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Department of Psychology, University of Texas at El Paso, El Paso, TX
2To whom correspondence should be addressed. E-mail: jdecastro{at}utep.edu.
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ABSTRACT |
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 TOP ABSTRACT METHODSRESULTSDISCUSSIONLITERATURE CITED |
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KEY WORDS: • meal pattern • eating • meal frequency • meal size
Ingested substances contain not only food energy and macro- and micronutrients but also water and fiber. Therefore, meals can vary greatly not only in energy content, but also in weight. Current theorization regarding food intake regulation is primarily referenced to the energy content of intake. However, it is possible that the intake of food is regulated not on the basis of its energy content but on that of its weight or volume. If the weight of the food is what is being controlled, then ingestion of foods that contain a large amount of energy relative to their weight (high–energy density foods) would result in greater food energy intake, whereas ingestion of foods that contain a large amount of water or fiber (low–energy density foods) would result in lower overall food energy intake. Hence, if the weight of the food and not its energy content is regulated, then the energy density of the diet would be a major determinant of the individual’s energy intake and in turn body weight and adiposity. Indeed, studies consistently show that dietary energy density is associated with dietary intake in humans (1–9) and nonhuman animals (10,11). Because energy density is clearly related to energy intake, which is in turn related to body weight and adiposity, it is possible that overweight and obesity are related to the energy density of the diet. Indeed, there are some indications that long-term manipulation of the energy density of the diet can lead to modest changes in body weight (9,12,13).
The research to date, however, has been primarily laboratory based and/or has involved manipulation of the ingested diets. It is not known whether energy density plays a role in the spontaneous dietary intake of free-living humans in their natural environments. Indeed, obese and nonobese adolescents do not differ in their ingestion of high–energy density foods (14), and members of identical twin pairs who differ in dietary energy density do not differ in body size (15). The present study attempted to ascertain the role of energy density in unmanipulated natural contexts by analyzing data that was obtained from normal adults in prior studies with 7-d self-report diet diaries (16–28). Participants who differed in dietary energy density were compared. The effect of the energy density of the diets consumed by individual subjects on different days was investigated. The effect of the energy density of individual meals was also studied.
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METHODS |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONLITERATURE CITED |
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Procedure. All participants completed a demographic questionnaire, the Three Factor Eating Inventory (29), and a 7-d diet diary of their nutrient intake. For a detailed review of the diet-diary method and the reliability and validity of the diet-diary procedure, see de Castro (30,31). The participants were given a pocket-sized (8 x 18 cm) diary and were instructed to record in as detailed a manner as possible every item that they ate and drank, the time they consumed it, the amount they consumed, how the food was prepared, and the number of other people eating with them. Self-ratings of degree of hunger, thirst, and the attractiveness of the food (7-point scale) were recorded at the beginning and again at the end of each meal. The participants initially recorded this information for 1 d and were then contacted by the experimenter, who reviewed the information, corrected any problems, and answered any questions. The participants were then asked to record their intake for 7 consecutive days. After this recording period the participants were contacted, their diaries were reviewed, and any ambiguities or missing data were clarified. In each case, two individuals who ate with the participant during the recording period were contacted and asked to verify the reported intake. Some witnesses had difficulty remembering exactly what the participant ate, but no witness contradicted the diary record regarding either the nature or the amount reported.
Data analysis.
The foods reported in the diaries were assigned codes from a computer file containing the nutrient compositions of common food items. A computer file of over 3500 food items was created from the U.S. Department of Agriculture Handbooks of the Nutritive Value of American Foods, no. 8 and 456; from package labels; from personal communications with food industry sources; and from current published literature. Meals were identified and the compositions of the individual items composing each meal were summed. To be classified as an individual meal, a reported intake had to provide 
209 kJ or, more stringently, 418 or 837 kJ. It also had to be separated in time from the preceding and following intakes by at least 15 min. More stringent definitions of 45 and 90 min were also employed. Five different definitions of a meal were used, combining the following minimum criteria: 15 min and 209 kJ, 45 min and 209 kJ, 45 min and 418 kJ, 45 min and 837 kJ, and 90 min and 209 kJ. Although there were apparent quantitative differences between the results obtained for the five meal definitions, the patterns of results were equivalent. Thus, only the minimum 209 kJ and 45 min definition is presented as representative.
The meals were characterized by their total energy content; carbohydrate, fat, protein, and alcohol content; duration and rate of intake; and the amount of time between meals, the before- and after-meal interval, the before- and after-meal palatability rating, and the subjective rating of hunger and thirst. In addition, for each meal the satiety ratio was calculated as the ratio of the after-meal interval divided by the meal size in kJ as a measure of the number of minutes of satiety till the next meal per kJ of energy in the meal, and the deprivation ratio was calculated as the ratio of the meal size in kJ divided by the before-meal interval as a measure of the amount of energy in the meal per minute of deprivation since the previous meal. The amounts ingested each day and over the entire 7-d period were summed. The mean of each meal characteristic and the mean daily intake were then calculated for each participant. These individual means were then used to calculate overall group means.
For the intersubject analysis, the means for each individual for overall and per-meal intake calculated over the entire 7-d recording period were used. Pearson product moment correlations between energy density and each of a number of variables were calculated across participants. Regardless of the veracity of the reporting, diary recording can produce reports of intake levels that are not representative of the individual’s typical daily intake. Reactivity to the measurement procedure can result in a decrease in intake during the recording period. To assess the degree to which the reported intake was representative of the actual typical daily intake, reported intake was compared to the estimated basal metabolic rate (BMRest) for each participant. Basal metabolic rate was estimated from body weight adjusted for age and sex, according to the procedure outlined by Schofield et al. (32). The ratio of the reported daily food energy intake (EI) to the BMRest was calculated for each participant. A reasonable cutoff for identifying unrepresentative intake is EI:BMRest < 1.1 (33–35). To ensure that the reported results were not biased by the inclusion of reported intakes that appear to be unrepresentative, separate analyses, as above, were performed for all participants and for participants with EI:BMRest > 1.1.
Intrasubject analyses of daily intake and meal pattern were also conducted. For the daily intake analysis, the mean overall and per-meal intakes for each day of the 7-d period were calculated for each participant. Energy density was then correlated with the intake measures across days for each participant. The group mean correlations were then calculated by averaging the individual correlations for each sex. Because correlation coefficients are not normally distributed, they were transformed to Z-scores before calculating group means or performing statistical analysis (36). The mean correlations and coefficients were then compared to 0 with a t test. Autocorrelations between the energy density and the amount eaten over a day and the energy density and amount eaten on subsequent days were also calculated individually for each participant, then a group mean autocorrelation was calculated. In addition, multiple linear regression analyses (37) were performed to predict the amount eaten during an entire day on the basis of the amount eaten and the dietary energy density of the preceding days. Multiple regressions were performed individually for each participant. Group means were then calculated and compared to 0 with a t test.
For the intrasubject meal pattern analysis, Pearson product moment correlations between meal energy density and each of a number of meal pattern variables were calculated across all individual meals reported over the 7-d period for each participant. The group mean correlations were then calculated by averaging the individual correlations. The correlations were transformed to Z-scores before calculating group means (36). The mean correlations were then compared to 0 with a t test. In addition, multiple linear regression analyses (37) were performed to predict the meal size on the basis of energy density plus 4 other variables that affect meal size (39): palatability (22,39), hunger (26), the time of day (16), and the number of people present at the meal (23–25,40,41). Multiple regressions were performed individually for each participant. Group means were then calculated and compared to 0 with a t test.
All presented results are significant (P < 0.05) unless otherwise indicated. Analyses were initially stratified by sex. However, the results were valid for both sexes, and there were no interactions with sex. Hence, only analyses for all participants are reported.
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RESULTS |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONLITERATURE CITED |
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In terms of the mean meal characteristics calculated over the entire period of data collection, dietary energy density was positively correlated with mean meal size primarily as a result of a positive relationship with the mean rate of intake (Table 1). The slopes of the regressions indicate that meal size increased by 245 ± 195 kJ for every kJ/g increase in the energy density of the diet. There was a slight negative relationship or a nonsignificant relationship between energy density and meal frequency. Thus, the greater overall intake associated with higher dietary energy density was associated with increased mean meal size and not increased meal frequency.
Energy density and daily intake—intrasubject analysis. The correlations calculated over days for each subject individually parallel those obtained in the intersubject analysis (Table 2). The daily energy density of the diet, whether calculated with or without drinks, correlated with the overall intake on that day, and the strongest macronutrient correlations were between energy density and fat intake. This was underscored by the correlations between energy density and the proportions of the macronutrients ingested daily. Daily dietary fat percentage was positively correlated with daily dietary energy density, whereas the proportions of carbohydrate and protein were negatively correlated with energy density. As was the case with overall intake, daily dietary energy density was inversely related to the daily water content of the diet and especially to the amount of water ingested daily in the form of drinks. The importance of water in drinks was underscored by the fact that when drinks were removed from the energy density calculation, the correlations with water in the diet were markedly reduced. Again, like the overall analysis, daily dietary energy density was associated with the mean daily meal size and the mean daily rate of intake.
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DISCUSSION |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONLITERATURE CITED |
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The results were consistent across the various analysis methodologies. High dietary energy density was associated with greater total intake, especially of fat, when dietary intake was correlated with energy density and when correlations were calculated for each participant individually for daily intake and dietary density. These same results occurred regardless of sex, low reporting, or the inclusion of intake from drinks in the energy density calculations. The increased intake associated with a high–energy density diet occurs primarily through an association of energy density with the rate of intake and in turn the size of the meals ingested. Once again, this result was present regardless of the analysis methodology, in the both the intersubject and intrasubject daily intake analyses and also in the intrasubject per-meal analysis. Hence, high dietary energy density appeared to be related to greater overall intake, particularly of fat, along with larger meal size and greater rate of intake by free-living humans in their natural environments.
The intrasubject analyses of per-meal patterns suggested that high dietary energy density was associated with larger meal size independent of a variety of other factors that affect meal size. Although meal energy density can have modest correlations with factors that affect meal size, including the time of day (16), the number of other people present (23–25,40,41), the palatability of the meal (22,39), and the level of hunger (26), covariation with these factors did not explain the energy density–meal size relation. Multiple-regression analysis showed that energy density was related to meal size even when the effects of these other factors were accounted for. Hence, meal energy density was independently related to meal intake.
Dietary energy density was positively associated with the total daily energy intake regardless of whether intake from drinks was included in the energy density calculation. However, energy density was related to the total per-meal energy intake only when intake from drinks was included in the calculation. In fact, without the intake from drinks, the relation of energy density to meal energy intake was slightly negative. The probable explanation is that the largest meals tend to have the smallest proportion of total weight in the form of drinks, with intake in the form of solids composing a relatively large proportion. Conversely, small meals tend to have a large proportion of total weight in the form of drinks. Therefore, removing intake from drinks from the calculation had a much greater effect on the smaller meals than the larger meals. This resulted in a much greater increase in the calculated energy density of small meals when drinks were removed than for large meals. This in turn created a small negative relation between energy density calculated without intake from drinks and the energy content of the meal. That this was indeed spurious is evidenced by the fact that when all water (both in drinks and bound in solids) was removed from the calculation of energy density, the correlations between meal energy density and meal energy content remained strongly positive. In addition, averaging the meals eliminated this effect. The mean meal size over the day or over the week was associated with mean meal energy density regardless of whether drinks were included in the energy density calculation. Also, when intake was integrated over all meals for the entire day or the entire week, the relation between energy density and intake was significantly positive even when intake from drinks was removed from the energy density calculation.
It was surprising, given the rather salient apparent effect of dietary energy density on meal and daily intake, that there was no significant relation between dietary energy density and body size, height, weight, or BMI. In a previous study, identical twins whose dietary intake differed in energy density did not differ in body weight or BMI (15). In addition, even though dietary density is related to overall intake, overall intake is unrelated to body size in weight-stable humans (18). These results suggest that in the natural environment, dietary energy density affects short-term per-meal and daily intake, but not body size.
The daily intake autocorrelation analysis suggests an explanation. When daily intake and dietary energy density were used in multiple-regression analysis to predict intake on subsequent days, there was a significant relation between daily intake and intake 1, 2, and 3 d later, as previously reported (21), but there was no significant relation between energy density and subsequent intake. This suggests that energy density affects the amount ingested in 1 d, but this influence is compensated for by adjustments to the amounts of nutrients ingested 1, 2, and 3 d later. Hence, daily dietary energy density may have no net effect on intake over time unless that energy density is maintained over a prolonged period. This occurs when individuals consume diets with specific levels of dietary energy density (9,12,13). However, when the energy density of only 1 daily meal is regulated, there is no net impact (3,52,53). Hence, the results suggest that continuous manipulation of dietary energy density may be useful for weight control. However, under conditions of natural variation in intake, there may be compensatory responses to the effects of energy density, so that there is no net effect on body weight. It is important to note, however, that the magnitudes of the reported autocorrelations are small and thus the degree of compensation may not be sufficient to completely account for the lack of relation between dietary density and body size.
We recently proposed a general model of intake regulation (54). The model incorporates separate sets of environmental, physiological, and homeostatic factors, with each factor having a preferred level that is influenced by heredity. The model also specifies that each factor has an individual weighting factor that specifies the magnitude of its effect on intake. The model clearly predicts that a stable shift in an environmental factor, such as dietary energy density, should result in a change in body weight. However, the model also predicts that compensation will occur for any transitory change in the environment. This is exactly what appears to occur with dietary energy density. If there is a persistent change in energy density, such as during a prescribed dietary regimen, then a sustained change in body weight should occur, as has been observed (9,12,13). However, if the energy density change is occasional, then compensation should occur, as has also been observed (3,52,53).
Reports suggest that the volume or weight of ingested nutrients is the characteristic of food that most influences overall intake in the short term (1,2,5,6). The clear and salient effects of density on short-term intake reported in the present study support this. However, over the long term, the energy content of food appears to be more important. This is supported by the fact that when both energy density and energy content were used to predict intake on subsequent days through multiple-regression autocorrelation analysis, only energy content was significant. Hence, the results of the present study and prior research on the influence of dietary energy density on intake and body weight fit well with the predictions of the general model of intake regulation (54) and indicate that dietary energy density can affect intake in the short term. However, the fact that there is no relation between energy density and body weight or BMI suggests that the effects of energy density may be transitory.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Manuscript received 17 June 2003. Initial review completed 17 July 2003. Revision accepted 29 October 2003.
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LITERATURE CITED |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONLITERATURE CITED |
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 N. C. Howarth, S. P. Murphy, L. R. Wilkens, J. H. Hankin, and L. N. Kolonel Dietary Energy Density Is Associated with Overweight Status among 5 Ethnic Groups in the Multiethnic Cohort Study J. Nutr., August 1, 2006; 136(8): 2243 - 2248. [Abstract] [Full Text] [PDF]
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J. H Ledikwe, H. M Blanck, L. Kettel Khan, M. K Serdula, J. D Seymour, B. C Tohill, and B. J Rolls Dietary energy density is associated with energy intake and weight status in US adults Am. J. Clinical Nutrition, June 1, 2006; 83(6): 1362 - 1368. [Abstract] [Full Text] [PDF]
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R. N. Close and D. A. Schoeller The Financial Reality of Overeating J. Am. Coll. Nutr., June 1, 2006; 25(3): 203 - 209. [Abstract] [Full Text] [PDF]
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J. M. de Castro Varying Levels of Food Energy Self-Reporting Are Associated with Between-Group, but Not Within-Subject, Differences in Food Intake J. Nutr., May 1, 2006; 136(5): 1382 - 1388. [Abstract] [Full Text] [PDF]
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J. H. Ledikwe, H. M. Blanck, L. K. Khan, M. K. Serdula, J. D. Seymour, B. C. Tohill, and B. J. Rolls Dietary Energy Density Determined by Eight Calculation Methods in a Nationally Representative United States Population J. Nutr., February 1, 2005; 135(2): 273 - 278. [Abstract] [Full Text] [PDF]
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