Annals of neurosciences
January 18, 2025 · via Europe PMC
Association Between BMI and Neurocognitive Functions Among Middle-aged Obese Adults: Preliminary Findings Using Machine-learning (ML)-based Approach.
Magan D, Yadav RK, Aneja J, Pandey S.
AI summary — for doctors, generated from the abstract only
In middle-aged Indian adults, higher BMI was associated with poorer neurocognitive scores in a preliminary machine learning analysis.
What was studied
A cross-sectional study of 137 participants (107 with obesity, 30 controls) with MMSE, MoCA and serum BDNF.
Key findings
- Associations between BMI and cognitive indices reported; specific statistics not fully captured in the abstract
- Machine learning models used to assess BMI's predictive performance
Clinical relevance
Preliminary findings only; cross-sectional design and truncated results limit interpretation.
Who should care
Limitations
Small sample; results largely not reported in the abstract.
BMI may relate to cognition in obesity, pending further study.
This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.
Abstract
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 p 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.
DOI
10.1177/09727531241307462
PMID
39834557
PMCID
PMC11742150
Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.
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