Medical Dietetics & Health Sciences, School of Health and Rehabilitation Sciences, The Ohio State Univ., Columbus, Ohio 43210, U.S.A.
School of Medicine, Case Western Reserve Univ., 2109 Adelbert Rd, Cleveland, Ohio 44106, U.S.A.
J Food Sci. 2018 Mar;83(3):831-836. doi: 10.1111/1750-3841.14065. Epub 2018 Feb 7.
This paper presents a simulation process to augment nutrition surveillance in the United States which incorporates product innovation data. Traditional point-estimates of nutritional quality in a food category are compared to those based on distributions of nutrient compositions using product-level variability seen in the market. Nationally representative consumption patterns provide dietary intakes. Cookies are used as an example food category. Nutrient composition data from Global New Product Database (GNPD) for 5259 cookies launched 2005 to 2012 were matched to dietary intakes from 2005 to 2012 National Health and Nutrition Examination Survey (NHANES) over the 2 y cycles of NHANES for 8284 cookie consumers. Average dietary intakes from traditional NHANES and GNPD-based estimations produced similar mean values for energy, carbohydrates, sugars, total fat, and protein. Saturated fat, fiber and cholesterol contributions using new product compositions were significantly higher than traditional NHANES approaches, estimates of sodium were significantly lower. These differences become pronounced when comparing adult and child consumption patterns and over time. This process also simulated trans fat consumption estimates not traditionally available within NHANES. On average cookies contributed 0.3 g/d (range 0 to 4.1 g/d). Much variability in food composition is seen in the market which is shown to influence estimates of the national diet.
Numerous factors drive changes in the food supply, including health trends, firm strategic choices, and food policy. This evolution presents a challenge for dietary assessments and nutrition monitoring. The public health impact of variability in nutritional composition, subpopulation consumption patterns and market dynamics are particularly difficult to evaluate and are shown to influence estimates of the national diet.
本文提出了一个模拟过程，以增加美国的营养监测，其中包括产品创新数据。使用市场上看到的产品层面的变异性，传统的食品类别营养质量的点估计与基于营养素组成分布的估计进行了比较。全国代表性的消费模式提供了饮食摄入量。饼干被用作示例食品类别。2005 年至 2012 年期间推出的 5259 种饼干的全球新产品数据库（GNPD）中的营养成分数据与 2005 年至 2012 年期间全国健康和营养检查调查（NHANES）中 8284 名饼干消费者的饮食摄入量相匹配。传统 NHANES 和基于 GNPD 的估计的平均饮食摄入量产生了相似的能量、碳水化合物、糖、总脂肪和蛋白质平均值。使用新产品成分计算的饱和脂肪、纤维和胆固醇摄入量明显高于传统 NHANES 方法，钠的估计值明显较低。当比较成人和儿童的消费模式和随时间的变化时，这些差异变得更加明显。这个过程还模拟了传统 NHANES 中不可用的反式脂肪消费估计。平均而言，饼干贡献了 0.3 克/天（范围为 0 至 4.1 克/天）。市场上可见到食品成分的大量变化，这会影响对全国饮食的估计。
许多因素推动了食品供应的变化，包括健康趋势、公司战略选择和食品政策。这种演变对膳食评估和营养监测提出了挑战。营养成分、亚人群消费模式和市场动态的变异性对公共健康的影响尤其难以评估，并会影响对全国饮食的估计。
