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Validity of a self-administered food frequency questionnaire for middle-aged urban cancer screenees: comparison with 4-day weighed dietary records.
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MedLine Citation:
PMID:  21963789     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
BACKGROUND: The validity of estimates of dietary intake calculated using a food frequency questionnaire (FFQ) depends on the specific population. The 138-item FFQ used in the 5-year follow-up survey for the Japan Public Health Center-based Prospective Study was initially developed for and validated in rural residents. However, the validity of estimates based on this FFQ for urban residents, whose diet and lifestyle differ from those of rural residents, has not been clarified. We examined the validity of ranking individuals according to level of dietary consumption, as estimated by this FFQ, among an urban population in Japan.
METHODS: Among 896 candidates randomly selected from examinees of cancer screening provided by the National Cancer Center, Japan, 144 participated in the study. In 2007-2008, at an average 2.7 years after cancer screening, participants were asked to respond to the questionnaire and to provide 4-day weighed diet records (4d-DRs) for use as the reference intake. Spearman correlation coefficients (CCs) between the FFQ and 4d-DR estimates were calculated, after correction for intraindividual variation of 4d-DRs.
RESULTS: The median (range) deattenuated CC for men and women was 0.57 (0.23 to 0.89) and 0.47 (0.08 to 0.94), respectively, across 45 nutrients and 0.51 (0.10 to 0.98) and 0.51 (-0.36 to 0.88) for 43 food groups.
CONCLUSIONS: Although the FFQ was developed for a rural population, it provided reasonably valid measures of consumption for many nutrients and food groups in middle-aged screenees living in urban areas in Japan.
Authors:
Ribeka Takachi; Junko Ishihara; Motoki Iwasaki; Satoko Hosoi; Yuri Ishii; Shizuka Sasazuki; Norie Sawada; Taiki Yamaji; Taichi Shimazu; Manami Inoue; Shoichiro Tsugane
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Publication Detail:
Type:  Comparative Study; Journal Article; Research Support, Non-U.S. Gov't; Validation Studies     Date:  2011-10-01
Journal Detail:
Title:  Journal of epidemiology / Japan Epidemiological Association     Volume:  21     ISSN:  1349-9092     ISO Abbreviation:  J Epidemiol     Publication Date:  2011  
Date Detail:
Created Date:  2011-11-07     Completed Date:  2012-01-18     Revised Date:  2014-02-05    
Medline Journal Info:
Nlm Unique ID:  9607688     Medline TA:  J Epidemiol     Country:  Japan    
Other Details:
Languages:  eng     Pagination:  447-58     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Adult
Aged
Diet / statistics & numerical data*
Diet Records
Diet Surveys*
Female
Humans
Japan
Male
Mass Screening
Middle Aged
Neoplasms / diagnosis
Questionnaires*
Reproducibility of Results
Urban Population*
Comments/Corrections

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

Full Text
Journal Information
Journal ID (nlm-ta): J Epidemiol
Journal ID (iso-abbrev): J Epidemiol
Journal ID (publisher-id): JE
ISSN: 0917-5040
ISSN: 1349-9092
Publisher: Japan Epidemiological Association
Article Information
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© 2011 Japan Epidemiological Association.
open-access:
Received Day: 30 Month: 11 Year: 2010
Accepted Day: 20 Month: 6 Year: 2011
Electronic publication date: Day: 5 Month: 11 Year: 2011
epreprint publication date: Day: 1 Month: 10 Year: 2011
collection publication date: Year: 2011
Volume: 21 Issue: 6
First Page: 447 Last Page: 458
PubMed Id: 21963789
ID: 3899461
DOI: 10.2188/jea.JE20100173
Publisher Id: JE20100173

Validity of a Self-Administered Food Frequency Questionnaire for Middle-Aged Urban Cancer Screenees: Comparison With 4-Day Weighed Dietary Records Alternate Title:Validity of Self-Administered FFQ for Urban Residents
Ribeka Takachi12
Junko Ishihara13
Motoki Iwasaki1
Satoko Hosoi1
Yuri Ishii1
Shizuka Sasazuki1
Norie Sawada1
Taiki Yamaji1
Taichi Shimazu1
Manami Inoue1
Shoichiro Tsugane1
1Epidemiology and Prevention Division, Research Center for Cancer Prevention and Screening, National Cancer Center, Tokyo, Japan
2Department of Community Preventive Medicine, Division of Social and Environmental Medicine, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
3Department of Nutrition Management, Sagami Women’s University, Kanagawa, Japan
Correspondence: Address for correspondence. Motoki Iwasaki, MD, PhD, Epidemiology and Prevention Division, Research Center for Cancer Prevention and Screening, National Cancer Center, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045 Japan (e-mail: moiwasak@ncc.go.jp).

INTRODUCTION

Accuracy in measuring individual dietary intake is an important issue in the analysis and evaluation of results from epidemiologic studies of the association between diet and disease. Food frequency questionnaires (FFQs) provide a view of usual food or nutrient intake over time and have been developed and validated in target populations of epidemiologic studies.1 Because the foods listed in an FFQ are selected according to their percentage contribution to the total consumption of nutrients among representatives of the target population for whom the FFQ is to be used, they might not necessarily reflect the foods eaten by a different population. Further, accuracy in remembering foods consumed appears to differ by education level and the degree of interest in diet.1 The validity of FFQ estimates of dietary intake therefore appears to depend on the specific population.

The FFQ used for the Japan Public Health Center-based Prospective Study 5-year follow-up survey was developed for use with residents of rural cohort areas.2 Of these resident, 27% worked in management, clerical, sales, or services, and 21% were employed in the agriculture, forestry, and fisheries sector.3 Further, the FFQ was validated among subsamples of these rural residents.46 It is therefore unclear whether this FFQ is accurate in estimating dietary intake among Japanese with an urbanized lifestyle. In addition, to our knowledge no such validation study has been restricted to an examination of subjects living in urban and adjacent areas.7

To confirm the suitability of this FFQ for use in epidemiologic studies of cancer screenees at the National Cancer Center, such as the participants in the Colorectal Adenoma Study in Tokyo, we evaluated the validity and reproducibility of ranking individuals by levels of dietary consumption—as estimated by this FFQ after minor modification—as a means of assessing dietary intake among middle-aged urban cancer screenees.8


METHODS
Study setting and participants

The study participants were selected from adults who underwent cancer screening at the Research Center for Cancer Prevention and Screening, National Cancer Center, “Japan from January 2004 through July 2006. Eligibility criteria were age between 40 and 69 years, residence in metropolitan Tokyo, and no previous or present diagnosis of cancer, cardiovascular disease, or diabetes mellitus. Eligible subjects were stratified by sex and age (40–49, 50–59, and 60–69 years) and randomly numbered for recruiting priority.

Among the 896 invited candidates, 187 (response rate: 20.9%) agreed to participate in the study. After excluding those who could not attend the study orientation, 144 participated in the study. As an incentive to participate, participants received a report of their results regarding the consumption of energy and nutrients based on 4-day dietary records, a small gift (an instrument for measuring the salt concentration of soup), and a free invitation to attend a class on healthful cooking. The study was approved by the Institutional Review Board of the National Cancer Center, Tokyo, Japan. All participants provided their written informed consent for participation, at the study orientation.

Data collection

The reference intake was 4-day weighed diet records (4d-DRs), which were obtained over 4 consecutive days during the period from May 2007 through April 2008. Before the start of data collection, all participants were invited to attend the study orientation, where the 4d-DR procedure was explained by trained dietitians. The self-administered FFQ was first administered during 2004–2006 at the time of cancer screening (FFQ0) and then during 2007–2008 at the orientation session (FFQ1).

Dietary assessment

The 4d-DR included 3 weekdays and 1 weekend day and was used as the reference method. Food portions were measured by each participant during meal preparation using supplied digital scales and measuring spoons and cups. For foods purchased or consumed outside the home, the participants were instructed to record the approximate quantity of all foods in the meal and/or the names of the product and company. Daily weighed records were faxed to the study office at the Research Center for Cancer Prevention and Screening, National Cancer Center on the morning after completion of that day’s record. Trained dietitians checked the record with the examinee by telephone and coded the foods and weights. Stores and restaurants were asked about the recipes of certain meals eaten outside the home.

The FFQ consisted of 138 food and beverage items and 9 frequency categories, which ranged from almost never to 7 or more times per day (or to 9 glasses per day, for beverages), and asked about the usual consumption of listed foods during the previous year. The food list, which was initially developed for the Japan Public Health Center-based Prospective Study,2 was modified for a middle-aged urban population as follows: 11 foods mainly consumed in specific areas (Okinawa and Nagano) or at specific times were excluded (luncheon meats, vivipara, qing-geng-cai [bok choy], leaf mustard, bitter gourd, chard, loofah, mugwort, yushi-tofu [soft, boiled tofu], calcium beverages, and beta carotene beverages), and 11 foods consumed throughout the year in urban areas were added (beef, stir-fried; chicken, stir-fried; chicken, stew; low-fat milk; Japanese amberjack; Welsh onion; eggplant; edible burdock; konnyaku foods [devil’s tongue]; and jam, strawberry or marmalade). Portion size was specified for each food item, using 3 standard sizes: medium (the standard amount), small (50% smaller), and large (50% larger).

Intakes of energy, 45 nutrients, and 43 food groups were calculated using the Standardized Tables of Food Composition, Fifth revised edition9,10 and a specially developed food composition table for isoflavones and lycopene in Japanese foods.11,12 We collapsed the individual food items into 18 predefined food groups according, to the Food Composition Tables, and 25 stream-specific subgroups. The grouping scheme for subgroups, eg, cruciferous vegetables and red meat, was based on the similarity of nutrient profiles or culinary usage among the foods and was somewhat similar to that used in other studies.

Statistical analysis

The mean intake of each nutrient and food group estimated using the FFQ1 was compared to that estimated using the 4d-DR among the 143 participants who completed both. Percentage differences were calculated for each nutrient and food group by dividing the difference in intake on the FFQ1 from that on the 4d-DR by those using the 4d-DR. To determine the validity of the FFQ, Spearman rank correlation coefficients (CCs) between intake estimates of the FFQ1 and 4d-DR were calculated for crude and energy-adjusted values. Regression coefficients between nutrient intakes according to the FFQ1 and 4d-DR were calculated for energy-adjusted values to examine the degree of attenuation in a diet–disease association in a hypothetical study using the FFQ.1 A residual model was used for energy adjustment.1 We corrected the observed CCs for the attenuating effect of random intraindividual error from the usual intake of each energy and nutrient and each food group. The deattenuated value was corrected using the ratios of the within- to between-individual variances based on the 4-day DRs according to the following formula:

[Formula ID: e]
deattenuated CCx=en-CCx*SQRT(1+λx/n),
where the observed en-CCx is the correlation in energy-adjusted value for nutrient x, λx is the ratio of within- to between-individual variance, and n is the number of dietary records (4 days).1 To measure the validity of categorization, we computed the number of participants classified into the same, adjacent, and extreme categories by joint classification according to both quintiles using the FFQ1 and the 4d-DR. For reproducibility, CCs between the FFQ1 and FFQ0 were calculated for crude and energy-adjusted values for the 144 participants who completed both FFQs. We confirmed the cumulative percentage among the top 20 foods for energy, because food variety was important in confirming the extent to which the list of FFQ items could be covered. Percentages of the sum of energy by individual foods eaten to total energy during the 4 days were also calculated. All analyses were performed using SAS Version 9.1 (SAS Institute Inc., Cary, NC).


RESULTS
Participants in the validation study

Age distribution (40s, 50s, 60s) at recruitment (2004–2006) was n = 11, 29, and 29, respectively, for men and n = 16, 30, and 29 for women. Mean body mass index (standard deviation) for men and women was 23.5 (2.5) and 21.5 (2.5), respectively. Overall, 51% of the participants were employed in management, clerical, sales, or services, and 2% worked in agriculture, forestry, or fisheries.

Mean intakes and FFQ validity

Table 1 shows daily intakes of energy and 45 nutrients, as assessed by 4d-DR and FFQ1, percentage differences between FFQ1 and the 4d-DR, and their correlations among men and women. Although estimated intake levels for energy were very similar between the 2 methods (difference: −6% for men, 2% for women), the percentage difference in nutrient intake between the 4d-DR and FFQ1 varied from −35% and −20% for beta-carotene to +99% and +198% for cryptoxanthin in men and women, respectively. The CCs of the crude values varied from 0.12 for retinol equivalents to 0.71 for daidzein in men and from 0.10 for polyunsaturated fatty acid to 0.57 for vitamin K in women. The median across the 45 nutrients was 0.43 for both men and women. After energy adjustment and deattenuation, the median CC improved to 0.57 in men and 0.47 in women. The regression coefficient for nutrient intake varied from 0.16 for retinol equivalents to 0.61 for copper in men and from 0.05 for cryptoxanthin to 0.63 for pantothenic acid in women (data not shown).

Table 2 shows daily intakes of 43 food groups assessed by the 4d-DR and FFQ1, the percentage difference between FFQ1 and 4d-DR, and their correlations among men and women. The percent difference in intakes between the 4d-DR and FFQ1 varied from −83% and −86% for seasonings and spices in men and women, respectively, to +111% for other cereals in men and +153% for citrus fruit in women. The CCs of the crude values varied from 0.04 and −0.28 for seasonings to 0.81 and 0.82 for coffee in men and women, respectively. The medians across 43 food groups for men and women were 0.45 and 0.35, respectively. After energy adjustment and deattenuation, the median CC slightly improved to 0.51 (varying from 0.10 for seasonings to 0.98 for noodles) in men and 0.51 (varying from −0.36 for seasonings to 0.88 for coffee) in women.

Joint classification by quintile

We conducted further analysis to compare FFQ1 with the 4d-DR based on joint classification by quintile. Most nutrients and food groups were classified into the opposite extreme categories by 5% or less of men or women, with a corresponding median value for men and women of 1% and 3%, respectively, for nutrients, and of 3% and 3%, respectively, for food groups (Supplemental Tables 1 and 2). In contrast, retinol for men and women showed a relatively high percentage of extreme categories by joint classification (6% and 12%, respectively) and a relatively low CC (0.32 and 0.11, respectively) and regression coefficient (0.18 and 0.15, respectively). Further, cryptoxanthin for women showed a relatively low percentage of the same and adjacent categories (53%) and a relatively low CC (0.07) and regression coefficient (0.05).

Reproducibility

We also examined the reproducibility of dietary intake estimated by 2 identical FFQs (FFQ0 and FFQ1) administered at an average interval of 2.7 years (range 1.3–4.0 years). CCs for nutrient intakes in the crude values varied from 0.54 for retinol to 0.80 for phosphorus (median r = 0.70) in men and from 0.48 for cholesterol and 0.72 for vitamin C (median r = 0.61) in women. With regard to the food groups, CC in the crude values varied from 0.35 for other cereals to 0.75 for coffee (median r = 0.64) in men and from 0.48 for red meat and 0.80 for coffee (median r = 0.63) in women (Supplemental Tables 3 and 4).

Percentage contributions of the top 20 foods to total energy

Finally, we conducted an additional analysis of the cumulative percentage contributions of the top 20 foods for energy, based on the 4d-DRs, to assess the foods listed in the FFQ. The cumulative percentage of the top 20 foods for energy was 44.0% and 41.0% for men and women, respectively (Supplemental Table 5).


DISCUSSION

We examined the validity of ranking middle-aged urban-dwelling cancer screenees in Japan by level of dietary intake using an FFQ, with 4-day DR data as the reference method. The FFQ was initially developed and validated in rural populations. As compared with reference intakes, differences in mean absolute consumption based on the FFQ varied and tended to be underestimated. However, using the FFQ, dietary assessment of many nutrients and food groups showed moderate validity and reproducibility in ranking urban residents, whose diet and lifestyle might differ from those of rural residents.

In comparison with 4d-DRs corrected for intraindividual variance, for most nutrients, the validity of the FFQ was similar to or better than that observed in a comparison with 28-day weighed diet records among the rural residents for which the FFQ was developed.6 In that initial validation study, median CCs for energy and 45 nutrients were 0.43 and 0.39 for men and women, respectively, and 0.38 and 0.32 for 19 main food groups. Evaluation of diet might be complicated by the apparently wider variety of foods eaten by urban as compared with rural residents in Japan (percent energy from cereal areas among the former was less than that among the latter13), as has been seen in China14 and Morocco,15 although we saw no large difference in the validity of intakes, as estimated by the FFQ, between urban and rural populations in the present study.

Wakai7 reviewed 21 validation studies of FFQs developed in Japan and reported a median CC for energy intake of 0.46 (range 0.20 to 0.87) and a median CC among the 21 studies ranging from 0.22 (n-6 PUFA) to 0.58 (calcium) for energy and 24 nutrients. As compared with the median CCs among the 21 studies for energy and 24 nutrients and 17 food groups, the CCs for the many nutrients and food groups evaluated in the present study were not substantially different or higher.7 Attenuation caused by measurement error may be unavoidable in studies that use FFQs to investigate diet–disease associations. For example, based on a true relative risk of 2.0, if the regression coefficient of intakes according to an FFQ and DR varies from 0.6 to 0.2, the corresponding relative risk is further attenuated from 1.52 to 1.15.1 A similar attenuation might be unavoidable in any examination that uses the present FFQ to assess diet–disease associations. Further investigation will be needed to examine the effects of measurement error on diet–disease associations in an actual dataset.

The CC for energy intake among women in this study (deattenuated CC: r = 0.34) was lower than the median of 21 previous studies. Further, the CCs of intakes based on the FFQ appeared to be lower in women than in men for most of the energy and nutrients examined (median deattenuated CC: 0.57 and 0.47 for men and women, respectively). This lower correlation in women than men has been previously observed in Japanese and Western populations.7,16 Sex differences in validity might be partly due to disparities in the ease of response to the structured questionnaire that result from differences between men and women in their interest in dietary habits.4 Moreover, we also found that the cumulative percentage among the top 20 foods for energy was lower for women than for men and that it was also lower than among subjects during the development of the initial FFQ (men: 63.9%, women: 56.3%).17 These results suggest that the lower validity for energy intake among women is partly attributable to a lower contribution to energy by individual foods in women than in men, as was seen among subjects during the development of the initial FFQ.

Our study has several potential limitations. First, the response rate was not necessarily high, although the participants were randomly chosen and recruited from among cancer screenees. Selection bias, eg, a higher proportion of health-conscious subjects than in the actual population, was likely present, and thus the possibility of overestimating the validity of the FFQ cannot be ruled out. This response rate is nevertheless reasonable considering the burden posed by studies such as this. Second, reference intakes were based on 4-day values, versus the 28-day values used for the initial validation study of the FFQ.46 A simple comparison of CCs might have been difficult, even though the present CCs were corrected for intraindividual variance. Moreover, although the dietary records were completed on consecutive days (ie, in the same season), the FFQ inquired about the previous year. In addition, responses to the FFQ might have depended on the season,18 and FFQ1 was conducted in the season during which the dietary record was done. Thus, the possibility that validity might have been overestimated cannot be ruled out, especially for seasonal foods such as fruit and vegetables. Third, in the examination of reproducibility, we were unable to consider the “true” change in diet. Although we would have liked to examine the effects of random variation in response to the FFQ, the effects of such variation and the “true” change of diet could not be readily separated, and both might have attenuated the reproducibility of the FFQ.1 Therefore, the reproducibility of this FFQ (in random variation in response) might have been underestimated.

In general, the advantages of FFQ-based dietary assessment are that the burden on participants is not heavy, an interviewer is unnecessary, costs are relatively low,19 and the long-term diet can be ranked. In the present study, too, the median percentages of extreme categories based on joint classification by quintile between FFQ and DR for nutrients and food groups were 1% and 3%, indicating that this FFQ is suitable for the ranking of individuals with regard to intakes of many nutrients and food groups in large-scale studies of urban populations. However, some nutrient and food group intakes estimated by this FFQ showed relatively low CCs and regression coefficients; thus, any application of this FFQ to the examination of diet–disease associations, such as investigations of retinol and cryptoxanthin, must carefully address the problem of classification.

In conclusion, these results indicate that the present FFQ, which was initially developed for rural populations, provides reasonably valid measures in ranking middle-aged cancer screenees in urban areas in Japan according to level of consumption of many nutrients and food groups.


ACKNOWLEDGMENTS

The authors would like to thank all members of the FFQ Study Group of the Research Center for Cancer Prevention and Screening, National Cancer Center for their invaluable advice and careful conduct of the study.

This work was supported by Grants-in-Aid for the Third-Term Comprehensive 10-year Strategy for Cancer Control from the Ministry of Health, Labour and Welfare of Japan, for The Japanese Society of Nutrition and Dietetics in 2006, and for Scientific Research (17015049, 20500738), and in part by the Foundation for Promotion of Cancer Research in Japan.

Conflicts of interest: None of the authors declares a personal or financial conflict of interest.


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Tables
[TableWrap ID: tbl01] Table 1.  Energy and nutrient intakes according to food frequency questionnaire 1 (FFQ1), percentage difference between FFQ1 and 4-day diet record (DR), and their correlations in men and women
  Men (n = 69) Women (n = 74)


  4-day DR FFQ1a %b Correlation coefficientc 4-day DR FFQ1a %b Correlation coefficientc






  Mean ± SD Mean ± SD Crude Energy-
adjusted
Deatte-
nuatedd
Mean ± SD Mean ± SD Crude Energy-
adjusted
Deatte-
nuatedd
Energy (kcal) 2271 ± 426 2141 ± 737 −6 0.48 0.53 1842 ± 298 1875 ± 733 2 0.29 0.34
Protein (g) 89.2 ± 15.6 76.2 ± 32.3 −15 0.31 0.55 0.67 75.0 ± 13.6 70.5 ± 32 −6 0.56 0.39 0.47
Total fat (g) 64.6 ± 14.3 64.6 ± 33.2 0 0.27 0.30 0.42 57.8 ± 16.3 63.0 ± 32.9 9 0.22 0.28 0.35
 SFA (g) 18.12 ± 4.85 20.21 ± 11.23 12 0.27 0.29 0.44 16.82 ± 5.84 20.04 ± 12.21 19 0.37 0.34 0.41
 MUFA (g) 22.63 ± 6.56 22.79 ± 13.15 1 0.31 0.28 0.38 20.34 ± 7.06 22.59 ± 12.41 11 0.26 0.39 0.49
 PUFA (g) 14.62 ± 3.21 13.38 ± 6.73 −8 0.53 0.53 0.72 12.33 ± 2.99 12.4 ± 6.01 1 0.10 0.24 0.38
  n-3 PUFA (g) 3.10 ± 1.05 2.58 ± 1.59 −17 0.26 0.34 0.56 2.48 ± 0.91 2.35 ± 1.28 −5 0.34 0.28 0.68
  n-6 PUFA (g) 11.45 ± 2.74 10.73 ± 5.43 −6 0.58 0.53 0.76 9.79 ± 2.51 9.97 ± 4.81 2 0.11 0.31 0.47
 Cholesterol (mg) 367 ± 132 303 ± 278 −18 0.31 0.39 0.51 333 ± 117 271 ± 168 −19 0.35 0.28 0.38
Carbohydrate (g) 301 ± 72.9 270.8 ± 99.2 −10 0.58 0.52 0.56 245.2 ± 46.9 245.7 ± 84.4 0 0.25 0.39 0.43

 Total dietary fiber (g) 20.3 ± 6.3 14.1 ± 6.6 −31 0.55 0.61 0.67 18.0 ± 4.6 15.3 ± 7.4 −15 0.44 0.46 0.53
  Water soluble (g) 4.7 ± 1.7 3.6 ± 1.9 −23 0.53 0.59 0.65 4.1 ± 1.2 3.8 ± 1.9 −9 0.44 0.48 0.56
  Water insoluble (g) 14.3 ± 4.6 9.9 ± 4.6 −31 0.55 0.64 0.71 13.0 ± 3.4 10.9 ± 5.3 −16 0.43 0.38 0.44
Sodium (mg) 4728 ± 1745 4269 ± 2312 −10 0.44 0.42 0.45 3943 ± 944 3920 ± 1953 −1 0.33 0.39 0.47
 Salt equivalent (g) 11.9 ± 4.4 10.8 ± 5.9 −9 0.44 0.39 0.42 9.9 ± 2.4 9.9 ± 4.9 0 0.33 0.38 0.46
Potassium (mg) 3695 ± 983 3072 ± 1208 −17 0.37 0.60 0.65 3204 ± 708 2992 ± 1318 −7 0.48 0.62 0.70
Calcium (mg) 707 ± 234 665 ± 423 −6 0.48 0.58 0.64 637 ± 204 657 ± 469 3 0.55 0.55 0.61
Magnesium (mg) 393 ± 112 317 ± 117 −19 0.43 0.53 0.58 323 ± 64 293 ± 125 −9 0.43 0.45 0.54
Phosphorus (mg) 1395 ± 296 1221 ± 512 −12 0.38 0.57 0.65 1183 ± 227 1144 ± 569 −3 0.55 0.40 0.47
Iron (mg) 11.2 ± 3.2 9.6 ± 3.8 −15 0.45 0.62 0.68 9.3 ± 2 8.8 ± 3.5 −6 0.46 0.44 0.55
Zinc (mg) 10.0 ± 2.2 8.8 ± 3.5 −12 0.40 0.53 0.65 8.7 ± 1.8 7.8 ± 3.2 −10 0.49 0.26 0.34
Copper (mg) 1.59 ± 0.41 1.35 ± 0.54 −15 0.59 0.67 0.74 1.31 ± 0.26 1.23 ± 0.47 −6 0.35 0.40 0.49
Manganese (mg) 5.03 ± 2.7 4.22 ± 1.75 −16 0.54 0.41 0.44 3.93 ± 1.31 4.35 ± 2.13 11 0.41 0.37 0.41

Retinol (µg) 318 ± 379 364 ± 308 14 0.21 0.32 0.56 348 ± 528 361 ± 274 4 0.13 0.11 0.16
Retinol Eq (µg) 749 ± 433 678 ± 383 −10 0.12 0.15 0.23 782 ± 560 754 ± 412 −4 0.35 0.24 0.33
α-carotene (µg) 542 ± 381 474 ± 387 −13 0.38 0.37 0.50 667 ± 534 632 ± 736 −5 0.51 0.53 0.78
β-carotene (µg) 4580 ± 2697 2960 ± 1854 −35 0.34 0.36 0.49 4588 ± 2281 3658 ± 2751 −20 0.54 0.53 0.70
Cryptoxanthin (µg) 539 ± 1148 1071 ± 1262 99 0.50 0.52 0.55 482 ± 668 1439 ± 1656 198 0.15 0.07 0.08
Lycopene (mg) 6583 ± 7892 4888 ± 7441 −26 0.48 0.45 0.52 4456 ± 5151 4319 ± 5617 −3 0.23 0.33 0.40
β-carotene Eq (µg) 5152 ± 2860 3731 ± 2289 −28 0.40 0.39 0.52 5194 ± 2625 4693 ± 3391 −10 0.54 0.49 0.62
Vitamin D (µg) 11.3 ± 6.5 7.9 ± 5.8 −30 0.47 0.52 0.88 9.9 ± 6.1 8.1 ± 6.2 −18 0.34 0.22 0.37
α-tocopherol (mg) 9.8 ± 3.0 8.1 ± 4.2 −17 0.26 0.41 0.48 8.6 ± 2.5 8.1 ± 4.3 −6 0.27 0.42 0.51
β-tocopherol (mg) 0.4 ± 0.1 0.4 ± 0.2 0 0.34 0.30 0.48 0.3 ± 0.1 0.4 ± 0.2 17 0.14 0.21 0.33
γ-tocopherol (mg) 13 ± 4 12 ± 6.8 −8 0.53 0.47 0.69 11.1 ± 3.5 10.9 ± 5.3 −1 0.10 0.22 0.33
δ-tocopherol (mg) 3.4 ± 1.4 3 ± 2.1 −10 0.69 0.68 0.89 2.7 ± 0.9 2.6 ± 1.2 −4 0.18 0.25 0.51
Vitamin K (µg) 345 ± 194 303 ± 306 −12 0.64 0.67 0.79 290 ± 108 270 ± 133 −7 0.57 0.61 0.94
Vitamin B1 (mg) 1.21 ± 0.38 1.01 ± 0.43 −17 0.23 0.47 0.54 1.05 ± 0.28 0.99 ± 0.45 −5 0.44 0.35 0.42
Vitamin B2 (mg) 1.71 ± 0.55 1.66 ± 0.79 −3 0.27 0.38 0.42 1.47 ± 0.37 1.58 ± 0.8 8 0.47 0.46 0.53
Niacin (mg) 24.2 ± 7.3 20.3 ± 8.6 −16 0.38 0.36 0.44 19.8 ± 5.2 19.0 ± 8.4 −4 0.44 0.26 0.32
Vitamin B6 (mg) 1.91 ± 0.55 1.57 ± 0.6 −18 0.38 0.39 0.44 1.53 ± 0.4 1.45 ± 0.63 −5 0.46 0.49 0.57
Vitamin B12 (µg) 10.8 ± 5.6 7.9 ± 5.1 −27 0.13 0.30 0.57 8.6 ± 4.6 7.2 ± 5.1 −16 0.46 0.36 0.67
Folate (µg) 512 ± 188 418 ± 176 −18 0.48 0.60 0.66 449 ± 124 433 ± 194 −3 0.48 0.35 0.41
Pantothenic acid (mg) 8.02 ± 1.9 7.66 ± 3.5 −4 0.41 0.58 0.67 6.83 ± 1.5 7.09 ± 3.15 4 0.53 0.57 0.66
Vitamin C (mg) 178 ± 82 136 ± 83 −24 0.62 0.67 0.73 156 ± 62 163 ± 96 4 0.45 0.45 0.51

Daidzein (mg) 17.14 ± 9.78 20.39 ± 20.45 19 0.71 0.66 0.84 12.81 ± 7.28 14.98 ± 8.08 17 0.49 0.49 0.79
Genistein (mg) 28.6 ± 16.27 34.13 ± 35.71 19 0.69 0.64 0.81 21.87 ± 12.3 24.84 ± 13.7 14 0.46 0.47 0.75

MEDIAN       0.43 0.52 0.57       0.43 0.39 0.47

Abbreviations: SD, standard deviation; SFA, saturated fatty acid; MUFA, monounsaturated fatty acid; PUFA, polyunsaturated fatty acid; Eq, equivalent.

aIntakes based on second FFQ, conducted in 2007–2008. bPercentage differences: (FFQ1 − DR)/DR * 100 (%). cSpearman’s rank correlation coefficients based on crude and energy-adjusted values. For men, r ≥ 0.24 = P < 0.05, r ≥ 0.31 = P < 0.01, r ≥ 0.39 = P < 0.001. For women, r ≥ 0.23 = P < 0.05, r ≥ 0.30 = P < 0.01, r ≥ 0.38 = P ≤ 0.001. dDeattenuated CCx = observed CCx * SQRT(1 + λx/n), where λx is the ratio of within- to between-individual variance for nutrient x, and n is number of dietary records; observed CCs were based on energy-adjusted values other than energy intake.


[TableWrap ID: tbl02] Table 2.  Food-group intakes according to food frequency questionnaire 1 (FFQ1), percentage difference between FFQ1 and 4-day diet record (DR), and their correlations in men and women
  Men (n = 69) Women (n = 74)


  4-day DR FFQ1a %b Correlation coefficientc 4-day DR FFQ1a %b Correlation coefficientc






  Mean ± SD
(g)
Mean ± SD
(g)
Crude Energy-
adjusted
Deatte-
nuatedd
Mean ± SD
(g)
Mean ± SD
(g)
Crude Energy-
adjusted
Deatte-
nuatedd
Cereals 447 ± 173 510 ± 215 14 0.67 0.45 0.51 332 ± 78 425 ± 153 28 0.29 0.33 0.41
 Rice 306 ± 169 351 ± 173 15 0.72 0.42 0.51 210 ± 85 259 ± 110 24 0.49 0.43 0.59
 Bread 47 ± 38 40 ± 57 −13 0.66 0.67 0.80 42 ± 27 53 ± 77 26 0.60 0.68 0.87
 Noodles 85 ± 71 97 ± 88 15 0.53 0.52 0.98 72 ± 49 95 ± 72 33 0.39 0.42
 Other cereals 10 ± 11 21 ± 34 111 0.15 0.15 0.19 8 ± 11 17 ± 24 103 0.26 0.26 0.33
Potatoes and starches 46 ± 33 27 ± 21 −41 0.29 0.32 0.49 44 ± 32 38 ± 29 −13 0.09 0.25 0.39
Sugar 9 ± 8 2 ± 4 −80 0.36 0.25 0.30 8 ± 8 1 ± 4 −82 0.07 0.06 0.07
Pulses 102 ± 106 97 ± 144 −6 0.59 0.53 0.66 72 ± 44 67 ± 44 −6 0.27 0.30 0.45
Nuts and seeds 7 ± 11 3 ± 4 −61 0.31 0.30 0.40 5 ± 7 3 ± 9 −33 0.01 −0.06 −0.09
Vegetables 403 ± 180 218 ± 145 −46 0.48 0.48 0.55 354 ± 125 245 ± 175 −31 0.39 0.45 0.52
 Green and yellow vegetables 194 ± 134 110 ± 90 −43 0.43 0.47 0.59 170 ± 86 114 ± 87 −33 0.38 0.41 0.57
 White vegetables 209 ± 102 108 ± 96 −48 0.53 0.50 0.68 184 ± 75 131 ± 128 −29 0.39 0.41 0.57
  Pickled vegetables 21 ± 51 15 ± 21 −32 0.43 0.37 0.42 18 ± 21 21 ± 50 21 0.32 0.34 0.45
  Cruciferous vegetables 91 ± 59 54 ± 68 −41 0.63 0.64 0.82 87 ± 64 55 ± 41 −37 0.46 0.45 0.54
  Green, leafy vegetable 43 ± 43 20 ± 20 −54 0.33 0.28 0.37 38 ± 23 21 ± 14 −43 0.26 0.29 0.41
  Yellow vegetables 128 ± 113 78 ± 83 −39 0.49 0.52 0.63 105 ± 73 79 ± 76 −25 0.36 0.42 0.51
  Other vegetables 121 ± 73 54 ± 38 −56 0.31 0.36 0.51 109 ± 55 71 ± 73 −35 0.34 0.37 0.56
Fruits 193 ± 160 209 ± 184 8 0.60 0.64 0.69 184 ± 113 255 ± 196 38 0.40 0.55 0.63
 Citrus fruit 49 ± 75 81 ± 88 67 0.46 0.46 0.51 43 ± 49 109 ± 139 153 0.23 0.18 0.20
 Other fruit 143 ± 126 126 ± 108 −12 0.54 0.57 0.75 140 ± 104 144 ± 103 3 0.31 0.49 0.85
Fungi 18 ± 17 11 ± 11 −36 0.48 0.48 0.57 23 ± 22 14 ± 12 −38 0.42 0.38 0.46
Algae 15 ± 22 8 ± 7 −43 0.18 0.17 0.22 10 ± 10 9 ± 8 −9 0.35 0.32 0.47
Fish and shellfish 115 ± 53 78 ± 66 −32 0.40 0.47 0.69 89 ± 40 73 ± 60 −18 0.44 0.35 0.57
Meats 72 ± 43 62 ± 57 −15 0.43 0.48 0.70 65 ± 38 55 ± 35 −17 0.35 0.26 0.36
 Processed meat 13 ± 16 6 ± 8 −52 0.46 0.45 0.63 13 ± 15 7 ± 7 −48 0.30 0.33 0.47
 Red meat 40 ± 30 42 ± 43 5 0.36 0.41 0.74 36 ± 29 32 ± 23 −11 0.45 0.36 0.53
 Poultry 19 ± 26 13 ± 18 −30 0.25 0.25 0.38 16 ± 19 15 ± 13 −5 0.27 0.22 0.36
Eggs 36 ± 23 32 ± 55 −11 0.50 0.46 0.67 33 ± 19 25 ± 30 −24 0.35 0.35 0.53
Milk and dairy products 176 ± 147 275 ± 305 56 0.62 0.58 0.66 174 ± 110 257 ± 337 48 0.70 0.62 0.76
 High-fat milk 87 ± 96 99 ± 157 13 0.47 0.44 0.50 95 ± 91 120 ± 201 26 0.64 0.59 0.69
 Low-fat milk 89 ± 137 177 ± 286 98 0.62 0.56 0.60 79 ± 83 137 ± 207 74 0.68 0.61 0.70
Fats and oils 11 ± 6 12 ± 8 12 0.40 0.35 0.45 10 ± 6 12 ± 8 24 0.38 0.52 0.73
 Butter 2 ± 2 1 ± 2 −49 0.32 0.34 0.50 2 ± 2 1 ± 4 −12 0.35 0.35 0.56
 Margarine and oils 9 ± 5 11 ± 8 25 0.31 0.26 0.35 9 ± 6 11 ± 6 31 0.29 0.42 0.57
Confectionaries 29 ± 28 23 ± 32 −19 0.28 0.37 0.45 37 ± 30 37 ± 46 1 0.34 0.32 0.43
 Japanese confectionery 11 ± 15 8 ± 15 −29 0.21 0.24 0.33 15 ± 23 15 ± 20 −1 0.09 0.04 0.05
 Western confectionery 18 ± 24 15 ± 21 −13 0.34 0.41 0.50 21 ± 21 22 ± 32 2 0.26 0.24 0.32
Alcoholic beverages 219 ± 276 263 ± 281 20 0.80 0.80 0.88 76 ± 151 90 ± 187 19 0.65 0.57 0.60
Nonalcoholic beverages 749 ± 772 863 ± 699 15 0.45 0.37 0.40 617 ± 434 888 ± 621 44 0.33 0.33 0.35
 Green tea 386 ± 738 519 ± 427 35 0.68 0.67 0.72 246 ± 220 603 ± 560 145 0.46 0.42 0.45
 Coffee 176 ± 204 199 ± 281 13 0.81 0.80 0.84 167 ± 175 157 ± 155 −6 0.82 0.82 0.88
 Other beverage 210 ± 260 144 ± 358 −31 0.43 0.45 0.49 268 ± 359 128 ± 190 −52 0.31 0.32 0.35
Seasonings and spices 138 ± 100 23 ± 15 −83 0.04 0.08 0.10 142 ± 111 20 ± 14 −86 −0.28 −0.31 −0.36

MEDIAN       0.45 0.45 0.51       0.35 0.35 0.51

Abbreviation: SD, standard deviation.

aIntakes based on second FFQ, conducted in 2007–2008. bPercentage differences: (FFQ1 − DR)/DR * 100 (%). cSpearman’s rank correlation coefficients based on crude and energy-adjusted values. For men, r ≥ 0.24 = P < 0.05, r ≥ 0.31 = P < 0.01, r ≥ 0.39 = P < 0.001. For women, r ≥ 0.23 = P < 0.05, r ≥ 0.30 = P < 0.01, r ≥ 0.38 = P ≤ 0.001. dDeattenuated CCx = observed CCx * SQRT(1 + λx/n), where λx is the ratio of within- to between-individual variance for nutrient x, and n is number of dietary records; observed CCs were based on energy-adjusted values other than energy intake.

—: not applicable for calculation.


[TableWrap ID: tbl11] Supplementary Table 1.  Comparison of food frequency questionnaire 1 (FFQ1) with 4-day diet record for energy-adjusted nutrients, based on joint classification by quintile (%)
  Men (n = 69) Women (n = 74)


  Same
category
Same and
adjacent
category
Extreme
category
Same
category
Same and
adjacent
category
Extreme
category
Energy 35 71 1a 28 64 5a
Protein 35 77 1 23 60 1
Total fat 28 61 1 31 70 4
 SFA 35 65 6 26 65 5
 MUFA 22 59 4 31 68 0
 PUFA 30 67 0 28 62 4
  n-3 PUFA 26 59 3 27 58 3
  n-6 PUFA 38 73 0 26 66 5
 Cholesterol 25 67 1 28 62 4
Carbohydrate 44 70 1 30 73 4

 Total dietary fiber 39 78 1 26 69 1
  Water soluble 35 80 1 31 70 1
  Water insoluble 33 84 0 24 64 1

Sodium 36 68 3 32 57 1
 Salt equivalent 36 68 3 27 61 1
Potassium 38 75 0 39 78 1
Calcium 28 73 0 30 68 0
Magnesium 39 73 0 37 65 1
Phosphorus 35 77 0 35 70 1
Iron 36 80 1 31 72 3
Zinc 38 74 1 23 61 3
Copper 36 80 0 24 65 1
Manganese 28 67 3 31 69 4

Retinol 33 62 6 23 62 12
Retinol Eq 28 62 9 26 62 4
α-carotene 38 68 3 37 70 0
β-carotene 33 65 6 35 70 0
Cryptoxanthin 33 78 3 18 53 4
Lycopene 38 75 4 31 70 5
β-carotene Eq 33 67 4 28 72 1
Vitamin D 36 75 1 22 58 3
α-tocopherol 29 61 1 22 69 3
β-tocopherol 20 67 4 19 57 4
γ-tocopherol 28 68 3 20 68 8
δ-tocopherol 42 80 0 18 68 4
Vitamin K 32 83 0 27 73 0
Vitamin B1 29 74 1 32 64 3
Vitamin B2 30 65 4 26 70 0
Niacin 30 65 3 27 64 5
Vitamin B6 33 67 1 41 69 0
Vitamin B12 22 65 4 30 65 3
Folate 32 70 0 26 66 4
Pantothenic acid 45 78 1 42 73 0
Vitamin C 39 87 0 26 68 0

Daidzein 30 81 0 27 76 1
Genistein 32 80 0 31 70 1

MEDIAN 33 70 1 28 68 3

Abbreviations: SFA, saturated fatty acid; MUFA, monounsaturated fatty acid; PUFA, polyunsaturated fatty acid; Eq, equivalent.

aJoint classification for energy intake was calculated by using crude values.


[TableWrap ID: tbl12] Supplementary Table 2.  Comparison of food frequency questionnaire 1 (FFQ1) with 4-day diet record for energy-adjusted food groups based on joint classification by quintile (%)
  Men (n = 69) Women (n = 74)


  Same
category
Same and
adjacent
category
Extreme
category
Same
category
Same and
adjacent
category
Extreme
category
Cereals 26 70 0 32 68 4
 Rice 30 71 3 42 72 3
 Bread 30 80 0 41 76 0
 Noodles 29 68 0 37 72 5
 Other cereals 19 52 4 24 55 5
Potatoes and starches 30 67 1 20 64 3
Sugar 26 57 3 16 55 7
Pulses 38 74 3 30 62 3
Nuts and seeds 26 58 0 15 54 10
Vegetables 26 70 1 27 73 3

 Green and yellow vegetables 45 68 4 27 70 0
 White vegetables 25 77 1 27 68 1
  Pickled vegetables 30 68 4 30 68 5

  Cruciferous vegetables 42 80 1 31 64 1
  Green, leafy vegetable 28 67 6 27 61 1
  Yellow vegetables 30 77 3 27 73 1
  Other vegetables 19 64 1 28 65 4
Fruits 49 81 1 38 73 0
 Citrus fruit 36 77 3 23 60 5
 Other fruit 36 77 1 30 69 1
Fungi 33 71 3 24 62 3
Algae 33 58 6 22 64 3
Fish and shellfish 28 71 1 23 61 3

Meats 38 78 6 28 66 7
 Processed meat 28 67 1 32 72 3
 Red meat 29 71 6 32 62 1
 Poultry 25 61 3 28 54 5
Eggs 36 74 1 26 61 3
Milk and dairy products 41 78 3 35 78 0
 High-fat milk 41 67 4 42 87 3
 Low-fat milk 36 78 3 42 82 3
Fats and oils 30 61 4 39 72 0
 Butter 32 64 6 34 70 5
 Margarine and oils 29 61 4 34 66 1
Confectionaries 20 67 1 28 62 3
 Japanese confectionery 22 64 4 14 55 5
 Western confectionery 32 65 0 24 60 5
Alcoholic beverages 46 91 0 42 72 0
Nonalcoholic beverages 26 64 1 22 65 3
 Green tea 48 80 0 27 65 0
 Coffee 45 93 0 50 91 0
 Other beverage 29 68 0 26 65 4
Seasonings and spices 16 49 4 16 42 12

MEDIAN 30 68 3 28 65 3

[TableWrap ID: tbl13] Supplementary Table 3.  Spearman rank correlation coefficients between 2 food frequency questionnaires, administered at an average interval 2.7 years, for estimated nutrient intakes
  Men (n = 69) Women (n = 75)


  Crude Energy-
adjusted
Crude Energy-
adjusted
Energy 0.72 0.59
Protein 0.76 0.65 0.59 0.55
Total fat 0.73 0.51 0.62 0.40
 SFA 0.75 0.54 0.66 0.55
 MUFA 0.71 0.47 0.62 0.41
 PUFA 0.68 0.62 0.54 0.44
  n-3 PUFA 0.64 0.52 0.63 0.59
  n-6 PUFA 0.68 0.59 0.52 0.42
 Cholesterol 0.76 0.50 0.48 0.46
Carbohydrate 0.65 0.77 0.57 0.43

 Total dietary fiber 0.70 0.74 0.62 0.66
  Water soluble 0.65 0.65 0.62 0.62
  Water insoluble 0.70 0.75 0.64 0.64

Sodium 0.71 0.52 0.66 0.58
 Salt equivalent 0.71 0.52 0.66 0.59
Potassium 0.73 0.74 0.65 0.76
Calcium 0.77 0.72 0.62 0.56
Magnesium 0.73 0.75 0.61 0.74
Phosphorus 0.80 0.74 0.61 0.51
Iron 0.70 0.66 0.61 0.69
Zinc 0.71 0.65 0.58 0.67
Copper 0.65 0.69 0.59 0.70
Manganese 0.72 0.75 0.69 0.70

Retinol 0.54 0.39 0.49 0.48
Retinol Eq 0.61 0.45 0.53 0.44
α-carotene 0.65 0.60 0.68 0.63
β-carotene 0.68 0.64 0.68 0.67
Cryptoxanthin 0.68 0.64 0.64 0.72
Lycopene 0.59 0.52 0.49 0.37
β-carotene Eq 0.68 0.64 0.69 0.67
Vitamin D 0.63 0.43 0.67 0.54
α-tocopherol 0.63 0.53 0.58 0.58
β-tocopherol 0.67 0.54 0.52 0.41
γ-tocopherol 0.64 0.51 0.51 0.46
δ-tocopherol 0.68 0.64 0.59 0.58
Vitamin K 0.65 0.67 0.55 0.58
Vitamin B1 0.74 0.61 0.59 0.51
Vitamin B2 0.74 0.62 0.67 0.67
Niacin 0.71 0.50 0.67 0.55
Vitamin B6 0.72 0.54 0.65 0.66
Vitamin B12 0.69 0.57 0.66 0.56
Folate 0.70 0.69 0.67 0.77
Pantothenic acid 0.71 0.76 0.61 0.69
Vitamin C 0.78 0.76 0.72 0.77

Daidzein 0.61 0.63 0.60 0.58
Genistein 0.61 0.63 0.60 0.58

MEDIAN 0.70 0.63 0.61 0.58

Abbreviations: SFA, saturated fatty acid; MUFA, monounsaturated fatty acid; PUFA, polyunsaturated fatty acid; Eq, equivalent.

For men, r ≥ 0.24 = P < 0.05, r ≥ 0.31 = P < 0.01, r ≥ 0.39 = P < 0.001. For women, r ≥ 0.23 = P < 0.05, r ≥ 0.30 = P < 0.01, r ≥ 0.38 = P ≤ 0.001.


[TableWrap ID: tbl14] Supplementary Table 4.  Spearman rank correlation coefficients between 2 food frequency questionnaires, administered at an average interval 2.7 years, for estimated food-group intakes
  Men (n = 69) Women (n = 75)


  Crude Energy-
adjusted
Crude Energy-
adjusted
Cereals 0.63 0.69 0.49 0.55
 Rice 0.64 0.62 0.65 0.63
 Bread 0.73 0.70 0.55 0.60
 Noodles 0.64 0.60 0.49 0.51
 Other cereals 0.35 0.38 0.65 0.64
Potatoes and starches 0.60 0.60 0.65 0.60
Sugar 0.74 0.68 0.65 0.50
Pulses 0.45 0.51 0.65 0.56
Nuts and seeds 0.42 0.32 0.63 0.60
Vegetables 0.63 0.63 0.70 0.64
 Green and yellow vegetables 0.64 0.58 0.61 0.51
 White vegetables 0.69 0.62 0.69 0.62
  Pickled vegetables 0.74 0.70 0.76 0.67
  Cruciferous vegetables 0.65 0.60 0.50 0.46
  Green, leafy vegetables 0.57 0.53 0.57 0.61
  Yellow vegetables 0.60 0.55 0.60 0.46
  Other vegetables 0.71 0.65 0.70 0.58
Fruits 0.70 0.67 0.63 0.69
 Citrus fruit 0.67 0.61 0.62 0.66
 Other fruit 0.66 0.64 0.61 0.55
Fungi 0.73 0.75 0.60 0.60
Algae 0.65 0.65 0.57 0.56
Fish and shellfish 0.62 0.39 0.70 0.62
Meats 0.69 0.57 0.54 0.52
 Processed meat 0.67 0.62 0.71 0.70
 Red meat 0.63 0.53 0.48 0.47
 Poultry 0.54 0.36 0.50 0.49
Eggs 0.66 0.53 0.50 0.51
Milk and dairy products 0.73 0.69 0.61 0.52
 High-fat milk 0.49 0.45 0.71 0.66
 Low-fat milk 0.68 0.65 0.50 0.52
Fats and oils 0.63 0.53 0.63 0.51
 Butter 0.57 0.45 0.63 0.55
 Margarine and Oils 0.61 0.54 0.64 0.51
Confectionaries 0.63 0.60 0.63 0.64
 Japanese 0.56 0.57 0.60 0.62
 Western 0.66 0.62 0.60 0.55
Alcoholic beverages 0.86 0.86 0.76 0.68
Non-alcoholic beverages 0.61 0.61 0.68 0.63
 Green tea 0.68 0.66 0.75 0.67
 Coffee 0.75 0.69 0.80 0.76
 Other beverage 0.45 0.48 0.56 0.52
Seasonings and spices 0.69 0.70 0.53 0.48

MEDIAN 0.64 0.61 0.63 0.58

For men, r ≥ 0.24 = P < 0.05, r ≥ 0.31 = P < 0.01, r ≥ 0.39 = P < 0.001. For women, r ≥ 0.23 = P < 0.05, r ≥ 0.30 = P < 0.01, r ≥ 0.38 = P ≤ 0.001.


[TableWrap ID: tbl15] Supplementary Table 5.  Cumulative percentage contribution of the top 20 foods to energy intake, as assessed by 4-day diet record
Code Food kcal/day Cumulative
percent
Men (n = 69)      
1088 Rice, Paddy rice grain, Well-milled rice 422.9 18.6
1026 Breads, White table bread 61.1 21.3
16006 Fermented alcoholic beverages, Beer, pale 52.8 23.6
12004 Hen’s eggs, whole, raw 51.0 25.9
13003 Liquid milks, Ordinary liquid milk 49.5 28.0
1085 Rice, Paddy rice grain, Brown rice 45.8 30.1
14006 Fats and oils, Vegetable oil, blend 44.7 32.0
4046 Natto (Fermented soybean), Itohiki-natto 31.7 33.4
1048 Chinese noodles, Wet form, boiled 28.8 34.7
16015 Distilled alcoholic beverages, Shochu, 25% alcohol 25.2 35.8
13025 Yogurt, Whole milk, unsweetened 24.0 36.9
1087 Rice, Paddy rice grain, Under-milled rice 22.8 37.9
1039 Udon, Wet form, boiled 20.8 38.8
7107 Bananas, Raw fruit 19.2 39.6
11221 Chicken, Broiler meats, Thigh, with skin, raw 18.2 40.4
3003 Sugars, Soft sugars, White 17.6 41.2
1064 Macaroni, spaghetti, Dry form, boiled 16.2 41.9
2017 Potatoes, Tuber, raw 16.1 42.6
11123 Pork, large breeds, Loin, lean and fat, raw 16.1 43.3
4032 Tofu (soybean curd), Momen-tofu 15.7 44.0
Women (n = 74)      
1088 Rice, Paddy rice grain, Well-milled rice 286.0 15.5
1026 Breads, White table bread 67.9 19.2
13003 Liquid milks, Ordinary liquid milk 54.3 22.2
12004 Hen’s eggs, whole, raw 46.8 24.7
14006 Fats and oils, Vegetable oil, blend 36.4 26.7
1048 Chinese noodles, Wet form, boiled 28.6 28.2
1085 Rice, Paddy rice grain, Brown rice 21.1 29.4
4046 Natto (Fermented soybean), Itohiki-natto 20.9 30.5
1089 Rice, Paddy rice grain, Well-milled rice with germ 19.1 31.6
2017 Potatoes, Tuber, raw 17.9 32.5
4040 Abura-age (Fried thin slices of pressed tofu, soybean curd) 17.3 33.5
1039 Udon, Wet form, boiled 17.2 34.4
13025 Yogurt, Whole milk, unsweetened 16.6 35.3
7148 Apples, Raw fruit 15.8 36.2
16006 Fermented alcoholic beverages, Beer, pale 15.7 37.0
15098 Biscuits, soft, Western-style confectioneries 15.3 37.8
11221 Chicken, Broiler meats, Thigh, with skin, raw 14.8 38.6
14001 Fats and oils, Olive oil 14.4 39.4
1117 Glutinous rice products, Rice cake 14.1 40.2
7107 Bananas, Raw fruit 14.1 41.0


Article Categories:
  • Original Article
Article Categories:
  • Nutrition

Keywords: Key words: dietary assessment, food frequency questionnaire, validity.

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