Research on body composition and fat distribution in Alzheimer's disease (AD) has presented conflicting findings.
Objective
Compare body composition and anthropometric measurements in older adults with and without AD.
Methods
A systematic review and meta-analysis were conducted following Cochrane guidelines and PRISMA standards. MEDLINE, Embase, Scopus, LILACS, WPRIM, and the Spanish Bibliographic Index of Health Sciences were searched up to September 2024, considering observational studies that compared body composition between AD groups and controls. Outcomes included body fat percentage, body mass index (BMI), impedance, resistance, and reactance. The methodological quality and level of evidence were assessed using the Joanna Briggs Institute scale and GRADE, respectively. A random-effects meta-analysis model was used to calculate mean differences (MD).
Results
Fourteen studies involving 2761 older adults were included. Older adult women with AD showed a lower body fat percentage (p < 0.01; MD = −5.07) and BMI (p = 0.05; MD = −1.28) compared to controls. Older adult men with AD had higher impedance (p = 0.01; MD = 2.05), resistance (p = 0.02; MD = 45.10), and lower reactance (p = 0.03; MD = −2.05) compared to controls. No significant differences in body fat percentage or BMI were found between older adults with and without AD, regardless of gender.
Conclusions
Women with AD showed lower body fat percentage and BMI, while men with AD had higher impedance, resistance, and lower reactance. These factors should be included in geriatric assessments for AD patients, though further research is needed to understand their link to cognitive outcomes in AD.
WinbladBAmouyelPAndrieuS, et al.Defeating Alzheimer’s disease and other dementias: a priority for European science and society. Lancet Neurol2016; 15: 455–532.
2.
Soria LopezJAGonzálezHMLégerGC. Alzheimer's disease. Handb Clin Neurol2019; 167: 231–255.
3.
FerriCPPrinceMBrayneC, et al.Global prevalence of dementia: a Delphi consensus study. Lancet2005; 366: 2112–2117.
4.
SchillingLPBalthazarMLFRadanovicM, et al.Diagnosis of Alzheimer's disease: recommendations of the Scientific Department of Cognitive Neurology and Aging of the Brazilian Academy of Neurology. Dement Neuropsychol2022; 16: 25–39.
5.
HintonBJFanBNgBK, et al.Dual energy X-ray absorptiometry body composition reference values of limbs and trunk from NHANES 1999-2004 with additional visualization methods. PLoS One2017; 12: e0174180.
6.
TaylorJLHollandDJCoombesJS, et al.Accuracy of dual-energy x-ray absorptiometry for assessing longitudinal change in visceral adipose tissue in patients with coronary artery disease. Int J Obes2021; 45: 1740–1750.
7.
KiliaanAJArnoldussenIACGustafsonDR. Adipokines: a link between obesity and dementia?Lancet Neurol2014; 13: 913–923.
8.
Prunet-MarcassusBCousinBCatonD, et al.From heterogeneity to plasticity in adipose tissues: site-specific differences. Exp Cell Res2006; 312: 727–736.
9.
SchwartzDHLeonardGPerronM, et al.Visceral fat is associated with lower executive functioning in adolescents. Int J Obes2013; 37: 1336–1343.
10.
YoonDHChoiSHYuJH, et al.The relationship between visceral adiposity and cognitive performance in older adults. Age Ageing2012; 41: 456–461.
11.
KanayaAMLindquistKHarrisTB, et al.Total and regional adiposity and cognitive change in older adults: the health, aging and body composition (ABC) study. Arch Neurol2009; 66: 329–335.
12.
UchidaKSugimotoTTangeC, et al.Association between abdominal adiposity and cognitive decline in older adults: a 10-year community-based study. J Nutr Health Aging2024; 28: 100175.
HigginsJPTGreenS. Cochrane handbook for systematic reviews of interventions, version 5.1.0. Oxford, UK: The Cochrane Collaboration, 2011.
15.
MoherDLiberatiATetzlaffJ, et al.Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Int J Surg2010; 8: 336–341.
16.
GuyattGHOxmanADVistGE, et al.GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ2008; 336: 924–926.
17.
KowalPDowdJE. Definition of an older or elderly person. Proposed working definition of an older person in Africa for the MDS Project. Geneva: World Health Organization, 2001.
18.
AromatarisELockwoodCPorrittK, et al.JBI Manual for evidence synthesis. Adelaide, Australia: JBI, 2024.
19.
BorensteinMHedgesLVHigginsJPT, et al.Introduction to meta-analysis. West Sussex, UK: John Wiley & Sons Ltd., 2011.
20.
HandollHHGSmithAF. How to perform a systematic review. Curr Anaesth Crit Care2004; 15: 227–234.
21.
DeeksJJHigginsJPAltmanDG, et al.Analysing data and undertaking meta-analyses. In: HigginsJPTThomasJChandlerJ (eds) Cochrane handbook for systematic reviews of interventions. Oxford, UK: The Cochrane Collaboration, 2019, pp.241–284.
22.
BrinkleyTELengIRegisterTC, et al.Changes in adiposity and cerebrospinal fluid biomarkers following a modified Mediterranean ketogenic diet in older adults at risk for Alzheimer’s disease. Front Neurosci2022; 16: 906539.
23.
SeoYKWonCWSohY, et al.Associations between body composition and cognitive function in an elderly Korean population: a cohort-based cross-sectional study. Medicine (Baltimore)2021; 100: e25027.
24.
MurataSOnoRSugimotoT, et al.Functional decline and body composition change in older adults with Alzheimer disease: a retrospective cohort study at a Japanese memory clinic. Alzheimer Dis Assoc Disord2021; 35: 36–43.
25.
CavazzottoTGde CamposCDVMazurCE, et al.Association between cognitive performance and sarcopenic obesity in older adults with Alzheimer’s disease. Dement Neuropsychol2022; 16: 28–32.
26.
McHughML. Interrater reliability: the kappa statistic. Biochem Med (Zagreb)2012; 22: 276–282.
27.
Gillette-GuyonnetSNourhashemiFAndrieuS, et al.Determination of appendicular muscle mass by dual energy X-ray absorptiometry method in women with sarcopenia and Alzheimer’s disease. J Nutr Health Aging2000; 4: 165–169.
28.
CovaIPomatiSMaggioreL, et al.Nutritional status and body composition by bioelectrical impedance vector analysis: a cross sectional study in mild cognitive impairment and Alzheimer’s disease. PLoS One2017; 12: e0171331.
29.
dos SantosTBNFonsecaLCTedrusGM, , et al.Alzheimer’s disease: nutritional status and cognitive aspects associated with disease severity. Nutr Hosp2018; 35: 1298–1304.
30.
BuffaRMereuRMPutzuPF, et al.Bioelectrical impedance vector analysis detects low body cell mass and dehydration in patients with Alzheimer’s disease. J Nutr Health Aging2010; 14: 823–827.
31.
BuffaRMereuEPutzuP, et al.Lower lean mass and higher percent fat mass in patients with Alzheimer’s disease. Exp Gerontol2014; 58: 30–33.
32.
SaragatBBuffaRMereuE, et al.Nutritional and psycho-functional status in elderly patients with Alzheimer’s disease. J Nutr Health Aging2012; 16: 231–236.
33.
ElmstahlSPeterssonMLiljaB, et al.Body composition in patients with Alzheimer’s disease and healthy controls. J Clin Exp Gerontol1992; 14: 17–31.
34.
RenvallMJSpindlerAANicholsJF, et al.Body composition of patients with Alzheimer’s disease. J Am Diet Assoc1993; 93: 47–52.
35.
AhmedRMLandin-RomeroRLiangCT, et al.Neural networks associated with body composition in frontotemporal dementia. Ann Clin Transl Neurol2019; 6: 1707–1717.
36.
LoskutovaNHoneaRAVidoniED, et al.Bone density and brain atrophy in early Alzheimer’s disease. J Alzheimers Dis2009; 18: 777–785.
37.
BurnsJMJohnsonDKWattsA, et al.Reduced lean mass in early Alzheimer disease and its association with brain atrophy. Arch Neurol2010; 67: 428–433.
38.
MartínISMBaratoVPOlivaSL, et al.Body composition, dietary, and gustatory function assessment in people with Alzheimer’s disease. Am J Alzheimers Dis Other Demen2018; 33: 508–515.
39.
DvorakRVPoehlmanET. Appendicular skeletal muscle mass, physical activity, and cognitive status patients with Alzheimer’s disease. Neurology1998; 51: 1386–1390.
40.
MereuESuccaVBuffaR, et al.Total body and arm bioimpedance in patients with Alzheimer’s disease. Exp Gerontol2018; 102: 145–148.
41.
ComptonJVan AmelsvoortTMurphyD. Mood, cognition and Alzheimer’s disease. Best Pract Res Clin Obstet Gynaecol2002; 16: 357–370.
42.
JanssenIHeymsfieldSBRossR. Low relative skeletal muscle mass (sarcopenia) in older persons is associated with functional impairment and physical disability. J Am Geriatr Soc2002; 50: 889–896.
43.
KimMSKimWJKheraAV, et al.Association between adiposity and cardiovascular outcomes: an umbrella review and meta-analysis of observational and Mendelian randomization studies. Eur Heart J2021; 42: 3388–3403.
44.
ReFOguntadeASBohrmannB, et al.Associations of general and central adiposity with hypertension and cardiovascular disease among south Asian populations: a systematic review and meta-analysis. BMJ Open2023; 13: e074050.
45.
StakosDAStamatelopoulosKBampatsiasD, et al.The Alzheimer’s disease amyloid-beta hypothesis in cardiovascular aging and disease. JACC Focus Seminar. J Am Coll Cardiol2020; 75: 952–967.
46.
Powell-WileyTMPoirierPBurkeLE, et al.Obesity and cardiovascular disease: a scientific statement from the American Heart Association. Circulation2021; 143: E984–E1010.
47.
Iso-MarkkuPKujalaUMKnittleK, et al.Physical activity as a protective factor for dementia and Alzheimer’s disease: systematic review, meta-analysis and quality assessment of cohort and case-control studies. Br J Sports Med2022; 56: 701–709.
48.
WallaceLMKTheouOGodinJ, et al.Investigation of frailty as a moderator of the relationship between neuropathology and dementia in Alzheimer’s disease: a cross-sectional analysis of data from the rush memory and aging project. Lancet Neurol2019; 18: 177–184.
49.
BuZHHuangALXueMT, et al.Cognitive frailty as a predictor of adverse outcomes among older adults: a systematic review and meta-analysis. Brain Behav2021; 11: e01926.
50.
BuchmanASWilsonRSBieniasJL, et al.Change in body mass index and risk of incident Alzheimer disease. Neurology2005; 65: 892–897.
51.
KimSKimJOKwonKJ, et al.Associations of truncal body composition with cognitive status in patients with dementia. Neurol Sci2021; 42: 209–214.
52.
SunJWenSZhouJ, et al.Association between malnutrition and hyperhomocysteine in Alzheimer’s disease patients and diet intervention of betaine. J Clin Lab Anal2017; 31: e22090.
53.
YuanSLarssonSC. Epidemiology of sarcopenia: prevalence, risk factors, and consequences. Metabolism2023; 144: 155533.
54.
UhlSSiddiqueSMMcKeeverL, et al.Malnutrition in hospitalized adults: A systematic review. Rockville, MD: Agency for Healthcare Research and Quality (US), 2021.
55.
KyleUGBosaeusIDe LorenzoAD, et al.Bioelectrical impedance analysis - Part I: review of principles and methods. Clin Nutr2004; 23: 1226–1243.
56.
HeymsfieldSBNuñezCTestolinC, et al.Anthropometry and methods of body composition measurement for research and field application in the elderly. Eur J Clin Nutr2000; 54: S26–S32.
57.
Camina MartínMAde Mateo SillerasBNescolarde SelvaL, et al.Bioimpedance vector analysis and conventional bioimpedance to assess body composition in older adults with dementia. Nutrition2015; 31: 155–159.
58.
JunMHKuBKimK, et al.A screening method for mild cognitive impairment in elderly individuals combining bioimpedance and MMSE. Front Aging Neurosci2024; 16: 1307204.
59.
KyleUGBosaeusIDe LorenzoAD, et al.Bioelectrical impedance analysis - Part II: utilization in clinical practice. Clin Nutr2004; 23: 1430–1453.
60.
KangSYKimYJJangW, et al.Body mass index trajectories and the risk for Alzheimer’s disease among older adults. Sci Rep2021; 11: 3087.
61.
WhiteHPieperCSchmaderK. The association of weight change in Alzheimer’s disease with severity of disease and mortality: a longitudinal analysis. J Am Geriatr Soc1998; 46: 1223–1227.
