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The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 60:499-505 (2005)
© 2005 The Gerontological Society of America

Behavioral Disturbances, Not Cognitive Deterioration, Are Associated With Altered Food Selection in Seniors With Alzheimer's Disease

Carol E. Greenwood1,2,5,, Carolyn Tam1, Mae Chan1, Karen W. H. Young1,5, Malcolm A. Binns3 and Robert van Reekum1,4

1 Kunin-Lunenfeld Applied Research Unit
2 Department of Food and Nutrition Services
3 Rotman Research Institute
4 Department of Psychiatry, Baycrest Centre for Geriatric Care, Toronto, Ontario, Canada.
5 Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Ontario, Canada.

Address correspondence to Carol E. Greenwood, PhD, Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada M5S 3E2. E-mail: carol.greenwood{at}utoronto.ca


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 References
 
Objective. We previously reported alterations in circadian patterns of food intake that are associated with measures of functional and cognitive deterioration in seniors with probable Alzheimer's disease (AD). This study further explored disturbed eating patterns in AD, focusing on alterations in macronutrient (protein, carbohydrate, and fat) selection, and their association with measures of functional and behavioral losses.

Methods. Forty-nine days of food intake collections were conducted on 32 residents (26 females, 6 males; age = 88.4 ± 4.1 years; body mass index = 24.1 ± 4.0 kg/m2) with probable AD residing at a nursing home (a fully accredited geriatric teaching facility affiliated with the University of Toronto's Medical School). All residents ate their meals independently. The relationships between patterns of habitual food consumption and measures of cognitive function (Severe Impairment Battery), behavioral disturbances (Neuropsychiatric Inventory-Nursing Home Version) and behavioral function (London Psychogeriatric Rating Scale) were examined, cross-sectionally.

Results. Consistent with our previous studies, breakfast intakes were not predicted by any of the measures of behavioral, cognitive, or functional deterioration, although those residents with greater functional deterioration, especially disengagement, attained lower 24-hour energy intakes. The presence of "psychomotor disturbances," including irritability, agitation, and disinhibition, were strongly associated with shifts in eating patterns toward carbohydrate and away from protein, placing individuals with these conditions at increased risk for inadequate protein intakes. Between-individual differences in intake patterns could not be explained by the use of either anorexic or orexigenic medications.

Conclusions. Behavioral, not cognitive, deterioration is associated with appetite modifications that increase risk of poor protein intake, perhaps indicating a common monoaminergic involvement.

ALTHOUGH seniors with probable Alzheimer's disease (AD) are at high risk for weight loss (1–3) and malnutrition (4–7), inadequate attention has been given to understanding specific alterations in food intake and how these alterations are associated with measures of disease progression. Yet, identifying stages of disease progression that are associated with disturbed intake patterns should allow for earlier intervention, prior to the onset of overt malnutrition. Furthermore, strategies to sustain nutritional status must be implemented against a background of deteriorating behavioral and cognitive function of the individual. Without accounting for associations between functional losses and altered eating behaviors, it is unlikely that interventions will be successful.

Our previous studies (8,9) focused on the relationship between measures of disease progression and total food intake. Yet problems encountered in feeding seniors with AD relate not only to the quantity, but also to the quality of foods consumed. Subjective and objective measures indicate that seniors with dementia, especially those with AD, have an increased preference for sweet foods (10,11) which can potentially translate to a greater proportion of energy being consumed as carbohydrate (CHO) and less as protein in comparison to healthy young and elderly persons (12). If this indication is true, then these data could imply that malnutrition risk in seniors with AD is associated not only with reduced food intake, but also with movement away from protein-containing foods. Whether these shifts in macronutrient selection have a clinically meaningful impact on chronic macronutrient (CHO, protein, and fat) intake (e.g., are associated with reduced protein intake) and when in the course of AD progression these shifts occur have not been systematically examined. Thus this study explored food intake patterns, including macronutrient selection, in a group of institutionalized seniors with AD and identified measures of cognitive and behavioral function that are associated with shifts in food intake patterns.


   METHODS
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 Abstract
 Methods
Results
 Discussion
 References
 
Residents
Residents of the AD units of the Apotex Centre at Baycrest Centre for Geriatric Care (an academic geriatric care facility associated with the University of Toronto's Medical School) were eligible for selection. Inclusion criteria were: a) a diagnosis of probable AD by an appropriate clinician, b) the ability to self-feed and/or requiring only minimal levels of assistance (e.g., opening containers), and c) receiving all foods orally. Exclusion criteria were: a) diseases requiring nutritional intervention (e.g., type 1 diabetes), b) prescription of an energy-restricted diet (e.g., for type 2 diabetes), c) swallowing difficulties requiring a texture-modified diet, and d) clinically recognized or suspected acute illness, such as infection or influenza. Residents were not excluded on the basis of other comorbid conditions, including depression. These pieces of information were obtained by conducting chart reviews and consulting with the residents' primary health care providers (primary physicians, attending nurses, and dieticians). Following protocol approval by the Baycrest ethics committee, written informed consent was obtained from the family or legal guardian. Thirty-four residents were recruited into the study, comprising an 87% participation rate of identified eligible residents. Two participants required hospitalization due to acute illness during the course of the study and were eliminated from all analyses.

Food Intake Measurements
Food intake was measured for 91 consecutive days for each resident, divided into five phases. The first four phases were each 21 days in duration, whereas the last phase was the remaining 7 days. Two different dietary interventions, providing a mid-morning snack (13) and altering dinner food choices (14), were randomly assigned during the second and fourth phases. The first, third, and fifth phases were baseline and washout periods where no intervention was imposed, yet food intake was monitored. Data from these three phases were pooled (49 days/resident) to provide a measure of habitual food intake.

All foods were weighed before and after consumption to quantify the amount consumed. Food consumption was converted to nutrient intake using a software program, Dietary Food Management (DFM; DFM Systems, Des Moines, IA), which contains all facility recipes and calculates the nutrient composition based on individual ingredients using the Canadian Nutrient Database (15). Energy and nutrient intakes for each meal were calculated both including and excluding intake from nutritional supplements. Eight residents were routinely receiving nutritional supplements (Ensure or Ensure Plus, in liquid or pudding form) with their meals, according to dietitian orders. Because nutritional supplements are of a fixed macronutrient composition, they do not allow for the expression of macronutrient preference and, consequently, may mask underlying appetite changes in some persons.

Cognitive and Behavioral Assessments
The Global Deterioration Scale (GDS) (16) and the Severe Impairment Battery (SIB) (17) were administered to assess cognitive abilities. Behavioral disturbances were assessed by the Neuropsychiatric Inventory-Nursing Home Version (NPI) (18), and behavioral function was assessed by the London Psychogeriatric Rating Scale (LPRS) (19). Lower scores on the SIB and higher scores on the GDS, LPRS, and NPI indicate greater impairment.

Trained research assistants, unfamiliar with the eating patterns of the resident, administered the SIB while the primary caregiver completed the GDS, NPI, and LPRS. All assessments were conducted during the baseline phase, and the SIB and NPI were repeated during the last week of the study, with the mean score being used in the analyses.

Sample Size Calculations
Separate power calculations estimated the number of days of food intake required per individual and the number of residents required. Estimating the number of days of food intake collection relied on our reports of mean, minimum, and maximum 24-hour and meal-related variability in food intake, measured in a comparable institutionalized group of 19 seniors with probable AD (8). Twenty-one days (duration of each study phase) is sufficient to capture habitual energy and macronutrient intakes of an individual (20). To explore the associations between food intake profiles and resident characteristics with a group level correlation of 0.5 ({alpha} = 0.05, ß = 0.20) 28 individuals were required. Assuming a loss of approximately 20% during the study, 34 residents were initially recruited.

Statistical Analyses
For each resident, mean values for meal-related and 24-hour nutrient intakes were used for further analyses. Consequently, measures of variability, expressed as standard deviation, represent between-resident variability only. To address macronutrient selection, or quality of diet consumed, all data for macronutrient intakes are expressed as a percentage of total energy consumed.

To explore associations between nutrient intake patterns, cognitive abilities and behavioral disturbances factor analyses (SAS for Windows, version 8; SAS Institute, Cary, NC) were first conducted (21) within each assessment administered, to identify which cognitive or behavioral symptoms occur together because many behavioral disturbances are likely to be grouped into a few syndromes (22,23). The number of factors retained was determined by examining a scree plot of eigenvalues and focusing on those with eigenvalues >1, using clinical judgment, and comparing them to previously published results (22,23). Orthogonal rotation of the factor matrix was used to obtain the factor loadings. Dominant symptoms within each factor were identified as those with factor loadings ≥0.60 in absolute terms. Multiple and simple regression analyses were conducted to investigate associations between 24-hour and meal-related intakes and the factor scores for each cognitive or behavioral assessment, using the reciprocal of the variance of mean intake measures for each individual as a weighting variable (24). In cases where only one factor was extracted (SIB and LPRS assessments), regression analyses were conducted between the assessments' subscales and intake measures. Recognizing that a sample exceeding 100 residents is a general criterion for conducting factor analysis (21), support for our results was sought from previously published NPI factor loadings using a larger sample from a similar population (22).


   RESULTS
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 Abstract
 Methods
 Results
Discussion
 References
 
Resident Characteristics and Nutrient Intakes
Thirty-two seniors [6 men, 26 women; age = 88.4 ± 4.1(79–97) years; body mass index = 24.1 ± 4.0 (15.3–32.7) kg/m2; values are means ± standard deviation (range)] completed all phases of the study. Refer to Table 1 for mean scores on the assessments and their subscales. For the SIB only, two legal guardians did not provide consent to perform this assessment.


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  		Table 1. Mean Scores on the Neuropsychiatric Inventory (NPI), Severe Impairment Battery (SIB), London Psychogeriatric Rating Scale (LPRS), Global Deterioration Scale (GDS), and Their Subscales.

 
Although there was no difference in energy consumption between meals (p =.651), breakfast intake was consistently lower in protein and fat and higher in CHO content, expressed both as absolute intake and as a percentage of energy consumed, relative to lunch and dinner (all p <.01; Table 2), which did not differ from one another. Breakfast was also the least variable meal; based on each resident's meal-related coefficient of variation (CV). Breakfast CVs were lower, relative to those of lunch and dinner, which did not differ from one another in total energy, CHO, and protein (all p <.04). CVs for fat approached significance for absolute intake (p =.078), but did not differ (p =.763) when data were expressed as a percentage of energy consumed (data not shown).


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  		Table 2. Habitual Energy and Macronutrient Intake of Institutionalized Seniors With Alzheimer's Disease.

 
Associations Between Nutrient Intake and Behavioral and Cognitive Assessments
Using all 12 subscales of the NPI, factor analysis identified three factors accounting for 60.9% of the total variance. The first factor (Table 3) represented "psychomotor regulation" (23) with high factor loadings on agitation, disinhibition, and irritability; the second factor represented "activity disturbance" with high factor loadings on apathy, aberrant motor activity, and nighttime disturbances; and the third factor represented "mood," with high factor loadings on depression/dysphoria and anxiety. Only one factor could be interpreted when factor analyses were done on the SIB and LPRS subscales.


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  		Table 3. Factor Analysis of the 12 Neuropsychiatric Inventory-Nursing Home Version Subscales.

 
To determine the associations between the resident assessments and food intake patterns, several multiple regression approaches were taken. The first approach examined total scores for the NPI, SIB, and LPRS measures. For LPRS and SIB, because only one factor could be interpreted when examining individual subscales, these subscales were subsequently entered into separate multiple regression models to examine the contribution of each subscale. By contrast, factor scores were examined first for the NPI scores. When factors were significantly associated with intake measures, the dominant subscales within the factor (i.e., factor loadings ≥0.60) were further investigated in a model that included that subscale only, but adjusted for the other factors.

Predictors of energy intake.-- Scores on both the LPRS and NPI, but not the SIB, were predictive of intake patterns at the 24-hour level (Table 4). Individuals with greater levels of disengagement, as measured by the LPRS, showed lower overall energy intakes, both when intake from supplements was and was not included in the analyses. Comparable to our previous studies (8), resident assessments were not associated with energy intake achieved at breakfast, with the exception that individuals with greater visuospatial ability consumed lower energy intakes, but this was only apparent when supplement intake was not accounted for. In general, LPRS scores continued to show the most consistent associations with lunch and dinner energy intakes, with those with greater levels of disability demonstrating lower intakes. Since greater disability on all LPRS subscales were associated with lower food intake, this relationship represents functional decline across all measures captured by the LPRS. This was a generalizable impact with disability on all subscales contributing. By contrast, the associations between declining cognitive and behavioral measures were more dominant at dinner in comparison with lunch, with greater levels of cognitive decline and behavioral disturbances, especially disinhibition, being associated with poorer dinner energy intakes.


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  		Table 4. Relationship Between Neuropsychiatric Inventory (NPI), Severe Impairment Battery (SIB), London Psychogeriatric Rating Scale (LPRS) Scores, and Energy and Macronutrient Intakes*.

 
Predictors of macronutrient intake.-- The most consistent associations when examining macronutrient intake either at individual meals or as a 24-hour total related to the socially irritating behavior subscale of the LPRS and the NPI factor 1 "psychomotor regulation." For both these parameters, greater levels of behavioral deterioration were associated with higher CHO and lower protein intakes, expressed as a percentage of calories consumed. Analyses of the intake data as a percentage of calories consumed remove a potential confounder associated with lower overall intakes in some residents. All dominant subscales (agitation, irritability, and disinhibition) loading with the "psychomotor regulation" factor showed strong associations with protein and CHO selection, suggesting that no one factor was playing an overriding role in driving the associations. Notably absent are associations between NPI factor 3 "mood" encompassing anxiety and depression.

Role of medications.-- To globally assess the role of medications, they were classified as anorectic (sertraline, venlafaxine, citalopram, donepezil rivastigmine, levodopa, pramipexole, cyproterone, amiodarone, quinidine sulfate), orexigenic (amitriptyline, olanzapine, risperidone, seroquel prednisone, medroxyprogesterone), or neutral according to published side effects of each drug used by our study population. Residents receiving anorectic medications had similar 24-hour intakes (1653 ± 276 kcal/d) relative to those who did not receive them (1514 ± 223 kcal/d; p =.145). Because individuals receiving these drugs were more cognitively intact and had fewer behavioral problems relative to those not using them (all p <.05), the cognitive and behavioral measures were included in the analyses to determine if the medications were masking underlying differences. No differences between groups, on the basis of medication use, was observed using this strategy.

Similarly, residents receiving orexigenic medications did not have greater 24-hour energy intakes (1572 ± 333 kcal/d) relative to those who did not receive them (1586 ± 171 kcal/d; p =.489). Irrespective of their degree of cognitive or behavioral deterioration, those residents receiving these medications, however, selected more energy as CHO (p =.027) and less as fat (p =.015) at breakfast and more energy as protein (p =.031) at dinner relative to those not using these medications.


   DISCUSSION
Top
 Abstract
 Methods
 Results
 Discussion
References
 
This study continues to demonstrate shifts in circadian patterns of intake in institutionalized seniors with AD (8), with lower food intakes consistently observed at lunch and dinner, but not breakfast, in individuals with higher levels of functional disability, particularly disengagement. Although disengagement was predictive of lower total food intake, increased "psychomotor regulation" disturbances, including irritability, agitation, and disinhibition, were primarily associated with higher CHO and lower protein selection. Notably, neuropsychiatric, and not cognitive, measures were stronger predictors of shifts in macronutrient selection, especially when intake from oral nutritional supplements was eliminated from the analyses. This association between "psychomotor regulation" and shifts toward CHO selection was observed at both breakfast and dinner—meals differing markedly in their CHO and protein content (9)—suggesting that the associations observed were not simply a reflection of foods offered at individual meals. These data strongly implicate the emergence of neuropsychiatric disturbances—especially irritability, agitation, and disinhibition—as being temporally associated with altered food selection profiles towards CHO and away from protein-containing foods.

Because low protein intakes can be of clinical concern, particularly in more progressed patients at greater risk for low overall intakes (8), the question becomes how to sustain protein status as the individual shifts to CHO consumption. The use of sweet, protein-dense foods, such as ice creams and puddings, especially in those displaying "psychomotor regulation" disturbances, may be of value, particularly at dinner when the drive toward high CHO foods is most evident.

It is interesting that the presence of mood disorders, including anxiety and depression, did not predict either total food intake or macronutrient selection. Thus, although others have argued that depression is a strong predictor of malnutrition risk in seniors (25–27), the adverse effects of depression may be more dominant in individuals with little to no cognitive decline. Rather, increased disengagement, as measured by the LPRS, is associated with lower food intake. In this study sample, greater NPI measures of apathy (p =.047), not depression (p =.735), correlated with disengagement, and although apathy in and of itself did not predict energy intake, its potential contribution should not be discounted. Alternatively, depression, as assessed by the NPI, may not have provided a sensitive enough measure to demonstrate this association, especially given limitations to sample size.

Although not specifically addressed, the temporal associations between neuropsychiatric symptoms and shifts in macronutrient intake are indicative of impairments to serotonergic neurotransmission, because altered serotonin signaling has been implicated in both behavioral dysfunction in AD (28) and control of feeding (29,30), specifically of CHO consumption. Whether use of serotonergic medications, for treatment of underlying behavioral difficulties, has subsequent impact on food selection patterns is unexplored. Conversely, the strong associations between disinhibition and increased CHO consumption could simply indicate that cognitive controls normally observed in the control of eating patterns (31) are no longer evident and that inherent preferences for sweet foods are being expressed or that the agitated individual is seeking ‘comfort’ foods as a form of self-medication.

Importantly, while not specifically exploring the role of individual drugs, we were unable to provide evidence that either the anorectic or orexigenic medications, as a whole, were strong predictors of total energy intake in this patient population. Because most residents did not undergo changes to their habitual medications during the course of the study, it is unknown whether initiation of medications had transitory affects on food intake or if this study simply lacked the power to observe such effects. Nevertheless, these data do not support an argument that energy intakes are systematically different in residents receiving drugs associated with anorexic or orexigenic properties.

Summary
The presence of neuropsychiatric symptoms, including irritability, agitation, and disinhibition, were strongly associated with shifts in eating patterns toward CHO and away from protein, placing individuals with these conditions at increased risk for inadequate protein intakes. The data both highlight the need to monitor protein status in individuals with these conditions and suggest that altering dinner food choices to provide protein-containing foods in more acceptable forms may assist this group to meet their protein needs (14).


   Acknowledgments
 
Research supported by a grant from the Canadian Institutes of Health Research (CIHR). Karen W. H. Young was the recipient of a K.M. Hunter/CIHR Doctoral Research Award and an Ontario Graduate Scholarship in Science and Technology.

This work was presented at the Second International Academy of Nutrition and Aging Congress, Albuquerque, New Mexico, July 2003.


   Footnotes
 
Decision Editor: John E. Morley, MB, BCh

Received September 13, 2003

Accepted December 3, 2003


   References
Top
 Abstract
 Methods
 Results
 Discussion
 References
 

  1. White H, Peiper C, Schmader K. The association of weight change in Alzheimer's disease with severity of disease and mortality: a longitudinal analysis. J Am Geriatr Assoc. 1998;46:1223-1227.[Medline]
  2. Cronin-Stubbs D, Beckett LA, Scherr PA, et al. Weight loss in people with Alzheimer's disease: a prospective population based analysis. BMJ. 1997;314:178-179.[Free Full Text]
  3. Burns A, Marsh A, Bender DA. Dietary intake and clinical, anthropometric and biochemical indices of malnutrition in elderly demented patients and non-demented subjects. Psychol Med. 1989;19:383-391.[Medline]
  4. Kerstetter J, Holthausen BA, Fitz PA. Malnutrition in the institutionalized older adult. J Am Diet Assoc. 1992;92:1109-1116.[Medline]
  5. Lipschitz D. Malnutrition in the elderly. Sem Dermatol. 1991;10:273-281.
  6. Silver A, Morley J, Strome L, Jones D, Vickers L. Nutritional status in an academic nursing home. J Am Geriatr Soc. 1988;36:487-491.[Medline]
  7. Keller H. Malnutrition in institutionalized elderly: how and why? J Am Geriatr Soc. 1993;41:1212-1218.[Medline]
  8. Young KWH, Greenwood CE. Shift in diurnal feeding patterns in nursing home residents with Alzheimer disease. J Gerontol Ser A Biol Sci Med Sci. 2001;56:M700-M706.
  9. Young KWH, Binns MA, Greenwood CE. Meal delivery practices do not meet needs of Alzheimer patients with increased cognitive and behavioral difficulties in a long-term care facility. J Gerontol Series A Biol Sci Med Sci. 2001;56:M656-M661.
  10. Keene J, Hope T. Hyperphagia in dementia. 2. Food choices and their macronutrient contents in hyperphagia, dementia and ageing. Appetite. 1997;28:167-175.[Medline]
  11. Mungas D, Cooper JK, Weiler PG, Gietzen D, Franzi C, Bernick C. Dietary preference for sweet foods in patients with dementia. J Am Geriatr Soc. 1990;38:999-1007.[Medline]
  12. Keene J, Hope T. Hyperphagia in dementia. 2. Food choices and their macronutrient contents in hyperphagia, dementia and ageing. Appetite. 1997;28:167-175.
  13. Young KWH, Greenwood CE, van Reekum R, Binns MA. Providing nutrition supplements to institutionalized seniors with probable Alzheimer's disease is least beneficial to those with low body weight status. J Am Geriatr Soc. 2004;52:1305-1312.[Medline]
  14. Young KWH, Greenwood CE, van Reekum R, Binns MA. A randomized crossover trial of high carbohydrate foods in nursing home residents with Alzheimer's disease: greater cognitive and behavioral problems predict a greater increase in food intake compared with those with fewer difficulties. J Gerontol Biol Sci Med Sci. In press.
  15. Department of National Health and Welfare. Canadian Nutrient File. Ottawa, Ontario, Canada: Health Services and Promotion Branch and Health Protection Branch; 1991.
  16. Reisberg B, Ferris S, de Leon MJ, Crook T. The Global Deterioration Scale for the assessment of primary degenerative dementia. Am J Psychiatry. 1982;139:1136-1139.[Abstract/Free Full Text]
  17. Panisset M, Roudier M, Saxton J, Boller F. Severe impairment battery. A neuropsychological test for severely demented patients. Arch Neurol. 1994;51:41-45.[Abstract/Free Full Text]
  18. Wood S, Cummings JL, Hsu MA, et al. The use of the neuropsychiatric inventory in nursing home residents. Characterization and measurement. Am J Geriatr Psychiatry. 2000;8:75-83.[Medline]
  19. Reid D, Tierney M, Zorzitto M, Snow G, Fisher R. On the clinical value of the London Psychogeriatric Rating Scale. J Am Geriatr Soc. 1991;39:368-371.[Medline]
  20. Basiotis P, Welsh S, Cronin F, Kelsay J, Mertz W. Number of days of food intake records required to estimate individual and group nutrients with defined confidence. J Nutr. 1987;117:1638-1641.
  21. Norman GR, Streiner DL. Principal components and factor analysis. In: Biostatistics: The Bare Essentials. St. Louis, MO: Mosby-Year Book; 1994:129–141.
  22. Frisoni GB, Rozzini L, Gozzetti A, et al. Behavioral syndromes in Alzheimer's disease: description and correlates. Dement Geriatr Cogn Disord. 1999;10:130-138.[Medline]
  23. Fuh JL, Liu CK, Mega MS, Wang SJ, Cummings JL. Behavioral disorders and caregivers' reaction in Taiwanese patients with Alzheimer's disease. Int Psychogeriatrics. 2001;13:121-128.
  24. Norman GR, Streiner DL. Multiple regression. In: Biostatistics: The Bare Essentials. St. Louis, MO: Mosby-Year Book; 1994:108–117.
  25. Cullen P, Abid F, Patel A, Coope B, Ballard CG. Eating disorders in dementia. Int J Geriatr Psychiatry. 1997;12:559-562.[Medline]
  26. Marcus EL, Berry EM. Refusal to eat in the elderly. Nutr Rev. 1998;56:163-171.[Medline]
  27. Morley JE. Anorexia of aging: physiologic and pathologic. Am J Clin Nutr. 1997;66:760-773.[Abstract/Free Full Text]
  28. Lai MK, Tsang SW, Francis PT, et al. Reduced serotonin 5-HT1A receptor binding in the temporal cortex correlates with aggressive behavior in Alzheimer disease. Brain Res. 2003;974:82-87.[Medline]
  29. Leibowitz SF, Alexander JT. Hypothalamic serotonin in control of eating behavior, meal size, and body weight. Biol Psychiatry. 1998;44:851-864.[Medline]
  30. Wurtman RJ, Wurtman JJ. Brain serotonin, carbohydrate-craving, obesity and depression. Adv Exp Med Biol. 1996;398:35-41.[Medline]
  31. Rogers PJ. Eating habits and appetite control: a psychobiological perspective. Proc Nutr Soc. 1999;58:59-67.[Medline]



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K. W. H. Young, C. E. Greenwood, R. van Reekum, and M. A. Binns
A Randomized, Crossover Trial of High-Carbohydrate Foods in Nursing Home Residents With Alzheimer's Disease: Associations Among Intervention Response, Body Mass Index, and Behavioral and Cognitive Function
J. Gerontol. A Biol. Sci. Med. Sci., August 1, 2005; 60(8): 1039 - 1045.
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