SGP_2019_FIES_v01_EN_M_v01_A_OCS
DDI_SGP_2019_FIES_v01_EN_M_v01_A_OCS_FAO
Office of the Chief Statistician
Nesstar Publisher
SGP_2019_FIES_v01_EN_M_v01_A_OCS_v01
Food Insecurity Experience Scale (FIES)
FIES
SGP_2019_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
Singapore
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.
SGP_2019_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.
1040
23
Nesstar 200801
Unique respondent identifier
1040
0
111338248
211042384
160103742.302
28700595.383
Worried you would not have enough food to eat because of a lack of money or other resources
1039
1
0
No
976
1
Yes
63
Sysmiss
1
Unable to eat healthy and nutritious food because of a lack of money or other resources
1038
2
0
No
986
1
Yes
52
Sysmiss
2
Ate only a few kinds of foods because of a lack of money or other resources
1037
3
0
No
974
1
Yes
63
Sysmiss
3
Skipped a meal because there was not enough money or other resources to get food
1037
3
0
No
1002
1
Yes
35
Sysmiss
3
Ate less than you thought you should because of a lack of money or other resources
1037
3
0
No
989
1
Yes
48
Sysmiss
3
Household ran out of food because of a lack of money or other resources
1037
3
0
No
1017
1
Yes
20
Sysmiss
3
Hungry but did not eat because there was not enough money or other resources for food?
1039
1
0
No
1009
1
Yes
30
Sysmiss
1
Went without eating for a whole day because of a lack of money or other resources?
1038
2
0
No
1025
1
Yes
13
Sysmiss
2
Post-stratification sampling weights
1040
0
0.249
2.456
1
0.716
Year when the GWP was administered in the country
1040
0
1
1
1040
Sysmiss
0
Number of adults 15 years of age and above in household
1039
1
01
01
161
02
02
474
03
03
222
04
04
130
05
05
40
06
06
7
07
07
1
10
10+
4
Sysmiss
1
Number of children under 15 years of age in household
1038
2
00
00
744
01
01
122
02
02
146
03
03
22
04
04
4
Sysmiss
2
Sum of Affirmative responses to FIES questions
1029
11
0
8
0.315
1.161
Estimated person parameters using the Rasch model
1029
11
-2.637
2.971
-2.428
0.768
Estimated person parameter errors using the Rasch model
1029
11
0.668
1.22
1.178
0.132
Probability of being moderately or severely food insecure
1029
11
0
0.996
0.041
0.171
Probability of being severely food insecure
1029
11
0
0.816
0.008
0.066
Age of the respondent
1040
0
15
100
45.175
17.233
Education of the respondent
1040
0
1
Elementary_or_less
112
2
Secondary
635
3
College
285
4
Dont_know
2
5
Refused
6
Sysmiss
0
Area
1040
0
1
Urban/Suburbs
1039
2
Towns/Rural
1
3
Dont_know
0
4
Refused
0
Sysmiss
0
Gender of the respondent
1040
0
1
Male
516
2
Female
524
Sysmiss
0
Income quintile
1040
0
1
Poorest_20%
184
2
Second_20%
174
3
Middle_20%
195
4
Fourth_20%
234
5
Richest_20%
253
Sysmiss
0