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The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 56:M700-M706 (2001)
© 2001 The Gerontological Society of America

Shift in Diurnal Feeding Patterns in Nursing Home Residents With Alzheimer's Disease

Karen W.H. Younga and Carol E. Greenwooda

a Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Ontario, Canada, and Kunin-Lunenfeld Applied Research Unit and Department of Food and Nutrition Services, Baycrest Centre for Geriatric Care, Toronto, Ontario, Canada

Karen W.H. Young, Department of Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada M5S 3E2 E-mail: karen.young{at}utoronto.ca.

Decision Editor: John E. Morley, MB, BCh


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 References
 
Background. Individuals with Alzheimer's disease (AD) are highly susceptible to weight loss and malnutrition, which, to date, have not been associated with decreased food consumption. The current study examined food intake patterns and how they change in relation to body mass index (BMI), behavioral function, and cognitive status in institutionalized seniors with AD.

Methods. Twenty-one consecutive days of investigator-weighed food intake collections were conducted on 25 subjects with likely AD residing at a home for the aged. All subjects maintained the ability to self-feed.

Results. Eighty-eight percent of participants did not meet targeted energy needs, including an estimated 37% prevalence of protein inadequacy. Subjects with increased behavioral difficulties, based on the London Psychogeriatric Rating Scale, had reduced meal-related intakes that were highly associated with decreased energy consumption at dinner. With behavioral changes, particularly increased mental disorganization and confusion, there was a shift in circadian eating patterns such that the greatest proportion of daily energy was consumed at breakfast. Individuals with low BMIs tended to be those with more behavioral difficulties, such that BMI was also associated with the shift in overall eating patterns.

Conclusions. Changes in behavioral function in seniors with AD result in a circadian shift in intake patterns with the preponderance of calories consumed at breakfast in those with increased behavioral difficulties. This shift in eating patterns associates both with poor overall intake and poor BMI.

ELIMINATING weight loss and malnutrition is a priority because of their association with an increased risk of morbidity (1), mortality (2)(3), and greater rates of disease progression in seniors with Alzheimer's disease (AD; 3). Although weight loss in AD is well documented (4)(5)(6)(7)(8)(9)(10) and considered a clinical feature consistent with this diagnosis (11), its etiology remains elusive. Reports of lower energy intakes in institutionalized AD patients compared to non-AD controls (12) and an association between weight change and decreased independence in self-feeding (8) support the hypothesis that weight loss may be secondary to decreased intakes. However, observations of weight loss in a group of AD outpatients with a concomitant increase in food intake (13), and reports of dietary intakes that were similar (4)(14)(15) and higher (6) in AD patients compared to controls, led others to suggest that weight loss is due to factors beyond reduced food intake.

Perhaps contributing to this ambiguity is the fact that measures of disease progression were not previously considered; rather, the AD population was compared, as a whole, to cognitively intact controls. Yet this clustering of the AD population is inconsistent with a neurodegenerative disease known for progressive behavioral deterioration. Rather, it is likely that intake patterns deteriorate with disease progression and that altered eating patterns are masked if disease status is not considered.

This study examines intake patterns in a group of senior residents in cognitive impairment (CI) units with likely AD, and how these patterns change in relation to measures of behavioral function, cognitive ability, and body weight status. Accurate methods to assess food intake were employed (16) and sufficient numbers of days of intake were examined (17) to capture habitual intake of the individual for the first time in this population.


   Methods
Top
 Abstract
 Methods
Results
 Discussion
 References
 
Subjects
All residents of the CI units of the Jewish Home for the Aged at the Baycrest Centre for Geriatric Care (Toronto, Canada) were considered. By examining medical histories, only residents with likely AD were included. Although AD diagnoses using National Institute of Neurological and Communicative Disorders-Alzheimer's Disease and Related Disorders Association criteria (11) were unavailable, residents were excluded if there was a diagnosis of CI secondary to other causes, such as vascular dementia or other neurodegenerative disorders. Subjects also met the following criteria: (i) maintains the ability to self-feed or requires only minimal assistance (e.g., tray set-up) and (ii) absence of other diseases requiring nutritional intervention (e.g., types 1 or 2 diabetes mellitus). Twenty-five individuals (3 men and 22 women; mean age 85.9 ± 7.6), comprising an ~60% participation rate of eligible subjects, were included. Following protocol approval by the Baycrest ethics committee, informed consent was obtained from the family or legal guardian.

Cognitive and Behavioral Function Assessments
Cognitive status was determined using the Mini-Mental State Examination (MMSE) (18) and behavioral function was assessed by the London Psychogeriatric Rating Scale (LPRS; 19). A higher score on the LPRS indicates greater disability and consists of four subscales: Mental Disorganization/Confusion (MENT), Physical Disability (PD), Socially Irritating Behavior (SIB), and Disengagement (DIS). In anticipation that the MMSE may "bottom-out," the LPRS was included because it was designed to specifically assess usual behavior of geriatric patients (19).

Food Intake Collection
Twenty-one consecutive days of investigator-weighed food intake and delivery were monitored on each subject. The nutrient profile of the meals was determined using Dietary Food Management software, which contains all in-house recipes and calculates the nutrient composition on the basis of individual ingredients using the Canadian Nutrient Database (20). Afternoon snack intake, usually muffins, juices, and nutrient supplements (e.g., Ensure), was estimated visually and standard weights assumed.

Statistics
Meal-related nutrient intakes and delivery, as well as within-individual variability, expressed as standard deviation (SD) and coefficient of variation (CV), were compared using a repeated measures analysis of variance, followed by Tukey's Honestly Significant Difference test, using SAS for Windows (v6.12). Data were examined for normality prior to analyses using the Shapiro-Wilk statistic. Estimation of the prevalence of inadequate protein intakes was performed by probability analysis (21). Regression analyses were used to determine the associations between cognitive status, behavioral function, BMI, mean energy intake of the individual, and mean percentage of contribution of each meal to the total energy intake ([meal kcal/total kcal]*100).


   Results
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 Abstract
 Methods
 Results
Discussion
 References
 
Subject Descriptions
Details of the subjects are contained in Table 1 . In terms of body weight as a risk factor for increased mortality (22), 48% of the subjects (2 males, 10 females) had high-risk BMIs (<22 kg/m2). Although all subjects were able to eat independently, 23 of 25 subjects were severely cognitively impaired, based on the MMSE (score: <=17 (23)). The remaining subjects were mildly impaired (score 18–23).


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  		Table 1. Average Age, BMI, MMSE, LPRS, and LPRS Subscales of Study Population

 
Dietary Intake and Its Variability
Mean 24-hour and meal-related energy and macronutrient intakes are given in Table 2 . All three meals contributed equally to mean 24-hour energy consumed. Because energy delivered was the lowest at breakfast (Table 3 ), on average, subjects consumed the greatest percentage of energy delivered ([consumed/delivered]*100%) at breakfast (p < .05). Energy needs (24), calculated as 1.3*basal metabolic rate, were not met by energy consumed for 88% of the subjects. Although the contributions of protein, fat, and carbohydrate to total energy consumed (14.8 ± 1.9%, 32.4 ± 4.1%, and 54.6 ± 5.7%, respectively) were in line with current recommendations (24), the estimated prevalence of inadequate protein intakes (<0.8 g protein/kg body weight) was 37% of the subjects. The protein density of the diet (14.8% of calories) would be appropriate if adequate levels of energy were consumed; thus the low energy intake was the likely contributor to the high level of protein inadequacy observed.


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  		Table 2. Group Mean and Variability of Energy and Macronutrient Consumption Based on 21-day Estimates for 25 Individuals

 

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  		Table 3. Group Mean Energy Delivered Based on 21-day Means for 25 Individuals

 
Mean protein intake was lowest at breakfast and highest at lunch, while mean fat consumed at breakfast was lower than at lunch and dinner, which were not different from each other. By contrast, mean carbohydrate intake was highest at breakfast, likely reflecting the carbohydrate-dense foods offered. Snacks also provided mostly carbohydrate foods (Table 2 ).

The within-individual variabilities in intake (SD and CV) were lower at breakfast compared to lunch and dinner, which did not differ from one another, for energy or the macronutrients (Table 2 ). This consistency of breakfast intake occurred in tandem with lower variability for energy delivered (Table 3 ).

Snacks
Table 2 shows the mean energy consumed at all snack times for 25 individuals (i.e., all snack times included, even those of 0 kcal), while Table 4 provides snack data that includes only snacks that were consumed. Snacks tended to be "treats," which, if received, were almost always consumed entirely. This "all-or-none" phenomenon contributed to the high within-subject variability in snack intake.


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  		Table 4. Mean Energy and Macronutrient Values of Consumed Snacks (n = 279)

 
Relationship Between BMI, Behavioral Function, and Cognitive Status
When the relationships between current BMI and MMSE, LPRS, and its subscales were investigated, a trend for a negative association between BMI and the MENT subscale was found (p = .061, r2 = .14). All other associations were not significant. Thus, even in this small group of reasonably homogeneous individuals, those with increased mental disorganization/confusion tended to show the poorest body weight status.

The MMSE was correlated with the LPRS (p = .002, r2 = 0.28) and the MENT subscale (p = <.001, r2 = .33). Thus, in-line with the MMSE, the LPRS, particularly the MENT subscale, is likely sensitive to disease progression (25).

Relationship Between Energy Consumed and Behavioral Function
Measures of behavioral dysfunction associated with total intake and demonstrated their strongest relationship with dinner consumption (Fig. 1), such that individuals with greater behavioral difficulties, indicated by higher total LPRS, PD, and SIB scores, consumed less energy at dinner. When expressed as a percentage of total intake ([meal kcal/total kcal]*100), a marked shift in the time of day when individuals were consuming the greatest proportion of their daily energy, depending on the degree of mental disorganization, is evident (Fig. 2). That is, individuals with increased mental disorganization/confusion tended to consume the greatest percentage of the day's total energy at breakfast and the least at dinner. Consistent with this shift in peak consumption times, associations with the LPRS (breakfast: p = .045, r2 = .16; dinner: p = .038, r2 = .17) and SIB (dinner: p = .035, r2 = .18) were also found.



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  		Figure 1. Relationship between 21-day mean energy consumed and measures of behavioral function, which was assessed by the London Psychogeriatric Rating Scale (LPRS), including its subscales (n = 25). A, Dinner vs LPRS: p = .024, r2 = .20. B, Dinner vs Socially Irritating Behavior (SIB) scale: p = .042, r2 = .17. C, Dinner vs Physical Disability (PD) scale: p = .036, r2 = .18. D, 24-hour Total vs PD: p = .039, r2 = .17.

 


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  		Figure 2. Relationship between the percent contribution of each meal to total energy consumption and the Mental Disorganization/Confusion (MENT) subscale of the London Psychogeriatric (LPRS) scale (n = 25). A, Breakfast: p = .049, r2 = .16. B, Lunch: p = .099, r2 = .11. C, Snack: p = .122, r2 = .10. D, Dinner: p = .058, r2 = .15.

 
Relationship Between BMI and Energy Intake
Individuals with poor BMIs had breakfast intakes that were indistinguishable from those with higher BMIs, but showed poor consumption profiles at lunch and dinner (Fig. 3). This resulted in a positive association between BMI and total meal intake (snack not included). By contrast, 24-hour intakes were not related to BMI, in part due to the greater snack consumption of those with low BMIs.



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  		Figure 3. Relationship between body mass index (BMI) and 21-day mean energy consumed (n = 25). A, Breakfast: p = .764, r2 = .004. B, Lunch: p = .017, r2 = .22. C, Dinner: p = .009, r2 = .26. D, Meal Total (B + L + D): p = .026, r2 = .20. E, Snack: p = .013, r2= .24. F, 24-hour Total (B + L + D + S): p = .105, r2 = .11.

 
With decreasing BMI, there is clearly a shift in the contribution of each meal to total intake (Fig. 4). Those with low BMIs consumed a greater percentage of the day's total energy at breakfast and less at lunch and dinner. Compared to those with higher BMIs, subjects with lower BMIs also tended to consume a higher percentage of energy as snacks.



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  		Figure 4. Relationship between the percent contribution of each meal to total energy consumption and body mass index (BMI; n = 25). A, Breakfast: p = .043, r2 = .17. B, Lunch: p = .033, r2 = .18. C, Snack: p = .009, r2 = .26. D, Dinner: p = .018, r2 = .22.

 

   Discussion
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 Abstract
 Methods
 Results
 Discussion
References
 
This study is the first to demonstrate a change in the diurnal eating patterns of patients with AD that associates with measures of behavioral function. Noteworthy is the fact that decreased meal-related intakes in those with increased behavioral dysfunction are associated with lower intakes at dinner, but not breakfast. Thus, with increased behavioral difficulties and disease progression individuals no longer engage in patterns of eating consistent with those who are less impaired. These findings question the validity of attempting to maintain meal-time patterns traditionally provided to cognitively intact individuals for those with increased behavioral difficulties.

In healthy young adults (18–41), there is a tendency for meal sizes to increase over the day with peak intakes at noontime and early evening (26). Thus breakfast contributes proportionately less to daily intake in comparison to lunch and dinner. With AD progression, reversal of this pattern occurs such that those with more behavioral difficulties achieve the lowest intakes at dinner, with breakfast contributing the greatest percentage to total energy intake (Fig. 1 and Fig. 2). These observations are consistent with known disruptions in circadian rhythms in AD (27)(28) and suggest that increased confusion or agitation in the afternoon or early evening, "sundowning" (29), likely contributes to the change in eating patterns. That is, scoring poorly on the MENT subscale, which associates with these disruptions in eating patterns, is a possible proxy indicator for patients exhibiting the sundowning syndrome.

Although the MMSE was not associated with a shift in eating patterns, this is likely due to "bottoming-out" of the scores. Indeed, 48% of the subjects scored 5 or lower. Nevertheless, it is likely that both disease progression and behavioral difficulties are predictive of the changes in eating patterns observed because the MMSE was highly correlated with the LPRS and MENT subscale.

Although these data demonstrate that behavioral function is important, it is unlikely the sole contributor to the eating patterns observed. Hunger and satiety signals are likely disturbed secondary to neuronal degeneration impacting on neurochemical (30)(31) and anatomical (32) pathways involved in food intake regulation, which may involve cell loss in the paraventricular nuclei (33). Thus, diminished hunger signals may not be sufficient to drive individuals to increase their breakfast intake to compensate for reduced dinner intake. Indeed, if this were the case, greater breakfast intakes would have been observed in those with increased behavioral difficulties. Additionally, this study did not account for the myriad of other factors reported to contribute to poor consumption in institutionalized seniors (reviewed in (34),(35)), including the possibility that decreased light exposure may exacerbate circadian rhythm disturbances (36). All may contribute.

Not only was energy consumed at breakfast similar among the participants based on BMI and behavioral function, it was also the most consistently consumed meal based on measures of within-individual variability of intake (Table 2 ). This supports our previous finding (37) that breakfast consumption is most consistent in a more impaired group of individuals, while others observed that refusal of foods occurs least often at breakfast in demented females (38). Interestingly, measures of within-individual variability in delivery and consumption parallel one another, such that both are lowest at breakfast, which suggests that food delivery practices may impact consumption patterns. An exploration of the impact of energy delivery on consumption is reported elsewhere (39).

Previous studies were unable to attribute weight loss and/or poor body weight status to lower food intake in the AD population. However, many of these studies were underpowered to demonstrate these relationships in terms of number of individuals studied and/or number of days of intake data collected. By overcoming these design issues, the current data demonstrate that individuals with low BMIs do have reduced meal-related intakes (Fig. 3). Although cross-sectional in nature, these data cannot prove that prior reductions in food intake contributed to poor body weight status; however, they are consistent with this hypothesis. Indeed, 88% of the subjects were not meeting basic energy needs. Were it not for the aggressive provision of snacks (usually nutritional supplements in those with low BMIs; Fig. 3), it is likely that further weight loss would have occurred.

The group mean energy intake, 1247 kcal/day, is less than that reported elsewhere (ranging from 1532 to 1894 kcal [4,6,12,38]). Whether this reflects inherent differences in clinical care or attributes of the specific study population is unknown. However, the current subjects comprised a more homogeneous group than those of previous investigations. Importantly, all participants maintained the ability to feed themselves. Thus, free-feeding patterns, not contaminated by different feeding assistants, were monitored. This selection criterion may have, in part, contributed to the lower overall intakes. We (40) and others (4) previously reported that residents not receiving feeding assistance have lower intakes than those receiving full feeding assistance.

Lower energy intakes may also have occurred because of the comparatively lower dietary fat content. Others reported that fat contributed 41.4% to total energy intake (38), while this group consumed 32.4% of energy from fat. A diet with a higher fat content may help increase overall energy intake. However, this strategy would not help overcome the high prevalence of protein inadequacy (estimated at 37%).

Higher PD was also associated with poor intake, especially at dinner, indicating that some participants may have required increased assistance. All participants were assessed by the clinical staff as requiring no, or only minimal, feeding assistance. The current results question the validity of these assessments, but also suggest that feeding assistance requirements change throughout the day. That is, in our facility, feeding assistance needs are usually assessed at lunch and the fact that measures of PD did not associate with lunch intake indicates that these assessments were appropriate for that meal. Nevertheless, the negative association between PD and dinner intake suggests that although these subjects were able to consume their lunch independently, this was no longer the case at dinner. Although more difficult to implement due to staffing profiles, our data suggest that these assessments are best made during the evening meal and that assistance needs may change throughout the day.

In summary, this study provides the most extensive measures of food intake in a population of institutionalized seniors with AD to date. Collectively, these data suggest that poor food intake, which associates with increased behavioral difficulties, possibly related to sundowning, likely contributes to poor BMI. Consistent with a disturbance in circadian rhythms, peak food consumption levels shift from evening to morning in those with decreased behavioral function. Importantly, this suggests that with behavioral changes and AD progression the provision of high energy, nutrient-dense afternoon and evening meals is unlikely to meet the nutritional needs of this population and that consideration must also be given to changes in meal-time assistance needs throughout the day.


   Acknowledgments
 
Research supported by a grant from the Program in Food Safety and the Canadian Institutes of Health Research (CIHR). K. Young was the recipient of a University of Toronto Open Fellowship, an Ontario Graduate Scholarship in Science and Technology, and a K.M. Hunter/CIHR Doctoral Research Award. The authors thank Drs. Rob van Reekum and Morris Freedman for their editorial advice.

Received October 25, 2000

Accepted October 27, 2000


   References
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 Methods
 Results
 Discussion
 References
 

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