DDI_MMR_2020_FIES_v01_EN_M_v01_A_OCS_FAO
Office of the Chief Statistician
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NADA
MMR_2020_FIES_v01_EN_M_v01_A_OCS_v01
Food Insecurity Experience Scale (FIES)
FIES
MMR_2020_FIES_v01_EN_M_v01_A_OCS
FAO Statistics Division
NADA
FAO Statistics Division
Socio-Economic/Monitoring Survey [hh/sems]
Food Insecurity
SDG
SDGs
Food Access
Sustainable Development Goal (SDG) target 2.1 commits countries to end hunger, ensure access by all people to safe, nutritious and sufficient food all year around. Indicator 2.1.2, “Prevalence of moderate or severe food insecurity based on the Food Insecurity Experience Scale (FIES)”, provides internationally-comparable estimates of the proportion of the population facing difficulties in accessing food. More detailed background information is available at http://www.fao.org/in-action/voices-of-the-hungry/fies/en/.
The FIES-based indicators are compiled using the FIES survey module, containing 8 questions. Two indicators can be computed:
1. The proportion of the population experiencing moderate or severe food insecurity (SDG indicator 2.1.2).
2. The proportion of the population experiencing severe food insecurity.
These data were collected by FAO through GeoPoll. National institutions can also collect FIES data by including the FIES survey module in nationally representative surveys.
Microdata can be used to calculate the indicator 2.1.2 at national level. Instructions for computing this indicator are described in the methodological document available in the documentations tab. Disaggregating results at sub-national level is not encouraged because estimates will suffer from substantial sampling and measurement error.
Myanmar
National
Individuals
Individuals of 15 years or older.
Sample survey data [ssd]
The FIES survey module includes the following questions to compute the FIES-based indicators:
During the last 12 months, was there a time when, because of lack of money or other resources;
1. You were worried you would not have enough food to eat?
2. You were unable to eat healthy and nutritious food?
3. You ate only a few kinds of foods?
4. You had to skip a meal?
5. You ate less than you thought you should?
6. Your household ran out of food?
7. You were hungry but did not eat?
8. You went without eating for a whole day?
In addition to the FIES questions, socio-demographic information on the respondent/household including gender, age, urban or rural area, region, education, composition of the household was collected.
The survey module was administered to respondents who answered on behalf of themselves (individually-referenced module). The questionnaire was translated into the main languages of each country.
Last 12 months.
A Random Digit Dialling (RDD) approach was used to form a random sample of telephone numbers. Stratified phone numbers made available from telephone service providers or administrative registers were also used to integrate RDD when needed. Socio-demographic characteristics collected in the survey were then compared with the available information from recent national surveys to verify the extent to which the sample mirrored the total population structure. In case of discrepancies, post-stratification sampling weights were computed to adjust for the under-represented populations, typically using sex and education level.
Exclusions: NA
Design effect: NA
Computer Assisted Telephone Interview [CATI]
Post-stratification weights are provided. Population statistics are used to weight the data by gender, age, and, where reliable
data are available, education or socioeconomic status.
Statistical validation assesses the quality of the FIES data collected by testing their consistency with the assumptions of the Rasch model. This analysis involves the interpretation of several statistics that reveal 1) items that do not perform well in a given context, 2) cases with highly erratic response patterns, 3) pairs of items that may be redundant, and 4) the proportion of total variance in the population that is accounted for by the measurement model.
Not Available.
Since the population with access to mobile telephones is likely to differ from the rest of the population with respect to their access to food, post-hoc adjustments were made to control for the potential resulting bias. Post-stratification weights were built to adjust the sample distribution by gender and education of the respondent at admin-1 level, to match the same distribution in the total population. However, an additional step was needed to try to ascertain the food insecurity condition of those with access to phones compared to that of the total population.
Using FIES data collected by FAO through the GWP between 2014 and 2019, and a variable on access to mobile telephones that was also in the dataset, it was possible to compare the prevalence of food insecurity at moderate or severe level, and severe level only, of respondents with access to a mobile phone to that of the total population at national level.
The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO.
Micro datasets disseminated by FAO shall only be allowed for research and statistical purposes. Any user which requests access working for a commercial company will not be granted access to any micro dataset regardless of their specified purpose. Users requesting access to any datasets must agree to the following minimal conditions:
- The micro dataset will only be used for statistical and/or research purposes;
- Any results derived from the micro dataset will be used solely for reporting aggregated information, and not for any specific individual entities or data subjects;
- The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO;
- The micro dataset cannot be re-disseminated by users or shared with anyone other than the individuals that are granted access to the micro dataset by FAO.
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.
MMR_2020_FIES_v01_EN_M_v01_A_OCS
This dataset contains the variables used to calculate the FIES-based indicator, deomographic variables and some derived variables calculated by FAO from the survey.
4184
22
Unique respondent identifier
Unique respondent identifier
Unique respondent identifier
Unique respondent identifier
Unique respondent identifier
4184
111023711
209995901
160280059.428
28844859.522
Worried you would not have enough food to eat because of a lack of money or other resources
Worried you would not have enough food to eat because of a lack of money or other resources
Worried you would not have enough food to eat because of a lack of money or other resources
Worried you would not have enough food to eat because of a lack of money or other resources
Worried you would not have enough food to eat because of a lack of money or other resources
4184
No
1
Yes
Sysmiss
Unable to eat healthy and nutritious food because of a lack of money or other resources
Unable to eat healthy and nutritious food because of a lack of money or other resources
Unable to eat healthy and nutritious food because of a lack of money or other resources
Unable to eat healthy and nutritious food because of a lack of money or other resources
Unable to eat healthy and nutritious food because of a lack of money or other resources
4180
4
No
1
Yes
Sysmiss
Ate only a few kinds of foods because of a lack of money or other resources
Ate only a few kinds of foods because of a lack of money or other resources
Ate only a few kinds of foods because of a lack of money or other resources
Ate only a few kinds of foods because of a lack of money or other resources
Ate only a few kinds of foods because of a lack of money or other resources
4183
1
No
1
Yes
Sysmiss
Skipped a meal because there was not enough money or other resources to get food
Skipped a meal because there was not enough money or other resources to get food
Skipped a meal because there was not enough money or other resources to get food
Skipped a meal because there was not enough money or other resources to get food
Skipped a meal because there was not enough money or other resources to get food
4184
No
1
Yes
Sysmiss
Ate less than you thought you should because of a lack of money or other resources
Ate less than you thought you should because of a lack of money or other resources
Ate less than you thought you should because of a lack of money or other resources
Ate less than you thought you should because of a lack of money or other resources
Ate less than you thought you should because of a lack of money or other resources
4184
No
1
Yes
Sysmiss
Household ran out of food because of a lack of money or other resources
Household ran out of food because of a lack of money or other resources
Household ran out of food because of a lack of money or other resources
Household ran out of food because of a lack of money or other resources
Household ran out of food because of a lack of money or other resources
4182
2
No
1
Yes
Sysmiss
Hungry but did not eat because there was not enough money or other resources for food?
Hungry but did not eat because there was not enough money or other resources for food?
Hungry but did not eat because there was not enough money or other resources for food?
Hungry but did not eat because there was not enough money or other resources for food?
Hungry but did not eat because there was not enough money or other resources for food?
4183
1
No
1
Yes
Sysmiss
Went without eating for a whole day because of a lack of money or other resources?
Went without eating for a whole day because of a lack of money or other resources?
Went without eating for a whole day because of a lack of money or other resources?
Went without eating for a whole day because of a lack of money or other resources?
Went without eating for a whole day because of a lack of money or other resources?
4184
No
1
Yes
Sysmiss
Post-stratification sampling weights
Post-stratification sampling weights
Post-stratification sampling weights
Post-stratification sampling weights
Post-stratification sampling weights
4184
4.17
0.851
0.952
Year when the study was administered in the country
Year when the study was administered in the country
Year when the study was administered in the country
Year when the study was administered in the country
Year when the study was administered in the country
4184
1
2020
Sysmiss
Number of adults 15 years of age and above in household
Number of adults 15 years of age and above in household
Number of adults 15 years of age and above in household
Number of adults 15 years of age and above in household
Number of adults 15 years of age and above in household
4175
9
00
00
01
01
02
02
03
03
04
04
05
05
06
06
07
07
08
08
09
09
10
10+
Sysmiss
Number of children under 15 years of age in household
Number of children under 15 years of age in household
Number of children under 15 years of age in household
Number of children under 15 years of age in household
Number of children under 15 years of age in household
4183
1
00
00
01
01
02
02
03
03
04
04
05
05
06
06
07
07
08
08
09
09
Sysmiss
Sum of Affirmative responses to FIES questions
Sum of Affirmative responses to FIES questions
Sum of Affirmative responses to FIES questions
Sum of Affirmative responses to FIES questions
Sum of Affirmative responses to FIES questions
4177
7
8
1.761
1.917
Estimated person parameters using the Rasch model
Estimated person parameters using the Rasch model
Estimated person parameters using the Rasch model
Estimated person parameters using the Rasch model
Estimated person parameters using the Rasch model
4177
7
-2.611
2.415
-1.486
1.199
Estimated person parameter errors using the Rasch model
Estimated person parameter errors using the Rasch model
Estimated person parameter errors using the Rasch model
Estimated person parameter errors using the Rasch model
Estimated person parameter errors using the Rasch model
4177
7
0.579
1.025
0.806
0.181
Probability of being moderately or severely food insecure
Probability of being moderately or severely food insecure
Probability of being moderately or severely food insecure
Probability of being moderately or severely food insecure
Probability of being moderately or severely food insecure
4177
7
0.996
0.2
0.314
Probability of being severely food insecure
Probability of being severely food insecure
Probability of being severely food insecure
Probability of being severely food insecure
Probability of being severely food insecure
4177
7
0.701
0.017
0.088
Age of the respondent
Age of the respondent
Age of the respondent
Age of the respondent
Age of the respondent
4184
18
79
35.646
12.861
Education of the respondent
Education of the respondent
Education of the respondent
Education of the respondent
Education of the respondent
4184
1
Elementary_or_less
2
Secondary
3
College
4
Dont_know
5
Refused
Sysmiss
Area
Area
Area
Area
Area
4184
1
Urban/Suburbs
2
Towns/Rural
3
Dont_know
4
Refused
Sysmiss
Gender of the respondent
Gender of the respondent
Gender of the respondent
Gender of the respondent
Gender of the respondent
4184
1
Male
2
Female
Sysmiss