6. Appendices
 

6.1. Examples of questionnaires

In nutrition baseline surveys the questionnaires are divided into community, household, individual (child) and supervisor questionnaires. The household questionnaires are further divided into samples adapted to urban and rural households, as there are some significant differences in socioeconomic and ecological descriptions of the two types of circumstances. In the Nutrition Baseline software only the questionnaires for the household and child are prepared automatically depending on the settings in the option sheet. Samples of the other two can be found in the following two chapters.

It should be emphasized here, once again, that these forms can only be used as a sample in order to become accustomed to the methods for formulating questionnaires. Obviously, content and language must always be adapted to the circumstances of the survey area. Item-by-item explanations for the planning and preparation of questionnaires are presented in Chapter 3.2.
 

6.1.1. Example of a Community Questionnaire
 
 
Community    
No. of Sub-Communities:    
No. Inhabitants:    
Major source of income:    
Infrastructure, Schools: 0 - Not available
1 - Primary School
2 - Secondary School		  
Health facilities: 0 - Not available
1 - Health post
2 - Health center		  
Shopping facilities: 0 - None
1 - Shop
2 - Market
3 - Kiosk (small)		  
Communication facilities: 1 - Postal service
2 - Newspaper
3 - Radio
4 - Television
5 - Telephon		  
Mass transportation means:  0 - Not available
1 - Pick-up/Truck 
2 - Bus/Minibus
3 - Boat		  
Type of road: 0 - No roads available
1 - Earth
2 - Stone
3 - Asphalt		  
Meeting place: 0 - None
1 - Open air
2 - Village Hall
3 - Religious Center		  
Worship place: 0 - None
1 - Available		  
Sport facilities: 0 - None 
1 - Available		  

 

6.1.2. Example of a Supervisor questionnaire
 

1.) Household number

2.) Supervisor

1) A
2) B
3) C

3.) Survey team

1) A      7) G
2) B      8) H
3) C      9) I
4) D     10) J
5) E     11) K
6) F     12) L
 

4.) Date of survey (day, month, year)

5.) Place of survey (village/suburb)

1) A      9) I
2) B     10) J
3) C     11) K
4) D     12) L
5) E     13) M
6) F     14) N
7) G     15) O
8) H

6.) Question: Name of child

7.) Observation: Age of the child (months)

8.) Question: Age of the mother (years)

9.) Question: How large is your farming operation? (ha)

10.) Question: What is the ownership status of the land?
1) Own land       4) Public land
2) Leased land    8) Don't know
3) Owned and leased land 9) No answer

11.) Question: Has your child suffered from a diarrheal disease during the last 7 days?

12.) Question: (If your child is not currently breastfed) how long did you breastfeed your child? (months)

13.) Question: How many hours after birth did you start with breast feeding?
1) 1-4 hours     8) Don't know
2) 5-12 hours    9) No answer
3) After 12 hours

14.) Question: Did your child receive any other fluid after birth besides colostrum?
1) Yes    8) Don't know
2) No     9) No answer

15.) Question: Regardless of whether your child is breastfed or not, how often was your child given something to eat yesterday?
8) Don't know
9) No answer

16.) Observation: Does the child possess an immunization record?
1) Yes   2) No

17.) Measurement: Weight of the child (kg)

18.) Measurement: Height of the child (cm)

19.) Measurement: Mid Upper Arm Circumference (cm)
 

6.2 List of variable codes

The following list gives all unique code names in alphabetic order. The variable number indicate the numbers of the variables that are discribed in chapter 3.2. The numbers that are marked with (*) are codes that are not considered in the forms as own variable. However, a specific code variable is given in case that these variables shall be considered in the spreadsheet for further statistical analysis.

No.    Variable Code   Description

1.   ADDDRINK   Fluid given to child in addition to breast-milk today
2.   ADDITBF    Fluid given to child after birth besides breast-milk
3.   *AGE       Age of child (months)
4.   AGEMOTHE   Actual age of mother
5.   AGEOLDCH   Age of mother when oldest child was born
6.   AGESOLID   Age child was first given solid foods
7.   AGEYOUNG   Age of mother when youngest child was born
8.   ANIMALFT   Food frequency of animal fats
9.   ANIMAL1    Use of animal 1
10.  ANIMAL2    Use of animal 2
11.  ANIMAL3    Use of animal 3
12.  ANIMAL4    Use of animal 4
13.  BIRTHDAT   Birthdate of the child
14.  BIRTHSPA   Number of cases with birth spacing of < 2 years
15.  *BMI       Body mass index of mother
16.  BOTTLE     Status of bottle-feeding of child
17.  BREASTDU   Months child was breast-fed
18.  BREASTFE   Current breast-feeding status
19.  CARERESP   Identification of person who takes care of children
20.  CHILDDTH   Preschool children mortality
21.  CHILDNO    Child number
22.  COLOSTRU   Child received colostrum
23.  CROP1      Use of crop 1
24.  CROP2      Use of crop 2
25.  CROP3      Use of crop 3
26.  CROP4      Use of crop 4
27.  EATFREQU   Eating frequency of child per day
28.  EATGREEN   Vegetables or fruits as supplementary feeding
29.  EATSOLID   Solid food as supplementary feeding
30.  EDUCFATH   Formal schooling of father
31.  EDUCMOTH   Formal schooling of mother
32.  EGG        Food frequency of eggs and egg products
33.  ELECTRIC   Electricity supply of household
34.  ENERCOOK   Kind of energy used for cooking
35.  ETHNIREL   Ethnic or religious affiliation of mother
36.  FARMAREA   Area of farming operation (ha)
37.  FISH       Food frequency of fish and other seafood
38.  FOAPRIL    Food shortage in April
39.  FOAUGUST   Food shortage in August
40.  FODECEMB   Food shortage in December
41.  FOFEBRUA   Food shortage in February
42.  FOJANUAR   Food shortage in January
43.  FOJUNE     Food shortage in June
44.  FOJULY     Food shortage in July
45.  FOMARCH    Food shortage in March
46.  FOMAY      Food shortage in May
47.  FONOVEMB   Food shortage in November
48.  FOOCTOBE   Food shortage in October
49.  FOODAID    Participation on feeding program
50.  FOSEPTEM   Food shortage in September
51.  FRUITS     Food frequency of fruits
52.  GARBAGE    Kind of garbage disposal
53.  GENDPREF   Gender preference regarding the next child
54.  GREENVEG   Food frequency of green leafy vegetables
55   *HFA       Height-for-age of child (z-score)
56.  HEIGHT     Height of child (cm)
57.  HEMOGLCH   Hemoglobin level in blood of child (g/L)
58.  HEMOGLMO   Hemoglobin level in blood of mother (g/L)
59.  HSHHDSEX   Gender of head of household
60.  HSHLOCAT   Location of househould (name of village or suburb)
61.  HSHMEMNO   Number of household members
62   HSHMMNO    Number of household members earning money
63.  HOUSEHNO   Household number
64.  IMMUNCRD   Presence of immunization record of child
65.  INFODAY    Suggested week day for survey meeting
66.  INFOTIME   Suggested time of day for survey meeting
67.  LANDOWN    Ownership of land
68.  MEATLARG   Food frequency of meat from large animals
69.  MEATSMAL   Food frequency of meat from small animals
70.  MILK       Food frequency of milk and milk products
71.  MOGOITER   Goiter in mother
72.  MOHEIGHT   Height of mother (cm)
73.  MOTHMONE   Money earned by mother during the last 3 months
74.  MOWEIGHT   Weight of mother (0.1 kg)
75.  MUAC       Mid upper arm circumference
76.  NBEDROOM   Number of bedrooms
77.  NIGHTBLI   Nightblindness of child
78.  NOCLDMEM   Number of members of household who are children
79.  OCCUPACI   Occupation of head of household
80.  OIL        Food frequency of oils
81.  ORIGIN     Geographical origin of mother
82.  OTHERVEG   Food frequency of other than green leafy vegetables
83.  PERIOARI   Period prevalence of acute respiratory diseases
84.  PERIODDD   Period prevalence of diarrheal disease of child
85.  PERIODIS   Period prevalence of other important disease
86.  *PERSOBED  Number of persons per bedroom
87.  POINTARI   Point prevalence of acute respiratory diseases
88.  POINTDD    Point prevalence of diarrheal disease of child
89.  PLANTFAT   Food frequency of plant fats
90.  PREGNANT   Time of pregnancy of mother
91.  PREPARED   Food frequency of pre-prepared, processed food
92.  PROBDISP   Household with neighbor disputes
93.  PROBEDUC   Household with unsatisfactory school situation
94.  PROBENER   Household with problems of energy supply
95.  PROBFOOD   Household with problems of food supply
96.  PROBILLN   Household with frequent disease problems
97.  PROBINCO   Household with too little income
98.  PROBLE1    Household with land tenure problems
99.  PROBLE2    Household with employment/yield problems
100. PROBLE3    Household with time problems to get to work
101. PROBLIVC   Household with bad living conditions
102. PROBNO     Household without problems
103. PROBOTHE   Household with other problems
104. PROBWATE   Household with problems of water supply
105. SALTIOD    Presence of iodine in salt sample
106. SALTYP     Kind of salt used in cooking and as table salt
107. SCHOOLFD   Participation on schoolfeeding program
108. SEWAGE     Kind of sewage disposal
109. SEX        Gender of child
110. SNACKS     Food frequency of snacks
111. SOCIALIF   Participation in social meetings
112. STAPLE1    Food frequency of staple food 1 (grains, tubers)
113. STAPLE2    Food frequency of staple food 2 (grains, tubers)
114. STAPLE3    Food frequency of staple food 3 (grains, tubers)
115. STAPLE4    Food frequency of staple food 4 (grains, tubers)
116. STARTBF    Start of breast-feeding after birth
117. SUGAR      Food frequency of sugars
118. SUPERVNO   Supervisor
119. SURVTNO    Survey team number
120. SURVDATE   Date of the survey
121. SURVDISC   Interest in discussion about results of survey
122. SURVPART   Acceptance of survey by responder
123. WAAPRIL    Water shortage in April
124. WAAUGUST   Water shortage in August
125. WADECEMB   Water shortage in December
126. WAFEBRUA   Water shortage in February
127. WAJANUAR   Water shortage in January
128. WAJUNE     Water shortage in June
129. WAJULY     Water shortage in July
130. WALL       Material of walls of children's bedroom
131. WAMARCH    Water shortage in March
132. WAMAY      Water shortage in May
133. WANOVEMB   Water shortage in November
134. WAOCTOBE   Water shortage in October
135. WASEPTEM   Water shortage in September
136. WATER      Source of drinking water
137. WEIGHING   Weighing status of child
138. WEIGHT     Weight of child (0.1 kg)
139. *WFA       Weight-for-age of child (z-score)
140. *WFH       Weight-for-height of child (z-score)
141. WHTCHART   Presence of weighing chart of child
 

6.3 Anthropometric Reference Tables

Sometimes a nutrition survey must be made without being able to calculate anthropometric data using a personal computer. In this instance, one can use the age, weight and height data for a child to determine if the child is within the normal variation of the population. These anthropometric standard values are based on the NCHS/CDC reference values as recommended by the WHO. Threshold values are given for stunting, wasting, and obesity. Thresholds are given for plus or minus two standard deviations from the reference population. In addition to values for stunting, wasting and obesity according to height, thresholds for obesity vs. age are also given.
 

6.3.1 Children
 

Thresholds for stunting (ht/age) and underweight (wt/age) in boys and girls (age : <2 years) in lying position
 
 
BOYS
GIRLS
AGE
(Months)
Stunting
(Z-score: -2)
Height in lying
position (cm)
Underweight
(Z-score: -2)
Weight
(kg)
Stunting
(Z-score: -2)
Height in lying
position (cm)
Underweight
(Z-score: -2)
Weight
(kg)
0
1
2
3
4
5
45.9
49.7
52.9
55.8
58.3
60.5
2.4
2.9
3.5
4.1
4.7
5.3
45. 5
49. 0
52. 0
54. 6
56. 9
58. 9
2. 2
2. 8
3. 3
3. 9
4. 5
5. 0
6
7
8
9
10
11
62.4
64.1
65.7
67.0
68.3
69.6
5.9
6.4
6.9
7.2
7.6
7.9
60. 6
62. 2
63. 7
65. 0
66. 2
67. 5
5. 5
5. 9
6. 3
6. 6
6. 9
7. 2
12
13
14
15
16
17
70.7
71.8
72.8
73.7
74.6
75.5
8.1
8.3
8.5
8.7
8.8
9.0
68. 6
69. 8
70. 8
71. 9
72. 9
73. 8
7. 4
7. 6
7. 8
8. 0
8. 2
8. 3
18
19
20
21
22
23
76.3
77.1
77.9
78.9
79.4
80.2
9.1
9.2
9.4
9.5
9.7
9.8
74. 8
75. 7
76. 6
77. 4
78. 3
79. 1
8. 5
8. 6
8. 8
9. 0
9. 1
9. 3

Thresholds for stunting (ht/age) and underweight (wt/age) (age: 2 - 5 years) in upright position
 
 
BOYS
GIRLS
AGE
(Months)
Stunting
(Z-score: -2)
Height in upright position (cm)
Underweight
(Z-score: -2)

Weight
(kg)
Stunting
(Z-score: -2)
Height in upright position (cm)
Underweight
(Z-score: -2)

Weight
(kg)
24
25
26
27
28
29
79. 2
79. 9
80. 6
81. 3
82. 0
82. 7
10. 1
10. 2
10. 3
10. 4
10. 5
10. 6
78. 0
78. 8
79. 6
80. 3
81. 0
81. 7
9. 4
9. 6
9. 8
9. 9
10. 1
10. 2
30
31
32
33
34
35
83. 4
84. 1
84. 7
85. 4
86. 0
86. 7
10. 7
10. 9
11. 0
11. 1
11. 2
11. 3
82. 5
83. 2
83. 8
84. 5
85. 2
85. 8
10. 3
10. 5
10. 6
10. 8
10. 9
11. 0
36
37
38
39
40
41
87. 3
87. 9
88. 6
89. 2
89. 8
90. 4
11. 4
11. 5
11. 7
11. 8
11. 9
12. 0
86. 5
87. 1
87. 7
88. 4
89. 0
89. 6
11. 2
11. 3
11. 4
11. 5
11. 6
11. 8
42
43
44
45
46
47
91. 0
91. 6
92. 2
92. 7
93. 3
93. 9
12. 1
12. 3
12. 4
12. 5
12. 6
12. 8
90. 2
90. 7
91. 3
91. 9
92. 5
93. 0
11. 9
12. 0
12. 1
12. 2
12. 3
12. 5
48
49
50
51
52
53
94. 4
95. 0
95. 5
96. 1
96. 6
97. 1
12. 9
13. 0
13. 1
13. 3
13. 4
13. 5
93. 5
94. 1
94. 6
95. 1
95. 6
96. 2
12. 6
12. 7
12. 8
12. 9
13. 0
13. 1
54
55
56
57
58
59
97. 7
98. 2
98. 7
99. 2
99. 7
100. 2
13. 8
13. 9
14. 1
14. 2
14. 2
14. 3
96. 7
97. 2
96. 6
98. 1
98. 6
99. 1
13. 2
13. 3
13. 4
13. 5
13. 6
13. 7

Thresholds for wasting (wt/ht) and obesity (wt/ht) (length in lying position: 49 - 100 cm)
 
 
BOYS
GIRLS
Height
(cm)
Wasting
(Z-score: -2)
Weight
(kg)
Obesity
(Z-score: +2)
Weight
(kg)
Wasting
(Z-score: -2)
Weight
(kg)
Obesity
(Z-score: +2)
Weight
(kg)
49
2. 5
4. 2
2. 6
4. 0
50
51
52
53
54
2. 5
2. 6
2. 8
2. 9
3. 1
4. 4
4. 6
4. 8
5. 0
5. 3
2. 6
2. 7
2. 8
3. 0
3. 1
4. 2
4. 4
4. 7
4. 9
5. 2
55
56
57
58
59
3. 3
3. 5
3. 7
3. 9
4. 1
5. 6
5. 9
6. 1
6. 4
6. 7
3. 3
3. 5
3. 7
3. 9
4. 1
5. 4
5. 7
6. 0
6. 3
6. 6
60
61
62
63
64
4. 4
4. 6
4. 9
5. 2
5. 4
7. 1
7. 4
7. 7
8. 0
8. 3
4. 3
4. 6
4. 8
5. 0
5. 3
6. 9
7. 2
7. 5
7. 8
8. 1 
65
66
67
68
69
5. 7
6. 0
6. 2
6. 5
6. 8
8. 7
9. 0
9. 3
9. 6
9. 9
5. 5
5. 8
6. 0
6. 3
6. 5
8. 4
8. 7
9. 0
9. 3
9. 6
70
71
72
73
74
7. 0
7. 3
7. 5
7. 8
8. 0
10. 2
10. 5
10. 8
11. 1
11. 4
6. 8
7. 0
7. 2
7. 5
7. 7
9. 9
10. 2
10. 5
10. 7
11. 0
75
76
77
78
79
8. 2
8. 4
8. 6
8. 8
9. 0
11. 6
11. 9
12. 1
12. 4
12. 6
7. 9
8. 1
8. 3
8. 5
8. 7
11. 2
11. 4
11. 7
11. 9
12. 1
80
81
82
83
84
9. 2
9. 4
9. 6
9. 7
9. 9
12. 9
13. 1
13. 3
13. 5
13. 7
8. 8
9. 0
9. 2
9. 4
9. 6
12. 3
12. 6
12. 8
13. 0
13. 2
85
86
87
88
89
10. 1
10. 3
10. 5
10. 6
10. 8
14. 0
14. 2
14. 4
14. 7
14. 9
9. 7
9. 9
10. 1
10. 3
10. 5
13. 4
13. 6
13. 9
14. 1
14. 3
90
91
92
93
94
11. 0
11. 2
11. 4
11. 6
11. 9
15. 1
15. 3
15. 6
15. 8
16. 1
10. 7
10. 9
11. 1
11. 3
11. 5
14. 5
14. 8
15. 0
15. 3
15. 6
95
96
97
98
99
12. 1
12. 3
12. 5
12. 8
13. 0
16. 3
16. 6
16. 8
17. 1
17. 4
11. 8
12. 0
12. 2
12. 5
12. 8
15. 9
16. 1
16. 5
16. 8
17. 1
100
13. 3
17. 7
13. 1
17. 4

Thresholds for wasting (wt/ht) and obesity (wt/ht) (stature, upright position: 75 - 127 cm)
 
 
BOYS
GIRLS
Height
(cm)
Wasting
(Z-score: -2)
Weight
(kg)
Obesity
(Z-score: +2)
Weight
(kg)
Wasting
(Z-score: -2)
Weight
(kg)
Obesity
(Z-score: +2)
Weight
(kg)
75
76
77
78
79
7. 9
8. 1
8. 3
8. 5
8. 7
12. 7
12. 9
13. 2
13. 4
13. 6
7. 7
7. 9
8. 1
8. 3
8. 5
12. 3
12. 5
12. 7
13. 0
13. 2
80
81
82
83
84
8. 9
9. 2
9. 4
9. 6
9. 7
13. 9
14. 1
14. 3
14. 6
14. 8
8. 7
8. 9
9. 1
9. 3
9. 5
13. 4
13. 6
13. 9
14. 1
14. 3
85
86
87
88
89
9. 9
10. 1
10. 3
10. 5
10. 7
15. 0
15. 3
15. 5
15. 7
15. 9
9. 7
9. 9
10. 1
10. 3
10. 5
14. 6
14. 8
15. 1
15. 3
15. 6
90
91
92
93
94
10. 9
11. 1
11. 3
11. 5
11. 7
16. 2
16. 4
16. 7
16. 9
17. 2
10. 7
10. 8
11. 0
11. 2
11. 4
15. 8
16. 1
16. 3
16. 6
16. 9
95
96
97
98
99
11. 9
12. 1
12. 4
12. 6
12. 8
17. 4
17. 7
17. 9
18. 2
18. 5
11. 6
11. 8
12. 0
12. 2
12. 4
17. 2
17. 5
17. 8
18. 1
18. 4
100
101
102
103
104
13. 0
13. 2
13. 5
13. 7
13. 9
18. 8
19. 1
19. 4
19. 7
20. 0
12. 7
12. 9
13. 1
13. 3
13. 5
18. 7
19. 0
19. 3
19. 6
20. 0
105
106
107
108
109
14. 2
14. 4
14. 7
14. 9
15. 2
20. 4
20. 7
21. 1
21. 4
21. 8
13. 8
14. 0
14. 3
14. 5
14. 8
20. 3
20. 7
21. 0
21. 4
21. 8
110
111
112
113
114
15. 4
15. 7
16. 0
16. 3
16. 6
22. 2
22. 6
23. 1
23. 5
24. 0
15. 0
15. 3
15. 6
15. 9
16. 2
22. 2
22. 5
23. 0
23. 4
23. 8
115
116
117
118
119
16. 9
17. 2
17. 5
17. 9
18. 2
24. 4
24. 9
25. 4
26. 0
26. 5
16. 5
16. 8
17. 1
17. 4
17. 7
24. 3
24. 8
25. 3
25. 8
26. 4
120
121
122
123
124
18. 5
18. 9
19. 2
19. 6
20. 0
27. 1
27. 6
28. 2
28. 9
29. 5
18. 1
18. 4
18. 8
19. 1
19. 5
27. 0
27. 6
28. 3
29. 0
29. 7
125
126
127
20. 4
20. 7
21. 1
30. 2
30. 9
31. 6
19.9
-
-
30. 5
-
-

6.3.2 Women
 

Thresholds for Wasting (BMI<18.5) and Obesity (BMI>27.5)
 

Stature
(cm)
Wasting
(BMI: 18.5)
Weight (kg)
Obesity
(BMI: 27.5)
Weight (kg)
145
146
147
148
149
38. 9
39. 4
40. 0
40. 5
41. 1
57. 8
58. 6
59. 4
60. 2
61. 1
150
151
152
153
154
41. 6
42. 2
42. 7
43. 3
43. 9
61. 9
62. 7
63. 5
64. 4
65. 2
155
156
157
158
159
44. 4
45. 0
45. 6
46. 2
47. 4
66. 1
66. 9
67. 8
68. 7
69. 5
160
161
162
163
164
47. 4
48. 0
48. 6
49. 2
49. 8
70. 4
71. 3
72. 2
73. 1
74. 0
165
166
167
168
169
50. 4
51. 0
51. 6
52. 2
52. 8
74. 9
75. 8
76. 7
77. 6
78. 5
170
171
172
173
174
53. 5
54. 1
54. 7
55. 4
56. 0
79. 5
80. 4
81. 4
82. 3
83. 3
175
176
177
178
179
56. 7
57. 3
58. 0
58. 6
59. 3
84. 2
85. 2
86. 2
87. 1
88. 1
180
181
182
183
184
59. 9
60. 6
61. 3
62. 0
62. 6
89. 1
90. 1
91. 1
92. 1
93. 1

6.4 Nutrient requirements
 

Nutrient requirements depend on the biological status of a person (gender, age, build, pregnancy, breastfeeding, etc.), health and nutritional conditions, physical activities and the body heat produced by the person. In addition to these, allowance must be made for external variables, such as ambient temperature and nutrient reserves, and increased needs under some environmental conditions - for example in order to counteract increased attacks by infections or irregular feeding.

Even if these conditions have been accurately determined, there is not always agreement at the international level. Nutritional recommendations are not consistent from one country to another. These differences are evident in the nutrient recommendations published over the last ten years.

The nutrient requirements listed on the following pages have been adapted from FAO/WHO recommendations. These recommendations are accepted in most developing countries.

Table 11. Average Energy and Protein Requirements of Infants and Small Children
 
Age
weighta (kg)c
Energy Requirements
Protein Requirementsb
    kcal/kg kJ/kg kcal/day kJ/day g/kgc g/dayc
Months:
3-6
6-9
9-12		 7
8.5
9.5		 100
95
100		 418
397
418		 700
810
950		 2300
3400
4000		 1.85
1.65
1.50		 13
14
14
Years:
1-2
2.3
3-5		 11
13.5
16.5		 105
100
95		 439
418
397		 1150
1350
1550		 4800
5700
6500		 1.20
1.15
1.10		 13.5
15.5
17.5

a Average weight for boys and girls at the mean age of the age group according to NCHS.
b Based on the protein quality (amino acid content and digestibility) of eggs or milk.
c Rounded to the nearest 0.05 or 0.5

World Health Organization (1985), Energy and protein requirements, Report of a Joint FAO/WHO/UNU Expert Consultation, Technical Report Series 724, WHO, Geneva
 

6.5 Randomized number table
 

The randomized number table on the following two pages consist of the 5,000 digits zero to nine in random order. From the point of view of statistical accuracy, if such tables are used repeatedly they cannot be considered "random." However, for practical use in evaluating surveys they are quite sufficient. It is advisable to obtain a new set of random numbers from time to time to replace the old ones.

Statistical textbooks contain random number tables for determining random sequences. If you have such tables available, these also can be used.

The digits in the tables may either be read from left to right or from top to bottom. When a row of numbers is finished then the next one down is taken. Similarly when using columns take the next one right. Assume that a randomly selected number between one and five is required. Go arbitrarily to any position in the table and read right for the next number between one and five. When you find such a number that is your randomly selected number. If you need another such number then start one over from where you finished last time, no matter where in the group of digits that may be. If you want a number with two digits then the first digit is in the ten's place and the second in the unit's place.

Every time a new number is sought you should start immediately after the previous identified number. Therefore mark the last digit used each time with a pencil.

Table 12. Randomized numbers

     0     1     2     3     4     5     6     7     8     9

0  59894 12161 60017 54948 45889 84002 53390 00386 09974 42942
1  36638 57682 82157 75236 15013 04478 24344 20134 03219 16422
2  18134 34678 81756 91082 64920 84396 86973 41828 01084 54335
3  08971 20750 47001 25140 82781 21128 91527 54397 37148 83053
4  77858 82288 15606 69731 64180 06684 59604 83386 85501 59111

5  28155 21474 24559 42851 68312 78638 07337 36209 88222 36321
6  64244 55237 79445 67676 38589 21596 69454 33332 62103 71010
7  84527 81383 39580 97882 34713 07567 62000 54562 99003 47527
8  60637 95417 01655 24389 47676 10846 51697 41868 89061 92304
9  67185 14448 65666 15129 98140 11435 56872 61624 75319 86429

10 84867 34444 48296 30314 46645 97312 00382 31990 19571 87550
11 67726 35108 02092 28688 69855 67782 80856 44613 81416 25652
12 22590 53549 53132 13576 89810 38804 12742 63263 07314 77356
13 98256 69696 37975 65444 91969 15821 18313 52475 57442 40871
14 96887 07346 22199 05775 38284 56418 68081 88167 57441 72314

15 41726 17042 84357 36789 87063 74298 77368 07509 20477 44428
16 02478 79787 24505 04336 64329 36714 95953 99966 64670 94482
17 60665 90351 47623 94771 38658 34888 61333 25702 77802 55660
18 05633 69585 62760 46055 36368 64071 61925 66912 62756 68569
19 23268 92767 23349 18108 97470 82625 53859 30831 57548 00430

20 75667 13924 93820 32535 71745 33648 88736 53869 94335 73074
21 88723 45432 33459 09728 20055 91780 26544 40596 96749 33488
22 52869 76944 33982 14236 44819 92626 63955 34411 10628 11044
23 20472 60192 40431 48094 63991 69972 97926 94290 86854 24325
24 27138 05002 16419 16862 38965 91742 62237 33525 05062 36222

25 01372 91112 38460 08183 54099 27957 22380 80641 00536 18372
26 93123 34477 54515 71820 68076 48672 45203 52246 86073 37355
27 03329 83243 40113 41306 39158 74316 78975 70461 96806 78551
28 81932 57206 19496 65044 62464 85314 02335 82652 21065 90751
29 57795 15755 01736 24770 53011 57617 35043 49201 60833 75054

30 71541 44832 57657 78895 58013 80311 90970 88068 67880 52318
31 09450 88811 04243 20173 23783 86761 17666 44034 74815 71084
32 17776 01586 41633 54126 68224 82168 26743 49436 77304 82753
33 59654 06792 38986 91957 96697 33195 71024 20167 03048 68769
34 48299 47003 14745 38254 19621 24271 49653 65723 17507 64233

35 80783 93479 41019 12446 65966 73456 62851 90802 86619 80305
36 26589 39905 50295 52587 14356 22968 62598 39239 27332 66725
37 40703 76909 23212 82165 03971 02166 18643 14031 60420 53829
38 74702 66799 38493 41793 81902 88827 17551 04772 76847 68755
39 66750 16069 61482 27006 33612 23763 08634 07805 68651 33737

40 61242 06100 76487 52698 89181 79142 87077 60174 62738 94121
41 88168 86400 25680 03749 31223 02079 83426 75777 61584 56781
42 69487 45373 65467 06945 41539 63272 12192 35054 52066 90316
43 78180 88305 47987 29043 36868 98199 33931 03067 16052 75936
44 36313 03238 96836 11401 12431 33405 68153 91732 60871 77374

45 41405 13690 42314 08362 76226 08231 15919 82774 43572 62708
46 33185 14776 80559 08194 13535 01485 14233 94568 62409 84853
47 79689 56567 08561 05145 55956 19365 47294 99096 69428 17084
48 00113 02735 15268 03053 16466 75174 26704 45636 75908 90351
49 68222 85394 92000 73983 76136 20113 89236 87045 82930 04874

50 62111 70722 57056 47585 00578 77467 07900 04571 15488 83241
51 29928 39172 01938 39455 50717 87896 40990 83711 77947 08851
52 30974 61120 76749 65525 33742 66239 67961 32244 35861 23069
53 10049 04919 43742 05962 35709 77620 19039 75262 71003 80510
54 16587 24521 78973 64749 05300 12098 29144 54273 54338 43210

55 70895 44988 61256 82653 85303 83948 47351 94740 66865 78579
56 48472 84667 76880 00619 52843 04277 58294 56581 00253 72628
57 42529 79302 02240 79696 84366 42578 15240 67261 92166 21444
58 27394 66619 67608 33847 59586 56855 86950 05393 57594 52381
59 62415 83740 63241 17745 54207 27869 39010 11525 53274 84799

60 54532 44091 73936 09518 89543 58504 39431 56486 03832 64946
61 78971 66966 80259 24884 06339 37323 14763 26180 20626 87571
62 95032 43376 39938 20533 37634 29350 89984 68156 24941 01919
63 65516 02756 61982 40975 85222 91496 08482 27210 84989 74300
64 29970 10457 09977 25385 35707 01233 88818 31091 07100 49416

65 57984 18260 00511 28018 75217 03440 55231 85288 12683 61001
66 63736 89304 45416 14741 36506 70550 97706 83552 18358 02563
67 30916 19423 09633 53579 08788 44088 88278 02525 50545 63449
68 51554 74283 76308 43434 76771 88946 26086 89791 26818 90261
69 79340 81968 72766 49425 41586 51206 20675 14483 39131 47028

70 81685 11194 99495 28687 12385 03790 43830 52507 71625 82031
71 66594 57141 67847 87676 48832 45372 52958 32789 09071 26854
72 21445 83978 20693 78887 65156 22693 01957 89570 10880 23311
73 90181 29051 28483 65332 41777 42892 14840 64637 91223 12317
74 66669 35441 10416 77461 21342 68673 53101 27800 68670 15737

75 43396 48778 58343 44660 84910 80247 52922 92061 92823 89883
76 89263 28259 46385 68675 79244 80185 60179 01706 19352 20590
77 42769 81513 15432 39177 01788 74086 95010 32458 42006 42795
78 33039 24721 14463 10998 11901 04946 10670 45655 32885 56112
79 46153 53563 21084 29060 00647 81078 22411 23836 49568 98037

80 24264 62462 06936 81280 88554 63782 20191 13671 88837 57297
81 92829 12186 63959 78781 08419 88129 61302 40327 43046 17133
82 03871 31824 86163 47071 27718 33294 61583 07292 06049 46615
83 50979 29404 46052 45405 31699 27667 29955 15782 55318 29629
84 47755 17473 06336 14946 37813 45510 04863 58784 69084 12211

85 12258 74583 54811 22496 04953 92625 72800 14781 33974 62312
86 46605 83284 22740 33859 64186 03284 18958 16192 57526 22377
87 30395 70848 07873 65017 22859 65542 63883 49837 10588 20820
88 73905 15889 75418 83779 20966 48399 68894 29540 93319 56823
89 79202 07223 78401 29604 97469 27280 97388 98613 01872 55238

90 91147 39885 89998 72536 66987 57720 87624 27202 40171 61132
91 21082 94493 55337 78026 33981 08379 49774 37766 98289 34855
92 68775 15044 86329 70704 50754 99486 76101 93925 78272 19697
93 22402 26521 77779 57262 03856 48537 72373 84189 48273 97408
94 93273 84243 51177 05234 97835 96216 97046 19287 10932 09939

95 94033 66709 35126 49775 35020 63683 49408 27152 89896 01254
96 08628 46815 05455 16317 23667 42309 71775 41364 21980 53140
97 16929 21982 66287 88184 58914 18579 67526 10938 66656 94138
98 58207 85243 45426 45711 46807 17143 24243 87845 98620 80280
99 47124 77314 31839 99604 75720 95879 04290 14776 41652 44083
 

6.6 Sample presentations of survey findings in technical reports
 

The following pages give examples of the presentation of findings in technical reports. The results are presented as vividly as possible. As a rule, a technical report is also aimed at readers who are not nutritional experts. To accomplish this, the text and presentation must be set out in such a manner that non-experts in the field are able to understand its contents. Tables and graphs should be self-explanatory. Information in visual form in graphs can often be much more informative and more readily understood than digital information given in tables. The following pages give some examples of tables and graphs.
 

6.6.1 Tables
 

Table 13. Demographic and socioeconomic characteristics of two low income urban communities in Belo Horizonte, Brazil (1986).
 
Characteristic "Serra" "St. Lucia/Vila Rita" Total
Families surveyed
Children < 6 years

Household members:
Total
Employed1

Length of residence
(years)

Living conditions:
Brick houses (%)
Bedrooms (n)
Piped drinking water (%)
Flushing toilets (%)
Public garbage collection (%)
Electricity connection (%)

 80
153
 

6.1±2.7
1.9±1.1*

12.0±9.0*
 
 

96.3
3.2±2.0*
45.0
23.3
16.3
92.5

 60
101
 

6.0±2.6
1.8±1.1*

8.5±7.3*
 
 

88.3
3.8±1.5*
76.7
25.0
16.7
98.3

 140
254
 

6.1±2.7
1.9±1.1*

10.5±9.0*
 
 

92.9
3.4±1.7*
58.6
24.3
16.5
95.0
1 Working: the number of members of the household who contribute financially to the household.
* Mean and standard deviation

Table 14. Educational level of parents in the Morro Sul suburb of Rio de Janeiro (1986)
 
Educational level
Mother
Father
(n) (%) (n) (%)
No formal education
(< 3 years schooling)
3-5 years schooling(a)
6-11 years schooling(b)
> 11 years education
No answer(c)		 58

102
87
11
6
-

 22.1

38.6
32.9
4.2
2.2
-

 47

85
94
8
-
30

 17.9

32.1
35.7
2.9
-
11.4
(a) Primary schooling
(b) Secondary schooling
(c) Female headed households

Table 15. Prevalence of anemia among children in the two urban communities in Belo Horizonte (1986)
 
 
"Serra"
"St. Lucia/Vila Rita"
Total children
  (n) (%) (n) (%) (n) (%)
Anemia
(Hb < 110.0 g/L)

Severe anemia
(Hb < 0.95 g/L)

Total children

 48
 

20
 

142

 33.8
 

14.1
 

100.0

 19
 

4
 

82

 23.2
 

4.9
 

100.0

 67
 

24
 

224

 29.9
 

10.7
 

100.0

Table 16. Prevalence of undernutrition among children of the observed villages in West Sumatra (1994)
 
Village Height-for-agea Weight-for-heighta Weight-for-heighta
Gando
Koto Baru T
Balai Gadang
Badus
Merapi
Piliang B
Batu Tebal
Padang Luar S
Lubuk Gadang
Silayang

All villages

 39.5
47.7
48.8
55.3
45.5
39.5
35.0
29.3
38.9
32.4

40.8

 31.6
34.1
43.9
52.6
48.5
23.7
30.0
31.7
41.7
24.3

35.4

 10.5
15.9
9.8
7.9
15.2
15.8
15.8
7.3
16.7
2.7

10.1
a Percentage of children who show a z-score lower than -2

Table 17. Relationship between anthropometric indices and age in under-five children of West Sumatra, Indonesia (1994)
 
Age
(months)		 Children
(n)		 Height-for-age
(mean: Z-score)		 Weight-for-height
(mean: Z-score)		 Weight-for-age
(mean: Z-score)
<6
6-12
12-18
18-24
24-36
> 36		 54
66
51
39
69
108		 -0.15±1.49
-0.94±1.12
-1.53±1.63
-1.85±1.33
-2.03±1.79
-2.59±1.18		 -0.15±1.84
-0.76±1.08
-0.88±1.45
-1.19±1.32
-0.59±1.21
-0.54±1.04		 -0.33±0.99
-1.34±1.04
-1.72±1.25
-1.86±1.16
-1.74±1.27
-1.94±0.93

Table 18. Relationship between the presence of acute respiratory infections (ARI) and anthropometric indices in children under-five children of West Sumatra, Indonesia (1994)
 
ARI Children
(n)		 Height-for-age
(mean: Z-score)		 Weight-for-height
(mean: Z-score)
Yes
No		 196
182		 -0.81±1.24a
-0.44±1.40		 -1.62±1.69
-1.65±1.57
a  p=0.003 ; corrected for village and age differences
 

6.6.2 Figures
 
 

Figure 13. Weight-for-height Z-scores of Indonesian children (N=168) from high-income families living in East-Jakarta (1994).

s164.gif (5069 Byte)

Figure 14. Frequency of body-mass-index of mothers from West-Kalimantan (1994)

s165.gif (7689 Byte)
 

6.7 Determination of intra- and inter observer errors.
 

Basically two types of errors can occur by taking anthropometric measurement of subjects during the survey:

  1. Occasional errors which happen at random because of wrong filling out of a form, incorrect reading of the weighing scale etc. These occasional errors sometimes can be detected afterwards because the measured value does not appear to be logic or consistent with other data.
  2. Systematical errors, due to differences between measuring equipment or surveyors. These errors are often difficult to detect because they occur in every measurement. For example a weighing scale may underestimate a person’s weight with 0.5 kg at each measurement.
Before starting the survey it is important to check whether systematic errors are likely to occur.

Therefore the quality of the equipment, and the performance of the surveyors needs to be examined. This can be carried out by using the methodology as described in the following example.

Example:

A survey which will be carried out in 15 villages plans to use 5 enumerators for weight measurements and 5 weighing scales. The 5 weighing scales and 5 enumerators should be compared, using 5-10 subjects. Weighing scales will be numbered W1 through W5, and enumerators will be numbered E1 through E5.

First, Enumerator 1 should weigh all subjects (S1- Sn) on weighing scale 1, E2 weighs all subjects on W2, E3 on W3 and so forth. To ease the weighing process, the subject that has been weighed in from E1 will pass to E2, then to E3, until the last enumerator. In a second round, E1 will weigh again all subject now with W2, E2 with E3 and finally E5 with E1. This process continues until all enumerators have weighed all subjects with all scales. Each enumerator fills out the following form with the results of the weighing.
 
Enumerator 1
Subject W1 W2 W3 W4 W5
1 ...... kg ...... kg      
2 ...... kg        
3          
           
n          

The results will then be analyzed using analysis of variance (ANOVA) with weight as dependent variable, and weighing scale (1 to 5), enumerator (1 to 5), and subject (1 to n) as factors. No significant effect should exist for weighing scale and for enumerator, and there should also be no significant interaction between these two factors.

In case there will be a significant difference between weighing scales the faulty weighing scale should be identified and replaced. In case one of the enumerators should weigh differently from the others, the enumerators should be trained again in taking measurements.
 

6.8 Statistical methods
 

The diagram on the following page provides an overview of the most relevant statistical tests. Before selecting a suitable statistical test for analysis of data, it is necessary to first determine some of the characteristics of the data.

The more information contained in the output data, the more clearly three steps can be distinguished :

  1. Frequency: The data are of equal value (e.g. sex: male = 1, female = 2; or place of origin: South = 1, Central = 2, North = 3).
  2. Ranking: The data have a rank order but the size of an interval cannot be assessed (e.g. educational level: None = 1, literate = 2, completed primary education = 3, completed secondary education = 4).
  3. Measurements: The data extend over a scale with constant intervals (e.g. height, weight, age, hemoglobin level).
Furthermore, the data must be tested as to whether or not they fall within the normal range. Here, descriptive statistics, such as skewness and kurtosis, are useful. Both values should lie between +2 and -2, indicating that the values fall with the range of normal.

Finally, the eventual selection of statistical methods depends on whether the statistics deal with only two factors (e.g. male-female, yes-no), or with more than two. Furthermore, the selection also depends on whether or not the data were collected from the same subject (e.g. a measurement for the same individual is taken at a different time).

If these characteristics are clearly understood, the suitable statistical test can be selected from the following table.

Table 19. Important Statistical Tests
 
  Frequency Ranking
Measurement values
non-normal distribution
normal distribution
Tests

for

2 factor

steps

 
independent sampling

 
Chi2-Test

 
Siegel-

Tutzey-Test

U-Test
Kolmogoroff

Smirnoff-Test
F-test

b-test
joint sampling

 
Tests for indications

 
Wilcoxon-Test

Spearman-Order Correlation Coefficient
t-Test

Product-moment Correlation

Linear regression
Tests

for

> 2

factor

steps
independent sampling

 
Chi2-Test

 
H-test

 
Variance analysis

Student-Newman-Keuls-Test
joint sampling

 
Q-test

 
Friedman-Test

multiple comparison between Wilcoxon and Wilcox
Variance analysis

Multi-various methods

For further guidance the following statistical handbook is recommended :

B.R. Kirkwood
Essentials of Medical Statistics
Blackwell Scientific Publications
Oxford, London, Edinburgh
 

6.9 Addresses of national and international institutions
 

Scientific and technical institutions:

Multilateral organizations: Bilateral Organizations: Non-governmental organizations:


6.10 WHO global database on child growth
 

Description:

Growth assessment is the best single measure for defining the health and nutritional status of children, while serving as an indirect indicator of the quality of life of entire populations. The goal of reducing, by the year 2000, severe and moderate protein-energy malnutrition in children under five years of age by half of 1990 prevalence levels has been endorsed in numerous international forums. The WHO Global Database on Child Growth, which is a standardized compilation of anthropometric data from population-based nutritional surveys conducted around the world from 1960 onwards, permits monitoring progress towards achieving this goal. The aim is to describe the worldwide distribution of child growth failure, to provide an accurate picture of child growth as a basis for intercountry and interregional comparisons, and to facilitate monitoring of national, regional and global trends. The standardized presentation of data by country in the database includes: a) systematic use of the NCHS/WHO international reference population, b) display of growth retardation prevalences for preschool children, as measured by the proportion of weight-for-age (underweight), height-for-age (stunting) and weight-for-height (wasting) below -2 (moderate) and -3 (severe) standard deviations (SD) from the median of the reference population, c) display of the prevalence of overweight, as measured by the proportion of children with weight-for-height above +2 SD, d) display of Z-score means and SD for the three indices, and e) stratification of the results according to age, sex, region, and rural/urban. This detailed account of data on child malnutrition will be relevant to national authorities in planning and evaluating nutrition interventions; it will also serve as a baseline for child nutritional status worldwide for all who are concerned with protecting and promoting optimal child growth. It is hoped that continual updating of the database will stimulate the gathering and sharing of new information, particularly in those countries and regions thus far scarcely investigated. At present the database covers over 80% of the total population of under-5-year-olds worldwide.

Source:

WHO programme information derived from population-based nutritional surveys.

Notes on usage:

Queries are received via all forms of communication. Responses are dispatched as print-outs of the relevant country data/references. Dissemination via WHO/LAN is being implemented.

Responsible Unit:

Please address any comments or suggestions concerning the contents to:

Nutrition Unit
WHO Telephone: (+41 22) 791 3320
20 Avenue Appia Fax: (+41 22) 791 0746
CH-1211 Geneva 27 E-mail: bloessnerm@who.ch
Switzerland deonism@who.ch

Download File (Winword 6.0 Format)
 

6.11 Construction plan for an anthropometer

 

 

6.12 Literature for further study
 

Beaton G, Kelly A, Kevany J, Martorell R, & Mason J. Appropriate uses of child anthropometry. ACC/SCN (SOA No.7). Geneva, Switzerland, 1990.

Beghin I, Cap M, & Dujardin B. A guide to nutritional assessment. WHO. Geneva, Switzerland, 1988.

Bennet S, Woods T, Liyanange WM, & Smith DL. A simplified general method for cluster-sample surveys of health in developing countries. Rapp trimest statist sanit mond 1991; 44:98-106.

Cameron N. The measurement of human growth. Croom Helm Ltd., Provident House, Burrell Row, Beckenham, Kent, UK, 1984.

Center for Disease Control and Health Service Administration. Weighing and measuring children: a training manual for supervisory personnel. Center for Disease Control, Atlanta, Georgia, USA, 1980.

Council for International Organizations of Medical Sciences (CIOMS). International guidelines for ethical review of epidemiological studies. Geneva, Switzerland, 1991.

Fink A & Kosecoff J. How to conduct surveys. Step-by-step guide. Ninth printing. Sage Publications. Newbury Park, London, UK; New Delhi, India, 1991.

FAO. Conducting small-scale nutrition surveys. A field manual. Nutrition in Agriculture No. 5. Food and Agriultural Organization of the United Nations. Rome, 1990.

Fowler FJ. Survey research methods. Saga Publications. New York, USA, 1984.

Gibson RS. Principles of nutritional assessment. Oxford University Press. Oxford, New York, Tokyo, 1990.

den Hartog AP & van Staveren WA. Manual for social surveys on food habits and consumption in developing countries. Pudoc. Wageningen, The Netherlands, 1983.

Hendrata L & Johnston M. Manual for community based under-fives weighing programme. Yayasan Indonesia Sejahtera, Jakarta, Indonesia, 1978.

Jelliffe DB. Paediatrics in the tropics. Teaching Aids at Low Costs. TALC. St. Albans, UK, 1985.

Jelliffe DB. The assessment of nutritional status of the community. WHO. Geneva, Switzerland, 1966.

Jelliffe DB. Community nutritional assessment. Oxford University Press. Oxford, New York, Tokyo, 1989.

Jennings J, Gillespie S, Mason J, Lofti M, & Scialfa T. Managing successful nutrition programmes. ACC/SCN (SOA No.8). Geneva, Switzerland, 1991.

Katz J. Sample-size implications for population-based cluster surveys of nutritional status. Am J Clin Nutr. 1995; 61:155-160.

Kirkwood BR. Essentials of medical statistics. Blackwell Scientific Publications. Oxford, London, Edinburgh, UK, 1988.

List B. Ernährungsaspekte in der ländlichen Entwicklung. 2. Auflage, DSE & GTZ. Feldafing, Eschborn, Germany, 1988.

Lohmann TG, Roche AF, & Martorell R. Anthropometric standardization reference manual. Abridged edition. Human Kinetics Books. Campaign, Illinois, USA, 988.

Lwanga SK & Lemeshow S. Sample size determination in health studies - a practical manual. WHO. Geneva, Switzerland, 1991.

Martorell R. Nutrition and health status indicators. LSMS Working Paper Series No. 13, The World Bank. Washington, USA, 1982.

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