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. 2022 Jul 24;14(15):3034. doi: 10.3390/nu14153034

Figure 1.

Figure 1

Figure 1

Figure 1

Odds ratios for obesity for four combinations of quartiles of each of food groups. (A). Odds ratios for obesity according to the combination of vegetables and fruits in quartiles by multi-logistic regression analysis. To investigate the interaction between vegetables and fruits in relation to obesity, 16 groups were formed by combining vegetables and fruits by quartiles. Multiple logistic regression analysis was used to investigate the odds ratios (OR) for obesity, with the reference group being the top quartile. (B). Odds ratios for obesity according to the combination of vegetables and soybeans/soy products in quartiles by multi-logistic regression analysis. To investigate the interaction between vegetables and soybeans/soy products in relation to obesity, 16 groups were formed by combining vegetables and soybeans/soy products by quartiles. Multiple logistic regression analysis was used to investigate the odds ratios (OR) for obesity, with the reference group being the top quartile. (C). Odds ratios for obesity according to the combination of fruits and soybeans/soy products in quartiles by multi-logistic regression analysis. To investigate the interaction between fruits and soybeans/soy products in relation to obesity, 16 groups were formed by combining fruits and soybeans/soy products by quartile. Multiple logistic regression analysis was used to investigate the odds ratios (OR) for obesity, with the reference group being the top quartile. (D). Odds ratios for obesity according to the combination of fruits and sweets in quartiles by multi-logistic regression analysis. To investigate the interaction between fruits and sweets in relation to obesity, 16 groups were formed by combining fruits and sweets by quartiles. Multiple logistic regression analysis was used to investigate the odds ratios (OR) for obesity, with the reference group for fruits being the top quantile and that for sweets being the bottom quantile.