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Beyond nutrient-based food indices: a data mining approach to search for a quantitative holistic index reflecting the degree of food processing and including physicochemical properties†
Food & Function ( IF 6.1 ) Pub Date : 2017-12-18 00:00:00 , DOI: 10.1039/c7fo01423f Anthony Fardet 1, 2, 3, 4, 5 , Sanaé Lakhssassi 1, 2, 3, 4, 5 , Aurélien Briffaz 6, 7, 8, 9
Food & Function ( IF 6.1 ) Pub Date : 2017-12-18 00:00:00 , DOI: 10.1039/c7fo01423f Anthony Fardet 1, 2, 3, 4, 5 , Sanaé Lakhssassi 1, 2, 3, 4, 5 , Aurélien Briffaz 6, 7, 8, 9
Affiliation
Processing has major impacts on both the structure and composition of food and hence on nutritional value. In particular, high consumption of ultra-processed foods (UPFs) is associated with increased risks of obesity and diabetes. Unfortunately, existing food indices only focus on food nutritional content while failing to consider either food structure or the degree of processing. The objectives of this study were thus to link non-nutrient food characteristics (texture, water activity (aw), glycemic and satiety potentials (FF), and shelf life) to the degree of processing; search for associations between these characteristics with nutritional composition; search for a holistic quantitative technological index; and determine quantitative rules for a food to be defined as UPF using data mining. Among the 280 most widely consumed foods by the elderly in France, 139 solid/semi-solid foods were selected for textural and aw measurements, and classified according to three degrees of processing. Our results showed that minimally-processed foods were less hyperglycemic, more satiating, had better nutrient profile, higher aw, shorter shelf life, lower maximum stress, and higher energy at break than UPFs. Based on 72 food variables, multivariate analyses differentiated foods according to their degree of processing. Then technological indices including food nutritional composition, aw, FF and textural parameters were tested against technological groups. Finally, a LIM score (nutrients to limit) ≥8 per 100 kcal and a number of ingredients/additives >4 are relevant, but not sufficient, rules to define UPFs. We therefore suggest that food health potential should be first defined by its degree of processing.
中文翻译:
超越基于营养的食品指数:一种数据挖掘方法,以寻找反映食品加工程度并包括理化性质的定量整体指数†
加工对食品的结构和组成均具有重大影响,因此对营养价值也具有重要影响。特别是,大量食用超加工食品会增加肥胖和糖尿病的风险。不幸的是,现有的食品指数仅关注食品的营养成分,而没有考虑食品的结构或加工程度。这项研究的目的是由此联系非营养食品特性(质地,水分活度(一w ^),血糖和饱足感(FF)以及保质期)至加工程度; 寻找这些特征与营养成分之间的联系;寻找整体的定量技术指标;并使用数据挖掘确定将食品定义为UPF的定量规则。在由在法国老年人280种最广泛消费的食品,选择了139固体/半固体食物用于质地和一瓦特的测量,并分级根据三度的处理。我们的研究结果表明,微创加工食品不太高血糖,更饱腹,有更好的营养轮廓,更高一w ^,与UPF相比,保质期短,最大应力更低,断裂能量更高。基于72种食物变量,多变量会根据其加工程度对差异化食物进行分析。然后,技术指标,包括食品营养成分,一个W¯¯,FF和结构参数,对技术组受试。最后,每100 kcal的LIM评分(要限制的养分)≥8,且许多成分/添加剂> 4是相关的规则,但不足以定义UPF。因此,我们建议应首先根据其加工程度确定食品健康潜力。
更新日期:2017-12-18
中文翻译:
超越基于营养的食品指数:一种数据挖掘方法,以寻找反映食品加工程度并包括理化性质的定量整体指数†
加工对食品的结构和组成均具有重大影响,因此对营养价值也具有重要影响。特别是,大量食用超加工食品会增加肥胖和糖尿病的风险。不幸的是,现有的食品指数仅关注食品的营养成分,而没有考虑食品的结构或加工程度。这项研究的目的是由此联系非营养食品特性(质地,水分活度(一w ^),血糖和饱足感(FF)以及保质期)至加工程度; 寻找这些特征与营养成分之间的联系;寻找整体的定量技术指标;并使用数据挖掘确定将食品定义为UPF的定量规则。在由在法国老年人280种最广泛消费的食品,选择了139固体/半固体食物用于质地和一瓦特的测量,并分级根据三度的处理。我们的研究结果表明,微创加工食品不太高血糖,更饱腹,有更好的营养轮廓,更高一w ^,与UPF相比,保质期短,最大应力更低,断裂能量更高。基于72种食物变量,多变量会根据其加工程度对差异化食物进行分析。然后,技术指标,包括食品营养成分,一个W¯¯,FF和结构参数,对技术组受试。最后,每100 kcal的LIM评分(要限制的养分)≥8,且许多成分/添加剂> 4是相关的规则,但不足以定义UPF。因此,我们建议应首先根据其加工程度确定食品健康潜力。