PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 14, 2026Journal of Alzheimer s Disease0 citationsOpen Access

Risk Prediction Nomogram for Cognitive Impairment in Elderly Using Anthropometric Indices

Association of central adiposity indices with cognitive impairment in elderly populations: Development and validation of a risk prediction nomogram using NHANES and CHARLS cohorts

View Full Paper
Ask AI
Bookmark
Share

Authors

JCJie ChenJGJinzhi GuanYZYu Zhang

Discussion

Loading...

Member takes

Overview

Demonstrates a risk prediction nomogram for mild cognitive impairment in elderly populations, highlighting the role of central adiposity indices and training set data.

Key Points

  • The central aim is developing and validating a model to predict mild cognitive impairment in older adults using central adiposity indices.
  • Calculated five central adiposity indices using measurements from US adults over 60
  • Assessed cognitive performance with standardized neuropsychological tests
  • Divided participants into training (n = 1725) and validation (n = 739) sets
  • Utilized external cohort from China Health and Retirement Longitudinal Study (n = 536)
  • Employed LASSO selection for predictors in multivariable logistic regression
  • Identified positive relationships between ABSI, CoI, and WWI with MCI risk (p < 0.05)
  • Nomogram with ABSI showed strong AUC (0.861 training, 0.826 internal, 0.798 external)
  • Demonstrated precise calibration and good clinical utility
  • Confirmed central adiposity indices as independent risk factors for MCI

Cite This Study

Chen et al. (2026) studied this question.

synapsesocial.com/papers/69b4ba0818185d8a39802674https://doi.org/10.1177/13872877261424471
View Full Paper
Ask AI
Bookmark
Share