
==== Front
J Educ Health Promot
J Educ Health Promot
JEHP
J Edu Health Promot
Journal of Education and Health Promotion
2277-9531
2319-6440
Wolters Kluwer - Medknow India

JEHP-13-197
10.4103/jehp.jehp_1458_23
Original Article
Body mass index and cognitive functioning decline: Exploring the relationship
Kaur Tanveer 1
Ranjan Piyush 3
Kaloiya Gauri S. 4
Bhatia Harpreet 1
Baboo Ananta G. K. 3
Rawat Nandini 3
Upadhyay Ashish D. 5
Chopra Sakshi 2
Anwar Wareesha 2
Sarkar Siddharth 4
1 Department of Psychology, University of Delhi, India
2 Department of Home Science, University of Delhi, India
3 Department of Medicine, AIIMS, New Delhi, India
4 Department of Psychiatry, AIIMS, New Delhi, India
5 Department of Biostatistics, AIIMS, New Delhi, India
Address for correspondence: Dr. Piyush Ranjan, Professor Department of Medicine, AIIMS, New Delhi, India. E-mail: drpiyushdost@gmail.com
2024
05 7 2024
13 19711 9 2023
05 12 2023
Copyright: © 2024 Journal of Education and Health Promotion
2024
https://creativecommons.org/licenses/by-nc-sa/4.0/ This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
BACKGROUND:

Cognitive functions may play an important role in the management of obesity by promoting compliance towards lifestyle-related behaviours. This study aimed to identify cognitive deficits among adults and examine their association across different Body Mass Index (BMI) categories in an Indian setting.

MATERIALS AND METHODS:

The study is a cross-sectional survey of a sample attending a tertiary care hospital in northern India. The Montreal Cognitive Assessment (MoCA) scale was administered as part of an interview schedule to evaluate participants’ cognitive performance across eight domains. The responses were analyzed to investigate the association between BMI and total MoCA scores, as well as domain-specific MoCA scores.

RESULTS:

Three hundred forty-nine participants, with a mean age of 36.9 ± 10.9 years and a BMI of 26.7 ± 4.6 kg/m2, were recruited. BMI was found to be significantly associated with the total MoCA score, indicating a negative relationship (P < 0.001). A significant negative association was found between six domain-specific scores, namely visuospatial, attention, language, abstraction, delayed recall (P < 0.001), orientation (P < 0.05), and BMI.

CONCLUSION:

An association between BMI and cognitive functioning (both overall and domain-specific) was observed, showing a dose-effect relationship. In these cases, visuospatial, attention, language, abstraction, delayed recall, and orientation were found to be affected.

Cognitive functioning
metabolic syndrome
MoCA
obesity
==== Body
pmcIntroduction

The interplay between cognitive decline and increased BMI has received considerable attention. Research indicates a bidirectional relationship, where diminished cognitive functions can increase the likelihood of unhealthy eating and exercise habits, potentially leading to higher BMI. Notably, obese individuals exhibit significant cognitive decline, especially in domains concerning executive control, working memory, and attention bias.[1,2,3]

However, the complex relationship between cognitive functions and BMI is influenced by population characteristics which includes social, demographic, and cultural dynamics. Notably, such a relationship has not been thoroughly explored within the Asian population. This study aims to (i) assess cognitive deficits across different BMI categories (underweight, normal, overweight), (ii) assess the dose-effect correlation between cognitive deficits and BMI, and (iii) investigate the associations between cognitive deficits and socio-demographic/cultural factors within the Indian context. By shedding light on this under-researched area, this study provides valuable insights into the cognitive-BMI landscape in the Indian context.

Materials and Methods

Study Design

A cross-sectional interview-based study was conducted from November 2021 to March 2022 within outpatient settings at a tertiary care hospital in northern India. The study, approved by the Institute Ethics Committee (IECPG-610/28.10.2021), adhered to STROBE guidelines.[4]

Sample Size

Sample size determination utilized an existing Indian study by Patel and Parikh, considering a correlation (r) of -0.174 between cognitive function and BMI. Employing the formula N = [(Zα+Zβ)/C]² +3, accounting for error rates (α, β), and C, yielded a population sample of 343.[5]

Participant Identification and Characteristics: Adult participants (18–60 years) with BMI ≥18.5 and ≤39.9 kg/m², capable of understanding Hindi or English, were included. Exclusions comprised individuals with end-stage organ disease and psychiatric conditions (e.g., depression, schizophrenia). Among the 384 invited participants, 35 were excluded, resulting in 349 participants [Figure 1].

Figure 1 Sample collection chart

Survey Questionnaire

The questionnaire encompassed Patient Information Sheet (PIS), Patient Informed Consent Form (PICF), demographic data and the Montreal Cognitive Assessment (MoCA),[6] assessing cognitive performance across eight domains, namely, visuospatial, naming, attention, language, abstraction, delayed recall, orientation, and memory.

Data Collection

Demographic questionnaire and MoCA

Two trained psychologists conducted interviews utilizing standardized MoCA administration guidelines. MoCA score categories were defined as: severe deficit (<10), moderate deficit (10–17), mild deficit (18–25), and normal (>26).

Anthropometric measurements

Weight and height were measured using digital scales and stadiometers. BMI was calculated using the weight (kg)/height (m²) formula.

Statistical Analysis

Descriptive statistics for categorical and continuous variables were employed. Correlation, Kruskal–Wallis tests, and regression analysis were performed to explore BMI-MoCA relationships. Stata 17 software was used for analysis. The significance level was set at P ≤ 0.05.

Results

Sample Description

The mean age was 36.97 ± 10.95 years, with 53.30% males, 46.42% from the middle, and 44.13% from the lower socioeconomic strata (Kuppuswamy scale).[7] Most participants were overweight or obese (BMI >23 kg/m²) as per the Asia-Pacific guidelines.[8]

MoCA Performance Scores

MoCA’s mean score was 19.59 ± 4.79 (range: 4–30). Only 12.89% scored within normal limits; 57.02% fell in the mild deficit range (18–25). The description of the various cognition domains has been presented.

Association of BMI and Total MoCA Performance Scores

Univariate regression showed a significant negative association between BMI and total MoCA scores (B = −0.27, SE = 0.05, P < 0.001, CI: −0.38 to −0.17) after adjusting for confounders. Multivariate analysis remained significant (B = −0.17, SE = 0.05, P < 0.001, CI: −0.27 to −0.07).

Association of BMI and Domain-Specific MoCA Performance Scores

Dose-effect correlation between BMI categories (underweight, overweight, obese) and domain-specific scores is shown in Table 1 An inverse relation between MoCA domain scores and BMI emerged. A negative association was significant in visuospatial, attention, language, abstraction, and delayed recall (P < 0.001); naming and orientation had no significant relationship. The findings are presented in Table 1.

Table 1 Relation between BMI and various cognitive domains (Mean±SD)

BMI	V	N	A	L	A	D	O	1 and 2	1 and 3	1 and 4	1 and 5	2 and 3	2 and 4	2 and 5	3 and 4	3 and 5	4 and 5	
Underweight (1)	2.72 (1.48)	2.36 (0.67)	3.72 (1.79)	1.63 (1.20)	1.18 (0.87)	3.09 (1.37)	5.54 (1.21)	n.s.	n.s.	n.s.	0.05	n.s.	0.001	0.001	0.01	0.001	n.s.	
Normal (2)	2.73 (1.45)	2.63 (0.51)	4.27 (1.62)	1.5 (1.11)	1.10 (0.77)	3.05 (1.67)	5.83 (0.47)	n.s.	n.s.	n.s.	n.s.	n.s.	n.s.	0.01	n.s.	0.01	0.01	
Overweight (3)	2.69 (1.46)	2.67 (0.55)	4.46 (1.62)	1.34 (0.92)	1.09 (0.77)	2.90 (1.68)	5.76 (0.89)	n.s.	n.s.	n.s.	n.s.	n.s.	n.s.	0.001	0.05	0.001	0.01	
Obese grade 1 (4)	2.14 (2.26)	2.59 (0.58)	3.91 (1.57)	1.02 (0.96)	0.90 (0.76)	2.45 (1.57)	5.66 (0.76)	n.s.	n.s.	0.05	0.05	n.s.	0.01	0.01	0.05	0.05	n.s.	
Obese grade 2 (5)	1.83 (1.32)	2.35 (0.72)	3.35 (1.64)	0.96 (0.90)	0.65 (0.72)	2.24 (1.63)	5.59 (0.98)	n.s.	n.s.	n.s.	0.05	n.s.	0.05	0.001	n.s.	0.001	0.05	
P	0.001	n.s.	0.001	0.001	0.001	0.001	n.s.	n.s.	n.s.	n.s.	n.s.	n.s.	n.s.	n.s.	n.s.	n.s.	n.s.	
V=visuospatial, N=naming, A=attention, L=language, A=abstract, D=delayed recall, O=orientation, BMI=body mass index, SD=standard deviation

Correlation Between Domain-Specific Scores and BMI

A significant negative correlation between BMI and six domains: visuospatial, attention, language, delayed memory, abstraction (P < 0.001), and orientation (P < 0.05) was found, as shown in Table 2.

Table 2 Spearman rho correlation for BMI and various cognitive domains

Domains	BMI	P	
Visuospatial	–0.24	0.001	
Naming	–0.09	n.s.	
Attention	–0.19	0.001	
Language	–0.18	0.001	
Abstraction	–0.20	0.001	
Delayed recall	–0.32	0.001	
Orientation	–0.10	0.05	

Association of MoCA Performance Scores and Demographics

Being female (P < 0.001), married (P < 0.001), and having lower socioeconomic status (P < 0.001) were significantly associated with greater deficits in total scores.

Discussion

Cognitive mechanisms play a pivotal role in shaping weight-related behaviours, yet their interaction with obesity remains complex and multifaceted, warranting exploration across diverse demographic and cultural contexts.

Our cross-sectional study aimed to investigate the association between cognitive decline, as measured by MoCA performance, and different BMI categories in the Indian adult population. Our findings highlight a significant positive association between cognitive decline and BMI, indicating a direct correlation. Consistent with the existing literature, we found that lower MoCA scores were associated with higher BMI in Indian adults.[9] Notably, a dose-effect relationship was observed, showing a linear decline in MoCA scores as BMI increased, even after adjusting for potential confounders. This aligns with studies conducted across various cultures and demographics.[10,11]

Notably, our analysis revealed specific cognitive domains that are significantly associated with obesity. Six out of the eight MoCA domains showed a positive correlation with BMI, especially in executive function, memory, attention, language, abstraction, and delayed memory. The significance of executive function lies in regulating eating behaviours and compliance, which affects BMI.[12] Attention and working memory impairments in individuals with higher BMI indicate a predisposition toward calorie-dense food cues, aligning with tendencies toward impulsivity.[13]

Furthermore, we identified gender and economic disparities in trends of cognitive decline. Women showed more significant cognitive decline as their BMI increased, reflecting global trends.[14] Lower economic strata participants also exhibited more cognitive decline, possibly due to limited resources such as access to education, healthcare disparities, lifestyle factors, and social interactions.[14]

Several studies have attempted to explore the relationship between obesity and cognitive decline among various population groups. The results have consistently shown an association between obesity and cognitive decline. A study by Quaye et al., (2022) revealed that participants with a higher BMI had significantly lower global cognition scores compared to normal-weight adults. Another study conducted in the United Kingdom by Cheke et al., (2016) also revealed similar findings. However, this relationship has not yet been explored within the Asian population group.[9,15]

Our study has implications for weight management strategies, suggesting that cognitive retraining may enhance interventions, particularly for women and economically disadvantaged individuals.[16,17,18] Further investigation is necessary to explore the reciprocal relationship between cognitive decline and BMI, as well as the specific cognitive domains involved. The study has limitations, such as potential selection bias and a cross-sectional design, which impact causal inferences. Nevertheless, our findings provide valuable insights into the intricate relationship between cognitive function and obesity within the Indian context.

Financial support and sponsorship

The study is supported by KIRAN Division of Department of Science and Technology, Government of India under Cognitive Science Research Initiative Program.

Conflicts of interest

There are no conflicts of interest.
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