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https://doi.org/10.1038/s43587-021-00138-z

has been cited by the following article:

• TITLE: Alzheimer’s Disease: An Analysis of Gender Effects

  AUTHORS: James M. Gregory

  KEYWORDS: Gender Effects, Alzheimer’s Disease, Dementia, Mathematical Modeling, Statins, Viagra, Cholesterol, Unsaturated Fat Diets

  JOURNAL NAME: Journal of Behavioral and Brain Science, Vol.12 No.10, October 9, 2022

  ABSTRACT: Alzheimer’s disease is a dreaded outcome that affects both men and women in later years of life. While root causes of this form of dementia are not clear, various factors are known that contribute to the risk of development and the reduction in risks based on gender and our choices in life. This paper evaluates the various factors that affect the risks of developing Alzheimer’s disease as we age. The focus of this paper is gender considerations in a mathematical model programmed in Excel. The model was first presented by Gregory [1] and was calibrated on one of the original population data sets with 50 - 50 male and female participants. This model overpredicted the risks for women and underpredicted the risks for men. A solution to this problem was found based on published values of sex hormones for men and women. Based on the expanded current model, two major factors contribute to the gender differences in predictions: gender factor values (10.5 ml·kg-1·min-1 for men and 3.5 ml·kg-1·min-1 for women) used in VO2max equations and a sex hormone factor that changes as hormones change for men and women with age. Smoking differences associated with gender and the risk associated with smoking was added to the model. Cognitive reserve based on education differences between men and women was also added. These are minor components compared to hormone effects. The expanded model includes an input for unsaturated fat diets and cholesterol reducing medications and use of Viagra by men that is known to reduce risk of developing Alzheimer’s disease. Predictions from the expanded model closely matched measured values from age 50 through age 95 for each gender with R2 values of 0.99, which were highly significant (p = 0.001). The expanded model predictions matched the reduced lifetime risk for men and women associated with a data set that included a population with the opportunity to use statins and Viagra. The expanded model seems to work well for both men and women.