Skip Navigation

This Article
Right arrow Abstract Freely available
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (31)
Right arrow Request Permissions
Google Scholar
Right arrow Articles by Tokudome, S
Right arrow Articles by Fujiwara, N
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Tokudome, S
Right arrow Articles by Fujiwara, N
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Japanese Journal of Clinical Oncology Pages 679-687

Development of Data-based Semi-quantitative Food Frequency Questionnaire for Dietary Studies in Middle-aged Japanese
Introduction
Subjects And Methods
   Subjects
   Weighed Diet Record
   Nutrients of Interest
   Selection of Foods/Recipes
   Intake Frequency
   Portion Size
Results
   Study Subjects
   Selection of Foods/Recipes
   List of Foods/Recipes
   Foods/Recipes for Macronutrients
   Percentage Coverage of Nutrients by SQFFQ
Discussion
   Appendix
   List of Foods/Recipes Included in a Semi-quantitative Food Frequency Questionnaire
Acknowledgments
References
Development of Data-based Semi-quantitative Food Frequency Questionnaire for Dietary Studies in Middle-aged Japanese

Development of Data-based Semi-quantitative Food Frequency Questionnaire for Dietary Studies in Middle-aged Japanese

Shinkan Tokudome1, Masato Ikeda2, Yuko Tokudome3, Nahomi Imaeda4, Ikumi Kitagawa5 and Nakako Fujiwara1

1Department of Public Health, Nagoya City University Medical School, Nagoya, 2Department of Occupational Health Economics, University of Occupational and Environmental Health, Kitakyushu, 3Nagoya Bunri College, Nagoya, 4Nagoya City Personnel Health Management Center, Nagoya and 5Nagoya Seirei Junior College, Seto, Japan

Background: We designed a data-based semi-quantitative food frequency questionnaire to clarify the relationship between food intake and lifestyle-related diseases among middle-aged Japanese.
Methods: A total of 351 middle-aged individuals were recruited to a one-day weighed diet record survey in 1994. In all, 586 foods were consumed. Intake of 31 nutrients including energy, protein, fat, carbohydrate, vitamins, minerals and dietary fiber by food was computed by multiplying the weight of food consumed by its nutrient content. First, 252 foods with up to 90 cumulative % contribution to nutrient intake were selected. Of these, foods having apparently the same/similar nutrient content were combined into 206 foods by research dietitians. Next, 183 foods with up to 0.90 cumulative multiple regression coefficient and 90 cumulative % contribution were chosen. At this stage an additional food grouping was made.
Results: Finally, 102 foods/recipes were included in the questionnaire: rice (2 items), bread and noodles (11), eggs, milk and dairy products (10), soybean, soybean products and other beans (7), meat including beef, pork and chicken (12), fish (5), other fish, shellfish and fish products (10), green-yellow vegetables (8), other vegetables and mushrooms (7), edible roots (2), seaweeds (3), seeds (2), fruits (8), beverages (7) and confectioneries (8). The frequencies were classified into eight categories. Portion size was calculated for the respective foods largely from the one-day weighed diet record.
Conclusions: The developed semi-quantitative food frequency questionnaire substantially covered the intake of 31 nutrients and may be competent to rank middle-aged Japanese efficiently.

Key words: weighed diet record - contribution analysis - multiple regression analysis - semi-quantitative food frequency questionnaire

INTRODUCTION

As is well known, the Japanese enjoy the longest life expectancy in the world, which may be accounted for by genetic predisposition, modest lifestyle, improvements in sanitary environment and a well-organized health care/medical/welfare system. Three-fifths of deaths are due to chronic diseases, such as cancer, heart disease and cerebrovascular disease. Among lifestyle factors, smoking, diet and exercise may be the top three. As with smoking and physical exercise, food intake is controllable. However, unlike either smoking, which is always harmful, or physical exercise, which is beneficial if done moderately, diet has two profiles. Food is primarily requisite and favorable, but excessive or imbalanced intake may be deleterious. Thus, further research is needed to elucidate the association between food intake and health/disease, including cancer, on the basis of a dietary questionnaire specifically and systematically developed in Japan.

Recently, we designed an evidence-based semi-quantitative food frequency questionnaire (SQFFQ) (1-3) on the basis of a one-day weighed diet record (WDR) according to multiple regression analysis (MRA) and also contribution analysis (CA). Although calibration/validation and reproducibility studies in terms of food list, intake frequency and portion size are currently in progress, it seemed informative to report the procedures undertaken for preparing this SQFFQ and the foods largely contributing to nutrient intake of interest and serving to classify individuals efficiently into a tertile/quartile/quintile categorization.

SUBJECTS AND METHODS

Subjects

A total of 351 (171 males and 180 females) middle-aged Japanese living in Aichi, Mie and Gifu Prefectures, in Central Japan, parents of student dietitians attending a Junior College and majoring in nutrition, participated in a one-day WDR survey during October-November 1994. The mean ages ± standard deviations for males and females were 50.2 ± 5.2 and 46.9 ± 4.4, respectively.

Weighed Diet Record

The WDR was carried out on a weekday. Weight measurement was done before cooking if food was prepared at home, otherwise after cooking. Foods were weighed individually; while foods such as soup were divided by the number of household members. Not only completeness but also accuracy of WDR were reviewed by the respective students and research nutritionists.

Nutrients of Interest

The following 31 nutrients were selected: energy, protein, fat, carbohydrate, total dietary fiber (TDF) [including soluble dietary fiber (SDF) and insoluble dietary fiber (IDF)], minerals (including potassium, calcium, magnesium, phosphorus, iron, zinc and copper) and vitamins (including carotene and vitamins A, C, D and E). Fat was divided into saturated fatty acids (SFA), mono-unsaturated fatty acids (MUFA) (including oleic acid), polyunsaturated fatty acids (PUFA), n-6 PUFA, n-3 PUFA and cholesterol. n-6 PUFA was subdivided into linoleic acid (18:2n-6) and arachidonic acid (18:3n-6) and n-3 PUFA was divided into [alpha]-linolenic acid (18:3n-3), eicosapentaenoic acid (EPA, 20:5n-3) and docosahexaenoic acid (DHA, 22:6n-3).

Selection of Foods/Recipes

In all, 586 foods were consumed by the subjects. The nutrient intake by food was computed by multiplying the food intake (in grams) or serving size by the nutrient content per gram of food as listed in the Standard Tables of Food Composition, Version 4 and the Follow-up of the Standard Tables of Food Composition, Version 4 (4,5). First, modified CA was applied to nutrients of interest as follows (6,7). We defined the percentage contribution of nutrient k by food i as the arithmetic mean of the individual % contribution of nutrient k by food (IPCjik), which was estimated by

if then IPCJ =  was assumed.

Percentage contribution of nutrient k by food

where j =1, ..., 351 subjects, i = 1, ..., 586 foods, k = 1, ..., 31 nutrient factors, Q = grams of foods consumed and D = nutrient content per gram of food. We selected 252 foods with up to 90 cumulative % contribution, except for 80% for potassium and calcium. Those foods having apparently the same/similar nutrient contents were combined into 206 foods by research nutritionists, irrespective of the different cooking processes or appearances: cooked bread (e.g. pre-cooked bread, sandwich, pizza); beef (e.g. steak, grilled beef, Sukiyaki, Shabu-shabu); blue-skinned fish (e.g. mackerel, sardines, horse mackerel, yellowtail, Spanish mackerel); bone-edible small fish (e.g. Wakasagi, Shishamo, Mezashi, Shirasuboshi); other green-yellow vegetables (e.g. Komatsuna, green pepper, garland chrysanthemum, leek, okra); other vegetables (e.g. cucumber, lettuce, bean sprouts, onion, eggplant, Chinese cabbage); edible roots (e.g. potato, sweet potato, taro, yam) and so on. Next, not only CA but also forward MRA (8) were performed by adopting total intake of a specific nutrient as the dependent variable and overall amounts of nutrient from 206 foods as the independent variables for the 351 individuals (9-11). We chose 183 foods with up to 90 cumulative % contribution and 0.90 cumulative multiple regression coefficient/cumulative R2. However, seasonings, such as salt and Shoyu (soy sauce), were excluded from the questionnaire and some foods, such as brown rice, kiwi fruit, strawberries, potato chips and milk powder, were intentionally included. At this phase we did additional food grouping. Finally, 102 foods/recipes were included in the SQFFQ.

Rice is a Japanese staple food and substantially provided most nutrients. Rice intake was inquired into in a special manner, that is, the intake frequency and portion size according to the size of rice bowl for breakfast, lunch, supper and meal/snack between meals, respectively.

Supplementary questions regarding fat and oil intake were also prepared. Intake frequency of vegetable oil, mayonnaise, dressing, butter, margarine, lard, etc. and foods/recipes cooked with such fat and oil were asked about separately by dish. The brand names of fat and oil consumed at home were further surveyed to assess fatty acids intake. Sea foods such as fish, shellfish and seaweeds are also part of the typical Japanese diet and they are major sources of n-3 PUFA such as EPA and DHA; therefore, food grouping was left rather loose in order to ascertain the intake of such nutrients.

Other information was collected on the type of breakfast (e.g. Japanese or Western type), the intake frequencies of fish and meat, lean and fatty meat, and chicken skin, the frequency of eating out and the type of food (e.g. Japanese, Chinese or Western) along with sweetness and saltiness.

In addition, a separate lifestyle questionnaire included smoking, physical exercise and sleeping hours, inquiries with regard to intake of alcohol, vitamin and mineral supplements, and functional (or designer) foods. The proportion of individuals taking vitamin and mineral supplements, however, was very small in this study population, and intake of vitamin and mineral supplements was not taken into consideration.

Table 1. Intake of macro-nutrients by the 351 subjects
  Male (171)
Mean (min-max)		 Female (180)
Mean (min-max)
Energy 2163 kcal (1045-3619) 1785 kcal (956-3169)
Protein 83.5 g (33.1-149.1) 70.4 g (35.5-123.4)
Fat 62.0 g (22.4-146.2) 57.7 g (17.2-118.8)
   Animal origin 24.7 g (0-84.1) 22.2 g (0-83.5)
   Vegetable origin 30.5 g (4.2-84.1) 30.6 g (4.5-76.5)
   Marine origin 6.8 g (0-31.7) 4.8 g (0-33.5)
Carbohydrate 281.6 g (112.3-606.2) 239.3 g (109.0-470.6)

Intake Frequency

Intake frequencies were classified into eight categories: never or seldom, 1-3 times per month, 1-2 times per week, 3-4 times per week, 5-6 times per week, once a day, twice a day and three or more times a day. For beverages, including coffee, green tea, black tea and oolong tea, questions on intake frequency were left open-ended when the answer was more than 5-6 times per week.

Portion Size

The mean portion size (or average serving size) was calculated for the respective foods from the one-day WDR and typical/standard values and/or natural units from the literature were also taken into account. Portion size was questioned whether the size was half as much, the same, 1.5 times larger or twice the average serving size. An open-ended response was also prepared.

RESULTS

Study Subjects

Table 1 shows the intake of energy, protein, fat and carbohydrate by study subjects. More macro-nutrients were consumed by males than females. These nutrients were slightly less than the national average in the respective age groups (12). Energy intake was somewhat less than the Recommended Dietary Allowances (RDA) in either sex (13). Protein intake was, however, slightly higher than the RDA. Approximately 60 g of fat on average or 25% of the fat-energy ratio was consumed, which was slightly above the RDA.

Selection of Foods/Recipes

As mentioned, 586 foods were initially consumed by the subjects. Firstly, CA was used and 252 foods with up to 90 cumulative % contribution were chosen for 31 nutrients. Those foods having apparently the same/similar nutrient contents were combined into 206 foods by the research nutritionists. Next, 183 foods satisfying not only the 90 cumulative % contribution but also 0.90 cumulative R2 were selected. The mean number of foods by CA was 46.7 with a range of 18 for carotene to 94 for phosphorus, which was significantly greater than the mean by MRA of 21.6 with a range of 1 for zinc and copper to 59 for protein (Table 2).

Table 2. Number of foods contributing to 31 nutrients with up to 90 cumulative % contribution and 0.90 cumulative R2 by the 351 subjects
  Cumulative % contribution Cumulative R2
Energy 78 45
Protein 82 59
Fat 61 41
Carbohydrate 35 18
SFA 50 25
MUFA 47 30
PUFA 43 20
Cholesterol 35 8
Oleic acid 40 23
n-6 PUFA 30 16
Linoleic acid 33 16
Arachidonic acid 29 19
n-3 PUFA 42 16
[alpha]-Linolenic acid 29 9
EPA 50* 10
DHA 28 11
Vitamin C 27 10
Carotene 18 2
Vitamin A 29 5
Vitamin E 62 24
Vitamin D 25 6
Potassium (K) 90 42
Calcium (Ca) 76 24
Magnesium (Mg) 49 27
Phosphorus (P) 94 54
Iron (Fe) 90 37
Zinc (Zn) 38 1
Copper (Cu) 40 1
TDF 36 29
SDF 29 16
IDF 32 27
*Stopped at 85% partly because 51 subjects did not consume foods/recipes providing EPA.

List of Foods/Recipes

According to the categorization scheme of the Standard Tables of Food Composition (4,5), 102 foods/recipes were included in the SQFFQ as follows: rice (2 items), bread and noodles (11), eggs, milk and dairy products (10), soybean, soybean products and other beans (7), meat including beef, pork and chicken (12), fish (5), other fish, shellfish and fish products (10), green-yellow vegetables (8), other vegetables and mushrooms (7), edible roots (2), seaweeds (3), seeds (2), fruits (8), beverages (7) and confectioneries (8) (see Appendix).

Table 3. Percentage contribution, cumulative % contribution and cumulative R2 of the top 20 foods for energy
Rank Food Cumulative
% contribution		 Rank Food % contribution Cumulative R2
1 Well-milled rice 31.0 1 Well-milled rice 31.0 0.35
2 White bread 35.6 2 Beer 2.0 0.43
3 Chicken egg 39.9 3 White bread 4.6 0.49
4 Milk (whole) 42.4 4 Beef (chuck loin) 0.8 0.52
5 Salad oil (mixed) 44.7 5 Chinese noodles 1.2 0.55
6 Udon/Soba (Japanese noodles) 46.8 6 Sake 1.1 0.58
7 Beer 48.8 7 Arare (rice cake cubes) 0.4 0.61
8 White sugar 50.4 8 Wheat flour 1.4 0.64
9 Tofu (soybean curd) 52.1 9 Milk (whole) 2.4 0.66
10 Wheat flour 53.4 10 Mayonnaise (egg yolk type) 1.2 0.68
11 Vegetable oil (mixed) 54.7 11 Pork (ground meat) 0.6 0.70
12 Pork (Boston butt) 56.0 12 Chicken egg 4.4 0.71
13 Mayonnaise (egg yolk type) 57.2 13 Mayonnaise(whole egg type) 0.6 0.73
14 Koji-miso (soybean paste) 58.5 14 Dorayaki (bean-jam pancake) 0.3 0.74
15 Chinese noodles 59.7 15 Mirin (sweet Sake used for seasoning) 0.4 0.75
16 Sake 60.8 16 Bread crumbs 0.4 0.76
17 Salmon 61.8 17 Udon/Soba (Japanese noodles) 2.1 0.77
18 Potatoes 62.8 18 Salad oil (mixed) 2.3 0.78
19 Beef (chuck loin) 63.6 19 Beef (sirloin) 0.2 0.79
20 Abura-age (fried soybean curd) 64.5 20 Under-milled rice 0.2 0.79

Table 4. . Percentage contribution, cumulative % contribution and cumulative R2 of the top 20 foods for protein
Rank Food Cumulative
% contribution		 Rank Food % contribution Cumulative R2
1 Well-milled rice 14.7 1 Well-milled rice 14.7 0.16
2 Chicken egg 23.2 2 Round herring (salted and dried, round) 0.3 0.21
3 White bread 27.2 3 Chicken egg 8.6 0.26
4 Tofu (soybean curd) 30.8 4 Yellowfin tuna 1.0 0.31
5 Salmon 34.0 5 Shoyu (soy sauce) 2.3 0.35
6 Milk (whole) 37.1 6 Dried squid 0.2 0.39
7 Koji-miso (soybean paste) 39.6 7 Pork (ground meat) 1.0 0.43
8 Shoyu (soy sauce) 41.9 8 Coffee drink (canned) 0.2 0.47
9 Mushi-Kamaboko (steamed fish paste) 43.8 9 Koji-miso (soybean paste) 2.5 0.50
10 Pork (Boston butt) 45.7 10 Chicken (breast) 0.5 0.52
11 Pacific saury 47.4 11 Milk (whole) 3.1 0.54
12 Beef (chuck loin) 48.8 12 Chinese noodles 1.1 0.56
13 Udon/Soba (Japanese noodles) 50.2 13 White bread 3.9 0.58
14 Shiba-shrimp (prawn) 51.4 14 Under-milled rice 0.1 0.60
15 Beef (flank) 52.5 15 Chicken (breast), sasami (fillet) 0.7 0.61
16 Chicken (wing) 53.5 16 Chicken (wing) 1.1 0.63
17 Chinese noodles 54.6 17 Salmon 3.2 0.64
18 Beef (inside round) 55.6 18 Lettuce 0.1 0.65
19 Chicken (thigh) 56.7 19 Squid 0.8 0.66
20 Abura-age (fried soybean curd) 57.7 20 Beef (sirloin) 0.4 0.67

Table 5. Percentage contribution, cumulative % contribution and cumulative R2 of the top 20 foods for fat
Rank Food Cumulative
% contribution		 Rank Food % contribution Cumulative R2
1 Chicken egg 10.3 1 Pork (ground meat) 1.2 0.10
2 Salad oil (mixed) 18.0 2 Mayonnaise (egg yolk type) 4.0 0.18
3 Vegetable oil (mixed) 22.5 3 Pork (Boston butt) 3.0 0.25
4 Milk (whole) 26.8 4 Chicken egg 10.3 0.31
5 Mayonnaise (egg yolk type) 30.8 5 Salad oil (mixed) 7.7 0.36
6 Well-milled rice 34.7 6 Beef (sirloin) 0.5 0.41
7 Tofu (soybean curd) 38.3 7 Safflower oil 1.8 0.45
8 Pork (Boston butt) 41.3 8 Vegetable oil (mixed) 4.5 0.48
9 Abura-age (fried soybean curd) 43.8 9 Beef (chuck loin) 2.2 0.53
10 Margarine 46.2 10 Milk (whole) 4.3 0.56
11 White bread 48.5 11 Mayonnaise (whole egg type) 1.9 0.59
12 Beef (chuck loin) 50.7 12 Margarine 2.3 0.61
13 Koji-miso (soybean paste) 52.7 13 Sausage (Vienna) 1.5 0.64
14 Mayonnaise (whole egg type) 54.6 14 Butter 1.2 0.66
15 Safflower oil 56.4 15 Butter peanuts 0.4 0.67
16 Pacific saury 58.1 16 Beef (ground meat) 1.1 0.69
17 Salmon 59.6 17 Pork (belly) 1.1 0.70
18 Sausage (Vienna) 61.1 18 Peanuts (dried) 0.2 0.72
19 Beef (flank) 62.6 19 Bacon 0.7 0.73
20 Corn oil 63.9 20 Beef (flank) 1.4 0.75

Table 6. Percentage contribution, cumulative % contribution and cumulative R2 of the top 20 foods for carbohydrate
Rank Food Cumulative
% contribution		 Rank Food % contribution Cumulative R2
1 Well-milled rice 50.5 1 Well-milled rice 50.5 0.45
2 White bread 57.1 2 Udon/Soba (Japanese noodles) 3.1 0.51
3 White sugar 60.2 3 Chinese noodles 1.8 0.57
4 Udon/Soba (Japanese noodles) 63.3 4 White bread 6.6 0.62
5 Wheat flour 65.5 5 Coffee drink (canned) 0.9 0.67
6 Chinese noodles 67.3 6 Wheat flour 2.2 0.70
7 Potatoes 68.9 7 Arare (rice cake cubes) 0.6 0.74
8 Milk (whole) 70.4 8 Mandarin orange 1.4 0.77
9 Kaki (Japanese persimmon) 71.9 9 Dorayaki (bean-jam pancake) 0.5 0.78
10 Mandarin orange 73.3 10 An-pan (bean-jam bun) 0.7 0.80
11 Apple 74.6 11 Macaroni 1.0 0.82
12 Beer 75.9 12 Short cake 0.6 0.83
13 Macaroni 77.0 13 Kaki (Japanese persimmon) 1.5 0.84
14 Banana 77.9 14 Under-milled rice 0.3 0.86
15 Coffee drink (canned) 78.8 15 Sweet potatoes 0.6 0.87
16 Onion 79.5 16 Manju (steamed bun with bean-jam filling) 0.4 0.88
17 An-pan (bean-jam bun) 80.2 17 Buckwheat flour 0.5 0.90
18 Pre-cooked Chinese noodles 80.9 18 Pre-cooked Chinese noodles 0.7 0.91
19 Shoyu (soy sauce) 81.6 19 Potatoes 1.6 0.91
20 Bread crumbs 82.2 20 Pumpkin 0.5 0.92

Foods/Recipes for Macronutrients

The percentage contribution, cumulative % contribution and cumulative R2 of the top 20 foods/recipes for energy, protein, fat and carbohydrate are shown in Table 3-6, respectively.

One-third of the energy was contributed by well-milled rice, followed by white bread, chicken egg, milk (whole) and salad oil (mixed) according to CA (Table 3). Well-milled rice, beer, white bread, beef (chuck loin) and Chinese noodles were selected in that order by MRA.

CA revealed that approximately 15% of total protein was derived from well-milled rice, followed by chicken egg, white bread, tofu (soybean curd) and salmon (Table 4). Well-milled rice, round herring (salted and dried, round), chicken egg, yellowfin tuna and Shoyu (soy sauce) were chosen by MRA.

For fat, chicken egg was ranked at the top based on CA, followed by salad oil (mixed), vegetable oil (mixed), milk (whole) and mayonnaise (egg yolk type) (Table 5). Pork (ground meat), mayonnaise (egg yolk type), pork (Boston butt), chicken egg and salad oil (mixed) were selected by MRA.

More than half the carbohydrate was supplied by well-milled rice, followed by white bread, white sugar, Udon/Soba (Japanese noodles) and wheat flour on the basis of CA (Table 6). Well-milled rice, Udon/Soba, Chinese noodles, white bread and coffee drink (canned) were chosen by MRA.

Percentage Coverage of Nutrients by SQFFQ

The percentage coverage of 31 nutrients by the SQFFQ was computed assuming all 586 foods as unity (Table 7). As mentioned, fat and oil intake in supplementary items in the SQFFQ and alcohol intake in a lifestyle questionnaire were taken into account. The average was 94% with a range from 85% for iron to 99% for [alpha]-linolenic acid.

DISCUSSION

Admittedly, the sample size was not large enough and the one-day WDR was done in a specific season and in a selected area in Japan. We were naturally unable to estimate within-individual variation on the basis of a one-day WDR. The present data therefore were not necessarily accurate or complete in terms of quality and quantity. The average intake of macro-nutrients, however, was somewhat less than the national data published (12) and slightly greater than the RDA (13); hence the profiles of study subjects were unlikely to be very different from those of the general population.

In choosing foods/recipes, there are two contrasting methods (14-15): one is based on CA (6,7) and the other on MRA (9-11). Each method has its particular advantages and disadvantages. The former approach is based on absolute intake and is useful for making energy adjustments. Hence this procedure is especially suitable for studies to clarify the association with absolute nutrient intake but often inappropriate for categorizing individuals. The latter is based on the variance of nutrient intake. The cumulative R2 was explained by a significantly smaller number of foods than cumulative % contribution, that is, MRA may be efficient in categorizing individuals, but unsuitable for computing the absolute nutrient level.

Substantial foods selected by MRA were covered by those chosen by CA; rather, specific foods were only chosen by MRA. The ranking was very different by each type of analysis. Well-milled rice, a Japanese staple food, is an exception; it was not only the greatest source of variance contribution but also the largest source of absolute contribution to energy, protein and carbohydrate. Chicken egg, for example, was ranked third in energy by CA but twelfth by MRA. On the other hand, Chinese noodles were a minor source of absolute contribution to energy but a major source of variance contribution.

It appeared odd that Shoyu (soy sauce) was chosen as a major provider of protein according to CA and MRA. Shoyu, however, is often used for seasoning of foods, including meat and fish, and seemed to have contributed substantially to absolute intake and variance in intake of protein. We know of an analogous observation where popcorn, cholesterol-free in itself, was picked as a major contributor to cholesterol, which may be plausibly explained by the fact that popcorn is ordinarily seasoned with butter in the USA (1).

Table 7. Percentage coverage of 31 nutrients by the SQFFQ
Energy 91
Protein 89
Fat 93
Carbohydrate 91
SFA 96
MUFA 97
PUFA 98
Cholesterol 97
Oleic acid 96
n-6 PUFA 98
Linoleic acid 98
Arachidonic acid 97
n-3 PUFA 98
[alpha]-Linolenic acid 99
EPA 96
DHA 96
Vitamin C 93
Carotene 95
Vitamin A 95
Vitamin E 96
Vitamin D 96
Potassium (K) 87
Calcium (Ca) 91
Magnesium (Mg) 86
Phosphorus (P) 89
Iron (Fe) 85
Zinc (Zn) 93
Copper (Cu) 94
TDF 93
SDF 92
IDF 93

Seasonings, such as salt and Shoyu, were selected by CA and MRA for certain minerals including sodium and magnesium. However, they were excluded from the SQFFQ because it is difficult to weigh seasonings accurately and measure actual intake. On the other hand, brown rice, kiwi fruit, strawberries, potato chips and powdered milk were not consumed by the subjects because some of them have seasonal variations, but they were included because they are important sources of vitamins, minerals and fat.

The percentage coverage of selected nutrients by the SQFFQ was 94% on average with a range from 85% for iron to 99% for [alpha]-linolenic acid. The coverage of certain nutrients may be overestimated, owing in part to the incompleteness of the composition table. The values were more than 81%, mathematically computed by multiplying 0.90 by 0.90 (that is, we selected foods according to 90 cumulative % contribution twice), substantially because foods chosen for other nutrients have covered a specific nutrient and supplementary questions in terms of fat and oil intake eventually attained a high coverage of fat, fatty acids and related nutrients. Consequently, the SQFFQ developed seemed efficient not only in estimating the absolute intake of nutrients, except for certain minerals, but also in categorizing individuals by variance in intake.

Although the reproducibility of dietary questionnaires has often been evaluated in Japan (16-18), few validation studies have been carried out (19-22). To our knowledge, few data-based Japanese SQFFQs have been developed. Questionnaires were frequently prepared by selecting foods on the basis of the nutrient content from the food composition tables according to researchers' interest, by citing historical questionnaires or by referring to National Nutritional Surveys. Such questionnaires appeared unsatisfactory for elucidating specific hypotheses. They were mostly designed to ask only about frequency and seemed inefficient in calculating nutrient intake and values adjusted for energy intake. Japanese dietitians have been concerned about calculating food and nutrient intake and giving advice on whether a client's nutrient intake is deficient or excessive. Epidemiologists, nutritionists and biostatisticians should collaborate to prepare a valid and reliable SQFFQ to be applied to a particular population under a specific hypothesis.

Appendix

List of Foods/Recipes Included in a Semi-quantitative Food Frequency Questionnaire

Rice

  1. Well-milled rice
  2. Brown rice, under-milled rice with embryo, rice boiled with barley

Bread and noodles

  1. White bread, soft rolls
  2. Croissant
  3. Bun, bean-jam bun
  4. Pre-cooked bread, sandwiches, pizza
  5. Japanese noodle [Udon (wheat noodle)]
  6. Japanese noodle [Soba (buckwheat noodle)]
  7. Spaghetti, macaroni au gratin
  8. Pre-cooked noodles (dried snack noodle)
  9. Chinese noodles [Ramen (Chinese noodle), fried noodle, Champon (Chinese-style hotchpotch with noodle), etc.]
  10. Okonomiyaki (Japanese pancake, a thin, flat, unsweetened oil fried with bits of vegetables, meat or shellfish)
  11. Mochi (Japanese rice cake)

Eggs, Milk and Dairy Products

  1. Eggs
  2. Milk (whole)
  3. Milk (condensed)
  4. Milk (low fat)
  5. Milk powder
  6. Lactic acid beverage
  7. Yogurt
  8. Cheese
  9. Ice cream (>8% milk fat)
  10. Other ice cream

Soybean, Soybean Products and Other Beans

  1. Tofu (soybean curd) for Miso soup
  2. Tofu, Yakko tofu (tofu cut in cubes), tofu steak, Mabo-dofu
  3. Nama-age (fried tofu), Agedashi-dofu (lightly fried tofu), Ganmodoki (fried tofu paste)
  4. Abura-age (fried tofu)
  5. Natto (fermented soybean), soybean
  6. Koji-miso (soybean paste) (Miso soup, vinegar Miso)
  7. Koya-dofu (frozen and dried tofu )

Meat

  1. Ground chicken [e.g. meatball, Soboro (powdered chicken)]
  2. Beef and pork ground together (e.g. hamburger, rolled cabbage)
  3. Ground beef (e.g. hamburger, meat sauce)
  4. Ground pork (e.g. dumpling)
  5. Chicken
  6. Beef (e.g. steak, grilled beef, Sukiyaki, Shabu-Shabu
  7. Other beef (e.g. fried with vegetables, cooked with vegetables)
  8. Pork
  9. Ham
  10. Sausage (except fish sausage)
  11. Bacon
  12. Liver

Fish

  1. Salmon, Trout
  2. Eel
  3. Blue-Skinned Fish (E.G. Mackerel, Sardines, Horse Mackerel, Yellowtail, Spanish Mackerel)
  4. Red-Meat Fish (E.G. Tuna, Bonito)
  5. White-Meat Fish (E.G. Red Bream, Sea Bream, Cod, Flatfish)

Other Fish and Shellfish

  1. Bone-Edible Small Fish [E.G. Wakasagi (Fresh-Water Smelt), Shishamo (Smelt), Mezashi (Salted And Semi-Dried Sardines), Shirasuboshi (Boiled And Semi-Dried Whitebait)]
  2. Cod Roe, Salmon Roe
  3. Canned Tuna
  4. Oyster
  5. Shellfish (E.G. Short-Necked Clam, Corbicula)
  6. Dried Cuttlefish/Squid
  7. Cuttlefish, Squid, Octopus
  8. Shrimp, Crab
  9. Fried Fish Paste Products (E.G. Satsuma-Age, Agemono)
  10. Fish Paste Products (E.G. Kamaboko, Chikuwa)

Green-Yellow Vegetables

  1. Spinach
  2. Pumpkin/Squash
  3. Carrot
  4. Broccoli
  5. Tomato
  6. Vegetable Juice, Tomato Juice
  7. Other Green-Yellow Vegetables (E.G. Komatsuna, Green Pepper, Garland Chrysanthemum, Leek, Okra)
  8. Pickles (E.G. Pickled Green-Yellow Vegetables, Takuan)

Other Vegetables

  1. Cabbage
  2. Daikon (Japanese Radish), Turnip
  3. Burdock, Bamboo Shoot
  4. Other Vegetables (E.G. Cucumber, Lettuce, Bean Sprouts, Onion, Eggplant, Chinese Cabbage)
  5. Kiriboshi-Daikon (Dry Strips Japanese Radish)

Mushrooms

  1. Shiitake (Mushroom) (Dried)
  2. Shiitake (Raw), Shimeji (Champignon), Etc.

Edible Roots

  1. Potatoes (E.G. Potato, Sweet-Potato, Taro, Yam)
  2. Kon-Nyaku (Devil'S Tongue)

Seaweeds

  1. Toasted Laver, Toasted And Seasoned Laver
  2. Hijiki (Brown Algae), Kombu (Kelop)
  3. Wakame (Seaweed)

Seeds

  1. Sesame
  2. Peanut, Almond

Fruits

  1. Citrus Fruits (E.G. Orange, Tangerine, Mandarin Orange)
  2. Fruit Juice
  3. Kaki (Japanese Persimmon)
  4. Banana
  5. Apples
  6. Strawberries
  7. Kiwi Fruit
  8. Other Fruits

Beverages

  1. Coffee Drink (Canned)
  2. Coffee (Regular, Instant)
  3. Black Tea
  4. Sugar For Coffee And Black Tea
  5. Green Tea
  6. Oolong Tea, Chinese Tea
  7. Other Refreshments

Confectioneries

  1. Kasutera (Sponge Cake)
  2. Sembei (Rice Crackers), Arare (Rice Cake Cubes)
  3. Japanese Style Confectioneries (Manju, Etc.)
  4. Potato Chips
  5. Doughnut
  6. Chocolate, Chocolate Cake
  7. Cookie
  8. Cake (E.G. Short Cake, Cream Puff)

Acknowledgments

The study was partly sponsored by a Grant-in-Aid from the Ministry of Education, Science, Sports and Culture (06454242). The authors thank Ms Y. Kubo and Ms Y. Ito for their technical assistance in preparing the manuscript.

References

1. Willett W. Nutritional Epidemiology. New York: Oxford University Press, 1990.

2. Margetts BM, Nelson M. Design Concepts in Nutritional Epidemiology. New York: Oxford University Press, 1991.

3. Thompson FE, Byers T. Dietary assessment resource manual. J Nutr 1994;124:S2245-S317.

4. Resources Council, Science and Technology Agency, Japan. Standard Tables of Food Composition in Japan, 4th ed. Tokyo: Resources Council, Science and Technology Agency, Japan, 1982 (in Japanese).

5. Resources Council, Science and Technology Agency, Japan. Follow-up of Standard Tables of Food Composition in Japan. Tokyo: Ishiyaku Shuppan, 1992 (in Japanese).

6. Block G, Dresser CM, Hartman AM, Carrol MD. Nutrient sources in the American diet: quantitative data from the NHANES II survey. I. Vitamins and minerals. Am J Epidemiol 1985;122:13-26. MEDLINE Abstract

7. Freudenheim JL, Krogh V, d'Amicis A, Scaccini C, Sette S, Ferro-Luzzi A, et al. Food sources of nutrients in the diet of elderly Italians: I. Macronutrients and lipids. Int J Epidemiol 1993;22:855-68. MEDLINE Abstract

8. SAS Institute. SAS/STAT User's Guide, Version 6, 4th ed., Vol. 2. Cary, NC: SAS Institute, 1990.

9. Hankin JH, Stallones RA, Messinger HB. A short dietary method for epidemiologic studies. III. Development of questionnaire. Am J Epidemiol 1968;87:285-98. MEDLINE Abstract

10. Byers T, Marshall J, Fiedler R, Zielezny M, Graham S. Assessing nutrient intake with an abbreviated dietary interview. Am J Epidemiol 1985;122:41-50. MEDLINE Abstract

11. Overvad K, Tjønneland A, Haraldsdóttir J, Ewertz M, Jensen OM. Development of a semiquantitative food frequency questionnaire to assess food, energy and nutrient intake in Denmark. Int J Epidemiol 1991;20:900-5. MEDLINE Abstract

12. Health Promotion and Nutrition Division, Health Service Bureau, Ministry of Health and Welfare. Recommended Dietary Allowances for the Japanese, 5th revision. Tokyo: Daiichi Shuppan, 1996.

13. Health Promotion and Nutrition Division, Health Service Bureau, Ministry of Health and Welfare. Status of National Nutrition. Results of National Nutrition Survey in 1994. Tokyo: Daiichi Shuppan, 1996 (in Japanese).

14. Stryker WS, Salvini S, Stampfer MJ, Sampson L, Colditz GA, Willett WC. Contributions of specific foods to absolute intake and between-person variation of nutrient consumption. J Am Diet Assoc 1991;91:172-8. MEDLINE Abstract

15. Mark SD, Thomas DG, Decarli A. Measurement of exposure to nutrients: an approach to the selection of informative foods. Am J Epidemiol 1996;43:514-21.

16. Fukao A, Shimizu H, Maezawa M, Hisamichi S. The reproducibility of answer to the questionnaire for food intake frequency in a survey. Nihon Koshu Eisei Zasshi 1990;37:347-52 (in Japanese).

17. Ozasa K, Watanabe Y, Higashi A, Liang H, Hayashi K, Shimouchi A, et al. Reproducibility of a self-administered questionnaire for dietary habits, smoking and drinking. Nihon Eiseigaku Zasshi 1994;48:1048-57 (in Japanese).

18. Fujiwara N, Tokudome S. Reproducibility of self-administered questionnaire in epidemiological surveys. J Epidemiol 1997;7:61-9. MEDLINE Abstract

19. Nakamura M, Aoki N, Nasu K, Kondo I. A comparison between a food frequency and amount questionnaire and 7-day diet record with weighing. Nihon Koshu Eisei Zasshi 1994;41:682-92 (in Japanese).

20. Takatsuka N, Kawakami N, Kawai K, Okamoto Y, Ishiwata K, Shimizu H. Validation of recalled food intake in the past in a Japanese population. J Epidemiol 1996;6:9-13. MEDLINE Abstract

21. Tsubono Y, Takamori S, Kobayashi M, Takahashi T, Iwase Y, Iitoi Y, et al. A data-based approach for designing a semiquantitative food frequency questionnaire for a population-based prospective study in Japan. J Epidemiol 1996;6:45-53. MEDLINE Abstract

22. Date C, Yamaguchi M, Tanaka H. Development of a food frequency questionnaire in Japan. J Epidemiol 1996;6:S131-S6. MEDLINE Abstract

Received February 2, 1998; accepted August 10, 1998
For reprints and all correspondence: Shinkan Tokudome, Department of Public Health, Nagoya City University Medical School, Mizuho-ku, Nagoya 467-8601, Japan. E-mail: tokudome{at}med.nagoya-cu.ac.jp
Abbreviations: SQFFQ, semi-quantitative food frequency questionnaire; WDR, weighed diet record; MRA, multiple regression analysis; CA, contribution analysis; TDF, total dietary fiber; SDF, soluble dietary fiber; IDF, insoluble dietary fiber; SFA, saturated fatty acid; MUFA, mono-unsaturated fatty acids; PUFA, polyunsaturated fatty acid; EPA, eicosapentaenoic acid; DHA, docosahexaenoic acid; RDA, Recommended Dietary Allowances

This page is run by Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, as part of the OUP Journals
Comments and feedback: www-admin{at}oup.co.uk
Last modification: 24 Nov 1998
Copyright©Japanese Journal of Clinical Oncology, 1998.
Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Cancer Epidemiol. Biomarkers Prev.Home page
T. Mizoue, Y. Kimura, K. Toyomura, J. Nagano, S. Kono, R. Mibu, M. Tanaka, Y. Kakeji, Y. Maehara, T. Okamura, et al.
Calcium, Dairy Foods, Vitamin D, and Colorectal Cancer Risk: The Fukuoka Colorectal Cancer Study
Cancer Epidemiol. Biomarkers Prev., October 1, 2008; 17(10): 2800 - 2807.
[Abstract] [Full Text] [PDF]

Home page
 Cancer Epidemiol. Biomarkers Prev.Home page
A. Hiraki, K. Matsuo, T. Suzuki, T. Kawase, and K. Tajima
Teeth Loss and Risk of Cancer at 14 Common Sites in Japanese
Cancer Epidemiol. Biomarkers Prev., May 1, 2008; 17(5): 1222 - 1227.
[Abstract] [Full Text] [PDF]

Home page
 CarcinogenesisHome page
T. Suzuki, K. Matsuo, K. Hirose, A. Hiraki, T. Kawase, M. Watanabe, T. Yamashita, H. Iwata, and K. Tajima
One-carbon metabolism-related gene polymorphisms and risk of breast cancer
Carcinogenesis, February 1, 2008; 29(2): 356 - 362.
[Abstract] [Full Text] [PDF]

Home page
 CarcinogenesisHome page
T. Suzuki, K. Matsuo, A. Hiraki, T. Saito, S. Sato, Y. Yatabe, T. Mitsudomi, T. Hida, R. Ueda, and K. Tajima
Impact of one-carbon metabolism-related gene polymorphisms on risk of lung cancer in Japan: a case control study
Carcinogenesis, August 1, 2007; 28(8): 1718 - 1725.
[Abstract] [Full Text] [PDF]

Home page
 Cancer Epidemiol. Biomarkers Prev.Home page
K. Kuriki, K. Wakai, K. Hirose, K. Matsuo, H. Ito, T. Suzuki, T. Saito, Y. Kanemitsu, T. Hirai, T. Kato, et al.
Risk of colorectal cancer is linked to erythrocyte compositions of Fatty acids as biomarkers for dietary intakes of fish, fat, and Fatty acids.
Cancer Epidemiol. Biomarkers Prev., October 1, 2006; 15(10): 1791 - 1798.
[Abstract] [Full Text] [PDF]

Home page
 CarcinogenesisHome page
K. Matsuo, K. Wakai, K. Hirose, H. Ito, T. Saito, T. Suzuki, T. Kato, T. Hirai, Y. Kanemitsu, H. Hamajima, et al.
A gene-gene interaction between ALDH2 Glu487Lys and ADH2 His47Arg polymorphisms regarding the risk of colorectal cancer in Japan
Carcinogenesis, May 1, 2006; 27(5): 1018 - 1023.
[Abstract] [Full Text] [PDF]

Home page
 J. Nutr.Home page
T. Mizoue, T. Yamaji, S. Tabata, K. Yamaguchi, S. Ogawa, M. Mineshita, and S. Kono
Dietary Patterns and Glucose Tolerance Abnormalities in Japanese Men
J. Nutr., May 1, 2006; 136(5): 1352 - 1358.
[Abstract] [Full Text] [PDF]

Home page
 CarcinogenesisHome page
K. Matsuo, H. Ito, K. Wakai, K. Hirose, T. Saito, T. Suzuki, T. Kato, T. Hirai, Y. Kanemitsu, H. Hamajima, et al.
One-carbon metabolism related gene polymorphisms interact with alcohol drinking to influence the risk of colorectal cancer in Japan
Carcinogenesis, December 1, 2005; 26(12): 2164 - 2171.
[Abstract] [Full Text] [PDF]

Home page
 CarcinogenesisHome page
C.-X. Yang, K. Matsuo, H. Ito, M. Shinoda, S. Hatooka, K. Hirose, K. Wakai, T. Saito, T. Suzuki, T. Maeda, et al.
Gene-environment interactions between alcohol drinking and the MTHFR C677T polymorphism impact on esophageal cancer risk: results of a case-control study in Japan
Carcinogenesis, July 1, 2005; 26(7): 1285 - 1290.
[Abstract] [Full Text] [PDF]

Home page
 Am J EpidemiolHome page
T. Mizoue, T. Yamaji, S. Tabata, K. Yamaguchi, E. Shimizu, M. Mineshita, S. Ogawa, and S. Kono
Dietary Patterns and Colorectal Adenomas in Japanese Men: The Self-Defense Forces Health Study
Am. J. Epidemiol., February 15, 2005; 161(4): 338 - 345.
[Abstract] [Full Text] [PDF]

Home page
 J. Nutr.Home page
K. Kuriki, T. Nagaya, Y. Tokudome, N. Imaeda, N. Fujiwara, J. Sato, C. Goto, M. Ikeda, S. Maki, K. Tajima, et al.
Plasma Concentrations of (n-3) Highly Unsaturated Fatty Acids Are Good Biomarkers of Relative Dietary Fatty Acid Intakes: A Cross-Sectional Study
J. Nutr., November 1, 2003; 133(11): 3643 - 3650.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (31)
Right arrow Request Permissions
Google Scholar
Right arrow Articles by Tokudome, S
Right arrow Articles by Fujiwara, N
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Tokudome, S
Right arrow Articles by Fujiwara, N
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?