KGZ_2017_FIES_v01_EN_M_v01_A_OCS
DDI_KGZ_2017_FIES_v01_EN_M_v01_A_OCS_FAO
Office of the Chief Statistician
Nesstar Publisher
KGZ_2017_FIES_v01_EN_M_v01_A_OCS_v01
Food Insecurity Experience Scale (FIES)
FIES
KGZ_2017_FIES_v01_EN_M_v01_A_OCS
FAO Statistics Division
Nesstar Publisher
FAO Statistics Division
Socio-Economic/Monitoring Survey [hh/sems]
Food Insecurity
SDG
SDGs
Food Access
Kyrgyzstan
National
Individuals
Individuals of 15 years or older.
Sample survey data [ssd]
Last 12 months.
Face-to-face par [f2f]
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.
As part of the statistical disclosure control process, values for number of children and number of adults that were 10 or above, were recoded as "10+" and categories for area were combined into "urban/suburbs" and "towns/rural".
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 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.
KGZ_2017_FIES_v01_EN_M_v01_A_OCS.NSDstat
This dataset contains the variables used to calculate the FIES-based indicator, deomographic variables and some derived variables calculated by FAO from the survey.
1000
23
Nesstar 200801
Unique respondent identifier
1000
0
111126745
211091282
161056648.855
28987944.137
Worried you would not have enough food to eat because of a lack of money or other resources
997
3
0
No
690
1
Yes
307
Sysmiss
3
Unable to eat healthy and nutritious food because of a lack of money or other resources
991
9
0
No
704
1
Yes
287
Sysmiss
9
Ate only a few kinds of foods because of a lack of money or other resources
990
10
0
No
647
1
Yes
343
Sysmiss
10
Skipped a meal because there was not enough money or other resources to get food
992
8
0
No
885
1
Yes
107
Sysmiss
8
Ate less than you thought you should because of a lack of money or other resources
989
11
0
No
800
1
Yes
189
Sysmiss
11
Household ran out of food because of a lack of money or other resources
991
9
0
No
828
1
Yes
163
Sysmiss
9
Hungry but did not eat because there was not enough money or other resources for food?
992
8
0
No
909
1
Yes
83
Sysmiss
8
Went without eating for a whole day because of a lack of money or other resources?
989
11
0
No
926
1
Yes
63
Sysmiss
11
Post-stratification sampling weights
1000
0
0.303
3.034
1
0.737
Year when the GWP was administered in the country
1000
0
1
2017
1000
Sysmiss
0
Number of adults 15 years of age and above in household
1000
0
01
01
195
02
02
399
03
03
200
04
04
138
05
05
47
06
06
16
07
07
5
Sysmiss
0
Number of children under 15 years of age in household
1000
0
00
00
252
01
01
206
02
02
221
03
03
183
04
04
97
05
05
28
06
06
5
07
07
5
08
08
2
09
09
1
Sysmiss
0
Sum of Affirmative responses to FIES questions
975
25
0
8
1.556
2.181
Estimated person parameters using the Rasch model
975
25
-2.383
2.573
-1.444
1.312
Estimated person parameter errors using the Rasch model
975
25
0.596
1.048
0.882
0.196
Probability of being moderately or severely food insecure
975
25
0
0.997
0.201
0.332
Probability of being severely food insecure
975
25
0
0.747
0.036
0.146
Age of the respondent
1000
0
15
91
42.654
16.992
Education of the respondent
1000
0
1
Elementary_or_less
132
2
Secondary
663
3
College
205
4
Dont_know
0
5
Refused
0
Sysmiss
0
Area
1000
0
1
Urban/Suburbs
200
2
Towns/Rural
800
3
Dont_know
0
4
Refused
0
Sysmiss
0
Gender of the respondent
1000
0
1
Male
346
2
Female
654
Sysmiss
0
Income quintile
1000
0
1
Poorest_20%
180
2
Second_20%
184
3
Middle_20%
200
4
Fourth_20%
206
5
Richest_20%
230
Sysmiss
0