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Journal of Epidemiology logoLink to Journal of Epidemiology
. 2013 May 5;23(3):178–186. doi: 10.2188/jea.JE20120106

Within- and Between-Individual Variation in Energy and Nutrient Intake in Japanese Adults: Effect of Age and Sex Differences on Group Size and Number of Records Required for Adequate Dietary Assessment

日本人成人におけるエネルギーと栄養素摂取量の個人内・個人間変動:適切な食事調査に必要な調査人数と日数に対する年齢と性の影響

Azusa Fukumoto 1, Keiko Asakura 2, Kentaro Murakami 3, Satoshi Sasaki 3, Hitomi Okubo 1, Naoko Hirota 4, Akiko Notsu 5, Hidemi Todoriki 6, Ayako Miura 7, Mitsuru Fukui 8, Chigusa Date 9
PMCID: PMC3700253  PMID: 23583922

Abstract

Background

Information on within- and between-individual variation in energy and nutrient intake is critical for precisely estimating usual dietary intake; however, data from Japanese populations are limited.

Methods

We used dietary records to examine within- and between-individual variation by age and sex in the intake of energy and 31 selected nutrients among Japanese adults. We also calculated the group size required to estimate mean intake for a group and number of days required both to rank individuals within a group and to assess an individual’s usual intake, all with appropriate arbitrary precision. A group of Japanese women (younger: 30–49 years, n = 58; older: 50–69 years, n = 63) and men (younger: 30–49 years, n = 54; older: 50–76 years, n = 67) completed dietary records for 4 nonconsecutive days in each season (16 days in total).

Results

Coefficients of within-individual variation and between-individual variation were generally larger in the younger group than in the older group and in men as compared with women. The group size required to estimate a group’s mean intake, and number of days required to assess an individual’s usual intake, were generally larger for the younger group and for men. In general, a longer period was required to rank women and older adults.

Conclusions

In a group of Japanese adults, coefficients of within-individual variation and between-individual variation, which were used to estimate the group size and number of records required for adequate dietary assessment, differed by age, sex, and nutrient.

Key words: nutrients, within- and between-individual variation, age, sex, Japanese

INTRODUCTION

Fluctuations in daily dietary intake values, which frequently hamper analysis of nutritional data, result from within- and between-individual variation.13 Within-individual variation is subject to several factors such as true day-to-day variation, variation by day of the week and season, and residual variation, including measurement error. Between-individual variation is strongly influenced by factors such as age and sex.18

These variations should be considered whenever dietary intake is assessed in individuals and groups.3,9 Properly designed nutritional research that includes dietary assessment should thus consider the number of subjects required in 1 group (group size) and the number of days required to implement the assessment efficiently.3,10 These variables can be estimated using within- and between-individual variation of nutrient intake.13,7 Dietary assessment is usually conducted for 1 of 3 purposes: (1) to compare the mean intake of different groups, (2) to rank individuals within a group, or (3) to assess an individual’s usual intake. Thus, knowledge of within- and between-individual variation is required in order to determine group size in studies comparing mean intake between groups,7 and the ratio of within- to between-individual variation is required in order to determine the number of days required for dietary assessment in studies that assess diet–disease associations using rankings of subjects within a group (eg, in estimating relative risk using quartile categorizations).1,5,11 Moreover, within-individual variation influences the number of days required to assess the usual intake of individuals (eg, to establish the true nature of dose-response).1,3,9

The magnitude of within- and between-individual variation in nutrient intake is largely determined by cultural and ecologic factors.2,3,12 The group size and number of days required for precise estimation of usual nutrient intake has been studied, but results have differed,7,13 and these variables might differ by age, sex, and country, due to different dietary habits.13 However, investigation of these issues has been limited in Japan.4,14,15

Here, we examined within- and between-individual variation in dietary intake by age and sex among Japanese adults. We assessed energy and 31 selected nutrients derived from dietary records (DRs) that were maintained for 4 nonconsecutive days in each season (16 days in total). We also estimated the group size required to estimate a group’s mean intake and the number of days required to rank individuals within a group and to assess an individual’s usual intake with adequate precision.

METHODS

Subjects

The study was conducted in 4 areas in Japan that differed in geographic conditions and dietary habits, namely Osaka (Osaka City: 11 743 persons/km2; urban), Nagano (Matsumoto City: 786 persons/km2; rural inland), Tottori (Kurayoshi City: 285 persons/km2; rural coastal), and Okinawa (Ginowan City: 4446 persons/km2; urban island),16 between November 2002 and September 2003.1720 We recruited apparently healthy women aged 30 to 69 years who were willing to participate with a cohabiting husband. The subjects were volunteers and were asked by local staff to participate in the study. Subject recruitment was continued until a sufficient number of participants was obtained. In each of the 4 areas, each 10-year age band (30–39, 40–49, 50–59, and 60–69 years) included 8 women; the age of the husband was not considered. Thus, a total of 128 women and 128 men were invited. Dietitians were excluded from the study. None of the subjects had recently received dietary counseling from a doctor or dietitian or had a history of educational hospitalization for diabetes or nutritional education from a dietitian. Before the study, group orientations were held to explain the study purpose and design. Written informed consent was obtained from each subject. The study did not undergo ethical approval because it was conducted before ethical guidelines for epidemiologic research were enforced in Japan. However, use of data from this study was approved by the Ethics Committee at the University of Tokyo Faculty of Medicine (No. 3421). A total of 121 women aged 30 to 69 years and 121 men aged 30 to 76 years completed 16-day DRs and were included in the present analysis.

Four 4-day semi-weighed dietary records

Between November 2002 and September 2003, each subject completed one 4-nonconsecutive-day semi-weighed DR in each of the 4 seasons at intervals of approximately 3 months: DR1 in November/December 2002 (autumn), DR2 in February 2003 (winter), DR3 in May 2003 (spring), and DR4 in August/September 2003 (summer).1720 The 4 recording days consisted of 3 randomly selected weekdays and 1 weekend day. During the orientation session, local staff (registered dietitians) gave subjects both written and verbal instructions on how to keep the dietary record, using a completed recording sheet as an example. Each couple was given blank recording sheets and a digital scale (Tanita KD-173, ±2 g precision for 0–250 g and ±4 g precision for 251–1000 g). Subjects were also instructed on how to weigh each food item and drink and were asked to record and weigh all foods and drinks consumed on each recording day. When weighing was difficult (eg, when eating out), we instructed them to record the size and quantity of foods they ate as precisely as possible, using household measures. For each recording day, the subjects were asked to fax the completed forms to the local staff. The staff reviewed the submitted forms and, if necessary, asked the subject to augment and/or modify records by telephone or fax. The responses were faxed or, in some cases, handed directly to the staff.

All collected records were checked by trained registered dietitians in each local center and then again in the data center. The coding of records and conversion of measurements into grams were performed by trained registered dietitians in the survey center in accordance with uniform procedures. A total of 1398 food and beverage items appeared in the dietary records. Intake of energy and 31 selected nutrients was assessed based on the estimated intake of all items and the Standard Tables of Food Composition in Japan.21

Anthropometric measurements, physical activity level, and reporting adequacy of reported energy intake

Body height and weight were measured to the nearest 0.1 cm and 0.1 kg, respectively, with subjects wearing light clothing and no shoes. Body mass index (BMI) was calculated as body weight (kg) divided by the square of body height (m). Basal metabolic rate (BMR) was calculated for each subject from age, measured body height, and weight with the use of the equations of Ganpule et al.22 Physical activity level (PAL) was obtained from a questionnaire that queried subjects on their occupation and leisure-time activity. PAL was classified into 1 of 4 categories, and the categorical classification of PAL was then converted to 1.5 for sedentary or light, 1.75 for active or moderate, and 2.0 for vigorous and heavy PAL (Ministry of Health, Labour and Welfare of Japan, 2009).23 Estimated energy requirement (EER) was calculated as the product of PAL and BMR. We used the ratio of reported energy intake (EI) to EER (EI/EER) as an indicator of the adequacy of energy intake reporting and defined a ratio of 1.0 as adequate reporting for the group.

Statistical analysis

All statistical analyses were performed separately for women and men in 2 age groups (younger: 30–49 years for both women and men; older: 50–69 years for women and 50–76 years for men) using SAS statistical software, version 9.2 (SAS Institute Inc., Cary, NC, USA). Means, coefficients of within-individual variation (CVw) and between-individual variation (CVb), variance ratio, required group size, and required number of days were compared between age groups and sexes.

Means, SD, CVw, and CVb for intakes were calculated. Variances of intake were estimated into 2 sources by 1-way ANOVA: (1) between-individual variance (σb2) and (2) within-individual variance (σw2) (ie, day-to-day variation unaccounted for by other sources). Estimates of σw2 and σb2 were calculated by setting mean squares equal to their expected values.

We used untransformed data to analyze within- and between-individual variation in energy and all nutrients because a previous study showed that the estimated relative contribution of sources of variance was not considerably affected by logarithmic transformation2 and because other previous studies showed that a logarithm and Box–Cox transformation did not improve the assumption of homoscedasticity across covariates in the models, that estimates based upon transformed nutrient data were difficult to interpret meaningfully, and that back-transformation would introduce bias to variance estimates.24,25

The group size of DR (G) required to estimate mean intakes with 95% CIs within the specified percentage deviation (D0) of group mean from group usual (“true”) mean intake was calculated using the following formula2: G = 1.962 × [(CVb2 + CVw2)/D02].

The number of days of DR (NR) required to ensure a specified level of correlation coefficient (r) between observed and unobserved usual (“true”) mean intakes in individuals was calculated using the following formula1,7: NR = [r2/(1 − r2)] × VR, where VR is the variance ratio as determined by σw2b2. For this analysis, r is thus a measure of confidence of ranking or classification of individuals into fractions (eg, fourths).

The number of days of DR (NI) required to estimate mean intakes with 95% CIs within the specified percentage deviation (D1) of individual mean from usual (“true”) mean intake based on CVw was calculated using the following formula13: NI = (1.96 × CVw/D1)2.

RESULTS

Table 1 shows the physical characteristics of men and women in the 2 age groups. The mean value of EI/EER was around 1.0 in all groups; the smallest value, 0.94, was for younger men, and largest value, 1.08, was for older women.

Table 1. Characteristics of study subjects according to sex and age group.

  Women (n = 121) Men (n = 121)


Youngera
(n = 58)
Oldera
(n = 63)
Youngera
(n = 54)
Oldera
(n = 67)




Mean SD Mean SD Mean SD Mean SD
Age (years) 39.0 5.0 58.9 5.7 40.5 5.2 61.5 6.5
Body height (cm) 156.6 5.7 152.8 6.1 170.3 6.1 165.1 6.0
Body weight (kg) 52.9 6.9 53.8 7.2 67.9 11.1 65.2 9.6
BMI (kg/m2) 21.6 2.8 23.0 2.7 23.4 3.2 23.8 2.7
BMR (kcal/day) 1122 92 1046 111 1498 151 1368 145
Physical activity level 1.67 0.13 1.65 0.13 1.73 0.22 1.68 0.17
EI/EER 0.97 0.15 1.08 0.18 0.94 0.21 1.03 0.18

Abbreviations: BMI = body mass index; BMR = basal metabolic rate; EI = energy intake; EER = estimated energy requirement.

aYounger: 30–49 years for women and men; older: 50–69 years for women and 50–76 years for men.

Table 2 shows means, SD, CVw, CVb, and VR of daily intake of energy and 31 selected nutrients. Mean intake was larger in the older than in the younger group in both sexes for most nutrients and larger in men than in women for energy and all nutrients. CVw was larger than CVb for energy and most nutrients irrespective of age or sex. CVw was larger in the younger than in the older group for both women (for energy and 26 nutrients; ±1%–65% differences) and men (for energy and 28 nutrients; ±2%–25% differences). The findings for CVb were similar among both women (for energy and 26 nutrients; ±5%–12% differences) and men (for energy and 29 nutrients; ±8%–11% differences). Additionally, CVw was larger in men than in women for both the younger (for energy and 21 nutrients; ±8%–4% differences) and older groups (for energy and 22 nutrients; ±7%–51% differences). Similar findings were obtained in CVb for both the younger (for energy and 29 nutrients; ±1%–8% differences) and older groups (for energy and 18 nutrients; ±4%–8% differences). VR was greater than 1 for all except water (in younger women and men and older men) and carbohydrate (in younger men). In contrast to the results for CVw and CVb, VR was larger in the older than in the younger group for both women (for energy and 21 nutrients) and men (for energy and 26 nutrients) and larger in women than in men for both the younger (for energy and 27 nutrients) and older groups (for energy and 16 nutrients).

Table 2. Mean daily energy and nutrient intake, coefficients of variation, and within- to between-individual variance ratios according to sex and age group.

  Women (n = 121) Men (n = 121)


  Youngera (n = 58) Oldera (n = 63) Youngera (n = 54) Oldera (n = 67)




Mean SD CVw (%)b CVb (%)c VRd Mean SD CVw (%)b CVb (%)c VRd Mean SD CVw (%)b CVb (%)c VRd Mean SD CVw (%)b CVb (%)c VRd
Energy (kcal) 1824 327 20.6 17.2 1.44 1845 246 18.3 12.5 2.15 2392 473 21.1 19.0 1.23 2330 370 18.5 15.2 1.49
Protein (g) 65.1 11.6 25.5 16.6 2.37 72.9 10.6 23.5 13.4 3.08 81.0 16.9 25.4 19.8 1.64 86.8 13.6 23.7 14.5 2.67
Fat (g) 59.7 12.6 35.0 19.3 3.28 54.6 9.4 34.9 15.0 5.43 71.6 18.2 37.0 23.6 2.45 63.1 12.3 35.9 17.3 4.30
Carbohydrate (g) 244 51 20.6 20.4 1.02 258 41 18.5 15.1 1.50 311 69 20.9 21.6 0.93 312 52 19.9 15.9 1.57
Dietary fiber (g) 12.4 3.2 33.8 24.8 1.86 16.8 3.9 32.4 21.8 2.22 13.3 3.7 34.1 26.5 1.65 17.4 4.1 30.5 22.1 1.90
Water (g) 1902 403 20.6 20.6 1.00 2161 483 17.0 22.0 0.60 2356 615 23.3 25.5 0.84 2476 498 18.6 19.6 0.90
Sodium (mg) 3742 734 33.7 17.7 3.61 4315 780 34.4 15.9 4.67 4574 1008 35.7 20.2 3.13 5053 860 34.1 14.7 5.35
Potassium (mg) 2322 519 27.4 21.3 1.66 2994 548 26.7 17.0 2.46 2676 661 26.0 23.8 1.19 3207 571 23.9 16.8 2.03
Calcium (mg) 507 152 38.8 28.3 1.88 628 164 34.3 24.7 1.93 534 196 40.0 35.4 1.28 637 166 34.7 24.6 2.00
Magnesium (mg) 240 48 28.4 18.7 2.31 306 56 26.6 17.1 2.41 286 67 27.0 22.4 1.45 343 62 25.6 17.0 2.28
Phosphorus (mg) 983 197 24.6 19.1 1.65 1138 192 22.4 15.9 1.98 1187 275 24.0 22.4 1.15 1313 219 22.7 15.7 2.10
Iron (mg) 7.2 1.4 35.1 17.4 4.07 9.2 2.0 33.1 20.4 2.62 8.4 1.9 35.1 21.3 2.71 10.1 1.8 31.3 16.2 3.74
Zinc (mg) 7.7 1.5 31.4 17.6 3.19 8.3 1.3 28.1 13.6 4.28 9.8 2.2 32.4 21.2 2.34 10.0 1.6 30.3 13.8 4.86
β-carotene equivalente (µg) 2891 1036 84.4 29.0 8.48 4345 1334 62.0 26.5 5.48 3252 1130 80.0 28.4 7.91 4475 1377 65.9 26.0 6.44
Vitamin Af (µg RE) 608 402 223.9 35.2 40.49 702 324 158.6 23.7 44.87 648 450 221.9 41.9 28.02 827 504 209.4 31.2 45.08
Vitamin D (µg) 6.0 2.2 105.6 25.3 17.38 9.4 3.7 99.9 30.6 10.66 7.4 2.7 106.0 24.4 18.82 11.3 4.5 93.3 32.0 8.52
α-tocopherol (mg) 6.9 1.5 36.5 20.1 3.30 7.9 1.5 36.9 16.3 5.12 8.0 2.0 39.9 23.0 3.01 8.8 1.8 38.1 17.7 4.65
Vitamin K (µg) 203 75 68.7 32.7 4.43 269 90 57.0 30.4 3.51 215 78 60.7 32.8 3.43 275 88 63.0 27.9 5.12
Vitamin B1 (mg) 0.8 0.2 41.2 17.8 5.32 0.9 0.2 34.1 14.3 5.71 1.0 0.2 44.9 21.0 4.57 1.1 0.2 36.5 14.6 6.30
Vitamin B2 (mg) 1.2 0.3 38.1 20.2 3.55 1.4 0.3 28.9 19.2 2.26 1.4 0.4 36.3 24.2 2.26 1.6 0.3 33.0 17.4 3.59
Niacin (mg) 15.9 3.6 38.5 20.4 3.57 18.3 3.7 34.7 18.3 3.58 21.6 5.8 39.4 24.8 2.51 22.6 5.6 36.4 23.2 2.47
Vitamin B6 (mg) 1.1 0.2 33.4 20.0 2.78 1.4 0.3 28.6 17.2 2.76 1.4 0.4 34.9 24.8 1.97 1.6 0.3 30.0 18.8 2.55
Vitamin B12 (µg) 6.4 2.6 103.8 30.3 11.73 8.7 3.0 88.6 26.0 11.63 8.0 3.6 96.1 38.5 6.23 10.9 4.2 96.4 29.7 10.54
Folate (µg) 300 82 51.8 24.0 4.67 411 97 39.1 21.4 3.33 339 96 53.6 25.0 4.58 451 103 49.6 19.2 6.69
Vitamin C (mg) 87.7 29.7 52.0 31.3 2.76 136.7 34.8 43.4 23.0 3.54 94.3 36.8 53.1 36.7 2.10 140.4 40.8 50.4 26.2 3.70
SFA (g) 17.3 4.3 40.9 22.6 3.28 15.1 3.2 40.8 18.8 4.71 20.2 6.4 45.1 29.7 2.31 16.9 3.5 41.3 18.2 5.16
MUFA (g) 21.6 5.0 40.7 20.8 3.85 18.8 3.7 41.2 17.0 5.90 26.6 7.0 42.5 24.2 3.09 22.3 5.3 42.4 21.1 4.02
PUFA (g) 12.9 2.4 40.3 15.9 6.42 12.8 2.3 40.1 14.9 7.21 15.9 3.5 40.7 19.2 4.47 14.8 3.0 39.7 17.8 5.00
n-6 PUFA (g) 10.7 2.1 42.0 16.2 6.69 10.2 1.9 43.3 14.9 8.45 13.0 2.9 42.8 19.5 4.80 11.7 2.5 42.6 18.6 5.26
n-3 PUFA (g) 2.2 0.5 55.9 20.0 7.82 2.6 0.6 57.1 19.0 9.02 2.8 0.7 57.0 22.3 6.51 3.1 0.8 57.8 21.2 7.47
Marine origin n-3 PUFAg (mg) 687 289 119.5 29.6 16.32 1030 392 104.1 27.7 14.15 900 411 123.9 33.6 13.57 1312 524 99.0 31.4 9.94
Cholesterol (mg) 330 83 52.8 21.6 5.97 332 79 51.3 20.0 6.60 397 103 49.0 23.0 4.54 398 103 47.6 23.0 4.28

Abbreviations: CVw = coefficient of within-individual variation; CVb = coefficient of between-individual variation; VR = ratio of within- to between-individual variance; RE = retinol equivalents; SFA = saturated fatty acids; MUFA = monounsaturated fatty acids; PUFA = polyunsaturated fatty acids.

aYounger: 30–49 years for women and men; older: 50–69 years for women and 50–76 years for men.

bCVw = [(within-individual variance)0.5/mean] × 100.

cCVb = [(between-individual variance)0.5/mean] × 100.

dVR = within-individual/between-individual variance ratio (σw2b2).

eSum of β-carotene, α-carotene/2, and cryptoxanthin/2.

fSum of retinol, β-carotene/12, α-carotene/24, and cryptoxanthin/24.

gSum of eicosapentaenoic acid, docosapentaenoic acid, and docosahexaenoic acid.

Table 3 shows the group size required to estimate mean intake of energy and nutrients with 95% CIs within a specified (ie, 2.5%, 5%, 10%, and 20%) deviation of a group’s mean from the group’s usual (“true”) mean intake by DR. The group size required to determine the mean intake of the group was larger in the younger than in the older group for both women (for energy and 29 nutrients) and men (for energy and 30 nutrients) and was larger in men than in women for both the younger (for energy and 26 nutrients) and the older groups (for energy and 22 nutrients).

Table 3. Group size required to estimate mean intake of energy and nutrients with 95% CIs within the specified % deviation (D0) of a group’s mean from the group’s usual (“true”) mean intake by dietary record according to sex and age groupa .

  Women (n = 121) Men (n = 121)


Youngerb (n = 58) Olderb (n = 63) Youngerb (n = 54) Olderb (n = 67)




D0 2.5% 5% 10% 20% 2.5% 5% 10% 20% 2.5% 5% 10% 20% 2.5% 5% 10% 20%
Energy 442 111 28 7 302 76 19 5 497 124 31 8 353 88 22 6
Protein 569 142 36 9 448 112 28 7 639 160 40 10 476 119 30 7
Fat 980 245 61 15 884 221 55 14 1186 297 74 19 976 244 61 15
Carbohydrate 517 129 32 8 352 88 22 5 556 139 35 9 400 100 25 6
Dietary fiber 1081 270 68 17 937 234 59 15 1145 286 72 18 872 218 54 14
Water 520 130 32 8 473 118 30 7 732 183 46 11 448 112 28 7
Sodium 889 222 56 14 881 220 55 14 1032 258 64 16 846 212 53 13
Potassium 741 185 46 12 618 155 39 10 764 191 48 12 524 131 33 8
Calcium 1416 354 88 22 1096 274 69 17 1752 438 109 27 1110 278 69 17
Magnesium 712 178 44 11 614 154 38 10 757 189 47 12 580 145 36 9
Phosphorus 596 149 37 9 464 116 29 7 661 165 41 10 467 117 29 7
Iron 946 236 59 15 929 232 58 15 1038 260 65 16 763 191 48 12
Zinc 794 198 50 12 598 149 37 9 921 230 58 14 682 170 43 11
β-carotene equivalentc 4889 1222 306 76 2793 698 175 44 4426 1106 277 69 3085 771 193 48
Vitamin Ad 31 569 7892 1973 493 15 808 3952 988 247 31 332 7833 1958 490 27 544 6886 1722 430
Vitamin D 7246 1812 453 113 6715 1679 420 105 7279 1820 455 114 5977 1494 374 93
α-tocopherol 1068 267 67 17 1002 250 63 16 1303 326 81 20 1085 271 68 17
Vitamin K 3558 890 222 56 2568 642 161 40 2925 731 183 46 2919 730 182 46
Vitamin B1 1237 309 77 19 842 210 53 13 1511 378 94 24 951 238 59 15
Vitamin B2 1141 285 71 18 738 184 46 12 1171 293 73 18 854 214 53 13
Niacin 1168 292 73 18 946 237 59 15 1331 333 83 21 1147 287 72 18
Vitamin B6 933 233 58 15 687 172 43 11 1127 282 70 18 770 193 48 12
Vitamin B12 7191 1798 449 112 5235 1309 327 82 6585 1646 412 103 6254 1563 391 98
Folate 2001 500 125 31 1219 305 76 19 2147 537 134 34 1741 435 109 27
Vitamin C 2261 565 141 35 1483 371 93 23 2564 641 160 40 1980 495 124 31
SFA 1344 336 84 21 1243 311 78 19 1789 447 112 28 1251 313 78 20
MUFA 1284 321 80 20 1222 305 76 19 1471 368 92 23 1378 344 86 22
PUFA 1155 289 72 18 1127 282 70 18 1245 311 78 19 1162 291 73 18
n-6 PUFA 1244 311 78 19 1290 323 81 20 1362 341 85 21 1326 332 83 21
n-3 PUFA 2170 543 136 34 2224 556 139 35 2301 575 144 36 2332 583 146 36
Marine origin n-3 PUFAe 9315 2329 582 146 7134 1784 446 111 10 124 2531 633 158 6624 1656 414 103
Cholesterol 2000 500 125 31 1862 465 116 29 1803 451 113 28 1715 429 107 27

Abbreviations: SFA = saturated fatty acids; MUFA = monounsaturated fatty acids; PUFA = polyunsaturated fatty acids.

aGroup size of dietary record assuming single observation for each individual = 1.962 × [(CVb2 + CVw2)/D02], where D0 = the specified % deviation of group mean from group usual (“true”) mean intake.

bYounger: 30–49 years for women and men; older: 50–69 years for women and 50–76 years for men.

cSum of β-carotene, α-carotene/2, and cryptoxanthin/2.

dSum of retinol, β-carotene/12, α-carotene/24, and cryptoxanthin/24.

eSum of eicosapentaenoic acid, docosapentaenoic acid, and docosahexaenoic acid.

Table 4 presents the number of days required to ensure specified (ie, 0.75, 0.80, 0.85, 0.90, and 0.95) correlation coefficients between observed and usual (“true”) mean intake of energy and nutrients by DR. The number of days required to rank individuals within a group by intake was larger in the older than in the younger group for both women (for energy and 20 nutrients) and men (for energy and 25 nutrients) and was larger in women than in men for both the younger (for energy and 29 nutrients) and older groups (for energy and 16 nutrients).

Table 4. Number of days required to ensure a specified correlation coefficient (r) between observed and usual (“true”) mean intake of energy and nutrients by dietary record according to sex and age groupa .

  Women (n = 121) Men (n = 121)


Youngerb (n = 58) Olderb (n = 63) Youngerb (n = 54) Olderb (n = 67)




r 0.75 0.8 0.85 0.9 0.95 0.75 0.8 0.85 0.9 0.95 0.75 0.8 0.85 0.9 0.95 0.75 0.8 0.85 0.9 0.95
Energy 2 3 4 6 13 3 4 6 9 20 2 2 3 5 11 2 3 4 6 14
Protein 3 4 6 10 22 4 5 8 13 28 2 3 4 7 15 3 5 7 11 25
Fat 4 6 9 14 30 7 10 14 23 50 3 4 6 10 23 6 8 11 18 40
Carbohydrate 1 2 3 4 9 2 3 4 6 14 1 2 2 4 9 2 3 4 7 15
Dietary fiber 2 3 5 8 17 3 4 6 9 21 2 3 4 7 15 2 3 5 8 18
Water 1 2 3 4 9 1 1 2 3 6 1 1 2 4 8 1 2 2 4 8
Sodium 5 6 9 15 33 6 8 12 20 43 4 6 8 13 29 7 10 14 23 49
Potassium 2 3 4 7 15 3 4 6 10 23 2 2 3 5 11 3 4 5 9 19
Calcium 2 3 5 8 17 2 3 5 8 18 2 2 3 5 12 3 4 5 9 18
Magnesium 3 4 6 10 21 3 4 6 10 22 2 3 4 6 13 3 4 6 10 21
Phosphorus 2 3 4 7 15 3 4 5 8 18 1 2 3 5 11 3 4 5 9 19
Iron 5 7 11 17 38 3 5 7 11 24 3 5 7 12 25 5 7 10 16 35
Zinc 4 6 8 14 29 6 8 11 18 40 3 4 6 10 22 6 9 13 21 45
β-carotene equivalentc 11 15 22 36 79 7 10 14 23 51 10 14 21 34 73 8 11 17 27 60
Vitamin Ad 52 72 105 173 375 58 80 117 191 415 36 50 73 119 259 58 80 117 192 417
Vitamin D 22 31 45 74 161 14 19 28 45 99 24 33 49 80 174 11 15 22 36 79
α-tocopherol 4 6 9 14 31 7 9 13 22 47 4 5 8 13 28 6 8 12 20 43
Vitamin K 6 8 12 19 41 5 6 9 15 32 4 6 9 15 32 7 9 13 22 47
Vitamin B1 7 9 14 23 49 7 10 15 24 53 6 8 12 19 42 8 11 16 27 58
Vitamin B2 5 6 9 15 33 3 4 6 10 21 3 4 6 10 21 5 6 9 15 33
Niacin 5 6 9 15 33 5 6 9 15 33 3 4 7 11 23 3 4 6 11 23
Vitamin B6 4 5 7 12 26 4 5 7 12 26 3 4 5 8 18 3 5 7 11 24
Vitamin B12 15 21 31 50 109 15 21 30 50 108 8 11 16 27 58 14 19 27 45 98
Folate 6 8 12 20 43 4 6 9 14 31 6 8 12 20 42 9 12 17 29 62
Vitamin C 4 5 7 12 26 5 6 9 15 33 3 4 5 9 19 5 7 10 16 34
SFA 4 6 9 14 30 6 8 12 20 44 3 4 6 10 21 7 9 13 22 48
MUFA 5 7 10 16 36 8 10 15 25 55 4 5 8 13 29 5 7 10 17 37
PUFA 8 11 17 27 59 9 13 19 31 67 6 8 12 19 41 6 9 13 21 46
n-6 PUFA 9 12 17 29 62 11 15 22 36 78 6 9 13 20 44 7 9 14 22 49
n-3 PUFA 10 14 20 33 72 12 16 23 38 83 8 12 17 28 60 10 13 19 32 69
Marine origin n-3 PUFAe 21 29 42 70 151 18 25 37 60 131 17 24 35 58 126 13 18 26 42 92
Cholesterol 8 11 16 25 55 8 12 17 28 61 6 8 12 19 42 6 8 11 18 40

Abbreviations: SFA = saturated fatty acids; MUFA = monounsaturated fatty acids; PUFA = polyunsaturated fatty acids.

aNumber of days of dietary record = [r2/(1 − r2)] × VR, where r = unobservable correlation coefficient between observed and usual (“true”) mean intakes of individuals and VR = within-individual/between-individual variance ratio (σw2b2).

bYounger: 30–49 years for women and men; older: 50–69 years for women and 50–76 years for men.

cSum of β-carotene, α-carotene/2, and cryptoxanthin/2.

dSum of retinol, β-carotene/12, α-carotene/24, and cryptoxanthin/24.

eSum of eicosapentaenoic acid, docosapentaenoic acid, and docosahexaenoic acid.

Table 5 shows the number of days required to assess mean intake of energy and nutrients with 95% CIs within a specified (ie, 5%, 10%, 20%, and 30%) deviation of an individual’s mean from usual (“true”) mean intake by DR. The number of days needed to assess the usual intake of individuals was larger in the younger than in the older group for both women (for energy and 26 nutrients) and men (for energy and 28 nutrients) and was larger in men than in women for both the younger (for energy and 20 nutrients) and older groups (for energy and 21 nutrients).

Table 5. Number of days required to assess mean intake of energy and nutrients with 95% CIs within the specified % deviation (D1) of an individual’s mean from usual (“true”) mean intake by dietary record according to sex and age groupa .

  Women (n = 121) Men (n = 121)


Youngerb (n = 58) Olderb (n = 63) Youngerb (n = 54) Olderb (n = 67)




D1 5% 10% 20% 30% 5% 10% 20% 30% 5% 10% 20% 30% 5% 10% 20% 30%
Energy 65 16 4 2 52 13 3 1 69 17 4 2 53 13 3 1
Protein 100 25 6 3 85 21 5 2 99 25 6 3 87 22 5 2
Fat 188 47 12 5 187 47 12 5 211 53 13 6 198 49 12 5
Carbohydrate 65 16 4 2 53 13 3 1 67 17 4 2 61 15 4 2
Dietary fiber 176 44 11 5 161 40 10 4 178 45 11 5 143 36 9 4
Water 65 16 4 2 44 11 3 1 84 21 5 2 53 13 3 1
Sodium 174 44 11 5 181 45 11 5 195 49 12 5 178 45 11 5
Potassium 116 29 7 3 110 27 7 3 104 26 6 3 88 22 5 2
Calcium 231 58 14 6 181 45 11 5 246 61 15 7 185 46 12 5
Magnesium 124 31 8 3 109 27 7 3 112 28 7 3 101 25 6 3
Phosphorus 93 23 6 3 77 19 5 2 88 22 6 2 79 20 5 2
Iron 190 47 12 5 168 42 11 5 190 47 12 5 150 38 9 4
Zinc 151 38 9 4 121 30 8 3 161 40 10 4 141 35 9 4
β-carotene equivalentc 1093 273 68 30 591 148 37 16 982 246 61 27 667 167 42 19
Vitamin Ad 7702 1926 481 214 3866 966 242 107 7563 1891 473 210 6737 1684 421 187
Vitamin D 1713 428 107 48 1535 384 96 43 1728 432 108 48 1337 334 84 37
α-tocopherol 205 51 13 6 210 52 13 6 245 61 15 7 223 56 14 6
Vitamin K 726 181 45 20 500 125 31 14 566 142 35 16 610 153 38 17
Vitamin B1 260 65 16 7 179 45 11 5 310 77 19 9 205 51 13 6
Vitamin B2 222 56 14 6 128 32 8 4 203 51 13 6 167 42 10 5
Niacin 228 57 14 6 185 46 12 5 238 60 15 7 204 51 13 6
Vitamin B6 172 43 11 5 126 32 8 4 187 47 12 5 138 35 9 4
Vitamin B12 1657 414 104 46 1205 301 75 33 1418 355 89 39 1428 357 89 40
Folate 412 103 26 11 234 59 15 7 441 110 28 12 379 95 24 11
Vitamin C 415 104 26 12 289 72 18 8 434 108 27 12 390 97 24 11
SFA 257 64 16 7 256 64 16 7 312 78 20 9 262 65 16 7
MUFA 255 64 16 7 261 65 16 7 278 69 17 8 276 69 17 8
PUFA 250 62 16 7 247 62 15 7 254 64 16 7 242 61 15 7
n-6 PUFA 271 68 17 8 288 72 18 8 282 70 18 8 279 70 17 8
n-3 PUFA 481 120 30 13 501 125 31 14 499 125 31 14 514 129 32 14
Marine origin n-3 PUFAe 2194 549 137 61 1666 416 104 46 2357 589 147 65 1505 376 94 42
Cholesterol 428 107 27 12 404 101 25 11 369 92 23 10 348 87 22 10

Abbreviations: SFA = saturated fatty acids; MUFA = monounsaturated fatty acids; PUFA = polyunsaturated fatty acids.

aNumber of days of dietary record = (1.96 × CVw/D1)2, where D1 = the specified % deviation of individual mean from usual (“true”) mean intake.

bYounger: 30–49 years for women and men; older: 50–69 years for women and 50–76 years for men.

cSum of β-carotene, α-carotene/2, and cryptoxanthin/2.

dSum of retinol, β-carotene/12, α-carotene/24, and cryptoxanthin/24.

eSum of eicosapentaenoic acid, docosapentaenoic acid, and docosahexaenoic acid.

DISCUSSION

In this study of Japanese women and men, we found that coefficients of within-individual variation and between-individual variation were generally larger in the younger group than in the older group, whereas variance ratio was larger in the older group than in the younger group. Similarly, both CVw and CVb were generally larger in men than in women, whereas VR was larger in women than in men. To our knowledge, this study is the first to examine within- and between-individual variation in dietary intake with respect to both age and sex in a Japanese population and in Asian men.

The results of this study are comparable with those of previous studies in Japan,4,14,15 namely, CVw was larger than CVb, and CVw, CVb, and VR were relatively small for energy, carbohydrate, protein, and water, intermediate for minerals, dietary fiber, and fat, and large for fatty acids, cholesterol, and vitamins. Ogawa et al used four 3-day DRs to investigate women (aged 47–76 years) and men (aged 45–77 years) living in a rural area.15 Their results for CVw and CVb were similar to our estimates. Egami et al used four 4-day DRs to assess women and men (aged >40 years) living in a coastal area.14 CVw was generally larger than in our results, whereas CVb was smaller. Tokudome et al used four 7-day DRs to investigate female dietitians (aged 32–66 years).4 CVw and CVb were generally smaller than in our study, possibly due to differences in eating patterns between their and our groups, which arose from the greater nutritional knowledge of their subjects.

Our findings are also consistent with those of several studies that examined CVw and CVb by age or sex.7,15,26 In a study of UK adults (a comparison among 4 groups categorized by sex and age, with younger groups aged 18–57 years using 7-day DRs vs older groups aged 60–80 years using three 7-day DRs), CVw and CVb were larger in the younger than in the older group for both sexes.7 In studies of Japanese adults living in a rural area (mentioned above),15 UK adults (mentioned above),7 and US elderly adults (aged >60 years using 3-day DRs),26 CVw and CVb were larger in men than in women. In a study of Chinese women (aged 40–59 years vs 60–70 years using 24-h dietary recall), while CVw was consistent with our study, CVb was larger in the older than in the younger group.5 Additionally, in studies of Japanese adults living in a coastal area (mentioned above),14 Korean elderly (mean [SD] age 70.4 [5.8] years using 5- or 6-day 24-h dietary recall),12 and Canadian adults (aged 25–44 years using 24-h dietary recall),2,27 CVw and CVb were larger in women than in men. These inconsistent results in some previous studies may be due to differences in study design: these studies2,5,12,27 used 24-h dietary recall, whereas we used DR. Cultural factors also likely played a role.2,3

The present results have implications for the design and interpretation of dietary assessment. First, among older adults and women, nutrient intake may be more homogeneous from day-to-day and among subjects than for younger adults and men, because smaller CVw and CVb were observed in older groups and in women than in their respective counterparts. Thus, as compared with men and younger adults, women and older adults may require a smaller group size and fewer days to assess the group’s and individual’s usual nutrient intake. Second, subjects can be more precisely ranked in groups of younger adults and/or men, because a smaller VR was observed in these groups. A smaller VR means that σw2 is relatively small compared with σb2 and that the difference in intake between individuals can be more easily distinguished. Therefore, if dietary assessment is conducted in individuals or groups by the same methods (number of days and group size) regardless of age or sex, the level of precision of the assessment will differ among the individuals or groups. If an analysis includes estimates of intake with a low level of precision, even in only 1 group, this may decrease the power of the statistical analysis and lead to misinterpretation of the association between dietary factors and an outcome.2,7,9,12 Third, regardless of age or sex, a large CVw means that many DR days would be required to characterize an individual’s usual intake—for example, 4 to 481 days would be needed to achieve within 20% deviation for younger women. Therefore, use of an alternative method (eg, a semi-quantitative food frequency questionnaire) that can estimate usual intakes over a longer period than DR or dietary recall may be necessary to accord with the study objective, study design, demographic characteristics of the population, and available resources.3,6,12,15

Several limitations of this study warrant mention. First, the generalizability of our results is hampered by the fact that the present subjects were not randomly sampled from the general Japanese population but were instead volunteers and possibly health-conscious. As we lacked information on the subjects’ characteristics, including education and occupation, we could not determine how such characteristics influenced our findings. Mennen et al13 assumed that the dietary recall of subjects who completed a protocol is more precise (smaller CVw) than that of subjects who dropped out. Hebert et al11 suggested that CVb is smaller in a population with higher socioeconomic status (SES). Thus, because of precise recording, CVw might have been smaller in our volunteers than in the general population consuming a similar diet. CVb might have been smaller because of limited variation in some variables (eg, health-consciousness). If so, the group size required to estimate a group’s mean intake in the general population would be larger than the estimates observed here (Table 3). Additionally, the number of days required to precisely estimate an individual’s usual intake in the general population would be larger than the estimates observed here (Table 5). Conversely, as we did not know whether VR was lower or higher in our volunteers than in the general population, the number of days required to rank individuals based on their intakes within the general population is unclear, that is, we cannot conclude that the required number of days is larger or smaller than the estimates observed here (Table 4).

Second, the subjects were married men and women living together, who likely frequently have the same meals. This implies that the CVw and CVb of men in this study might be underestimated as compared with the general male population because the daily menu is probably usually decided by women, who in our study had a smaller CVw and CVb. Third, although we compared within- and between-individual variation between sexes and age groups (younger vs older), several unanticipated confounding factors, such as SES, might be present in our analysis. If the distribution of SES differs between sexes or age groups, and SES has an effect on dietary habits, it should be adjusted for in the analysis. However, we designed the study so as to consider important confounding factors that may affect the comparisons. For example, sex itself is an important confounding factor in a comparison between age groups, and age is the same in a comparison between sexes. To address this problem, we recruited the same number of subjects for each sex and age category. Living area, season, and timing of data collection (weekday or weekend day) are other possible confounding factors, and they were equalized between sexes and age groups.14,28,29 Finally, DR is susceptible to measurement error due to erroneous recording and potential changes in eating behavior.3 However, the adequacy of reported energy intake was likely adequate at the group level, given that the mean value of EI/EER was around 1.0.

In conclusion, the present study of Japanese adults showed that CVw and CVb were larger in a younger group than in an older group and larger in men than in women for energy and most nutrients. Precise estimation of usual nutrient intakes requires consideration of differences not only in CVw and CVb by age and sex, but also in group size and number of days estimated using CVw and CVb. The present findings may have important implications for the design and interpretation of dietary assessment in Japanese adults.

ONLINE ONLY MATERIALS

Abstract in Japanese.
je-23-178-s001.pdf (136.3KB, pdf)

ACKNOWLEDGMENTS

This work was supported by grants from the Japanese Ministry of Health, Labour and Welfare. All the authors contributed to the preparation of the manuscript and approved the final version submitted for publication. A.F. performed statistical analyses and wrote the manuscript. K.A. and K.M. assisted in writing and editing the manuscript. S.S. contributed to the concept and design of the study, study protocol, and data collection, and assisted in writing and editing the manuscript. H.O., N.H., A.N., H.T., A.M., M.F., and C.D. were involved in the study design, data collection, and data management.

Conflicts of interest: None declared.

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Abstract in Japanese.
je-23-178-s001.pdf (136.3KB, pdf)

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