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Year : 2019  |  Volume : 13  |  Issue : 1  |  Page : 43-47

Impact of body mass index on cognitive function among young adults

Physiotherapy Department, SPB Physiotherapy College, Surat, Gujarat, India

Date of Submission01-Oct-2018
Date of Acceptance14-Jan-2019
Date of Web Publication29-Jun-2019

Correspondence Address:
Dr. Salvi Shah
SPB Physiotherapy College, Ugat-Bhesan Road, Surat - 395 005, Gujarat
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/PJIAP.PJIAP_44_18

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BACKGROUND AND PURPOSE: Cognition is the mental action on the process of acknowledge and understanding through thought, experience, and sense. A glowing body of literature is binding that being overweight (OW) or obese (O) has an effect on cognition as well as on physical functioning. A better understanding of this relationship could help target psychological services and public health strategies more effectively. The aim of the present study was to find out the impact of body mass index (BMI) on cognitive function among young adults.
MATERIALS AND METHODS: A convenient sample of 300 participants aged between 18 and 24 years was selected for the study. Demographic data and anthropometric measurements were taken. After that, BMI was calculated for all participants and participants were divided into two groups: Group A (normal BMI, n = 150) and Group B (OW/O, n = 130). Twenty students were excluded from the study because of their underweight. Rest of the participants (n = 280) were asked to performed Rey Verbal Auditory Learning test (RVALT), Stroop test, and Trail Making test A and B.
STATISTICAL ANALYSIS: Unpaired t-test was used to find out a significant difference in cognitive functions among two groups.
RESULTS: It was found that cognition score (all three tests) obtained by normal BMI group was higher than score obtained by OW/O group (RVALT: P<0.0001, Stroop test: P<0.0001, Trail Making Test: Part A: P < 0.04 and for Part B: P < 0.0001).
CONCLUSION: The present study concluded that high BMI individuals have lower cognitive functions.

Keywords: Body mass index, cognition, young adults

How to cite this article:
Chauhan S, Shah S, Shah S. Impact of body mass index on cognitive function among young adults. Physiother - J Indian Assoc Physiother 2019;13:43-7

How to cite this URL:
Chauhan S, Shah S, Shah S. Impact of body mass index on cognitive function among young adults. Physiother - J Indian Assoc Physiother [serial online] 2019 [cited 2022 Jan 17];13:43-7. Available from: https://www.pjiap.org/text.asp?2019/13/1/43/261820

  Introduction Top

Cognition is the mental action or process of acquiring knowledge and understanding through thought, experience, and senses.[1] It encompasses process such as knowledge, attention, memory and working memory, judgment and evaluation, reasoning and computation, problem solving and decision-making, comprehension, and production of language.[2] Cognitive functions constitute processing, integration, storage and retrieval of information related to memory, attention, association, processing speed, perception, and executive function. Superior cognitive function is key to maintaining a high quality of life as it helps individuals carry out day-to-day activities.[3]

Obesity in youth has received significant attention, as being overweight or obese as a child or adolescent predicts being overweight or obese later in life.[4] Further, childhood and adult obesity have been associated with a number of long-term negative outcomes. Obesity has been determined to be a risk factor for several medical conditions, including hypertension, Type 2 diabetes, heart disease, sleep apnea, and cancer.[5] In addition, increased body mass index (BMI) has been linked to increased risk for the development of both dementia and Alzheimer's disease.[6]

Although the impact of a high BMI on the body of excess is well known and widely studied,[7],[8],[9] and similarly its impacts on health,[10] little is known about the consequences of being overweight or obese on cognitive function.[11] The diverse studies that have linked BMI to cognitive function observe that obesity in old age is associated with lower cognitive scores,[12],[13] but the association between these variables in aging is not yet fully understood. It has also been observed that a high BMI at around 40 years of age precedes a generally lower cognitive ability and cognitive decline in men and women.[14] Being underweight, overweight, or obese has been identified as a risk factor for dementia in old age.[15],[16],[17],[18]

To clarify whether cognition really depends on body mass or fatness in humans, an epidemiological setting comparing the cognitive pattern of participants with different BMI or body fat mass is the better approach. From the literature, conflicting results emerge. Till now, various studies have been done to determine the impact of BMI on cognitive function in children and elderly individuals, and most studies establish a relationship between obesity and cognition as risk factors for developing cognitive impairment; little is known about the impact of BMI on different cognitive functions in young adults.[19] Hence, the present study was undertaken.

  Materials and Methods Top

A convenient sample of 300 participants aged between 18 and 24 years was randomly selected from different colleges of Surat city (interior designing, physiotherapy, engineering, B. Sc., B.com., etc.), after receiving permission from the college. Participants (both males and females) who willing to participate in the study and able to write and read English language were selected for the study. Participants with color blindness, with any known neurological condition, and with any inability to follow test instructions were excluded from the study. All participants were asked to sign the consent form prior to participate in research study. Information about demographic data, educational status, and name of college were obtained from all eligible participants and after that anthropometric measurements such as weight, height, waist circumference, and hip circumference were taken.

Then, BMI was calculated for each participant. From 300 participants, 20 participants were underweight (BMI < 18), so they were not included in the study. The rest of the 280 students were divided into two groups as follows: Group A (normal BMI, n = 150) and Group B (over weight/obese, n = 130).[20]

All of the cognitive tests were performed in classroom. The information about the cognition tests was given to all participants. Participants performed Rey Verbal Auditory Learning test (RVALT), Stroop test, and Trail Making test A and B in randomized order. Reliability and validity of all the tests to measure cognition are good.[21],[22],[23]

RVALT was used to assess episodic memory. An auditory recording of 15 words (e.g., drum, bell, coffee, and school) was played. Immediately after the presentation, participants were asked to write down as many of the words they could remember in any order in 1 min. The list presentation and recall was repeated five times with different lists. After the completion of recording, the author counted and recorded how many words they remembered correctly and how many words they remembered incorrectly. The average between all six trials was calculated for each participant.[24]

Trail Making Test A and B was used to assess perceptual speed. Participants were shown a sample Part A. The author demonstrated the process of connecting the numbers in numerical order from 1 to 8 (sample A). After that, the author demonstrated Part B, which asks the participants to connect the numbers and letters in numerical and alphabetical order (e.g., 1-A-2-B-3-C-4-D etc.). The participants were given sample Part A and sample Part B and then asked to complete it knowing that it is not timed. If any errors were made, the author stopped the participant, addressed the error, and explained why it was wrong. Once they completed sample A and sample B correctly, participants were given Part A and Part B and asked to complete as fast and accurately as possible connecting the numbers. If any mistakes were made here, author stopped the participant and asked them to go back to the last correct circle and continue, while still the timing was noted. The author recorded the time.[24]

Stroop test: A variant of the Stroop test was used to assess executive functioning. First, participants were shown a piece of paper with 44 congruent color words (e.g., “RED” was in red ink) and asked to read as fast as possible. The author recorded the time. Next, the participants were presented with 44 incongruent color words (e.g., “RED” was in blue ink) and asked to read as fast as possible. If there were errors made in either the congruent or incongruent colour words, the author stopped the participant and asked the participant to start from the last correct word. The author recorded the time.[24]

Before performing the tests, the therapist explained each test and demonstrated it in a standardized manner to measure cognition. After performing the tests, the test results were noted by the therapist. All tests are time-based tests so that the time was noted by the therapist with the use of stopwatch. Verbal auditory learning test is the only test which was performed in the group and another two were performed individually in the sequence.

For RVALT score, the number of correct words (average of six trials), for Stroop test score, average of time for reading congruent color word list and incongruent color words list, and for Trail Mailing test score, timing for completing Part A and Part B were noted.

Then, all the data were entered in an Excel sheet. Statistical analysis was done using IBM SPSS 20. A statistical significance level of P < 0.05 was adopted for statistical tests.

  Results Top

A total of 280 participants (169 females and 111 males) were included in the present study. From that, 150 participants were having normal BMI (Group A) and 130 participants were overweight/obese (Group B). The mean age of all participants in Group A was 20.41 years, and for Group B, the mean age was 20.68 years. All the cognitive function tests (RVALT, Stroop test, and Trail Making test [task A and task B]) were performed by all the participants, and the results were noted by the therapist.

Unpaired t-test was used to find out a significant difference in cognitive function between the two groups.

Physical characteristics of all participants in Group A and Group B are shown in [Table 1] and [Table 2] which display the group statistics of age distribution among Group A and Group B. No significant difference was noted for age across the two groups. The mean value of three different cognitive tests for Group A and Group B is shown in [Table 3].
Table 1: Physical characteristics of Group A and Group B

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Table 2: The group statistics of age (years) distribution among Group A and Group B

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Table 3: Mean value of three different cognitive tests for Group A and Group B

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Results of the study showed that there is a significant difference in cognitive function (RVALT, Stroop test, and Trail Making test [Part A and Part B]) between Group A and Group B [Table 3].

  Discussion Top

Results of the present study showed that there was a significant difference between normal BMI and overweight/obese young adult's performance on different measures of cognitive functioning. Our results converge with previous studies, suggesting that overweight/obese individuals demonstrate less efficient cognitive flexibility, a key cognitive control function.[25] Previous studies demonstrated that higher BMI is associated with chronic low-grade inflammation and with augmented production of pro-inflammatory cytokines, which may account for the detrimental effect of dopaminergic-driven cognitive functions observed in obese and overweight individuals.[26],[27] It remains to be investigated whether the cognitive control deficits and associated neuronal dysfunctions [28],[29] observed in individuals with overweight and obesity play a causal role or are instead the consequence of these conditions.[30]

Emerging research proposes a range of plausible mechanisms that might contribute to an independent effect of overweight/obesity on cognitive function including structural brain changes,[31],[32] impaired cerebral metabolism,[33] elevated leptin,[34],[35] and inflammation.[36] Independent associations between obesity and structural brain changes including greater brain atrophy,[31],[32] decreased gray matter volumes,[31],[37] and increased white-matter hyperintensities [38] have been demonstrated. Furthermore, a negative relationship between prefrontal cerebral metabolism and BMI has been identified.[34] Leptin, a hormone contained in body fat, and thus found in greater levels in overweight/obese individuals, has been associated with impaired cognitive performance.[35],[36] While inflammatory proteins (e.g., c-reactive protein), found more commonly in overweight/obese individuals, have also been associated with lower cognitive scores among obese females,[39] inflammatory markers have also been linked with reduced total brain volume,[40] providing further evidence that neuronal degradation might be implicated in the obesity–cognition relationship.

One suggests a direct action of adiposity in neuronal tissue through pro-inflammatory mediators produced by adipocytes and endocrine messengers that respond to food ingestion. Adipose tissue is known as a source of pro-inflammatory cytokines in obese humans and in animal models due to receptor insensitivity to leptin. Most obese people have an altered adipose tissue function caused by the interaction of genetic and environmental factors, which lead to hypertrophy, hypoxia, and a variety of inflammatory processes in the adipose tissue. Visceral fat accumulation may be considered a consequence of a dysfunction of adipose tissue, characterized by changes in cell function, increased lipid storage, and secretion of pro-inflammatory molecules such as cytokines, and inflammatory and procoagulant peptides. One study found that levels of interleukins 1β correlated with adiposity and cognitive impairment. Inflammation, particularly chronic low-grade inflammation, seems to affect several brain functions, from the early development of the brain to the development of neurodegenerative and psychiatric diseases, associated with cognitive deficits and dementia.[41]

In summary, findings of the present study showed that individuals with high BMI may exhibit deficits on different measures of cognitive functioning (e.g., working memory [RVALT], attention, speed, and cognitive flexibility [Stroop test], and visual attention and task switching [Trail mailing test]). This further highlights the urgency to institute public health interventions to promote a healthy weight in young individuals.

One limitation of the study is that it was cross-sectional research. Cross-sectional research only allows for a brief glimpse into the lives of the participants and does not examine how the relationship between physical and behavioral variables affects change over time. Cognitive impairments have been indicated in a number of conditions comorbid with overweight and obesity (such as hypertension and sleep apnea), ones that were not assessed in this study. Diet quality and physical activity may influence cognitive control and weight status and warrant further investigation in relation to the role of cognitive control in overweight and obesity. Important consideration for future research is recent evidence that resistance training can improve cognitive function. Review of the literature suggests that strength training benefits general health as well as cognitive health. Based on the findings in the literature, it may be suggested that researchers in the future account for the aerobic capacity as well as resistance training status of each individual.

  Conclusion Top

The results of the present study concluded that overweight and obese participants have lower cognitive functions as compared to normal BMI individuals. Further research is needed to clarify the mechanism for the same and also for examining the link and directionality between cognition and childhood obesity. Future scope of the study is that the longitudinal study may be performed rather than cross sectional and a uniform method of cognitive function may be utilized for future intervention strategies.


Researchers would like to thank all the students, teachers, and principals of the colleges for their kind cooperation and valuable support required for the data collection.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Small DM. Individual differences in the neurophysiology of reward and the obesity epidemic. Int J Obes (Lond) 2009;33 Suppl 2:S44-8.  Back to cited text no. 1
Von Eckardt B. What is Cognitive Science?. Cambridge: MIT Press; 1995.  Back to cited text no. 2
Ball K, Brown W, Crawford D. Who does not gain weight? Prevalence and predictors of weight maintenance in young women. Int J Obes Relat Metab Disord 2002;26:1570-8.  Back to cited text no. 3
Painter, Kimberly N. Associations between elevated body mass index and cognitive functioning in adolescents (Doctoral dissertation, Pacific University) 2014.  Back to cited text no. 4
Bray GA. Medical consequences of obesity. J Clin Endocrinol Metab 2004;89:2583-9.  Back to cited text no. 5
Gustafson D, Rothenberg E, Blennow K, Steen B, Skoog I. An 18-year follow-up of overweight and risk of Alzheimer disease. Arch Intern Med 2003;163:1524-8.  Back to cited text no. 6
Bhurosy T, Jeewon R. Overweight and obesity epidemic in developing countries: A problem with diet, physical activity, or socioeconomic status? ScientificWorldJournal 2014;2014:964236.  Back to cited text no. 7
Solís-Ortiz S, Gutiérrez-Muñoz M, Morado-Crespo L, Trejo-Bahena SA, Kala L. Executive functions correlated with body mass index in overweight middle-aged women. Psychology 2016;7:410.  Back to cited text no. 8
Olaiz G, Rivera J, Shamah T, Rojas R, Villalpando S, Hernández M, et al. National health and nutrition survey. Cuernavaca, Morelos, Mexico: National Institute of Public Health; 2006.  Back to cited text no. 9
Zera C, McGirr S, Oken E. Screening for obesity in reproductive-aged women. Prev Chronic Dis 2011;8:A125.  Back to cited text no. 10
Porsteinsson AP, Drye LT, Pollock BG, Devanand DP, Frangakis C, Ismail Z, et al. Effect of citalopram on agitation in Alzheimer disease: The CitAD randomized clinical trial. JAMA 2014;311:682-91.  Back to cited text no. 11
Kivimäki M, Lawlor DA, Singh-Manoux A, Batty GD, Ferrie JE, Shipley MJ, et al. Common mental disorder and obesity: Insight from four repeat measures over 19 years: Prospective Whitehall II cohort study. BMJ 2009;339:b3765.  Back to cited text no. 12
Aslan AK, Starr JM, Pattie A, Deary I. Cognitive consequences of overweight and obesity in the ninth decade of life? Age Ageing 2015;44:59-65.  Back to cited text no. 13
Blakemore SJ, Burnett S, Dahl RE. The role of puberty in the developing adolescent brain. Hum Brain Mapp 2010;31:926-33.  Back to cited text no. 14
García-Ptacek S, Faxén-Irving G, Cermáková P, Eriksdotter M, Religa D. Body mass index in dementia. Eur J Clin Nutr 2014;68:1204-9.  Back to cited text no. 15
Anstey KJ, Cherbuin N, Budge M, Young J. Body mass index in midlife and late-life as a risk factor for dementia: A meta-analysis of prospective studies. Obes Rev 2011;12:e426-37.  Back to cited text no. 16
Chen YC, Chen TF, Yip PK, Hu CY, Chu YM, Chen JH, et al. Body mass index (BMI) at an early age and the risk of dementia. Arch Gerontol Geriatr 2010;50 Suppl 1:S48-52.  Back to cited text no. 17
Karunathilaka RN, Hewage DC, Wimalasekera SW, Amarasekara AA. Cognitive functions and body mass index: Is there a relationship? – Preliminary study among a sample of peri-urban young adults in Colombo district, Sri Lanka. Proceedings of 9th International Research Conference. Sri Lanka: KDU; 8th-9th September, 2016.  Back to cited text no. 18
Solís-Ortiz S, Gutiérrez-Muñoz M, Morado-Crespo L, Trejo-Bahena SA, Kala L. Executive functions correlated with body mass index in overweight middle-aged women. Psychology 2016;7:410.  Back to cited text no. 19
Santos R, Mota J. The ALPHA health-related physical fitness test battery for children and adolescents. Nutr Hosp 2011;26:1199-200.  Back to cited text no. 20
Paula JJ, Melo LP, Nicolato R, Moraes EN, Bicalho MA, Hamdan AC, et al. Reliability and construct validity of the Rey-auditory verbal learning test in Brazilian elders. Arch Clin Psychiatry (São Paulo) 2012;39:19-23.  Back to cited text no. 21
Siegrist M. Test-retest reliability of different versions of the Stroop test. J Psychol 1997;131:299-306.  Back to cited text no. 22
Wagner S, Helmreich I, Dahmen N, Lieb K, Tadic A. Reliability of three alternate forms of the trail making tests a and B. Arch Clin Neuropsychol 2011;26:314-21.  Back to cited text no. 23
Samantha R. Exercise and cognition in young adults. Psychological sciences undergraduate publications, Presentations and Projects; 2015.  Back to cited text no. 24
Miyake A, Friedman NP, Emerson MJ, Witzki AH, Howerter A, Wager TD, et al. The unity and diversity of executive functions and their contributions to complex “Frontal lobe” tasks: A latent variable analysis. Cogn Psychol 2000;41:49-100.  Back to cited text no. 25
Mathieu P, Lemieux I, Després JP. Obesity, inflammation, and cardiovascular risk. Clin Pharmacol Ther 2010;87:407-16.  Back to cited text no. 26
Felger JC, Hernandez CR, Miller AH. Levodopa reverses cytokine-induced reductions in striatal dopamine release. Int J Neuropsychopharmacol 2015;18. pii: pyu084.  Back to cited text no. 27
Volkow ND, Wang GJ, Telang F, Fowler JS, Goldstein RZ, Alia-Klein N, et al. Inverse association between BMI and prefrontal metabolic activity in healthy adults. Obesity (Silver Spring) 2009;17:60-5.  Back to cited text no. 28
Hsu CL, Voss MW, Best JR, Handy TC, Madden K, Bolandzadeh N, et al. Elevated body mass index and maintenance of cognitive function in late life: Exploring underlying neural mechanisms. Front Aging Neurosci 2015;7:155.  Back to cited text no. 29
Volkow ND, Wang GJ, Baler RD. Reward, dopamine and the control of food intake: Implications for obesity. Trends Cogn Sci 2011;15:37-46.  Back to cited text no. 30
Beck AT, Steer RA, Ball R, Ranieri W. Comparison of beck depression inventories –IA and -II in psychiatric outpatients. J Pers Assess 1996;67:588-97.  Back to cited text no. 31
Van der Does AJ, Williams JM. Leiden Index of Depression Sensitivity-Revised (LEIDS-R). Leiden University; 2003.  Back to cited text no. 32
Mathieu P, Lemieux I, Després JP. Obesity, inflammation, and cardiovascular risk. Clin Pharmacol Ther 2010;87:407-16.  Back to cited text no. 33
Mathieu P, Pibarot P, Larose E, Poirier P, Marette A, Després JP, et al. Visceral obesity and the heart. Int J Biochem Cell Biol 2008;40:821-36.  Back to cited text no. 34
Dantzer R. Cytokine-induced sickness behaviour: Mechanisms and implications. Ann N Y Acad Sci 2001;933:222-34.  Back to cited text no. 35
Hsu CL, Voss MW, Best JR, Handy TC, Madden K, Bolandzadeh N, et al. Elevated body mass index and maintenance of cognitive function in late life: Exploring underlying neural mechanisms. Front Aging Neurosci 2015;7:155.  Back to cited text no. 36
Baron-Cohen S, Wheelwright S, Skinner R, Martin J, Clubley E. The autism-spectrum quotient (AQ): Evidence from Asperger syndrome/high-functioning autism, males and females, scientists and mathematicians. J Autism Dev Disord 2001;31:5-17.  Back to cited text no. 37
Miller GE, Freedland KE, Carney RM, Stetler CA, Banks WA. Pathways linking depression, adiposity, and inflammatory markers in healthy young adults. Brain Behav Immun 2003;17:276-85.  Back to cited text no. 38
Hillman JB, Dorn LD, Bin Huang. Association of anxiety and depressive symptoms and adiposity among adolescent females, using dual energy X-ray absorptiometry. Clin Pediatr (Phila) 2010;49:671-7.  Back to cited text no. 39
Elena BA, Gabriela B, Andreea V, Tatar R, Daniela S, Tilea I, et al. Association between increased waist circumference and depression and anxiety trend. Acta Med Marisiensis 2015;61:87-90.  Back to cited text no. 40
Bhattacharya S, Sarkar A. Impact of Body Mass Index on Cognitive Attention Function in University Students. India; 19 April, 2017, 25 July, 2017.  Back to cited text no. 41


  [Table 1], [Table 2], [Table 3]

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