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.
Kind of data
Sample survey data [ssd]
- v01: Edited, anonymous datasets for public distribution.
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)
Unit of analysis
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.
Producers and sponsors
United Nations Children’s Fund
Central Bureau of Statistics of Nepal
United Nations Children’s Fund
Financial and technical support
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.
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.
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, from certain Primary Sampling Unit (PSU) within certain category. The sampling fraction is the product of probabilities of selection at every stage in each sampling stratum.
A second component in the calculation of sample weights takes into account the level of nonresponse for the household and individual interviews. The adjustment for household non-response is equal to the inverse value of: RRh = Number of interviewed households in stratum h/ Number of occupied households listed in stratum h
The non-response adjustment factors for women’s and under-5s’ questionnaires are applied to the adjusted household weights. Numbers of eligible women and under-5s 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 above factors 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 the total sample size at the subregional level. Normalization is performed by dividing the aforementioned design weights by the average design weight at the subregional level. The average design weight is calculated as the sum of the design weights divided by the unweighted total. A similar standardization procedure was followed in obtaining standardized weights for the women’s and under-5s’ questionnaires. The great majority of the adjusted (normalized) household weights were in the range of 0.3 to 2.0, but a few fell outside this range, usually because of large disparities between the original estimated size of a ward or segment and the actual size found during listing.
Sample weights were appended to all datasets and analyses were performed by weighting each household, woman or under-5 with these sample weights.
Dates of collection
Mode of data collection
Data collection supervision
There is one supervisor for each of the 12 data collection teams in the field.
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).
Central Bureau of Statistics of Nepal
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.
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.
Other forms of 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
- Completeness of reporting
- Observation of places for hand washing
- Observation of women's health cards
- Observation of under-5s birth certificates
- Observation of vaccination cards
- Presence of mother in the household and the person interviewed for the under-5 questionnaire
- Selection of children age 2-14 years for the child discipline module
- School attendance by single age
The results of each of these data quality tables are shown in appendix D in document "Nepal Multiple Indicator Cluster Survey 2010 - Final Report" pp.224-233.
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 of Nepal. Nepal Multiple Indicator Cluster Survey (MICS) 2010, Ref. NPL_2010_MICS_v01_M. Dataset downloaded from [url] on [date].
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.