As of 2019, the Yangon region was the most populous region in Myanmar with a population of over eight million. Located in the south of the country, the region is home to the largest city, Yangon, which is also the former capital of Myanmar. Naypyidaw Union Territory, where the country's capital Naypyidaw is located, had around 1.27 million inhabitants in 2019. The total population of Myanmar amounts to over 53 million and is set to increase over the next years.

In 2023, the total population of all ASEAN states amounted to an estimated 619.02 million inhabitants. The ASEAN (Association of Southeast Asian Nations) member countries are Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand, and Vietnam. ASEAN opportunity The Association of Southeast Asian Nations was founded by five states (Thailand, Indonesia, the Philippines, Malaysia, and Singapore) in 1967 to improve economic and political stability and social progress among the member states. It was originally modelled after the European Union. Nowadays, after accepting more members, their agenda also includes an improvement of cultural and environmental conditions. ASEAN is now an important player on the global stage with numerous alliances and business partners, as well as more contenders wanting to join. The major player in the SouthIndonesia is not only a founding member of ASEAN, it is also its biggest contributor in terms of gross domestic product and is also one of the member states with a positive trade balance. In addition, it has the highest number of inhabitants by far. About a third of all people in the ASEAN live in Indonesia – and it is also one of the most populous countries worldwide. Among the ASEAN members, it is certainly the most powerful one, not just in numbers, but mostly due to its stable and thriving economy.

Myanmar Mobile Phone User: per 100 Population: Shan State data was reported at 80.000 Number in 2018. This records an increase from the previous number of 75.000 Number for 2017. Myanmar Mobile Phone User: per 100 Population: Shan State data is updated yearly, averaging 77.500 Number from Mar 2017 (Median) to 2018, with 2 observations. The data reached an all-time high of 80.000 Number in 2018 and a record low of 75.000 Number in 2017. Myanmar Mobile Phone User: per 100 Population: Shan State data remains active status in CEIC and is reported by Central Statistical Organization. The data is categorized under Global Database’s Myanmar – Table MM.TB002: Mobile Phone User: By State and Region.

This thematic report presents the status of maternal mortality in Myanmar. The analysis shows that maternal mortality in the country is high at 282 deaths per 100,000 live births, and that there is a need for concerted efforts to ensure that women have access to services that provide high quality health care before, during and after childbirth. Furthermore, about 10 per cent of female deaths of women of reproductive age (15-49 years) are attributed to maternal deaths. By State and Region, maternal mortality ratios are very high in Chin, Ayeyawady and Magway, while they are lowest in Tanintharyi, Nay Pyi Taw and Yangon. Although steps are being taken to provide health services in these areas with high maternal mortality, there is also a need to carry out more specialized surveys to determine why mortality rates remain high in the country and in specific States and Regions.

Abstract

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Geographic coverage

The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

Analysis unit

Households and individuals

Universe

The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING GUIDELINES FOR WHS

Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

STRATIFICATION

Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

MULTI-STAGE CLUSTER SELECTION

A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which

Abstract

In order to provide the Government and international funding agencies with a reliable and up to date integrated assessment of all major aspects of household living conditions in the Union of Myanmar, the United Nations Development Programme (UNDP) and the Government of the Union of Myanmar have agreed on the implementation of an Integrated Household Living Conditions Assessment (IHLCA) in 2003-2005.

The expected outputs of this project include: - A nationwide qualitative study on people’s perceptions of poverty in Myanmar including 224 focus groups in December 2003. The results of this study were published in July 2004 in four volumes; - A nationwide quantitative survey of 18,660 households with two rounds of data collection (November-December 2004 and May 2005); - A Poverty Management Information System (PMIS).

The IHLCA involved two phases: (i) the first phase was a qualitative study which aimed at providing information on the perceptions of the people of Myanmar on living conditions to feed into the final selection of indicators to include in the questionnaire of the second quantitative phase of this baseline survey; (ii) this last phase included two rounds of data collection.

The first analysis of IHLCA data led to the preparation of four reports: - Integrated Household Living Conditions Assessment in Myanmar: Poverty Profile; - Integrated Household Living Conditions Assessment in Myanmar: Vulnerability–Relevant Information; - Integrated Household Living Conditions Assessment in Myanmar: MDG-Relevant Information; - Integrated Household Living Conditions Assessment in Myanmar: Quantitative Survey Technical Report.

SURVEY OBJECTIVES

In order to provide a holistic assessment of living conditions in Myanmar, drawing on reliable data that are representative of the country’s population, the IHLCA was a logical continuation of previous assessments of social and economic conditions and outcomes. On the basis of IHLCA results, it will be possible to better understand the situation of the population in relation to poverty, vulnerability and inequality. The information generated will allow for better planning of policies and programs for improving household living conditions.

The main objectives of the Survey were the following: - To obtain an accurate and holistic assessment of population well-being by measuring a number of indicators related to living conditions from an integrated perspective; - To provide reliable and updated data for identifying different levels of poverty in order to help better focus programmatic interventions and prioritize budget allocations; - To provide quantitative and qualitative data for better understanding the dimensions of wellbeing and poverty in Myanmar and the endogenous and exogenous factors behind the observed patterns and trends in living conditions; - To provide baseline information for monitoring progress towards the achievement of the Millennium Development Goals and other national and international targets; - To develop a rigorous and standardized methodology for establishing a framework for monitoring living conditions and conducting future time-trend analysis.

Given the breadth of information that was to be generated by the integrated survey and the range of stakeholders involved in the project, there were also a number of secondary objectives including:

• The compilation of updated statistics for a series of indicators that were also addressed in previous surveys in Myanmar for comparative time-trend analyses on specific aspects of living conditions where appropriate;
• The compilation of precise statistics on the spatial distribution of poor and non-poor households for poverty mapping;
• For economic and social analysis, improved data for monitoring differentials in living conditions by urban-rural residence, gender and other population sub-groups;
• For policy and programmatic formulation, comprehensive data on the population’s perceptions of living conditions, in particular prioritization in terms of their preferences to improve well-being and reduce poverty across regions of the country.

Geographic coverage

Administratively, the Union of Myanmar is divided into 17 States/Divisions. These in turn are subdivided into 61 Districts. Districts are further subdivided into Townships, Wards, Village Tracts and Villages.

The IHLCA Survey covered both the urban and rural areas at the regional and national levels.

The Survey aimed to produce data at the regional level for each of the 17 States/Divisions. No Township estimates were to be provided as this would necessitate too large a sample size. The sample was large enough to provide good sample estimates of a number of important living conditions characteristics at the national level, and reasonably good sample estimates at the State/Division level.

Kind of data

Sample survey data [ssd]

Sampling procedure

In order to minimise sampling errors, the careful design of a statistically sound sampling plan was deemed of critical importance. The starting point of such a plan was a sampling frame, or complete listing of communities and households from which a sample can be drawn, and the desired precision level for key indicators, to be used in the determination of the expected sample size. The sampling plan was designed to collect representative information from a stratified multiple-stage random sample of around 18888 households across all regions of the country.

A number of factors had to be addressed in the determination of a survey design, including the sampling plan. Factors to be considered with regard to sampling were: - The specific objectives of the survey; - The country’s characteristics, in particular its administrative divisions; - The level of precision desired for the resulting estimates; - The desired timeframe for availability of results; - The availability of human and financial resources.

On the one hand, designing a plan to include a very large sample of households would allow for more precise estimates of the selected indicators and enable greater degrees of disaggregation at the sub-national level.

On the other hand, in favor of a sample size that was not too big were the needs of concerned stakeholders to have results available in a timely manner (within a few weeks or months from the end of fieldwork) as well as the workload and budget constraints. Experience has shown that surveys with very large samples: (i) have a high probability of becoming bogged down, creating delays of several years in results publication; (ii) are prone to poor data quality, in particular due to non-sampling errors; and (iii) represent a major disturbing factor for other statistical operations that technical and reporting agencies must conduct. While from an international perspective the financial costs of conducting surveys may be relatively low in Myanmar, the opportunity cost of the time and resources spent on a very large-scale survey and not on other productive activities was taken into account.

Another consideration was the desired level of disaggregation by the IHLCA main data users. It was decided to ensure collection of representative data for the following spatial units: - National level; - States/divisions (17); - Urban/rural areas by state/division.

This breakdown suggested a total of 34 strata (2 area types * 17 states/divisions).

One significant constraint to the design of the sampling plan for the IHLCA quantitative survey was the absence of a reliable updated sampling frame or complete listing of households across the country from which a sample could be drawn. Usually such frames are based on the results of the most recent population census; however there had been no national count in Myanmar since 1983. Updated population estimates were to be obtained from The Department of Population (DOP) of the Ministry of Population. The frame was imperfect. In addition a number of areas were excluded by PD because of inaccessibility for fieldwork implementation due to transportation/communication problems or ongoing security concerns.

The options for selecting households for questionnaire implementation ranged from simple random sampling of households across the country (the most efficient methodology from a purely statistical viewpoint, but one for which fieldwork costs may be prohibitive), to multi-stage random selection based on probability proportional to size (a more commonly used approach given the costs-benefits tradeoffs). However, considering the lack of reliable population numbers at the lowest levels of geographic disaggregation for Myanmar, the sampling plan had to rely on probability proportional to estimated size (PPES) approaches and the measures of size used were the number of households at different geographical levels.

Another issue that was considered in the determination of the sample size was the desired precision level by the IHLCA main data users. The calculation was based on observed variances for key variables in past survey experiences.

Mode of data collection

Face-to-face [f2f]

Research instrument

The following survey questionnaires were used for the IHLCA survey3:

1) The household questionnaire, administered at household level, included 9 modules covering different aspects of household living conditions: Module 1: Household Basic Characteristics; Module 2: Housing; Module 3: Education; Module 4: Health; Module 5: Consumption Expenditures; Module 6: Household Assets; Module 7: Labour and Employment; Module 8: Business; Module 9: Finance and Savings.

2) The Community questionnaire, administered to local key informants, which included 4 modules which aimed at providing general information on the village/wards where the survey was being undertaken and at reducing

Abstract

The MPLCS 2015 is a comprehensive study of how people in Myanmar live. It is a joint analysis conducted by a technical team from the Ministry of Planning and Finance, Government of Myanmar, and the Poverty and Equity Global Practice of the World Bank. It collects data on the occupations of people, how much income they earn, and how they use this to meet the food, housing, health, education, and other needs of their families.

The Myanmar Poverty and Living Conditions Survey has the following objectives: - Put forward trends in poverty between 2004/05, 2009/10 and 2015 - Present a measure of poverty that reflects the situation of poverty in Myanmar in 2015 at the national, urban/rural and agro-zone - Conduct analysis about the situation and nature of poverty in Myanmar that informs policy choices and strategies.

Geographic coverage

National coverage. The survey is a representative of the Union Territory, four agro-zones, and urban/rural areas.

Analysis unit

• Households
• Individuals
• Agricultural parcel and crops
• Consumption items

Universe

The survey covered only the usual household residents, excluding people living in hotels/motels/guesthouses, military camps, police camps, orphanages/homes for the aged, religious centers, boarding schools/colleges/universities, correctional facilities/prisons, hospitals, camps/hostels for workers, and homeless/other collective quarters.

Kind of data

Sample survey data [ssd]

Sampling procedure

The MPLCS sample design was developed based on the sampling frame from the April 2014 Census pre-enumeration listing data. In addition to providing statistically representative estimates at the national level, the sample was designed so that representative estimates were derived for each of four agro-ecological zones (Hills and Mountains, Dry Zone, Coastal and Delta), for the urban/rural levels overall, and specifically Yangon and surrounding area. The data are not representative at the state or region level.

The sample primary sampling units (PSUs) for this sample are the enumeration areas (EAs) defined for the 2014 Myanmar Population and Housing Census. There are 304 EAs and 3648 sample households.

A stratified multi-stage sample design is used for the MLPCS 2015. The stratum are agro--ecological zone and rural/urban. The classification of the EAs in the 2014 Myanmar Census of Population and Housing frame by urban and rural stratum was based on the administrative structure of the hierarchical geographic areas in Myanmar; all EAs in administrative areas defined as wards are considered urban, and all EAs in village tracks are classified as rural. The distribution of the households in the 2014 Myanmar Census of Population and Housing frame by region, urban and rural stratum, based on the preliminary Census data.

Sampling deviation

A total of 14 sample EAs selected for the MPLCS could not be enumerated, mostly because of security problems.

Refer to MPLCS 2014/15 Survey Conduct and Quality Control Report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The MPLCS questionnaire builds from earlier household expenditure and living conditions surveys conducted in Myanmar, in particular, the Integrated Household Living Conditions Assessment (IHCLA-I, 2005 and IHLCA-II, 2010) and the Household Income and Expenditure Survey (between 1989 and 2012) and WORLD BANK's LIVING STANDARD surveys. The MPLCS brings all these previous household surveys together into a single survey and provides one comprehensive source of living conditions information.

The MPLCS 2014/2015 household questionnaire consists of 13 modules. 1. Roster 2. Education and literacy 3a. Health status 3b. Health care 4. Labor and employment 5a. International migration (current household members) 5b. Remittances (former household members and others) 6. Housing 7. Household assets/durables 8a. Household consumption in the last 7 days 8b. Non-food consumption expenditure in the last 30 days 8c. Non-food consumption expenditure in 6 and 12 months 9. Non-farm enterprises 10a. Parcel roster 10b. Inputs 10c. Labor 10d. Harvest and crop disposition 10e. Livestock 10f. Agricultural machinery and equipment 10g. Aquaculture and fisheries 11a. Loans/credit 11b. Financial inclusion 12. Food security/subjective assessment of well-being 13. Shocks and coping strategies

Sampling error estimates

Tables with calculated sampling errors and confidence intervals for the most important survey estimates, the different sources of non-sampling error presented in MPLCS 2015 Survey Conduct and Quality Control Report section 5.

Data appraisal

For detail of data quality control and measurement, see in MPLCS 2015 Survey Conduct and Quality Control Report section 3.5.

Following an outbreak of violence on 25 August 2017 in Rakhine State, Myanmar, a new massive influx of Rohingya refugees to Cox’s Bazar, Bangladesh started in late August 2017. Most of the Rohingya refugees settled in Ukhia and Teknaf Upazilas of Cox’s Bazar, a district bordering Myanmar identified as the main entry area for border crossings.

This dataset presents the result of the NPM Round 14 Site Assessment exercise, which collected information related to the Rohingya refugee population distribution and needs during the months of December 2018 and January-February 2019.

• The data collection for NPM baseline survey was conducted between 9 to 19 December 2018: it provides an update about the population distribution and movements.
• The data collection for NPM Site Assessment survey was conducted between 14 January to 13 February 2019: in addition to an update about the population figures, this includes a multi-sectoral needs assessment.

Rohingya refugee population distribution by para in Teknaf upazila. Please click here.

Abstract

Following an outbreak of violence on 25 August 2017 in Rakhine State, Myanmar, a new massive influx of Rohingya refugees to Cox’s Bazar, Bangladesh started in late August 2017. Most of the Rohingya refugees settled in Ukhia and Teknaf Upazilas of Cox’s Bazar, a district bordering Myanmar identified as the main entry area for border crossings.

This dataset presents the result of the NPM Round 11 exercise, which collected information related to the Rohingya refugee population distribution and needs during the months of June and July 2018.

• The data collection for NPM baseline survey was conducted between 2 and 14 June 2018: it provides an update about the population distribution and movements.
• The data collection for NPM Site Assessment survey was conducted between 1 and 22 July 2018: in addition to an update about the population figures, this includeds a multi-sectoral needs assessment.

The full maps and GIS packages by camp produced based on NPM Baseline and Site Assessment 11 are available at the links below:

• Please click here to access the data by camp as of May 2018.
• Please click here to access the data by camp as of July 2018.

Rohingya refugee population distribution by para in Teknaf upazila. - Please click here.

Geographic coverage

Bangladesh

Kind of data

Observation data/ratings [obs]

Following extreme violence in August 2017 in Rakhine State, Myanmar, an estimated 700,000 Rohingya refugees fled to Cox’s Bazar district, Bangladesh. Previous influxes were recorded in October 2016, when approximately 87,000 people crossed into Bangladesh, and other waves were registered during the previous decades. Most of the Rohingya refugees settled in Ukhyia and Teknaf Upazilas of Cox’s Bazar, a district bordering Myanmar identified as the main entry area for border crossings.

The two datasets present the results of the NPM Round 17 Site Assessment exercise, which collected information related to the Rohingya refugee population distribution and multisectoral needs. Information for this assessment was collected using Key Informant Interview methodology. Female key informants in 1906 locations and Male key informants in 1990 locations were interviewed face to face between the 18th December 2019 – 28th January 2020.