Spatial distribution and differences of stroke occurrence in the Rhone department of France (STROKE 69 cohort).
Julie FreyssengeFlorent RenardCarlos El KhouryLaurent DerexAnne TermozAmine ChakirMarion DouplatEstelle BravantAnne-Marie SchottKarim TazarourtePublished in: Scientific reports (2020)
In France, 110,000 patients are admitted to hospital per year for stroke. Even though the relationship between stroke and risk factors such as low socio-economic status is well known, research in the spatial distribution (SD) of stroke as a contributing risk factor is less documented. Understanding the geographic differences of the disease may improve stroke prevention. In this study, a statistical spatial analysis was performed using a French cohort (STROKE 69) to describe spatial inequalities in the occurrence of stroke. STROKE 69 was a cohort study of 3,442 patients, conducted in the Rhône department of France, from November 2015 to December 2016. The cohort included all consecutive patients aged 18 years or older, with a likelihood of acute stroke within 24 hours of symptoms onset. Patients were geolocated, and incidence standardized rates ratio were estimated. SD models were identified using global spatial autocorrelation analysis and cluster detection methods. 2,179 patients were selected for analysis with spatial autocorrelation methods, including 1,467 patients with stroke, and 712 with a transient ischemic attack (TIA). Within both cluster detection methods, spatial inequalities were clearly visible, particularly in the northern region of the department and western part of the metropolitan area where rates were higher. Geographic methods for SD analysis were suitable tools to explain the spatial occurrence of stroke and identified potential spatial inequalities. This study was a first step towards understanding SD of stroke. Further research to explain SD using socio-economic data, care provision, risk factors and climate data is needed in the future.
Keyphrases
- atrial fibrillation
- risk factors
- end stage renal disease
- ejection fraction
- chronic kidney disease
- cerebral ischemia
- newly diagnosed
- healthcare
- risk assessment
- prognostic factors
- peritoneal dialysis
- palliative care
- physical activity
- chronic pain
- depressive symptoms
- climate change
- big data
- patient reported outcomes
- blood brain barrier
- deep learning
- subarachnoid hemorrhage
- health insurance