent of the estimated mean for the whole country, for urban areas, and for rural areas are 2.2 percent, 4.7 percent, and 2.3 percent, respectively.
The confidence interval (e.g., as calculated for contraceptive use among currently married women age 15-49) can be interpreted as follows: the overall national sample proportion is 0.306 and its standard error is 0.007. Therefore, to obtain the 95 percent confidence limits, one adds and subtracts twice the standard error to the sample estimate, i.e. 0.306±2(0.007). There is a high probability (95 percent) that the true average proportion of contraceptive use among currently married women age 15 to 49 is between 0.293 and 0.320.
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 2000 MDHS to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.
Name | Affiliation | URL | |
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MEASURE DHS | ICF International | www.measuredhs.com | archive@measuredhs.com |
Use of the dataset must be acknowledged using a citation which would include:
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.
Name | URL | |
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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 |
DDI_MWI_2000_DHS_v01_M
Name | Role |
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World Bank, Development Economics Data Group | Generation of DDI documentation |
2012-04-04
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