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Principal Component Analysis Applied to Alzheimerâ??s Disease in the USA

Bodo Parady

Principal Component Analysis (PCA) of Alzheimer’s disease (AD) and twelve epidemiological and socio-economic components of the USA states inform etiology by extracting large scale patterns. The components were selected from those having statistically significant correlations suggested by published clinical or epidemiological analysis, or from general social status and welfare measures. The twelve components demonstrate simple pair wise Pearson correlations to AD, and then are analyzed by PCA for loadings associated with AD. Repetitive factor analysis and the culling of questionable data reduced the factors (all per capita) associated with AD to two. The first principal component combines dentists and wine consumption, and the second component combines beer consumption and dentists. Dentists and wine are likely associated with reduced AD incidence because of the known inverse association with elevated education. Dental care is known to be inversely associated with AD incidence. The second factor reflects the known association of AD with periodontitis. Periodontitis suggests that the cerebral pathogenesis of fungal/bacterial biofilm components are enabled by transmigration and immunosuppression associated with poor iodine status aggravated by high beer consumption.

Отказ от ответственности: Этот реферат был переведен с помощью инструментов искусственного интеллекта и еще не прошел проверку или верификацию