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Poor sleep quality (PSQI > 9.5) is associated with increased odds of fall history in older adults with type 2 diabetes

In a cross-sectional study of 60 participants (30 with T2DM, 30 controls), PSQI was the only variable significantly associated with fall status within the T2DM group (OR = 1.239, 95% CI: 1.033–1.488). ROC analysis showed PSQI had acceptable discriminative ability (AUC = 0.785, p = 0.010) with an optimal cut-off of 9.5, yielding 72.7% sensitivity and 84.2% specificity.

2 min readUpdated Aug 22, 20260 RCTsView structured evidence →
Evidence Score34/100
Human RCT☆☆☆☆☆
Meta-analysis☆☆☆☆☆
Mechanism★★★★★
Safety★★★★
Confidencelow

This article is automatically generated from the structured evidence profile behind the claim above. Scores reflect the quality and quantity of available research, not clinical advice.

Poor sleep quality (PSQI > 9.5) is associated with increased odds of fall history in older adults with type 2 diabetes The current body of evidence comprises 1 study. EvidenceHub rates the overall confidence at 34/100 (low).

The Claim

Poor sleep quality (PSQI > 9.5) is associated with increased odds of fall history in older adults with type 2 diabetes

This conclusion is most relevant to: Middle-aged and older adults (aged >50) with type 2 diabetes mellitus (n=30) and age- and gender-matched healthy controls (n=30).

What the Research Shows

The conclusion draws on 1 linked study. Highlights from the cited literature:

  • Dual-task timed up and go performance and sleep quality in relation to fall history in older adults with type 2 diabetes: a cross-sectional study. (Frontiers in public health, 2026) —

How It Works

The proposed biological pathway:

  • T2DM is associated with impairments in motor and cognitive function, increasing fall risk
  • Poor sleep quality may further impair cognitive and motor performance, increasing fall risk
  • PSQI score >9.5 identified as a critical threshold for fall risk
  • Fall risk in T2DM is multidimensional, with behavioral and psychological factors playing a key role

Who Might Benefit

Evidence fit by population:

  • Middle-aged and older adults (aged >50) with type 2 diabetes mellitus (n=30) and age- and gender-matched healthy controls (n=30)

Limitations & Caveats

Important context when interpreting this evidence:

  • Cross-sectional design prevents causal inference
  • Small sample size (n=60) and single-center study may limit generalizability
  • Fall history was self-reported, subject to recall bias
  • Potential unmeasured confounders (e.g., medication use, neuropathy severity) not accounted for

Frequently Asked Questions

What is the optimal PSQI cutoff for predicting fall risk in older adults with type 2 diabetes?

The study found a PSQI score greater than 9.5 to be the optimal cutoff, with 72.7% sensitivity and 84.2% specificity for identifying fallers.

Is poor sleep quality more important than mobility performance for fall risk in T2DM?

In this study, PSQI was the only significant predictor of fall status in logistic regression, while TUG-DT performance was not significantly associated with falls, suggesting sleep quality may be a stronger correlate.

How does TUG-DT performance differ between T2DM patients and healthy controls?

T2DM patients showed significantly impaired TUG-DT performance, with increased cognitive errors, cognitive pauses, and movement pauses compared to controls, indicating reduced functional mobility.

What lifestyle factors were associated with T2DM in this study?

Smoking and exercise behavior differed significantly between T2DM and control groups, but these were not significant predictors of fall status within the T2DM group.

References

  1. 1.Zhang X, Wang S, Sun C, Li S, Hu Y. “Dual-task timed up and go performance and sleep quality in relation to fall history in older adults with type 2 diabetes: a cross-sectional study..” Frontiers in public health, 2026. PMID: 42625614 DOI: 10.3389/fpubh.2026.1856870
Disclaimer: This article is auto-generated from structured research data for educational purposes only and is not medical advice. Evidence scores reflect the quality and quantity of available research, not clinical recommendations. Always consult a healthcare professional before starting any supplement or intervention.