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November 2000, Volume 24, Number 11, Pages 1500-1506
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Does energy intake underreporting involve all kinds of food or only specific food items? Results from the Fleurbaix Laventie Ville Santé (FLVS) study
L Lafay1, L Mennen1, A Basdevant2, M A Charles1, J M Borys3, E Eschwège1 and M Romon4 the FLVS study group3

1Institut National de la Santé Et de la Recherche Médicale, Unité 258, Faculté de Médecine Paris Sud, Villejuif, France

2Department of Nutrition, Hôtel-Dieu Hospital, Paris, France

3Fleurbaix Laventie Ville Santé Association, Armentières, France

4Department of Nutrition, University Hospital, Lille, France

Correspondence to: L Lafay, INSERM Unité 258, 16 Avenue Paul Vaillant-Couturier, 94807 Villejuif Cedex,


OBJECTIVE: To determine if energy intake underreporting concerns all major food groups or if it occurs for specific food groups only.

DESIGN: Cross-sectional study on dietary habits and food consumption.

SUBJECTS: Five-hundred and four women and 529 men, aged between 25 and 55 y participating in the Fleurbaix Laventie Ville Santé study.

MEASUREMENTS: A nutritional survey was conducted between March and June 1993 using a 3-day food record. Reported weight and height were used to estimate body mass index and basal metabolic rate. Underreporters were defined as subjects whose ratio of mean energy intake to basal metabolic rate was lower than 1.05. Food consumption was compared between underreporters and non-underreporters.

RESULTS: Energy percentage of fat and carbohydrate were lower in underreporters than in non-underreporters in contrast to the energy percentage of protein. This was due to the fact that food items rich in fat and/or carbohydrates (such as butter, French fries, sugars and confectionery, cakes and pastries) were reported to be less frequently eaten and/or in smaller quantities in underreporters compared to non-underreporters.

CONCLUSION: Although this study presents some limitations, like the use of reported weight and a standard value for physical activity, it shows that reported foods differed, quantitatively and qualitatively, between severe underreporters and non-underreporters. Underreporting of food intake does not result from a systematical underestimation of portion sizes for all food items, but seems to concern specific food items which are generally considered 'bad for health'.

International Journal of Obesity (2000) 24, 1500-1506


underreporting; energy intake; foods; fat; carbohydrate; snacks


Food consumption is frequently assessed in studies on the etiology of chronic diseases. The majority of these nutritional studies rely on self-reported methods and are liable to several potential biases.1 In particular, self-reported energy intake is often underestimated. Doubly labelled water methods can be used to validate the estimated energy intake, but its costs and complexity do not allow it to be used in large epidemiological studies. A simple method developed by Goldberg et al 2 based on the ratio of energy intake to estimated basal metabolic rate (EI:BMR) can be used to identify weight-stable subjects who severely underestimate their energy intake. In a review, Black et al 3 concluded that underreporting of energy intake was observed in a great majority of nutritional surveys, whatever technique was employed. Some studies have shown that associations of nutritional factors with clinical, biological or socioeconomic parameters,4,5 are modified when underreporters are excluded from analysis, especially in surveys on obesity. A better description of underreporters and their food habits may help to reduce the bias induced by underreporting in nutritional epidemiology.

In a previous study,6 we observed that about 16% of a free-living population from Northern France were underreporters. As found in other studies,7,8 the prevalence of underreporting increased with body mass index but underestimation of energy intake was not confined to overweight subjects; it was strongly associated with dieting, cognitive dietary restraint and socioprofessional class. Although the characteristics of subjects who underreport their food intake have been well documented,6,7,9,10,11 the type of underreported foods and the causes of underreporting remain poorly understood. Heitmann and Lissner8 have shown that the underestimation of energy intake is not linked to underreporting of protein intake and concluded that an underestimation of foods rich in fat and/or carbohydrates may have caused the underestimation of energy intake. Few studies have focused on the description of food items reported by underreporters.9,10,12 Bingham et al 12 found that carbohydrate-rich foods like cakes, sugars and confectionery were less reported by underreporters, whereas vegetables, fruit and fish were reported similarly by underreporters and non-underreporters. Poppitt et al 13 found that food items eaten between meals were less frequently reported by underreporters, in both obese and non-obese subjects. Nevertheless, these studies did not differentiate qualitative and quantitative underestimation.

To verify the hypothesis that food items rich in fat and/or carbohydrates, those eaten as snacks and those considered 'bad for health' are specifically underestimated by subjects who underreported their energy intake, we compared food consumption between underreporters (UR) and non-underreporters (non-UR), in both qualitative and quantitative terms, by taking into account confounding factors.

Material and methods


The subjects of this survey were 1175 parents of the children included in the Fleurbaix Laventie Ville Santé study, a 5-year prospective study in Northern France evaluating the impact of a nutritional education at school on the eating behaviour of children and their family. The main sociodemographic characteristics of this population have been detailed elsewhere.6,14 After exclusion of 18 pregnant women, and 81 women and 43 men who indicated that they had lost weight over the last 2 months, 504 women and 529 men remained and were included in the present study.

The Fleurbaix Laventie Ville Santé study was approved by the ethical committee (Comité Consultatif de Protection des Personnes dans la Recherche Biomédicale, CCPPRB) of Lens and by the French Commission Nationale Informatique et Libertés (CNIL). All subjects gave their written informed consent.

Dietary assessment and definition of underreporters

Nutritional data were collected using a 3-day food record. Subjects had to report all the foods and beverages consumed at meals and between meals during two weekdays and one day of the weekend. They had to estimate portion sizes using household measures. Nine trained dieticians gave instructions on how to fill out the food records at a first home visit, and collected and checked the records at a second visit. Foods were coded and household measures were converted to grammes or millilitres. Nutrient intake was calculated using the French food composition tables 'Répertoire général des aliments'15 and the McCance and Widdowson's food composition tables.16 The mean of the three recorded days was used in the analyses. An autoquestionnaire on socioprofessional class, current body weight and height, weight preoccupations and weight history was also completed by participants. Basal metabolic rate (BMRest) was estimated according to Schofield's equations17 and the ratio of mean energy intake (EI) to the estimated basal metabolic rate (EI:BMRest) was used to define UR. Using Goldberg's criterion,2 UR were subjects whose EI:BMRest was lower than 1.05. Further details on the procedure of the nutritional survey and the definition of underreporters are given elsewhere.6,14

Data analysis

The food composition table contained 530 different foods but, for analysis, some items were combined, resulting in a total of 326 food items. The food consumptions were available for a whole day, not by meal. The food groups and food items studied were: vegetables, green vegetables only, fruit, milk, yoghurt, cheese, dairy desserts, butter, vegetable fat, meat, processed meat, eggs, fish, breakfast cereals, pasta and rice, potatoes (except French fries), French fries, bread, sugars and confectionery, cakes/pastries/ biscuits, fat-reduced foods, sweet beverages (including sodas, fruit juice, etc.), sodas only, fruit juice only, beer, wine and other alcoholic drinks. The classification of foods is shown in Appendix 1. The macronutrient composition of the specific food groups and food items is shown in Appendix 2.

The percentages of men and women who reported consuming at least once a given food item or one item of a given group, were compared between UR and Non-UR, using logistic regression procedures. Reported portion sizes were compared using general linear model procedures. Subjects who did not report consumption of a given food item or at least one item of the given food group were not included in the latter analyses. As age, body mass index (BMI=weight/height2) and socioprofessional class are strongly associated with eating habits and energy intake underestimation,6 analyses were adjusted for these three parameters by including them in the regression models. The contributions of macronutrient to energy intake and those of the three main meals and collations to energy intake were compared between UR and non-UR using a multivariate analysis of variance. Data are presented as adjusted percentages and means and standard error of the mean for portion sizes. Analyses were performed using SAS software.18


Underreporting of food intake involved 81 women and 85 men. UR were, on average, older than non-UR, had a higher mean BMI and were, in men, more frequently from a high socioprofessional class (Table 1). Weight preoccupations were more frequently reported by UR than by non-UR. The distribution of energy intake according to macronutrients was globally different between UR and non-UR (Wilk's criterion=28.8, P<0.0001 in men and Wilk's criterion=27.5, P<0.0001 in women). The contribution of protein was significantly higher in UR and was balanced by a lower contribution of fat and of carbohydrates, especially. In men only, the percentage of energy from alcohol was higher in UR than in non-UR. Absolute intakes of fat, protein and carbohydrates were lower in UR than in non-UR (Table 1).

Nevertheless, the differences between UR and non-UR were greater for fat and carbohydrates than for protein. Absolute intake of alcohol did not differ between UR and non-UR in men and was slightly higher in non-UR women. The repartition of energy intake according to breakfast, lunch, dinner and collations was globally different between UR and non-UR (Wilk's criterion=4.0, P<0.01 in men and Wilk's criterion=4.1, P<0.01 in women). The contribution of snacks and collations to energy intake was lower in UR than in non-UR in both women and men. The contributions of lunch in men and of dinner in women were higher in UR (Figure 1).

The median of the distribution of the number of recorded food items in the whole population was 31. In UR, only 19% (in both women and men) recorded more than 31 items, whereas this was 53% in non-UR (P<0.001).

Butter, dairy desserts, sugars and confectionery, cakes/pastry/biscuits, French fries and to a lesser extent fruit, were statistically less frequently reported by both female and male UR (Table 2). Eggs and potatoes were less frequently reported by women who underestimated their food intake, while male UR reported milk less frequently. Other food items like vegetables, green vegetables, fish and meat were reported with a similar frequency by UR and non-UR. Fat-reduced foods were reported more frequently by UR than by non-UR, but the difference did not reach statistical significance.

Sweet beverages were less frequently reported by UR than by non-UR, as were sodas and fruit juice (Table 3). Among alcoholic beverages, beer was less frequently reported by UR, in men only. Wine and the other alcoholic drinks were reported with a similar frequency.

The reported portion sizes of cheese, butter, processed meats, potatoes, French fries, bread, sugars and confectionery, cakes/pastry/biscuits, and pasta and rice were lower for UR than for non-UR, in both men and women (Table 4). In women only, vegetable fats were reported in lower quantities by UR. Although the differences were not statistically significant, fat-reduced foods, fish and green vegetables were reported with greater portion sizes by UR, in both men and women. Yoghurt was reported with significantly larger portion sizes by UR, in women. There was no statistically significant difference in the portion sizes of recorded beverages between UR and non-UR (Table 5).


The aim of the present study was to compare food consumption between UR and non-UR in a free-living population after taking into account confounding factors such as age, body mass index and socioprofessional class. Our results show that underreporting of energy intake is related to three phenomena which are linked: underreporting of some specific food items, underestimation of food size of some foods, and underreporting of snacks.

It must be pointed out, however, that there may have been some subjects who have reported their energy intake correctly but underreported the intake of one specific macronutrient while overreporting the two others. There is however no simple method to determine underreporting of specific macronutrients and we have to underline that the results of this study concern only subjects who underestimated their energy intake. Furthermore, only severe underreporters were studied here. By using a cut-off value of 1.05, as suggested by Goldberg,2 based on the assumption that the mean physical activity level was 1.55, some underreporters may have been defined as correctly reporting their energy intake but this way the probability of having a correct reporting subject defined as an UR was very low. Finally, it is important to notice that by using reported weight and height, which have been shown to be frequently under- and over-estimated respectively,19 the prevalence of UR may be underestimated. Thus, our results concern only severe underreporters in a particular population of parents aged between 25 and 55 and cannot be extrapolated to the whole French population.

On average, women and men UR reported respectively seven and five food items less than non-UR. This underreporting was food-item specific. Food items which were qualitatively underestimated were rich in fat and/or in carbohydrates (butter, French fries, sugars and confectionery, cakes/pastries/biscuits, etc.) while foods rich in protein (meat, vegetables, etc.), were reported as frequently in UR and non-UR.

The majority of food groups less frequently recorded by UR were also reported with lower portion sizes. Some foods were reported with a similar frequency but with lower portion sizes; this concerned cheese, processed meat, bread, pasta and rice (and potatoes in men only and vegetable fats in women). On the other hand, several food items or groups, like vegetables, especially green vegetables, meat and fish, were reported with similar frequencies and quantities by UR. Although differences did not reach significance, fat-reduced foods were reported more frequently and in greater portion sizes by UR.

Contribution of alcohol to energy intake was found to be similar in both UR and non-UR women, but higher in men who underestimated their energy intake compared to those who did not. Bingham also found no difference in alcohol intake between UR and non-UR.20 We may hypothesize that reasons for alcohol underestimation are probably different from those for energy intake. Underestimation of alcohol intake probably concerns other subjects than those who underestimate their energy intake.

As reported by others,9,10,12,21 UR were found to have a higher protein intake and a lower intake of both fat and carbohydrates. This is in line with the observation that UR had lower contributions from snacks to their energy intake balanced by higher contributions of the main meals, especially lunch and dinner. Among the food items reported less frequently or with smaller portion sizes by underreporters, a lot of them are easily consumed between meals, like confectioneries, cakes, pastries and biscuits, and sweet beverages. These results are concordant with those found in an experimental survey in a metabolic facility; only foods eaten as snacks and rich in carbohydrates were underreported.13 However, this study was realized in a small sample of women under very specific conditions which differ from free-living conditions. The authors concluded that the underreporting of energy intake in their study was due to difficulties for subjects in remembering what they had eaten between meals. However, in our study, like in those from Pryer10 and Bingham,12 underreporting was not limited to foods eaten between meals; some foods central to a meal such as French fries, bread, potatoes, pasta and rice were, especially quantitatively, less recorded by UR.

The fact that UR reported some food items less frequently, while they recorded them with similar portion sizes and the fact that they reported some items with a higher portion size, tends to show that food intake underreporting does not only result from inaccurate portion sizes estimates. Even if we cannot exclude this kind of error, it does not appear to be the main reason for underreporting. In a recent study, Macdiarmid and Blundell22 investigated why people underreport their food intake. They could classify subjects who admitted underreporting into two main groups: those for whom the recording of a normal intake was inconvenient but their mean EI:BMR was 1.50 so that they were not defined as underreportersby our criterion. The second group admitted underreporting for reasons of guilt and they had a lower mean EI:BMR (1.20), which corresponds to the cut-off used to define underreporting in epidemiologic studies. This latter group was characterized by a high dietary restraint, which is in line with the well-documented association of underreporting with dietary restraint or weight concern.6,11,23 Restraint subjects associate a higher level of guilt with many common foods than unrestrained subjects.24 Subjects who had higher weight fluctuations and especially those who were very concerned with dieting, reported also more anxiety, discomfort and guilt when eating specific foods.25 On contrary to non-dieters, dieters feel guilty with both sweet and salt snacks and with high caloric and high-fat foods.26

Food items generally considered 'bad for health' (butter, French fries, etc.) were less reported by UR than food items frequently considered 'good for health' (fat-reduced foods, vegetables, etc). Nevertheless, in our study, no data concerning food perception was available. As UR felt more concerned about their weight and their image, we may assume that they were also more concerned about their diet,12,23 and that they were more prone to modifying their diet during the recording days. We may also assume that, instead of really modifying their diet UR under-report specific foods in order to appear in a socially favourable light.27

In conclusion, for nutrition research, data should be analysed with and without exclusion of the subjects with a high probability of underreporting. The results of this study also point out to the need to train dieticians or interviewers to obtain valid data on consumption of especially snacks and foods with a bad image. It also appears that questions about attitude towards food, food perceptions, social desirability and specific questions about snacking habits are necessary in dietary surveys.


We thank Boehringer-Mannheim France, Eridania Béghin-Say, Groupe Fournier, Lesieur and Nestlé France for their support to the Fleurbaix Laventie Ville Santé study.


1 Schoeller DA. Limitations in the assessment of dietary energy intake by self-report. Metabolism 1995; 44: (Suppl 2) 18-22. MEDLINE

2 Goldberg GR, Black AE, Jebb SA, Cole TJ, Murgatroyd PR, Coward WA, Prentice AM. Critical evaluation of energy intake data using fundamental principles of energy physiology: 1. Derivation of cut-off limits to identify under-recording. Eur J Clin Nutr 1991; 45: 569-581. MEDLINE

3 Black AE, Goldberg GR, Jebb SA, Livingstone MBE, Cole TJ, Prentice AM. Critical evaluation of energy intake data using fundamental principles of energy physiology: 2. Evaluating the results of published surveys. Eur J Clin Nutr 1991; 45: 583-599. MEDLINE

4 Lissner L, Heitmann BL, Lindroos AK. Measuring intake in free-living human subjects: a question of bias. Proc Nutr Soc 1998; 57: 333-339. MEDLINE

5 Carter LM, Whiting SJ. Underreporting of energy intake, socioeconomic status, and expression of nutrient intake. Nutr Rev 1998; 56: 179-182. MEDLINE

6 Lafay L, Basdevant A, Charles MA, Vray M, Balkau B, Borys J-M, Eschwège E, Romon R. Determinants and nature of dietary underreporting in a free-living population: the Fleurbaix Laventie Ville Santé (FLVS) study. Int J Obes Relat Metab Disord 1997; 21: 567-573. MEDLINE

7 Price GM, Paul AA, Cole TJ, Wadsworth MEJ. Characteristics of the low-energy reporters in a longitudinal national dietary survey. Br J Nutr 1997; 77: 833-851. MEDLINE

8 Heitmann BL, Lissner L. Dietary underreporting by obese individuals-is it specific or non-specific? BMJ 1995; 311: 986-989. MEDLINE

9 Johansson L, Solvoll K, Bjørneboe GEA, Drevon CA. Under- and overreporting of energy intake related to weight status and lifestyle in a nationwide sample. Am J Clin Nutr 1998; 68: 266-274. MEDLINE

10 Pryer JA, Vrijheid M, Nichols R, Kiggins M, Elliott P. Who are the 'low energy reporters' in the Dietary and Nutritional Survey of British Adults? Int J Epidemiol 1997; 26: 146-153. MEDLINE

11 Heitmann BL. The influence of fatness, weight change, slimming history and other lifestyle variables, on diet reporting in Danish men and women aged 35-65 years. Int J Obes Relat Metab Disord 1993; 17: 329-336. MEDLINE

12 Bingham SA, Cassidy A, Cole TJ, Welch A, Runswick SA, Black AE, Thurnham D, Bates C, Khaw KT, Key TJA, Day NE. Validation of weighed records and other methods of dietary assessment using the 24 h urine nitrogen technique and other biological markers. Br J Nutr 1995; 73: 531-550. MEDLINE

13 Poppitt SD, Swann D, Black AE, Prentice AM. Assessment of selective under-reporting of food intake by both obese and non-obese women in a metabolic facility. Int J Obes Relat Metab Disord 1998; 22: 303-311. MEDLINE

14 Lafay L, Vray M, Boute D, Basdevant A and the FLVS Study Group. Food and nutritional data for a population from northern France: The Fleurbaix Laventie Ville Santé (FLVS) study. Rev Epidémiol Santé Publ 1998; 46: 263-275.

15 Feinberg M, Favier JC, Ireland-Ripert J. Répertoire général des aliments. Technique et documentation. Lavoisier; Paris, 1991,

16 Paul AA, Southgate DAT (eds). 4th edn. HMSO: London, 1978,

17 Schofield WN, Schofield C, James WPT. Basal metabolic rate. Hum Nutr Clin Nutr 1985; 39C: (Suppl 1) 1-96.

18 SAS/STAT User's Guide, Version 6. 4th edn. SAS institute Inc.: Cary, NC, 1989,

19 Kuskowska-Wolk A, Karlsson P, Stolt M, Rössner S. The predictive validity of body mass index based on self-reported weight and height. Int J Obes 1989; 13: 441-453. MEDLINE

20 Bingham SA. The use of 24-h urine samples and energy expenditure to validate dietary assessments. Am J Clin Nutr 1994; 59: (Suppl) 227S-231S. MEDLINE

21 Rutishauser IHE. Is dietary underreporting macronutrient specific? Eur J Clin Nutr 1995; 49: 219-220. MEDLINE

22 Macdiarmid JL, Blundell JE. Short report: dietary underreporting: what people say about recording their food intake. Eur J Clin Nutr 1997; 51: 199-200. MEDLINE

23 Ballard-Barbash R, Graubard I, Krebs-Smith SM, Schatzkin A, Thompson FE. Contribution of dieting to the inverse association between energy intake and body mass index. Eur J Clin Nutr 1996; 50: 98-106. MEDLINE

24 Sunday SR, Einhorn A, Halmi KA. Relationship of perceived macronutrient and caloric content to affective cognitions about food in eating-disordered, restrained, and unrestrained subjects. Am J Clin Nutr 1992; 55: 362-371. MEDLINE

25 Kirkley BG, Burge JC, Ammerman A. Dietary restraint, binge eating, and dietary behavior patterns. Int J Eating Disorder 1988; 7: 771-778.

26 King GA, Herman CP, Polivy J. Food perception in dieters and non-dieters. Appetite 1987; 8: 147-158. MEDLINE

27 Hebert JR, Clemow L, Pbert L, Ockene IS, Ockene JK. Social desirability bias in dietary self-report may compromise the validity of dietary intake measures. Int J Epidemiol 1995; 24: 389-398. MEDLINE

Appendix 1

Appendix 2


Figure 1 Contribution of breakfast, lunch, dinner and snacks to total daily energy intake in underreporters (UR), and non-underreporters (non-UR), for men and women.


Table A1  Classification of foods

Table 1 Comparison of general characteristics and nutrient intake between underreporters (UR) and non-underreporters (non-UR) for men and women; the FLVS Study

Table 2 Percentage of subjects reporting to consume a food (group), adjusted for age, BMI and socioprofessional class for underreporters (UR) and non-underreporters (non-UR) in 504 women and 529 men; the FLVS Study

Table 3 Percentage of subjects reporting to consume beverage, adjusted for age, BMI and socioprofessional class for underreporters (UR) and non-underreporters (non-UR) in 504 women and 529 men; the FLVS Study

Table 4 Reported portion sizes (g/day) (in consumers only), adjusted for age, BMI and socioprofessional class by underreporters (UR) and non-underreporters (non-UR) for women and men; the FLVS Study

Table 5 Reported beverage intakes (ml/day) (in consumers only), adjusted for age, BMI and socioprofessional class by underreporters (UR) and non-underreporters (non-UR) for women and men; the FLVS Study

Table A2  Composition table of specific food items (g/100 g food)

Received 3 June 1999; revised 2 May 2000; accepted 24 May 2000
November 2000, Volume 24, Number 11, Pages 1500-1506
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