HomeLarge Type Edition
HOME ARCHIVE SEARCH TABLE OF CONTENTS
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Services
Right arrow Download to citation manager
PubMed
Right arrow PubMed Citation
The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 59:1304-1309 (2004)
© 2004 The Gerontological Society of America

Hunger and Aversion: Drives That Influence Food Intake of Hospitalized Geriatric Patients

Danielle St-Arnaud-McKenzie1,2, Catherine Paquet1,3, Marie-Jeanne Kergoat1,4, Guylaine Ferland1,2 and Laurette Dubé1,3,

1 Research Center, Institut Universitaire de Gériatrie de Montréal, Canada.
2 Nutrition Department, Université de Montréal, Canada.
3 Faculty of Management, McGill University, Montréal, Canada.
4 Medicine Department, Université de Montréal, Canada.

Address correspondence to Laurette Dubé, Faculty of Management, McGill University, 1001 Sherbrooke West, Montreal, Québec, Canada H3A 1G5. E-mail: laurette.dube{at}mcgill.ca


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 References
 
Background. Diminished appetite occurs frequently with aging and is considered an important clinical symptom of malnutrition, a condition associated with negative clinical outcome, decreased quality of life, and increased health care costs in hospitalized geriatric patients. Yet, in this population, research is scant on hunger and aversion, the two underlying drives that shape appetite, or on their influence on food intake. This study aimed (a) to examine their interrelationship and respective contribution to food intake; (b) to determine how each relate to other health-related contemporaneous subjective states preceding the meal (good physical health, positive mood, pain); and (c) to explore clinical variables as moderators of the drives–intake relationships to identify population segments for which these relationships are the strongest.

Methods. 32 patients (21 women, 11 men; age range, 65–92 years) were observed during repeated meals in a geriatric rehabilitation unit (for a total of 1477 meals). Perceived hunger, aversion, and contemporaneous subjective states were reported before each meal. Protein and energy consumption was calculated from plate leftovers. Clinical measures were obtained from participants' medical charts.

Results. The hunger–aversion relationship had a low inverse correlation (p =.001), with each uniquely contributing to protein intake (positive and negative effects, respectively; all p <.05). Hunger was positively associated with the perception of physical health and with mood (all p =.001). Aversion was associated with pain (p =.001). Furthermore, aversion–intake relationships were influenced by moderators, whereas hunger–intake relationships remained constant.

Conclusions. From a clinical perspective, these results suggest that nutritional interventions aimed at bolstering hunger and curbing aversion may be necessary to ensure optimal food intake. Subgroups of patients who would particularly benefit from these interventions are suggested.

DIMINISHED appetite is frequently reported in older persons and is associated with decreased food intake (1–3). It is also considered an important clinical symptom of malnutrition (4,5), a condition associated with negative clinical outcomes, decreased quality of life, and increased health care costs in hospitalized geriatric patients (6–9). Yet, in this population, research is scant on hunger and aversion, the two underlying drives that shape appetite at the meal level, or on their impact on food intake (10–13). This limitation of previous research is particularly important considering that feelings of hunger and aversion are altered with aging (1,14,15), possibly influencing food intake in the hospitalized elderly (3,16,17).

Our current research was based on the premise that, in the hospitalized elderly, a better understanding of how feelings of hunger and aversion are modulated at any meal, and how they operate in influencing food intake, could lead to the development of innovative nutritional care strategies. We had three specific objectives. The first objective was to study the relationship between hunger and aversion and their respective contribution to food intake. Because research shows that positive and negative affective responses generally are not correlated strongly with each other (18,19), and that motivational processes tied to approach and withdrawal tendencies have distinct neurologic substrates (20), we expected hunger and aversion to vary relatively independently and to contribute significantly to food intake at any given meal.

Our second objective was to acquire knowledge on the relationships between each drive and other contemporaneous facets of subjective experience preceding the meal, such as the perception of good physical health, positive mood, and pain. For instance, although research shows that feelings of hunger are tied to the experience of positive mood around mealtime (21), previous research on mood suggests that it is an unlikely correlate of aversion (22). In addition, controlling pain in elderly patients with terminal cancer, who often develop food aversions, successfully improves food intake (23). However, pain research suggests that such intervention would leave hunger unaffected (24). Thus, in this regard, we expected hunger and aversion to have distinct significant contemporaneous correlates.

Finally, we studied moderators of the relationships between drives and intakes to identify population segments in whom the two drives have the most powerful impact on patients' food intake. Such segments would particularly benefit from the careful tailoring of interventions to modulate both hunger and aversion to achieve optimal food intake. We expected drive–intake relationships to be moderated by individual (age, sex, body mass index), psychological (cognitive deficits, feelings of depression), and clinical factors (appetite, nutritional status, functional independence, physical impairment, and use of multiple medications) (1–3,25,26). This expectation is also based on research showing that important contextual variations exist in the signaling value of drives and other visceral influences in guiding decision making and behavior (27).


   METHODS
Top
 Abstract
 Methods
Results
 Discussion
 References
 
Study Overview
We collected our data as part of a larger investigation of the individual and organizational determinants of food intake and nutritional status of hospitalized elderly patients. Figure 1 shows an overview of the relationships that we explored to achieve the proposed research objectives. The study was longitudinal, with repeated measurements collected for a large number of meals, a given meal being the unit of analysis. For each participant, we obtained meal-level measures for all three main meals, every other day of the hospital stay until discharge (for a maximum of 6 weeks).



View larger version (17K):
[in this window]
[in a new window]
  		Figure 1. The contribution of feelings of hunger and aversion to protein and energy intake was assessed using random coefficient analysis. The degree of correlation between hunger and aversion, between each drive and subjective premeal contemporaneous states (physical health, mood, and pain), and between each drive and food intake was tested using partial correlation coefficients. The moderating effect of individual, psychological, and clinical variables on the drives–intake relationships was also explored (see the analytical strategy described in Methods)

 
Participants
We screened all patients newly admitted to the rehabilitation unit of the Institut Universitaire de Gériatrie de Montréal between December 1999 and June 2001 for eligibility. Figure 2 shows the selection criteria and recruitment algorithm. We selected these criteria based on their potential interference with informed consent and perceptual measures or on their known resistance to nutritional interventions.



View larger version (25K):
[in this window]
[in a new window]
  		Figure 2. During the study, all elderly patients newly admitted to the rehabilitation unit of the Institut Universitaire de Gériatrie de Montréal were screened for eligibility. A maximum of two participants were observed on any single day. When a slot was freed, the first available newly admitted eligible patient was invited to participate. MMSE = Mini-Mental State Examination (32); GDS-15 = Geriatric Depression Scale-15 (33)

 
Thirty-two participants completed the study (21 women, 11 men; mean age, 78.8 ± 6.5 years; main diagnoses: stroke [53%], fracture [22%], and deconditioning [25%]). Table 1 shows the participants' sociodemographic and clinical characteristics. The facility's research ethics committee approved the protocol, and participants provided informed consent. After giving consent, the participants were trained in using the measurement scales to be used to provide momentary self-reports. Participants received a $50 CAN compensation.


View this table:
[in this window]
[in a new window]
  		Table 1. Participants' Characteristics and Descriptive Statistics for the Total Sample and by Subgroups Based on the Median Values, Except for Gender and Appetite for Which Categories Were Predefined.

 
Measures
Premeal self-reports of drives and contemporaneous states.-- Approximately 5 to 10 minutes before meals were served, participants described their drives and contemporaneous states using five visual analog scales with sliding rules, all integrated into a rigid magnetic board. Labels to the left of each scale were "I feel hungry" (hunger), "the thought of eating disgusts me" (aversion), "I feel happy" (positive mood), "I feel pain" (pain), and "I feel my physical health is good" (subjective physical health). Each scale's response continuum was specified by a 153 mm line. Following standard instructions for momentary self-reports (18,28), participants were asked to move the sliding rules from "not at all" (0 mm) to "very much" (153 mm) to reflect the intensity of their subjective experience "at the present time."

Energy and protein intake.-- Food intake was determined from the visual estimation of plate leftovers using the Comstock scale (29,30). To reduce measurement error in the estimation of food intake, rigorous and systematic monitoring of portion sizes from standardized recipes was performed during the study period [see Paquet and colleagues (31) for details]. We translated the estimated intake portions into energy and protein intake using the NutriWatch Nutrient Analysis Program (version 6.1.5F Delphi, E. Warwick, Cornwall, PEI, 1997). We expressed each participant's meal energy and protein intake in terms of his or her meal-level nutritional needs. We calculated meal-level nutritional needs as the product of a participant's daily energy and protein requirements (Harris-Benedict x activity factor of 1.3) by the mean proportion of the participant's daily intake for the corresponding meal type (breakfast, lunch, dinner) during the observation period.

Moderators.-- We obtained patient-level measures of individual, psychological, and clinical measures from the patients' hospital charts.

Individual characteristics we considered included age, sex, and body mass index (kg/m2).

Psychological variables were cognitive status and degree of depressed feelings. Cognitive status was evaluated using the Mini-Mental State Examination (32), with a higher score (maximum, 30) indicating better cognitive ability. We used the Geriatric Depression Scale-15 to rate depression (33), with a higher score indicating more feelings of depression.

Clinical variables included self-reported appetite at admission, nutritional status, functional status, severity of impairment, and use of multiple medications. Appetite was dichotomized (1 = normal or good appetite; 0 = diminished appetite). We assessed nutritional status based on Thomas's Protein-Energy Malnutrition Index, which comprises body mass index, percentage of ideal body weight, triceps skinfold, midarm circumference, serum albumin, total lymphocyte count, and hemoglobin (34). We adapted the Protein-Energy Malnutrition Index so that a score of 3 or higher with both anthropometric and biochemical anomalies on this 7-point scale indicated severe malnutrition. We assessed functional independence using the Functional Independence Measure (35), with a higher score (maximum, 126) indicating greater independence. The geriatrician on the research team (M.J.K.) evaluated the severity of physical impairment from the participants' physical examination report using the Cumulative Illness Rating Scale (36), with a higher score (maximum, 52) indicating greater impairment. Finally, polypharmacy reflects the number of prescription drugs patients were taking at admission.

Statistical Analyses
We collected data for 1477 meals. We excluded participants for whom information for a variable was missing, or meals for which data were missing for a meal-level variable, from the analyses involving that particular variable.

Analyses performed to fulfill research objectives were of three kinds. First, we tested the distinctive contribution of hunger and aversion to intake using random coefficient analysis (37). This analysis estimated the ability of feelings of hunger and aversion reported before each meal to predict food intakes (energy and protein), taking into consideration both within-participants and between-participants variability. In random coefficient analyses, the proportion of variance in the dependent variables explained by the predictor is reflected in Schwarz's Bayesian Information Criterion (BIC) (38), with a higher value reflecting better fit. The contribution of each predictor is estimated in a distinct parameter (akin to beta in a regression analysis).

Second, we computed partial correlations between three sets of measures, that is, (a) between the two drives, hunger and aversion; (b) between each drive and other subjective contemporaneous states (physical health, mood, and pain); and (c) between each drive and intakes (energy and protein). We did this to control for response tendencies associated with repeated measurements so as to render all observations comparable. To achieve this, we determined correlations based on residual scores obtained from regression analyses in which each variable to be correlated was predicted by indicator variables created for all participants (39).

Third, to explore the moderating role that individual, psychological, and clinical factors may play on the relationships between drives and intakes, we calculated the same set of partial correlations (just described) separately for subgroups presenting low and high values of each moderator. The subgroup assignment was based on the variable's median value (except for sex and age, for which categories were predefined). We compared subgroup correlation coefficients using Fisher's Z transformation (40). All data were entered using Microsoft Excel 97 (Microsoft, Redmond, WA). We performed the analyses using SPSS 10.0.5 for Windows (SPSS, Chicago, IL). We performed the random coefficient analysis using the Proc Mixed procedure from SAS version 6.12 (SAS Institute, Cary, NC). In all analyses, we considered two-tailed probability values (p <.05) significant; however, because of the early stage of research, results with p <.10 are also presented.


   RESULTS
Top
 Abstract
 Methods
 Results
Discussion
 References
 
Hunger, Aversion, and Their Respective Contribution to Food Intake
Consistent with expectations, analyses revealed that the inverse correlation between the two drives was low (r = –0.113, p =.001) and that each of them contributed uniquely to food intake. Specifically, results showed that protein intake (BIC = –4764), more than energy intake (BICriterion = –9116), was sensitive to variation in feelings of hunger and aversion. Both hunger (p =.017) and aversion (p =.032) uniquely contributed to protein intake, with a corresponding positive or negative effect of comparable magnitude (both parameter estimates = 0.12). The relationships with energy intake, although not significant (p >.10), were directionally as expected.

Contemporaneous Correlates of Hunger and Aversion
Analyses further revealed that the two drives presented distinct contemporaneous correlates. Namely, that hunger was directly related to the contemporaneous experience of perceiving oneself to be in good physical health (r = 0.21, p =.001) and in a good mood (r = 0.26, p =.001), with no statistical link with pain intensity (p >.90). In contrast, pain was the only correlate of aversion (r = 0.17, p =.001; the other two p values >.15).

Moderators
We considered moderators of drives–intake relationships to explore characteristics that could define subgroups that differed in terms of the strength of these associations (Figure 1). We analyzed each moderator separately.

Although the hunger–intake relationships remained insensitive to all moderators (all p values >.19), those between aversion and intake varied by sex, cognitive status, appetite, nutritional status, degree of functional independence, and impairment severity (Table 2). More specifically, aversion was more strongly inversely related to both intakes in men, in participants with lower cognitive status, and in those with lower impairment. The more functionally independent participants showed a stronger aversion–energy relation, with directionally consistent results for protein intake. Furthermore, the aversion–protein relation was stronger in those with normal or good appetite and better nutritional status.


View this table:
[in this window]
[in a new window]
  		Table 2. Moderating Effects of Individual, Psychological, and Clinical Variables on the Relationships Between Aversion and Food Intake in Terms of Energy and Protein Intake.

 

   DISCUSSION
Top
 Abstract
 Methods
 Results
 Discussion
References
 
Results showed that premeal feelings of hunger and aversion, as measured in this study, were relatively independent drives that had an equal but opposite impact on protein intake, with each being sensitive to distinct correlates. Effects for energy intake, although not statistically significant, were nonetheless directionally consistent. Furthermore, feelings of hunger were correlated with the contemporaneous experience of good subjective physical health, and positive mood, whereas aversion was tied to pain intensity.

The finding that hunger and aversion were weakly correlated was consistent with previous research on other types of affective responses (18,19). This implies that interventions designed to improve hunger may have little effect on the prevention of aversion, and vice versa. Because both hunger and aversion contributed equally to food intake, it is important to envision interventions aimed specifically at each drive. Insights into appropriate strategies are provided by their distinct correlates.

Recall that hunger was tied to the contemporaneous state of good physical health and positive mood. Reliable evidence suggests that mood is sensitive to factors that can be built into the meal environment, such as music, aesthetic decor, and pleasant smell (41), and that such environmental manipulations do affect food intake in hospitalized geriatric patients (42), although the possible intermediary role of positive mood was not explored. We found no research that has tested strategies to improve perceptions of good physical health. However, comments from participants in the current study suggested that ensuring time to rest before the meal after the various activities and therapies that patients engage in between meals might contribute to improvements in this regard. This proposition would have to be tested in future research.

Turning to aversion, pain relief, through a more effective use of pain medication or simply using relaxation techniques, for example, could help curb feelings of aversion and their deleterious effects on food intake. This would be consistent with findings of the study in elderly patients with terminal cancer noted earlier (23). Furthermore, the aversion–protein intake relationship was particularly strong for elderly patients with good appetite and better nutritional status at admission, making them susceptible to potential onset of malnutrition during the course of hospitalization. In support of this idea, other research has noted that patients' feelings of aversion may arise in hospital settings where meals are eaten in the presence of other patients with feeding tubes or who exhibit inappropriate feeding behaviors (25). Thus, our results suggest that interventions designed to monitor and curb feelings of aversion by ensuring an appropriate social environment at mealtime, for example, may help to prevent malnutrition.

Finally, questions arise about the drives' effects being observed more strongly on protein intake compared with energy intake. These results may be tied to the fact that protein is particularly sensitive to mechanisms regulating short-term human feeding behavior (43), which may also make it especially sensitive to drives. In addition, our findings could also be tied to results of studies that have found animal protein to be a privileged target for learned food aversions in humans (44).

In the current study, we identified population segments for whom the careful tailoring of interventions to modulate hunger and aversion to improve food intake might be particularly beneficial. These segments included patients for whom aversion was most strongly associated with intakes (i.e., men, patients with light cognitive deficits, and those in relatively better clinical condition at admission, as indicated by normal appetite, good nutritional status, greater functional independence, and lower levels of impairment). Further quantitative studies are needed to test the existence of these segments in a larger population sample.

Conclusion
Our results underscore the need to enrich current nutrition practice in treating malnutrition in hospitalized geriatric patients with a more systematic consideration of interventions that aim to modulate hunger and aversion as an intrinsic part of nutritional care. Because drives are influenced by the quality of the immediate subjective experience (45), careful design of sensorial, environmental, and social components surrounding the meal are likely to improve food intake. Indeed, results from recent studies of the influence of specific interventions on food intake in elderly people are consistent with this notion (23,46). We hope that our findings will foster further practice and research development in this direction.


   Acknowledgments
 
Supported by the Canadian Institutes of Health Research (operating grant to Laurette Dubé and Graduate Studies Fellowship to Catherine Paquet) and by the Danone Institute of Canada (Graduate Studies Fellowship to Danielle St-Arnaud-McKenzie). The authors thank the nutrition and health professionals and to the staff of the dietetics and food services of the Institut Universitaire de Gériatrie de Montréal for their help and collaboration during the study.

Laurette Dubé is a Canadian Institute of Health Research/Social Sciences and Humanities Research Council of Canada career scientist.

Received March 17, 2003

Accepted August 11, 2003


   References
Top
 Abstract
 Methods
 Results
 Discussion
 References
 

  1. Morley JE. Anorexia of aging: physiologic and pathologic. Am J Clin Nutr. 1997;66:760-773.[Abstract/Free Full Text]
  2. Van Staveren WA, de Graaf C, de Groot LC. Regulation of appetite in frail persons. Clin Geriatr Med. 2002;18:675-684.[Medline]
  3. Mowé M, Bømer T. Reduced appetite. A predictor for undernutrition in aged people. J Nutr Health Aging. 2002;6:81-83.[Medline]
  4. Chapman KM, Nelson RA. Loss of appetite: managing unwanted weight loss in the older patient. Geriatrics. 1994;49:54-59.
  5. Kergoat M-J. La perte de poids chez les résidants âgés des centres d'hébergement et de soins de longue durée. Rev Med Suisse Romande. 2000;120:853-861.[Medline]
  6. Sullivan DH, Walls RC. Impact of nutritional status on morbidity in a population of geriatric rehabilitation patients. J Am Geriatr Soc. 1994;42:471-477.[Medline]
  7. Frisoni GB, Franzoni S, Rozzini R, Ferrucci L, Boffelli S, Trabucchi M. Food intake and mortality in the frail elderly. J Gerontol Med Sci. 1995;50A:M203-M210.
  8. Crogan NL, Pasvogel A. The influence of protein-calorie malnutrition on quality of life in nursing homes. J Gerontol Biol Sci Med Sci. 2003;58A:159-164.
  9. Pertoldi W, Herrmann F, Quadri P, et al. Évaluation de l'état nutritionnel chez une population hospitalisée, âgée et potentiellement non-malnourrie, et relation avec les coûts et la durée d'hospitalisation. Age Nutrition. 2000;11:13-20.
  10. Brehm JW. The intensity of emotion. Pers Soc Psychol Rev. 1999;3:2-22.[Abstract/Free Full Text]
  11. Bellisle F, Dalix A, de Castro JM. Eating patterns in French subjects studied by the ‘weekly food diary’ method. Appetite. 1999;32:46-52.[Medline]
  12. Pelchat ML, Rozin P. The special role of nausea in the acquisition of food dislikes by humans. Appetite. 1982;3:341-351.[Medline]
  13. Bernstein IL. Taste aversion learning: a contemporary perspective. Nutrition. 1999;15:229-234.[Medline]
  14. Pelchat M, LaChaussee JL. Food cravings and taste aversions in the elderly. Appetite. 1994;23:193.[Medline]
  15. de Castro JM. Age-related changes in the social, psychological, and temporal influences on food intake in free-living healthy, adult humans. J Gerontol Med Sci. 2002;57A:M368-M377.
  16. Mowe M, Bohmer T, Kindt E. Reduced nutritional status in an elderly population (>70 y) is probable before disease and possibly contributes to the development of disease. Am J Clin Nutr. 1994;59:317-324.[Abstract/Free Full Text]
  17. Berntein IL. Food aversion learning: a risk factor for nutritional problems in the elderly. Physiol Behav. 1999;66:199-201.[Medline]
  18. Dube L, Morgan, MS. Trend effects and gender differences in retrospective judgments of consumption emotions. J Consum Res. 1996;23:156-162.
  19. Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect: the PANAS Scales. J Pers Soc Psychol. 1988;54:1063-1070.[Medline]
  20. Davidson RJ. Cerebral asymmetry, emotion, and affective style. In: Davidson RJ, Hugdahl K, eds. Brain Asymmetry. Cambridge: Massachusetts Institute of Technology; 1995:361–387.
  21. Macht M. Characteristics of eating in anger, fear, sadness and joy. Appetite. 1999;33:129-139.[Medline]
  22. Isen AM, Shalker TE. The effect of feeling states on evaluation of positive, neutral, and negative stimuli: when you ‘accentuate the positive,’ do you ‘eliminate the negative’? Soc Psychol Q. 1982;45:58-63.
  23. Feuz A, Rapin CH. An observational study of the role of pain control and food adaptation of elderly patients with terminal cancer. J Am Diet Assoc. 1994;94:767-770.[Medline]
  24. Eccleston C, Crombez G. Pain demands attention: a cognitive-affective model of the interruptive function of pain. Psychol Bull. 1999;125:356-366.[Medline]
  25. Morley JE, Silver AJ. Nutritional issues in nursing home care. Ann Intern Med. 1995;123:850-859.[Abstract/Free Full Text]
  26. Keller HH. Malnutrition in institutionalized elderly: how and why? J Am Geriatr Soc. 1993;41:1212-1218.[Medline]
  27. Loewenstein G. Out of control: visceral influences on behavior. Org Behav Human Decis Proc. 1996;65:272-292.
  28. Robinson MD, Clore GL. Belief and feeling: evidence for an accessibility model of emotional self-report. Psychol Bull. 2002;128:934-960.[Medline]
  29. Comstock EM, St-Pierre RG, Mackierman YD. Measuring individual plate waste in school lunches. J Am Diet Assoc. 1981;79:290-296.[Medline]
  30. Berrut G, Favreau AM, Dizo E, et al. Estimation of calorie and protein intake in aged patients: validation of a method based on meal portions consumed. J Gerontol Med Sci. 2002;57A:M52-M56.
  31. Paquet C, St-Arnaud-McKenzie D, Ferland G, Dubé L. A blueprint-based case study analysis of nutrition services provided in a mid-term care facility for the elderly. J Am Diet Assoc. 2003;103:363-368.[Medline]
  32. Folstein M, Folstein SE, McHugh PR. ‘Mini-Mental State’: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12:189-198.[Medline]
  33. Sheikh JA, Yesavage JA. Geriatric Depression Scale (GDS): recent findings and development of a shorter version. In: Brink TL, ed. Clinical Gerontology: A Guide to Assessment and Intervention. New York: Howarth Press; 1986:165–173.
  34. Thomas DR, Verdery RB, Gardner L, et al. A prospective study of outcome of protein-energy malnutrition in nursing home residents. JPEN J Parenter Enteral Nutr. 1991;15:400-404.[Abstract/Free Full Text]
  35. Hamilton BB, Granger CV, Sherwin FS, Zielezny M, Tashman JS. A uniform national data system for medical rehabilitation. In: Fuhrer MJ, ed. Rehabilitation Outcomes: Analysis and Measurement. Baltimore: Paul H. Brooks; 1987:135–147.
  36. Linn BS, Linn MW, Gurel L. Cumulative Illness Rating Scale. J Am Geriatr Soc. 1968;16:622-626.[Medline]
  37. Bryk A, Raudenbush SW. Application of hierarchical linear models to assessing change. Psychol Bull. 1987;101:147-158.
  38. Schwarz G. Estimating the dimension of a model. Ann Stat. 1978;6:461-464.
  39. Priester JR, Petty RE. The gradual threshold model of ambivalence: relating the positive and negative bases of attitudes to subjective ambivalence. J Pers Soc Psychol. 1996;71:431-449.[Medline]
  40. O'Mahony M. Correlation and regression. In: O'Mahony M, ed. Sensory Evaluation of Food: Statistical Methods and Procedures. New York: Marcel Dekker; 1986:294–295.
  41. Dubé L, Morin S. Background music pleasure and store evaluation: intensity effects and psychological mechanisms. J Busin Res. 2001;54:107-113.
  42. Mathey MFAM, Vanneste VGG, de Graaf C, de Groot LCPGM, van Staveren WA. Health effect of improved meal ambiance in a Dutch nursing home: a 1-year intervention study. Prev Med. 2001;32:416-423.[Medline]
  43. French SJ. The effects of specific nutrients on the regulation of feeding behavior in human subjects. Proc Nutr Soc. 1999;58:533-540.[Medline]
  44. Midkiff EE, Bernstein LL. Target of learned aversions in human. Physiol Behav. 1984;34:839-841.
  45. Berridge KC. Pleasure, pain, desire, and dread: hidden core processes of emotion. In: Kahneman D, Diener E, Schwarz N, eds. Well-being: The Foundations of Hedonic Psychology. New York: Russell Sage Foundation; 1999:525–557.
  46. Mathey MF, Siebelink E, de Graaf C, Staeren WAV. Flavor enhancement of food improves dietary intake and nutritional status of elderly. J Gerontol Med Sci. 2001;56A:M200-M205.




This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Services
Right arrow Download to citation manager
PubMed
Right arrow PubMed Citation

HOME ARCHIVE SEARCH TABLE OF CONTENTS