Multiple Indicator Cluster Survey 2012-2013
Bangladesh, 2012 - 2013
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BGD_2012_MICS_v01_M
Multiple Indicator Cluster Survey 2012-2013
| Name | Country code |
|---|---|
| Bangladesh | BGD |
Multiple Indicator Cluster Survey - Round 5 [hh/mics-5]
Since its inception in 1995, the Multiple Indicator Cluster Surveys, known as MICS, has become the largest source of statistically sound and internationally comparable data on women and children worldwide. In countries as diverse as Costa Rica, Mali and Qatar, 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 has been a major source of data on the Millennium Development Goals (MDG) indicators and will be a major data source in the post-2015 era.
The Multiple Indicator Cluster Survey, Round 5 (MICS5) is the fifth round of MICS surveys, previously conducted around 1995 (MICS1), 2000 (MICS2), 2005-2007 (MICS3) and 2009-2011 (MICS4). MICS was originally developed to support countries measure progress towards an internationally agreed set of goals that emerged from the 1990 World Summit for Children.
The fifth round of Multiple Indicator Cluster Surveys (MICS5) is scheduled for 2013-2016 and survey results are expected to be available from 2015 onwards. Data collected in MICS5 will play a critical role in the final assessment of the MDGs in September 2015 and subsequent surveys in MICS6 will provide the baselines for the Sustainable Development Goals that will follow.
Information on more than 130 internationally agreed-upon indicators is being collected through MICS5. In addition to collecting information on intervention coverage, MICS also explores knowledge of and attitudes to certain topics, and specific behaviors of women, men and children, enabling analysts to gain insights into behaviours that may affect women’s and children’s lives. MICS routinely disaggregates data so that disparities associated with age, gender, education, wealth, location of residence, ethnicity and other characteristics are revealed.
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 survey presents data from an equity perspective by indicating disparities by sex, area, division, education, living standards, and other characteristics. Bangladesh MICS 2012-2013 is based on a sample of 51,895 households interviewed and provides a comprehensive picture of children and women in the seven divisions of the country. A two-stage, stratified cluster sampling approach was used for the selection of the survey sample.
Sample survey data [ssd]
- individuals
- households
Version
- v01: Edited, anonymous datasets for public distribution.
Scope
The scope of the Multiple Indicator Cluster Survey includes:
- Household: List of Household Members, Education, Household Characteristics, Child Discipline, Water and Sanitation, Handwashing, and Salt Iodization;
- Women: Women's Background, Access to Mass Media and use of Information/Communication Technology, Marriage, Child Mortality, Desire for Last Birth, Maternal and Newborn Health, Post-Natal Health Checks, Contraception, Unmet Need, Illness Symptoms, and HIV/AIDS;
- Children: Child's Age, Birth Registration, Early Childhood Development, Breastfeeding, Care of Illness, and Anthropometry.
Coverage
National
The survey covered all de jure household members (usual residents), all women aged between 15-49 years, all children under 5 living in the household.
Producers and sponsors
| Name | Affiliation |
|---|---|
| United Nations Children’s Fund | |
| Bangladesh Bureau of Statistics | Ministry of Planning |
| Name | Role |
|---|---|
| United Nations Children’s Fund | Financial and technical support |
Sampling
The primary objective of the sample design for the Multiple Indicator Cluster Survey (MICS) was to produce statistically reliable estimates of most indicators, at the national level, for urban and rural areas, for the seven divisions, and for the sixty four districts of the country. Districts of the country were defined as the sampling strata.
A two-stage, stratified cluster sampling approach was used for the selection of the survey sample.
The sample size for the Multiple Indicator Cluster Survey (MICS) was calculated as 55,200 households. For the calculation of the sample size, the key indicator used was the proportion of women with 4+ ANC visits.
The number of households selected per cluster for the Bangladesh MICS 2012-2013 was determined as 20 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 50 sample clusters would need to be selected in each of the 20 UNDAF districts and 40 sample clusters would need to be selected from the remaining 44 districts.
As the individual districts were considered to be domains of estimation and the sample size was determined to address the minimum requirement for the number of sample households, there was no need for increasing the sample based on the population of the district; therefore proportional allocation by district was not used. As mentioned before, 50 clusters were allocated to each UNDAF district and 40 clusters allocated for the remaining districts, with the final sample size calculated as 55,200 households (50 clusters 20 districts 20 sample households per cluster for UNDAF districts, and 40 clusters 44 districts 20 sample households per cluster for non-UNDAF districts).
The 2011 census frame was used for the selection of clusters. Census enumeration areas (EAs) were defined as primary sampling units (PSUs), and were selected from each of the sampling strata using a probability proportional to size (PPS) sampling procedure, based on the number of households in each enumeration area from the population and housing census 2011 frame. The first stage of sampling was thus completed by selecting the required number of enumeration areas from each of the sixty four (64) districts. The definition of urban areas used in MICS is in line with the one followed by the Bangladesh Bureau of Statistics for the enumeration and results of the national Population and Housing Census 2011.
Since the sampling frame (the 2011 census) was not up-to-date, a field operation before the survey for a new listing of households was conducted in all the sample enumeration areas during the period of 30 November to 6 December, 2012. For this purpose, experienced staff of the Bangladesh Bureau of Statistics were assigned with background information and training in this listing task. The assigned staff visited all households following survey protocols and filled a prescribed schedule with necessary information. Directions to the selected cluster were also provided in the listing schedule along with the free hand sketch map.
Lists of households were prepared by the listing staff in the field for each enumeration area. The households were then sequentially numbered from 1 to n (the total number of households in each enumeration area) at the BBS HQ, where the selection of 20 households in each enumeration area was carried out using random systematic selection procedures.
From the list of 20 households selected from each enumeration area for the survey (cluster), a sub-sample of 5 households was selected using the random systematic selection procedure for collecting information on arsenic content of the drinking water used by the household. From among these 5 selected households, one household was randomly chosen for testing E.coli content. This particular household was also identified for collection and testing of 'source' water for arsenic and E.coli content. Thus, a total of 13,800 households (2760 clusters*5) were selected for testing of arsenic content in household drinking water; 2,760 households were selected for testing of E.coli in household drinking water and the same households were also identified for testing the 'source' water (source from which the household collected its drinking water) for both arsenic and E.coli contents. To facilitate selection of households for water testing in the field, a 'Household selection table' was provided to the Supervisor in each of the survey teams.
The sampling procedures are more fully described in "Bangladesh Multiple Indicator Cluster Survey 2012-13 - Final Report" pp.157-161.
Of the 55,120 households selected for the sample, 52,711 were found to be occupied. Of these, 51,895 were successfully interviewed for a household response rate of 98.5 percent.
In the interviewed households, 59,599 women (age 15-49 years) were identified. Of these, 51,791 were successfully interviewed, yielding a response rate of 86.9 percent within interviewed households.
There were 23,402 children under age five listed in the household questionnaires. Questionnaires were completed for 20,903 of these children, which corresponds to a response rate of 89.3 percent within interviewed households.
Overall response rates for households, women’s questionnaire, and overall response rate for under-5 questionnaire are calculated for the individual interviews of women, and under-5s, respectively.
Overall response rates 85.6 and 87.9 percent are calculated for the individual interviews of women and under-5s, respectively.
Sample weights were calculated and used in the subsequent analyses of the survey data.
The major component of the weight is the reciprocal of the sampling probabilities employed in selecting the number of sample households in that particular sampling stratum and PSU. The sampling fraction is the product of the 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.
The non-response adjustment factors for the individual women and under-5 questionnaires were applied to the adjusted household weights. The numbers of eligible women 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 nonresponse) 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 nonresponse). A similar standardization procedure was followed in obtaining standardized weights for the individual women and under-5 questionnaires. Adjusted (normalized) weights varied between 0.057542 and 7.620269 in the 2760 sample enumeration areas (clusters).
Sample weights were appended to all data sets, and analyses were performed by weighting households, women, and under-5s with these sample weights.
Survey instrument
The questionnaires for the Generic MICS were structured questionnaires based on the MICS5 model questionnaire with some modifications and additions. Household questionnaires were administered in each household, which collected various information on household members including sex, age and relationship. The household questionnaire includes List of Household Members, Education, Household Characteristics, Child Discipline, Water and Sanitation, Handwashing, and Salt Iodization.
In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49 and children under age five. The questionnaire was administered to the mother or primary caretaker of the child.There is also a water quality testing questionnaire to measure arsenic and E.coli content in the household drinking water in a sub-sample of households.
The women's questionnaire includes Women's Background, Access to Mass Media and use of Information/Communication Technology, Marriage, Child Mortality, Desire for Last Birth, Maternal and Newborn Health, Post-Natal Health Checks, Contraception, Unmet Need, Illness Symptoms, and HIV/AIDS.
The children's questionnaire includes Child's Age, Birth Registration, Early Childhood Development, Breastfeeding, Care of Illness, and Anthropometry.
The questionnaire on water quality testing was administered to a sub-sample of sampled households for measuring arsenic and E. coli- content in the household drinking water and included only one module. A sub-sample of 5 households were selected per cluster, out of the selected 20 household for the survey, to test arsenic content of the household drinking water and one of these 5 households was identified to test E.coli content in the drinking water. Source water for this household was tested for arsenic and E.coli content.
The questionnaires are based on the MICS5 model questionnaire3 tested during the global MICS5 pilot study in Sirajganj and Bogra during May-June 2012. From the MICS5 pilot English version, the questionnaires were translated into Bengali and tested during the global MICS5 pilot. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires. 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 age under 5 years. Details and findings of these measurements are provided in the respective sections of the report.
Data collection
| Start | End |
|---|---|
| 2012-12 | 2013-04 |
| Name | Affiliation |
|---|---|
| Bangladesh Bureau of Statistics | Ministry of Planning |
There is one supervisor for each of the 32 data collection teams in the field.
Training for the fieldwork was conducted for 14 days in November, 2012. Training included lectures on interviewing techniques and the contents of the questionnaires, and mock interviews between trainees to gain practice in asking questions. Towards the end of the training period, trainees spent 2 (two) days in practice interviewing in Dhaka and Narayanganj.
The data were collected by 32 teams; each was comprised of four (04) female interviewers, one editor, one measurer and a supervisor. Fieldwork began in December, 2012 and concluded in April, 2013.
Data processing
Data were entered using the CSPro software. The data were entered on 30 microcomputers and carried out by 30 data entry operators and 1 data entry supervisors. In order to ensure quality control, all questionnaires were double entered and internal consistency checks were performed. Procedures and standard programs developed under the global MICS5 programme and adapted to the Bangladesh questionnaire were used throughout. Data processing began simultaneously with data collection in December, 2012 and was completed in May, 2013. Data were analysed using the Statistical Package for Social Sciences (SPSS) software program, Version 18, and the model syntax and tabulation plans developed by UNICEF were used for this purpose.
Data appraisal
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, and is a measure of the sampling error. 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 the 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 per cent of all possible samples of identical size and design.
For the calculation of sampling errors from the MICS data, programs developed in CSPro Version 5.0, SPSS Version 21 Complex Samples module and CMRJack have 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. Given the use of normalized weights, by comparing the weighted and unweighted counts it is possible to determine whether a particular domain has been under-sampled 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 over-sampled. As explained later in the footnote of Table SE.1, there is an exception in the case of indicators 4.1 and 4.3, and for household drinking water arsenic count, for which the unweighted count represents the number of sample households, and the weighted counts reflect the total population.
Sampling errors are calculated for indicators of primary interest, for the Bangladesh level, for urban and rural areas, and for all divisions. Three of the selected indicators are based on households, 4 are based on household members, 7 are based on women and 7 are based on children under 5.
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 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 under-5s birth certificates
- Observation of women’s health cards
- Observation of places for hand washing
- Presence of mother in the household and the person interviewed for the under-5 questionnaire
- Selection of children age 1–14 years for the child discipline module
- School attendance by single age
- Sex ratio at birth among children ever born and living
The results of each of these data quality tables are shown in appendix D in document "Bangladesh Multiple Indicator Cluster Survey 2012-13 - Final Report" pp.177-189.
Access policy
UNICEF
UNICEF
http://mics.unicef.org/surveys
Cost: None
Depositor information
| Name |
|---|
| United Nations Children's Fund |
Data Access
| Name | Affiliation | URL | |
|---|---|---|---|
| Childinfo | UNICEF | http://www.childinfo.org/mics4_surveys.html | mics@unicef.org |
| Is signing of a confidentiality declaration required? | Confidentiality declaration text |
|---|---|
| yes | 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.
Example,
United Nations Children’s Fund, Bangladesh Bureau of Statistics. Bangladesh Multiple Indicator Cluster Survey (MICS) 2012-2013, Ref. BGD_2012_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.
Contacts
| Name | Affiliation | |
|---|---|---|
| Dr. Dipankar Roy | Bangladesh Bureau of Statistics | dr.droy69@gmail.com |
| Abdur Rashid Howlader | Bangladesh Bureau of Statistics | arhowlader@yahoo.com |
Metadata production
DDI_BGD_2012_MICS_v01_M_WB
| Name | Affiliation | Role |
|---|---|---|
| Development Data Group | The World Bank | Documentation of the DDI |
2015-12-10
Metadata version
Version 01 (December 2015)