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ABSTRACT: Background
We investigated the association between various food groups and obesity in Japanese patients with type 2 diabetes.Methods
2070 patients with type 2 diabetes who attended 26 diabetes clinics throughout Japan were analyzed and were divided into obese and non-obese groups. Intakes of food groups determined by a food frequency questionnaire were compared. Odds ratios for obesity for quartiles of individual food groups were calculated using a logistic regression model.Results
Non-obese patients consumed a larger variety of food groups than obese patients, with the diets of non-obese individuals closer to the traditional Japanese diet characterized by fish, seaweed, and soybeans/soy products. Among 21 food groups, low vegetable intake and high sweets intake were the most strongly associated with obesity in both men and women. Low intake of both fruits and vegetables and the combination of high intake of sweets and low intake of fruits were associated with obesity.Conclusions
Food groups and their combinations that were strongly associated with obesity in Japanese patients with type 2 diabetes were identified. Our findings also suggested an inverse association between the traditional Japanese diet and obesity.
SUBMITTER: Hatta M
PROVIDER: S-EPMC9331232 | biostudies-literature | 2022 Jul
REPOSITORIES: biostudies-literature
Hatta Mariko M Horikawa Chika C Takeda Yasunaga Y Ikeda Izumi I Yoshizawa Morikawa Sakiko S Kato Noriko N Kato Mitsutoshi M Yokoyama Hiroki H Kurihara Yoshio Y Maegawa Hiroshi H Fujihara Kazuya K Sone Hirohito H
Nutrients 20220724 15
<h4>Background</h4>We investigated the association between various food groups and obesity in Japanese patients with type 2 diabetes.<h4>Methods</h4>2070 patients with type 2 diabetes who attended 26 diabetes clinics throughout Japan were analyzed and were divided into obese and non-obese groups. Intakes of food groups determined by a food frequency questionnaire were compared. Odds ratios for obesity for quartiles of individual food groups were calculated using a logistic regression model.<h4>R ...[more]