Population health Research Institute, McMaster University, Hamilton ON, Canada
Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton ON, Canada
Department of Medicine, McMaster University, Hamilton ON, Canada
Department of Physiology, University of Zimbabwe College of Health Sciences, Harare, Zimbabwe
Abstract
Background
There is little information in the literature on methods of food composition database development to calculate nutrient intake from food frequency questionnaire (FFQ) data. The aim of this study is to describe the development of an FFQ and a food composition table to calculate nutrient intake in a Black Zimbabwean population.
Methods
Trained interviewers collected 24-hour dietary recalls (24 hr DR) from high and low income families in urban and rural Zimbabwe. Based on these data and input from local experts we developed an FFQ, containing a list of frequently consumed foods, standard portion sizes, and categories of consumption frequency. We created a food composition table of the foods found in the FFQ so that we could compute nutrient intake. We used the USDA nutrient database as the main resource because it is relatively complete, updated, and easily accessible. To choose the food item in the USDA nutrient database that most closely matched the nutrient content of the local food we referred to a local food composition table.
Results
Almost all the participants ate sadza (maize porridge) at least 5 times a week, and about half had matemba (fish) and caterpillar more than once a month. Nutrient estimates obtained from the FFQ data by using the USDA and Zimbabwean food composition tables were similar for total energy intake intra class correlation (ICC) = 0.99, and carbohydrate (ICC = 0.99), but different for vitamin A (ICC = 0.53), and total folate (ICC = 0.68).
Conclusion
We have described a standardized process of FFQ and food composition database development for a Black Zimbabwean population.
Introduction
Diet is central in the development of obesity and chronic diseases and is changing rapidly in low and middle income countries
Subjects and methods
Study population
The urban participants lived in Harare, either in a relatively affluent area, or in an urban low-income area; the rural participants lived in Chidamoyo, 345 km from Harare. All participants were = 35 years of age, and free of any reported co-morbid conditions. The study was approved by the Institutional Review Boards of the participating institutions and the relevant authorities.
Development of FFQ
There were three major steps in FFQ development. First, we prepared a list of commonly eaten foods in Zimbabwe, including estimates of the usual portion sizes and frequencies of intake. Second, based on this list we developed a long FFQ. Third, we tested the long FFQ in the field and shortened it. We are using this version of the FFQ in our study and are validating by comparing it with multiple 24-hour dietary recalls.
Development of the food list
We used three approaches to create a food list: we conducted a 24-hour dietary recall in November 2003 among 200 persons in urban and rural areas. Second, we added foods to this list that were commonly eaten in that Zimbabwean population at other times of the year and on special occasions. Third, we further expanded this list by adding foods that were nutrient rich but were not captured in the previous steps (caterpillar for example) from a previously prepared food composition table for Zimbabwe and the observations of the local Zimbabwean nutritionists.
We then formatted the foods on the expanded list into questions. We organized the foods items based on their similarities in nutrient content into 6 major food groups as has been done elsewhere
Frequency of intake
To estimate average frequency of intake of most foods in the previous year we used closed-ended responses consisting of 9 categories: Never or less than once/month, 1–3/m, 1/week, 2–4/wk, 5–6/wk, 1/day, 2–3/d, 4–5/d, >6/d
Portion size
To obtain food portion size, we physically examined all reported portions and took the most commonly consumed portion as the unit of measurement.
Seasonality
Unlike in most western countries fruit and vegetable availability and cost vary greatly by season in Zimbabwe. We asked how often on average fruits and vegetables with seasonal variation were consumed in season. Our colleagues in Zimbabwe prepared the list of seasonal fruits and vegetables and estimated the length of season for each item. This allowed us to take seasonality into account to calculate the average daily intakes of such foods.
Testing of pilot FFQ
We pilot tested the long FFQ by administering it to 100 participants in July 2004, and excluded infrequently eaten foods.
Food composition database
The food composition database that we found for Zimbabwe was 24 years old and was not updated regularly. Moreover, the reported nutrients in the food composition table included those recommended by Southgate in 1974
However, the USDA nutrient database has many different entries for the same food with different nutrient compositions. If we arbitratily chose any one of those foods its nutrient composition might have been different from that of the same food used in Zimbabwe. We therefore used the Zimbabwen food composition database to help us choose the same food item from the USDA nutrient databse that was most similar in nutrient composition to the one used in Zimbabwe. For example, among 13 apples in USDA nutrient database, Apples, raw, with skin code 9003 was the most similar to the apple in Zimbabwe food composition table (Table
Comparison of nutrient composition of an apple described in the local Zimbabwe food composition table with different apples in the USDA nutrient database
NDB No
Shrt_Desc
Water/g
Energ/Kcal
Protein/g
Lipid/g
CHO/g
Ca/mg
Fe/mg
P/mg
K/mg
Na/mg
Vit_C/mg
Vit B1/mg
Vit B2/mg
Niacin/mg
Vit B6/mg
Folate/mg
Vit_A RAE
09003
Apple, raw w Skin
85.56
52
0.26
0.17
13.81
6
0.12
11
107
1
4.6
0.017
0.026
0.091
0.041
3
3
09004
Apple raw wo, skin
86.67
48
0.27
0.13
12.76
5
0.07
11
90
0
4
0.019
0.028
0.091
0.037
0
2
09005
Apple raw wo, skin Ckd bld
85.47
53
0.26
0.36
13.64
5
0.19
8
88
1
0.2
0.016
0.012
0.095
0.044
1
2
09006
Apple raw wo, skin / ckd microwave
84.63
56
0.28
0.42
14.41
5
0.17
8
93
1
0.3
0.017
0.011
0.061
0.046
1
2
09007
Apple cnd, swtnd, sliced, dr nd, unhtd
82.36
67
0.18
0.49
16.7
4
0.23
5
68
3
0.4
0.009
0.01
0.073
0.044
0
3
09008
Apple cnd, swtnd Sliced, drnd, htd
82.28
67
0.18
0.43
16.84
4
0.24
6
70
3
0.2
0.009
0.01
0.081
0.044
0
3
09009
Apple, Dehyd (lo moist) sulfured unckd
3
346
1.32
0.58
93.53
19
2
55
640
124
2.2
0.046
0.13
0.68
0.28
1
4
09010
Apple, Dehyd (lo moist) sulfured stwd
79.36
74
0.28
0.12
19.91
4
0.43
12
136
26
0.6
0.008
0.029
0.14
0.054
0
1
09011
Apple, dried sulfured, unckd
31.76
243
0.93
0.32
65.89
14
1.4
38
450
87
3.9
0
0.159
0.927
0.125
0
0
09012
Apple, dried sulfured, stwd, wo/sugar
84.13
57
0.22
0.07
15.32
3
0.33
9
105
20
1
0.006
0.019
0.129
0.05
0
1
09013
Apple, dried sulfured, stwd, w/sugar
78.76
83
0.2
0.07
20.73
3
0.31
8
98
19
0.9
0.006
0.018
0.121
0.047
0
1
09014
Apple, frz, unswtnd, unhtd
86.85
48
0.28
0.32
12.31
4
0.18
8
77
3
0.1
0.013
0.011
0.042
0.034
1
2
09015
Apple, frz, unswtnd, htd
87.16
47
0.29
0.33
12
5
0.19
8
76
3
0.4
0.014
0.011
0.043
0.032
1
1
Apple_Zimbabwe
84.6
56.2
0.4
0.6
13.1
6.5
0.6
10.8
106
1.5
5.4
0.03
0.03
0.15
0.03
3.9
13.39
Comparison of nutrient content of some foods calculated from Zimbabwe and USDA food composition tables
Foods
Code
Energy kcal
Protein g
Fat g
CHO g
Ca mg
P mg
Fe mg
K mg
Na mg
Vit† A RE
Vit C mg
B1 mg
B2 mg
B3 mg
B6 mg
B12 mg
Folate mg
Corn flour
Zim_FCT*
356.2
4.5
2.1
84.0
7.0
45.7
1.6
30.5
26.0
0
0
0.01
0
0.10
tr**
0
tr
Corn, white
20314
365
9.42
4.74
74.2
7
210
2.71
287
35
0
0
3.627
0.622
0
Corn flour, whole-grain, white
20316
361
6.93
3.86
76.85
7
272
2.38
315
5
0
0
1.900
0.370
0
25
Cornmeal, whole-grain, white
20320
362
8.12
3.59
76.89
6
241
3.45
287
35
0
0
3.632
0.304
0
25
Shakata (Mobola Plum) this must be a mistake
167.5
1.2 0
0.5
41.9
2.2
158.3
55.7
0.5
Plums, raw
09279
46
0.70
0.28
11.42
6
16
0.17
157
0
17
9.5
0.417
0.029
0
5
Plums, canned, purple, water pack, solids and liquids
09281
41
0.39
0.01
11.03
7
13
0.16
126
1
46
2.7
0.370
0.027
0
3
Plums, canned, purple, light syrup pack, solids and liquids
09283
63
0.37
0.10
16.28
9
13
0.86
93
20
12
0.4
0.297
0.027
0
3
Guavas this also
66
1
0.5
14.6
16.6
26.0
0.9
290
4.0
50.0
221.4
0.05
0.04
1.1
0.0
Guavas, common, raw
09139
68
2.55
0.95
14.32
18
40
0.26
417
2
31
228.3
1.084
0.110
0
49
Chicken raw
Zim_FCT
195.1
19
12.9
0
12
179
1.3
227
68.3
105
0.9
0.8
0.15
7.7
0.3
0.4
5
Chicken raw
5006
215
18.6
15.1
0
11
147
0.9
189
70
41
1.6
0.06
0.12
6.8
0.35
0.3
6
Chicken raw, meat and skin stewing
5123
258
17.6
20.3
1.04
10
172
1.04
204
71
52
0
0.11
0.17
6.26
0.33
0.3
6
Chicken roast, skin and meat
Zim_FCT
216
26.7
8.2
0
12
214
1.5
308
82.4
45
0
0.7
0.23
5.6
Chicken roast, skin and meat
5111
216
17.1
15.9
0
10
166
1.01
196
68
38
0
0.06
0.12
6.57
0.32
0.3
6
Chicken roasted, skin and meat
5055
239
28.2
13.2
0
24
165
1.39
237
96
28
0
0.07
0.22
7.069
0.34
0.3
7
Chicken, cooked, roasted
5069
216
27
11.2
0
12
175
1.33
229
90
30
0
0.07
0.22
5.994
0.34
0.3
8
Spinach (Mova)
Zim_FCT
15.9
1.2
0.2
2.4
33.1
30.3
0.9
228.3
8.9
419.4
11.10
0.07
0.08
0.35
0.06
0
32.80
Malabar, Spinach, cooked
11986
23
2.98
0.78
2.71
124
36
1.48
256
55
58
5.9
0.787
0.086
0
114
New Zealand spinach, cooked, boiled, drained, without salt
11277
12
1.30
0.17
2.20
48
22
0.66
102
107
181
16.0
0.390
0.237
0
8
* Zim_FCT = Zimbabwe food composition table
** Tr = trace
† Vit = vitamin
For mixed dishes we entered local recipes into an Excel spreadsheet and applied yield and retention factors taken form USDA Handbook No.102 (food yields, summarized by different stages of preparation)
For those food items, which were not available in the USDA nutrient database such as caterpillar, we chose a food item from the same food category (sushi caterpillar)
Finally, for some other foods which were not available in USDA we found the common name, scientific name of local food items and matched them with the same scientific name in English and then chose similar food item from USDA. For example, taro is
Recipe analysis
To calculate the nutrient content of mixed dish gathered local recipes as described elsewhere
Data management and statistical analysis
We entered information from the FFQ and basic demographic characteristics of the participants into SPSS. We calculated the frequency of intake of a portion of each food on the FFQ. We administered the FFQ to 100 people and estimated the mean and standard deviation (SD) of nutrient intake from 30 commonly eaten foods using the USDA and Zimbabwean food composition tables. To compare the estimates we calculated intraclass correlations.
Results
Of the 200 persons who responded to the 24 hr Dr and FFQ slightly more than half were women (Table
Characteristics of subjects who participated in 24 hr dietary recall and pilot testing Long-FFQ*
FFQ
24 hr DR
Women
N = 55
N = 43
Age (years)
50.6 (12.1)
52.3 (14.4)
BMI (kg/m2)
26.3 (4.8)
23.6 (5.0)
Men
(N = 43)
N = 45
Age (years)
51.4 (16.1)
51 (13.6)
BMI (kg/m2)
23.7 (6.0)
21.8 (3.6)
Income (ZW $)**
Very-Low
22 (52.4%)
63 (88.7%)
Low
15 (35.7%)
7 (9.9%)
Middle
5 (11.9%)
1 (1.4%)
No response
56
24
Marital status
Never married
3 (3%)
4 (4.5%)
Married
72 (72.2%)
48 (53.9%)
Widow, divorced or separated
25 (24.2%)
37 (41.6%)
Education
Illiterate
10 (10.1%)
20 (22.5%)
Primary or secondary school
87 (87.8%)
61 (68.6%)
University, college
2 (2%)
5 (5.6%)
Profession
Professionals
1 (1.3%)
4 (5.6%)
Technicians and associated worker
17 (22.1%)
3 (4.2%)
Elementary occupation
22 (28.6%)
40 (56.3%)
Homemaker
37 (48.1%)
3 (4.2%)
* The numbers in each of the categories in this table are different because the number of reponses we received varied
** Exchange rate US $ 1 = 5300 Zimbabwe dollar
Very low < 3 × 105 ZW $/month
Low 3 × 105 to 1 × 106 ZW $/month
Middle 1 × 106to 2.5 × 106 ZW $/month
High >2.5 × 106 ZW $/month
The staple food in this population was maize. It was cooked in different ways such as sadza, samp, or mealie porridge (Table
Description of some foods unique to Zimbabwe
Food
Description
Bread, cereal and starches
Sadza
Stiff porridge (prepared from meal of maize, millet, sorghum or rice) and contain a small amount of fibre. The meal of maize is the staple food in Zimbabwe
Samp (Mashakada*)
Boiled maize grain (previously dried), sometimes its degerminated broken grain, pounded and boiled
Mealie Porridge
Ground corn, boiled not too thick, if more is added becomes sadza, other foods can be added like peanut butter (sometimes margarine), sugar (amounts depends on quantity), milk, some people even add bread
Pumpkin Porridge African bread
Mash prepared from cattle melon or pumpkin ingredients: corn flour, egg, sugar and water
Fruits
Baobab
Adansonia digitata
Paw Paw
Carica Papaya, Papaya
Naartjie
Citrus aurantium, Tangerine
Shakata
Parinari Curatellifolia, Mobola Plum
Vegetables
Gourd (dende*)
Lagenaria siceraria, Containe of groundnut butter
Taro
Colacasia antiquorum, Yam
Mowa
Decumbent perennial weed; Amaranthus thunbergii& graecizans (leaves cooked as spinach)
Meat
Caterpillar
Edible caterpillar (dark, with white fur, found on musasa trees. Eaten fried or sun-dried
Matemba, Kapenta Mouse
Small fish caught mostly from lake Kariba Wild mice (not rats or house mice), these are trapped in the wild or fields. Eaten cooked with soup or dried.
Milk and dairy product
Lacto
Commercially produced fermented milk and taste sour
* Name of food in Shona
In Table
Reported consumption of selected foods in the past year in Zimbabwe from FFQ
Foods
Frequency of consumption
Never, <1/mo
1–3 / mo
1/wk
2–4 / wk
≥ 5 / wk
Bread, cereal and starches
Sadza (maize)
0
0
0
4 (2%)
97 (98%)
White bread
40 (40.8%)
16 (16.3%)
4 (4.1%)
7 (7.1%)
31 (31.6%)
Starch roots and tubers
Sweet potato
3 (3%)
9 (9.1%)
9 (9.1%)
32 (32.3%)
44 (44.5%)
Meat and eggs
Matemba
46 (46.5%)
24 (24.2%)
16 (16.2%)
11 (11.1%)
2 (2%)
Caterpillar
52 (52.5%)
28 (28.3%)
5 (5.1%)
12 (12.1%)
2 (2%)
Mice
66 (66.7%)
12 (12.1%)
11 (11.1%)
3 (3%)
7 (7.1%)
Dairy products
Lacto
36 (36.4%)
38 (38.4%)
9 (9.1%)
15 (15.2%)
1 (1%)
Whole milk
79 (79.8%)
9 (9.1%)
2 (2%)
6 (6.1%)
3 (3%)
Fruits in season
Mango
2 (2%)
3 (3%)
12 (12.1%)
19 (19.2%)
63 (63.8%)
Guava
9 (9.1%)
9 (9.1%)
10 (10.1%)
24 (24.2%)
47 (47.5%)
Fruits out of season
Banana
33 (33.3%)
25 (25.3%)
7 (7.1%)
10 (10%)
24 (24.2%)
Paw Paw
77 (77.8%)
16 (16.2%)
3 (3%)
1 (1%)
2 (2%)
Type of oil most commonly used for cooking (N,%) Vegetable oil 98 (99%)
We obtained very similar estimates by the USDA and Zimbabwean food composition tables for energy intake from 30 selected foods (1492 kcal versus 1401 kcal, ICC = 0.99), and carbohydrate (300 g versus 289 g, ICC = 0.99) (Table
Comparison of nutrient intake of 100 participants by USDA and Zimbabwe food composition table
Nutrients
USDA Mean (SD)
Zim FCT* Mean (SD)
Intraclass correlation
Energy (kcal)
1492 (661)
1401 (597)
0.99
Protein (g)
33 (15)
46 (25)
0.94
Fat (g)
20 (12)
26 (15)
0.97
Carbohydrate (g)
300 (131)
289 (133)
0.99
Calcium (mg)
443 (222)
360 (226)
0.98
Phosphorus (mg)
560 (250)
987 (367)
0.94
Potassium (mg)
2746 (1830)
3955 (2177)
0.98
Sodium (mg)
1160 (401)
1561 (644)
0.78
Vitamin A, (RE)**
4362 (2978)
1240 (789)
0.53
Vitamin C (mg)
567 (462)
506 (523)
0.99
Total folate (μ-g)
99 (66)
309 (183)
0.68
* FCT = Food composition table
** RE = Retinol equivalents
Discussion
In this paper we have desc