India’s geriatric population is projected to reach 319 million by 2050, reflecting the global aging trend. Cognitive impairment significantly impacts the quality of life of older adults. Anthropometric measures serve as accessible indicators of nutritional status and body composition with potential associations with cognitive function. This study investigates the relationship between anthropometric measures and cognitive abilities using the Indian Council of Medical Research (ICMR)-Multilingual Dementia Research and Assessment (MUDRA) Toolbox among geriatric populations in Gorakhpur, Uttar Pradesh.
Methods
This cross-sectional study enrolled 1013 participants aged 60 years and above from 7 randomly selected administrative blocks in Gorakhpur. Cognitive assessment was performed using the ICMR-MUDRA Toolbox, evaluating global cognition, attention, executive functioning, episodic memory, language, and visuospatial abilities. Anthropometric measurements included height, weight, BMI, waist circumference, hip circumference, Waist-to-Hip Ratio (WHR), and Mid-Upper Arm Circumference (MUAC). Statistical analysis included Spearman rank correlation and binomial logistic regression.
Results
Significant positive correlations were observed between MUAC and cognitive domains of the MUDRA toolbox. Conversely, WHR demonstrated significant negative correlations with the domains (P ≤ 0.05). Participants with moderate-risk WHRs had higher odds of impairment in attention/executive function (aOR = 1.79), memory (aOR = 1.69), and visuospatial function (aOR = 2.50), while high-risk WHRs were associated with greater impairment in memory (aOR = 2.18) and language (aOR = 2.21).
Conclusion
This study reveals significant relationships between anthropometric measures and cognitive function in the geriatric population, with MUAC positively correlating with cognitive performance while WHR demonstrating negative correlations. The findings indicate that central obesity may be a particular risk factor for cognitive decline.
JayanandanRRamasubramanianRSanthanamRS. A cross-sectional study on prevalence of cognitive impairment and its associated factors among the elderly in an urban area of Chennai, India. Int J Community Med Public Health. 2020;7(12):5126-5133.
5.
SobralAIGD Pde AraújoCMTSobralMFF. Mild cognitive impairment in the elderly Relationship between communication and functional capacity. Dement Neuropsychol. 2018;12(2):165-172.
6.
GorelickPBScuteriABlackSE, et al.Vascular contributions to cognitive impairment and dementia. Stroke. 2011;42(9):2672-2713.
7.
MohanDIypeTVargheseSUshaAMohanM. A cross-sectional study to assess prevalence and factors associated with mild cognitive impairment among older adults in an urban area of Kerala, South India. BMJ Open. 2019;9(3):e025473.
8.
SenguptaPBenjaminAISinghYGroverA. Prevalence and correlates of cognitive impairment in a north Indian elderly population. WHO South East Asia J Public Health. 2014;3(2):135-143.
9.
CornierMADesprésJPDavisN, et al.Assessing adiposity: a scientific statement from the American Heart Association. Circulation. 2011;124(18):1996-2019.
NguyenJCDKillcrossASJenkinsTA. Obesity and cognitive decline: role of inflammation and vascular changes. Front Neurosci. 2014;8:375.
12.
MillerAASpencerSJ. Obesity and neuroinflammation: a pathway to cognitive impairment. Brain Behav Immun. 2014;42:10-21.
13.
AttiARPalmerKVolpatoSWinbladBDe RonchiDFratiglioniL. Late-life body mass index and dementia incidence: nine-year follow-up data from the Kungsholmen Project. J Am Geriatr Soc. 2008;56(1):111-116.
14.
GeorgieffMK. Nutrition and the developing brain: nutrient priorities and measurement. Am J Clin Nutr. 2007;85(2):614S-620S.
15.
WhitmerRAGundersonEPQuesenberryCPZhouJYaffeK. Body mass index in midlife and risk of Alzheimer disease and vascular dementia. Curr Alzheimer Res. 2007;4(2):103-109.
16.
AnsteyKJCherbuinNBudgeMYoungJ. Body mass index in midlife and late-life as a risk factor for dementia: a meta-analysis of prospective studies. Obes Rev. 2011;12(5):e426-e437.
17.
ChenXLiuZSachdevPSKochanNAO’LearyFBrodatyH. Dietary patterns and cognitive health in older adults: findings from the Sydney memory and ageing study. J Nutr Health Aging. 2021;25(2):255-262.
18.
BajpaiNSachsJDholakiaRH. Improving Access and Efficiency in Public Health Services: Mid-term Evaluation of India’s National Rural Health Mission; 2010:1.
19.
MenonRNVargheseFPaplikarA, et al.Validation of Indian Council of medical research neurocognitive tool box in diagnosis of mild cognitive impairment in India: lessons from a harmonization process in a linguistically diverse society. Dement Geriatr Cogn Disord. 2020;49(4):355-364.
20.
VermaMTripathiMNehraA, et al.Validation of ICMR neurocognitive toolbox for dementia in the linguistically diverse context of India. Front Neurol. 2021;12:661269.
21.
PanditPKumariRTripathiAMishraP. Cognitive functioning among community-dwelling older adults in rural population of Lucknow and its association with comorbidities. Indian J Psychol Med. 2024;46(4):338-343.
22.
NasreddineZSPhillipsNABédirianV, et al.The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695-699.
23.
RoyMMolnarF. Systematic review of the evidence for Trails B cut-off scores in assessing fitness-to-drive. Can Geriatr J. 2013;16(3):120-142.
24.
McDonnellMDillLPanosS, et al.Verbal fluency as a screening tool for mild cognitive impairment. Int Psychogeriatr. 2020;32(9):1055-1062.
25.
AlegretMEspinosaAValeroS, et al.Cut-off scores of a brief neuropsychological battery (NBACE) for Spanish individual adults older than 44 years old. PLoS One. 2013;8(10):e76436.
26.
MailletDMatharanFLe ClésiauH, et al.TNI-93: a new memory test for dementia detection in illiterate and low-educated patients. Arch Clin Neuropsychol. 2016;31(8):896-903.
27.
PaplikarAIyerGKVargheseF, et al.A screening tool to detect stroke aphasia: adaptation of Frenchay Aphasia Screening Test (FAST) to the Indian context. Ann Indian Acad Neurol. 2020;23(Suppl 2):S143-S148.
28.
LuvizuttoGJFogaroliMOTheotonioRMde Moura NetoEde Carvalho NunesHRBazanR. Norm scores of cancelation and bisection tests for unilateral spatial neglect: data from a Brazilian population. Clinics. 2020;75:e1468.
29.
DaltonMCameronAJZimmetPZ, et al.Waist circumference, waist-hip ratio and body mass index and their correlation with cardiovascular disease risk factors in Australian adults. J Intern Med. 2003;254(6):555-563.
30.
UtkualpNErcanI. Anthropometric measurements usage in medical sciences. BioMed Res Int. 2015;2015:404261.
31.
DwivediLKBanerjeeKSharmaR, et al.Quality of anthropometric data in India’s National Family Health Survey: disentangling interviewer and area effect using a cross-classified multilevel model. SSM Popul Health. 2022;19:101253.
32.
VermaMDasMSharmaPKapoorNKalraS. Epidemiology of overweight and obesity in Indian adults - a secondary data analysis of the national family health surveys. Diabetes Metab Syndr. 2021;15(4):102166.
33.
GambhirISKhuranaVKishoreDSinhaAKMohapatraSC. A clinico-epidemiological study of cognitive function status of community-dwelling elderly. Indian J Psychiatry. 2014;56(4):365-370.
34.
MenonJKantipudiSJVinothSKuchipudiJD. Prevalence of subjective cognitive decline and its association with physical health problems among urban community dwelling elderly population in South India. Alzheimers Dement. 2025;21(2):e14505.
35.
PhilipAJJohnsF. Prevalence of cognitive defects among senior inmates of old-age homes in a district of South Kerala. Cureus. 2024;16(7):e65082.
36.
BhatiaMSSrivastavaSMoondV. Prevalence of cognitive dysfunction, psychological morbidity and abuse in the community-based elderly population in India. Gen Psychiatr. 2020;33(5):e100207.
37.
PanghalCBelsiyalCXRawatVSDharM. Impact of cognitive impairment on activities of daily living among older adults of North India. J Fam Med Prim Care. 2022;11(11):6909-6915.
38.
KaurASonalAGhoshTAhamedF. Cognitive reserve and other determinants of cognitive function in older adults: insights from a community-based cross-sectional study. J Fam Med Prim Care. 2023;12(9):1957-1964.
39.
KondaPRSharmaPKGandhiARGangulyE. Correlates of cognitive impairment among Indian urban elders. J Gerontol Geriatr Res. 2018;7(6):489.
40.
SpanglerHBLynchDHHowardAG, et al.Association between mid-arm muscle circumference and cognitive function: a longitudinal study of Chinese adults. J Geriatr Psychiatry Neurol. 2024;37(4):272-281.
41.
CarrilloJÁZafrillaMPMarhuendaJ. Cognitive function and consumption of fruit and vegetable polyphenols in a young population: is there a relationship?Foods. 2019;8(10):507.
42.
BhagwasiaMRaoARBanerjeeJ, et al.Association between cognitive performance and nutritional status: analysis from LASI-DAD. Gerontol Geriatr Med. 2023;9:23337214231194965.
43.
WestNAHaanMN. Body adiposity in late life and risk of dementia or cognitive impairment in a longitudinal community-based study. J Gerontol A Biol Sci Med Sci. 2009;64(1):103-109.
44.
Rodríguez-FernándezJMDaniesEMartínez-OrtegaJChenWC. Cognitive decline, body mass index, and waist circumference in community-dwelling elderly participants. J Geriatr Psychiatry Neurol. 2017;30(2):67-76.
45.
RoyA. Association between body mass index and cognitive function among older adults in India: findings from a cross-sectional study. Exp Aging Res. 2024;50(1):102-116.
46.
LassekWDGaulinSJC. Waist-hip ratio and cognitive ability: is gluteofemoral fat a privileged store of neurodevelopmental resources?Evol Hum Behav. 2008;29(1):26-34.
47.
BooranasuksakulUMacdonaldIAStephanBCMSiervoM. Body composition, sarcopenic obesity, and cognitive function in older adults: findings from the national health and nutrition examination Survey (NHANES) 1999-2002 and 2011-2014. J Am Nutr Assoc. 2024;43(6):539-552.
48.
BatsisJAHaudenschildCRothRM, et al.Incident impaired cognitive function in sarcopenic obesity: data from the national health and aging trends survey. J Am Med Dir Assoc. 2021;22(4):865-872.e5.
49.
GottesmanRFSchneiderALCAlbertM, et al.Midlife hypertension and 20-year cognitive change: the atherosclerosis risk in communities neurocognitive study. JAMA Neurol. 2014;71(10):1218-1227.
50.
JoyceOCMcHughCMocklerDWilsonFKellyÁM. Midlife hypertension is a risk factor for some, but not all, domains of cognitive decline in later life: a systematic review and meta-analysis. J Hypertens. 2024;42(2):205-223.
51.
Interactive effect of central obesity and hypertension on cognitive function in older out-patients with Type 2 diabetes - PubMed [Internet]. [cited 2025 Apr 16]. Available from. https://pubmed.ncbi.nlm.nih.gov/19046243/
52.
BaoJLiuJLiZ, et al.Relationship between hypertension and cognitive function in an elderly population: a population-based study in rural northern China. Front Neurol. 2022;13:885598.
53.
FarronMRKabetoMULevineDAWixomCRLangaKM. Blood pressure and cognitive function among older adults in India. J Int Med Res. 2022;50(1):03000605211068720.
54.
NganduTLehtisaloJSolomonA, et al.A 2 year multidomain intervention of diet, exercise, cognitive training, and vascular risk monitoring versus control to prevent cognitive decline in at-risk elderly people (FINGER): a randomised controlled trial. Lancet. 2015;385(9984):2255-2263.
55.
KobayashiLCMateenFJMontanaL, et al.Cognitive function and impairment in older, rural South African adults: evidence from “health and aging in Africa: a longitudinal study of an INDEPTH community in rural South Africa.”. Neuroepidemiology. 2019;52(1–2):32-40.
56.
GardenerSLRainey-SmithSR. The role of nutrition in cognitive function and brain ageing in the elderly. Curr Nutr Rep. 2018;7(3):139-149.
57.
KeyMNSzabo-ReedAN. Impact of diet and exercise interventions on cognition and brain health in older adults: a narrative review. Nutrients. 2023;15(11):2495.
