Li · Diabetes care 2017 · retrospective cohort study · n=16,706

Visit-to-Visit Variations in Fasting Plasma Glucose and HbA 1c Associated With an Increased Risk of Alzheimer Disease: Taiwan Diabetes Study.

Cited 82 times in the scientific literature.

Level 3 - non-randomized controlled study

Observational longitudinal cohort study with competing risk analysis.

PubMed 28705834 · doi:10.2337/dc16-2238 · record verified 2026-08-29

What was done

This cohort study analyzed 16,706 patients aged 60 years or older with type 2 diabetes mellitus (T2DM) and no baseline Alzheimer disease (AD) enrolled in Taiwan's National Diabetes Care Management Program. Visit-to-visit variability in fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c) was calculated using the coefficient of variation (CV). Extended Cox proportional hazards regression models accounting for competing mortality risks were used to assess the association between glycemic variability tertiles and incident AD over a median follow-up of 8.88 years, adjusting for sociodemographics, lifestyle factors, medication use, baseline glycemic values, and comorbidities.

What was found

Over median 8.88 years of follow-up, 831 incident AD cases were recorded (crude incidence rate 3.5 per 1,000 person-years). After full multivariable adjustment, both FPG CV and HbA1c CV independently predicted AD incidence: - Highest tertile of FPG CV: HR 1.27 (95% CI 1.06–1.52) - Highest tertile of HbA1c CV: HR 1.32 (95% CI 1.11–1.58)

Why it matters

This study shows that long-term fluctuation in glycemic control, independent of average HbA1c and FPG levels, is a distinct risk factor for developing Alzheimer disease in older adults with type 2 diabetes.

Limits

The observational design cannot establish causality or exclude residual confounding. Diagnosis of AD was based on clinical registry records rather than standardized prospective neurocognitive batteries, risking misclassification or underdetection of milder dementia cases. The findings from this Taiwanese cohort may not fully generalize to other populations or healthcare systems.

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