Attentional performance and body composition in older adults with preserved cognition and mild cognitive impairment: a comparative and association study

Abstract

Background: Neurocognitive disorders are of great public health importance due to population aging. Early identification for timely intervention remains a challenge, highlighting the need for biomarkers and tests capable of detecting early changes. Phase angle (PhA), a marker of cellular integrity, and computerized attention tests have been studied as useful tools in this scenario. Objective: To compare attentional performance using the Computerized Visual Attention Test (CVAT) and body composition by bioelectrical impedance analysis (BIA), highlighting PhA, in older adults with preserved cognition and mild cognitive impairment, as well as to investigate associations between body composition and attention parameters. Methods: An ongoing cross-sectional study including 39 participants to date. Cognitive assessment was performed using the Clinical Dementia Rating (CDR). Only individuals with scores of 0 and 0.5 were included, and CDR 1 was excluded due to insufficient sample size (n=1), resulting in a final sample of 38 older adults. Attentional performance was evaluated by CVAT, providing omission errors (OE), commission errors (CE), reaction time (RT), and reaction time variability (RTV). Body composition was assessed using the BIODYNAMICS MODEL 450 device, providing measurements of PhA, reactance, and lean mass percentage (LM%). Student's t-test and Mann-Whitney U test were used for between-group comparisons, and Spearman's correlation for association analysis, with a 5% significance level. Results: The sample consisted of 38 participants, with a mean age of 74.11±8.7 years (60-97 years), 86.8% (n=33) female and 13.2% (n=5) male. Groups were divided into CDR 0 (n=15; age 74±9.1 years; education 8.13±4.01 years) and CDR 0.5 (n=23; age 74.17±8.6 years; education 10.43±2.9 years). No significant differences were observed between groups for PhA (5.9±0.64 vs 6.19±0.87; p=0.298), RT (p=0.910), and RTV (p=0.934). Non-normal variables, expressed as median [P25-P75], also did not differ between groups: LM% (65.8 [60-74.8] vs. 69.1 [64.6-71.2]; p=0.460), OE (8 [1-15] vs. 2 [1-9]; p=0.235), and CE (6 [2-7] vs 3 [1-5]; p=0.101). However, Spearman's correlation revealed a significant negative association between LM% and RT (ρ = -0.324; p = 0.048) and a trend toward a negative correlation between PhA and reaction time variability (ρ = -0.305; p = 0.062). Conclusion: In the studied sample, bioimpedance and attention parameters did not show significant differences between older adults with preserved cognition and mild cognitive impairment. However, the association between lean mass percentage and reaction time indicates that the decline in body composition is related to the slowing of attentional processing in aging. Increasing the sample size is necessary to define whether such markers can distinguish the early stages of cognitive impairment.