Parkinson’s Disease and Food Expenditure in Italy: Stochastic and Non-Stochastic Analyses of Food Elements - Cornelli, Umberto; Iftime, Maria Daniela; Malnati, Sofia; Mandelli, Kevin; Masini, Chiara; Messina, Beatrice; Nebbia, Stefano; Piarulli, Gabriele; Piccinini, Daniele; Pelucchi, Francesca; Radici, Alessandro; Rattaggi, Matteo; et al. (European Journal of Applied Sciences, 2024)
Background: The correlation between food and Parkinson's disease (PD) shows that the Mediterranean diet (MeD) brings positive benefits. Objective: To find the correlation between PD and food components in the various regions of Italy in 2016. Methods: The protein, fat, mineral and vitamin content of 275 foods belonging to 56 distinct food categories were correlated with PD in terms of standardised mortality ratio (SMR). Data were computed for 19,500 families in 540 Italian municipalities for 2016. Life expectancy, demographic data and level of well-being were also analysed. Stochastic and non-stochastic analyses (neural network mapping) were used to compute the associations with PD. Results: The following results were obtained by focusing on the food components deemed significant in both stochastic and non-stochastic analyses: Alcohol, saturated and monounsaturated fats, calcium and sodium were found to be causative or partially causative factors. Soluble sugars, carbohydrates, starch, selenium and vitamin D were seen to be protective or partially protective. The SMR of PD was significantly lower in Southern Italy than in the North due to a lower consumption of causative foods and higher consumption of protective ones. Furthermore, the lower gross domestic product (GDP) in the South may also have a significant effect. Conclusions: In 2016, the PD death rate in Southern Italy was significantly lower than in the North. The food component pattern that emerged in Southern regions was also significantly different: a lower consumption of causative food components and higher consumption of protective ones together with a lower GDP and life expectancy. Using data on food expenditure and quantities enable us to track the correlation with PD SMR on an annual basis.