TY - JOUR
T1 - Influence of sociodemographic factors on eating motivations–modelling through artificial neural networks (ANN)
AU - Guiné, Raquel P.F.
AU - Ferrão, Ana Cristina
AU - Ferreira, Manuela
AU - Correia, Paula
AU - Mendes, Mateus
AU - Bartkiene, Elena
AU - Szűcs, Viktória
AU - Tarcea, Monica
AU - Sarić, Marijana Matek
AU - Černelič-Bizjak, Maša
AU - Isoldi, Kathy
AU - EL-Kenawy, Ayman
AU - Ferreira, Vanessa
AU - Klava, Dace
AU - Korzeniowska, Małgorzata
AU - Vittadini, Elena
AU - Leal, Marcela
AU - Frez-Muñoz, Lucia
AU - Papageorgiou, Maria
AU - Djekić, Ilija
PY - 2020/5
Y1 - 2020/5
N2 - This study aimed at investigating the influence of some sociodemographic factors on the eating motivations. A longitudinal study was carried conducted with 11960 participants from 16 countries. Data analysis included t-test for independent samples or ANOVA, and neural network models were also created, to relate the input and output variables. Results showed that factors like age, marital status, country, living environment, level of education or professional area significantly influenced all of the studied types of eating motivations. Neural networks modelling indicated variability in the food choices, but identifying some trends, for example the strongest positive factor determining health motivations was age, while for emotional motivations was living environment, and for economic and availability motivations was gender. On the other hand, country revealed a high positive influence for the social and cultural as well as for environmental and political and also for marketing and commercial motivations.
AB - This study aimed at investigating the influence of some sociodemographic factors on the eating motivations. A longitudinal study was carried conducted with 11960 participants from 16 countries. Data analysis included t-test for independent samples or ANOVA, and neural network models were also created, to relate the input and output variables. Results showed that factors like age, marital status, country, living environment, level of education or professional area significantly influenced all of the studied types of eating motivations. Neural networks modelling indicated variability in the food choices, but identifying some trends, for example the strongest positive factor determining health motivations was age, while for emotional motivations was living environment, and for economic and availability motivations was gender. On the other hand, country revealed a high positive influence for the social and cultural as well as for environmental and political and also for marketing and commercial motivations.
KW - cross-cultural survey
KW - Food choice
KW - healthy diet
KW - neuronal modelling
U2 - 10.1080/09637486.2019.1695758
DO - 10.1080/09637486.2019.1695758
M3 - Article
AN - SCOPUS:85075738373
SN - 0963-7486
VL - 71
SP - 614
EP - 627
JO - International Journal of Food Sciences and Nutrition
JF - International Journal of Food Sciences and Nutrition
IS - 5
ER -