JA Barnard 1 *, LC Tapsell 1, PSW Davies 2, VL Brenninger 1 and LH Storlien 1

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1 (2002) 56, ß 2002 Nature Publishing Group All rights reserved /02 $ ORIGINAL COMMUNICATION Relationship of high energy expenditure and variation in dietary intake with reporting accuracy on 7 day food records and diet histories in a group of healthy adult volunteers JA Barnard 1 *, LC Tapsell 1, PSW Davies 2, VL Brenninger 1 and LH Storlien 1 1 Department of Biomedical Sciences and Smart Foods Centre, University of Wollongong, Wollongong, New South Wales, Australia; and 2 School of Human Movement Studies, Faculty of Health, Queensland University of Technology, Brisbane, and Children s Nutrition Research Centre, Department of Paediatrics and Child Health, University of Queensland, Royal Children s Hospital, Herston, Brisbane, Queensland, Australia Objectives: To assess the accuracy of reporting from both a diet history and food record and identify some of the characteristics of more accurate reporters in a group of healthy adult volunteers for an energy balance study. Design: Prospective measurements in free-living people. Setting: Wollongong, Australia. Subjects: Fifteen healthy volunteers (seven male, eight female; aged y; body mass index (BMI) kg=m 2 ) from the local community in the city of Wollongong, Australia. Interventions: Measurement of energy intake via diet history interview and 7 day food records, total energy expenditure by the doubly labelled water technique over 14 days, physical activity by questionnaire, and body fat by dual-energy X-ray absorptiometry. Results: Increased misreporting of energy intake was associated with increased energy expenditure (r ¼ 0.90, P < , diet history; r S ¼ 0.79, P ¼ , food records) but was not associated with age, sex, BMI or body fat. Range in number of recorded dinner foods correlated positively with energy expenditure (r S ¼ 0.63, P ¼ 0.01) and degree of misreporting (r S ¼ 0.71, P ¼ 0.003, diet history; r S ¼ 0.63, P ¼ 0.01, food records). Variation in energy intake at dinner and over the whole day identified by the food records correlated positively with energy expenditure (r ¼ 0.58, P ¼ 0.02) and misreporting on the diet history (r ¼ 0.62, P ¼ 0.01). Conclusions: Subjects who are highly active or who have variable dietary and exercise behaviour may be less accurate in reporting dietary intake. Our findings indicate that it may be necessary to screen for these characteristics in studies where accuracy of reporting at an individual level is critical. Sponsorship: The study was supported in part by Australian Research Council funds made available through the University of Wollongong. (2002) 56, DOI: =ej=ejcn= Keywords: energy intake; energy metabolism; diet records; intervention studies *Correspondence: J Barnard, Department Biomedical Sciences, University of Wollongong, NSW 2522, Australia. jag02@uow.edu.au Guarantor: L Tapsell. Contributors: JAB and VLB recruited subjects, analysed food record and diet history data and collected urine samples for analysis. PSWD analysed the urine samples and estimated EE. JAB carried out analysis and statistical procedures on resulting data. LHS provided conceptual and statistical guidance. LCT prepared the initial draft of the manuscript, which was worked up and finished by JAB. VLB made editorial contributions. LCT and LHS were responsible for the overall supervision of the project. Received 9 August 2000; revised 29 August 2001; accepted 6 September 2001

2 Introduction Accurate reporting of energy intake is critical in studies that examine the effects of energy balance and macronutrient fuel mix on human metabolism. Whilst studies under controlled conditions contribute substantially, it is the longterm clinical trials in free-living humans which provide the best evidence for dietary management. In clinical studies, energy and macronutrient intakes are appropriately assessed using the diet history method (DH) and=or food records (FR) which rely on self-report. The doubly labelled water (DLW) technique acts as a gold standard against which reported energy intakes can be validated in weight-stable conditions (Black et al, 1993). Studies involving the DLW technique have shown that misreporting of energy intakes is widespread (Black et al, 1991), although a number of researchers identify overweight subjects as being more likely to report inaccurately (Bingham et al, 1995; Braam et al, 1998; Heitmann & Lissner, 1995; Lafay et al, 1997). While in the latter case psychosocial factors may be involved (Herbert et al, 1995; Mela & Aaron, 1997), there will be other contextual aspects of reporting dietary intake which may affect all subgroups. The aim of the study reported here was to assess the accuracy of reporting from both a diet history and food record in a group of healthy adult volunteers and to identify some of the characteristics of more accurate reporters with particular emphasis on variation in the lifestyle parameters of eating and physical activity behaviour. Methods Subjects Fifteen normal healthy adults (seven male, eight female; aged y, body mass index (BMI) kg=m 2 ) from the local community in the city of Wollongong, Australia volunteered for the study. BMI was assessed as weight (kg) divided by height (m 2 ). Digital scales (Soehnle, Germany) were used to measure weight to the nearest 0.1 kg and a stadiometer (SECA, model no. 220, Germany) to measure height to the nearest 0.1 cm. The project was approved by the University of Wollongong Human Research Ethics Committee. portion sizes were noted. Dietary data were entered into the Foodworks (v. 1.05) nutrient analysis software packages (Xyris software, Brisbane, Australia), containing the Australian nutrient database, NUTTAB95 (Lewis et al, 1995). Total energy expenditure Total EE was assessed over 14 days using the DLW technique. On day 0, each participant consumed an oral dose of 0.05 g=kg body weight of 2 H 2 O and 0.13 g=kg H 2 18 O. Urine samples were collected on days 0, 1 and 14 for measurement of enrichment of each isotope using isotope ratio mass spectrometry (Hydra, Europa Scientific Ltd, UK). Since the 2 H leaves the body in water and the 18 O in both water and exhaled carbon dioxide, the difference in the rate of disappearance from the body of the two isotopes in urine was used to estimate carbon dioxide production. EE was then estimated using indirect calorimetry equations. Changes in body weight were incorporated into the assessment using estimated figures for weight loss and gain (FAO=WHO=UNU Expert Consultation, 1985). Body composition Percentage body fat (BF) was measured up to 3 weeks prior to day 0 by dual-energy X-ray absorptiometry with a Norland XR Bone Densitometer (Norland XR-36, Norland Corporation, Fort Atkinson, WI, USA) using host software revision and scanner software revision (Norland Corporation, Fort Atkinson, WI, USA). The resolution (pixel size) and scan speed used were mm and 180 mm=s, respectively. The whole body entrance skin radiation dose at this resolution and speed is 0.07 millrems. Assessment of reporting accuracy Reporting accuracy was determined by calculating a ratio of energy intake (EI) to the DLW value (EE DLW ). Subjects with discrepancy values within the range 0.79 EI:EE DLW 1.21 (Black, 1997) or with EI within 21% EE DLW using either DH or FR method were classified as accurate reporters and the remaining subjects were classified as inaccurate reporters. 359 Dietary assessment Subjects underwent open-ended DH interviews with trained dietitians at baseline (day 0) and kept a weighed FR for the following 7 days (days 1 7) during the period of energy expenditure (EE) measurement (days 0 14). In the DH subjects were asked to describe their usual daily eating patterns including variations (for example weekends or social events), and to complete a food checklist at the end of this description. They were given full instructions for keeping food records and were supplied with measuring cups, spoons and kitchen scales and recording sheets. Food records were checked by the dietitian, and details regarding recipes and Lifestyle characteristics To examine the effect of variation in lifestyle parameters on reporting accuracy, FR and physical activity data were further analysed. To characterise meal-time variability, the dinner meal from the FR was examined by classifying foods into groups. Dinner was chosen as the reference meal due to greater variation in food choices compared to lunch and breakfast (Tapsell et al, 2000). To capture the additional complexity of reporting mixed meals, meat-, seafood- and vegetable-based dishes were separated according to whether they were served as discrete portions, or components of mixed dishes such as stews and stir-fry meals. Major

3 360 components of each dinner meal (excluding dessert foods, snack items and drinks) were then counted each day for each subject. Mixed dishes were weighted by a factor of 4 to reflect their complexity. The modifiable activity questionnaire (MAQ) adapted from Kriska (1997) was used to obtain type and quantity of leisure-time activities and occupation (including home duties) over the previous year. The questionnaire was modified to include leisure activities appropriate to Australian conditions as indicated in the questionnaire instructions, to ask subjects for an estimate of intensity of leisure activities, to include more general questions to assess sedentary behaviour replacing those that assessed extremes of inactivity (eg surgery), and to exclude a question on lifetime involvement in team or individual sports. The MAQ was also used to determine EE (EE MAQ ) to trial it as a cheap and simple alternative to DLW for the assessment of EE in clinical trials. Statistics t-tests were used to investigate significant differences between the accurate and inaccurate reporters for age, BMI, BF and EE, and for sex, chi-squared tests were applied. The relationships between reported energy intakes (DH and FR) and the gold standard for EE (EE DLW ) were examined by regression analysis. The relationship between the degree of misreporting defined as the absolute difference between EI and EE DLW, and EE DLW was investigated. The relationship between the degree of misreporting with BMI, BF and with age was also investigated. A food range score for dinner foods was determined by calculating the difference between the minimum and maximum number of foods eaten at dinner over the 7 days of recording for the FR. The food range score as well as the number of leisure-time, occupational and total (leisure-time plus occupational) activities was compared to age, BMI, BF, EE DLW, and the degree of misreporting using regression analysis. The comparisons with sex were made using t-tests. In addition, intra-individual variation in number of foods eaten at dinner and energy intake over the whole day and at dinner only (excluding dessert foods, snack items and drinks) was assessed using the coefficient of variation (%CV ¼ s.d.=mean100%) for the 7 days of recording intake. Subjects were divided into younger ( 28 y) and older ( 36 y) age groups and the groups were compared via t-tests for differences in %CV and number of leisure, occupational, and sum of leisure and occupational (total) activities. Multiple regression analysis was performed to determine which factors accounted for variation in degree of misreporting on the FR and DH. For the MAQ, time spent per day in light, moderate and heavy leisure and occupational activities as well as for sleep and inactivity and miscellaneous activities was estimated. Basal EE was estimated using standard equations (Schofield et al, 1985) and thermic effect of food was estimated as 10% of the mean of the sum of EI from the FR and DH. EE using the MAQ (EE MAQ ) was calculated by a factorial method using BMR factors for each activity type from FAO=WHO=UNU Expert Consultation (1985). The relationship of EE MAQ with EE DLW, and EI from DH and FR was examined using regression analysis. All data were analysed using the statistical package JMP v (SAS Institute Inc., Cary, NC, USA). Statistical significance was accepted at the 95% confidence level (P < 0.05). Data are presented as mean (s.d.). Results Subject characteristics and EI and EE data can be found in Tables 1 and 2. Of the 15 subjects, seven were accurate reporters (five males, two females; age 38.7 (4.9), BMI 24.7 (1.6), BF 29.5 (13.4) and eight were inaccurate (five females and three males; age 34.0 (3.5), BMI 25.0 (1.8), BF 29.7 (10.4); Table 3). The EE of accurate reporters was MJ (0.83), and MJ (1.57) for inaccurate reporters. There was no significant difference between the groups for gender proportions, age, BMI or BF, but the difference for EE DLW was significant (P ¼ ). There was a significant positive relationship between the degree of misreporting and EE DLW for both the DH (r ¼ 0.90, P < ; Figure 1A) and FR (r S ¼ 0.79, P ¼ ; Figure 1B). Figure 1B indicated two distinct clusters, which we then re-examined on a plot of real difference between EI(FR) and EE DLW against EE DLW to expose the distinctive difference in misreporting when EE DLW is more than 15 MJ (Figure 2). There was no significant relationship between degree of misreporting and BMI (Figure 3) or BF (Figure 4), however, there was a Table 1 Subject characteristics Subject Age BMI %BF Weight change (kg) Women Mean (s.d.), n ¼ (9.6) 23.8 (5.3) 38.4 (9.0) a 0.1 (1.7) Men Mean (s.d.), n ¼ (13.1) 25.9 (3.9) 21.9 (6.8) a 0.1 (1.1) Mean (s.d.), n ¼ (11.7) 24.9 (4.6) 29.6 (11.4) 0.1 (1.3) a Significantly different (P ¼ ).

4 Table 2 Individual energy intake and expenditure data Energy intake Energy expenditure 361 Subject DH FR DLW MAQ Women NA NA Mean (s.d.), n ¼ (1403.7) a (1685.7) b (4531.7) (836.4) c Men NA NA NA Mean (s.d.), n ¼ (5140.9) a (1764.4) b (6857.9) (2562.3) c Mean (s.d.), n ¼ (5315.6) (2873.8) (5777.0) Mean (s.d.), n ¼ (3766.5) a Significantly different (P ¼ 0.005). b Significantly different (P ¼ ). c Significantly different (P ¼ 0.001). Table 3 Individual reporting accuracy data Degree of mis-reporting a Percentage difference from DLW Percentage difference from MAQ Subject DH FR DH FR DH FR Women NA NA NA NA Mean (s.d.), n ¼ (4187.3) (4386.6) (16.3) b (19.8) c (21.7) (22.7) Men NA NA NA NA NA NA Mean (s.d.), n ¼ (5430.6) (5965.4) (50.1) b (24.6) c 15.9 (41.5) (12.7) Mean (s.d.), n ¼ (4719.9) (5211.9) (44.3) (24.8) Mean (s.d.), n ¼ (35.4) (18.6) Note: accurate reports are indicated in bold. a Absolute difference between energy intake and energy expenditure as measured by DLW in kj. b Significantly different (P < 0.05).

5 362 significant relationship between age and degree of misreporting for the DH (r ¼ , P ¼ 0.015). There was no difference in degree of misreporting between males and females for either DH or FR. Dinner food groups used for analysis are listed in Table 4 and variation data relating to energy intake along with detailed physical activity data can be found in Table 5. There was no relationship between the food range score and age, sex, BMI or BF, but there were positive correlations between the food range score and EE DLW (r S ¼ 0.63, P ¼ 0.01), degree of misreporting on the FR (r S ¼ 0.63, P ¼ 0.01), and degree of misreporting on the DH (r S ¼ 0.71, P ¼ 0.003). Variation in EI at dinner correlated positively with EE DLW (r ¼ 0.58, P ¼ 0.02) and degree of misreporting on the DH (r ¼ 0.62, P ¼ 0.01), and negatively with age (r ¼ , P ¼ 0.02). Variation in EI over the whole day correlated positively degree of misreporting on the DH (r S ¼ 0.53, P ¼ 0.04), and negatively with age (r S ¼ , P ¼ ), but correlations did not quite reach significance for degree of misreporting on the FR (r S ¼ 0.50, P ¼ 0.06) or EE DLW (r S ¼ 0.44, P ¼ 0.10). When grouped by age, younger subjects had significantly greater variation in EI for dinner only (P ¼ 0.01) and over the whole day (P ¼ 0.009). There was no relationship between and BMI, EE DLW or degree of misreporting on the FR or DH, and the number of activities (leisure, occupational and total) was not different between the sexes Figure 1 Relationship between the degree of misreporting (absolute value of EI 7 EE DLW ) on the diet history (A) and 7 day food record (B) with energy expenditure measured by doubly labelled water.

6 363 Figure 2 Real difference between EI(FR) plotted against EE DLW exposing distinct subgroups of reporters above and below 15 MJ. or between accurate and inaccurate reporters. There tended to be a lower number of leisure-time activities with increasing age (r ¼ , P ¼ 0.07) and BF (r ¼ , P ¼ 0.08). Younger subjects had significantly more leisure-time (P ¼ 0.01) and total (P ¼ 0.03) activities than older subjects when grouped by age, but there was no difference in number of occupational activities. In our multiple regression analysis, higher EE DLW, female sex and higher %CV in number of dinner foods accounted for more than 96% of the variation in misreporting on the FR. Higher EE DLW, younger age, higher %CV in number of dinner foods, higher food range score, and female sex accounted for almost 96% of the variation in misreporting on the DH. There was no correlation between EE MAQ and EE DLW, however correlations with EI from the FR (r ¼ 0.75, P ¼ 0.01) and DH (r ¼ 0.58, P ¼ 0.08) were both good. Discussion There is a common perception in the literature that overweight subjects tend to under-report energy intakes, yet our study found that accuracy was more associated with EE, and was not related to degree of overweight or obesity. Under energy balance conditions, subjects with higher EE would have to report a lot more. Some subjects performed better in one method of dietary assessment than with the other, but then the DH assesses usual intake and relies on memory, whereas the FR assesses actual intake and is subject to an intervention effect (Tapsell et al, 1993). The different measurement contexts and skills required in recording and reporting may account for differences in performance, which is why we did not select one method over the other to categorise accurate reporters. As with the FR, the period of measurement of EE with DLW is assumed to be representative of usual behaviour, which may serve as a limitation since in reality it measures actual behaviour. For our purposes, however, the finding linking higher EE with inaccurate reporting was found using both dietary assessment methods (Figures 1 and 2). Our finding that high BMI does not define misreporting subjects is supported by work in Swedish cohorts. In these investigations, misreporting in overweight and obese subjects with a wide range of BMI ( ) was not found to increase with increasing BMI (Lindroos et al, 1999), nor was there evidence of obesity-specific misreporting when nonobese subjects categorised according to BMI were compared with obese subjects (Lindroos et al, 1997). In addition, analysis of data from Livingstone et al (1990) with normal weight, overweight and obese subjects showed no difference in BMI of accurate and inaccurate reporters when classified as in the present study. Classification of individuals according to BMI is known to be an imprecise tool, often categorising those with a greater muscle mass into overweight or obese categories. Highly active subjects with greater EE can fall into this category, and have previously been shown to be inaccurate in reporting dietary intake (Beidleman et al, 1995; Edwards et al, 1993; Trappe et al, 1997). The lack of contribution of BMI or BF together with the strong contribution of EE DLW to misreporting in both modes of dietary assessment indicates the involvement of a factor or factors which are quite separate to weight issues but still related to higher EE. The current study showed that dietary variation together with higher EE predicted misreporting.

7 364 Figure 3 Relationship between the degree of misreporting (absolute value of EI 7 EE DLW ) on the diet history (A) and 7 day food record (B) with body mass index. Higher energy expenders who are weight stable may achieve a matching high EI by eating greater quantities of foods and=or eating many different foods. Difficulties in estimating larger portion sizes have previously been reported (Vuckovic et al, 2000). It seems intuitive that a greater number of foods would also be difficult to record or recall accurately. Our results indicate that stability in the number of different foods eaten at the dinner meal is important for both recording and recall accuracy and that a larger range of foods eaten at dinner over 7 days is detrimental to accuracy in recall on the diet history. Interestingly, less variation at dinner was associated with increasing age, as was better performance on the DH. Other investigators have also found reduced variation in foods consumed by older people (Neuhaus et al, 1991; Fanelli & Stevenhagen 1985), but this was not linked to more accurate reporting. Our older subjects had a lower number of leisuretime and total activities than the younger ones, and older

8 365 Figure 4 Relationship between the degree of misreporting (absolute value of EI 7 EE DLW ) on the diet history (A) and 7 day food record (B) with percentage body fat. subjects would also be expected to have a lower EE. Thus it appears that people with highly active and varied lifestyles may find it more difficult to report that variation accurately. It is also important to point out that larger portion sizes and a greater number of foods at any given meal may be difficult for an investigating dietitian to capture and so errors can also be made in the recording process for dietary assessments which involve an interview-based process such as the DH. In fact error in dietary assessment can occur anywhere along the path from recording to analysis (Bingham, 1991). The concept of misreporting may therefore be better characterised by the term mismeasurement since a range of factors are involved which are inclusive but not limited to the reporting ability of the subject. The DLW method has been reported to be very accurate compared to indirect calorimetry (Schoeller et al, 1986), and has been described as a gold standard for validating EI (Beaton et al, 1997). However some of our subjects had higher EE that was not explained by self-reported physical activity. This might have reflected the difference between the assessment of habitual EE and actual EE and highlights the need to be cautious in our comparison of habitual EI and actual EE. While neither the DH nor the FR performed well against DLW, more subjects were able to report accurately on

9 366 Table 4 Food List of dinner foods obtained from the 7 day food records Beef=lamb=veal=pork=chicken portion Beef=lamb=veal=pork=chicken mixed dish Seafood portion Seafood mixed dish Vegetables Potato Pasta Rice Sauces=gravies=pastes Toppings=cheese=cream=dressings Quiche=pie=pastie Nachos=corn chips=tortilla Toast=bread=muffin=crumpet Egg Soup Hot chips Pizza Salad=vegetables mixed dish the FR. It is possible that this was a carry-over effect from the practice provided by the preceding DH. However, again we would expect closer correspondence between FR and DLW since they both attempt to measure behaviour during the study period while DH measures past behaviour. Acknowledging this difference is critical; although it is habitual diet that is important in the development of diet disease relationship and to develop treatment strategies in clinical practice, we still have no definitive way to assess it accurately. In this study we trialled an alternative method of assessing EI via self-reported physical activity in a subset of subjects. Our method is detailed enough to enable factorial calculation of EE while being time-effective in small-scale clinical trials. While the there was no correlation between EE MAQ and EE DLW, we achieved good correlations between the two measurements of past behaviour (EE MAQ and DH) which is impressive since the processes used to obtain each set of data are quite different with a different set of associated errors. While acknowledging the limitation of the small sample size and the distinct possibility that both measures are inaccurate, further exploration of this cheap and readily available method is warranted in both heterogeneous and homogeneous populations. Conclusions Studies such as clinical trials that require volunteers to report dietary intakes accurately under free-living conditions may need to consider characteristics of volunteers in addition to medical screening. The results of our study indicate that it may be difficult to capture both usual consumption and=or the foods consumed during the study period for people with a higher EE. This may be true for subjects with either a consistently or sporadically high activity level as well as for some overweight subjects. Stability of eating behaviour as well as exercise may also be important. For these reasons it may be necessary to screen for highly active subjects, patterns of higher activity levels, and stability of eating and exercise behaviours in studies where accuracy of measurement of dietary intake at an individual level is critical. Applying our knowledge of differences in performance between dietary assessment methods for specific study populations should also be considered. Subjects with less stable lifestyles, for example, younger and more active subjects may Table 5 Lifestyle characteristics %Variation in EI FR Number of activities %Variation in number of Subject Whole day Dinner dinner foods (FR) Food range score Leisure Occupational Women NA NA NA NA Mean (s.d.) 21.9 (10.8) 42.9 (18.7) 49.7 (6.4) 7.6 (1.6) 5.0 (1.2) 2.6 (0.6) Men NA NA NA NA NA NA Mean (s.d.) 20.4 (6.0) 51.0 (22.7) 52.0 (6.0) 7.5 (1.5) 6.8 (1.2) 2.8 (1.2) Mean (s.d.) 21.1 (8.3) 47.3 (20.6) 50.9 (16.4) 7.5 (4.1) 5.9 (2.6) 2.7 (1.3) Note: results not significantly different between males and females.

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