The Calculator of Anti-Alzheimer’s Diet. Macronutrients

Marcin Studnicki, Grażyna Woźniak and Dariusz Stępkowski

PLOS ONE, 2016, vol. 11, issue 12, 1-18

Abstract: The opinions about optimal proportions of macronutrients in a healthy diet have changed significantly over the last century. At the same time nutritional sciences failed to provide strong evidence backing up any of the variety of views on macronutrient proportions. Herein we present an idea how these proportions can be calculated to find an optimal balance of macronutrients with respect to prevention of Alzheimer’s Disease (AD) and dementia. These calculations are based on our published observation that per capita personal income (PCPI) in the USA correlates with age-adjusted death rates for AD (AADR). We have previously reported that PCPI through the period 1925–2005 correlated with AADR in 2005 in a remarkable, statistically significant oscillatory manner, as shown by changes in the correlation coefficient R (Roriginal). A question thus arises what caused the oscillatory behavior of Roriginal? What historical events in the life of 2005 AD victims had shaped their future with AD? Looking for the answers we found that, considering changes in the per capita availability of macronutrients in the USA in the period 1929–2005, we can mathematically explain the variability of Roriginal for each quarter of a human life. On the basis of multiple regression of Roriginal with regard to the availability of three macronutrients: carbohydrates, total fat, and protein, with or without alcohol, we propose seven equations (referred to as “the calculator” throughout the text) which allow calculating optimal changes in the proportions of macronutrients to reduce the risk of AD for each age group: youth, early middle age, late middle age and late age. The results obtained with the use of “the calculator” are grouped in a table (Table 4) of macronutrient proportions optimal for reducing the risk of AD in each age group through minimizing Rpredicted−i.e., minimizing the strength of correlation between PCPI and future AADR.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0168385

DOI: 10.1371/journal.pone.0168385

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