Abstract
Introduction: Obesity impacts quality of life, healthcare resource utilization and survival. Obesity-related inflammation is linked to metabolic syndrome, cardiovascular disease and cancer. Inflammatory cytokines have also been shown to interact with the central nervous system influencing neural activity, cognition, and behavior. Despite reports of obesity affecting cognition on psychometric tests, there is no current standard for assessment of obesity-related neurologic impairment. We used an eye-movement-based “oculometric” assessment task to quantify aspects of dynamic vision, indicators of functional neurological performance. Methods: After informed consent, we collected data from 19 participants using a validated, non-invasive, oculometric device (neuroFit ONE) that uses eye movements to assess dynamic vision. We excluded patients with a history of cirrhosis (including liver transplant and hepatic encephalopathy), cognitive brain disease, individuals with ongoing alcohol or illicit substance abuse. Oculometrics included smooth pursuit latency, acceleration, gain, proportion smooth pursuit, saccadic amplitude, direction noise, speed tuning responsiveness and noise, which we combined into a composite score (nFit). We ran two analyses: first, we stratified by body mass index (BMI) and compared all raw oculometrics and nFit; second, we ran correlation between BMI and oculometric performance. Results: Baseline demographics included age (median 51 years; range 23-76 years), sex (50% female), BMI (median 25.1; range 17.1-39.2), and years of education (mean 16.8 years ± 1.4). Participants with elevated BMI exhibited impairment in all domains of dynamic vision as compared to those with a normal BMI, although not all impairments reached significance (Table 1). Impairment was most pronounced in the direction noise domain (7.78 degrees vs. 14.36 degrees, p=0.0002). A significant negative correlation was observed between BMI and nFit, our composite oculometric score (Pearson's R, r=-0.59, p<0.01)[Figure 1].1031_A Figure 1. Comparison of Dynamic Visual Processing Metrics by Body Mass IndexConclusion: In our sample, we observed an effect of BMI on visual processing. It remains unclear if this functional neurological impairment is related to obesity-related central nervous system inflammation, subclinical liver disease (fatty liver, nonalcoholic steatohepatitis, cirrhosis), or both. Oculometrics may provide new biomarkers of brain health in obese patients.1031_B Figure 2. Correlation Between Body Mass Index and the nFit Composite of Dynamic Vision
Published Version
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