Nonlinear relationship between sleep quality and prevalence of type 2 diabetes: A cross-sectional study of community patients with chronic diseases.

The prevalence of type 2 diabetes among community-dwelling chronic disease patients in this sample was 62.64%.

• A total of 902 valid samples were included in the study.
• 565 of the 902 participants were cases of T2D.
• Participants were community-dwelling patients with chronic diseases recruited via questionnaire surveys.
• The study design was cross-sectional.

The average Pittsburgh Sleep Quality Index (PSQI) score among study participants was 11.11, indicating generally poor sleep quality in the sample.

• The PSQI was used as the measure of sleep quality.
• Higher PSQI scores indicate worse sleep quality.
• The mean score of 11.11 is above the commonly used clinical cutoff of 5, suggesting the sample had substantially impaired sleep.
• Sleep quality data were collected via questionnaire surveys.

A positive association was observed between higher PSQI scores and prevalence of T2D across all three regression models.

• Three logistic regression models were applied, all showing consistent positive associations.
• Descriptive and logistic regression analyses were conducted prior to restricted cubic spline (RCS) regression.
• The association held across models, suggesting robustness of the finding.
• Higher PSQI scores (indicating worse sleep quality) were associated with higher prevalence of T2D.

Restricted cubic spline regression confirmed a nonlinear dose-response relationship between sleep quality and T2D prevalence, with two inflection points identified at PSQI scores of 12 and 13.

• RCS regression was applied to explore a possible nonlinear dose-response relationship.
• Two inflection points were discerned at PSQI scores of 12 and 13.
• When PSQI score was greater than 12, the odds ratio (OR) increased with higher PSQI scores, 'suggesting a significant increase in the association with the prevalence of T2D.'
• When the PSQI score reached 13, the OR stabilized, 'indicating that the rate of increase in risk has slowed.'
• The authors describe this as a 'threshold range effect.'

The authors identified a high-risk subgroup of patients with PSQI scores ≥12 as potentially benefiting most from targeted sleep improvement interventions to reduce T2D prevalence.

• Community health practitioners are suggested to consider sleep quality assessment as a supplementary tool, particularly in patients with existing chronic conditions.
• Implementing targeted sleep improvement interventions in the subgroup with PSQI ≥12 'may hold substantial potential to be associated with reduced T2D prevalence.'
• The threshold effect at PSQI=12 was identified as the clinically meaningful cutpoint for identifying high-risk individuals.
• The study focused on community-dwelling chronic disease patients, which defines the target population for this recommendation.