Multiple Indicator Cluster Survey 2016, Khuvsgul Province
Mongolia, 2016
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Reference ID
MNG_2016_MICS-KP_v01_M
Producer(s)
National Statistics Office of Mongolia, United Nations Children’s Fund
Collection(s)
Metadata
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Jul 31, 2018
Last modified
Jul 31, 2018
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Identification
Survey ID Number
MNG_2016_MICS-KP_v01_M
Title
Multiple Indicator Cluster Survey 2016, Khuvsgul Province
Subtitle
Khuvsgul Province
Country/Economy
| Name | Country code |
|---|---|
| Mongolia | MNG |
Study type
Multiple Indicator Cluster Survey - Round 5 [hh/mics-5]
Series Information
The “Child Development Survey” (Multiple Indicator Cluster Survey) was carried out in Khuvsgul province, Mongolia 2016 by National Statistical Office, as part of the global MICS programme. Financial and technical 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 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.
Abstract
The Survey provides valuable information on the status of children and women in Khuvsgul province and gives statistically sound and internationally comparable data essential for developing evidence-based policies and programmes, and for monitoring progress towards local government’s goals and commitments.
OBJECTIVES
The 2016 CDS in Khuvsgul province has as its primary objectives:
- To provide up-to-date information for assessing the situation of children and women in Khuvsgul province;
- 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 furnish data needed to monitor progress towards the Millennium Development Goals and other internationally agreed upon goals, as a basis for future action at the provincial level;
- To generate data for the assessment of the progress towards of the objectives set out in the UNICEF Country Program for Mongolia, 2012-2016;
- To contribute to the generation of baseline data for the post-2016 agenda;
- To validate data from other sources and the results of focused interventions.
OBJECTIVES
The 2016 CDS in Khuvsgul province has as its primary objectives:
- To provide up-to-date information for assessing the situation of children and women in Khuvsgul province;
- 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 furnish data needed to monitor progress towards the Millennium Development Goals and other internationally agreed upon goals, as a basis for future action at the provincial level;
- To generate data for the assessment of the progress towards of the objectives set out in the UNICEF Country Program for Mongolia, 2012-2016;
- To contribute to the generation of baseline data for the post-2016 agenda;
- To validate data from other sources and the results of focused interventions.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- Individuals
- Households
- Households
Version
Version Description
- v01: Edited, anonymous datasets for public distribution.
Scope
Notes
The scope of the Multiple Indicator Cluster Survey includes:
- HOUSEHOLD: Household information panel, List of Household Members, Education, Child Functioning (age 5-17), Child Labour, Child Discipline, Child Jockeys, Household Characteristics, Water and Sanitation, Hand Washing and 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, Post-natal Health Checks, Illness Symptoms, Contraception, Unmet Need, Attitudes toward Domestic Violence, Marriage/ Union, Sexual Behaviour, HIV/AIDS, Tobacco and Alcohol Use and Life Satisfaction.
- CHILDREN: Age, Birth Registration, Early Childhood Development, Breastfeeding and Dietary Intake, Immunization, Care of Illness, Child Functioning (age 2-4) and Anthropometry.
- MAN: Man’s Background, Access to Mass Media and Use of Information and Communication Technology, Fertility, Attitudes toward Domestic Violence, Marriage/Union, Contraception, Sexual Behaviour, HIV/AIDS, Tobacco and Alcohol Use and Life Satisfaction.
- WATER: Testing of residential water quality and water quality testing results.
- HOUSEHOLD: Household information panel, List of Household Members, Education, Child Functioning (age 5-17), Child Labour, Child Discipline, Child Jockeys, Household Characteristics, Water and Sanitation, Hand Washing and 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, Post-natal Health Checks, Illness Symptoms, Contraception, Unmet Need, Attitudes toward Domestic Violence, Marriage/ Union, Sexual Behaviour, HIV/AIDS, Tobacco and Alcohol Use and Life Satisfaction.
- CHILDREN: Age, Birth Registration, Early Childhood Development, Breastfeeding and Dietary Intake, Immunization, Care of Illness, Child Functioning (age 2-4) and Anthropometry.
- MAN: Man’s Background, Access to Mass Media and Use of Information and Communication Technology, Fertility, Attitudes toward Domestic Violence, Marriage/Union, Contraception, Sexual Behaviour, HIV/AIDS, Tobacco and Alcohol Use and Life Satisfaction.
- WATER: Testing of residential water quality and water quality testing results.
Coverage
Geographic Coverage
Provincial level , for urban and rural areas, for six regions namely Central, Touristic, Agricultural, Ider, Tes-Ekh and Murun.
Geographic Unit
Bagh within soum in the province is the lowest administrative units and is defined as primary sampling units.
Universe
The survey covered all de jure household members (usual residents), all women age 15-49 years, all men age 15-49 years and all children under 5 living in the household.
Producers and sponsors
Primary investigators
| Name |
|---|
| National Statistics Office of Mongolia |
| United Nations Children’s Fund |
Funding Agency/Sponsor
| Name | Abbreviation |
|---|---|
| United Nations International Children's Fund | UNICEF |
Sampling
Sampling Procedure
The sample for the Khuvsgul province CDS was designed to provide estimates for a large number of indicators on the situation of children and women at provincial level, for urban and rural areas, for six regions namely Central, Touristic, Agricultural, Ider, Tes-Ekh and Murun. The regions were identified as the main sampling domains and the sample was selected in two stages. At the first stage the primary sampling units (PSUs) were the baghs in soums in Khuvsgul province.
A total of 2650 households were selected and selection probabilities and corresponding weights vary by PSUs and by the second stage stratum of households with and without children under 5 years of age.
Within each sampling stratum, the sample was selected in two stages. The PSUs within each stratum were selected systematically with probability proportional to size (PPS). After a household listing was carried out in each sample PSU, a systematic sample of households was selected separately for households with and without children, for a total of 25 sample households per PSU. The 2015 official statistics of the household registration was used as a sampling frame.
The sample was stratified by region and is not self-weighting. For reporting all survey results, sample weights are used. As it was mentioned before the lowest administrative units (bagh within soum in the province) were defined as primary sampling units. The survey covered 23 soums and 106 sample baghs; the listing of households was updated during September-October 2016.
During the data collection fieldwork in October-December 2016, we had encountered problems due to seasonal movement of families; transportation means to reach remote families were broken due to heavy snow falls and severe cold. In spite of this, we managed to collect survey data in all of the 106 selected PSUs.
For reporting survey results, sample weights are used. A more detailed description of the ample design can be found in the Final Report (Appendix A) attached as Related Material.
A total of 2650 households were selected and selection probabilities and corresponding weights vary by PSUs and by the second stage stratum of households with and without children under 5 years of age.
Within each sampling stratum, the sample was selected in two stages. The PSUs within each stratum were selected systematically with probability proportional to size (PPS). After a household listing was carried out in each sample PSU, a systematic sample of households was selected separately for households with and without children, for a total of 25 sample households per PSU. The 2015 official statistics of the household registration was used as a sampling frame.
The sample was stratified by region and is not self-weighting. For reporting all survey results, sample weights are used. As it was mentioned before the lowest administrative units (bagh within soum in the province) were defined as primary sampling units. The survey covered 23 soums and 106 sample baghs; the listing of households was updated during September-October 2016.
During the data collection fieldwork in October-December 2016, we had encountered problems due to seasonal movement of families; transportation means to reach remote families were broken due to heavy snow falls and severe cold. In spite of this, we managed to collect survey data in all of the 106 selected PSUs.
For reporting survey results, sample weights are used. A more detailed description of the ample design can be found in the Final Report (Appendix A) attached as Related Material.
Response Rate
Of the 2650 households selected for the sample 2641 households were available. Of these 2626 households were successfully interviewed yielding a response rate of 99.4 percent. A total of 2115 women age 15-49 years were listed within the interviewed households, of which 2039 were successfully interviewed, indicating a response rate of 96.4 percent.
The survey also sampled men age 15-49, but required only a subsample of every second household. 1007 men age 15-49 years were listed in the household questionnaires. Questionnaires were completed for 943 eligible men, which corresponds to a response rate of 93.6 percent within eligible interviewed households.
In addition, 1134 children under 5 were listed in the household questionnaires. Questionnaires were completed for 1129 of these children, which corresponds to a response rate of 99.6 percent within interviewed households.
Overall response rates in Khuvsgul province stands at 93.1 percent of men age 15-49 years, 95.9 percent for women and 99.0 percent calculated for mothers/ caregivers of children under 5.
The survey also sampled men age 15-49, but required only a subsample of every second household. 1007 men age 15-49 years were listed in the household questionnaires. Questionnaires were completed for 943 eligible men, which corresponds to a response rate of 93.6 percent within eligible interviewed households.
In addition, 1134 children under 5 were listed in the household questionnaires. Questionnaires were completed for 1129 of these children, which corresponds to a response rate of 99.6 percent within interviewed households.
Overall response rates in Khuvsgul province stands at 93.1 percent of men age 15-49 years, 95.9 percent for women and 99.0 percent calculated for mothers/ caregivers of children under 5.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2016-10-21 | 2016-12-10 |
Data Collection Mode
Face-to-face [f2f]
Data Collection Notes
Training for 45 fieldwork personnel was conducted for fifteen days on 10-20 October 2016 by combined forms of lectures and practice sessions.
The training included lectures on interviewing techniques and the contents of the questionnaires. Moreover, it has concentrated on teaching paper and tablet questionnaires and mock interviews between trainees to gain practice in asking questions.
The paper questionnaires testing was carried out in 7th bagh of Murun soum of Khuvsgul province for two days and testing of tablets in 6th bagh for another two days. As module on water quality was included in MICS for the first time, Mr Andrew Shantz consultant of UNICEF has supported training on water quality testing. Finally, all 45 participants were taken tests and the interviewers, editors and supervisors were selected based on their performance in the test.
The data were collected by five teams; each team was comprised of a supervisor, 5 interviewers (2 men assigned as main measurers) and 2 drivers.
The data collection fieldwork was carried out during October 21 to December 10, 2016. Monitoring, assessment and timely clarification of the data entered on the central network during the data collection helped improve the quality of data. In addition, field monitoring visits were done by NSO and UNICEF staff who have been involved in the training process during the data collection processes who observed some interviews and held discussions with the teams to address the issues and inaccuracies and ways for improvement. These contributed to overall quality of the data.
The training included lectures on interviewing techniques and the contents of the questionnaires. Moreover, it has concentrated on teaching paper and tablet questionnaires and mock interviews between trainees to gain practice in asking questions.
The paper questionnaires testing was carried out in 7th bagh of Murun soum of Khuvsgul province for two days and testing of tablets in 6th bagh for another two days. As module on water quality was included in MICS for the first time, Mr Andrew Shantz consultant of UNICEF has supported training on water quality testing. Finally, all 45 participants were taken tests and the interviewers, editors and supervisors were selected based on their performance in the test.
The data were collected by five teams; each team was comprised of a supervisor, 5 interviewers (2 men assigned as main measurers) and 2 drivers.
The data collection fieldwork was carried out during October 21 to December 10, 2016. Monitoring, assessment and timely clarification of the data entered on the central network during the data collection helped improve the quality of data. In addition, field monitoring visits were done by NSO and UNICEF staff who have been involved in the training process during the data collection processes who observed some interviews and held discussions with the teams to address the issues and inaccuracies and ways for improvement. These contributed to overall quality of the data.
Questionnaires
Questionnaires
Questionnaire contents and indicators for the survey were identified based on the survey objectives and covering the main indicators of the MICS5 model questionnaire recommended by UNICEF. Moreover, the principle of international comparability and with previous surveys was considered.
Five 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 age 15-49 years;
3. A questionnaire for individual men administered in every second household to all men age 15-49 years;
4. An under-5 questionnaire, administered to mothers (or caretakers) for all children under 5 living in the household; and
5. A questionnaire for evaluating water quality administered in every third household.
In addition to the administration of the questionnaires, fieldwork teams tested the salt used for cooking in the households for iodine content, observed the place for hand washing and measured the weights and heights of children age under 5 years.
The Questionnaire for Child under 5 was administered to mothers or caretakers of all children under 55 years of age living in the households. Normally, the questionnaire was administered to mothers of under-5 children; in cases when the mother was not listed in the household roster, a primary caretaker for the child was identified and interviewed.
Every third household was administered question on drinking-water quality, questioning water source of the household and testing residential water quality.
The questionnaires were pre-tested in July 2016 in 3 baghs of Kherlen and Tsenkhermandal soums of Khentii province and 2 khesegs of 8th khoroo of Bayangol District, Ulaanbaatar.
Five 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 age 15-49 years;
3. A questionnaire for individual men administered in every second household to all men age 15-49 years;
4. An under-5 questionnaire, administered to mothers (or caretakers) for all children under 5 living in the household; and
5. A questionnaire for evaluating water quality administered in every third household.
In addition to the administration of the questionnaires, fieldwork teams tested the salt used for cooking in the households for iodine content, observed the place for hand washing and measured the weights and heights of children age under 5 years.
The Questionnaire for Child under 5 was administered to mothers or caretakers of all children under 55 years of age living in the households. Normally, the questionnaire was administered to mothers of under-5 children; in cases when the mother was not listed in the household roster, a primary caretaker for the child was identified and interviewed.
Every third household was administered question on drinking-water quality, questioning water source of the household and testing residential water quality.
The questionnaires were pre-tested in July 2016 in 3 baghs of Kherlen and Tsenkhermandal soums of Khentii province and 2 khesegs of 8th khoroo of Bayangol District, Ulaanbaatar.
Data Processing
Data Editing
The MICS utilized tablet PCs for data collection. This environmental friendly solution offered many advantages including, sending the data collected from the field immediately to the central office at a click of a button, time saving from data entry (in the case of paper surveys), cost in the long term and ensuring information collected are of high quality.
The data collected by the interviewers from the respondents aggregated at the team supervisors and after required clarification and editing, the data was sent to the central network of the NSO. The data received at the central office were monitored and checked. Where additional clarifications were needed on a particular data, the team supervisors were made to contact the particular household. Followed by entering the survey data to online database using Census and Survey Processing System 5.03 (CSPro 5.03) public domain software. These followed procedures and standard programs developed under the global MICS programme and adapted to the SISS Mongolia 2013 questionnaire were used throughout.
Customization of the generic CDS syntaxes developed for MICS5 for the analysis of the data was done. Data were analyzed using the Statistical Package for Social Sciences Version 21.0 (SPSS) software program and model syntax and tabulation plans were developed by global MICS/UNICEF team.
The data collected by the interviewers from the respondents aggregated at the team supervisors and after required clarification and editing, the data was sent to the central network of the NSO. The data received at the central office were monitored and checked. Where additional clarifications were needed on a particular data, the team supervisors were made to contact the particular household. Followed by entering the survey data to online database using Census and Survey Processing System 5.03 (CSPro 5.03) public domain software. These followed procedures and standard programs developed under the global MICS programme and adapted to the SISS Mongolia 2013 questionnaire were used throughout.
Customization of the generic CDS syntaxes developed for MICS5 for the analysis of the data was done. Data were analyzed using the Statistical Package for Social Sciences Version 21.0 (SPSS) software program and model syntax and tabulation plans were developed by global MICS/UNICEF team.
Data Appraisal
Estimates of Sampling Error
The sample of respondents selected in the Khuvsgul province’s CDS-2016 is only one of the samples that could have been selected from the same population, using the same design and 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 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): 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 replication 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 which contains the true value of the indicator for the population, with a specified level of confidence. For CDS results 95% confidence intervals are used, which is the standard for this type of survey. The concept of the 95% confidence interval can be understood in this way: if many repeated samples of identical size and design were taken and the confidence interval computed for each sample, then 95% of these intervals would contain the true value of the indicator.
For the calculation of sampling errors from CDS data, programs developed in CSPro Version 5.0, SPSS Version 21 Complex Samples module and CMRJack1 have been used.
Given the use of normalized weights, by comparing the weighted and unweighted counts it is possible to determine whether a particular domain has been undersampled or over-sampled compared to the average sampling rate. If the weighted count is smaller than the unweighted count, this means that the particular domain had been oversampled.
Sampling errors are calculated for indicators of primary interest, for the province level, for urban and rural areas, and for all regions. Three of the selected indicators are based on households, 11 are households members, 41 are based on women, 24 are based on men, and 39 are based on children under 5.
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 replication 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 which contains the true value of the indicator for the population, with a specified level of confidence. For CDS results 95% confidence intervals are used, which is the standard for this type of survey. The concept of the 95% confidence interval can be understood in this way: if many repeated samples of identical size and design were taken and the confidence interval computed for each sample, then 95% of these intervals would contain the true value of the indicator.
For the calculation of sampling errors from CDS data, programs developed in CSPro Version 5.0, SPSS Version 21 Complex Samples module and CMRJack1 have been used.
Given the use of normalized weights, by comparing the weighted and unweighted counts it is possible to determine whether a particular domain has been undersampled or over-sampled compared to the average sampling rate. If the weighted count is smaller than the unweighted count, this means that the particular domain had been oversampled.
Sampling errors are calculated for indicators of primary interest, for the province level, for urban and rural areas, and for all regions. Three of the selected indicators are based on households, 11 are households members, 41 are based on women, 24 are based on men, and 39 are based on children under 5.
Access policy
Contacts
Confidentiality
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.
Citation requirements
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
Example,
National Statistics Office of Mongolia, United Nations Children’s Fund. Mongolia - Multiple Indicator Cluster Survey (MICS) 2016, Khuvsgul Province. Ref. MNG_2016_MICS-KP_v01_M. Dataset downloaded from [url] on [date].
- 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
Example,
National Statistics Office of Mongolia, United Nations Children’s Fund. Mongolia - Multiple Indicator Cluster Survey (MICS) 2016, Khuvsgul Province. Ref. MNG_2016_MICS-KP_v01_M. Dataset downloaded from [url] on [date].
Access authority
| Name | URL | |
|---|---|---|
| UNICEF | mics@unicef.org | Link |
Location of Data Collection
UNICEF
Archive where study is originally stored
UNICEF
http://mics.unicef.org/surveys
Cost: None
http://mics.unicef.org/surveys
Cost: None
Disclaimer and copyrights
Disclaimer
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.
Metadata production
DDI Document ID
DDI_MNG_2016_MICS-KP_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Economics Data Group | DECDG | The World Bank | Documentation of the DDI |
Date of Metadata Production
2018-07-30
DDI Document version
Version 01 (July 2018)