College of Nursing and Medical College of Georgia, Augusta University, Augusta, GA 30912, USA.
Hull College of Business, Augusta University, Augusta, GA 30912, USA.
Nutrients. 2018 May 26;10(6):674. doi: 10.3390/nu10060674.
For personalized nutrition in preparation for precision healthcare, we examined the predictors of healthy eating, using the healthy eating index (HEI) and glycemic index (GI), in family-based multi-ethnic colorectal cancer (CRC) families. A total of 106 participants, 53 CRC cases and 53 family members from multi-ethnic families participated in the study. Machine learning validation procedures, including the ensemble method and generalized regression prediction, Elastic Net with Akaike's Information Criterion with correction and Leave-One-Out cross validation methods, were applied to validate the results for enhanced prediction and reproducibility. Models were compared based on HEI scales for the scores of 77 versus 80 as the status of healthy eating, predicted from individual dietary parameters and health outcomes. Gender and CRC status were interactive as additional predictors of HEI based on the HEI score of 77. Predictors of HEI 80 as the criterion score of a good diet included five significant dietary parameters (with intake amount): whole fruit (1 cup), milk or milk alternative such as soy drinks (6 oz), whole grain (1 oz), saturated fat (15 g), and oil and nuts (1 oz). Compared to the GI models, HEI models presented more accurate and fitted models. Milk or a milk alternative such as soy drink (6 oz) is the common significant parameter across HEI and GI predictive models. These results point to the importance of healthy eating, with the appropriate amount of healthy foods, as modifiable factors for cancer prevention.
为了在精准医疗中进行个性化营养，我们使用健康饮食指数 (HEI) 和血糖指数 (GI) 来研究基于家庭的多民族结直肠癌 (CRC) 家庭中健康饮食的预测因素。共有 106 名参与者，53 名 CRC 病例和 53 名来自多民族家庭的家庭成员参加了这项研究。应用了机器学习验证程序，包括集成方法和广义回归预测、带校正的 Akaike 信息准则的弹性网络和留一法交叉验证方法，以验证结果，提高预测和重现性。根据健康饮食指数的分数为 77 与 80 作为健康饮食状态，比较了基于个体饮食参数和健康结果预测的模型。性别和 CRC 状态是 77 分健康饮食指数的额外预测因素。作为良好饮食标准的 80 分健康饮食指数的预测因素包括五个显著的饮食参数（摄入量）：全水果（1 杯）、牛奶或豆奶等牛奶替代品（6 盎司）、全谷物（1 盎司）、饱和脂肪（15 克）和油和坚果（1 盎司）。与 GI 模型相比，HEI 模型呈现出更准确和拟合的模型。牛奶或豆奶等牛奶替代品（6 盎司）是 HEI 和 GI 预测模型共有的显著参数。这些结果表明，适量摄入健康食品作为癌症预防的可改变因素，健康饮食的重要性。
