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Anthropometric, metabolic, dietary and psychosocial profiles of underreporters of energy intake: a doubly labeled water study among overweight/obese postmenopausal women—a Montreal Ottawa New Emerging Team study

Abstract

Background/Objectives:

To analyze the anthropometric, metabolic, psychosocial and dietary profiles of underreporters, identified by the doubly labeled water technique, in a well-characterized population of overweight and obese postmenopausal women.

Subjects/Methods:

The study population consisted of 87 overweight and obese sedentary postmenopausal women (age: 57.7±4.8 years, body mass index: 32.4±4.6 kg/m2). Subjects were identified as underreporters based on the energy intake to energy expenditure ratio of <0.80. We measured (1) body composition (by dual-energy X-ray absorptiometry), (2) visceral fat (by computed tomography), (3) blood profile, (4) resting blood pressure, (5) peak oxygen consumption (VO2 peak), (6) total energy expenditure, (7) muscle strength and (8) psychosocial and dietary profiles.

Results:

Out of 87 subjects, 50 (57.5%) were identified as underreporting subjects in our cohort. Underreporters showed higher levels of body mass index, fat mass, visceral fat, hsC-reactive protein, perceived stress and percentage of energy from protein, as well as lower levels of VO2 peak, dietary intake of calcium, fiber, iron, vitamin B-1 and 6, as well as servings of fruit and vegetables. Logistic regression analysis showed that fat mass, odd ratio 1.068 (95% confidence interval 1.009–1.130) and perceived stress, odd ratio 1.084 (95% confidence interval 1.011–1.162) were independent characteristics of underreporters.

Conclusions:

Results from this study show significant differences in anthropometric, metabolic, psychosocial and dietary profiles between underreporters and non-underreporters in our cohort of overweight and obese postmenopausal women.

Introduction

Accurate assessment of energy intake (EI) is crucial in evaluating clinical status, nutrition interventions and health outcomes. EI is commonly estimated using self-report dietary assessment techniques, with their inherent concerns of misreporting, day-to-day variations and changes in dietary habits (Trabulsi and Schoeller, 2001). Underreporting is a frequent problem using these techniques and can range widely from 10 to 91% depending on the population, method, definition and cut-point used to categorize underrepoters (Briefel et al., 1997; Hirvonen et al., 1997; Asbeck et al., 2002; Livingstone and Black, 2003; Livingstone et al., 2003). Underreporting has been shown to be more prevalent in women than in men (Briefel et al., 1997; Asbeck et al., 2002; Dwyer et al., 2003), in older individuals than in younger subjects (Briefel et al., 1997; Hirvonen et al., 1997; Huang et al., 2005) and among obese individuals (Briefel et al., 1997; Hirvonen et al., 1997; Price et al., 1997; Pryer et al., 1997).

The doubly labeled water (DLW) method is accurate, unobtrusive and unbiased for the measurement of total energy expenditure (TEE) over an extended period of time in free-living individuals. Therefore, this approach becomes a powerful technique for assessing the accuracy of conventional EI methodologies. Indeed, several studies have shown that EI using self-reported methods is underreported to TEE when the DLW technique is used (Black and Cole, 2001; Hill and Davies, 2001; Trabulsi and Schoeller, 2001).

Evidence shows that underreporting may be associated with more frequent dieting attempts and an unfavorable psychosocial profile such as depression, lower body image, eating restraint, disinhibition and anxiety (Asbeck et al., 2002; Novotny et al., 2003; Tooze et al., 2004; Abbot et al., 2008). Moreover, several studies have observed that dietary factors such as eating less fat may be predictors of underreporting (Briefel et al., 1997; Price et al., 1997; Voss et al., 1998). Finally, to our knowledge only one study has examined the association between underreporting and metabolic complications (Rosell et al., 2003). In that study, the prevalence of the metabolic syndrome was significantly higher in underreporters.

A major limitation in this area is that most studies examining the profiles of underreporters of EI considered only anthropometric, metabolic, psychosocial and dietary characteristics separately at a time. To our knowledge no data seem to be available using a multivariate approach in one study. This approach may give us a better insight into the most important factors involved in underreporting. Therefore, the purpose of this study was to analyze the anthropometric, metabolic, dietary and psychosocial profiles of underreporters, identified by the DLW technique, in a well-characterized population of overweight and obese postmenopausal women.

Materials and methods

The study sample of baseline data only was drawn from the Montreal Ottawa New Emerging Team project in obesity designed to analyze the effect of resistance training during weight loss (6 months) and weight maintenance (12 months) on detailed, metabolic, inflammatory and hormonal profile, body composition, energy expenditure, psychosocial profile and insulin sensitivity in overweight and obese postmenopausal. The study sample consisted of 89 out of 137 non-diabetic sedentary overweight and obese postmenopausal women aged between 46 and 69 years old, in whom dietary and DLW energy expenditure data were available. The study was approved by the University of Montreal ethics committee. Participants were recruited from the Montreal communities using advertisements in the local newspapers. After reading and signing the consent form, each participant was invited to the Metabolic Unit for a series of tests. Inclusion criteria and methods for body composition, computed tomography, blood pressure, blood samples, peak oxygen consumption (VO2 peak), muscle strength, energy expenditure as well as dietary and psychosocial factors were determined as described earlier (Messier et al., 2008; St-Pierre et al., 2009; Strychar et al., 2009). Briefly, daily energy expenditure was determined from DLW over a 10-day period and the dietary food record was completed during the same period of time as the DLW. It should be noted that the aforementioned parameters were chosen because they have been reported to be associated with chronic diseases such as type II diabetes, cardiovascular disease and obesity (Rosengren et al., 2004; Iqbal et al., 2008; McQueen et al., 2008). Women were included in the study if they met the following criteria: (1) body mass index 27 kg/m2, (2) cessation of menstruation for more than 1 year and a follicle-stimulating hormone level 30 U/l and (3) free of known inflammatory disease. On physical examination or biological testing, all participants had no history or evidence of: (1) cardiovascular disease, peripheral vascular disease or stroke, (2) diabetes and (3) medications that could affect cardiovascular function and/or metabolism.

Body composition

Body weight, lean body mass and fat mass were measured using dual-energy X-ray absorptiometry (General Electric Lunar Corporation version 6.10. 019, Madison, WI, USA).

Nutrient intakes

Food intake was assessed using a 3-day food record at baseline. Subjects were instructed by a registered dietitian to keep a record of food intake, including condiments and beverages, over two week days and one weekend day although maintaining their usual habits. Subjects were asked to write as much information as possible regarding the foods they ate (that is, brand names, percentage of fat, how the food was cooked, and so on.). An example of a detailed meal was given to the subjects. No portion-size estimation measurement aid was given to the subjects, however, they were asked to use the usual tools to estimate their portion sizes (that is, teaspoon/tablespoon/cup in ml or ounces) and, if possible, weight their portions. On their return, each food record was reviewed by a registered dietitian with each subject to verify the precision of the information written and to complete missing information. Analyses were conducted with the Food Processor SQL program (Food Processor SQL Edition, version 9.6.2, 2004, ESHA Research, Salem, OR, USA) using the 2001 Canadian Nutrient Data File and the USDA database. The data entry from the food records in the software was realized by a registered dietitian and independently verified by a second one.

Psychosocial assessment

The psychosocial factors (body-esteem, self-esteem, stress, dietary restraint, disinhibition, hunger, quality of life, self-efficacy, perceived benefits and perceived risks) were evaluated using a self-administered validated questionnaire. Body-esteem was assessed using the Mendelson et al. Body-Esteem Scale (Mendelson et al., 2001), a 23-item measure that includes three subscales: appearance (10 items), attribution—that is, how a woman perceives other people's evaluation of her body appearance (5-items), and weight (8-items). Mean scores, ranging from 0 to 4, were calculated for total body-esteem and each subscale, with higher scores reflecting higher body-esteem. Self-esteem was assessed using Rosenberg Self-Esteem Scale (Rosenberg, 1965); mean scores, ranging from 1 to 4, were calculated for this 10-item measure, with lower scores reflecting higher self-esteem. Perceived stress was assessed using Cohen et al. Perceived Stress Scale (Cohen et al., 1983). Scores on this 14-item measure were summed (each response ranged from 0 to 4) for a total score ranging from 0 to 56; higher scores indicate higher stress. Dietary restraint, disinhibition and hunger were assessed using the Stunkard & Messick's 3-Factor Eating Questionnaire (Stunkard and Messick, 1985). Dietary restraint reflects conscious mechanisms for restraining food intake (21-items, scores range from 0 to 21), disinhibition reflects overeating in response to emotional and situational cues (16-items, scores range from 0 to 16), and hunger reflects susceptibility to hunger (11-items, scores range from 0 to 14). Higher scores indicate higher dietary restraint, disinhibition and hunger. Quality of life was measured using the Medical Outcomes Study General Health Survey (20-items) with scores being transformed to a scale of 0–100% (Stewart et al., 1989; McDowell and Newell, 1996); higher scores indicate higher quality of life. Self-efficacy was assessed using a measure developed for this study according to the Social Cognitive Theory (Baranowski et al., 2003): it measures confidence in being able to control one′s weight (6-items). Perceived benefits assess the benefits of controlling one's weight (four-items) and perceived risks of developing heart disease (one-item) and diabetes mellitus (one-item), according to the Health Belief Model (Janz et al., 2003). Mean scores (ranging from 1 to 4) were calculated, with higher scores indicating higher self-efficacy, benefits and perceived risk. The Cronbach coefficient (Ghiselli et al., 1981), a measure of internal consistency reliability, was calculated for each measure with more than one item and varied between 0.62 and 0.91.

Identifying underreporting subjects

Under energy balance, TEE is equivalent to EI. Thus, the ratio of reported EI to TEE should be equal to 1. In this study, we used the ratio of reported EI to EE of <0.80 as a cut-point to identify underreporting subjects as described earlier in DLW studies (Black and Cole, 2000). In an effort to avoid misclassification related to overreporting of food-intake, subjects with a ratio of reported EI to TEE above 1.20 were identified as overreporters (n=2) and removed from statistical analysis.

Statistical analysis

The data are expressed as the mean±s.d. We first verified the normality of the distribution of variables with a Kolmogorov–Smirnov test and found that all variables were normally distributed. An independent t-test was used for the comparison of variables between underreporters and non-underreporters. A binary logistic regression forward stepwise (likelihood ratio) model was used to determine characteristics of underreporters in our cohort. Statistical analysis was performed using SPSS for Windows (version 15) (Chicago, IL, USA). Significance was accepted at P<0.05.

Results

Out of 87 subjects, 50 (57.5%) were identified as underreporting subjects in our cohort. Table 1 shows the physical characteristics of underreporters and non-underreporters in overweight/obese postmenopausal women. Both groups of women were comparable for age, lean body mass, resting metabolic rate and muscle strength. Body mass index, fat mass, subcutaneous adipose tissue, visceral fat and TEE were significantly higher in underreporters. In contrast, peak oxygen uptake was significantly lower in underreporters. When statistically controlling for fat mass, significant differences in TEE levels between the groups persisted.

Table 1 Physical characteristics of underreporters and non-underreporters

Metabolic variables are presented in Table 2. Subjects that underreported had significantly higher values for hsC-reactive protein (CRP). In addition, both groups were comparable for total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, blood pressure as well as fasting glucose and insulin. When statistically controlling for fat mass or visceral fat, significant differences in hsCRP levels between the groups were abolished.

Table 2 Metabolic characteristics of underreporters and non-underreporters

Reported dietary intake is shown in Table 3. By design, EI, the EI/TEE ratio as well as the difference between EI and TEE were significantly lower in underreporters. No differences between groups were noted for percentage of energy from carbohydrate, total fat, saturated, monounsaturated and polyunsaturated fats and also vitamin C, D and E. Intakes of fiber, calcium, iron, vitamin B-1, B-6 as well as servings of fruits and vegetables were significantly lower in underreporters. Absolute values of carbohydrate, protein, total fat, saturated, monounsaturated and polyunsaturated fats were significantly lower in underreporters. In contrast, percentage of energy from protein was significantly higher in underreporters. When statistically controlling for EI, significant differences between groups for all dietary factors were abolished. When statistically controlling for fat mass, significant differences for carbohydrate, protein, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, fiber, calcium, iron, vitamin B-1 and B-6 intakes as well as servings of fruit and vegetables between the groups persisted, whereas the differences in percentage of energy from protein were abolished.

Table 3 Reported dietary intake of underreporters and non-underreporters

The reported psychosocial factors are shown in Table 4. Perceived stress was significantly higher in underreporters and there was a trend for a lower total quality of life in underreporters (P=0.08). No differences in total body esteem, perceived benefits, self-efficacy, self-esteem, perceived risk for diseases, dietary restraint, desinhibition and hunger were observed in both groups. When statistically controlling for fat mass, significant differences in perceived stress between the groups persisted.

Table 4 Reported psychosocial characteristics of underreporters and non-underreporters

We performed a binary logistic regression analysis to examine the independent characteristics of underreporters. Independent variables considered in the final model for underreporters were fat mass, VO2 peak, CRP, perceived stress and total quality of life. Table 5 illustrates the summary of the model. Our results show that the variables of fat mass and perceived stress were independent characteristics of underreporters (P<0.05).

Table 5 Logistic regression analysis regarding independent characteristics of underreporters

Discussion

The purpose of this study was to analyze the anthropometric, metabolic, dietary and psychosocial profiles of underreporters, identified by the DLW technique, in a well-characterized population of overweight and obese postmenopausal women. In this study, we observed significant differences in anthropometric and metabolic risk factors such as higher levels of body mass index, fat mass, subcutaneous adipose tissue, visceral fat and CRP as well as lower levels of VO2 peak in underreporters. Moreover, we showed that underreporters had significantly lower dietary intake of vitamin B-1 and 6, calcium, fiber, iron and servings of fruit and vegetables and also higher percentage of energy from protein. Finally, underreporters had higher levels of perceived stress and a trend for lower levels of quality of life. Interestingly, after controlling for fat mass, perceived stress, TEE, calcium, iron, fiber, vitamin B-1 and B-6 intakes as well as servings of fruit and vegetables remained significant between groups. However, differences in CRP levels and percentage of energy from protein between groups were abolished after controlling for fat mass, suggesting that fat mass may be a potential mediating factor. Furthermore, results show that when statistically controlling for EI, significant differences between groups for all dietary factors were abolished. This suggests that underreporters may not be selective for certain nutrients intakes. Collectively, these results suggest that underreporters could show unfavorable anthropometric, metabolic, dietary and psychosocial profiles compared with non-underreporters in our cohort, which may be associated with an increase risk of cardiovascular disease. These results also suggest that multiple factors could be implicated in the profile of underreporters in overweight and obese postmenopausal women. Therefore, studies characterizing underreporting may want to consider several outcomes measures in different domains in order to have a complete understanding of underreporters. It should be noted that in this study, 57.5% of subjects were identified as underreporters. A similar prevalence in obese women has been reported in other studies (Hirvonen et al., 1997; Tooze et al., 2004; Abbot et al., 2008). For example, using the DLW technique to identify underreporters, Tooze et al. (2004) reported a prevalence of 50% of underreporting in women.

In this study, we attempted to develop a model that includes multiple anthropometric, metabolic and psychosocial measurements that may help us better understand characteristics of underreporting. It should be noted that dietary factors were not included in the model because we found that they were not associated with underreporting when we controlled for EI. Results from the logistic regression analysis showed that fat mass and perceived stress were independent characteristics of underreporting in our cohort. This suggests that higher levels of fat mass and perceived stress may be associated with a higher risk of underreporting. Accordingly, similar results have been shown in other studies (Rosell et al., 2003; Samuel-Hodge et al., 2004; Bazelmans et al., 2007; Lanctot et al., 2008). These results potentially underscores the importance of fat mass and perceived stress as potential modulating factors in the development of underreporting in overweight and obese postmenopausal women because multiple factors in different fields were used in this study. It could be argued that obese women may not be comfortable in reporting their food intake because of their high levels of fat mass or they may lack the awareness regarding the amount and type of food they consume. Interestingly, higher levels of perceived stress add new insight into the understanding of characterizing underreporting. The strength of this finding is reinforced by the fact that it is present even in a homogenous population of overweight/obese postmenopausal women. That is, even within an overweight/obese population of similar body fat content, the differences in perceived stress between the two groups were evident. A possible mechanism explaining the association between perceived stress and underreporting could be related to the possibility that higher stress leads to lack of attention to awareness to food intake.

There are several limitations in this study. First, we used a cross-sectional approach, which does not allow us to conclude to any causal associations between anthropometric, metabolic, psychosocial and dietary factors with underreporting in our cohort. Second, our cohort is composed of non-diabetic sedentary overweight and obese postmenopausal women participating in a weight loss intervention. Therefore, our findings are limited to this population. Third, on the basis of the literature, it is clear that underreporters report certain nutrients differently compared with more accurate reporters. However, it should be noted that there is no way of knowing if underreporters per se truly eat more or less certain nutrients differently from accurate reporters. Despite these limitations, we believe we used a relevant population to study underreporting. Furthermore, our results are strengthened by using gold standard techniques for the measurement of insulin sensitivity, body composition and energy expenditure as well as by studying a well-characterized cohort in a relatively large sample size.

In conclusion, results from this study show significant differences in metabolic, psychosocial and dietary profiles between underreporters and non-underreporters in our cohort of overweight and obese postmenopausal women. In addition, higher levels of fat mass and perceived stress were characteristics of underreporting. Thus, a better understanding of factors associated with underreporting could lead to the development of more precise methods to correct for errors in reporting, which may provide a basis for adjustment for select confounding factors.

Conflict of interest

The authors declare no conflict of interest.

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Acknowledgements

This study was supported by grants from the Canadian Institutes of Health Research (University of Montreal and University of Ottawa New Emerging Team project). Dr Rémi Rabasa-Lhoret, Dr Antony Karelis, Marie-Eve Lavoie and Virginie Messier are supported by the Fonds de la Recherche en Santé du Québec. Dr Rémi Rabasa-Lhoret is the recipient of the J-A DeSeve Research Chair for Clinical Research. Éric Doucet is a recipient of a CIHR/Merck-Frosst New Investigator Award, a Canadian Foundation for Innovation New Opportunities Award and an Early Research Award (Ontario).

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Karelis, A., Lavoie, ME., Fontaine, J. et al. Anthropometric, metabolic, dietary and psychosocial profiles of underreporters of energy intake: a doubly labeled water study among overweight/obese postmenopausal women—a Montreal Ottawa New Emerging Team study. Eur J Clin Nutr 64, 68–74 (2010). https://doi.org/10.1038/ejcn.2009.119

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Keywords

  • underreporters
  • body composition
  • obesity
  • perceived stress
  • energy expenditure and doubly labeled water

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