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.
For Nepal, this fifth round of the global MICS was the first survey in the country to capture data specifically on the status of children and women at the national level. In addition, the inclusion of anthropometric measurements and water quality testing in NMICS has significantly developed the capacity of interviewers, supervisors and ultimately CBS to carry out such types of comprehensive and instrumental surveys in the future.
The Nepal Multiple Indicator Cluster Survey (MICS) 2014 was conducted by the Central Bureau os Statistics (CBS) in 2014 in collaboration with UNICEF Nepal. It is part of the global MICS exercise - the fifth round since its start in Nepal as sub-national MICS in the Mid- and Far Western region, 2010.
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.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- v01: Edited, anonymous datasets for public distribution.
The scope of the Multiple Indicator Cluster Survey includes:
- Household: List of Household Members, Education, Child Labour, Child Discipline, Household Characteristics, Water and Sanitation, Handwashing, Salt Iodization.
- Women: 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
- Children: Age, Birth Registration, Early Childhood Development, Breastfeeding and Dietary Intake, Immunization, Care of Illness, Anthropometrym.
- Water Quality: This Questionnaire 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 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.
Producers and sponsors
United Nations Children’s Fund
Central Bureau of Statistics Nepal
United Nations Children’s Fund
Financial and technical support
Government of Nepal
Financial and technical support
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.
Of the 13,000 households selected for the sample, 12,598 were found to be occupied. Of these, 12,405 were successfully interviewed for a household response rate of 98.5 percent. One cluster was dropped due to remote location and heavy snowfall.
In the interviewed households, 14,936 women (aged 15–49 years) were identified. Of these, 14,162 were successfully interviewed, yielding a response rate of 94.8 percent for women within the interviewed households.
There were 5,663 children under five listed in the household questionnaires. Questionnaires were completed for 5,349 of these children, which corresponds to a response rate of 94.5 percent for children under five within interviewed households.
Overall response rates of 93.4 percent and 93.0 percent are calculated for the individual interviews of women and children under five, respectively.
The household response rates were similar across regions and areas, with a slightly lower rate in the Far Western Terai. The response rates for women and children under five show a similar pattern, with the exception of the Western Mountains, where the women’s overall response rate was 85.8 percent.
The Nepal MICS 2014 sample is not self-weighting. Essentially, by allocating equal numbers of households to each of 11 zones and another size to three zones and a high over-sampling in one more zone, different sampling fractions were used in each zone since the sizes of the ecological zones varied. For this reason, sample weights were calculated and these were used in the subsequent analyses of the survey data.
The major component of the weight is the reciprocal of the sampling fraction employed in selecting the number of sample households in that particular sampling stratum (h) and PSU (i): Whi=1/Fhi The term fhi, the sampling fraction for the i-th sample PSU in the h-th stratum, is the product of probabilities of selection at every stage in each sampling stratum.
A final component in the calculation of sample weights takes into account the level of non-response for the household and individual interviews. The adjustment for household non-response in each stratum is equal to: 1/RRh Where RRh is the response rate for the sample households in stratum h, defined as the proportion of the number of interviewed households in stratum h out of the number of selected households found to be occupied during the fieldwork in stratum h.
After the completion of fieldwork, response rates were calculated for each sampling stratum. These were used to adjust the sample weights calculated for each cluster. The non-response adjustment factors for the individual women, men, and under-5 questionnaires were applied to the adjusted household weights. Numbers of eligible women, men and under-5 children were obtained from the roster of household members in the Household Questionnaire for households where interviews were completed.
The design weights for the households were calculated by multiplying the inverse of the probabilities of selection by the non-response adjustment factor for each enumeration area. These weights were then standardized (or normalized), one purpose of which is to make the weighted sum of the interviewed sample units equal to the total sample size at the national level. Normalization is achieved by dividing the full sample weights (adjusted for non-response) by the average of these weights across all households at the national level. This is performed by multiplying the sample weights by a constant factor equal to the unweighted number of households at the national level divided by the weighted total number of households (using the full sample weights adjusted for non-response). A similar standardization procedure was followed in obtaining standardized weights for the individual women, men and under-5 questionnaires. Adjusted (normalized) weights varied between 0.02 and 4.93 in the 520 sample enumeration areas (clusters).
Sample weights were appended to all datasets and analyses were performed by weighting households, women, men or under-5s with these sample weights.
Dates of Data Collection
Data Collection Mode
The data were collected by 15 teams; each team comprised three female interviewers, one editor, one measurer and one supervisor.
Data Collection Notes
Master training of trainers was held 12–20 January 2014. This was followed by three weeks of residential training for fieldworkers from 30 January to 19 February 2014 in Banepa, Kavre District. Training included lectures on interviewing techniques and the contents of the questionnaires, mock interviews between trainees to gain practice in asking questions, and demonstration on anthropometric measurement and water quality test. Towards the end of the training period, trainees spent four days in practice interviewing in villages near to Banepa.
The data were collected by 15 teams; each comprised three female interviewers, one editor, one measurer and one supervisor. Fieldwork began in February 2014 and concluded in June 2014.
Central Bureau of Statistics Nepal
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.
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 performed. Procedures and standard programs developed under the global MICS programme and adapted to the Nepal questionnaire were used throughout. Data processing began simultaneously with data collection in March 2014 and was completed in July 2014. Data were analysed using the Statistical Package for Social Sciences (SPSS) software, Version 21.0. Model syntax and tabulation plans developed by UNICEF were customized and used for this purpose.
Estimates of Sampling Error
The following sampling error measures are presented in this appendix for each of the selected indicators:
- Standard error (se): Standard error is the square root of the variance of the estimate. For survey indicators that are means, proportions or ratios, the Taylor series linearization method is used for the estimation of standard errors. For more complex statistics, such as fertility and mortality rates, the Jackknife repeated replications method is used for standard error estimation.
- Coefficient of variation (se/r) is the ratio of the standard error to the value (r) 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 based on the same sample size. 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 of the survey is as efficient as a simple random sample for a particular indicator, while a deft value above 1.0 indicates an 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 MICS data, programs developed in CSPro Version 5.0, SPSS Version 21 Complex Samples module and CMRJack have been used.
A series of data quality tables are available to review the quality of the data and include the following:
- Age distribution of household population
- Age distribution of eligible and interviewed women
- Age distribution of children in household and under-5 questionnaires
- Birth date reporting: Household population
- Birth date and age reporting: Women
- Birth date and age reporting: Under-5s
- Birth date reporting: Children, adolescents and young people
- Birth date reporting: First and last births
- Completeness of reporting
- Completeness of information for anthropometric indicators: Underweight
- Completeness of information for anthropometric indicators: Stunting
- Completeness of information for anthropometric indicators: Wasting
- Heaping in anthropometric measurements
- Observation of birth certificates
- Observation of vaccination cards
- Observation of women's health cards
- Observation of places for handwashing
- Respondent to the under-5 questionnaire
- Selection of children aged 1–17 years for the child labour and child discipline modules
- School attendance by single age
- Sex ratio at birth among children ever born and living
- Births by calendar years
- Reporting of age at death in days
- Reporting of age at death in months
The results of each of these data quality tables are shown in appendix D in document "Multiple Indicator Cluster Survey 2014 - Final Report" pp.283-298.
Multiple Indicator Cluster Surveys
Uttam Narayan Malla
Central Bureau of Statistics
Central Bureau of Statistics
Users of the data agree to keep confidential all data contained in these datasets and to make no attempt to identify, trace or contact any individual whose data is included in these datasets.
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
United Nations Children's Fund, Central Bureau of Statistics Nepal. Nepal Multiple Indicator Cluster Survey (MICS) 2014, Ref. NPL_2014_MICS_v01_M. Dataset downloaded from [url] on [date].
Location of Data Collection
Archive where study is originally stored
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
DDI Document ID
Development Economics Data Group
The World Bank
Documentation of the DDI
Date of Metadata Production
DDI Document version
Version 01 (May 2016)