Abstract

The 2022 Nepal Demographic and Health Survey (NDHS) is the sixth survey of its kind implemented in the country as part of the worldwide Demographic and Health Surveys (DHS) Program. It was implemented by New ERA under the aegis of the Ministry of Health and Population (MoHP) of the Government of Nepal with the objective of providing reliable, accurate, and up-to-date data for the country.

The primary objective of the 2022 NDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the 2022 NDHS collected information on fertility, marriage, family planning, breastfeeding practices, nutrition, food insecurity, maternal and child health, childhood mortality, awareness and behavior regarding HIV/AIDS and other sexually transmitted infections (STIs), women’s empowerment, domestic violence, fistula, mental health, accident and injury, disability, and other healthrelated issues such as smoking, knowledge of tuberculosis, and prevalence of hypertension.

The information collected through the 2022 NDHS is intended to assist policymakers and program managers in evaluating and designing programs and strategies for improving the health of Nepal’s population. The survey also provides indicators relevant to the Sustainable Development Goals (SDGs) for Nepal.

Geographic coverage

National coverage

Analysis unit

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

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, men ageed 15-49, and all children aged 0-4 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2022 NDHS is an updated version of the frame from the 2011 Nepal Population and Housing Census (NPHC) provided by the National Statistical Office. The 2022 NDHS considered wards from the 2011 census as sub-wards, the smallest administrative unit for the survey. The census frame includes a complete list of Nepal’s 36,020 sub-wards. Each sub-ward has a residence type (urban or rural), and the measure of size is the number of households.

In September 2015, Nepal’s Constituent Assembly declared changes in the administrative units and reclassified urban and rural areas in the country. Nepal is divided into seven provinces: Koshi Province, Madhesh Province, Bagmati Province, Gandaki Province, Lumbini Province, Karnali Province, and Sudurpashchim Province. Provinces are divided into districts, districts into municipalities, and municipalities into wards. Nepal has 77 districts comprising a total of 753 (local-level) municipalities. Of the municipalities, 293 are urban and 460 are rural.

Originally, the 2011 NPHC included 58 urban municipalities. This number increased to 217 as of 2015. On March 10, 2017, structural changes were made in the classification system for urban (Nagarpalika) and rural (Gaonpalika) locations. Nepal currently has 293 Nagarpalika, with 65% of the population living in these urban areas. The 2022 NDHS used this updated urban-rural classification system. The survey sample is a stratified sample selected in two stages. Stratification was achieved by dividing each of the seven provinces into urban and rural areas that together formed the sampling stratum for that province. A total of 14 sampling strata were created in this way. Implicit stratification with proportional allocation was achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before sample selection, according to administrative units at the different levels, and by using a probability-proportional-to-size selection at the first stage of sampling. In the first stage of sampling, 476 primary sampling units (PSUs) were selected with probability proportional to PSU size and with independent selection in each sampling stratum within the sample allocation. Among the 476 PSUs, 248 were from urban areas and 228 from rural areas. A household listing operation was carried out in all of the selected PSUs before the main survey. The resulting list of households served as the sampling frame for the selection of sample households in the second stage. Thirty households were selected from each cluster, for a total sample size of 14,280 households. Of these households, 7,440 were in urban areas and 6,840 were in rural areas. Some of the selected sub-wards were found to be overly large during the household listing operation. Selected sub-wards with an estimated number of households greater than 300 were segmented. Only one segment was selected for the survey with probability proportional to segment size.

For further details on sample design, see APPENDIX A of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four questionnaires were used in the 2022 NDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Nepal. In addition, a self-administered Fieldworker Questionnaire collected information about the survey’s fieldworkers.

Input was solicited from various stakeholders representing government ministries and agencies, nongovernmental organizations, and international donors. After all questionnaires were finalized in English, they were translated into Nepali, Maithili, and Bhojpuri. The Household, Woman’s, and Man’s Questionnaires were programmed into tablet computers to facilitate computer-assisted personal interviewing (CAPI) for data collection purposes, with the capability to choose any of the three languages for each questionnaire. The Biomarker Questionnaire was completed on paper during data collection and then entered in the CAPI system.

Cleaning operations

Data capture for the 2022 NDHS was carried out with Microsoft Surface Go 2 tablets running Windows 10.1. Software was prepared for the survey using CSPro. The processing of the 2022 NDHS data began shortly after the fieldwork started. When data collection was completed in each cluster, the electronic data files were transferred via the Internet File Streaming System (IFSS) to the New ERA central office in Kathmandu. The data files were registered and checked for inconsistencies, incompleteness, and outliers. Errors and inconsistencies were immediately communicated to the field teams for review so that problems would be mitigated going forward. Secondary editing, carried out in the central office at New ERA, involved resolving inconsistencies and coding the open-ended questions. The New ERA senior data processor coordinated the exercise at the central office. The NDHS core team members assisted with the secondary editing. The paper Biomarker Questionnaires were compared with the electronic data file to check for any inconsistencies in data entry. The pictures of vaccination cards that were captured during data collection were verified with the data entered. Data processing and editing were carried out using the CSPro software package. The concurrent data collection and processing offered a distinct advantage because it maximized the likelihood of the data being error-free and accurate. Timely generation of field check tables allowed for effective monitoring. The secondary editing of the data was completed by July 2022, and the final cleaning of the data set was completed by the end of August.

Response rate

A total of 14,243 households were selected for the sample, of which 13,833 were found to be occupied. Of the occupied households, 13,786 were successfully interviewed, yielding a response rate of more than 99%. In the interviewed households, 15,238 women age 15-49 were identified as eligible for individual interviews. Interviews were completed with 14,845 women, yielding a response rate of 97%. In the subsample of households selected for the men’s survey, 5,185 men age 15-49 were identified as eligible for individual interviews and 4,913 were successfully interviewed, yielding 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 result from mistakes made in implementing data collection and in data processing, such as failing to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and entering the data incorrectly. Although numerous efforts were made during the implementation of the 2022 Nepal Demographic and Health Survey (2022 NDHS) to minimize 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 2022 NDHS is only one of many samples that could have been selected from the same population, using the same design and expected sample size. Each of these samples would yield results that differ somewhat from the results of the selected sample. Sampling errors are a measure of the variability among all possible samples. Although the exact degree of variability is unknown, 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, and so on), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the

Abstract

The Nepal Multiple Indicator Cluster Survey (NMICS) 2010 is a subnational survey of 7,372 women aged 15–49 years and 3,574 children under five from 6,000 households in the Mid- and Far Western Regions (MFWR) of Nepal. NMICS 2010 was implemented as part of the fourth round of the global MICS household survey programme with technical and financial support from UNICEF Nepal in collaboration with the Government of Nepal. The main purpose of NMICS 2010 is to support the government to generate statistically sound and comparable data for monitoring the situation of children and women in the MFWR of the country. NMICS 2010 covers topics related to nutrition, child health, water and sanitation, reproductive health, child development, literacy and education, child protection, HIV and AIDS, mass media and the use of information and communication technology, attitude towards domestic violence, the use of tobacco and alcohol, and life satisfaction. In addition, NMICS 2010 is the first survey in Nepal to provide baseline information on the prevalence of chaupadi (women who live in a separate house or animal shed during menstruation) in the MFWR and evidence on women’s life satisfaction.

Geographic coverage

Mid- and Far- Western regions, both urban and rual areas. (Mid-Western Mountains, Mid-Western Hills, Mid-Western Terai, Far Western Mountains, Far Western Hills,and Far Western Terai)

Analysis unit

• individuals
• households

Universe

The survey covered all de jure household members (usual residents), all women aged between 15-49 years, and all children under 5 living in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The primary objective of the sample design for NMICS 2010 was to produce statistically reliable estimates of most indicators at each of the six subregions: Mid-Western Mountains, Mid-Western Hills, Mid-Western Terai, Far Western Mountains, Far Western Hills and Far Western Terai. It also provides estimates in aggregate at urban and rural areas of the combined Mid- and Far Western Regions of Nepal. In subregions where urban areas exist, (i.e., four of six subregions), urban and rural areas were defined as the sampling strata.

A two-stage, cluster sampling design was used for the selection of the survey sample.

The target sample size for NMICS 2010 was calculated as 6,000 households. For the calculation of the sample size, the key indicator used was the comprehensive knowledge about the HIV transmission among women aged 15-49 years.

The resulting number of households from this exercise was 1,000 households, which is the sample size needed in each subregion-thus yielding about 6,000 in total. The average number of households selected per cluster for NMICS 2010 was determined as 25 households, based on a number of considerations, including the design effect, intra-class correlation coefficient, the budget available, and the time that would be needed per team to complete one cluster. Dividing the total number of households by the number of sample households per cluster, it was calculated that 40 sample clusters would need to be selected in each subregion.

Equal allocation of the total sample size to the six subregions was used. Therefore, 40 clusters were allocated to each subregion, with the final sample size calculated at 6,000 households (40 clusters * 6 subregions * 25 sample households per cluster). In each subregion, the clusters (primary sampling units) were distributed to urban and rural domains, proportional to the size of urban and rural households in that subregion.

The sampling procedures are more fully described in "Nepal Multiple Indicator Cluster Survey 2010 - Final Report" pp.196-200.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2010 Nepal MICS used the standard MICS4 questionnaires and included several country-specif ic questions and modules. Three sets of questionnaires were used in the survey.

Household questionnaires were administered to a knowledgeable adult living in the household. The household questionnaire includes household listing form, education, water and sanitation, household characteristics, child labour, de-worming (Nepal-specific module), child discipline, handwashing and salt iodisation.

In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49 and children under age five. The questionnaire for children under 5 years of age was administered to mothers or caregivers of all children under 5 years of age living in the households.

The women's questionnaire includes woman's background, access to mass media and use of information communication technology, desire for last birth, maternal and newborn health, illness symptoms, contraception, unmet need, attitudes toward domestic violence (Nepal-specific module), marriage/union, HIV/AIDS Tobacco and alcohol use and life satisfaction.

The children's questionnaire includes child's age, birth registration, early childhood development, breastfeeding, care of illness, malaria, immunization and child grant (Nepal-specific module).

Cleaning operations

Data were entered using the CSPro software on four microcomputers by four data-entry operators and two data-entry supervisors. In order to ensure a high level of quality control, all questionnaires were double-entered and internal consistency checks were performed. Procedures and standard programmes developed under the global MICS4 programme and adapted to the Nepal questionnaires were used throughout. Data entry started in November 2010 and was completed in March 2011. Data were analysed using the Statistical Package for Social Sciences (SPSS) software programme, Version 18. The model syntax and tabulation plans developed by UNICEF were used for this purpose.

Response rate

Of the 6,000 households selected for the sample, 5,917 were found to be occupied. Of these, 5,899 were successfully interviewed, giving a household response rate of 99.7 percent. In interviewed households, 7,674 women (aged 15–49 years) were identified. Of these, 7,372 were successfully interviewed, yielding a response rate of 96.1 percent within interviewed households. In addition, 3,688 children under five were listed in the household questionnaire. Questionnaires were completed for 3,574 of these children, giving a response rate of 96.9 percent within interviewed households. Overall response rates of 95.8 percent and 96.6 percent are calculated for women’s and under-fives’ interviews, respectively. Response rates for households, women and children under five were similar (above 95 percent) between urban/rural areas and across all subregions.

Sampling error estimates

Sampling errors are a measure of the variability between the estimates from all possible samples. The extent of variability is not known exactly, but can be estimated statistically from the survey data.

The following sampling error measures are presented in this appendix for each of the selected indicators: • Standard error (se): Sampling errors are usually measured in terms of standard errors for particular indicators (means, proportions etc). Standard error is the square root of the variance of the estimate. The Taylor linearization method is used for the estimation of standard errors. • Coefficient of variation (se/r) is the ratio of the standard error to the value of the indicator, and is a measure of the relative sampling error. • Design effect (deff) is the ratio of the actual variance of an indicator, under the sampling method used in the survey, to the variance calculated under the assumption of simple random sampling. The square root of the design effect (deft) is used to show the efficiency of the sample design in relation to the precision. A deft value of 1.0 indicates that the sample design is as efficient as a simple random sample, while a deft value above 1.0 indicates the increase in the standard error due to the use of a more complex sample design. • Confidence limits are calculated to show the interval within which the true value for the population can be reasonably assumed to fall, with a specified level of confidence. For any given statistic calculated from the survey, the value of that statistic will fall within a range of plus or minus two times the standard error (r + 2.se or r – 2.se) of the statistic in 95 percent of all possible samples of identical size and design.

For the calculation of sampling errors from NMICS data, SPSS Version 18 Complex Samples module has been used. The results are shown in the tables that follow. In addition to the sampling error measures described above, the tables also include weighted and unweighted counts of denominators for each indicator.

Sampling errors are calculated for indicators of primary interest, for the sub national level, for the subregions, and for urban and rural areas. One of the selected indicators is based on households, five are based on household members, 15 are based on women, and 15 are based on children under five. All indicators presented here are in the form of proportions.

Data appraisal

A series of data quality tables are available to review the quality of the data and include the following:

• Age distribution of the household population
• Age distribution of eligible and interviewed women
• Age distribution of under-5s in household and under-5 questionnaires
• Women's completion rates by socio-economic characteristics of households

- Completion rates for under-5 questionnaires by socio-economic characteristics of households

Abstract

The objective of the three-year Nepal Household Risk and Vulnerability panel survey is to provide the Government of Nepal with empirical evidence on the patterns of exposure to shocks at the household level and on the vulnerability of households' welfare to these shocks. It covers 6,000 households and 400 communities in non-metropolitan areas of Nepal. The survey helps address the following research questions:

a) What significant adverse events (both anticipated and unanticipated) are faced by households during a given year? b) What strategies do households employ, and what systems of informal support do they rely on (ex-ante and ex-post) to cope with these events? c) How are households' short- and medium-term welfare affected by these events? d) What formal government assistance do households receive? Is it sufficient to help them cope?

Geographic coverage

National level

Analysis unit

Households

Universe

All households in non-metropolitan areas per the 2010 Census definition, excluding households in the Kathmandu valley (Kathmandu, Lalitpur and Bhaktapur districts).

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample frame was segmented into 11 analytical strata, defined to correspond to those used in the Nepal LSS III (excluding the three urban strata used there). The allocation of districts to strata are indicated in the “Section_0” file of each wave. To increase the concentration of sampled households, 50 of the 75 districts in Nepal were selected with probability proportional to size (the measure of size being the number of households). PSUs were selected with probability proportional to size from the entire list of wards in the 50 selected districts, one stratum at a time. The number of PSUs per stratum is proportional to the stratum's population share and corresponds closely to the allocations used in the LFS-II and Nepal LSS-III (adjusted for different overall numbers of PSUs in those surveys). In each of the selected PSUs (administrative wards), survey teams compiled a list of households in the ward based on existing administrative records and cross-checked with local leaders. The number of households shown in the list was compared to the ward population in the 2010 Census, adjusted for likely population growth. Where the listed population deviated by more than 10% from the projected population based on the census data, the team conducted a full listing of households in the ward. 15 households were selected at random each ward list for interviewing, and a further 5 households were selected as potential replacements.

Sampling deviation

During the fieldwork, one PSU in Lapu VDC was inaccessible due to weather, and was replaced by a ward in Hastichaur VDC using PPS sampling on that stratum (excluding the already selected PSUs). All other sampled PSUs were reached and retained throughout the three-year study period. Response rates were high, with 5,654 (94%) of the 6,000 Wave 1 households participating in all three waves. In Wave 2, a sample of 6,005 households were interviewed, of which 5,835 (97%) were households from Wave 1, and 165 (3%) were new households added to replace Wave 1 households that could not be reached. Additionally, five households that had split since Wave 1 were also interviewed. In Wave 3, a sample of 6,051 households were interviewed. The number was higher because some households interviewed in Wave 1 but not in Wave 2 were reached again in Wave 3. Of the 6,051 households, 192 were replacement households and four were split households. The majority of non-response was explained by respondents not being located or having migrated.

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

After the data collection was complete, data cleaning started in HQ. During data cleaning the following actions were carried out:

• Different Versions of HH Questionnaires were appended
• Variables were labelled
• Data exported to STATA
• Responses were checked under possible responses (by do files) and extreme values were verified and checked by back check-calls
• Answers to open ended questions were translated

Cleaned data set was submitted to the World Bank Team for further analysis.

Response rate

94 percent

Data appraisal

The data was cleaned for spelling errors and translation of Nepali phrases, and suspicious values were checked by calling respondents. Datafiles can be linked within and across waves using the unique household-level identifier HHID, and the unique individual-level identifier, MEMBER_ID. Care was taken to ensure these variables correctly identify the same individual and households across rounds, but researchers should independently check consistency before use. No other transformations have taken place.

Abstract

The NLSS 1995/96 is basically limited to the living standards of households.

The basic objectives of this survey was to provide information required for monitoring the progress in improving national living standards and to evaluate the impact of various government policies and program on living condition of the population. This survey captured comprehensive set of data on different aspects of households welfare like consumption, income, housing, labour markets, education, health etc.

Geographic coverage

National coverage The 4 strata of the survey: - Mountains - Hills (Urban) - Hills (Rural) - Terai

Analysis unit

• Household
• Individual
• Community

Universe

The survey covered all modified de jure household members (usual residents).

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design

Sample Frame: A complete list of all wards in the country, with a measure of size, was developed in order to select from it with Probability Proportional to Size (PPS) the sample of wards to be visited. The 1991 Population Census of Nepal was the best starting point for building such a sample frame. The Central Bureau of Statistics (CBS) constructed a data set with basic information from the census at the ward level. This data set was used as a sample frame to develop the NLSS sample.

Sample Design: The sample size for the NLSS was set at 3,388 households. This sample was divided into four strata based on the geographic and ecological regions of the country: (i) mountains, (ii) urban Hills, (iii) rural Hills, and (iv) Terai.

The sample size was designed to provide enough observations within each ecological stratum to ensure adequate statistical accuracy, as well as enough variation in key variables for policy analysis within each stratum, while respecting resource constraints and the need to balance sampling and non-sampling errors.

A two-stage stratified sampling procedure was used to select the sample for the NLSS. The primary sampling unit (PSU) is the ward, the smallest administrative unit in the 1991 Population Census. In order to increase the variability of the sample, it was decided that a small number of households - twelve - would be interviewed in each ward. Thus, a total of275 wards was obtained.

In the first stage of the sampling, wards were selected with probability proportional to size (PPS) from each of the four ecological strata, using the number of household in the ward as the measure of size. In order to give the sample an implicit stratification respecting the division of the country into Development Regions, the sample frame was sorted by ascending order of district codes, and these were numbered from East to West. The sample frame considered all the 75 districts in the country, and indeed 73 of them were represented in the sample. In the second stage of the sampling, a fixed number of households were chosen with equal probabilities from each selected PSU.

The two-stage procedure just described has several advantages. It simplified the analysis by providing a self-weighted sample. It also reduced the travel time and cost, as 12 or 16 households are interviewed in each ward. In addition, as the number of households to be interviewed in each ward was known in advance, the procedure made it possible to plan an even workload across different survey teams.

Mode of data collection

Face-to-face [f2f]

Research instrument

A preliminary draft of the questionnaire was first prepared with several discussions held between the core staff and the consultant to the project. Several documents both received from the world bank as well as from countries that had already conducted such surveys in the past were referred during this process. Subsequently the questionnaire was translated into NepalI.

After a suitable draft design of the questionnaire, a pre-test was conducted in five different places of the country. The places selected for the pre-test were Biratnagar, Rasuwa, Palpa, Nepalganj and Kathmandu Valley. The entire teams created for the pre-test were also represented by either a consultant or an expert from the bank. Feedback received from the field was utilized for necessary improvements in finalizing the seventy page questionnaire.

The content of each questionnaire is as follows:

HOUSEHOLD QUESTIONNAIRE

Section 1. HOUSEHOLD INFORMATION This section served two main purposes: (i) identify every person who is a member of the household, and (ii) provide basic demographic data such as age, sex, and marital status of everyone presently living in the household. In addition, information collected also included data on all economic activities undertaken by household members and on unemployment.

Section 2. HOUSING This section collected information on the type of dwelling occupied by the household, as well as on the household's expenditures on housing and amenities (rent, expenditure on water, garbage collection, electricity, etc.).

Section 3. ACCESS TO FACILITIES This section collected information on the distance from the household's residence to various public facilities and services.

Section 4. MIGRATION This section collected information from the household head on permanent migration for reasons of work or land availability.

Section 5. FOOD EXPENSES AND HOME PRODUCTION This section collected information on all food expenditures of the household, as well as on consumption of food items that the household produced.

Section 6. NON-FOOD EXPENDITURES AND INVENTORY OF DURABLE GOODS This section collected information on expenditure on non-food items (clothing, fuels, items for the house, etc.), as well as on the durable goods owned by the household.

Section 7. EDUCATION This section collected information on literacy for all household members aged 5 years and above, on the level of education for those members who have attended school in the past, and on levelof education and expenditures on schooling for those currently attending an educational institution.

Section 8. HEALTH This section collected information on illnesses, use of medical facilities, expenditure on health care, children's immunization, and diarrhea.

Section 9. ANTHROPOMETRICS This section collected weight and height measurements for all children 3 years or under.

Section 10. MARRIAGE AND MATERNITY HISTORY This section collected information on maternity history, pre/post-natal care, and knowledge/use of family planning methods.

Section 11. WAGE EMPLOYMENT This section collected information on wage employment in agriculture and in non-agricultural activities, as well as on income earned through wage labor.

Section 12. FARMING AND LIVESTOCK This section collected information on all agricultural activities -- land owned or operated, crops grown, use of crops, income from the sale of crops, ownership of livestock, and income from the sale of livestock.

Section 13. NON-FARM ENTERPRISES/ACTIVITIES This section collected information on all non-agricultural enterprises and activities -- type of activity, revenue earned, expenditures, etc.

Section 14. CREDIT AND SAVINGS This section collected information on loans made by the household to others, or loans taken from others by household members, as well as on land, property, or other fixed assets owned by the household.

Section 15. REMITTANCES AND TRANSFERS This section collected information on remittances sent by members of the household to others and on transfers received by members of the household from others.

Section 16. OTHER ASSETS AND INCOME This section collected information on income from all other sources not covered elsewhere in the questionnaire.

Section 17. ADEQUACY OF CONSUMPTION This section collected information on whether the household perceives its level of consumption to be adequate or not.

RURAL COMMUNITY QUESTIONNAIRE

Section 1. POPULATION CHARACTERISTICS AND INFRASTRUCTURES This section collected information on the characteristics of the community, availability of electricity and its services and water supply and sewerage.

Section 2. ACCESS TO FACILITIES Data on services and amenities, education status and health facilities was collected.

Section 3. AGRICULTURE AND FORESTRY Information on the land situation, irrigation systems, crop cycles, wages paid to hired labor, rental rates for cattle and machinery and forestry use were asked in this section.

Section 4. MIGRATION This section collected information on the main migratory movements in and out.

Section 5. DEVELOPMENT PROGRAMS, USER GROUPS, etc. In this section, information on development programs, existence user groups, and the quality of life in the community was collected.

Section 6. RURAL PRIMARY SCHOOL This section collected information on enrollment, infrastructure, and supplies.

Section 7. RURAL HEALTH FACILITY This section collected information on health facilities, equipment and services available, and health personnel in the community.

Section 8. MARKETS AND PRICES This section collected information on local shops, Haat Bazaar, agricultural inputs, sale of crops and the conversion of local units into standard units.

URBAN COMMUNITY QUESTIONNAIRE

Section 1. POPULATION CHARACTERISTICS AND INFRASTRUCTURE Information was collected on the characteristics of the community, availability of electricity, water supply and sewerage system in the ward.

Section 2. ACCESS TO FACILITIES This section collected information on the distance from the community to the various places and public facilities and services.

Section 3. MARKETS AND PRICES This section collected information on the availability and prices of different goods.

Section 4. QUALITY OF LIFE Here the notion of the quality of life in the community was

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system. The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Abstract

Since its inception in the mid-1990s, the Multiple Indicator Cluster Surveys programme, known as MICS, has become the largest source of statistically sound and internationally comparable data on children and women worldwide. In countries as diverse as Bangladesh, Thailand, Fiji, Qatar, Cote d’Ivoire, Turkmenistan and Argentina, trained fieldwork teams conduct face-to-face interviews with household members on a variety of topics – focusing mainly on those issues that directly affect the lives of children and women. MICS is an integral part of plans and policies of many governments around the world, and a major data source for more than 30 Sustainable Development Goals (SDGs) indicators. The MICS programme continues to evolve with new methodologies and initiatives, including MICS Plus, MICS Link, MICS GIS and the MICS Tabulator.

Geographic coverage

Nepal The majority of MICS surveys are designed to be representative at the national level. Sample sizes are sufficient to generate robust data at the regional or provincial levels, and for urban and rural areas. Subnational surveys, covering specific population groups (such as Palestinians in Lebanon) or specific geographical areas (such as selected regions of East in Afghanistan) within countries are also conducted.

Analysis unit

Household, Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample sizes vary greatly from one survey to the other, currently averaging around 12,000 households (for national surveys).

The sample for the Multiple Indicator Cluster Survey (MICS) was designed to provide estimates on a large number of indicators on the situation of children and women at the national level, for areas of residence, and for geographical locations, such as regions, governorates, or districts. A multi-stage, stratified cluster sampling approach was typickly used for the selection of the survey sample. MICS6 surveys are not self-weighting. For reporting national level results, sample weights were used. A more detailed description of the sample design can be found in Appendix A of Final Report.

Mode of data collection

Face-to-face [f2f]

Research instrument

MICS questionnaires were designed by implementing agencies, typically the National Statistical Offices. In each country, MICS questionnaires were based on an assessment of the country’s data needs. The starting point were the standard MICS questionnaires designed by UNICEF’s Global MICS Team, in close coordination with experts, development partners and other international survey programmes. Countries chose from the MICS modules in the standard MICS questionnaires. UNICEF’s MICS experts supported implementing agencies to customize the questionnaires, as required, to the national setting. All survey activities, from sample and survey design, to fieldwork and report writing are carried out by the implementing agencies – with continuous technical support from UNICEF.

The sixth round of MICS included six model questionnaires: • Household Questionnaire • Water Quality Testing Questionnaire • The Questionnaire for Individual Women • The Questionnaire for Individual Men • The Questionnaire for Children Age 5-17 and • The Questionnaire for Children Under Five

The flexible, modular nature of MICS questionnaires makes it easy to remove modules which may not be relevant, and modules for which there is already good quality data from other sources.

Refer to tools page on mics.unicef.org for more detailed information on the flow of questionnaires and contents of the modules.

Abstract

Although various socio-economic surveys are being conducted in Nepal, at times these surveys do not coincide with the planning and reporting cycles of HMG and UN agencies. Also, different surveys have different objectives, but the data from a comprehensive survey that covers indicators related to women and children is always valuable. A comprehensive Nepal Family Health Survey was conducted in 1996, which provided data for the mid-decade review in retrospect. Current data and indicators relating to issues of women and children are needed for gender specific planning and policy formulation. These data can also be used in planning other national-level programmes which are to begin in the middle of next year. This has led to the planning and execution of the present survey to generate data and indicators related to issues of women and children.

The primary objective of the Between Census Household Information for Monitoring and Evaluation System (BCHIMES) was to provide social indicators on issues related to women and children. This survey has come up with indicators on issues related to women and children for an end-decade assessment of progress of this decade and provide benchmark data for the next programme cycle.

Geographic coverage

National coverage Urban/Rural areas Ecological zones Sub-regions All eco-development regions of the Hills and Terai For mountain eco-development regions:

Eastern, Central & Western Mountains combined in one group Mid- and Far-western Mountains combined in another group Kathmandu Valley

Analysis unit

Household as well as individual

Universe

The survey covered all selected household members, all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The NMIS evaluation report suggested that instead of two cycles per year in NMIS one survey be carried out every year with detailed analysis that would have wide-ranging dissemination and plans of data use. In the future, BCHIMES (Between Census Household Information, Monitoring and Evaluation System) will be conducted on a regular basis to generate needed data. The following suggestions were also made in the NMIS evaluation report for the effective design of the sample:

• For every new study, always select a new sample so as to minimise the Hawthorne effect.
• In order to minimise the standard error of the estimate, always try to make the cluster size small, i.e., around 50, as compared to an average cluster size of 120 for the NMIS cycles.

Thus, the new sample design should limit the average cluster size to 50 or smaller and a new sample should be drawn for a new study every time for the minimisation of the Hawthorne effect.

Domains of estimation A sample design to provide district level estimates was desirable keeping in view the decentralisation programme of the His Majesty's Government of Nepal. However, as the sample size needed for this would be very large and the survey undertaking also huge as well as expensive, it was decided that the size of the survey should provide national as well as some sub-regional estimates. Under the guidance of the Steering Committee as well as the discussion between the CBS personnel and UNICEF led to the conclusion that a minimum of 13 estimates is needed for different geographic areas and these are 1. Five eco-development regions each from the Terai and Hills; 2. Estimates for the Kathmandu Valley; and finally 3. Two estimates for the mountain region, for which the Central, Eastern and Western Mountain regions would be combined as one and the other would be the combination of the Mid-western and Far-western Mountain regions.

Although there are some variations within these mountain regions, regions having comparable characteristics would be combined as one. Since the number of households was the basis of the selection of our sample, we used average size of the household as an indicator to provide the similarity between these combined areas. For example, the average household size was 5.5 in both the Far-western and Mid-western Mountains. Likewise, the average household size for the Eastern, Central and Western Mountains is, respectively, 5.3, 5.0 and 4.8. That is, the average household size was slightly higher in the Far-western and the Mid-western regions and was slightly lower in the others including the Eastern, Central and Western Mountains. In other words, the areas that were combined were quite close in terms of average household size.

Stratification In domains with urban areas, the stratification was done according to urban/rural residence. Although the urban/rural estimates for these domains would be of interest, it would have increased the sample size considerably. Thus, at this stage, there were no plans to obtain urban/rural estimates for these 13 domains of estimation. Note, however, that the urban/ rural estimates could be available for the national level, as well as for the Hills and Terai. Because the sample was selected separately for each domain, there was a built-in stratification for the Hills, Terai and Mountains as well as the development regions for most of the domains of study.

Estimation of sample size Estimates of the sample size, to a large extent, depend on the variable under study. As some variables have a larger variation, sample size estimates depend on the variables. To circumvent this problem, statisticians usually resort to estimating the sample size for variables where the largest sample size is needed and use this as the required minimum sample size. Also, because most of the sample survey use the cluster sample approach, it was necessary to make an allowance of about 2 for the design effect. The magic figure of 2 was based on the design effect calculated for different variables in the Nepal Family Health Survey 1996. It was estimated that a sample size of 800 was adequate for most of the variables, taking into account a design effect factor of 2. This sample size of 800 was regarded as the minimum sample size required for the domain of analysis. Since there are 13 domains, a total of 13x800 = 10400 households were required.

Sample frame The sample frame for this study was the data from the 1991 Census data on Households for VDCs and their wards. When the census was undertaken in 1991 there were only 31 urban areas in Nepal. However, after 1991 Census, the government declared new municipalities. As a result, there are currently 58 municipalities, of which one is a metropolitan city and three are sub-metropolitan cities. The census data was updated to take into account the change in urban areas.

Allocation of the sample In domains that have urban areas, the urban sample was be allocated proportionately. Urban and rural samples were selected separately using a PPS (Probability Proportional to Size) method. Examples for this are provided in Table A1, page 161 of the Report on the Situation of Women, Children and Households, Between Census Household Information, Monitoring and Evaluation system (BCHIMES), March-May 2000.

The total number of clusters surveyed was 208 with an average cluster size of 50, providing a sample size of nearly 10,400. Likewise, the number of urban clusters will be 27 and the number of rural clusters will be 181. The proportion of urban clusters was 13 percent (See Table A1, Appendix 1 of the Report on the Situation of Women, Children and Households).

Selection procedure used For any given domain, the districts were arranged according to the code for districts provided by the Central Bureau of Statistics. If the code of a district is lowest, it appears first in the list. Within the district, VDCs are listed in an alphabetical order. For each VDC, there will be nine wards, for which there is data regarding number of households, total population, males and females.

Initially, the number of households in a domain was cumulated. The total number of households in a domain is divided by the number of clusters selected in the domain. This provided the systematic interval. Then, a random number between 1 and the systematic interval was selected for the first selection. Once the first selection was made, the systematic interval was added to that for the second selection and so on, until the last selection for the domain was made. If a domain consisted of urban and rural areas, then the selection was made separately for the urban and rural areas. Obviously, a proportionate allocation of sample was done for urban as well as rural areas within a domain. Note that a cluster size of 50 was used for the purpose of data collection. In fact, a number of wards will have a population well over 50, and in some cases a ward could have a population substantially less than 50. In some cases, some wards may have to be split and other wards merged to provide a cluster size of around 50.

Distribution of the samples A total of 208 clusters (10,295 households), with 181 rural clusters (87%) and 27 urban clusters (13%s) were selected from 69 districts for the survey. The average cluster size was 50 households per cluster. Since the sample was stratified by region, it is not self-weighting; hence, sample weights were used for reporting national-level results.

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaires were administered to households, currently married women aged 15-49 years, children aged 6-15 years, and children under 5 years of age in each selected household. The questionnaires were based on the Multiple Indicator Cluster Survey (MICS) model questionnaire. The English version of the questionnaires was

Abstract

The Nepal Multiple Indicator Cluster Survey (MICS) was carried out in 2014 by the Central Bureau of Statistics (CBS) as part of the global MICS programme. Technical and financial support was provided by the United Nations Children’s Fund (UNICEF). The global MICS programme was developed by UNICEF in the 1990s as an international household survey programme to support countries in the collection of internationally comparable data on a wide range of indicators on the situation of children and women. MICS surveys measure key indicators that allow countries to generate data for use in policies and programmes, and to monitor progress towards the Millennium Development Goals (MDGs) and other internationally agreed upon commitments.

The Nepal Multiple Indicator Cluster Survey (MICS 2014) was conducted by the Central Bureau of Statistics under the National Planning Commission from January to June 2014. Technical and financial support for the survey was provided by the United Nations Children’s Fund (UNICEF) Nepal.

Nepal MICS 2014 provides valuable information and the latest evidence on the situation of children and women in Nepal before the country was hit by an earthquake of 7.8 magnitude on 25 April 2015. The survey presents data from an equity perspective by indicating disparities by sex, region, area, education, household wealth, and other characteristics. Nepal MICS 2014 is based on a sample of 12,405 households interviewed and provides a comprehensive picture of children and women in the 15 sub-regions of the country.

Geographic coverage

National coverage

Analysis unit

• Individuals
• Households

Universe

The survey covered all de jure household members (usual residents) the household, and the dwelling, all women aged 15-49 years resident in the household, all children aged 0-4 years (under age 5) resident in the household, and water quality testing questionnaire to test for bacteria and measure E. coli content in household drinking water and water source in a subsample of the households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The primary objective of the sample design for the Nepal MICS 2014 was to produce statistically reliable estimates of most indicators, at the national level, for urban and rural areas, and for the 15 ecological zones of the country: Eastern Mountains, Eastern Hills, Eastern Terai, Central Mountains, Central Hills, Central Terai, Western Mountains, Western Hills, Western Terai, Mid-Western Mountains, Mid-Western Hills, Mid-Western Terai, Far Western Mountains, Far Western Hills, Far Western Terai. Urban and rural areas in each of the 15 ecological zones were defined as the sampling strata. The Central Hills zone is further divided into two substrata as Kathmandu Valley and Other urban areas.

A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample.

Water quality testing was carried out in each of the 519 clusters sampled for this survey. Three households were selected from the list of 25 households interviewed in each cluster using a random systematic selection procedure. This yielded a total of 1,557 households for E. coli testing in drinking water. For one of the three households in each cluster, a sample was also taken from the household's source of drinking water, yielding 519 samples. Samples of household drinking water were taken from a glass of water that would be given to a child to drink, and each sample of source water was collected in a sterile Whirl-Pak bag.

The sample size for the Nepal MICS 2014 was calculated as 13,000 households. For the calculation of the sample size, the key indicator used was the birth registration prevalence among children aged 0-4 years.

For the calculation, r (birth registration) was assumed to be 42.3 percent. The value of deff (design effect) was taken as 2 based on estimates from previous surveys, pb (percentage of children aged 0-4 years in the total population) was taken as 9.7 percent, AveSize (average household size) was taken as 4.88 persons per household, and the response rate was assumed to be 95 percent, based on experience from previous surveys.

Calculations of the required sample sizes indicated that 800 households per domain would be adequate to yield estimates with sufficient precision for most of the indicators, but in the case of three large domains (Eastern Terai, Central Terai, and Western Hills) the decision was made to increase the sample size to 1,000 households. One domain (Western Mountains) posed a particular problem because of its small size. The natural inclination would be to combine it with Mid-Western Mountains, but that was considered undesirable, because of the need to have a separate estimate for this latter domain (which is also known as Karnali). The decision was therefore made to keep Western Mountains as a separate domain. Only 400 households were allocated to it on the clear understanding that the resulting estimates were bound to have lower precision than corresponding estimates for other domains. The overall total sample size was 13,000 households.

The number of households selected per cluster for the Nepal MICS 2014 was determined as 25 households, based on a number of considerations, including the design effect, the budget available, and the time that would be needed per team to complete one cluster. Dividing the total number of households by the number of sample households per cluster, it was calculated that 40, 32 or 16 sample clusters would need to be selected in each zone.

The sampling procedures are more fully described in "Multiple Indicator Cluster Survey 2014 - Final Report" pp.233-237.

Mode of data collection

Face-to-face [f2f]

Research instrument

Four sets of questionnaires were used in the survey: (1) a household questionnaire which was used to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a questionnaire for individual women administered in each household to all women aged 15–49 years; (3) an under-5 questionnaire, administered to mothers (or caretakers) for all children under five years of age living in the household; and (4) a water quality testing questionnaire to test for bacteria and measure E. coli content in household drinking water and water source in a subsample of the households.

The Household Questionnaire included the following modules: List of Household Members, Education, Child Labour, Child Discipline, Household Characteristics, Water and Sanitation, Handwashing, Salt Iodization.

The Questionnaire for Individual Women was administered to all women aged 15–49 years living in the households, and included the following modules: Woman’s Background, Access to Mass Media and Use of Information/Communication Technology, Fertility/Birth History, Desire for Last Birth, Maternal and Newborn Health, Postnatal Health Checks, Illness Symptoms, Contraception, Unmet Need, Attitudes Toward Domestic Violence, Marriage/Union, HIV/AIDS, Tobacco and Alcohol Use, Life Satisfaction.

The Questionnaire for Children Under Five was administered to mothers (or caretakers) of children under five years of age1 living in the households. Normally, the questionnaire was administered to mothers of under-5s; in cases when the mother was not listed in the household roster, a primary caretaker for the child was identified and interviewed. The questionnaire included the following modules: Age, Birth Registration, Early Childhood Development, Breastfeeding and Dietary Intake, Immunization, Care of Illness, Anthropometry.

The Questionnaire for Water Quality Testing was administered to a sub-sample of selected households for measuring E. coli content in the household drinking water and included only one module: Water Quality

The questionnaires are based on the MICS5 model questionnaire. From the MICS5 model English version, the questionnaires were customized and translated into Nepali, Maithili and Bhojpuri. Pre-test training was conducted in Dhulikhel, Kavre District, from 25 October to 2 November 2013. Pre-test fieldwork was conducted in 25 households of both urban and rural locations in Sindhupalchowk District (Mountains), Tanahun District (Hills) and Dhanusa District (Terai) during November 2013. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires. A copy of the Nepal MICS questionnaires is provided in Appendix F.

In addition to the administration of questionnaires, fieldwork teams tested the salt used for cooking in the households for iodine content, observed the place for handwashing, and measured the weights and heights of children under five. Details and findings of these observations and measurements are provided in the respective sections of the report.

In each cluster, water from three households and one source of drinking water were tested for E. coli. Testing was conducted by the team measurer. As a routine quality control measure, the supervisor regularly observed the measurer in the testing of blanks. In addition, professional laboratory technicians from an external agency were engaged for the purpose. They visited field teams during the survey and observed the measurers during testing, giving corrective support as needed.

Cleaning operations

Data were entered using CSPro software, Version 5.0. Data were entered on 10 laptop computers by 10 data-entry operators, one questionnaire administrator, overseen by one data-entry supervisor with two secondary editors. For quality assurance purposes, all questionnaires were double-entered and internal consistency checks were

Abstract

In Nepal, the industrialization process is stagnant; the contribution of Manufacturing Sector to the national economy is minor and most of the factories are of small scales. The fifth decennial survey of small manufacturing establishments (SSME) 2008-2009 is one of the primary source of industrial statistics which covers all functioned manufacturing activities of the nation with a formal registration that engage less than 10 persons. The sampling survey undertaken by the Central Bureau of Statistics in establishment approach has provided complementary information of the Census of Manufacturing Establishments (CME) which is summarized in a set of 101 tables. This information is based on the responses of 614 questions interviewed by permanent staffs in 3737 randomly selected sample establishments. The survey report has quantified the size, composition, and distribution of the small manufacturing sector including ten principal indicators by internationally comparable and standard industrial classification at Development Region level.

There were 32326 small manufacturing establishments found active during mid July 2008 to mid-July 2009, the reference period of the survey when the listing operation had conducted in all districts. In this period, they had altogether contributed Rs. 11.5 Arab value added in the national economy and generated employment for 122 thousand persons. Moreover, there were 75 types of industries which produced 154 items using 186 types of raw materials in the reference period.

The survey has disclosed that grain milling, wearing apparel sewing, furniture making, and jewellery designing are the top four small manufacturing activities in Nepal. Share of which are nearly 39, 17, 10, and 7 percent of total in number; and they contribute about 20, 14, 14 and 7 percent of total value added in the small manufacturing sector.

Geographically, the Central Development Region has the largest number of small factories. It belongs to 45 percent establishments and contributes 50 percent value added to the small manufacturing sector in Nepal which follows by Eastern Development Region with 27 percent establishments and 24 percent value added.

Finally, the survey has told about the capacity utilization status and problem faced by the small industries. Only 32 percent of the industries utilized 60 percent or more than their installed capacity during the reference period and their major problem is the lack of electricity followed by capital dearth in national level. The ratio of capital utilization and problem faced by those establishments are found vary from industrial activity to activity and region to region.

Geographic coverage

National 5 Development Regions Urban-Rural

Analysis unit

The basic unit of analysis of the survey is the establishment. The survey describes the characteristic of a small scale manufacturing establishment. Among these features, there may be some differences in characteristics from one NSIC to another and from one Development Region to another.

Universe

The survey covered all active manufacturing establishments in Nepal that engage less than 10 persons and have a legal registration.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design of SSME 2008-2009 comprised of complete as well as sample enumeration. Actually, there were three modes of selecting samples and the probability of selection of a sample is unequal. The sampling frame for the design was obtained by conducting one year listing operation throughout the country. In that operation, there were 32326 small industries found active. Out of them, 3737 had been selected for the survey.

At first, the sampling frame was sorted and split by NSIC and development regions. Then, a cut-off point (<5 establishments) was determined and in turn, all establishments under a NSIC with frequency less than 5 in a development region are selected. The total number of such establishments was 152. In fact, they were chosen for complete enumeration. This was done to achieve more reliable and better representative sampling distribution. The probability of selection of these establishments was considered one.

Secondly, the remaining establishments of the sampling frame had been further divided into two groups. The first group contained all establishments within NSIC 1531, 1810, 2811, 3610 and 3691; and the next group belonged to remaining NSICs. The first group again classified into 3 strata by number of persons engaged. There were altogether 24837 establishments within this group. Out of them, 2485 simple random samples were selected with probability 0.10 proportional among the strata.

Thirdly, the next group had 7337 establishments. It was also divided into 3 strata by number of persons engaged. Among them, 1100 simple random samples had been selected with probability 0.15 proportionally.

Finally, about 12 percent of total industries were selected. Out of total about 45 percent belong to Central Development region. Eastern and Western Development Region contains nearly 27 percent and 16 percent samples respectively.

Mode of data collection

Face-to-face [f2f]

Research instrument

In CBS, it is a general procedure to consult with a Technical Committee composed of subject matter specialists, prominent users and data processing experts in order to give original shape to the questionnaire and tabulation plan before the survey or census starts. In place of such committee, during the questionnaire design stage of the SSME 2008-2009, a consultative committee was composed under the chairmanship of the Deputy Director General of Economic Statistics Division of CBS. This committee consisted of all six directors of each section under the division. At first, they discussed on the purposed first draft of the questionnaire prepared by the Section. Later many additional improvements were incorporated, in particular, related to the format, sequential flow or logical arrangement of data items in accordance with the recommendation provided by the committee.

In fact, the questionnaire for the SSME 2008-2009 was a kind of structured questionnaire especially based on the CME 2006-2007 questionnaire with some modifications and additions. An establishment questionnaire was administered to each establishment which collected various information on employment, input-output and capital formation including legal status, major activity, capacity utilization, indirect taxes paid and problem faced by the establishment.

It contains 15 sections as stated below:

1. Employment
2. Purchase of Fuels
3. Purchase of Raw Materials
4. Production and Sale
5. Service Industries Only
6. Cost of and Receipt from Industrial and Other Services
7. Stocks
8. Indirect Tax and Fees
9. Loan Transaction
10. Cost of Non-industrial Services
11. Receipts from Non-industrial Services
12. Utilization of Production Capacity
13. Fixed Assets
14. Environment
15. Major problems faced by the establishments during the reference period

Aside from these 15 sections, there was an introduction part at the first page of the questionnaire. It was a large questionnaire. There were altogether 614 questions to be filled or answered.

The questionnaire was first developed in Nepali language and translated into English version for report writing purpose. The translation was undertaken by Mr.Lok Bahadur Khatri, the Statistics Officer of ECSS of CBS. The translation was then reviewed finally by Mrs Ganga Dabadi, the Director of the section. The Nepali questionnaire was tested in some establishments at Kathmandu Valley.

Cleaning operations

For quality control and to make successive steps easier the usual practice was to have manual editing in the field of some key items which generally cannot be corrected in the center. Such edit instructions were mainly of the following types:

i. To check if all cells are properly filled in according to the instruction manual; ii. To ensure whether all entries are consistent with one another; iii. To check if all skipping instructions have been correctly followed; iv. To work out some ratios or rates and see if they are reasonable.

For examples of such calculations are: a. Percentage of output quantity on principal raw material consumed, and b. Average wage per employees etc.

In spite of these strict and clear cut rules, many forms would be found with blank cells and incorrect entries. There was always a heavy load at the time of detailed editing. As far as possible, correction works including imputations were done by developing suitable procedures. But, sometimes, there was no way out except to return to the field for the correct information. It is still a general tendency of respondents to report more expenditures and less outputs or receipts. In most cases, the value added figures turn out to be very low or sometimes negative. This situation had created a lot of headache at the processing stage. Since it was not possible to go back to the field for a majority of the forms, the only meaningful alternative was to correct the wrong reporting by adopting some plausible assumptions.

After editing process, the next step was to perform coding work. In order to avoid clerical errors, a complete recheck process or, in some cases, on sampling basis was the general practice to correct previous mistakes as far as possible. As in the previous CME and SSME, in SSME 2008-2009, the coding scheme of NSIC and CPC 1.0 was used to made data comparable nationally and internationally.

Moreover, there were many inconsistencies found especially in the following area of the filled questionnaire:

• Monthly wage and salary of a paid employee
• Per

Abstract

The Demographic Sample Survey 1986/87, shortly called as DSS 1986/87 is carried out by the Central Bureau of Statistics (CBS) with financial support from UNFPA and technical assistance from UNDTCD.

The major objectives of the DSS are to provide intercensal estimates of some important demographic parameters such as birth, death, migration, etc. The DSS 1986/87 not only provides these parameters but also examines the factors affecting fertility, mortality and migration in more details.

Geographic coverage

National Urban/ Rural areas Ecological Zones: Mountain, Hill, Terai

Analysis unit

Individual, Household

Universe

All private households

Kind of data

Sample survey data [ssd]

Sampling procedure

The DSS 1986/87 is a longitudinal study based on multi-stage national probability sample of 129 identifiable compact clusters known as ward/subwards. Ward/subwards (81 rural and 48 urban) were drawn from 35 districts (14 from Terai Zone and 18 and 3 from the Hill and Mountain zones respectively), out of a total of 75 districts in the country. The emphasis that the ultimate sampling units of DSS 1986/87 should be easily identifiable compact clusters is to ensure that the survey could be smoothly carried out in several successive rounds. The DSS 1986/87 drew samples from rural and urban areas separately in order to provide estimates of demographic and non-demographic parameters independently for each of the area.

Altogether 8640 households were eventually selected in the DSS 1986/87 for baseline and prospective study. The rural sample consisits of 6126 households while the urban sample accounts for 2514 households. The households selected in the Mountain, Hill and Terai are 675, 4179 and 3786 respectively. The urban households in the Hill and Terai are 1200 and 1314 respectively. In the Mountain there is no urban area. The sample consists of 35101 rural and 14412 urban population.

Refer to page 2 of "DSS Report" for a detailed description of the Sample Design.

Mode of data collection

Face-to-face [f2f]

Research instrument

The data at baseline survey were collected by using six different schedules:

1. Household schedule The household schedule was employed to collect information on some conventional socio-demographic measures of each usual/permanent member of the selected households.

2. In-migration schedule The In-migration schedule was used to collect detailed information on internal migrants and for immigrants.

3. Fertility and Mortality schedule The Fertility and Mortality schedule was used to collect the information on fertility anf mortality history of ever married worman in the household.

4. Out-migration schedule The Out-migration schedule was used to obtain detailed information on each out-migrant from the household which took place in the last five years preceding the survey.

5. Socio-economic status of the household schedule The Socio-economic status of the household schedule was used to obtain socio-economic characteristics of the households.

6. Migration survey-individual questionnaire The Migration survey-individual questionnaire was administered to internal migrants.

Refer to page 5 of "DSS Report" for detailed information on the types and contents of the questionnaires.

Abstract

The principal objective of the 2006 Nepal Demographic and Health Survey (NDHS) is to provide current and reliable data on fertility and family planning behavior, child mortality, adult and maternal mortality, children’s nutritional status, the utilization of maternal and child health services, and knowledge of HIV/AIDS. For the first time, the 2006 NDHS conducted anemia testing at the household level for the country as a whole to provide information on the prevalence of anemia at the population level. The specific objectives of the survey are to:

• collect data at the national level which will allow the calculation of key demographic rates;
• analyze the direct and indirect factors which determine the level and trends of fertility;
• measure the level of contraceptive knowledge and practice among women and men by method, urban-rural residence and region,
• collect high-quality data on family health including immunization coverage among children, prevalence and treatment of diarrhea and other diseases among children under five, and maternity care indicators including antenatal visits, assistance at delivery, and postnatal care;
• collect data on infant and child mortality, and maternal and adult mortality;
• obtain data on child feeding practices including breastfeeding, and collect anthropometric measures to use in assessing the nutritional status of women and children;
• collect data on knowledge and attitudes of women and men about sexually transmitted infections and HIV/AIDS and evaluate patterns of recent behavior regarding condom use;
• conduct hemoglobin testing on women age 15-49 and children age 6-59 months in the households selected for the survey to provide information on the prevalence of anemia among women in the reproductive ages and young children.

This information is essential for informed policy decisions, planning, monitoring, and evaluation of programs on health in general and reproductive health in particular at both the national and regional levels. A long-term objective of the survey is to strengthen the technical capacity of government organizations to plan, conduct, process, and analyze data from complex national population and health surveys. Moreover, the 2006 NDHS provides national, regional and subregional estimates on population and health that are comparable to data collected in similar surveys in other developing countries. The first Demographic and Health Survey (DHS) in Nepal was the 1996 Nepal Family Health Survey (NFHS) conducted as part of the worldwide DHS program, and was followed five years later by the 2001 Nepal Demographic and Health Survey (NDHS). Data from the 2006 NDHS survey, the third such survey, allow for comparison of information gathered over a longer period of time and add to the vast and growing international database on demographic and health variables.

Wherever possible, the 2006 NDHS data are compared with data from the two earlier DHS surveys—the 2001 NDHS and the 1996 NFHS—which also sampled women age 15-49. Additionally, men age 15-59 were interviewed in the 2001 NDHS and the 2006 NDHS to provide comparable data for men over the last five years.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men age 15-59

Kind of data

Sample survey data

Sampling procedure

The primary focus of the 2006 NDHS was to provide estimates of key population and health indicators, including fertility and mortality rates, for the country as a whole and for urban and rural areas separately. In addition, the sample was designed to provide estimates of most key indicators for the 13 domains obtained by cross-classifying the three ecological zones (mountain, hill and terai) with the five development regions (East, Central, West, Mid-west, and Far-west).

The 2006 NDHS used the sampling frame provided by the list of census enumeration areas with population and household information from the 2001 Population Census. Each of the 75 districts in Nepal is subdivided into Village Development Committees (VDCs), and each VDC into wards. The primary sampling unit (PSU) for the 2006 NDHS is a ward, subward, or group of wards in rural areas, and subwards in urban areas. In rural areas, the ward is small enough in size for a complete household listing, but in urban areas the ward is large. It was therefore necessary to subdivide each urban ward into subwards. Information on the subdivision of the urban wards was obtained from the updated Living Standards Measurement Survey. The sampling frame is representative of 96 percent of the noninstitutional population.

The sample for the survey is based on a two-stage, stratified, nationally representative sample of households. At the first stage of sampling, 260 PSUs (82 in urban areas and 178 in rural areas) were selected using systematic sampling with probability proportional to size. A complete household listing operation was then carried out in all the selected PSUs to provide a sampling frame for the second stage selection of households. At the second stage of sampling, systematic samples of about 30 households per PSU on average in urban areas and about 36 households per PSU on average in rural areas were selected in all the regions, in order to provide statistically reliable estimates of key demographic and health variables. However, since Nepal is predominantly rural, in order to obtain statistically reliable estimates for urban areas, it was necessary to oversample the urban areas. As such, the total sample is weighted and a final weighting procedure was applied to provide estimates for the different domains, and for the urban and rural areas of the country as a whole.

The survey was designed to obtain completed interviews of 8,600 women age 15-49. In addition, males age 15-59 in every second household were interviewed. To take nonresponse into account, a total of 9,036 households nationwide were selected.

Mode of data collection

Face-to-face

Research instrument

Three questionnaires were administered for the 2006 NDHS: the Household Questionnaire, the Women’s Questionnaire, and the Men’s Questionnaire. These questionnaires were adapted to reflect the population and health issues relevant to Nepal at a series of meetings with various stakeholders from government ministries and agencies, NGOs and international donors. The final draft of the questionnaires was discussed at a questionnaire design workshop organized by MOHP in September 2005 in Kathmandu. The survey questionnaires were then translated into the three main local languages—Nepali, Bhojpuri and Maithili and pretested from November 16 to December 13, 2005.

The Household Questionnaire was used to list all the usual members and visitors in the selected households and to identify women and men who were eligible for the individual interview. Some basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. For children under age 18, the survival status of the parents was determined. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor of the house, ownership of various durable goods, and ownership of mosquito nets. Additionally, the Household Questionnaire was used to record height, weight, and hemoglobin measurements of women age 15-49 and children age 6-59 months. The Women’s Questionnaire was used to collect information from all women age 15-49.

These women were asked questions on the following topics: - respondent’s characteristics such as education, residential history, media exposure, - pregnancy history, childhood mortality, - knowledge and use of family planning methods, - fertility preferences, - antenatal, delivery, and postnatal care, - breastfeeding and infant feeding practices, - immunization and childhood illnesses, - marriage and sexual activity, - woman’s work and husband’s background characteristics, - awareness and behavior regarding AIDS and other sexually transmitted infections (STIs), and - maternal mortality.

The Men’s Questionnaire was administered to all men age 15-59 living in every second household in the 2006 NDHS sample. The Men’s Questionnaire collected much of the same information found in the Women’s Questionnaire, but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health or nutrition.

In addition, the Verbal Autopsy Module into the causes of under-five mortality was administered to all women age 15-49 (and anyone else who remembered the circumstances surrounding the reported death) who reported a death or stillbirth in the five years preceding the survey to children under five years of age.

Response rate

A total of 9,036 households were selected, of which 8,742 were found to be occupied during data collection. Of these existing households, 8,707 were successfully interviewed, giving a household response rate of nearly 100 percent.

In the selected households, 10,973 women were identified as eligible for the individual interview. Interviews were completed for 10,793 women, yielding a response rate of 98 percent. Of the 4,582 eligible men identified in the selected subsample of households, 4,397 were successfully interviewed, giving a 96 percent response rate. Response rates were higher in rural than urban areas, especially for eligible men.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2)

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

Nepal Multiple indicator Cluster Survey (NMICS) was conducted in 2019 by Central Bureau of Statistics (CBS) with the primary objective of filling the data gap on children, women and men of Nepal. The NMICS 2019 was implemented as part of the sixth round of the global MICS household survey programme with technical and financial support of UNICEF, Nepal. NMICS 2019 has generated a wealth of information on children and women which is of immense importance to monitor and evaluate plan and programmes related to children and women of Nepal. These data will help to monitor towards goals and targets of international agreements such as Sustainable Development Goal. The NMICS 2019 covers topics related to child health, water and sanitation, reproductive health, child development, education and literacy, child protection, HIV and AIDS, mass media and use of information and communication technology, attitude towards domestic violence, tobacoo and alchohol use and life satisfaction. The 2019 Nepal MICS has as its primary objectives:

· To provide up-to-date information for assessing the situation of children, women and men in Nepal; · To generate data for the critical assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention; · To furnish data needed for monitoring progress toward goals established in the Sustainable Development and other internationally agreed upon goals, as a basis for future action; · To collect disaggregated data for the identification of disparities, to allow for evidence-based policy-making aimed at social inclusion of the most vulnerable; · To contribute to the generation of baseline data for the post-2015 agenda; · To validate data from other sources and the results of focused interventions.

Geographic coverage

National, urban and rural, province

Analysis unit

Household, Women aged 15-49 years, Men aged 15-49 years, Children Under 5, Children Aged 5-17

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49 years resident in the household, men aged 15-49 years resident in the alternative household, children aged 5-17 resident in the household, and all children aged 0-4 years (under age 5) resident in the household, Ecoli and arsenic test of resouce water & drinking water

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the Nepal MICS was designed to provide estimates for a large number of indicators on the situation of children, women and men at the national level, for urban and rural areas, and for the province.

The urban and rural areas within each region were identified as the main sampling strata and the sample was selected in two stages. Within each stratum, a specified number of census enumeration areas (i.e 512) were selected from each of the sampling strata by using systematic probability proportional to size (pps) sampling procedures, based on the number of households in each enumeratiion area from the 2011 Census frame.

The first stage of sampling was subsequently completed by selecting the required number of sample EAs specified from each of the seven provinces, separately for the urban and rural strata including Kathmandu valley urban. The households were then sequentially numbered from 1 to Mhi (the total number of households in each enumeration area) at the CBS, where the selection of 25 households in each enumeration area was carried out using random systematic selection procedures. The MICS6 spreadsheet template for systematic random selection of households was adapted for this purpose.

The survey also included a questionnaire for individual men that wasto be administered in half of the sampled households. The MICS household selection template includes an option to specify the proportion of households to be selected for administering the individual questionnaire for men, and the spreadsheet automatically selected the corresponding subsample of households.All men age 15 to 49 years in the selected households were eligible for interview.

The households listed in each sample cluster were divided into two strata for the second stage selection: households with and without children under 5. A separate sample of households was selected from each group, using a higher sampling rate for households with children under 5. This sampling strategy increased the number of children under 5 in the sample to increase the precision of the indicators based on under-5 children. Of the 25 households selected in each cluster, the target number of sample households with children under age 5 years was 13. Therefore, in sample clusters where more than 13 households with children under age 5 were listed, 13 of these households were selected using random systematic sampling; and 12 households without children under age 5 were selected from the other stratum. In sample clusters where 13 or less households with children under 5 were listed, all of these households were selected for the survey. In these clusters, the number of households without children under 5 to be selected was equal to 25 minus the number of households with children.

The Nepal MICS also included water quality testing for both E. coli and Arsenic for a subsample of households within each sample cluster. A subsample of 5 of the 25 selected households was selected in each sample cluster using random systematic sampling for conducting water quality testing, for both water in the household and at the source for E. coli, and only at the source for Arsenic. The MICS household selection template includes an option to specify the number of households to be selected for the water quality testing, and the spreadsheet automatically selected the corresponding subsample of households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Six sets of questionnaires were used in the survey: 1. HH Questionnaire: a household questionnaire which was used to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling 2. Children Age 5-17 Questionnaire: an questionnaire was administered to mothers (or caretakers) for all children 5-17 years of age living in the household 3. Children Under 5 Questionnaire: an under-fives questionnaire, administered to mothers (or caretakers)for all children under five years of age living in the household 4. Individual Women Questionnaire: a questionnaire for individual women administered in each household to all women aged 15-49 years 5. Individual Men Questionnaire: a questionnaire for individual men administered in alternative household to all men aged 15-49 years 6. Water Quality Testing Questionnaire: a water quality testing questionnaire to test for bacteria and measure E. coli and arsenic content in household drinking water and source in a sub-sample of the households.

The quesitonnaires developed in English ' MICS6 Model Questionnaires' were modified somehow to Nepalese context where needed and were translated into Nepali version. After an initial review the questionnaires were translated back into English by an independent translator with no prior knowledge of the survey. The back translation version was independently reviewed and compared to the English original. Differences in translation were reviewed and resolved in collaboration with the original translators. The English and Nepali questionnaires were both piloted as part of the survey pretest.

The Household Questionnaire included the following modules:

• Household listing
• household characteristics
• education
• social transfer
• household energy use
• drinking water and sanitation
• handwashing facility

The Individual Women Questionnaire included the following modules:

• Woman's background
• access to mass media and use of information and/communication technology
• marriage/union
• fertility/birth history
• desire for last birth
• post-natal health checks
• maternal and newborn health
• illness symptoms
• contraception
• unmet need
• attitudes towards domestic violence
• human trafficking
• adult functioning
• HIV/AIDS knowledge
• tobacco and alcoholic use
• life satisfaction

The Individual Men Questionnaire included the following modules:

• Man's background
• access to mass media and use of information and/communication technology
• marriage/union
• fertility
• attitudes towards domestic violence
• human trafficking
• adult functioning
• HIV/AIDS knowledge
• tobacco and alcoholic use
• life satisfaction.

The Children Under Five Questionnaire included the following modules:

• Under-Five Child Information
• Under-Five Children's background
• Birth registration
• Early Childhood Development
• Child Discipline
• Child Functioning
• Breastfeeding and Dietary intake
• Immunisation
• Care of illness and immunization
• Anthropometry

The Children age 5-17 included the following modules:

• Child Information
• Child's Background
• Child Discipline
• Child Functioning
• Parental involvement
• Foundational Learning Skills

The water quality test questionnaire included the following modules:

• Water quality testing- arsenic testing
• E-coli

Cleaning operations

Data were received at the Central Bureau of Statistics’ central office via Internet File Streaming System (IFSS) integrated into the management application on the supervisors’ tablets. Whenever logistically possible, synchronisation was daily. The central office communicated application updates to field teams through this system. During data collection and following the completion of fieldwork, data were edited according to editing process described in detail

Nepal NP: SPI: Pillar 2 Data Services Score: Scale 0-100 data was reported at 63.400 NA in 2023. This stayed constant from the previous number of 63.400 NA for 2022. Nepal NP: SPI: Pillar 2 Data Services Score: Scale 0-100 data is updated yearly, averaging 62.017 NA from Jul 2016 (Median) to 2023, with 8 observations. The data reached an all-time high of 63.400 NA in 2023 and a record low of 42.767 NA in 2016. Nepal NP: SPI: Pillar 2 Data Services Score: Scale 0-100 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nepal – Table NP.World Bank.WDI: Governance: Policy and Institutions. The data services pillar overall score is a composite indicator based on four dimensions of data services: (i) the quality of data releases, (ii) the richness and openness of online access, (iii) the effectiveness of advisory and analytical services related to statistics, and (iv) the availability and use of data access services such as secure microdata access. Advisory and analytical services might incorporate elements related to data stewardship services including input to national data strategies, advice on data ethics and calling out misuse of data in accordance with the Fundamental Principles of Official Statistics.;Statistical Performance Indicators, The World Bank (https://datacatalog.worldbank.org/dataset/statistical-performance-indicators);Weighted average;

Abstract

The primary objective of the 2016 Nepal Demographic and Health Survey (NDHS) is to provide up-to-date estimates of basic demographic and health indicators. The NDHS provides a comprehensive overview of population, maternal, and child health issues in Nepal. Specifically, the 2016 NDHS: - Collected data that allowed calculation of key demographic indicators, particularly fertility and under-5 mortality rates, at the national level, for urban and rural areas, and for the country’s seven provinces - Collected data that allowed for calculation of adult and maternal mortality rates at the national level - Explored the direct and indirect factors that determine levels and trends of fertility and child mortality - Measured levels of contraceptive knowledge and practice - Collected data on key aspects of family health, including immunization coverage among children, prevalence and treatment of diarrhea and other diseases among children under age 5, maternity care indicators such as antenatal visits and assistance at delivery, and newborn care - Obtained data on child feeding practices, including breastfeeding - Collected anthropometric measures to assess the nutritional status of children under age 5 and women and men age 15-49 - Conducted hemoglobin testing on eligible children age 6-59 months and women age 15-49 to provide information on the prevalence of anemia in these groups - Collected data on knowledge and attitudes of women and men about sexually transmitted diseases and HIV/AIDS and evaluated potential exposure to the risk of HIV infection by exploring high-risk behaviors and condom use - Measured blood pressure among women and men age 15 and above - Obtained data on women’s experience of emotional, physical, and sexual violence

The information collected through the 2016 NDHS is intended to assist policymakers and program managers in the Ministry of Health and other organizations in designing and evaluating programs and strategies for improving the health of the country’s population. The 2016 NDHS also provides data on indicators relevant to the Nepal Health Sector Strategy (NHSS) 2016-2021 and the Sustainable Development Goals (SDGs).

Geographic coverage

National coverage

Analysis unit

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

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2016 NDHS is an updated version of the frame from the 2011 National Population and Housing Census (NPHC), conducted by the Central Bureau of Statistics (CBS).

The sampling frame contains information about ward location, type of residence (urban or rural), estimated number of residential households, and estimated population. In rural areas, the wards are small in size (average of 104 households) and serve as the primary sampling units (PSUs). In urban areas, the wards are large, with average of 800 households per ward. The CBS has a frame of enumeration areas (EAs) for each ward in the original 58 municipalities. However, for the 159 municipalities declared in 2014 and 2015, each municipality is composed of old wards, which are small in size and can serve as EAs.

The 2016 NDHS sample was stratified and selected in two stages in rural areas and three stages in urban areas. In rural areas, wards were selected as primary sampling units, and households were selected from the sample PSUs. In urban areas, wards were selected as PSUs, one EA was selected from each PSU, and then households were selected from the sample EAs.

For further details on sample design, see Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

Six questionnaires were administered in the 2016 NDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, the Biomarker Questionnaire, the Fieldworker Questionnaire, and the Verbal Autopsy Questionnaire (for neonatal deaths). The first five questionnaires, based on The DHS Program’s standard Demographic and Health Survey (DHS-7) questionnaires, were adapted to reflect the population and health issues relevant to Nepal. The Verbal Autopsy Questionnaire was based on the recent 2014 World Health Organization (WHO) verbal autopsy instruments (WHO 2015a).

Cleaning operations

The processing of the 2016 NDHS data began simultaneously with the fieldwork. As soon as data collection was completed in each cluster, all electronic data files were transferred via the IFSS to the New ERA central office in Kathmandu. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The biomarker paper questionnaires were compared with the electronic data files to check for any inconsistencies in data entry. Data entry and editing were carried out using the CSPro software package. The secondary editing of the data was completed in the second week of February 2017. The final cleaning of the data set was carried out by The DHS Program data processing specialist and was completed by the end of February 2017.

Response rate

A total of 11,473 households were selected for the sample, of which 11,203 were occupied. Of the occupied households, 11,040 were successfully interviewed, yielding a response rate of 99%.

In the interviewed households, 13,089 women age 15-49 were identified for individual interviews; interviews were completed with 12,862 women, yielding a response rate of 98%. In the subsample of households selected for the male survey, 4,235 men age 15-49 were identified and 4,063 were successfully interviewed, yielding a response rate of 96%.

Response rates were lower in urban areas than in rural areas. The difference was slightly more prominent for men than for women, as men in urban areas were often away from their households for work.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Non-sampling errors result from mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding 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 2016 Nepal DHS (NDHS) to minimize 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 2016 NDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2016 NDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in either ISSA or SAS, using programs developed by ICF. These programs use the Taylor linearization method of variance estimation 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.

A more detailed description of estimates of sampling errors are presented in Appendix B of the survey final report.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Age distribution of eligible and interviewed men - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months - Sibling size and sex ratio of siblings - Pregnancy-related mortality trends

See details of the data quality tables in Appendix C of the survey final report.

Abstract

The survey streamlines data collection and monitoring of impact and outcome level results as part of multi-year country strategy. Monitoring progress towards education enrollment and sustainable livelihoods results is vital to inform course correction in the operation’ annual implementation plan and budgeting. The RMS and SEA are to be representative of persons of concern (PoC). This exercise was part of the 2022 RMS pilot.

Geographic coverage

National

Analysis unit

Households and Individuals

Universe

Registered Refugees in Nepal 2022

Kind of data

Sample survey data [ssd]

Sampling procedure

Simple Random Sampling

Mode of data collection

Face-to-face [f2f]

Abstract

Annual Household Survey is a recent endeavor of the CBS conducted with a purpose of providing frequent socio-economic information on household consumption, employment and other socioeconomic aspects of Nepalese households. The survey aims to provide estimates for Nepal, urban and rural area and also by consumption quintiles and deciles. Altogether 3,000 households (1500 from urban and 1500 from rural) were selected from 200 wards/sub wards.

Geographic coverage

National, Urban and Rural sectors.

Analysis unit

The Annual Household survey have the following unit of analysis: income, expenditure, consumption,employment, unemployment,and educational status of individual and households.

Universe

The survey covered all de jure household members (usual residents), all individual aged 5 years and above.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey has followed two stage sampling design with stratifications of the households into urban and rural area. A complete list of wards with number of households provided by National Population Census 2011 was used as a sampling frame for the survey. Altogether, there were 806 wards in urban area and 35,214 wards in rural area of Nepal. In order to avoid extremity of the size of wards, some big wards were segregated into blocks or enumeration areas (EAs). The sampling frame contained 4,861 EAs in urban and 36,181 EAs in rural areas making a total of 41042 EAs in Nepal. The survey aimed to provide estimates for Nepal, urban and rural area, and accordingly, the population was stratified into urban and rural area. Wards or sub wards (EAs) were the primary sampling units (PSUs). The number of PSUs to be selected were 100 from rural and 100 from urban area making a total of 200 PSUs. The sample size was determined on the basis of the sampling variance of previous surveys. PSUs were selected on the basis of probability proportional to the size (PPS), the measure of the size being the number of households in each ward. Selected PSUs were spread over 65 districts. Households were the ultimate sampling units (USUs) selected with equal probability on the basis of systematic random sampling technique. Fifteen (15) households were selected from each PSUs.Altogether 3000 households (1500 from urban and 1500 from rural) were selected for the interview. In a nutshell, procedures followed to select sample households were: -selection of PSUs based on PPS from the frame, - listing of households in the selected PSU, and -selection of SSUs from the updated list of household in the selected PSU.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire mainly contain household information and Individual information. Parts 2, 3 and 4 cover housing, food and non-food consumption expenditure while part 1 and 5 cover individual information. Part 1 contains questions on demographic characteristics, migration, literacy/education, and Part 5 on economic activities.

Cleaning operations

For the data entry,editing, and verification at the field, a simple and clear data entry programme was developed in CSPro software, and each team was given a personal computer having the entry program so that every team could be able to enter the interviewed household data in the respective field area. To maintain uniformity in consistency check and skip pattern check, a 3-day review meeting was organized in Kavre comprising all the team leaders who were responsible for data entry and data editing at the PSU level. During the review meeting, necessary instructions were issued to rectify the errors and inconsistencies found in the field work especially in the computer data entry programme.

At the center, completeness and structural checking was done by using STATA software after gathering all electronic files of the raw data. During this checking, mannual review of questioniare was reviewed mannually and outliers were omitted if necessary.

Abstract

The objectives of the 2001 Population Census were:

a. to develop a set of benchmark data for different purposes, b. to provide data for small administrative areas of the country on population, housing and household facilities, c. to provide reliable frames for different types of sample surveys, d. to provide sex disaggregated data of the population and other variables related to households, demographic, social and economic conditions of the country, and e. to provide detailed information on women, children, the aged and the disabled.

Content of the Census Questionnaire:

Short Form : Schedule 1

Household Information

1. Type of housing unit occupied by the household
2. Tenure of housing unit
3. Whether any land operated for agriculture
4. Area of agricultural land operated
5. Whether any livestock/ poultry raised
6. Number of livestock/ poultry on the holding
7. Whether any female member owned any house/land
   • Area of land owned
8. Whether any female member owned any livestock
   • Number of livestock (big and small head)

Individual Information

1. Serial number of household member
2. Full name of the household member
3. Male/Female
4. Age
5. Caste/Ethnicity
6. Relationship of the household head
7. Religion
8. Language spoken
   • Mother tongue
   • Second language

Long Form : Schedule 2

Household Information

1. Main source of drinking water
2. Main fuel used for cooking
3. Main source of light
4. Toilet facility
5. Household conveniences
6. Whether any death in the household
7. Information on the deceased person(s)
   • Sex, age, date, and cause

Individual Information

1. Serial number of household member
2. Full name and sex of the household member
3. Age
4. Place of birth
5. Duration of stay at the present place
6. Reason for staying in this district
7. Residence five years ago
8. Whether able to read and write
9. Level of education
10. Whether currently attending any school
11. Marital status
12. Age at first marriage
13. No. of children ever born
14. Any live births during last 12 months
15. Work usually done during the last 12 months
16. No. of months worked during the last 12 months
17. Occupation (type of usual work)
18. Industry (place of usual work)
19. Employment Status
20. Reasons for usually not working
21. Living arrangements of children below 16 years

Geographic coverage

National coverage

Analysis unit

individuals and households

Universe

The survey covered all household members (usual residents) in the household.

Kind of data

Census/enumeration data [cen]

Sampling procedure

The 2001 census collected data based on short form for the complete enumeration of the benchmark information and the long form for the sample enumeration of other socio-economic and demographic information. The long form was administered for population dwellings in about 20 percent of the total housing units. Based on these, estimates were generated at the district level with reliable degree of precision.

The sampling scheme of the 2001 Population Census for the long form is summarized below.

1. The sampling covered the private households only. For the institutional population, Schedule-1 only was administered.

2. For the sampling, 75 administrative districts formed the main strata and VDC's and municipalities within the district formed the domains.

3. There were around 36,000 wards in the country at the time of the census. For the purpose of the census enumeration some of the large wards were further divided into sub-wards. These wards and sub-wards formed the EA's for sampling. The total number of EAs thus formed were around 40,000.

4. Sampling was carried out in each EA; housing unit being the sampling unit.

5. The list of housing units and households served as the sampling frame for the EA. The housing units were selected by systematic sampling method. The sampling interval taken was 8.

6. The list of selected housing units was made available to the enumerator for the enumeration. All households and persons found in the selected units were enumerated.

7. The ratio method was used in making estimates for the sample.

8. Tabulation groups were created separately for tabulation of persons and those for households. The main control variables for the majority of tabulations for persons were two variables: age sex. Tabulation groups for household tabulations were formed in a different manner: taking households as a tabulation group in the domain.

9. To implement the ratio estimation, first weights were calculated. The weights for sample data were computed by dividing the 100 percent counts for the same tabulation groups in the domain by sample counts for the same tabulation groups in the domain. To avoid inconsistency due to rounding, the figures were converted to whole numbers.

This detailed sampling procedure is provided in the document 'Sample Design for the 2001 Census of Housing and Population, Nepal'.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two types of schedules were prepared. Form 1 for complete enumeration and Form 2 for sample enumeration. Both schedules contained questions on household as well as individuals.

FORM 1: (COMPLETE Enumeration) A. Household Information (Question relating to Household), House type & ownership, Agriculture land holding, Livestock/poultry raised for agriculture purpose, Female ownership on house, land and Livestock/Cattle, Small scale economic activities other than agriculture, Absentees from Household (HH), reasons & country of destination. B. Individual Information (Question relating to Individuals), Name, sex, age, relationship to the Household head, Caste/ethnicity, religion, Language spoken, citizenship, disability.

FORM 2: (SAMPLE Enumeration) A. Household Information (Question relating to Household), Source of drinking water, Type of cooking/ lighting fuel, Type of Toilet & Household facilities (Radio, TV etc), Deaths in last 12 months in the Household. B. Individual Information (Question relating to Individuals), Place of birth, Migration, Literacy, Educational attainment, Marital status, Age at first Marriage, Children born, Economic/Non-economic activities, occupation/Industry, employment status, Reasons for not being active, Living arrangement of children below 16 years of age.

Cleaning operations

Data editing took place at a number of stages throughout the processing, including:

a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing e) Structural checking of SPSS data files

Response rate

At the time of census there were 3,914 VDC's and 58 municipalities. VDC's contained a total of 35,226 wards while urban areas contained 806 wards. Thus total numbers of wards in the country were 36,032. Out of these wards, 957 wards (including 2 urban wards) were affected due to the political disturbances in the country. Works in 83 VDC's of 12 districts were completely affected. 747 wards were completely affected. 2 wards of 2 municipalities and some wards of 37 VDC's were partially affected. In Salyan and Kalikot even listing was disturbed in some areas. In these districts population was estimated on the basis of listing sheet and following other estimation procedures.

For form 2, there is no available data for response rate.

Sampling error estimates

Estimates from a sample survey are affected by two types of errors: 1) non-sampling errors and 2) sampling errors.

The sampling error is not available.

Non-sampling errors are the results of mistakes made in the implementation of data collection and data processing. Numerous efforts were made during implementation of the population census 2001 to minimize this type of error, however, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

This method is discussed in detail in the document 'Sample Design for the 2001 Census of Housing and Population, Nepal'.

Data appraisal

The post enumeration survey was conducted to assess the completeness in the census enumeration and also the quality of the answers given to the questions asked in the population census. An independent verification of the census enumeration through a PES on a sample basis can provide an estimate of the extent of under enumeration or over enumeration that occurred at the census.

The PES 2001 was planned as an independent intensive re-interviews of all households in the sampled enumeration areas. The sample was restricted to a manageable size as mentioned elsewhere. A single stage stratified sampling design was adopted for the household enumeration sampling 7900 households and a two stage stratified design was used for the individual questionnaire. The Dual System Estimation metod was adopted for the survey design.

The detailed information can be found in PES Report under Census Report.

Abstract

This research of registered businesses with one to four employees was conducted in Nepal from March 8 to June 15, 2009, at the same time with 2009 Nepal Enterprise Survey. Data from 118 establishments was analyzed.

Micro-Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country's business environment. The remaining questions assess the survey respondents' opinions on what are the obstacles to firm growth and performance.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is an establishment with one to four employees.

Universe

The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities sectors.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for Nepal was selected using stratified random sampling. Two levels of stratification were used for the Micro-Enterprise Survey: industry and region.

Industry stratification was designed at three levels: the universe was stratified into manufacturing, retail, and other services industries. Other services were further divided into tourism and non-tourism as the World Bank wanted to oversample tourism firms.

Regional stratification was defined in terms of the geographic regions with the main cities of economic activity in the country. Western Nepal included Butwal, Dhangadhi, Nepalgunj, and Pokhara; Central Nepal included Banepa, Bhaktapur, Bharatpur, Birgunj, Hetauda, Kathmandu, Lalitpur, and Simara; Eastern Nepal included Bhadrapur, Biratnagar, and Itahari.

120 micro establishments were targeted for interviews.

Initially a sample frame was sought from the Government of Nepal and from appropriate trade associations; but the lists that were obtained were deemed incomplete and potentially out of date. In consultation with the contractor, the World Bank decided to undertake block enumeration, i.e. the contractor would physically create a list of establishments from which to sample from. In total, the contractor enumerated 6,755 establishments for the survey fieldwork.

Detailed information about block enumeration strategy can be can be found in "Description of Nepal Implementation 2009" in "Technical Documents" folder.

Mode of data collection

Face-to-face [f2f]

Research instrument

The current survey instruments are available: - Core Questionnaire + Manufacturing Module [ISIC Rev.3.1: 15-37] in English with Nepali translation - Core Questionnaire + Retail Module [ISIC Rev.3.1: 52] in English with Nepali translation - Core Questionnaire [ISIC Rev.3.1: 45, 50, 51, 55, 60-64, 72] in English with Nepali translation - Screener Questionnaire in English

The “Core Questionnaire” is the heart of the Enterprise Survey and contains the survey questions asked of all firms across the world. There are also two other survey instruments - the “Core Questionnaire + Manufacturing Module” and the “Core Questionnaire + Retail Module.” The survey is fielded via three instruments in order to not ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.

Micro-Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

Complete information regarding the sampling methodology, sample frame, weights, response rates, and implementation can be found in "Description of Nepal Implementation 2009" in "Technical Documents" folder.

Abstract

The COVID-19 Socioeconomic-/Cash-Based Intervention Post-Distribution Monitoring (CBI PDM) was conducted in September 2021 to assess the needs of the refugees in Eastern Nepal and Kathmandu. The survey consists of two parts. The first part of the survey measures the impact of COVID-19 on refugees' knowledge, behavior and health as well as refugees' economic livelihoods and the second part monitors the latest cash assistance programme. As a response to COVID-19, UNHCR has since the start of the pandemic launched multiple new cash grants and expanded existing programs. UNHCR's cash assistance complements governments' efforts by contributing with an additional safety net for vulnerable refugees and others left behind. Also during the course of 2021, UNHCR has continued to support the COVID-19 emergency response with cash assistance. UNHCR uses PDM as a mechanism to collect refugees' feedback on the quality, sufficiency, utilization and effectiveness of the assistance items they receive. In order to ensure that the cash assistance provided meets the intended programme objectives and that desired outcomes are achieved, UNHCR conducts regular post-distribution and outcome monitoring with a sample or all of the recipients.

Geographic coverage

The survey covers Eastern Nepal (Pathari sanichare and Beldangi refugee camps) and refugees living in Kathmandu.

Analysis unit

Households

Universe

The sample universe covers all urban refugee households (239) living in Kathmandu as well as all 2,409 Bhutanese refugee households living in Pathari sanichare and Beldangi camps.

Kind of data

Sample survey data [ssd]

Sampling procedure

Stratified random sampling was implemented drawing two samples seperately for urban and Bhutanese (camp) refugees.

Mode of data collection

Mail Questionnaire [mail]