Association between diabetes and subsequent Parkinson disease: A record-linkage cohort study
- PMID: 29898968
- DOI: 10.1212/WNL.0000000000005771
Association between diabetes and subsequent Parkinson disease: A record-linkage cohort study
Abstract
Objective: To investigate the association between type 2 diabetes mellitus (T2DM) and subsequent Parkinson disease (PD).
Methods: Linked English national Hospital Episode Statistics and mortality data (1999-2011) were used to conduct a retrospective cohort study. A cohort of individuals admitted for hospital care with a coded diagnosis of T2DM was constructed, and compared to a reference cohort. Subsequent PD risk was estimated using Cox regression models. Individuals with a coded diagnosis of cerebrovascular disease, vascular parkinsonism, drug-induced parkinsonism, and normal pressure hydrocephalus were excluded from the analysis.
Results: A total of 2,017,115 individuals entered the T2DM cohort and 6,173,208 entered the reference cohort. There were significantly elevated rates of PD following T2DM (hazard ratio [HR] 1.32, 95% confidence interval [CI] 1.29-1.35; p < 0.001). The relative increase was greater in those with complicated T2DM (HR 1.49, 95% CI 1.42-1.56) and when comparing younger individuals (HR 3.81, 95% CI 2.84-5.11 in age group 25-44 years).
Conclusions: We report an increased rate of subsequent PD following T2DM in this large cohort study. These findings may reflect shared genetic predisposition and/or disrupted shared pathogenic pathways with potential clinical and therapeutic implications.
© 2018 American Academy of Neurology.
Comment in
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Reader response: Association between diabetes and subsequent Parkinson disease: A record-linkage cohort study.Neurology. 2019 May 7;92(19):925. doi: 10.1212/WNL.0000000000007458. Neurology. 2019. PMID: 31061216 No abstract available.
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Author response: Association between diabetes and subsequent Parkinson disease: A record-linkage cohort study.Neurology. 2019 May 7;92(19):925-926. doi: 10.1212/WNL.0000000000007459. Neurology. 2019. PMID: 31061217 No abstract available.
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