PDF(Pubmed)
Abstract：
This study aimed to compare the nutritional quality of beverages sold in Türkiye according to their labeling profiles. A total of 304 nonalcoholic beverages sold in supermarkets and online markets with the highest market capacity in Türkiye were included. Milk and dairy products, sports drinks, and beverages for children were excluded. The health star rating (HSR) was used to assess the nutritional quality of beverages. The nutritional quality of beverages was evaluated using a decision tree model according to the HSR score based on the variables presented on the beverage label. Moreover, confusion matrix tests were used to test the model\'s accuracy. The mean HSR score of beverages was 2.6±1.9, of which 30.2% were in the healthy category (HSR≥3.5). Fermented and 100% fruit juice beverages had the highest mean HSR scores. According to the decision tree model of the training set, the predictors of HSR quality score, in order of importance, were as follows: added sugar (46%), sweetener (28%), additives (19%), fructose-glucose syrup (4%), and caffeine (3%). In the test set, the accuracy rate and F1 score were 0.90 and 0.82, respectively, suggesting that the prediction performance of our model had the perfect fit. According to the HSR classification, most beverages were found to be unhealthy. Thus, they increase the risk of the development of obesity and other diseases because of their easy consumption. The decision tree learning algorithm could guide the population to choose healthy beverages based on their labeling information.
摘要：
这项研究旨在根据标签概况比较Türkiye出售的饮料的营养质量。包括在Türkiye市场容量最高的超市和在线市场上销售的304种非酒精饮料。牛奶和乳制品，运动饮料,儿童饮料被排除在外。健康之星评级（HSR）用于评估饮料的营养质量。根据基于饮料标签上呈现的变量的HSR评分,使用决策树模型评价饮料的营养质量。此外，混淆矩阵测试用于测试模型的准确性。饮料的平均HSR评分为2.6±1.9，其中30.2%属于健康类别（HSR≥3.5）。发酵和100%果汁饮料具有最高的平均HSR得分。根据训练集的决策树模型,高铁质量得分的预测因子，按重要性排序,如下：添加糖(46%)，甜味剂（28%），添加剂（19%），果糖葡萄糖浆（4%），咖啡因（3%）。在测试集中，准确率和F1评分分别为0.90和0.82，这表明我们的模型的预测性能具有完美的拟合。根据高铁分类，大多数饮料被发现是不健康的。因此，由于容易食用，它们增加了肥胖和其他疾病发展的风险。决策树学习算法可以指导人群根据标签信息选择健康饮料。
