Ulusal Amyotrofik Lateral Skleroz (ALS) Kayıt Risk Faktörü Anketi Verilerinin Ön Sonuçları.

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BackgroundThe National ALS Registry is made up of two components to capture amyotrophic lateral sclerosis (ALS) cases: national administrative databases (Medicare, Medicaid, Veterans Health Administration and Veterans Benefits Administration) and self-identified cases captured by the Registry's web portal. This study describes self-reported characteristics of U.S. adults with ALS using the data collected by the National ALS Registry web portal risk factor surveys only from October 19, 2010 through December 31, 2013.ObjectiveTo describe findings from the National ALS Registry's web portal risk factor surveys.MeasurementsThe prevalence of select risk factors among adults with ALS was determined by calculating the frequencies of select risk factors-smoking and alcohol (non, current and former) histories, military service and occupational history, and family history of neurodegenerative diseases such as ALS, Alzheimer's and/or Parkinson's.ResultsNearly half of survey respondents were ever smokers compared with nearly 41% of adults nationally. Most respondents were ever drinkers which is comparable to national estimates. The majority were light drinkers. Nearly one-quarter of survey respondents were veterans compared with roughly 9% of US adults nationally. Most respondents were retired or disabled. The industries in which respondents were employed for the longest time were Professional and Scientific and Technical Services. When family history of neurodegenerative diseases in first degree relatives was evaluated against our comparison group, the rates of ALS were similar, but were higher for Parkinson's disease, Alzheimer's disease and any neurodegenerative diseases.ConclusionsThe National ALS Registry web portal, to our knowledge, is the largest, most geographically diverse collection of risk factor data about adults living with ALS. Various characteristics were consistent with other published studies on ALS risk factors and will allow researchers to generate hypotheses for future research.

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