| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
Original Research Communications |
 |
ABSTRACT |
|---|
 TOP ABSTRACT INTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIX AREFERENCES |
|---|
Objective: The purpose of this study was to determine whether dietary variety within food groups influences energy intake and body fatness.
Design: Seventy-one healthy men and women (aged 20–80 y), who provided accurate reports of dietary intake and completed a body-composition assessment, were studied.
Results: Dietary variety was positively associated with energy intake within each of 10 food groups (r = 0.27–0.56, P < 0.05). In multiple regression analysis with age and sex controlled for, dietary variety of sweets, snacks, condiments, entrées, and carbohydrates (as a group) was positively associated with body fatness (partial r = 0.38, P = 0.001) whereas variety from vegetables was negatively associated (partial r = -0.31, P = 0.01) (R2 = 0.46, P < 0.0001). In separate models, both a variety ratio (variety of vegetables/variety of sweets, snacks, condiments, entrées, and carbohydrates) and percentage dietary fat were significant predictors of body fatness (controlled for age and sex, partial r = -0.39 and 0.31, respectively, P < 0.01). However, dietary fat was no longer significantly associated with body fatness when the variety ratio and dietary fat were included in the same model.
Conclusions: Our data, coupled with those of previous short-term studies, suggest that a high variety of sweets, snacks, condiments, entrées, and carbohydrates coupled with a low variety of vegetables promotes long-term increases in energy intake and body fatness. These findings may help explain the rising prevalence of obesity.
Key Words: Dietary variety • dietary fat • dietary composition • body composition • obesity • energy intake • adults • vegetables
|
INTRODUCTION |
|---|
|
TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIX AREFERENCES |
|---|
See corresponding editorial on 350.
Of the many dietary factors that have been implicated, the percentage of energy from dietary fat has received particular attention (4, 5). Recently, however, an expert panel concluded that dietary fat may not be the sole dietary determinant of body fatness it has widely been assumed to be (6). Additional research is therefore needed to examine other dietary contributors to weight gain and obesity.
One potential factor that has received relatively little attention in humans is dietary variety. In laboratory animals, access to a variety of foods increases energy intake within and between meals compared with access to a single food (7–14) and over the long term induces weight gain and fat gain (9, 11). Results of single-meal studies in humans are consistent with animal data, showing that subjects consume more total food when offered a variety of different foods than when only a single food is presented (15–20). However, it is not known whether the effects of dietary variety on food intake in humans persist in the long term and lead to changes in body weight and fat content. If so, and in view of the fact that the variety of commercial foods has risen dramatically in recent years (21), excessive dietary variety might help to explain the rising national prevalence of obesity.
The purpose of this study was to test the hypothesis that dietary variety is associated with energy intake and body fatness in free-living adults consuming self-selected diets. In addition, we hypothesized that the relation between dietary variety and body fatness depends critically on the types of foods being consumed. Specifically, high variety is associated with fatness when the variety comes from foods with a high energy content, but with leanness when the variety comes from foods with a low energy content. In addition, we also tested dietary variety as a predictor of body fatness relative to other putative dietary predictors of body fatness, including the proportion of dietary energy derived from fat, energy density, fiber, and energy intake per kilogram body weight.
|
SUBJECTS AND METHODS |
|---|
|
TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIX AREFERENCES |
|---|
Dietary intake
Usual dietary intake over the preceding 6 mo was assessed by using the Fred Hutchinson Cancer Research Center Food Frequency Questionnaire (FFQ), version 06.10.88 (modified Block; 23); energy and macronutrient intakes were calculated by using Minnesota NDS software (food database version 11A, nutrient database version 2.8; Nutrition Coordination Center, University of Minnesota, Minneapolis). Energy density was calculated as the total daily energy consumption divided by the total daily weight of food consumed, including all beverages.
Dietary variety within food groups was assessed in the following manner. First, 10 food groups were formed by using the FFQ food groupings as an initial basis on which to combine food types listed, and slight modifications were made according to each food type's place in the diet and physical state (beverages and solid foods). For example, breakfast food condiments were separated from the remaining breakfast foods. The 10 food groups and the number of food types within each group are shown in Table 1
along with representative food types in each group; a complete list is given in Appendix A. These 10 initial food groups were later collapsed into 8 groups on the basis of the results of multiple regression analyses (see Data analysis). Because of the nature of standard FFQs, some individual foods were already grouped together and thus could not be distinguished from one another. For example, "apples, applesauce, and pears" is the first item listed on the FFQ and, for the purpose of this analysis, all 3 items were considered 1 food type.
|
Body composition
Body weight and height were measured to the nearest 0.01 kg and 0.25 cm, respectively, and body composition was measured by hydrostatic weighing after subjects fasted overnight (24). Body density was corrected for residual lung volume measured on land by the nitrogen washout method (model 505, Med Science Nitralyzer, St Louis; Sensormedics Vmax, Yorba Linda, CA) (25). Fat mass and fat-free mass were calculated by using the equation of Siri (26), and the average of 4 tests with results within 1% body fat was used for analysis.
Data analysis
Statistical analyses were performed by using SYSTAT software (version 7.0.1; SPSS, Inc, Chicago). Descriptive data are presented as means ± SDs unless otherwise indicated. To determine whether dietary variety was associated with the amount of food consumed within a food group, Pearson correlation coefficients between dietary variety and the energy intake per day from each food group were calculated. Pearson correlations were also calculated to determine associations among the different dietary variables. Stepwise multiple linear regression analysis was used to determine the association between dietary variety and body fatness (expressed as % of wt). All 10 initial food groups, as well as several combinations of food groups, were tested. On the basis of trends noted in regression analysis, certain food groups were combined to create food group combinations. For example, when variety in more than one food group was positively associated with body fatness, the food groups were combined and the variety score was recomputed from the new, larger food group and regression analysis was repeated. Variety was recomputed as the number of food types consumed from the new food group divided by all possible food types in the new, larger group (eg, there were 44 possible food types for the combined sweets, snacks, condiments, entrées, and carbohydrates group; see Table 1
and Appendix A for the number of possible food types in each of the original 10 food groups) and converted to a percentage. Data are presented for the resulting individual and combinations of food groups that yielded the highest R2 values in regression analyses. To compare the relative predictive value of dietary variety within food groups on body fatness with other putative dietary predictors of body fatness, partial correlations of each dietary variable with body fatness were computed (after age and sex were controlled for). For all statistical tests, a P value <0.05 was accepted as significant.
|
RESULTS |
|---|
|
TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIX AREFERENCES |
|---|
, the subjects varied widely in age and fatness. Their dietary intakes also varied widely, but were not unusual. Information on the dietary variety consumed within each food group in the preceding 6 mo (expressed as a percentage of total possible group variety) is shown in Table 3. The mean dietary variety ranged between 32% and 80% for the 10 different food groups. In all food groups, there was substantial variability among subjects, with some individuals consuming little variety and others consuming a much greater variety. For example, women consumed between 7% and 100% of the possible vegetable types. Pearson correlations of age with the different dietary variables indicated that older subjects consumed a greater variety of vegetables (r = 0.51, P < 0.001) and, hence, had a greater intake of fiber per megajoule energy consumed (r = 0.32, P < 0.05) and a lower energy intake per kilogram body weight (r = -0.49, P < 0.001) than did younger subjects.
|
|
. In all 8 food groups, there was a significant positive association between dietary variety and energy intake derived from each specific food group (r = 0.27–0.52, P < 0.05). Results were similar for the remaining 2 groups, breakfast food condiments (r = 0.29, P = 0.01) and beverage condiments (r = 0.56, P < 0.0001) (data not shown). Thus, within every food group tested, consumption of a greater variety of foods was associated with a greater energy intake from those foods.
|
. After age and sex were controlled for, in a single model, variety from the vegetables group was negatively associated with body fatness, and variety from the combined group of sweets, snacks, condiments, entrées, and carbohydrates was positively associated with body fatness. Interaction terms of dietary variety with age were not significant, indicating that age did not modify the relation between dietary variety and body fatness in this study population. The overall best-fit regression model, controlled for age and sex and containing dietary variety from these 2 food groups, yielded an R2 of 0.46 (P < 0.0001). Models in which the entrées group and different combinations of sweets, snacks, carbohydrate, and condiments groups were considered separately, and were also significant, but yielded lower R2 values. Dietary variety scores in the remaining food groups were not significant predictors of body fatness.
|
. As shown, variety from the vegetables group was negatively associated with energy intake per kilogram body weight, and positively associated with dietary fiber intake (per MJ consumed). Variety from the sweets, snacks, condiments, entrées, and carbohydrates group was positively associated with dietary fat intake and energy density and negatively associated with fiber intake. The variety ratio was negatively associated with dietary fat intake and energy density and positively associated with fiber intake.
|
), the ratio was tested for its association with body fatness after dietary fat was controlled for. As can be seen in Figure 3, the variety ratio remained significantly associated with body fatness, even after dietary fat was controlled for (R2 = 0.44, P < 0.0001). Furthermore, dietary fat was no longer significantly related to body fatness once both dietary variety and dietary fat were included in the same regression model.
|
|
DISCUSSION |
|---|
|
TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIX AREFERENCES |
|---|
In multiple regression models accounting for age and sex, we observed for the first time a significant association between body fatness and dietary variety within different food groups. Most noteworthy, the relation between dietary variety and body fatness was shown to depend on the food group that provided it. For sweets, snacks, condiments, entrées, and carbohydrates there was a positive association between body fatness and variety. In contrast, there was a negative association between body fatness and the variety of vegetables (excluding potatoes) consumed. Moreover, the variety ratio was the strongest predictor of body fatness, and the proportion of dietary energy provided by fat was not a significant predictor of body fatness in regression models that included the variety ratio. Thus, dietary variety was found to be a double-edged sword for energy regulation, having both positive and negative associations with body fatness depending on the food group that provided the variety.
Note that our study probably underestimated the effects of dietary variety on body fatness. This is because we used an FFQ to obtain dietary data and this kind of instrument limits the information that can be obtained on variety within different food groups. Thus, it is possible that even stronger relations between dietary variety and body fatness may be found with use of food measurement methods, such as 7-d weighed intake, which allow specific information on each consumed item to be obtained.
Our additional finding that variety was positively associated with dietary intake within all food groups studied extends and is entirely consistent with results of previous single-meal studies in adults, a 4-d study in infants, and as short- and long-term studies in animal models (7–20, 27). Although the possibility cannot be ruled out that body fatness might influence dietary variety, the combination of our current cross-sectional data with previous single-meal studies in humans (15–20) and longer-term studies in rats (9, 11) strongly suggests that dietary variety exerts a long-term effect on body fatness through short-term influences on food and energy intake.
The fact that high variety was associated with increased energy intakes within the food groups tested in this study undoubtedly helps to explain the opposing associations of different food groups with body fatness. A notable difference between the foods that were positively associated with increased body fat (sweets, snacks, condiments, entrées, and carbohydrates) and the food group negatively associated with body fat (vegetables) is their energy density. Because adults tend to consume a constant daily weight of food (28, 29), increased amounts of low-energy vegetables, prompted by high variety, may replace rather than supplement intakes of higher-energy items and lead to an overall decrease in energy intake and hence body fatness. Conversely, increased amounts of high-energy sweets, snacks, and condiments, prompted by high variety, may increase energy intake and body fatness. Variety within groups defined as dairy products, energy-containing beverages, and fruit was not associated with body fatness in this study, perhaps because these staple foods tend to be eaten more out of habit than for interest, but also possibly because of the intermediate energy density of several of the food items within these groups.
A generalized and instinctive basis for the effects of dietary variety in humans is suggested by the fact that greater dietary variety is associated with greater food intake in all food groups and all species investigated to date. Although the mechanism by which a drive for dietary variety gets translated into increased food consumption is not known, the phenomenon of sensory-specific satiety (the term used to describe the fact that perception of food preference decreases as increasing amounts of that food are eaten) is a probable candidate (18, 19). In human prehistory, individuals who experienced sensory-specific satiety and ate from a greater variety of foods may well have had a better micronutrient status than individuals who ate a lesser variety of foods because no single basic food supplies every essential nutrient. Obtaining a balanced diet is harder when dietary choices are limited than when there is great dietary variety. Moreover, because the foods available to primitive hunters and foragers were both limited and intermittently available, those individuals who ate more total food when an increased variety of foodstuffs could be found may have fared better than those who did not. Thus, under the conditions existing when early humans evolved, individuals with a strong drive to eat a variety of foods and to increase total food intake in the presence of dietary variety were likely to have benefited from the metabolic, physical, and cognitive advantages that a balanced diet provides (30–33). What can be termed the "variety principle" may thus have been strongly beneficial in human prehistory, becoming favored in genetic selection and predominating in the lineage from which modern humans descend. Today, however, a drive to overeat when variety is plentiful is disadvantageous for weight regulation because dietary variety is greater than ever before and comes primarily from energy-dense commercial foods rather than from the energy-poor but micronutrient-rich vegetables and fruit for which the variety principle originally evolved.
There are several important implications for the observed influences of dietary variety on body fatness. In particular, dietary variety may be an important tool in the prevention and treatment of disorders of weight regulation. In situations in which an increase in energy intake is mandated, such as in elderly adults experiencing unexplained weight loss, increasing the variety of high-energy foods offered may accomplish the desired result without the necessity of intensive medical interventions.
Diets providing a high variety of vegetables and a low variety of sweets, snacks, condiments, entrées, and carbohydrates may promote a long-term reduction in voluntary energy intake and body fatness without resort to a conscious restriction of energy intake, thus preventing and perhaps helping to treat obesity and overweight. Our results may also help explain the rising national prevalence of obesity. The variety of vegetables now consumed is low (one-half of the total vegetable consumption in the United States is as fresh and frozen potatoes, head lettuce, processed tomatoes, and onions) and our data suggest that this may be a factor in limiting the total consumption to only 3.2 servings/d, on average (34). Moreover, an enormous number of high-energy commercial sweets, snacks, condiments, and carbohydrates have been introduced into the US food market in the past 30 y (21), which our model predicts will increase energy intake. As shown in Figure 4, these trends closely parallel the increasing national prevalence of obesity (2), and are strikingly out of proportion to the modest number of vegetable and fruit products introduced during the same period.
|
|
APPENDIX A |
|---|
|
TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIX AREFERENCES |
|---|
Lunch and dinner entrées
1) Hamburgers, cheeseburgers, and other ground beef items; 2) beef, including on sandwiches; 3) beef stew or pot pie; 4) liver; 5) pork; 6) fried chicken; 7) chicken or turkey; 8) fried fish; 9) tuna; 10) shellfish; 11) other fish; 12) spaghetti, lasagna, or other pasta; 13) pizza; 14) mixed dishes with cheese; 15) hot dogs; 16) luncheon meats; 17) vegetable and tomato soups; 18) other soups; and 19) chili with beans.
Sweets, snacks, and carbohydrates
1) Ice cream; 2) sherbet or gelatin; 3) frozen yogurt and ice milk; 4) doughnuts, cookies, cake, and pastry; 5) pies; 6) chocolate candy; 7) other candy; 8) jelly, honey, and brown sugar; 9) potato chips and corn chips; 10) popcorn; 11) French fries and fried potatoes; 12) sweet potatoes and yams; 13) other potatoes; 14) rice; 15) biscuits, muffins, and burger rolls; 16) white breads, bagels, and crackers; 17) dark breads, bagels, and crackers; and 18) corn bread, corn muffins, and corn tortillas.
Condiments
1) Gravies made with meat drippings or white sauce, 2) peanuts and peanut butter, 3) margarine on bread or rolls, 4) butter on bread or rolls, 5) regular salad dressing and mayonnaise, 6) diet salad dressing and diet mayonnaise, and 7) butter, margarine, or other fat added to vegetables or potatoes.
Fruit
1) Apples, applesauce, and pears; 2) bananas; 3) peaches and apricots (canned, frozen, or dried); 4) peaches, apricots, and nectarines (fresh); 5) cantaloupe (in season); 6) watermelon (in season); 7) strawberries (fresh, in season); 8) oranges; 9) grapefruit; and 10) other fruit including berries and fruit cocktail.
Vegetables
1) String beans and green beans; 2) peas; 3) other beans; 4) corn; 5) tomatoes and tomato juice; 6) broccoli; 7) cauliflower or Brussels sprouts; 8) spinach (raw); 9) spinach (cooked); 10) mustard greens, turnip greens, and collards; 11) cole slaw, cabbage, and sauerkraut; 12) carrots or mixed vegetables with carrots; 13) green salad; and 14) other vegetables, including cooked onions and summer squash.
Energy-containing beverages
1) Orange juice or grapefruit juice; 2) other fruit juices and fortified fruit drinks; 3) whole milk and beverages with whole milk; 4) 2% milk and beverages with 2% milk; 5) skim milk, 1% milk, or buttermilk; 6) regular soft drinks; 7) beer; 8) wine; and 9) liquor.
Dairy products
1) Regular cottage cheese, 2) low-fat cottage cheese and other low-fat cheeses, 3) other cheeses and cheese spreads, 4) flavored yogurt, and 5) plain yogurt.
Breakfast food condiments
1) Milk added to cereal, and 2) sugar added to cereal.
Beverage condiments
1) Nondairy creamer, 2) milk, 3) cream and half-and-half, and 4) sugar.
|
ACKNOWLEDGMENTS |
|---|
|
FOOTNOTES |
|---|
2 Supported in part by grants AG00209, AG12829, DK09747, DK46124, and DK46200 from the National Institutes of Health.
3 Address reprint requests to SB Roberts, Energy Metabolism Laboratory, The Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, 711 Washington Street, Boston, MA 02111–1524. E-mail: Roberts_em{at}hnrc.tufts.edu.
|
REFERENCES |
|---|
|
TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONAPPENDIX AREFERENCES |
|---|
This article has been cited by other articles:
|
|
 |
|
  V. L. Forman-Hoffman, K. K. Richardson, J. W. Yankey, S. L. Hillis, R. B. Wallace, and F. D. Wolinsky Retirement and Weight Changes Among Men and Women in the Health and Retirement Study J. Gerontol. B. Psychol. Sci. Soc. Sci., May 1, 2008; 63(3): S146 - S153. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. E Schebendach, L. E. Mayer, M. J Devlin, E. Attia, I. R Contento, R. L Wolf, and B T. Walsh Dietary energy density and diet variety as predictors of outcome in anorexia nervosa Am. J. Clinical Nutrition, April 1, 2008; 87(4): 810 - 816. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 K. E. Peterson, J. R. Hebert, T. G. Hurley, K. Resnicow, F. E. Thompson, G. W. Greene, A. R. Shaikh, A. L. Yaroch, G. C. Williams, J. Salkeld, et al. Accuracy and Precision of Two Short Screeners to Assess Change in Fruit and Vegetable Consumption among Diverse Populations Participating in Health Promotion Intervention Trials J. Nutr., January 1, 2008; 138(1): 218S - 225S. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. R. Hebert, T. G. Hurley, K. E. Peterson, K. Resnicow, F. E. Thompson, A. L. Yaroch, M. Ehlers, D. Midthune, G. C. Williams, G. W. Greene, et al. Social Desirability Trait Influences on Self-Reported Dietary Measures among Diverse Participants in a Multicenter Multiple Risk Factor Trial J. Nutr., January 1, 2008; 138(1): 226S - 234S. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. E. O'Neil and T. A. Nicklas State of the Art Reviews: Relationship Between Diet/ Physical Activity and Health American Journal of Lifestyle Medicine, December 1, 2007; 1(6): 457 - 481. [Abstract] [PDF]
|
|
|
|
|
|
S. K. Das, C. H Gilhooly, J. K Golden, A. G Pittas, P. J Fuss, R. A Cheatham, S. Tyler, M. Tsay, M. A McCrory, A. H Lichtenstein, et al. Long-term effects of 2 energy-restricted diets differing in glycemic load on dietary adherence, body composition, and metabolism in CALERIE: a 1-y randomized controlled trial Am. J. Clinical Nutrition, April 1, 2007; 85(4): 1023 - 1030. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. D. Ard, S. Fitzpatrick, R. A. Desmond, B. S. Sutton, M. Pisu, D. B. Allison, F. Franklin, and M. L. Baskin The Impact of Cost on the Availability of Fruits and Vegetables in the Homes of Schoolchildren in Birmingham, Alabama Am J Public Health, February 1, 2007; 97(2): 367 - 372. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 D. W. Pittman, C. E. Labban, A. A. Anderson, and H. E. O'Connor Linoleic and Oleic Acids Alter the Licking Responses to Sweet, Salt, Sour, and Bitter Tastants in Rats Chem Senses, November 1, 2006; 31(9): 835 - 843. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 P. Mirmiran, L. Azadbakht, and F. Azizi Dietary Diversity within Food Groups: An Indicator of Specific Nutrient Adequacy in Tehranian Women. J. Am. Coll. Nutr., August 1, 2006; 25(4): 354 - 361. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 N. P. Hays, G. P. Bathalon, R. Roubenoff, M. A. McCrory, and S. B. Roberts Eating behavior and weight change in healthy postmenopausal women: results of a 4-year longitudinal study. J. Gerontol. A Biol. Sci. Med. Sci., June 1, 2006; 61(6): 608 - 615. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. B. Roberts and I. Rosenberg Nutrition and Aging: Changes in the Regulation of Energy Metabolism With Aging Physiol Rev, April 1, 2006; 86(2): 651 - 667. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. L. Eckhardt, C. Suchindran, P. Gordon-Larsen, and L. S. Adair The Association between Diet and Height in the Postinfancy Period Changes with Age and Socioeconomic Status in Filipino Youths J. Nutr., September 1, 2005; 135(9): 2192 - 2198. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. B. Roberts, C. L. Hajduk, N. C. Howarth, R. Russell, and M. A. McCrory Dietary Variety Predicts Low Body Mass Indexand Inadequate Macronutrient and MicronutrientIntakes in Community-Dwelling Older Adults J. Gerontol. A Biol. Sci. Med. Sci., May 1, 2005; 60(5): 613 - 621. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. G. Pittas, R. Hariharan, P. C. Stark, C. L. Hajduk, A. S. Greenberg, and S. B. Roberts Interstitial Glucose Level Is a Significant Predictor of Energy Intake in Free-Living Women with Healthy Body Weight J. Nutr., May 1, 2005; 135(5): 1070 - 1074. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
H. M Snoek, L. Huntjens, L. J van Gemert, C. de Graaf, and H. Weenen Sensory-specific satiety in obese and normal-weight women Am. J. Clinical Nutrition, October 1, 2004; 80(4): 823 - 831. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. M.-M. Sea, J. Woo, P. C.-Y. Tong, C.-C. Chow, and J. C.-N. Chan Associations between Food Variety and Body Fatness in Hong Kong Chinese Adults J. Am. Coll. Nutr., October 1, 2004; 23(5): 404 - 413. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. A. Foote, S. P. Murphy, L. R. Wilkens, P. P. Basiotis, and A. Carlson Dietary Variety Increases the Probability of Nutrient Adequacy among Adults J. Nutr., July 1, 2004; 134(7): 1779 - 1785. [Abstract] [Full Text]
|
|
|
|
 |
|
 I. E. de Araujo and E. T. Rolls Representation in the Human Brain of Food Texture and Oral Fat J. Neurosci., March 24, 2004; 24(12): 3086 - 3093. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. Yao, M. A McCrory, G. Ma, K. L Tucker, S. Gao, P. Fuss, and S. B Roberts Relative influence of diet and physical activity on body composition in urban Chinese adults Am. J. Clinical Nutrition, June 1, 2003; 77(6): 1409 - 1416. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
R. D. Mattes Ready-to-eat Cereal Used as a Meal Replacement Promotes Weight Loss in Humans J. Am. Coll. Nutr., December 1, 2002; 21(6): 570 - 577. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. A. McCrory, V. M.M. Suen, and S. B. Roberts Biobehavioral Influences on Energy Intake and Adult Weight Gain J. Nutr., December 1, 2002; 132(12): 3830S - 3834. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 L. M. Delahanty Evidence-Based Trends for Achieving Weight Loss and Increased Physical Activity: Applications for Diabetes Prevention and Treatment Diabetes Spectr, July 1, 2002; 15(3): 183 - 189. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
N. P Hays, G. P Bathalon, M. A McCrory, R. Roubenoff, R. Lipman, and S. B Roberts Eating behavior correlates of adult weight gain and obesity in healthy women aged 55-65 y Am. J. Clinical Nutrition, March 1, 2002; 75(3): 476 - 483. [Abstract] [Full Text] [PDF]
|
|
|
|
