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

This survey was conducted in Malawi by the National Statistical Office. 4,849 women between the ages of 15 - 49 and 1,1151 men between the ages of 20-54 were interviewed from September 1992 - November 1992. Major topics covered: Anthropometry; Arm Circumference; HIV Knowledge; Maternal Mortality; Men's Survey; Service Availability

Data access requires registration with USAID. USAID now makes this data available directly on their website, which can be accessed here: https://dhsprogram.com/methodology/survey/survey-display-52.cfm - along with additional years of data here: https://dhsprogram.com/data/available-datasets.cfm

We advise you use this location to access the data as they have updated formats, etc. This material remains in the archive for preservation and historical purposes.

Abstract

The principal aim of the 2002 Malawi DHS EdData Survey (MDES) is to provide upto-date information on education among children of primary school age (age 6-13). The survey focuses on factors influencing household decisions about children's school attendance. These data supplement the data collected by the Ministry of Education, Science, and Technology by focusing on attendance rather than enrolment and exploring the costs of schooling (monetary and non-monetary) and parent/guardian attitudes about schooling.The survey provides data on topics such as the age of children's first school attendance and dropout; the reasons for overage first-time enrolment in school, never enrolling in school, and dropout; the frequency of and reasons for pupil absenteeism; household expenditures on schooling and other contributions to schooling; distances and travel times to schools; and parent/guardian perceptions of school quality and the benefits and disadvantages of schooling.

The 2002 MDES was designed to supplement education data sources and to provide data to assist policy-makers in evaluating education programmes in the country. In broad terms, the 2002 MDES aims to: • Provide baseline data on key education indicators • Assist in the evaluation of Malawi's education programmes • Advance survey methodology in Malawi and contribute to national and international databases.

In more specific terms, the 2002 MDES was designed to: • Provide data on the schooling status of Malawian children of primary school age and on factors influencing whether children ever enrol in school and why pupils drop out of school • Quantify household expenditures on children's schooling and examine differential patterns of expenditure by various background characteristics • Measure parent/guardian attitudes about schoolin - including their perceptions of the quality of schooling and of the effects of Free Primary Education, to provide an understanding of attitudes that shape parents' and guardians. willingness to send their children to school • Measure the frequency of pupil absenteeism and the reasons for missing school in order to suggest approaches to maximise pupil attendance.

Geographic coverage

National

Analysis unit

Households Individuals

Universe

The principal aim of the 2002 Malawi DHS EdData Survey (MDES) is to provide up-to-date information on education among children of primary school age (age 6-13)

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the 2002 MDES was based on the sampling frame for the 2000 MDHS, which was designed to provide estimates of health and demographic indicators. The discussion in this section first addresses the sample design for the 2000 Malawi DHS, then the subsequent design for the 2002 MDES.

The 2000 Malawi DHS was designed to provide estimates at the national and regional levels and for urban and rural areas. It was also designed to provide estimates of some health and demographic indicators at the sub-regional level in 11 districts.

The 2000 Malawi DHS sample points (clusters) were systematically sampled from a list of enumeration areas (EAs) defined in the 1998 Malawi Census of Population and Housing. A total of 560 clusters were drawn from the census sample frame: 449 in rural areas and 111 in urban areas. After selecting the 560 clusters, the NSO trained teams to conduct the comprehensive listing of households and to update maps in the selected clusters. Nine listing teams conducted a comprehensive listing of households and updated maps in the selected clusters, from April through May 2000. This exercise provided a basis for second-stage sampling for the 2000 Malawi DHS-and later, for the 2002 MDES.

After the listing operation, households to be included in the 2000 Malawi DHS were selected; the number of households selected per cluster was inversely proportional to the size of the cluster. In the Malawi DHS sampling frame, as in the 2002 MDES sampling frame, the number of EAs selected in each district was not proportional to the total population; rather, urban areas were oversampled in order to generate unbiased urban estimates.

As part of the 2002 MDES pre-test, a verification exercise was conducted in one urban and two rural enumeration areas around Zomba to estimate what percentage of households identified at the time of the 2000 household listing would be found during the 2002 MDES fieldwork. During this verification exercise-using structure numbers that were written on buildings during the household listing, and the name of the household head at the time of the listing exercise-92 percent of the urban and 95 percent of the rural households were located. These results suggested that the household listing conducted in 2000 as part of the Malawi DHS remained usable for purposes of the 2002 MDES.

While structures and households were still identifiable, in many instances, the household head (and sometimes the entire household) had changed between 2000 and 2002. In 52 percent of the households in the urban area and 15 percent of the households in the rural areas, the name of the household head was different in 2002 than in 2000. In other words, household composition had changed for over half of the households in the urban area and for one-seventh of the households in the rural areas, supporting the decision not to try to link information from the 2000 Malawi DHS and 2002 MDES at the household level.

For the 2002 MDES, 129 EAs-111 in rural areas and 18 in urban areas-were selected from the 560 EAs in the 2000 Malawi DHS sample.The 2002 MDES was designed to provide estimates at the national and regional levels and for urban and rural areas.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used for the 2002 MDES: the Household Questionnaire, the Parent/Guardian Questionnaire, and the Eligible Child Questionnaire.

The three purposes of the MDES Household Questionnaire were to 1) list all household members and visitors to the household, 2) identify which children were eligible (qualified) to be covered by the Eligible Child Questionnaire, and 3) identify a parent or guardian as the respondent for each eligible child. Children age 6-14 were eligible to be covered by the Eligible Child Questionnaire.

The Parent/Guardian Questionnaire collected background information on each parent/guardian respondent and on general education issues. Information was collected on the parent/guardian’s age, education, literacy, and religion. Questions were asked about the walking time and distance to the nearest primary and secondary schools, and about household participation in school activities. Information was also collected on each primary school attended by the children for whom the parent/guardian responded, including the school type and location, the reason for selection of that school, and perceived school quality.

The Eligible Child Questionnaire collected different kinds of information about each eligible child, depending on the child’s schooling status. While the subject of the Eligible Child Questionnaire was the eligible child and his/her schooling, the respondent for the questionnaire was the child’s parent/guardian, as the purpose of the questionnaire was to collect information on issues from the parent/guardian’s perspective. Data were collected on the following topics, according to a child’s schooling status:

• Schooling background and participation during the current school year (attended school during the 2002 school year, dropped out of school, or never attended school) • Frequency of and reasons for pupil absenteeism, household expenditures on schooling, other costs of schooling (for children who attended school during the 2001 school year) • Reasons for dropping out of school (for children who have dropped out of school) • Reasons for not attending school during the 2002 school year (for children who have never attended school) • Children’s eating patterns

In April, the questionnaires were pre-tested in Chichewa in and around Zomba. A total of 108 households were interviewed and 120 Parent/Guardian Questionnaires and 367 Eligible Child Questionnaires were completed. Based on the results of the pre-test, minor changes in the pre-test survey questionnaires were made before the main survey fieldwork was conducted.

Response rate

A total of 3,866 households were selected, of which 3,325 were occupied. Of the 3,325 occupied households, 3,290 were interviewed successfully, yielding a household response rate of 99 percent. In the interviewed households, 2,048 parents/guardians were identified to be interviewed. Completed interviews were conducted with all of these parents/guardians, yielding a response rate of 100 percent. Since the parent/guardians responded to the questions for their children and the children for whom they were responsible, the Eligible Child Questionnaire response rate reflects the percentage of eligible children for whom data were collected. A total of 3,755 eligible children were identified and data were collected on 3,752 of these children, yielding a response rate of nearly 100 percent.

Contains data from the DHS data portal. There is also a dataset containing Malawi - Subnational Demographic and Health Data on HDX.

The DHS Program Application Programming Interface (API) provides software developers access to aggregated indicator data from The Demographic and Health Surveys (DHS) Program. The API can be used to create various applications to help analyze, visualize, explore and disseminate data on population, health, HIV, and nutrition from more than 90 countries.

Abstract

The 2000 Malawi Demographic and Health Survey (MDHS) is a nationally representative sample survey covering 14,213 households, 13,220 women age 15-49, and 3,092 men age 15-54. The 2000 MDHS is similar, but much expanded in size and scope, to the 1992 MDHS. The survey was designed to provide information on fertility trends, family planning knowledge and use, early childhood mortality, various indicators of maternal and child health and nutrition, HIV/AIDS, adult and maternal mortality, and malaria control programme indicators. Unlike earlier surveys in Malawi, the 2000 MDHS sample was sufficiently large to allow for estimates of certain indicators to be produced for 11 districts in addition to estimates for national, regional, and urban-rural domains. Twenty-two mobile survey teams, trained and supervised by the National Statistical Office, conducted the survey from July to November 2000.

The principal aim of the 2000 MDHS project is 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 1992 MDHS survey, a national-level survey of similar scope. The 2000 MDHS survey also strived to collect data that would be comparable to those collected under the international Multiple Indicator Cluster Survey (MICS), sponsored by UNICEF.

In broad terms, the 2000 MDHS survey aimed to : - Assess trends in Malawi's demographic indicators-principally, fertility and mortality - Assist in the evaluation of Malawi's health, population, and nutrition programmes - Advance survey methodology in Malawi and contribute to national and international databases. In more specific terms, the 2000 MDHS survey was designed to provide data on the family planning and fertility behaviour of the Malawian population and to thereby enable policymakers to evaluate and enhance family planning initiatives in the country. - Measure changes in fertility and contraceptive prevalence and at the same time, study 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. A particular emphasis was placed on the area of malaria programmes, including prevention activities and treatment of episodes of fever. - Describe levels and patterns of knowledge and behaviour related to the prevention of HIV/AIDS and other sexually transmitted infections. - Measure the level of adult and maternal mortality at the national level. - Assess the status of women in the country.

SUMMARY OF FINDINGS

• FERTILITY Fertility Decline. The 2000 MDHS data indicate that there has been a modest decline in fertility since the 1992 MDHS. Large Fertility Differentials. Fertility levels remain high in Malawi, especially in rural parts of the country. The total fertility rate among rural women is 6.7 births per woman compared with 4.5 births in urban areas. Childbearing at Young Ages. One-third of adolescent females (age 15-19) have either already had a child or are currently pregnant.

• FAMILY PLANNING Increasing Use of Contraception. A principle cause of the fertility decline in Malawi is the steady increase in contraceptive use over the last decade. Changing Method Mix. Currently, the most widely used methods among married women are injectable contraceptives (16 percent), female sterilisation (5 percent), and the pill (3 percent). Source of Family Planning Methods. The survey results show that government-run facilities remain the major source for contraceptives in Malawi-providing family planning methods to 68 percent of the current users.

• CHILD HEALTH AND SURVIVAL Progress in Reducing Early Childhood Mortality. The 2000 MDHS data indicate that mortality of children under age 5 has declined since the early 1990s. Childhood Vaccination Coverage Declines. The 2000 MDHS results show that 70 percent of children age 12-23 months are fully vaccinated. Improved Breastfeeding Practices. The 2000 MDHS results show that exclusive breast-feeding of children under 4 months of age has increased to 63 percent from only 3 percent in the 1992 MDHS. Nutritional Status of Children. The results show no appreciable change in the nutritional status of children in Malawi since 1992; still, nearly half (49 percent) of the children under age five are chronically malnourished or stunted in their growth.

• MALARIA CONTROL PROGRAMME INDICATORS Bednets. The use of insecticide-treated bednets (mosquito nets) is a primary health intervention proven to reduce malaria transmission. Treatment of Fever in Children Under Age Five. The survey found that 42 percent of children under age five had a fever in the two weeks preceding the survey.

• WOMEN'S HEALTH Maternal Health Care. The survey findings indicate that use of antenatal services remains high in Malawi. Constraints to Use of Health Services. Women in the 2000 MDHS were asked whether certain circumstances constrain their access to and use of health services for themselves. Rising Maternal Mortality. The survey collected data allowing measurement of maternal mortality. For the period 1994-2000, the maternal mortality ratio was estimated at 1,120 maternal deaths per 100,000 live births. This represents a rise from 620 maternal deaths per 100,000 estimated from the 1992 MDHS for the period 1986-1992.

• HIV/AIDS Impact of the Epidemic on Adult Mortality. All-cause mortality has risen by 76 percent among men and 74 percent among women age 15-49 during the 1990s. The age patterns of the increase are consistent with causes related to HIV/AIDS. Improved Knowledge of AIDS Prevention Methods. The 2000 MDHS results indicate that practical AIDS prevention knowledge has improved since the 1996 MKAPH survey. Condom Use. One of the main objectives of the National AIDS Control Programme is to encourage consistent and correct use of condoms, especially in high-risk sexual encounters. The HIV-testing Experience. The 2000 MDHS data show that 9 percent of women and 15 percent of men have been tested for HIV. However, more than 70 percent of both men and women, while not yet tested, said that they would like to be tested.

Geographic coverage

National

Analysis unit

• Household
• Women age 15-49
• Men age 15-54

Universe

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.

Kind of data

Sample survey data

Sampling procedure

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

Abstract

The 1992 Malawi Demographic and Health Survey (MDHS) was a nationally representative sample survey designed to provide information on levels and trends in fertility, early childhood mortality and morbidity, family planning knowledge and use, and maternal and child health. The survey was implemented by the National Statistical Office during September to November 1992. In 5323 households, 4849 women age 15-49 years and 1151 men age 20-54 years were interviewed.

The Malawi Demographic and Health Survey (MDHS) was a national sample survey of women and men of reproductive age designed to provide, among other things, information on fertility, family planning, child survival, and health of mothers and children. Specifically, the main objectives of the survey were to: - Collect up-to-date information on fertility, infant and child mortality, and family planning - Collect information on health-related matters, including breastleeding, antenatal and maternity services, vaccinations, and childhood diseases and treatment - Assess the nutritional status of mothers and children - Collect information on knowledge and attitudes regarding AIDS - Collect information suitable for the estimation of mortality related to pregnancy and childbearing - Assess the availability of health and family planning services.

MAIN FINDINGS

The findings indicate that fertility in Malawi has been declining over the last decade; at current levels a woman will give birth to an average of 6.7 children during her lifetime. Fertility in rural areas is 6.9 children per woman compared to 5.5 children in urban areas. Fertility is higher in the Central Region (7.4 children per woman) than in the Northem Region (6.7) or Southern Region (6.2). Over the last decade, the average age at which a woman first gives birth has risen slightly over the last decade from 18.3 to 18.9 years. Still, over one third of women currently under 20 years of age have either already given birlh to at least one child or are currently pregnant.

Although 58 percent of currently married women would like to have another child, only 19 percent want one within the next two years. Thirty-seven percent would prefer to walt two or more years. Nearly one quarter of married women want no more children than they already have. Thus, a majority of women (61 percent) want either to delay their next birth or end childbearing altogether. This represents the proportion of women who are potentially in need of family planning. Women reported an average ideal family size of 5.7 children (i.e., wanted fertility), one child less than the actual fertility level measured in the survey--further evidence of the need for family planning methods.

Knowledge of contraceptive methods is high among all age groups and socioeconomic strata of women and men. Most women and men also know of a source to obtain a contraceptive method, although this varies by the type of method. The contraceptive pill is the most commonly cited method known by women; men are most familiar with condoms. Despite widespread knowledge of family planning, current use of contraception remains quite low. Only 7 percent of currently married women were using a modem method and another 6 percent were using a traditional method of family planning at the time of the survey. This does, however, represent an increase in the contraceptive prevalence rate (modem methods) from about 1 percent estimated from data collected in the 1984 Family Formation Survey. The modem methods most commonly used by women are the pill (2.2 percent), female sterilisation (1.7 percent), condoms (1.7 percent), and injections (1.5 percent). Men reported higher rates of contraceptive use (13 percent use of modem methods) than women. However, when comparing method-specific use rates, nearly all of the difference in use between men and women is explained by much higher condom use among men.

Early childhood mortality remains high in Malawi; the under-five mortality rate currently stands at 234 deaths per 1000 live births. The infant mortality rate was estimated at 134 per 10130 live births. This means that nearly one in seven children dies before his first birthday, and nearly one in four children does not reach his fifth birthday. The probability of child death is linked to several factors, most strikingly, low levels of maternal education and short intervals between births. Children of uneducated women are twice as likely to die in the first five years of life as children of women with a secondary education. Similarly, the probablity of under-five mortality for children with a previous birth interval of less than 2 years is two times greater than for children with a birth interval of 4 or more years. Children living in rural areas have a higher rate ofunder-fwe mortality than urban children, and children in the Central Region have higher mortality than their counterparts in the Northem and Southem Regions. Data were collected that allow estimation ofmatemalmortality. It is estimated that for every 100,000 live births, 620 women die due to causes related to pregnancy and childbearing.

The height and weight of children under five years old and their mothers were collected in the survey. The results show that nearly one half of children under age five are stunted, i.e., too short for their age; about half of these are severely stunted. By age 3, two-thirds of children are stunted. As with childhood mortality, chronic undernutrition is more common in rural areas and among children of uneducated women.

The duration of breastfeeding is relatively long in Malawi (median length, 21 months), but supplemental liquids and foods are introduced at an early age. By age 2-3 months, 76 percent of children are already receiving supplements.

Mothers were asked to report on recent episodes of illness among their young children. The results indicate that children age 6-23 months are the most vulnerable to fever, acute respiratory infection (ARI), and diarrhea. Over half of the children in this age group were reported to have had a fever, about 40 percent had a bout with diarrhea, and 20 percent had symptoms indicating ARI in the two-week period before the survey. Less than half of recently sick children had been taken to a health facility for treatment. Sixty-three percent of children with diarrhea were given rehydration therapy, using either prepackaged rehydration salts or a home-based preparation. However, one quarter of children with diarrhea received less fluid than normal during the illness, and for 17 percent of children still being breastfed, breastfeeding of the sick child was reduced.

Use of basic, preventive maternal and child health services is generally high. For 90 percent of recent births, mothers had received antenatal care from a trained medical person, most commonly a nurse or trained midwife. For 86 percent of births, mothers had received at least one dose of tetanus toxoid during pregnancy. Over half of recent births were delivered in a health facility.

Child vaccination coverage is high; 82 percent of children age 12-23 months had received the full complement of recommended vaccines, 67 percent by exact age 12 months. BCG coverage and first dose coverage for DPT and polio vaccine were 97 percent. However, 9 percent of children age 12-23 months who received the first doses of DPT and polio vaccine failed to eventually receive the recommended third doses.

Information was collected on knowledge and attitudes regarding AIDS. General knowledge of AIDS is nearly universal in Malawi; 98 percent of men and 95 percent of women said they had heard of AIDS. Further, the vast majority of men and women know that the disease is transmitted through sexual intercourse. Men tended to know more different ways of disease transmission than women, and were more likely to mention condom use as a means to prevent spread of AIDS. Women, especially those living in rural areas, are more likely to hold misconceptions about modes of disease transmission. Thirty percent of rural women believe that AIDS can not be prevented.

Geographic coverage

National

Analysis unit

• Household
• Women age 15-49
• Men age 20-54

Universe

The population covered by the 1992 MDHS is defined as the universe of all women age 15-49 in malawi and all men age 20-54 living in the household.

Kind of data

Sample survey data

Sampling procedure

Based on the 1987 Malawi Population and Housing Census, the country is demarcated into 8,652 enumeration areas (EAs) of roughly equal population size. This sampling frame of census EAs was stratified by urban and rural areas within each of the three administrative regions, making six sampling strata in total. Within each sampling stratum, districts were geographically ordered, thereby providing additional implicit stratification.

The MDHS sample of households was selected in two stages. First, 225 EAs were selected from the 1987 census frame of EAs with probability proportional to population size. The distribution of selected sample points (EAs) is shown in the map of Malawi. The measure of EA size was based on the number of households enumerated during the 1987 census. NSO staff, after being trained in listing procedures and methods for updating maps, were sent to the selected EAs to list all households and produce maps which provided the orientation for later data collection teams in finding selected households. Households in refugee camps and institutional populations (army barracks, police camps, hospitals, etc.) were not listed. In the second stage, a systematic sample of households was selected from the above lists, with the sampling interval from each EA being proportional to its size based on the results of the household listing operation.

Models A and C specify the logarithm of district under five population, and models B and D specify a spline of the log of under five population. Models A and B are for all districts in Malawi except Likoma, while Models C and D are for all districts except Likoma and Zomba districts.

These data are from a cohort of over 4000 pregnant women in Mchinji District, Malawi, who were followed up for 6 months after the end of their pregnancy. The women were asked the London Measure of Unplanned Pregnancy (LMUP) and the pregnancy intention question from the Demographic and Health Survey (DHS) at 1 and 6 months postnatally. The order of these two questions was varied in order to be able to investigate whether there was any effect of question order on the reported level of pregnancy intention with either the LMUP or the DHS.

Abstract

The 2010 Malawi Demographic and Health Survey (2010 MDHS) presents the major findings of a large, nationally representative sample survey conducted by the National Statistical Office (NSO) in partnership with the Ministry of Health Community Sciences Unit (CHSU). It is the fourth survey of its kind to be conducted in Malawi, encompassing a total of 27,000 households and involving 24,000 female and 7,000 male respondents. The survey, which has expanded in sample size over the years, updates the 1992, 2000, and 2004 survey findings. The 2010 report is the second in the series to include results of HIV testing. In addition to presenting national estimates, the report provides estimates of key indicators for rural and urban areas in Malawi, the three regions, and for the first time, the 27 districts.

The 2010 Malawi Demographic and Health Survey (2010 MDHS) was implemented by the National Statistical Office (NSO) from June through November 2010, with a nationally representative sample of more than 27,000 households. All eligible women age 15-49 in these households and all eligible men age 15-54 in a subsample of one-third of the households were individually interviewed.

The survey is a follow-up to the 1992, 2000, and 2004 MDHS surveys, although it expands the content and provides updated estimates of basic demographic and health indicators covered in these earlier surveys. Similar to the 2004 MDHS survey, the 2010 MDHS includes information on violence against women and HIV testing among women age 15-49 and men age 15-54. Although previous surveys collected data at the national, regional, and selected district levels, the 2010 MDHS is the first MDHS survey to collect data on basic demographic and health indicators at the district level.

The primary objectives of the 2010 MDHS project are 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; maternal mortality; maternal and child health; malaria; awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections; and HIV prevalence.

The 2010 MDHS results demonstrate a decline in current fertility, an increase in use of modern methods of contraception, an improvement in child vaccination rates, and expanded coverage of prior HIV testing.

Geographic coverage

The 2010 MDHS called for a nationally representative sample of about 25,600 interviews of women between the ages of 15 and 49. Administratively, Malawi is divided into 28 districts. The sample was designed to provide estimates in 27 districts for most health and demographic indicators. The district of Likoma is small and therefore was combined with Nkhata Bay. Indicators are also shown for the Northern, Central, and Southern Regions of the country.

Analysis unit

• Household
• Women age 15-49
• Men age 15-54
• children age 6-59 months

Universe

The population covered by the 2010 MDHS is defined as the universe of all women age 15-49 in malawi and all men age 15-54 living in the household.

Kind of data

Sample survey data

Sampling procedure

The 2010 MDHS called for a nationally representative sample of about 25,600 interviews of women between the ages of 15 and 49. The survey was designed to provide information on fertility and childhood mortality, family planning, maternal and child health, knowledge and behaviour regarding AIDS and other sexually transmitted infections (STI), domestic violence, and HIV prevalence and other health issues among the adult population.

Administratively, Malawi is divided into 28 districts. The sample was designed to provide estimates in 27 districts for most health and demographic indicators. The district of Likoma is small and therefore was combined with Nkhata Bay. Indicators are also shown for the Northern, Central, and Southern Regions of the country. - Northern Region: Chitipa, Karonga, Likoma, Mzimba, Nkhata Bay, and Rumphi - Central Region: Dedza, Dowa, Kasungu, Lilongwe, Mchinji, Nkhotakota, Ntcheu, Ntchisi, and Salima - Southern Region: Balaka, Blantyre, Chikhwawa, Chiradzulu, Machinga, Mangochi, Mulanje, Mwanza, Neno, Nsanje, Mwanza, Neno, Nsanje, Phalombe, Thyolo, and Zomba

In addition, a men's survey was conducted in a subsample of one in three households selected for the women's survey. All men age 15-54 in the subsample of households were eligible for the men's survey. The men's survey was designed to collect information on family planning, knowledge and behaviour regarding AIDS and other STIs, and adult health issues. All men age 15-54 and all women age 15-49 in the households selected for the men's survey were also eligible for HIV testing.

SAMPLING FRAME

The sampling frame used for the 2010 MDHS was based on summary data for the enumeration areas (EAs) of the 2008 Malawi Population and Housing Census (PHC). The sampling frame consists of 9,145 EAs throughout the nation. Maps delineating the EA boundaries were created. Of the 9,145 EAs, 1,076 are urban and 8,069 are rural. The EA size (i.e., number of regular households in the EA or village) varies from 0 to 954, with an average of 249 households. The sampling frame was stratified into the 27 districts. Within each of the districts, the sampling frame was further stratified by urban and rural areas.

SAMPLE ALLOCATION

Sample allocation plays an important part in sample design because it relates to the survey precision at the national level. In the absence of accurate information on the main survey indicators at the domain level, the best allocation is proportional allocation. The allocation is proportional to the domain's population size. Because the desired sample size at the national level is large (at least 27,200 households), survey precision at the national level was not the only goal for the design of the 2010 MDHS. Rather, given the number of study domains (27 domains), the survey precision at the domain level was an important objective for the 2010 MDHS.

To ensure comparability across the study domains, the sample size for each domain should be similar. Due to the range in population size of the districts, however, proportional allocation could not be used. This would lead to very different levels of precision between the estimates for these districts. The initial plan for the sample design included a flat sample of 1,000 households per district. However, this plan was revised to allow for a larger sample size in the districts of Lilongwe and Blantyre because these two districts contain the major urban centers in the country. The sample size in these districts was increased to 1,300 households, and the target sample size was decreased from 1,000 households to 950 in the eight smallest districts to reach approximately the same target sample size of households at the national level (27,345). Using this approach, the larger domains would be undersampled and the smaller domains would be oversampled to achieve accurate representation of each domain. [Given the small size of the urban population (10 percent), oversampling is applied to urban areas to ensure that the survey precision is comparable across urban and rural areas].

The sample allocation between urban and rural areas is a power allocation, which is an allocation between proportional allocation and equal size allocation. A power value is applied to achieve a satisfactory sample size. Oversampling or undersampling any particular domain does not pose any problems for representativeness if sampling weights are properly calculated and applied in tabulation.

The sample allocation must be converted to a number of primary sampling units (PSUs). It was decided to select 20 households in an urban cluster and 35 households in a rural cluster.The total number of clusters is 849, with 158 urban clusters and 691 rural clusters. The total number of households selected is 27,345, with 3,160 urban households and 24,185 rural households.

SAMPLING PROCEDURE AND UPDATING OF THE SAMPLING FRAME

The 2010 MDHS sample is a stratified sample selected in two stages. Stratification is achieved by separating each study domain into urban and rural areas. Areas are defined as urban or rural based on the classification in the 2008 Malawi PHC. Therefore, the 27 domains are stratified into a total of 54 sampling strata.

Samples are selected independently in every stratum, by a two-stage selection. This means that 54 independent samples were selected, one from each sampling stratum. Implicit stratifications were achieved at each of the lower geographical or administrative levels by sorting the sampling frame according to the geographical/administrative order and by using probability proportional to the size in the first stage of sampling. The explicit and implicit stratifications together guarantee a better scattering of the sampled points.

In the 2010 MDHS design the primary sampling units (PSUs) are the enumeration areas (EAs) from the 2008 Malawi PHC, and the secondary sampling units (SSUs) are the households.

In the first stage of selection for the 2010 MDHS, the 849 EAs were selected with a probability proportional to the size EA. The EA size is the number of households it contains. After this selection and before the data collection, a household listing operation was conducted during May-June 2009 in all of the selected 849 EAs. The listing operation consisted of visits to every selected EA. During the visits, records were made of every structure found on the ground; structures were identified by type (residential or not); number of households in each residential structure were identified; and a location map and a sketch

Abstract

The Integrated Household Survey is one of the primary instruments implemented by the Government of Malawi through the National Statistical Office (NSO) roughly every 3-5 years to monitor and evaluate the changing conditions of Malawian households. The IHS data have, among other insights, provided benchmark poverty and vulnerability indicators to foster evidence-based policy formulation and monitor the progress of meeting the Millennium Development Goals (MDGs), the goals listed as part of the Malawi Growth and Development Strategy (MGDS) and now the Sustainable Development Goals (SDGs).

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals
• Consumption expenditure commodities/items
• Communities
• Agricultural household/ Holder/ Crop
• Market

Universe

Members of the following households are not eligible for inclusion in the survey: • All people who live outside the selected EAs, whether in urban or rural areas. • All residents of dwellings other than private dwellings, such as prisons, hospitals and army barracks. • Members of the Malawian armed forces who reside within a military base. (If such individuals reside in private dwellings off the base, however, they should be included among the households eligible for random selection for the survey.) • Non-Malawian diplomats, diplomatic staff, and members of their households. (However, note that non-Malawian residents who are not diplomats or diplomatic staff and are resident in private dwellings are eligible for inclusion in the survey. The survey is not restricted to Malawian citizens alone.) • Non-Malawian tourists and others on vacation in Malawi.

Kind of data

Sample survey data [ssd]

Sampling procedure

The IHS5 sampling frame is based on the listing information and cartography from the 2018 Malawi Population and Housing Census (PHC); includes the three major regions of Malawi, namely North, Center and South; and is stratified into rural and urban strata. The urban strata include the four major urban areas: Lilongwe City, Blantyre City, Mzuzu City, and the Municipality of Zomba. All other areas are considered as rural areas, and each of the 27 districts were considered as a separate sub-stratum as part of the main rural stratum. The sampling frame further excludes the population living in institutions, such as hospitals, prisons and military barracks. Hence, the IHS5 strata are composed of 32 districts in Malawi.

A stratified two-stage sample design was used for the IHS5.

Note: Detailed sample design information is presented in the "Fifth Integrated Household Survey 2019-2020, Basic Information Document" document.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

HOUSEHOLD QUESTIONNAIRE The Household Questionnaire is a multi-topic survey instrument and is near-identical to the content and organization of the IHS3 and IHS4 questionnaires. It encompasses economic activities, demographics, welfare and other sectoral information of households. It covers a wide range of topics, dealing with the dynamics of poverty (consumption, cash and non-cash income, savings, assets, food security, health and education, vulnerability and social protection). Although the IHS5 household questionnaire covers a wide variety of topics in detail it intentionally excludes in-depth information on topics covered in other surveys that are part of the NSO’s statistical plan (such as maternal and child health issues covered at length in the Malawi Demographic and Health Survey).

AGRICULTURE QUESTIONNAIRE All IHS5 households that are identified as being involved in agricultural or livestock activities were administered the agriculture questionnaire, which is primarily modelled after the IHS3 counterpart. The modules are expanding on the agricultural content of the IHS4, IHS3, IHS2, AISS, and other regional agricultural surveys, while remaining consistent with the NACAL topical coverage and methodology. The development of the agriculture questionnaire was done with input from the aforementioned stakeholders who provided input on the household questionnaire as well as outside researchers involved in research and policy discussions pertaining to the Malawian agriculture. The agriculture questionnaire allows, among other things, for extensive agricultural productivity analysis through the diligent estimation of land areas, both owned and cultivated, labor and non-labor input use and expenditures, and production figures for main crops, and livestock. Although one of the major foci of the agriculture data collection effort was to produce smallholder production estimates for major crops, it is also possible to disaggregate the data by gender and main geographical regions. The IHS5 cross-sectional households supply information on the last completed rainy season (2017/2018 or 2018/2019) and the last completed dry season (2018 or 2019) depending on the timing of their interview.

FISHERIES QUESTIONNAIRE The design of the IHS5 fishery questionnaire is identical to the questionnaire designed for IHS3. The IHS3 fisheries questionnaire was informed by the design and piloting of a fishery questionnaire by the World Fish Center (WFC), which was supported by the LSMS-ISA project for the purpose of assembling a fishery questionnaire that could be integrated into multi-topic household-surveys. The WFC piloted the draft instrument in November 2009 in the Lower Shire region, and the NSO team considered the revised draft in designing the IHS5 fishery questionnaire.

COMMUNITY QUESTIONNAIRE The content of the IHS5 Community Questionnaire follows the content of the IHS3 & IHS4 Community Questionnaires. A “community” is defined as the village or urban location surrounding the enumeration area selected for inclusion in the sample and which most residents recognize as being their community. The IHS5 community questionnaire was administered to each community associated with the cross-sectional EAs interviewed. Identical to the IHS3 and IHS4 approach, to a group of several knowledgeable residents such as the village headman, the headmaster of the local school, the agricultural field assistant, religious leaders, local merchants, health workers and long-term knowledgeable residents. The instrument gathers information on a range of community characteristics, including religious and ethnic background, physical infrastructure, access to public services, economic activities, communal resource management, organization and governance, investment projects, and local retail price information for essential goods and services.

MARKET QUESTIONNAIRE The Market Survey consisted of one questionnaire which is composed of four modules. Module A: Market Identification, Module B: Seasonal Main Crops, Module C: Permanents Crops, and Module D: Food Consumption.

Cleaning operations

DATA ENTRY PLATFORM To ensure data quality and timely availability of data, the IHS5 was implemented using the World Bank’s Survey Solutions CAPI software. To carry out IHS5, 1 laptop computer and a wireless internet router were assigned to each team supervisor, and each enumerator had an 8–inch GPS-enabled Lenovo tablet computer. The use of Survey Solutions allowed for the real-time availability of data as the completed data was completed, approved by the Supervisor and synced to the Headquarters server as frequently as possible. While administering the first module of the questionnaire the enumerator(s) also used their tablets to record the GPS coordinates of the dwelling units. In Survey Solutions, Headquarters can then see the location of the dwellings plotted on a map of Malawi to better enable supervision from afar – checking both the number of interviews performed and the fact that the sample households lie within EA boundaries. Geo-referenced household locations from that tablet complemented the GPS measurements taken by the Garmin eTrex 30 handheld devices and these were linked with publically available geospatial databases to enable the inclusion of a number of geospatial variables - extensive measures of distance (i.e. distance to the nearest market), climatology, soil and terrain, and other environmental factors - in the analysis.

The range and consistency checks built into the application was informed by the LSMS-ISA experience in previous IHS waves. Prior programming of the data entry application allowed for a wide variety of range and consistency checks to be conducted and reported and potential issues investigated and corrected before closing the assigned enumeration area. Headquarters (NSO management) assigned work to supervisors based on their regions of coverage. Supervisors then made assignments to the enumerators linked to their Supervisor account. The work assignments and syncing of completed interviews took place through a Wi-Fi connection to the IHS5 server. Because the data was available in real time it was monitored closely throughout the entire data collection period and upon receipt of the data at headquarters, data was exported to STATA for other consistency checks, data cleaning, and analysis.

DATA MANAGEMENT The IHS5 Survey Solutions CAPI based data entry application was designed to stream-line the data collection process from the field. IHS5 Interviews were collected in “sample” mode (assignments generated from headquarters) as opposed to “census” mode (new interviews created by interviewers from a template) for the NSO to have more control over the sample.

The range and consistency checks built into the application was informed by the LSMS-ISA experience in previous IHS waves. Prior programming of the data

Analysis unit

Woman, Birth, Child, Birth, Man, Household Member

Universe

Women age 15-49, Births, Children age 0-4, Men age 15-54, All persons

Kind of data

Demographic and Household Survey [hh/dhs]

Sampling procedure

MICRODATA SOURCE: National Statistical Office (NSO) [Malawi] and ICF.

SAMPLE UNIT: Woman SAMPLE SIZE: 24562

SAMPLE UNIT: Birth SAMPLE SIZE: 68074

SAMPLE UNIT: Child SAMPLE SIZE: 17286

SAMPLE UNIT: Man SAMPLE SIZE: 7478

SAMPLE UNIT: Member SAMPLE SIZE: 120492

Mode of data collection

Face-to-face [f2f]

Descriptive statistics of all variables included in the data analysis.

Lighting functionality in the delivery area in facilities offering night-time care and delivery services (in %).

Information and communication technologies and medical devices: Odds ratios and 95% confidence intervals of energy source and continuity.

Analysis unit

Woman, Birth, Child, Man, Member

Universe

Women age 15-49, Births, Children age 0-4, Men age 20-54, All persons

Kind of data

Demographic and Household Survey [hh/dhs]

Sampling procedure

MICRODATA SOURCE: National Statistical Office [Malawi] and Macro International Inc.

SAMPLE UNIT: Woman SAMPLE SIZE: 4849

SAMPLE UNIT: Birth SAMPLE SIZE: 16330

SAMPLE UNIT: Child SAMPLE SIZE: 4495

SAMPLE UNIT: Man SAMPLE SIZE: 1151

SAMPLE UNIT: Member SAMPLE SIZE: 25131

Mode of data collection

Face-to-face [f2f]

Analysis unit

Woman, Birth, Child, Man, Member

Universe

Women age 15-49, Births, Children age 0-4, Men age 15-54, All persons

Kind of data

Demographic and Household Survey [hh/dhs]

Sampling procedure

MICRODATA SOURCE: National Statistical Office [Malawi] and ORC Macro.

SAMPLE UNIT: Woman SAMPLE SIZE: 13220

SAMPLE UNIT: Birth SAMPLE SIZE: 40421

SAMPLE UNIT: Child SAMPLE SIZE: 11926

SAMPLE UNIT: Man SAMPLE SIZE: 3092

SAMPLE UNIT: Member SAMPLE SIZE: 63823

Mode of data collection

Face-to-face [f2f]

Malawi MW: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 data was reported at 46.900 % in 2016. This records an increase from the previous number of 22.300 % for 2010. Malawi MW: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 data is updated yearly, averaging 17.700 % from Dec 2000 (Median) to 2016, with 4 observations. The data reached an all-time high of 46.900 % in 2016 and a record low of 11.000 % in 2000. Malawi MW: Women Participating in the Three Decisions: Own Health Care, Major Household Purchases, and Visiting Family: % of Women Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Malawi – Table MW.World Bank: Health Statistics. Women participating in the three decisions (own health care, major household purchases, and visiting family) is the percentage of currently married women aged 15-49 who say that they alone or jointly have the final say in all of the three decisions (own health care, large purchases and visits to family, relatives, and friends).; ; Demographic and Health Surveys (DHS); ;

Description of SPA and DHS samples included in the study.

Electricity sources and continuity by covariate (in percent).

Malawi MW: Demand for Family Planning Satisfied by Modern Methods: % of Married Women with Demand for Family Planning data was reported at 74.600 % in 2016. This records an increase from the previous number of 73.600 % for 2014. Malawi MW: Demand for Family Planning Satisfied by Modern Methods: % of Married Women with Demand for Family Planning data is updated yearly, averaging 44.800 % from Dec 1992 (Median) to 2016, with 7 observations. The data reached an all-time high of 74.600 % in 2016 and a record low of 14.900 % in 1992. Malawi MW: Demand for Family Planning Satisfied by Modern Methods: % of Married Women with Demand for Family Planning data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Malawi – Table MW.World Bank: Health Statistics. Demand for family planning satisfied by modern methods refers to the percentage of married women ages 15-49 years whose need for family planning is satisfied with modern methods.; ; Demographic and Health Surveys (DHS).; Weighted Average;