Is Weight Loss More Severe in Older People with Dementia?

Abstract

Weight loss, a hallmark feature of dementia, is associated with higher mortality in older people. However, there is a lack of consensus in the literature as to whether the weight loss commonly observed in older people with dementia results from reduced energy intake and/or increased energy expenditure. Understanding the cause of energy imbalance in older people with dementia would allow more targeted interventions to avoid detrimental health effects in this vulnerable group. In this paper, we review studies that have considered weight change, energy intake, and energy expenditure in older people with and without dementia. We critically assess the studies’ methodology and outline the various factors which may decrease and increase energy intake and expenditure respectively in older people with and without dementia. Current available literature does not support the view that there is a lower energy intake and/or a higher energy expenditure in older people with dementia when compared to those without dementia. The need for more high-quality studies is also highlighted in order to shed more light towards this issue which continues to elude researchers and clinicians alike.

Keywords

Aged dementia energy intake energy metabolism weight loss

INTRODUCTION

A decline in memory and decreasing cognition are features of normal aging [1]. However, in dementia these abilities decline more dramatically and to a greater degree. According to the World Health Org-anization, dementia is a cognitive impairment syndrome affecting an individual’s memory as well as cognitive abilities that significantly hinders the ability of the individual to carry out their regular tasks [2]. There are many forms of dementia; the most common being Alzheimer’s disease (AD), vascular dementia, and dementia with Lewy bodies [3].

Many studies have shown that weight loss is a key feature of dementia [4 –8]. Weight loss may precede the onset of cognitive signs of dementia and becomes more common as the condition progresses [9]. A large multinational study found a strong association between the severity of dementia and the incidence of reported weight loss [10]. These findings are useful to inform the management of the illness, since weight loss and malnutrition have been strongly associated with mortality in this population [11 –13].

The exact mechanism contributing to the widesp-read prevalence of weight loss and malnutrition in older people with dementia remains unknown. Some authors have proposed that the cause relates to inadequate energy intake [14, 15] while others have sug-gested that the cause may be related to increases in energy expenditure [16, 17] which tip energy equilibrium toward weight loss. This review aims to synthe-size and critically assess studies that have considered weight change, energy intake, and energy expenditure in older people with and without dementia. An increased understanding of the reason(s) behind the prevalent weight loss will assist in developing the most appropriate interventions to achieve better health outcomes for this population.

A database search was performed using the bib-liographic databases PubMed and Cochrane library. Original research articles reporting on energy intake, resting energy expenditure (REE) and total energy expenditure (TEE) of older people with dementia were retrieved from database inception to August 2020 with no language exclusion. The search strategy was a combination of MeSH terms and text-based terms: ((dementia[MeSH Terms]) OR (Alzheimer di-sease[MeSH Terms]) OR (cognitive dysfunction[MeSH Terms])) AND ((energy intake^*[Title/Abstract]) OR (food intake^*[Title/Abstract]) OR (dietary in-take^*[Title/Abstract]) OR (calori^* intake^*[Title/Ab-stract]) OR (nutrient intake^*[Title/Abstract]) OR (energy expend^*[Title/Abstract]) OR (REE[Title/Abstract]) OR (TEE[Title/Abstract]) OR (DEE[Title/Abstract]) OR (TDEE[Title/Abstract]))

Studies were considered eligible if they were available in full-text and the mean age of participants was 65 years and above. This chronological age for older people was chosen as it coincides with the definition of old-age dependency ratio set at 65 years old by the United Nations [18]. Studies which did not specify the participants’ age were excluded.

ENERGY INTAKE IN OLDER PEOPLE LIVING WITH DEMENTIA VERSUS NON-DEMENTIA CONTROLS

Methods of dietary intake collection

The selection of methodology for dietary assessment of older people with dementia often present unique challenges. The impairment in memory and ability to recall invalidates the use of retrospective methods (such as 24 h dietary recall and food frequ-ency questionnaire) unless an appropriate surrogate is present [19]. The presence of cognitive decline, especially in severe cases of dementia, may also render prospective dietary assessment methods (such as food record and food diary) inaccurate due to the inability of older people with dementia to record food intake. Therefore, an appropriate surrogate is often necessary when studying the dietary intake of people with dementia. The use of a surrogate also presents problems as the surrogate may not be with the study participants at all times, may not know the exact composition of composite dishes (if food is prepared by others) and there may be multiple individuals involved in the care of the subject [20]. Additionally, surrogate reporters may also be subjected to incre-ased carer burden from having the additional task of reporting the participants’ food intake. This may create a reactivity bias where surrogates alter the dietary behaviors of the people under their care for ease of recording [19]. Therefore, it is important to recognize that dietary assessment per se is difficult in older people and that this difficulty is compounded in older people living with dementia due to cognitive decline affecting the accuracy and ability to recognize and estimate food intake as well as the complexity of invo-lving surrogate reporters.

Table 1 summarizes 24 studies involving more than 3,200 participants that investigated energy in-take in older people with dementia compared with non-dementia controls in both non-free living and free-living conditions [7 , 21–43]. Most of these stu-dies employed prospective dietary assessment methods, except for three studies [24 , 41] which used retrospective dietary assessment methods. One study [42] did not state the dietary assessment method at all. The three-day food record/diary (consisting of two-day weekdays and one-day weekend) dietary ass-essment method used by most studies is considered more representative and accurate than single observation 24 h recalls, especially for use in older people with cognitive decline [44 –46]. However, as with all dietary assessment methods, the three-day food re-cord is still prone to underreporting due to many factors including mis-quantifying of amount of food consumed [45 , 47–52]. The three-day plate waste method and three-day weighed food record methods used by some of the studies [7 , 38] mitigate the issue of mis-quantifying food as everything is weighed. However, these methods impose a high burden on the caregivers or participants and therefore may not always be feasible in free-living individuals.

Table 1

Studies investigating differences between energy intake in older people with dementia compared to non-dementia controls

References	Non-free living/free living	Characteristics of subjects with dementia	Dementia sub-types	Methods of dementia classification & severity of dementia	Characteristics of control subjects	Energy intake (kcal/day) (mean±SD)	Dietary assessment method
Thomas et al., 1986 [21]	Non-free living	n = 23 (9 m, 14 f)	NR	NR	n = 23 (9 m, 14 f)	(mean±standard error)	3-day weighed
		Male age: 75.0			Male age: 75.1	with dementia: Male: 1600±52^*,	food record
		(66.0 –83.0) y			(69.0 –82.0) y	female: 1500±78
		Female age: 78.6			Female age: 76.8	without dementia: Male: 2100±160^*,
		(68.0 –85.0) y			(67.0 –85.0) y	female: 1800±140
Litchford & Wakefield, 1987 [22]	Non-free living	n = 15 (3 m, 12 f)	AD	NR	n = 13 (3 m, 10 f)	with dementia: 1532±324^*	3-day plate
		Age: 75 –95 y			Age: 75 –95 y	without dementia: 2034±307^*	waste study
Burns et al., 1989 [23]	Non-free living &	Non-free living: n = 21	MID, SD	MMSE; mild-	n = 29 (10 m, 19 f)	with dementia (non-free living):	3-day weighed
	free-living -	(5 m, 16 f) age: 81.1±5.7 y		severe dementia	Age: 80.3±6.2 y	1800±385^* with dementia	food record
	dementia group	Free-living: n = 28				(free-living): 1780±240^*
	Free living – control	(5 m, 23 f) age: 80.1±7.3 y				without dementia: 1470±132^*
O’Neill et al., 1990 [24]	Free living	n = 9 (NR)	AD	MMSE; mild -	n = 9 (NR)	(mean±standard error)	7-day diet history
		Age: 73±5.1 y		severe dementia	Age: 75±4.7 y	with dementia: 2079±96
						without dementia: 2173±120
Winograd et al., 1991 [25]	Free living	n = 35 (23 m, 12 f)	AD	MMSE, GDS;	n = 29 (24 m, 5 f)	with dementia: Male: 2012±489,	3-day food record
		Male age: 68±8 y		moderate dementia	Male age: 67±7 y	female: 1899±482
		Female age: 66±7 y			Female age: 74±6 y	without dementia: Male: 2206±562,
						female: 1848±188
Niskanen et al., 1993 [26]	Non-free living	n = 20 (all f)	AD, MID	MMSE; moderate -	n = 10 (all f)	with AD: 1709±117	3-day weighed
	Free living - control	Age: 64 –90 y (for AD),		severe dementia	Age: 75 y	with MID: 1581±170	food record
		77 –91 y (for MID)				without dementia: 1684±347
Donaldson et al., 1996 [27]	Free living	n = 25 (8 m, 17 f)	AD	MMSE; mild -	n = 73 (23 m, 50 f)	with dementia:1794±443	3-day food record
		Age: 74±8 y		severe dementia	Age: 69±7 y	without dementia:1787±427
Franzoni et al., 1996 [28]	Non-free living	n = 33 (3 m, 30 f)	NR	MMSE; moderate -	n = 25 (3 m, 22 f)	(kcal/kg body weight)	3-day weighed
		Age: 85.7±5.7 y		severe dementia	Age: 84.9±5.7 y	with dementia: 28.2±7.9	food record
						without dementia: 28.0±7.9
Spindler et al., 1996 [29]	Non-free living	n = 17 (6 m, 11 f)	AD	NR	n = 23 (9 m, 14 f)	(kcal/kg body weight)	Dementia group: 2-day
	Free-living - control	Male age: 76.6±7.6 y	Male age: 72.9±5.9 y	with dementia: 34^*	weighed food record
		Female age: 80.6±6.2 y			Female age: 71.9±7.2 y	without dementia: 24^*	Non-dementia group:
							4-day food record
Poehlman et al., 1997 [30]	Free living	n = 30 (13 m, 17 f)	AD	MMSE; mild -	n = 103 (51 m, 52 f)	with dementia: 1799±403	3-day food record
		AD: 73±8 y		severe dementia	Age: 69±7 y	without dementia: 1878±519
Dvorak & Poehlman, 1998 [31]	Free living	n = 30 (13 m, 17 f)	AD	MMSE; mild -	n = 30 (13 m, 17 f)	with dementia: 1799±403	3-day food record
		Age: 74±8 y		severe dementia	Age: 73±7 y	without dementia: 1812±370
Wang et al., 2004 [7]	Free living	n = 51 (29 m, 22 f)	AD	MMSE, CDR; mild-	n = 27 (15 m, 12 f)	(kcal/kg body weight)	3-day weighed
		Age: 76.2±7.4 y		moderate dementia	Age: 71.2±6.7 y	with dementia: 38.0±11.1^*	food record
						without dementia: 31.5±7.9^*
Kwan et al., 2005 [32]	Free living	n = 45 (10 m, 35 f)	AD	MMSE, FAS;	n = 36 (16 m, 20 f)	with dementia: 1566±471^*	3-day food record
		Age: 76.8±6.8 y		mild - severe dementia	Age: 72.9±6.4 y	without dementia: 1490±416^*
Tabet et al., 2005 [33]	Free living	n = 26 (15 m, 11 f)	NR	MMSE; mild	n = 26 (11 m, 15 f)	with dementia: 1636±300	3-day food record
		Age: 77 (75 –80) y		dementia	Age: 74 (72 –76) y	without dementia: 1629±153
Shatenstein et al., 2007 [34]	Free living	n = 36 (14 m, 22 f)	AD	MMSE, GDS; mild cognitive	n = 58 (13 m, 45 f)	with dementia: 1527±364^*	2-day food record or
		Age: 77.8±4.6 y		impairment - mild dementia	Age: 73.7±5.5 y	without dementia: 1781±419^*	24 h diet recall
Presse et al., 2008 [35]	Free living	n = 31 (11 m, 20 f)	AD	MMSE; very mild –mild	n = 31 (11 m, 20 f)	with dementia: 1543±395^*	2-day food record
		Age: 77.5±4.9 y		dementia	Age: 77.5±4.9 y	without dementia: 1836±394^*
Jesus et al., 2012 [36]	Non-free living	n = 223 (NR)	NR	MMSE; moderate -	n = 111 (NR)	(kcal/kg body weight)	3-day food record
		Age: 88.0±6.6 y		severe dementia	Age: 87.7±7.4 y	with dementia: 27.1±8.7
						without dementia: 25.0±8.9
Sadamori et al., 2012 [37]	Non-free living	n = 20 (all f)	NR	N geriatric rating scale	n = 11 (all f)	with dementia: 1535±157	Nursing home food
		Age: 87.0±6.3 y		for mental states;	Age: 87.8±3.4 y	without dementia: 1436±262	record chart
				moderate ∼dementia
Galesi et al., 2013 [38]	Non-free living	n = 72 (17 m, 46 f)	NR	MMSE; moderate	n = 78 (46 m, 32 f)	(median (interquartile range))	3-day weighed
		Age: 77.0±10.0 y		dementia	Age: 77.0±10.0 y	with dementia: Male: 1742 (393),	food record
						female: 1716 (628)
						without dementia: Male: 1792 (667),
						female: 1707 (529)
Ahmed et al., 2014 [39]	Free living	n = 75 (54 m, 21 f)	SD, AD	CDR; questionable	n = 18 (9 m, 9 f)	SD group has higher	Dietary Questionnaire
		Age: SD - 66±6.1 y		dementia - moderate	Age: 70±5.1 y	energy intake compared	for Epidemiological
		AD –67±7.2 y		cognitive impairment	to AD and control	Study (Food Frequency Questionnaire)
Puranen et al., 2014 [40]	Free living	n = 99 (68 m, 31 f)	AD	MMSE; mild -	n = 99 (31 m, 68 f)	with dementia: Male: 1897±416^*,	3-day food record
		Male age: 77.8±5.3 y		moderate dementia	Male age: 77.4±7.1 y	female: 1313±340^*
		Female age: 76.5±6.1 y			Female age: 74.2±6.7 y	without dementia: Male: 1605±458^*,
						female: 1536±402^*
Kim et al., 2016 [41]	Free living	n = 105 (41 m, 64 f)	NR	MMSE, mild -	n = 304 (91 m, 213 f)	with dementia: 1494±43	24 h food record
		Age: 75.3±0.6 y		moderate dementia	Age: 72.5±0.4 y	without dementia: 1542±32
Venturelli et al., 2016 [42]	Non-free living	n = 85 (27 m, 58 f)	AD	MMSE, CDR; mild - severe	n = 86 (23 m, 63 f)	with dementia: 1804±159	NR
		Age: 76±4 y		cognitive impairment	Age: 78±5 y	without dementia: 1804±157
Batchelor-Murphy et al., 2019 [43]	Non-free living	n = 592 (NR)	NR	NR	n = 194 (NR)	with dementia: 1305±348	% of consumed meals
		Age: 65 and older			Age: 65 and older	without dementia: 1315±326	from food record chart

^*Statistically significant (p < 0.05); m, male; f, female; y, years; NR, not recorded; AD, Alzheimer’s disease; MID, multi-infarct dementia; SD, semantic dementia; VaD, vascular dementia; MMSE, Mini-Mental State Examination; GDS, Global Deterioration Scale; FAS, Functional Assessment Staging; CDR, Clinical Dementia Rating.

The use of new technologies to assist in the re-cording of intake events may improve accuracy and alleviate the participants’ burden in order to increase the quality of the data on food intake. Newer technologies utilizing computerized assessment coupled with image-assisted or image-based technology such as handheld devices, wearable video camera to augment established techniques have been well-validated against food diary and weighed food record among the older people [53 –56]. The Novel Assessment of Nutrition and Aging (NANA) is one such tool which eliminates the limitation of retrospective assessment methods as dietary information as well as photographs of the food and drink are recorded as they are about to be consumed [55]. Furthermore, this tool reduces interviewer bias as the dietary intake collection is self-administered [55]. Another tool called the Dietary Intake Monitoring System (DIMS) integrates a weighing machine as well as a camera [56]. Utilizing this combination of weight and image data, the tool exerts its advantage over traditional dietary assessment and image-based assessment methods by more accurately estimating portion sizes [56].

Factors affecting energy intake in older people with dementia versus non-dementia controls

Increasing age had been independently associated with declining nutritional status in older people [57]. Therefore, age may be a confounding factor in terms of energy intake especially when non-dementia controls are not age-matched or correction for age was not made during analysis. The majority of studies in Table 1 were corrected for age and showed no significant differences between the two groups. However, four studies [21 , 43] did not provide details of any statistical comparison of age between the group or any correction for age, and seven studies [25–27 , 39] did not account for age differences between the participants. This lack of detail and consideration for age differences in the participants limit the validity of the results because the presence of age as a confounding factor was not considered when the comparison was made.

Most studies included participants of varying degree of dementia severity (from mild to severe) determined using the Mini-Mental State Examination (MMSE), with six studies using alternative or additional methods of classification such as Clinical Dementia Rating (CDR) and Global Deterioration Scale (GDS). However, three studies [21 , 29] did not report on the severity of the dementia in the participants.

It is also important to consider the stage of dementia as a possible confounding factor since later stages of dementia have been associated with eating problems such as slow eating and food refusal [14, 58]. However, despite grading the dementia severity, most studies did not account for this difference in dementia severity when comparing energy intake between the groups. Instead, all older people with dementia were considered as a single dementia group. One study [32] grouped dementia participants into early and late stage but did not find significant differences in energy intake between the two sub-groups. Significant differences were instead observed between the sub-group’s lean body mass and their energy balance (TEE –energy intake) [32]. Similarly, a recent study by Salminen et al. [59] found that there is no significant difference in energy intake between non-free living older people with severe dementia compared to the ones with mild dementia (classified according to CDR). Despite this observation, there is a significantly higher proportion of the former relying on oral nutritional supplements in order to match the energy intake of older people with mild dementia. Hence, older people with more severe dementia tend to require additional interventions in order to maintain their energy intake.

More studies (n = 13) were conducted in older people with dementia under free-living conditions than in non-free living older people with dementia (n = 8), with 3 studies conducted in mixed setting (non-free living and free-living) conditions. In the studies involving free-living participants, older people with dementia had caregivers reporting food intake while healthy controls self-reported. This dichotomy created the possibility of a reporting bias due to the presence of a proxy-reporter for older people with dementia when compared to controls who self-rep-orted their own intake. For example, in one study [7] it was reported that AD patients group ate more than healthy controls. However, it was unknown if the excessive eating was due to caregiver’s insistence of giving more food to the AD patients. It is also important to consider whether the caregivers reported what was served or what was actually eaten. This external influence might not exist in the non-dementia control group who ate ad libitum, hence creating a reporting bias.

The majority of the studies observed no significant difference in energy intake between older people living with or without dementia. Similarly, earlier reviews did not observe significant lowered energy intake in older people with dementia when compared to non-dementia controls [16, 60]. In the current review, five studies [21 , 40] (male only in Thomas et al. [21]’s study and female only in Puranen et al. [40]’s study) observed significantly lower energy intakes in older people with dementia when compared to non-dementia controls, while five studies [7 , 40] found significantly higher energy intake in older people with dementia compared to non-dementia controls. The observations that older people with dementia had significantly higher energy intake compared to healthy controls are in direct contrast to the frequently reported unintended weight loss commonly found in patients with dementia [60]. As mentioned above, the higher energy intake observed in older people with dementia compared to non-dementia controls may be attributed to caregiver persuading older people with dementia to consume more thereby increasing the latter’s intake [7] compared to healthy controls who might not have the same external motivation to increase their intake. It is also important to consider possible variations affecting the outcome such as differing study setting. For example, one of the studies [29] was conducted with the non-dementia controls living in the community compared to older people with dementia who lived in long-term care setting. This different environment means that the results are difficult to fully interpret.

One study [23] accounted for setting differences through comparing three environments, i.e., non-free living older people with dementia, free-living older people with dementia, and healthy free-living older people. The study observed that both older people with dementia living in a non-free living setting and free-living older people with dementia had significan-tly higher energy intake compared to healthy control. However, the dietary assessment was only conducted on a randomly selected subgroup (n not reported) of each of the main groups, hence reducing the sample size. The dietary assessment method was also different in that they used an investigator-led three-day weighed dietary record for six days in total for the healthy controls and free-living older people and 21 days for non-free living older people with dementia. There was no statement on whether the three-day weighed dietary record was performed consecutively on randomly selected days within the period of observation or whether the choice of days was left to the investigator’s discretion. This was a potential reporting bias which might have affected the results.

Most studies shown in Table 1 did not report whether participants with dementia lost weight or reported no active weight loss. Only four studies [7 , 43] reported active weight loss among the participants. Wang et al. [7] observed that older people with dementia had significantly higher energy intake/kilogram (kg)/day compared with healthy control despite the dementia group having lower body mass index (BMI) and a higher percentage of participants living with dementia was actively undergoing weight loss. The reasons for this observation were unclear although the effect of focusing on food intake may draw the attention of both subjects and caregivers to food and therefore inadvertently encouraged food intake.

In terms of macronutrient intake, older people have higher requirement for protein than younger adults, at 1.0–1.2 g/kg/day to compensate for age-related changes in protein metabolism [61]. Table 2 summarizes the protein, fat, and carbohydrate intake of older people with dementia and non-dementia controls. There were 15 studies [7 , 38–41] which reported the protein intake of the participants, though only five studies [7 , 40] reported the protein intake as g/kg/day. Of the 5 studies, only families with male caregivers in Puranen et al. [40]’s study did not meet the higher protein requirement of older people. It was reported, however, that this observation may potentially be caused by male caregivers having more comorbidities, being older, and less skilled in food preparation compared to families with female caregivers [40].

Table 2

Differences in protein, fat and carbohydrate intake of older people with dementia compared to non-dementia controls

References	Macronutrient intake
Protein (g/day) (mean±SD)	Fats (g/day) (mean±SD)	Carbohydrate (g/day) (mean±SD)
Thomas et al., 1986 [21]	(mean±standard error)	Not reported	Not reported
	with dementia: Male: 62.0±2.6^*,
	female: 57.0±2.6
	without dementia: Male: 73.0±4.0^*,
	female: 64.0±3.6
Litchford &Wakefield, 1987 [22]	with dementia: 63.0±20.0	with dementia: 60.0±20.0	with dementia: 162.0±46.0^*
	without dementia: 74.0±15.0	without dementia: 77.0±16.0	without dementia: 213.0±48.0^*
Burns et al., 1989 [23]	with dementia (non-free living): 73.0±8.3^*	with dementia (non-free living): 78.0±18.1	Not reported
	with dementia (free-living): 61.0±12.0^*	with dementia (free-living): 78.0±17.1
without dementia: 44.0±15.2^*	without dementia: 59.0±20.6
O’Neill et al., 1990 [24]	(mean±standard error)	(mean±standard error)	(mean±standard error)
	with dementia: 79.0±5.0	with dementia: 75.0±6.0	with dementia: 283.0±17.0
	without dementia: 90.0±6.0	without dementia: 83.0±5.0	without dementia: 278.0±16.0
Winograd et al., 1991 [25]	with dementia: Male: 89.0±27.0,	with dementia: Male: 82.0±27.0,	with dementia: Male: 219.0±60.0,
	female: 76.0±16.0	female: 80.0±22.0	female: 215.0±83.0
	without dementia: Male: 99.0±37.0,	without dementia: Male: 86.0±23.0,	without dementia: Male: 249.0±74.0,
	female: 76.0±14.0	female: 65.0±15.0	female: 246.0±46.0
			Simple sugar (as % of total energy):
			with dementia: Male: 17±6, female: 15±6
			without dementia: Male: 18±5, female: 26±4
Dvorak & Poehlman, 1998 [31]	Not reported	Not reported	Not reported
Wang et al., 2004 [7]	(g/kg body weight)	(g/kg body weight)	(g/kg body weight)
	with dementia: 1.5±0.6	with dementia: 1.3±0.5	with dementia: 5.3±1.4^*
	without dementia: 1.4±0.4	without dementia: 1.1±0.4	without dementia: 4.1±1.3^*
Kwan et al., 2005 [32]	with dementia: 72.3±25.7	Not reported	Not reported
	without dementia: 67.9±18.5
Tabet et al., 2005 [33]	Not reported	with dementia: 64.4±9.7	with dementia: 209.0±26.3
		without dementia: 66.4±7.5	without dementia: 206.5±17.3
Shatenstein et al., 2007 [34]	with dementia: 64.0±19.0^*	with dementia: 55.0±17.0^*	with dementia: 194.0±49.0^*
	without dementia: 74.0±17.0^*	without dementia: 65.0±23.0^*	without dementia: 225.0±56.0^*
Presse et al., 2008 [35]	Not reported	Not reported	Not reported
Jesus et al., 2012 [36]	(g/kg body weight)	(in %)	(in %)
	with dementia: 1.1±0.4^*	with dementia: 36.8±6.1^*	with dementia: 46.5±6.0
	without dementia: 1.0±0.4^*	without dementia: 38.7±7.5^*	without dementia: 45.6±6.8
Sadamori et al., 2012 [37]	Not reported	Not reported	Not reported
Galesi et al., 2013 [38]	(median (interquartile range))	Not reported	Not reported
	with dementia: Male: 47.4 (11.4),
	female: 55.9 (15.9)
	without dementia: Male: 56.7 (24.8),
	female: 50.2 (19.1)
Ahmed et al., 2014 [39]	No significant difference in	No significant difference in fat	Older people with AD and
	protein intake between	intake between dementia	SD have higher carbohydrate
	dementia and control group	and control group	intake/day (not significant)
			Total sugar intake (g/day)
			with SD: 114^*
			control: 76^*
Puranen et al., 2014 [40]	(g/kg body weight)	Not reported	Not reported
	with dementia: Male: 1.04±0.30^*,
	female: 0.86±0.32^*
	without dementia: Male: 0.93±0.30^*,
	female: 1.00±0.30^*
Kim et al., 2016 [41]	with dementia: 59.5±2.3	with dementia: 32.0±1.8	with dementia: 246.2±7.0
	without dementia: 63.7±1.7	without dementia: 33.8±1.3	without dementia: 251.8±5.2
Venturelli et al., 2016 [42]	Not reported	Not reported	Not reported
Batchelor-Murphy et al., 2019 [43]	Not reported	Not reported	Not reported

^*Statistically significant (p < 0.05).

Comparing the protein intake of older people with dementia and older people without dementia, only six studies reported significant differences with three studies reporting a higher protein intake in older people without dementia [21 , 40] (female only in Puranen et al. [40]’s study) while the other studies reported higher protein intake in older people with dementia [23 , 40] (male only in Puranen et al. [40]’s study). Hence, similar to the lack of evidence for a lower calorie intake in older people with dementia, there is also a lack of evidence for a lower protein intake in older people with dementia compared to older people without dementia.

Other than protein, fats and carbohydrates intake have been shown to have impacts on the development of dementia. Both fats and protein intake have been theorized to be crucial in the maintenance of neuronal membranes and myelin sheath in the brain [62]. A diet high in carbohydrates and refined sugars, on the other hand, may have deleterious effects on cognitive functions as high insulin level has been associated to a decline in cognitive function and hyperglycemia may increase oxidative stress and the formation of advanced glycation endproducts (AGE) [63 –65].

There were 11 [7 , 41] and 10 [7 , 41] studies, respectively, which reported participants’ fat and carbohydrate intake. However, only two studies [34, 36] observed significantly lower fat consumption in older people with dementia and two other studies [22, 34] observing significantly lower carbohydrate consumption in older people with dementia compared to older people without. Wang et al. [7]’s study was the only one which observed a significantly higher carbohydrate consumption in older people with dementia compared to older people without. Interestingly, one study observed a significantly higher sugar intake in older people with dementia [39, 39] and one study observed a significantly higher frequency of intake of cookies and snacks in older people with dementia [41]. As discussed above, diet high in caloric intake from carbohydrate and low in caloric intake from fat and protein was shown to increase the risk of mild cognitive impairment or dementia in older people [62] and refined carbohydrate-rich diet [66] have been associated with increased risk of dementia. Whether or not the participants’ intake in the studies of Ahmed et al. [39] and Kim et al. [41] reflected their intake prior to developing dementia was uncertain due to the nature of the cross-sectional study design; however, this observation is crucial to avoid further exacerbation and deterioration of the mental status of the older people. It is hence important to not only ensure that older people with dementia consume enough calories but also consume enough from the right sources of calories.

In summary, current available literature does not demonstrate a lower energy and macronutrient intake in older people living with dementia compared to non-dementia controls in non-free living and free-living setting. However, those older people living with dementia are at high risk of weight loss and malnutrition. In order to further elucidate the reasons behind this, it is useful to consider whether an incr-ease in energy expenditure is the cause of the imbalance in energy equilibrium and therefore leading to weight loss.

RESTING ENERGY ENXPENDITURE IN OLDER PEOPLE LIVING WITH DEMENTIA VERSUS NON-DEMENTIA CONTROLS

Measurement of resting energy expenditure (REE)

Table 3 summarizes eight studies [26 , 68] that compared resting energy expenditure in older people with dementia to non-dementia con-trols in both non-free living and free-living conditions. All included studies measuring REE, except for two [42, 68], utilized the gold standard REE measurement of indirect calorimetry. Among the six studies utilizing indirect calorimetry, five of the studies [26 , 30–32] ensured a fasting period of at least five hours before measurement and three of these studies [27 , 31] ensured that the participants abstained from vigorous physical activity for at least 14 hours before REE measurements or moderate physical activity for at least two hours before measurements. However, most of the six studies failed to mention if the measurements were done in thermal-neutral conditions and if a brief period of rest and acclimatization was accorded to the participants, especially if the latter traveled in the morning to reach the research center where REE were measured. These are important factors which might affect the REE readings if not controlled [69].

Table 3

Studies investigating differences between REE in older people with dementia compared to non-dementia controls

References	Non-free living/free living	Characteristics of subjects with dementia	Dementia sub-types	Methods of dementia classification & severity of dementia	Characteristics of control subjects	REE (kcal/day) (mean±SD) collection	Methods of REE
Niskanen et al., 1993 [26]	Non-free living	n = 20 (all f)	AD, MID	MMSE; moderate -	n = 10 (all f)	with AD: 1089±129	Indirect calorimetry
	Free living - control	Age: 64 –90 y (AD),		severe dementia	Age: 75 y	with MID: 1078±102
		77 –91 y (MID)				without dementia: 1188±143
Wolf-Klein et al., 1995 [67]	Free living	n = 5 (2 m, 3 f)	AD	MMSE; moderate -	n = 7 (2 m, 5 f)	Older people living with	Indirect calorimetry
		Male age: 84.0		severe dementia	Male age: 69.0 (62.0 –76.0) y	dementia have higher REE
		(83.0 –85.0) y			Female age: 80.0 (73.0 –86.0) y	compared to control^*
		Female age: 84.0
		(74.0 –91.0) y
Donaldson et al., 1996 [27]	Free living	n = 25 (8 m, 17 f)	AD	MMSE; mild -	n = 73 (23 m, 50 f)	with AD: 1314±134	Indirect calorimetry
		Age: 74±8 y		severe dementia	Age: 69±7 y	without dementia:
						1342±149
Poehlman et al., 1997 [30]	Free-living	n = 30 (13 m, 17 f)	AD	MMSE; mild -	n = 103 (51 m, 52 f)	with AD:1287±227	Indirect calorimetry
		Age: 73±8 y		severe dementia	Age: 69±7 y	(unadjusted) without
						dementia:1418±246
						(unadjusted)
Dvorak &	Free-living	n = 30 (13 m, 17 f)	AD	MMSE; mild -	n = 30 (13 m, 17 f)	with AD: 1286±222	Indirect calorimetry
Poehlman, 1998 [31]		Age: 74±8 y		severe dementia	Age: 73±7 y	without dementia:
						1317±208
Kwan et al., 2005 [32]	Free living	n = 45 (10 m, 35 f)	AD	MMSE; mild -	n = 36 (16 m, 20 f)	(kcal/kg/day)	Indirect calorimetry
		Age: 76.8±6.8 y		severe dementia	Age: 72.9±6.4 y	with AD: 31±3.8
						without dementia: 31±3.8
Venturelli et al., 2016 [42]	Non-free	n = 85 (27 m, 58 f)	AD	CDR; mild -	n = 86 (23 m, 63 f)	with AD: 1066±86	RMR estimated using equation,
	living	Age: 76±4 y		severe cognitive	Age: 78±5 y	without dementia:	Brage’s branched equation
				impairment	1059±99
Ahmed et al., 2017 [68]	Free-living	n = 32 (17 m, 15 f)	AD	FRS; moderate -	n = 16 (10 m, 6 f)	with AD: 1356±171	RMR estimated using equation,
		Age: 66±8.2 y (AD)		severe dementia	Age: 65±7.7 y	without dementia:	Brage’s branched equation
						1442±174

^*Statistically significant (p < 0.05); m, male; f, female; y, years; REE, Resting Energy Expenditure; AD, Alzheimer’s disease; MID, multi-infarct dementia; MMSE, Mini-Mental State Examination; CDR, Clinical Dementia Rating; FRS, Frontal Rating Scale.

The main challenges of REE measurement in older people using indirect calorimetry are to ensure that participants remain in a restful state and are able to breathe smoothly especially throughout the steady state measurement period [70]. Difficulties such as agitation, fear, restlessness, and easily falling asleep had been reported in this population group [16]. None of the studies quoted in Table 3, however, mentioned such challenges during REE measurement in this group.

Factors affecting resting energy expenditure in older people with dementia versus non-dementia controls

The finding of increased metabolic rate in a triple transgenic mice model of AD [71] has contributed to the hypothesis that hypermetabolism may be the cause of weight loss in older people living with dementia. Furthermore, the fact that no significant difference between energy intake in older people living with dementia compared to non-dementia controls has been confirmed, it is then reasonable to suggest that a state of hypermetabolism exists which causes energy imbalance leading to weight loss. However, conflicting results have been seen in studies on energy expenditure in older people with dementia [26 , 68]. Most of the studies comparing REE in older people living with dementia compared to non-dementia controls have not found significant differences between the groups [26 , 68].

Wolf-Klein et al. [67] observed significantly higher REE levels in older people with dementia than non-dementia controls. They attributed this finding to higher fat-free mass (FFM) among older people with dementia [67] but did not discuss the possible reasons why FFM was higher in the dementia group. Unfortunately, the relatively small sample size of the study limits the generalizability of the findings.

Gender difference has been recognized as a contributing factor toward REE differences, with REE in males being reported as higher than in females [72, 73] of the same age and weight from puberty to adulthood. This difference is mainly due to differences in body composition between males and females namely FFM, fat mass and fat distribution [74]. However, this gender difference in REE may be less significant amongst those aged 60 and above due to age related decline in FFM. A review on energy requirements in older people, encompassing 2,450 participants, concluded that gender was not a determinant of REE for individuals in this age group [75]. Aside from study by Niskanen et al. [26] (whose participants were all women), the other seven studies identified did not perform subgroup analysis on REE differences between the gender. However, most of them either had matched participants for FFM or corrected for body composition differences in the analysis [27 , 67]. Only two studies [42, 68] matched the participants by their BMI (surrogate measure of body fatness). Hence, the presence of confounding factors such as gender and body composition limit the validity of their results.

Ethnicity is another factor that may influence the REE of an individual. Individuals born in tropical regions have been observed with lower REE compared to Caucasians of similar age groups [76, 77]. Adzika Nsatimba et al. [78] also observed that there was a significant difference between the REE of sub-Saharan Africans compared to Australians of European descent. Furthermore, the various reports of over- and underestimation of REE when predictive equations were applied to different ethnic groups from which predictive equations were developed [79] suggested that the differences in REE between different ethnic groups may be independent of the individuals’ body composition. This may be explained by research on uncoupling protein genes (linked to an individual’s susceptibility to obesity) which suggested that these genes may be involved in the processes leading to lower REE of African American females compared to white females [80, 81]. Research investigating REE differences of older people based on ethnicity is limited. One which compared the REE of older people including Spanish, Amerindian, and African found no differences in REE (after adjustment for FFM) of older people [82]. However, the relatively small sample size and limited ethnicity involved in the study mean that the results may not be applicable in other study groups. Hence, ethnicity may still be an important factor to be considered in REE and TEE studies as it may be a confounding factor but this requires further elucidation. This is especially true if the participants of the study were of different ethnicity from each other. Unfortunately, none of the eight studies identified gave details on the ethnicity of their study populations and this may confound the conclusion that there was no difference in REE between dementia and control group.

In the above studies, variations also exist in the severity of the disease as well as the presence or absence of weight loss and its severity in the participants. These confounding factors may affect the REE values of participants directly or indirectly through the loss of FFM. Regardless, from the eight studies identified, it is apparent that there is not a significant elevation in the REE of older people living with dementia compared to non-dementia controls. Niskanen et al. [26] and Heshka et al. [83] hypothesized a state of hypermetabolism early in the disease with REE later decreasing to a level similar to the ones found in non-dementia older people as FFM was reduced as weight was lost. This concept of hypermetabolism early in the disease phase was further supported by recent findings from Doorduijn et al. [84] where they showed a higher REE (kcal/kg FFM) but similar energy intake in individuals with mild AD and mild cognitive impairment compared to individuals without. This may explain the early weight loss observed in individuals even before the signs of dementia became apparent [9]. A prospective cohort study, tracking the weight history, REE, and energy intake of the participants, would elucidate whether hypermetabolism may actually be the cause of elevated REE driving early weight loss in individuals before the onset of dementia starts. Although, the existence of various comorbidities are often present in older people, and the possible interplay from other factors, such as low food intake, may create difficulties in singling out hypermetabolism caused by dementia (if, at all) to be a significant cause of weight loss in an individual.

As current available literature suggests that there is no significant difference between REE of older people living with dementia compared to healthy controls, TEE should now be considered. Higher TEE compared to energy intake would lead to weight loss. Hence, TEE measurement will enable direct comparison with energy intake to analyze if weight loss observed in older people living with dementia is truly caused by imbalance between energy intake and TEE.

TOTAL ENERGY EXPENDITURE IN OLDER PEOPLE LIVING WITH DEMENTIA VERSUS NON-DEMENTIA CONTROLS

Measurement of total energy expenditure (TEE)

Studies comparing TEE between older people living with dementia and healthy controls, summarized in Table 4 [30–32 , 68], are limited. Traditionally, two methods commonly used to measure TEE are direct calorimetry (using whole-room calorimeter) and doubly-labeled water (DLW). The latter is the preferred method and is often considered the gold standard to measure TEE. Direct calorimetry, on the other hand, requires a whole-room calorimeter with complex engineering which limits its accessibility [85]. Furthermore, whole-room calorimeter requires the participants to remain within the physically confined space for an extended period of time [85] and hence may not be suitable for some participants, especially older people with dementia. Two of the included studies measuring TEE [30, 31] used DLW, while two other studies [42, 68] used a physical activity monitor (Actiheart, CamNtech), which calculated activity energy expenditure (AEE) using branched equations on electrocardiogram (ECG) reading and activity level [86]. Estimated REE (using the Schofield equation [68, 86], diet-induced thermogenesis (assumed to be a constant 10% of TEE)) and AEE were then used to estimate the TEE of the wearer [68, 86]. Actiheart, however, has not been successfully validated against DLW for use on either healthy older people, nor people with dementia.

Table 4

Studies investigating differences between TEE in older people with dementia compared to non-dementia controls

References	Non-free living/free living	Characteristics of subjects with dementia	Dementia sub-types	Methods of dementia classification & severity of dementia	Characteristics of control subjects	TEE (kcal/day) (mean±SD)	Methods of TEE collection
Poehlman et al., 1997 [30]	Free-living	n = 30 (13 m, 17 f)	AD	MMSE; mild -	n = 103 (51 m, 52 f)	with AD: 1901±517	Doubly-labeled water
		Age: 73±8 y		severe dementia	Age: 69±7 y	without dementia:
						2213±513 (unadjusted)^*
Dvorak & Poehlman, 1998 [31]	Free-living	n = 30 (13 m, 17 f)	AD	MMSE; mild -	n = 30 (13 m, 17 f)	with AD: 2015±538	Doubly-labeled water
		Age: 74±8 y		severe dementia	Age: 73±7 y	without dementia:
						2139±418
Kwan et al., 2005 [32]	Free living	n = 45 (10 m, 35 f)	AD	MMSE; mild -	n = 36 (16 m, 20 f)	(kcal/kg/day)	Estimated from REE
		Age: 76.8±6.8 y		severe dementia	Age: 72.9±6.4 y	with AD: 208±35^*	and physical activity
						without dementia: 258±39^*	questionnaire
Venturelli et al., 2016 [42]	Non-free	n = 85 (27 m, 58 f)	AD	CDR; mild - severe	n = 86 (23 m, 63 f)	with AD: 1640±132	∼Actiheart
	living	Age: 76±4 y		cognitive impairment	Age: 78±5 y	without dementia: 1629±153
Ahmed et al., 2017 [68]	Free-living	n = 32 (17 m, 15 f)	AD	FRS; moderate -	n = 16 (10 m, 6 f)	with AD: 2029±441	Actiheart
		Age: 66±8.2 y (AD)		severe dementia	Age: 65±7.7 y	without dementia: 2182±246

^*Statistically significant (p < 0.05); m, male; f, female; y, years; TEE, total energy expenditure; AD, Alzheimer’s disease; bvFTD, behavioral variant frontotemporal dementia; MMSE, Mini-Mental State Examination; CDR, Clinical Dementia Rating; FRS, Frontal Rating Scale.

Another study [32] utilized a modified version of two physical activity questionnaires, namely the Yale Physical Activity Questionnaire and the Baecke Questionnaire, in the derivation of TEE values. Neither of which have been well-validated against DLW for use in older people with dementia [87, 88].

Based on the quality statements developed by Porter et al. [89], the DLW protocol employed by Poehlman et al. [30] and Dvorak and Poehlman [31] were well-designed with both studies stating the DLW dosage as well as their methods for converting carbon dioxide (CO₂) production to energy expenditure. Poehlman et al. [30]’s isotope ratio analysis also met the 10% precision requirements for TEE measurement. However, both studies did not clearly report if the study subjects were fasted for 5–12 hours before administration of DLW.

Factors affecting total energy expenditure in older people with dementia versus non-dementia controls

The current review of the literature has not found sufficient evidence to suggest that TEE in older people living with dementia is higher than in healthy controls. In fact, Poehlman et al. [30] and Kwan et al. [32] observed a lower TEE in older people with dementia compared to healthy controls. Poehlman et al. [30] attributed the differences in TEE to lower REE and when adjusted for different body composition, they found no significant differences between the REE of the dementia and control group. However, Kwan et al. [32] attributed the lower TEE in the dementia group to lower AEE found in the group as caregivers may have restricted the movements of the participants for safety reasons.

An aspect which often needs to be considered in older people living with dementia is AEE as fidgeting and wandering behavior had been reported in people living with dementia [90]. These characteristics may contribute to the increase in AEE and hence increase the overall TEE, a possible contributor to the weight loss experienced in this group.

Prentice et al. [91] commented that TEE was much higher in participants who showed the characteristic wandering and rocking often seen in people with dementia compared to participants who were mostly sedentary. In addition, Moyle et al. [92] also observed this heightened agitation levels among older people with dementia especially between 3 pm and 6:59 pm, which may be a characteristic of ‘sundowning’. Dvorak and Poehlman [31] reported on non-purposeful movements such as fidgeting and shivering that their participants exhibited. However, they found no differences in TEE between the participants with and without dementia [31]. Wang et al. [7] also observed higher incidence of wandering behavior in older people with dementia but found that the group still had lower metabolic equivalent of task (MET) per day compared to non-dementia controls, thereby expending less energy. Evidence seems to be conflicting on whether or not wandering and fidgeting behaviors increase TEE. As weight loss is also often seen in older people with dementia who do not display the characteristics of wandering and fidgeting, the latter may not be a significant contributor towards weight loss in older people with dementia. Noninvasive activity measurement tools such as Actiheart and SenseWear may be useful to integrate into future studies to determine the extent of wandering and fidgeting behaviors. Further validation of these tools in this population is needed.

WEIGHT LOSS AND ENERGY BALANCE IN OLDER PEOPLE LIVING WITH DEMENTIA VERSUS NON-DEMENTIA CONTROLS

Current available literature does not support the view that there is a lowered energy intake and a higher energy expenditure (REE and TEE) in older people living with dementia compared to non-dementia controls. With weight loss being a result of negative energy balance (due to inadequate energy intake or increased energy expenditure), the findings of this review suggest that there is not an increased risk of weight loss caused by negative energy balance in older people with dementia when compared to their counterparts who have no dementia. In fact, Wang et al. [93] observed that while older people with dementia had lower weights throughout their stay within the long-term care setting compared to healthy controls, mean weights did not change during the 4-years study period. The findings of their study showed that with interventions, the frequently reported low energy intake in older people with dementia could be ameliorated.

Despite these findings, other studies had previously shown that older people with dementia were more likely to lose more weight compared to non-dementia group [8 , 94] even when the former appeared to have adequate energy intake [7 , 95]. Hence, the precise reasons behind weight loss in older people with dementia continue to elude researchers and clinicians alike.

It is possible that weight loss in older people with dementia occur during discrete episodes of low food intake and high energy expenditure, for example during hospitalization or periods of illness and low appetite. These episodes, unfortunately, would not be captured in cross-sectional studies which were the typical study designs in the field (Tables 1, 3, and 4). Or perhaps, as Singh et al. [95] had proposed earlier that being thin may be a risk factor for developing dementia instead of the former being a symptom of dementia. This hypothesis seems to be a possible explanation as Stewart et al. [9] had observed that there was an increasing difference in BMI between older people with dementia compared to older people without dementia and that the former lost significantly more weight six years prior to diagnosis. Future research should hence focus on longitudinal studies, with dementia as the outcome of interest, measuring older people’ energy intake and expenditure at discrete episodes to better elucidate the state of energy equilibrium in this population group and the reasons behind their weight loss.

LIMITATION AND CONCLUSION

Based on the current literature, this review does not support the rationale that a lower energy intake and/or raised REE and TEE in older people living with dem-entia compared to non-dementia controls are the underlying causes for the observed weight loss. However, there are elements missing in this puzzle which should be addressed in future research. Utilizing image-assisted methods to collect dietary intake may enable more accurate estimates and relieve some burden from the participants in collecting food intake data.

Furthermore, there was considerable heterogeneity in the methodology of the studies as well as the extent of methodology details reported. Some studies did not clearly indicate their inclusion and exclusion criteria [22 , 38], while others did not frame the setting of their recruitment and selection processes in detail [24 , 68], leaving possibilities for selection bias to occur. Three studies [21 , 67] purposively chose the study participants, hence introducing selection error to the study methodology. With regards to the demographics of the participants recruited, it is essential that subjects are comparable in terms of age, ethnicity, body weight, height, FFM, and the presence or absence of weight loss. If this is not possible, a method to normalize the data should always be incorporated to account for differences in body composition. Another factor to be considered is the severity of dementia. Some studies cited in this review did not describe the severity of the dementia or differentiate between participants with mild or severe dementia. It has been suggested that there is a correlation between dementia severity and worsened nutritional status [13], while other studies suggested a state of hypermetabolism in the early phase of the disease [26 , 84]. Hence, future research should look at early, moderate and severe stages of dementia separately in order to determine differences in energy balance between these stages.

Future research should also include longitudinal studies instead of cross-sectional in order to observe differences in energy balance throughout the lifespan of older people with and without dementia in order to find out whether there are discrete episodes of weight loss and also to get a more accurate portrayal of energy intake and expenditure of older people living with dementia. These longitudinal studies would also be able to reveal if weight loss was a risk factor per se, rather than a symptom of dementia. Finally, there is clearly a need for more high-quality studies comparing energy intake and expenditures in older people with and without dementia.

This review has summarized and explored available studies on energy intake and expenditures in older people with dementia compared to non-dem-entia controls. Future studies should focus on longitudinal study design and also segregate subjects taking account differences in study settings (non-free living versus free-living) as well as severity of dementia. Such an analysis would further strengthen the evidence, enabling targeted interventions to reduce unintentional weight loss in this population.

Footnotes

ACKNOWLEDGMENTS

The authors thank A^*STAR for supporting this review. This research is supported by Wilmar International Limited, under its WILMAR @NUS Corp Lab: Clinical evaluation of functional food ingredients and food products (Project Code: SC34/18-3001B0-NUSW).

Authors’ disclosures available online ().

References

Anstey

, Low

(2004) Normal cognitive changes in aging. Aust Fam Physician 33, 783–787.

World Health Organization (2018) World Health Organization, Geneva, Switzerland, p. 6.

McNamara

(2011) Preface: Hopeful Trends in Meeting the Challenge of the Dementias. In Dementia: Volume 1 History and Incidence. Praeger, Santa Barbara, CA, pp. ix-xi.

Cronin-Stubbs

, Beckett

, Scherr

, Field

, Chown

, Pilgrim

, Bennett

, Evans

(1997) Weight loss in people with Alzheimer’s disease: A prospective population based analysis. BMJ 314, 178–179.

Gillette-Guyonnet

, Nourhashemi

, Andrieu

, de Glisezinski

, Ousset

, Riviere

, Albarede

, Vellas

(2000) Weight loss in Alzheimer disease. Am J Clin Nutr 71, 637s–642s.

Gillette Guyonnet

, Abellan Van Kan

, Alix

, Andrieu

, Belmin

, Berrut

, Bonnefoy

, Brocker

, Constans

, Ferry

, Ghisolfi-Marque

, Girard

, Gonthier

, Guerin

, Hervy

, Jouanny

, Laurain

, Lechowski

, Nourhashemi

, Raynaud-Simon

, Ritz

, Roche

, Rolland

, Salva

, Vellas

(2007) IANA (International Academy on Nutrition and Aging) Expert Group: Weight loss and Alzheimer’s disease. J Nutr Health Aging 11, 38–48.

Wang

, Yang

, Lin

, Chen

, Chwang

, Liu

(2004) Weight loss, nutritional status and physical activity in patients with Alzheimer’s disease. A controlled study. J Neurol 251, 314–320.

White

, Pieper

, Schmader

, Fillenbaum

(1996) Weight change in Alzheimer’s disease. J Am Geriatr Soc 44, 265–272.

Stewart

, Masaki

, Xue

, Peila

, Petrovitch

, White

, Launer

(2005) A 32-year prospective study of change in body weight and incident dementia: The Honolulu-Asia Aging Study. Arch Neurol 62, 55–60.

10.

Albanese

, Taylor

, Siervo

, Stewart

, Prince

, Acosta

(2013) Dementia severity and weight loss: A comparison across eight cohorts. The 10/66 study. Alzheimers Dement 9, 649–656.

11.

Luchsinger

, Patel

, Tang

, Schupf

, Mayeux

(2008) Body mass index, dementia, and mortality in the elderly. J Nutr Health Aging 12, 127–131.

12.

White

, Pieper

, Schmader

, Fillenbaum

(1997) A longitudinal analysis of weight change in Alzheimer’s disease. J Am Geriatr Soc 45, 531–532.

13.

White

, Pieper

, Schmader

(1998) The association of weight change in Alzheimer’s disease with severity of disease and mortality: A longitudinal analysis. J Am Geriatr Soc 46, 1223–1227.

14.

Cipriani

, Carlesi

, Lucetti

, Danti

, Nuti

(2016) Eating behaviors and dietary changes in patients with dementia. Am J Alzheimers Dis Other Demen 31, 706–716.

15.

Liu

, Cheon

, Thomas

(2014) Interventions on mealtime difficulties in older adults with dementia: A systematic review. Int J Nurs Stud 51, 14–27.

16.

Mazzali

, Bissoli

, Gambina

, Residori

, Pagliari

, Guariento

, Sun

, Broggio

, Bosello

, Zamboni

(2002) Energy balance in Alzheimer’s disease. J Nutr Health Aging 6, 247–253.

17.

Smith

, Greenwood

(2008) Weight loss and nutritional considerations in Alzheimer disease. J Nutr Elder 27, 381–403.

18.

United Nations Department of Economic and Social Affairs (2019) World Population Ageing 2019. United Nations, New York, pp. 5-17.

19.

Thomson

, Subar

(2001) Dietary assessment methodology. In Nutrition in the Prevention and Treatment of Disease, Coulston AM, Rock CL, Monsen ER, eds. Academic Press, San Diego, CA, pp. 3-30.

20.

Emmett

(2009) Workshop 2: The use of surrogate reporters in the assessment of dietary intake. Eur J Clin Nutr 63, S78–S79.

21.

Thomas

, Chung

AOKO

, Dickerson

, Tidmarsh

, Shaw

(1986) Tryptophan and nutritional status of patients with senile dementia. Psychol Med 16, 297–305.

22.

Litchford

, Wakefield

(1987) Nutrient intakes and energy expenditures of residents with senile dementia of the Alzheimer’s type. J Am Diet Assoc 87, 211–213.

23.

Burns

, Marsh

, Bender

(1989) Dietary intake and clinical, anthropometric and biochemical indices of malnutrition in elderly demented patients and non-demented subjects. Psychol Med 19, 383–391.

24.

O’Neill

, McKiernan

, Gibney

, Walsh

, Coakley

(1990) Dietary and anthropometric measures in mild to moderate senile dementia of the Alzheimer type (SDAT). J Hum Nutr Diet 3, 177–181.

25.

Winograd

, Jacobson

, Butterfield

, Cragen

, Edler

, Taylor

, Yesavage

(1991) Nutritional intake in patients with senile dementia of the Alzheimer type. Alzheimer Dis Assoc Disord 5, 173–180.

26.

Niskanen

, Piirainen

, Koljonen

, Uusitupa

(1993) Resting energy expenditure in relation to energy intake in patients with Alzheimer’s disease, multi-infarct dementia and in control women. Age Ageing 22, 132–137.

27.

Donaldson

, Carpenter

, Toth

, Goran

, Newhouse

, Poehlman

(1996) No evidence for a higher resting metabolic rate in noninstitutionalized Alzheimer’s disease patients. J Am Geriatr Soc 44, 1232–1234.

28.

Franzoni

, Frisoni

, Boffelli

, Rozzini

, Trabucchi

(1996) Good nutritional oral intake is associated with equal survival in demented and nondemented very old patients. J Am Geriatr Soc 44, 1366–1370.

29.

Spindler

, Renvall

, Nichols

, Ramsdell

(1996) Nutritional status of patients with Alzheimer’s disease: A 1-year study. J Am Diet Assoc 96, 1013–1018.

30.

Poehlman

, Toth

, Goran

, Carpenter

, Newhouse

, Rosen

(1997) Daily energy expenditure in free-living non-institutionalized Alzheimer’s patients: A doubly labeled water study. Neurology 48, 997–1002.

31.

Dvorak

, Poehlman

(1998) Appendicular skeletal muscle mass, physical activity, and cognitive status in patients with Alzheimer’s disease. Neurology 51, 1386–1390.

32.

Kwan

, Kwok

, Lam

, Woo

, Chiu

(2005) A pilot study of associated factors of weight changes in community-dwelling patients with Alzheimer’s disease. Nutr Res 25, 111–118.

33.

Tabet

, Mantle

, Walker

, Orrell

(2005) Higher fat and carbohydrate intake in dementia patients is associated with increased blood glutathione peroxidase activity. Int Psychogeriatr 17, 91–98.

34.

Shatenstein

, Kergoat

, Reid

(2007) Poor nutrient intakes during 1-year follow-up with community-dwelling older adults with early-stage Alzheimer dementia compared to cognitively intact matched controls. J Am Diet Assoc 107, 2091–2099.

35.

Presse

, Shatenstein

, Kergoat

, Ferland

(2008) Low vitamin K intakes in community-dwelling elders at an early stage of Alzheimer’s disease. J Am Diet Assoc 108, 2095–2099.

36.

Jesus

, Desport

, Massoulard

, Villemonteix

, Baptiste

, Gindre-Poulvelarie

, Lorgueuilleux

, Javerliat

, Fraysse

, Preux

(2012) Nutritional assessment and follow-up of residents with and without dementia in nursing homes in the Limousin region of France: A health network initiative. J Nutr Health Aging 16, 504–508.

37.

Sadamori

, Hayashi

, Fujihara

, Abekura

, Hamada

, Akagawa

(2012) Nutritional status and oral status of the elderly with dementia: A 2-year study. Gerodontology 29, e756–760.

38.

Galesi

, Leandro-Merhi

, de Oliveira

(2013) Association between indicators of dementia and nutritional status in institutionalised older people. Int J Older People Nurs 8, 236–243.

39.

Ahmed

, Irish

, Kam

, van Keizerswaard

, Bartley

, Samaras

, Hodges

, Piguet

(2014) Quantifying the eating abnormalities in frontotemporal dementia. JAMA Neurol 71, 1540–1546.

40.

Puranen

, Pietila

, Pitkala

, Kautiainen

, Raivio

, Eloniemi-Sulkava

, Jyvakorpi

, Suominen

(2014) Caregivers’ male gender is associated with poor nutrient intake in AD families (NuAD-trial). J Nutr Health Aging 18, 672–676.

41.

Kim

, Lee

, Youn

, Chang

(2016) Food and nutrient intake status of Korean elderly by degree of cognitive function. J Nutr Health 49, 313–322.

42.

Venturelli

, Cè

, Limonta

, Muti

, Scarsini

, Brasioli

, Schena

, Esposito

(2016) Possible predictors of involuntary weight loss in patients with Alzheimer’s disease. PLoS One 11, e0157384.

43.

Batchelor-Murphy

, Kennerly

, Horn

, Barrett

, Bergstrom

, Boss

, Yap

(2019) Impact of cognition and handfeeding assistance on nutritional intake for nursing home residents. J Nutr Gerontol Geriatr 38, 262–276.

44.

Food and Agriculture Organization of the United Nations (2018) United Nations, Rome, Italy, pp. 10-39.

45.

Prentice

, Mossavar-Rahmani

, Huang

, Van Horn

, Beresford

, Caan

, Tinker

, Schoeller

, Bingham

, Eaton

, Thomson

, Johnson

, Ockene

, Sarto

, Heiss

, Neuhouser

(2011) Evaluation and comparison of food records, recalls, and frequencies for energy and protein assessment by using recovery biomarkers. Am J Epidemiol 174, 591–603.

46.

Watanabe

, Nanri

, Sagayama

, Yoshida

, Itoi

, Yamaguchi

, Yokoyama

, Watanabe

, Goto

, Ebine

, Higaki

, Ishikawa-Takata

, Kimura

, Yamada

(2019) Estimation of energy intake by a food frequency questionnaire: Calibration and validation with the doubly labeled water method in Japanese older people. Nutrients 11, 1546.

47.

Magkos

, Yannakoulia

(2003) Methodology of dietary assessment in athletes: Concepts and pitfalls. Curr Opin Clin Nutr Metab Care 6, 539–549.

48.

Mertz

, Tsui

, Judd

, Reiser

, Hallfrisch

, Morris

, Steele

, Lashley

(1991) What are people really eating? The relation between energy intake derived from estimated diet records and intake determined to maintain body weight. Am J Clin Nutr 54, 291–295.

49.

Prentice

, Black

, Coward

, Davies

, Goldberg

, Murgatroyd

, Ashford

, Sawyer

, Whitehead

(1986) High levels of energy expenditure in obese women. Br Med J (Clin Res Ed) 292, 983–987.

50.

Lichtman

, Pisarska

, Berman

, Pestone

, Dowling

, Offenbacher

, Weisel

, Heshka

, Matthews

, Heymsfield

(1992) Discrepancy between self-reported and actual caloric intake and exercise in obese subjects. N Engl J Med 327, 1893–1898.

51.

Buhl

, Gallagher

, Hoy

, Matthews

, Heymsfield

(1995) Unexplained disturbance in body weight regulation: Diagnostic outcome assessed by doubly labeled water and body composition analyses in obese patients reporting low energy intakes. J Am Diet Assoc 95, 1393–1400; quiz 1401-1392.

52.

Poslusna

, Ruprich

, de Vries

, Jakubikova

, van’t Veer

(2009) Misreporting of energy and micronutrient intake estimated by food records and 24 hour recalls, control and adjustment methods in practice. Br J Nutr 101 Suppl 2, S73–85.

53.

Monacelli

, Sartini

, Bassoli

, Becchetti

, Biagini

, Nencioni

, Cea

, Borghi

, Torre

, Odetti

(2017) Validation of the photography method for nutritional intake assessment in hospitalized elderly subjects. J Nutr Health Aging 21, 614–621.

54.

Pouyet

, Cuvelier

, Benattar

, Giboreau

(2015) A photographic method to measure food item intake. Validation in geriatric institutions. Appetite 84, 11–19.

55.

Timon

, Astell

, Hwang

, Adlam

, Smith

, Maclean

, Spurr

, Forster

, Williams

(2015) The validation of a computer-based food record for older adults: The Novel Assessment of Nutrition and Ageing (NANA) method. Br J Nutr 113, 654–664.

56.

Ofei

, Mikkelsen

, Scheller

(2019) Validation of a novel image-weighed technique for monitoring food intake and estimation of portion size in hospital settings: A pilot study. Public Health Nutr 22, 1203–1208.

57.

Forster

, Gariballa

(2005) Age as a determinant of nutritional status: A cross sectional study. Nutr J 4, 28.

58.

Morris

, Hope

, Fairburn

(1989) Eating habits in dementia. A descriptive study. Br J Psychiatry 154, 801–806.

59.

Salminen

, Suominen

, Kautiainen

, Roitto

, Pitkala

(2019) Energy intake and severity of dementia are both associated with health-related quality of life among older long-term care residents. Nutrients 11, 2261.

60.

Doorduijn

, van de Rest

, van der Flier

, Visser

, de

van der Schueren MAE

(2019) Energy and protein intake of Alzheimer’s disease patients compared to cognitively normal controls: Systematic review. J Am Med Dir Assoc 20, 14–21.

61.

Bauer

, Biolo

, Cederholm

, Cesari

, Cruz-Jentoft

, Morley

, Phillips

, Sieber

, Stehle

, Teta

, Visvanathan

, Volpi

, Boirie

(2013) Evidence-based recommendations for optimal dietary protein intake in older people: A position paper from the PROT-AGE Study Group. J Am Med Dir Assoc 14, 542–559.

62.

Roberts

, Roberts

, Geda

, Cha

, Pankratz

, O’Connor

, Knopman

, Petersen

(2012) Relative intake of macronutrients impacts risk of mild cognitive impairment or dementia. J Alzheimers Dis 32, 329–339.

63.

Stolk

, Breteler

, Ott

, Pols

, Lamberts

, Grobbee

, Hofman

(1997) Insulin and cognitive function in an elderly population. The Rotterdam Study. Diabetes Care 20, 792–795.

64.

Yaffe

, Lindquist

, Schwartz

, Vitartas

, Vittinghoff

, Satterfield

, Simonsick

, Launer

, Rosano

, Cauley

, Harris

(2011) Advanced glycation end product level, diabetes, and accelerated cognitive aging. Neurology 77, 1351–1356.

65.

Reddy

, Zhu

, Perry

, Smith

(2009) Oxidative stress in diabetes and Alzheimer’s disease. J Alzheimers Dis 16, 763–774.

66.

Gentreau

, Chuy

, Féart

, Samieri

, Ritchie

, Raymond

, Berticat

, Artero

(2020) Refined carbohydrate-rich diet is associated with long-term risk of dementia and Alzheimer’s disease in apolipoprotein E ɛ4 allele carriers. Alzheimers Dement 16, 1043–1053.

67.

Wolf-Klein

, Silverstone

, Lansey

, Tesi

, Ciampaglia

, O’Donnell

, Galkowski

, Jaeger

, Wallenstein

, Leleiko

(1995) Energy requirements in Alzheimer’s disease patients. Nutrition 11, 264–268.

68.

Ahmed

, Landin-Romero

, Collet

, van der Klaauw

, Devenney

, Henning

, Kiernan

, Piguet

, Farooqi

, Hodges

(2017) Energy expenditure in frontotemporal dementia: A behavioural and imaging study. Brain 140, 171–183.

69.

Fullmer

, Benson-Davies

, Earthman

, Frankenfield

, Gradwell

, Lee

, Piemonte

, Trabulsi

(2015) Evidence analysis library review of best practices for performing indirect calorimetry in healthy and non-critically ill individuals. J Acad Nutr Diet 115, 1417–1446.e1412.

70.

Psota

, Chen

(2013) Measuring energy expenditure in clinical populations: Rewards and challenges. Eur J Clin Nutr 67, 436–442.

71.

Knight

, Verkhratsky

, Luckman

, Allan

, Lawrence

(2012) Hypermetabolism in a triple-transgenic mouse model of Alzheimer’s disease. Neurobiol Aging 33, 187–193.

72.

Bitar

, Fellmann

, Vernet

, Coudert

, Vermorel

(1999) Variations and determinants of energy expenditure as measured by whole-body indirect calorimetry during puberty and adolescence. Am J Clin Nutr 69, 1209–1216.

73.

Morio

, Beaufrère

, Montaurier

, Verdier

, Ritz

, Fellmann

, Boirie

, Vermorel

(1997) Gender differences in energy expended during activities and in daily energy expenditure of elderly people. Am J Physiol 273, E321–327.

74.

Lührmann

, Herbert

, Neuhäuser-Berthold

(2001) Effects of fat mass and body fat distribution on resting metabolic rate in the elderly. Metabolism 50, 972–975.

75.

Gaillard

, Alix

, Sallé

, Berrut

, Ritz

(2007) Energy requirements in frail elderly people: A review of the literature. Clin Nutr 26, 16–24.

76.

Henry

, Rees

(1991) New predictive equations for the estimation of basal metabolic rate in tropical peoples. Eur J Clin Nutr 45, 177–185.

77.

de Boer

, van Es

, Voorrips

, Blokstra

, Vogt

(1988) Energy metabolism and requirements in different ethnic groups. Eur J Clin Nutr 42, 983–997.

78.

Adzika Nsatimba

, Pathak

, Soares

(2016) Ethnic differences in resting metabolic rate, respiratory quotient and body temperature: A comparison of Africans and European Australians. Eur J Nutr 55, 1831–1838.

79.

Itoi

, Yamada

, Yokoyama

, Adachi

, Kimura

(2017) Validity of predictive equations for resting metabolic rate in healthy older adults. Clin Nutr ESPEN 22, 64–70.

80.

Kimm

, Glynn

, Aston

, Damcott

, Poehlman

, Daniels

, Ferrell

(2002) Racial differences in the relation between uncoupling protein genes and resting energy expenditure. Am J Clin Nutr 75, 714–719.

81.

Schonfeld-Warden

, Warden

(2002) Uncoupling proteins: A molecular basis for racial differences in energy expenditure (and obesity?). Am J Clin Nutr 75, 607–608.

82.

Alemán-Mateo

, Salazar

, Hernández-Triana

, Valencia

(2006) Total energy expenditure, resting metabolic rate and physical activity level in free-living rural elderly men and women from Cuba, Chile and México. Eur J Clin Nutr 60, 1258–1265.

83.

Heshka

, Yang

, Wang

, Burt

, Pi-Sunyer

(1990) Weight loss and change in resting metabolic rate. Am J Clin Nutr 52, 981–986.

84.

Doorduijn

, de van der Schueren

MAE

, van de Rest

, de Leeuw

, Hendriksen

HMA

, Teunissen

, Scheltens

, van der Flier

, Visser

(2020) Energy intake and expenditure in patients with Alzheimer’s disease and mild cognitive impairment: The NUDAD project. Alzheimers Res Therapy 12, 116.

85.

Johnson

, Coward-McKenzie

(2001) Energy requirement methodology. In Nutrition in the prevention and treatment of disease, eds. Coulston AM, Rock CL, Monsen ER, eds. Academic Press, San Diego, CA, pp. 31-42.

86.

CamNtech Ltd, The Actiheart user manual,CamNtech Ltd, https://www.camntech.com/Products/Actiheart/The%20Actiheart%20User%20Manual.pdf, 4 June 2020, Accessed 17 August 2020.

87.

Liu

, Woo

, Tang

, Ng

, Ip

, Yu

(2001) Assessment of total energy expenditure in a Chinese population by a physical activity questionnaire: Examination of validity. Int J Food Sci Nutr 52, 269–282.

88.

Farina

, Hughes

, Watts

, Lowry

(2019) Use of physical activity questionnaires in people with dementia: A scoping review. J Aging Phys Act 27, 413–421.

89.

Porter

, Nguo

, Collins

, Kellow

, Huggins

, Gibson

, Davidson

, Schoeller

, Prentice

, Neuhouser

, Snetselaar

, Truby

(2019) Total energy expenditure measured using doubly labeled water compared with estimated energy requirements in older adults (≥65 y): Analysis of primary data. Am J Clin Nutr 110, 1353–1361.

90.

Rheaume

, Riley

, Volicer

(1987) Meeting nutritional needs of Alzheimer patients who pace constantly. J Nutr Elder 7, 43–52.

91.

Prentice

, Leavesley

, Murgatroyd

, Coward

, Schorah

, Bladon

, Hullin

(1989) Is severe wasting in elderly mental patients caused by an excessive energy requirement?. {Age Ageing 18, 158–167.

92.

Moyle

, Jones

, Murfield

, Draper

, Beattie

, Shum

, Thalib

, O’Dwyer

, Mervin

(2017) Levels of physical activity and sleep patterns among older people with dementia living in long-term care facilities: A 24h snapshot. Maturitas 102, 62–68.

93.

Wang

, Fukagawa

, Hossain

, Ooi

(1997) Longitudinal weight changes, length of survival, and energy requirements of long term care residents with dementia. J Am Geriatr Soc 45, 1189–1195.

94.

Meijers

JMM

, Schols

JMGA

, Halfens

RJG

(2014) Malnutrition in care home residents with dementia. J Nutr Health Aging 18, 595–600.

95.

Singh

, Mulley

, Losowsky

(1988) Why are Alzheimer patients thin?. Age Ageing 17, 21–28.