Abstract

The 2016-16 Malawi Demographic and Health Survey (2015-16 MDHS) was conducted between October 2015 and February 2016 by the National Statistical Office (NSO) of Malawi in joint collaboration with the Ministry of Health (MoH) and the Community Health Services Unit (CHSU). Malawi conducted its first DHS in 1992 and again in 2000, 2004, and 2010. The 2015-16 MDHS is the fifth in the series. The survey is based on a nationally representative sample that provides estimates at the national and regional levels and for urban and rural areas with key indicator estimates at the district level. The survey included 26,361 households, 24,562 female respondents, and 7,478 male respondents.

The primary objective of the 2015-16 MDHS is to provide current estimates of basic demographic and health indicators. The MDHS provides a comprehensive overview of population, maternal, and child health issues in Malawi. More specifically, the 2015-16 MDHS: - collected data that allow the calculation of key demographic indicators, particularly fertility and under 5 and adult mortality rates - provided data to explore the direct and indirect factors that determine the levels and trends of fertility and child mortality - measured the levels of contraceptive knowledge and practice - obtained data on key aspects of family health, such as immunisation coverage among children, prevalence and treatment of diarrhoea and other diseases among children under age 5, and maternity care indicators that include antenatal visits and assistance at delivery - obtained data on child feeding practices including breastfeeding - collected anthropometric measures that assess nutritional status, and conducted anaemia testing for all eligible children under age 5 and women age 15-49 - collected data on knowledge and attitudes of women and men about sexually-transmitted diseases (STDs) and HIV/AIDS, potential exposure to the risk of HIV infection (risk behaviours and condom use) and coverage of HIV Testing and Counselling (HTC) and other key HIV programmes - collected dried blood spot (DBS) specimens for HIV testing from women age 15-49 and men age 15-54 to provide information on the prevalence of HIV among the adult population in the prime reproductive ages.

The micronutrient component of the 2015-16 MDHS was designed to: (1) determine the prevalence of micronutrient deficiencies (vitamin A, B, iron, iodine, zinc) and anaemia among pre-school and school-age children, women, and men of child-bearing age; (2) estimate micronutrient supplementation and fortification coverage; and (3) assess the knowledge and practices in maternal and child nutrition.

The information collected in the 2015-16 MDHS will assist policy makers and programme managers in evaluating and designing programmes and strategies that can improve the health of the country’s population.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15-54

Universe

The survey covered all de jure household members (usual residents), women age 15-49 years and men age 15-54 years resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2015-16 MDHS is the frame of the Malawi Population and Housing Census (MPHC), conducted in Malawi in 2008, and provided by the Malawi National Statistical Office (NSO). The census frame is a complete list of all census standard enumeration areas (SEAs) created for the 2008 MPHC. A SEA is a geographic area that covers an average of 235 households. The sampling frame contains information about the SEA location, type of residence (urban or rural), and the estimated number of residential households.

Administratively, Malawi is divided into 28 districts. The sample for the 2015-16 MDHS was designed to provide estimates of key indicators for the country as a whole, for urban and rural areas separately, and for each of the 28 districts.

The 2015-16 MDHS sample was stratified and selected in two stages. Each district was stratified into urban and rural areas; this yielded 56 sampling strata. Samples of SEAs were selected independently in each stratum in two stages. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before sample selection, according to administrative units in different levels, and by using a probability proportional to size selection at the first stage of sampling.

In the first stage, 850 SEAs, including 173 SEAs in urban areas and 677 in rural areas, were selected with probability proportional to the SEA size and with independent selection in each sampling stratum.

In the second stage of selection, a fixed number of 30 households per urban cluster and 33 per rural cluster were selected with an equal probability systematic selection from the newly created household listing.

For further details on sample selection, see Appendix B of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Four questionnaires were used in the 2015-16 MDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. These questionnaires, based on The DHS Program’s standard Demographic and Health Survey questionnaires, were adapted to reflect the population and health issues relevant to Malawi. Input was solicited from stakeholders who represented government ministries and agencies, nongovernmental organisations, and international donors. After the preparation of the definitive questionnaires in English, the questionnaires were then translated into Chichewa and Tumbuka languages. All four questionnaires were programmed into tablet computers to facilitate computer-assisted personal interviewing (CAPI) for data collection, and to offer the option to choose either English, Chichewa or Tumbuka for each questionnaire.

Cleaning operations

All electronic data collected in the 2015-16 MDHS were received via IFSS at the NSO central office in Zomba, where the data were stored on a password-protected computer. The data processing operation included secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by four individuals who took part in the fieldwork training, and were supervised by two senior staff from NSO. Data editing was accomplished with CSPro software. Secondary editing and data processing were initiated in October 2015 and completed in March 2016.

Response rate

A total of 27,516 households were selected for the sample, of which 26,564 were occupied. Of the occupied households, 26,361 were successfully interviewed, for a response rate of 99%.

In the interviewed households, 25,146 eligible women were identified for individual interviews. Interviews were completed with 24,562 women, for a response rate of 98%. In the subsample of households selected for the male survey, 7,903 eligible men were identified and 7,478 were successfully interviewed, for a response rate of 95%.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. 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 2015-16 Malawi Demographic and Health Survey (2015-16 MDHS) to minimise this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the year acronym 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 among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

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% 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 2015-16 MDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed by SAS programs developed by ICF International. These programs use the Taylor linearisation method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

Note: A more detailed description of