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Journal of the American College of Nutrition, Vol. 26, No. 4, 327-333 (2007)
Published by the American College of Nutrition

Low Energy Reporting Related to Lifestyle, Clinical, and Psychosocial Factors in a Randomly Selected Population Sample of Greek Adults: The ATTICA Study

Mary Yannakoulia, PhD, Demosthenes B. Panagiotakos, PhD, Christos Pitsavos, MD, PhD, Eirini Bathrellou, MSc, Christina Chrysohoou, MD, PhD, Yannis Skoumas, MD, PhD and Christodoulos Stefanadis, MD, PhD

Department of Nutrition and Dietetics, Harokopio University (M.Y., D.B.P., E.B.)
First Cardiology Clinic, School of Medicine, University of Athens (C.P., C.C., Y.S., C.S.), Athens, GREECE

Address reprint requests to: Mary Yannakoulia, PhD, Department of Nutrition and Dietetics, Harokopio University, El. Venizelou 70, Athens 17671, GREECE. E-mail: myiannak{at}hua.gr


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 CONCLUSIONS
 ACKNOWLEDGMENTS
 REFERENCES
 
Objective: Aim of the present study was to identify potential dietary, lifestyle, psychosocial and clinical correlates of underreporting in a population-based sample.

Methods: Following a random multistage sampling, 1514 men (46±13 years old) and 1528 women (45±13 years old) from the Attica area, in Greece, participated in this study. All participants underwent a standard assessment procedure that included clinical, psychosocial and lifestyle parameters. Food consumption was assessed through a validated semi-quantitative food frequency questionnaire. The ratio of energy intake to estimated basal metabolic rate (EI/BMR) and the Goldberg cut-off points were used for the classification of subjects as low energy reporters (LERs) and non-LERs.

Results: LERs represented 12.2% of the sample. This percentage was higher in obese subjects compared to overweight or normal weight (20.6 % vs. 9.9 % vs. 10.6 %, p = 0.05), as well as in women compared to men (14.6% vs. 9.9%, p<0.001). Data analysis was stratified by gender, since a significant interaction was observed between gender and LER group on several dietary parameters. Female LERs had higher Med Diet Score compared to non-LERs (30.6 ± 8.2, 95%CI 30.2–31.04 vs. 26.9 ± 6.3, 95%CI 26.05–27.7, p<0.001). Multiple regression analysis revealed that lower EI/BMR values were associated with younger age (p<0.001), higher BMI (p<0.001), presence of diabetes mellitus (p=0.012) and lower depression score (p=0.056) in women, whereas with younger age (p<0.001), higher BMI (p<0.001), higher education level (p=0.046) and higher anxiety score (p=0.08) in men.

Conclusion: Several psychosocial and clinical characteristics operate in low energy reporting in both genders. Nutrition-related professionals should be aware of these gender-specific trends in dietary assessment procedures.

Key words: underreporting, energy intake, overweight, diabetes, depression, anxiety


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 CONCLUSIONS
 ACKNOWLEDGMENTS
 REFERENCES
 
The determination of food intake is the core of dietary assessment. Linking this information with other nutritional status measurements, disease outcomes or lifestyle behaviours is important in public health. There is a number of methods that can be used alone or in combination to monitor dietary intake. However, available literature reveals a variable degree of misreporting in the total energy and individual food and nutrient intakes, regardless of the method employed [1–4]. Still, it is the misreporting of energy intake that has traditionally attracted the most interest; if energy is inadequate, intakes of other nutrients are likely to be suboptimal as well.

Relevant studies have shown that underreporting of energy intake is widespread within the population, with the prevalence of low energy reporters (LERs) ranging from 10% to 88%, depending on the population studied and the method used [5]. Such a bias may considerably compromise the interpretation of dietary surveys. Hence, identifying the factors associated with underreporting remains an active field of research, in an attempt to more thoroughly understand how the various subject characteristics and attributes could influence reporting of food intake.

A number of studies have been conducted along these lines and, for the most part, indicate that underreporting prevails among women [6–8], older persons [9,10], and overweight individuals [7,8,10–14]. Besides gender, age and adiposity, there is much inconsistency regarding the effect of several other socioeconomic, demographic and lifestyle factors [7,8,11,12,14,15], while information on the role of various cognitive and behavioural parameters, e.g. restraint and distress, body image perception, depression and anxiety symptomatology, is scarce and studied only in female populations [16]. A recent review on the role of psychosocial and behavioral characteristics on energy misreporting indicate that more research evaluating the effect of anxiety and other psychological distress is needed [17]. What is more, the potential influence of some clinical conditions has never been considered, though underreporting has been found to be high in clinical populations [18–22].

Aim of the present study was to evaluate the association of dietary, lifestyle, psychosocial and clinical characteristics with underreporting of energy in a randomly selected population sample of "apparently healthy" Greek men and women.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 CONCLUSIONS
 ACKNOWLEDGMENTS
 REFERENCES
 
Study Population
The "ATTICA" study has been carried out in the province of Attica (including 78% urban and 22% rural areas), where Athens is the major metropolis. The sampling was random, multistage (by city) and it was based on an age - sex distribution of the province of Attica provided by the National Statistical Service (census of 2001). From the 4056 inhabitants who were randomly selected to participate into the study, 3042 agreed to participate (75% participation rate). Of them, 1514 were men (46 ± 13 years old) and 1528 women (45 ± 13 years old). Subjects had no clinical evidence for cardiovascular disease, chronic viral infections, cold or flu, acute respiratory infection, dental problems or any type of surgery in the week preceding the study. Aims, methods and design of the ATTICA Study have been published elsewhere [23–25].

Demographic, Lifestyle, Clinical and Biochemical Characteristics
From May 2001 to December 2002, all participants underwent a standard interviewing procedure by trained personnel (cardiologists, general practitioners, dieticians and nurses), based on the standard ATTICA questionnaire, composed from several thematic entities. Information on subjects’ gender, age, education level (in years of school) and smoking habits (cigarette packs per day and years of smoking) was collected. Being physically active was defined as having a leisure-time activity at least once per week during the past year, regardless of its intensity or duration. All other subjects were defined as physically inactive.

Arterial blood pressure was measured three times at the right arm at the end of the physical examination with subject in sitting position at least for 30 minutes. Patients whose average blood pressure levels were greater or equal to 140 / 90 mm Hg or were under antihypertensive medication were classified as having hypertension. In addition, for classification purposes hypercholesterolemia was defined as total serum cholesterol levels greater than 200 mg/dl or the use of lipid-lowering agents and diabetes mellitus as fasting blood glucose levels >125 mg/dl or the use of antidiabetic medication.

Height and weight were measured without shoes and in light clothing to the nearest 0.5 cm and 100 g, respectively. Body mass index (BMI) was calculated as weight (in kilograms) divided by height (in meters squared). Based on the World Health Organization [26], body weight status was categorized as normal weight, defined as BMI <25.0 kg/m2, overweight as BMI 25.0–29.9 kg/m2, and obesity as BMI≥30 kg/m2.

Psychological State: Anxiety and Depression
The anxious state was assessed using the Spielberger State-Trait Anxiety Inventory (STAI), a 20-item self-reported questionnaire. The STAI differentiates between the temporary condition of "state anxiety" and the more general and long-standing quality of "trait anxiety" [27,28]. The 20 items are rated from 1 to 4 in terms of frequency categories (never, sometimes, often, always) and total scores are obtained by summing the values assigned to each response (namely, range from 20 to 80). Higher scores indicate more trait or state anxiety [27]. Depressive symptomatology was assessed using a translated and validated version of the Zung Self-Rating Depression Scale (ZSDS), a well-known and world-widely used self-rating scale for the measurement of depression [29]. The ZSDS consists of 20 items that cover affective, psychological, and somatic symptoms (range from 20 to 80). Higher scores on this scale are indicative of more severe depression [29].

Dietary Assessment
Consumption of non-refined cereals and products, vegetables, fruits, pulses, dairy products, fish, nuts, potatoes, eggs, sweets, poultry, red meat and meat products were measured as an average per week during the past year through a validated semi-quantitative food - frequency questionnaire [30] that has been kindly provided by the Department of Hygiene of Athens Medical School. Energy and macronutrient intake were calculated based on the participants’ responses on the questionnaire. In addition, a special Mediterranean Diet score (Med Diet Score) was estimated for each participant, according to the reported monthly frequency consumption of various food groups, following the guidelines of the Mediterranean diet pyramid [31]. Higher values of this score indicate adherence to the traditional Mediterranean diet.

Assessment of Underreporting
Basal Metabolic Rate (BMR) was estimated using the Schofield equations for the prediction of BMR [32], adopted by the 2004 FAO/WHO/UNU report [33]. The ratio of the Energy Intake / Basal Metabolic Rate (EI/BMR) was then calculated for each individual. Participants with EI/BMR <1.14 were classified as "energy underreporters" or "low energy reporters" (LERs) based on the cut-off limits developed by Goldberg et al [32], whereas those with EI/BMR >2.4 as "energy overreporters", for the range 2.0–2.4 was suggested as the maximum for sustainable lifestyle [33,34]. "Normal energy reporters" or non-LERs were participants with 1.14≤EI/BMR≤2.4.

Statistical Analysis
Continuous variables are presented as mean values ± standard deviation and 95% confidence intervals, while categorical variables are presented as absolute and relative frequencies. Associations between categorical variables were tested by use of chi-squared test. Comparisons between normally distributed continuous variables and groups of the participants were performed by the use of Student's t-test, after testing for equality of variances and normality of the dependent outcome. The Shapiro - Wilk test was applied to assess normality. Multiple regression analysis was then applied in order to evaluate the explanatory ability of various characteristics of the participants in relation to the investigated outcome, after adjusting for potential confounders and interactions using likelihood ratio tests. The results from the regression models are presented as standardised beta (B) coefficients. The assumptions of linearity for the continuous independent variables and constant variance of the standardized residuals were assessed through plotting the residuals against the fitted values. Co-linearity in the multivariable models was tested using the Variance Inflation Factor (VIF); typically, VIF > 5 is of concern. The explanatory ability of each regression model is evaluated using the coefficient of determination, R2. All reported P-values were based on two-sided tests. Statistical Package for Social Sciences software, version 13.0 (SPSS Inc. 2003, Chicago, IL, USA), was used for all the statistical calculations.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
CONCLUSIONS
 ACKNOWLEDGMENTS
 REFERENCES
 
From the study sample, 11.3% (n = 171) of men and 15.7% (n = 240) of women were on a slimming diet (p < 0.001) and were therefore excluded from the analysis. Descriptive characteristics of the remaining sample (n = 2631) are shown in Table 1. The mean value of EI/BMR for the whole sample was 1.54 ± 0.30 (95% CI 1.53–1.55), while men were found to have a higher mean EI/BMR compared to women (1.55 ± 0.33, 95%CI 1.54–1.56 vs. 1.53 ± 0.26, 95%CI 1.52–1.54, p = 0.034). Low energy reporters (LERs) represented 12.2 % of the population (95%CI 10.9–13.5). This percentage was higher in women, compared to men (14.6 % vs. 9.9% respectively, p ≤ 0.001), as well as in obese subjects compared to overweight and normal weight ones (20.6 % vs. 9.9 % and 10.6 % respectively, p = 0.05). Over-reporters accounted only for 2.5 % (n = 66) of the whole population and were not included in the subsequent analysis.


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  		Table 1. Descriptive Characteristics of the Studied Sample [Mean (Standard Deviation) or Relative Frequency]

 
A significant interaction was observed between gender and LER group on Med Diet score (p for interaction <0.001), various food groups (i.e., dairy products: p < 0.001, potatoes: p < 0.001 and poultry: p < 0.001). Thus, data analysis was stratified by gender. Male and female LERs, compared to normal energy reporters, had significantly lower energy intake and higher percentage of energy provided by protein. No other differences were observed with regards to macronutrient intake in both sexes (Table 2). However, female LERs were found to have a higher Med Diet Score compared to non-LERs (30.6 ± 8.2, 95%CI 30.2–31.04 vs. 26.9 ± 6.3, 95%CI 26.05–27.7, p < 0.001). On a food group basis, LERs’ intake of specific food items differed according to gender. Female LERs consumed significantly fewer vegetables, more potatoes, meat and poultry compared with non-LERs, while male LERs consumed more dairy products and meat and less fish in comparison to male normal energy reporters (Table 2). Among LERs, females reported lower energy intake compared to males (p < 0.001), had higher Med Diet Score (p < 0.001) and reported to consume less meat (p < 0.05). No other differences were detected between female and male LERs regarding macronutrient composition and food intake (see Table 2).


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  		Table 2. Dietary Assessment, Macronutrient Composition and Weekly Consumption of Various Food Groups (Servings/Week) by LER Status [mean (Standard Deviation)]

 
Demographic, anthropometric, dietary, clinical and psychological correlates of energy underreporting were further explored using multiple regression analysis, to control for successively introduced potential confounders. Since several differences were observed in univariate analyses between genders (especially on EI and BMI levels), the regression analysis was stratified by gender. It was revealed that lower EI/BMR values were associated with younger age, higher BMI, presence of diabetes mellitus and lower depression score (borderline significance) in women, whereas in men lower EI/BMR values were associated with younger age, higher BMI, higher education level and higher anxiety score (borderline significance) (Table 3). Other factors were also included in the models but they were not significantly associated with EI/BMR, such as years of physical activity and smoking status, presence of hypertension, hypercholesterolemia and Med Diet Score. No co-linearity was observed between the independent predictors of EI/BMR (i.e. all VIF < 4), while the final models presented in Table 3 showed good explanatory ability (R2 in males = 22% and R2 in females = 8%).


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  		Table 3. Results from Multiple Regression Model* That Evaluated Associations of Various Characteristics of the Participants with EI/BMR

 

   DISCUSSION
 
In this work we sought to explore the effect of a variety of factors, like demographic, lifestyle, psychosocial and clinical, in low energy reporting. Our results indicate that, the presence of diabetes mellitus and, less significantly, the absence of depression were associated with underreporting of energy intake in females. Women, compared to men, tend to be more preoccupied about weight, food and dieting; therefore, they are more prone to be embarrassed about their dietary intake and, thus, more prone to underreport [35]. On the other hand, diabetic patients are concerned about their food intake, as one of the important means for managing their disease state [36]. They usually receive extensive information on food, are becoming familiar with portion sizes and often monitor their dietary intake in order to achieve beneficial changes in biochemical markers. In spite of seemingly becoming more aware about their diet, they exhibit high rates of low energy reporting [19,20,37]. The significance placed on dietary intake among diabetic patients in combination with female sex renders diabetic women a high-risk group for low energy reporting.

Interestingly, we found depression symptomatology tended to prevent women from underreporting. Although this may seem irrational, it could be hypothesised that while the phenomenon of low energy reporting may be at least partially explained by a feeling of social pressure regarding food intake [38], depression does not induce such a feeling or makes women indifferent of what they report. Similar finding with regards to the positive association between depression and accuracy of energy reporting have been also presented by Kretsch et al. in obese women [16], and were attributed to factors related to the questionnaire used, namely the nature of the questions and the validity of low scores.

On the other hand, in males, high education and, less significantly, presence of anxiety were found to predict low energy reporting. The effect of education on the underestimation of energy intake is controversial in the literature [4]: less educated people with poor literacy skills are expected to underreport their food intake; on the other hand, health or diet consciousness in the more educated people may result in the same response concerning food intake. As far as anxiety is concerned, our results indicate that high scorers in STAI scale may be associated with low EI/BMR ratio, and, thus, with implausible dietary intakes. Anxiety, a generalised feeling of anticipation, dread and inner emotional tension, seems to interfere with dietary behaviours as well, leading men intentionally or not to underreport energy intake. Alternatively, bearing in mind some evidence suggesting that stress in general is associated with restraint eating in males [39], one may speculate that restraint is the underlying element of the anxious men that make them more prone to report lower than actual dietary intake; otherwise, it may be that stressed men tend to underreat and they were falsely classified as under-reporters by this assessment method.

Age and BMI were found to be significant predictors of low energy reporting in both males and females, with people of younger age and higher BMI being more likely to underreport. With regards to age, our finding opposes that of the majority of relevant studies, despite the fact that there are few studies in the literature describing similar trends [16,40,41]. Nevertheless, Livingstone and Black [4] hypothesised that the higher proportion of low energy reporters among older people may not be a true finding but rather an artifact of applying a single cut-off for EI/BMR to all ages, as older people have lower energy expenditure. From our data, we could, then, assume that younger age people incline towards underreporting food intake due to being more health conscious and diet preoccupied. Consistently with the majority of studies [38], BMI was positively correlated to low energy reporting. More specific, LERs were represented two times more among obese individuals compared to normal weight or overweight ones.

Noticeably, meat weekly servings were found to be statistically higher in both male and female LERs compared to their non-LERs counterparts. The finding may be also reflected in the significantly higher percentage of energy derived from protein exhibited by LERs compared to non-LERs in this study as well as in previous research [8,11,20,42]. However, the differences in the percent of protein energy in both males and females are not so great as to lead to mistaken conclusions with regards to macronutrient balance.

Overall, the percentage of underreporting was 12.2%, which is similar to what was described for a Greek population in a previous study using the same cut-off point and the same dietary assessment tool, namely a food frequency questionnaire [43]. With regards to the assessment of energy intake, it would be argued that every tool induces method-specific alterations in both actual eating and eating recording. However, Black & Cole [2] concluded that there was a tendency for people classified as under-reporters by one method to be also by other methods of dietary intake, even the more sophisticated ones.

The present study, as a cross-sectional one, has several limitations. Confounding factors may always exist; therefore, no causal inference could be made regarding the link between the factors tested and the low energy reporting and the hypotheses described need to be assessed through future clinical studies. Furthermore, the degree of underreporting was estimated by the use of BMR prediction equation instead of directly measuring metabolic rate by the doubly labeled water method, and no distinction was made between under-recording and under-eating as different entities of low energy reporting.


   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 CONCLUSIONS
ACKNOWLEDGMENTS
 REFERENCES
 
Assessment of dietary intake is a laborious task, which may be complicated by the presence of underreporting. Underreporting should not be solely regarded as a methodological problem. Understanding its nature and the factors associated with remains an important issue. Several psychosocial and clinical characteristics operate in male and female low energy reporters, sometimes in a different way. Nutrition-related professionals should be aware of these trends and develop appropriate tools to detect the degree of underreporting and minimize its effect on the estimation of energy intake. In public health nutrition, this is of major importance, given the multilevel relationship between diet and disease.


   ACKNOWLEDGMENTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 CONCLUSIONS
 ACKNOWLEDGMENTS
REFERENCES
 
The ATTICA Study is funded by research grants from the Hellenic Cardiology Society and the Hellenic Atherosclerosis Society. The authors would like to thank the field investigators of "ATTICA" study: Natasa Katinioti (physical examination), Akis Zeimbekis (physical examination), Spiros Vellas (physical examination), Efi Tsetsekou (physical/psychological evaluation), Dina Massoura (physical examination), Lambros Papadimitriou (physical examination), Marina Toutouza (senior investigator / biochemical analysis), as well as the technical team: Carmen Vassiliadou (genetic analysis), Manolis Kambaxis (nutritional evaluation), Konstadina Palliou (nutritional evaluation), Constadina Tselika (biochemical evaluation), Sia Poulopoulou (biochemical evaluation) and Maria Toutouza (database management).

Received June 27, 2006. Accepted November 8, 2006.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 CONCLUSIONS
 ACKNOWLEDGMENTS
 REFERENCES
 

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