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Association Between BMI and Neurocognitive Functions Among Middle-aged Obese Adults: Preliminary Findings Using
Dipti Magan1, Raj Kumar Yadav2, Jitender Aneja3
1Department of Physiology, All India Institute of Medical Sciences, Bathinda, Punjab, India.
Background:
Studies suggest that obesity predisposes individuals to developing cognitive dysfunction and an increased risk of dementia, but the nature of the relationship remains largely unexplored for better prognostic predictors.
Purpose:
This study, the first of its kind in Indian participants with obesity, was intended to explore the use of quantification of different neurocognitive indices with increasing body mass index (BMI) among middle-aged participants with obesity. Additionally, machine-learning models were used to analyse the predictive performance of BMI for different cognitive functions.
Methods:
In the cross-sectional analytical study, a total of 137 (n = 137) participants were included. Out of the total, 107 healthy obese (BMI = 23.0-30.0 kg m-2; age between 36 and 55 years of both genders) were recruited from the out-patient department of the Department of Endocrinology and General Medicine, and 30 participants were recruited as the control group, between March 2023 to February 2024. The participants underwent neuropsychological assessments, including mini-mental state examination (MMSE), Montreal cognitive assessment (MoCA) and serum levels of brain-derived neurotrophic factor (BDNF).
Results:
Significant (p < .05) differences were observed for neurocognitive functions for the obese group versus the control group. According to the correlation heatmaps, BMI was significantly (p < .05) negatively associated with BDNF. Multivariate linear regression analysis revealed a substantial (p < .05) decline in BDNF with a change in BMI, accenting its significant impact on cognitive ageing. Additionally, consistent decreasing trends were observed across the MoCA and MMSE, confirming the robustness of the findings across diverse analytical methodologies. Furthermore, the linear regression model and super vector machine model contributed additional evidence to the consistency of the trends in cognitive decline linked to BMI variations.
Conclusion:
The preliminary results of the present study support that increased BMI is an important physiological indicator that influences neurocognition and neuroplasticity in individuals with obesity.
