食物的化学成分很复杂,变量,取决于许多因素。这对营养研究产生了重大影响,因为它从根本上影响了我们充分评估营养素和其他化合物实际摄入量的能力。尽管如此,关于营养素摄入量的准确数据是调查摄入量之间关联和因果关系的关键,健康,和疾病风险,以制定基于证据的饮食指导,从而改善人口健康。这里,我们通过使用三种生物活性物质作为模型来调查食物含量变异性对营养研究的影响来举例说明这一挑战的重要性:Favan-3-ols,(-)-表儿茶素,和硝酸盐。我们的结果表明,旨在解决即使是相同食物的高成分变异性的常见方法通常会阻碍对营养素摄入量的准确评估。这表明,许多使用食物成分数据的营养研究结果可能不可靠,并且具有比通常理解的更大的局限性。因此,导致饮食建议具有显著的fi不能限制和对公共卫生的不可靠影响。因此,当前与营养摄入评估相关的挑战需要通过开发涉及使用营养生物标志物的改良饮食评估方法来解决和缓解.
关于食物或营养素的健康益处的研究通常不一致。一项研究可能会发现特定食物的健康益处,并可能建议人们增加对这种食物的消费以降低疾病风险。另一项研究可能会发现相反的情况。不一致的研究结果助长了混乱和沮丧,减少对研究的信任。研究设计中的局限性可能会归咎于不一致的发现。例如,许多研究依赖于参与者自我报告他们的食物摄入量和食物营养成分的数据库。但是人们可能无法准确地报告他们的食物摄入量。食物的营养成分各不相同,甚至在相同食物的两个项目之间,例如两个苹果。个人如何代谢食物会进一步影响他们接受的营养。营养生物标志物是测量特定营养素的饮食摄入量的潜在替代方法。生物标志物是身体代谢特定营养素时产生的化合物。因此,测量生物标志物可以为科学家提供更准确和公正的营养摄入量评估。Ottaviani等人。进行了一项研究,以测试使用营养生物标志物与更常规工具估算营养摄入量时的差异。他们分析了一项涉及18,000多名参与者的营养研究的数据。实验使用计算机建模来评估研究结果,使用自我报告的食物摄入量与食物成分数据库信息相结合,或三种生物标志物的测量,估计黄烷-3-醇的摄入量,表儿茶素,和硝酸盐。这些模型表明,自我报告的摄入量和食物数据库信息通常导致不准确的结果,与生物标志物测量结果不一致。测量营养生物标志物提供了更准确和无偏见的营养摄入评估。使用这些测量代替传统的方法来测量营养摄入量可能有助于提高营养研究的可靠性。科学家必须努力识别和确认营养素的生物标志物,以促进这项工作。在研究中使用这些更精确的营养测量可能会导致更一致的结果。这也可能为消费者带来更可靠的推荐。
The chemical composition of foods is complex, variable, and dependent on many factors. This has a major impact on nutrition research as it foundationally affects our ability to adequately assess the actual intake of nutrients and other compounds. In spite of this, accurate data on nutrient intake are key for investigating the associations and causal relationships between intake, health, and disease risk at the service of developing evidence-based dietary guidance that enables improvements in population health. Here, we exemplify the importance of this challenge by investigating the impact of food content variability on nutrition research using three bioactives as model: flavan-3-ols, (-)-
epicatechin, and nitrate. Our results show that common approaches aimed at addressing the high compositional variability of even the same foods impede the accurate assessment of nutrient intake generally. This suggests that the results of many nutrition studies using food composition data are potentially unreliable and carry greater limitations than commonly appreciated, consequently resulting in dietary recommendations with significant limitations and unreliable impact on public health. Thus, current challenges related to nutrient intake assessments need to be addressed and mitigated by the development of improved dietary assessment methods involving the use of nutritional biomarkers.
Studies about the health benefits of foods or nutrients are often inconsistent. One study may find a health benefit of a particular food and may recommend that people increase their consumption of this food to reduce their disease risk. Yet another study may find the opposite. Inconsistent study results fuel confusion and frustration, and reduce trust in research. Limitations in the studies’ designs are likely to be blamed for the inconsistent findings. For example, many studies rely on participants to self-report their food intake and on databases of the nutritional content of food. But people may not accurately report their food intake. Foods vary in their nutritional content, even between two items of the same food such as two apples. And how individuals metabolize foods can further affect the nutrients they receive. Nutritional biomarkers are a potential alternative to measuring dietary intake of specific nutrients. Biomarkers are compounds the body produces when it metabolizes a specific nutrient. Measuring biomarkers therefore give scientists a more accurate and unbiased assessment of nutrient intake. Ottaviani et al. conducted a study to test the differences when estimating nutrient intake using nutritional biomarkers compared with more conventional tools. They analyzed data from a nutrition study that involved over 18,000 participants. The experiments used computer modelling to assess study results using self-reported food intake in combination with food composition database information, or measures of three biomarkers estimating the intake of flavan-3-ols,
epicatechin, and nitrates. The models showed that self-reported intake and food database information often led to inaccurate results that did not align well with biomarker measurements. Measuring nutritional biomarkers provides a more accurate and unbiased assessment of nutritional intake. Using these measurements instead of traditional methods for measuring nutrient intake may help increase the reliability of nutrition research. Scientists must work to identify and confirm biomarkers of nutrients to facilitate this work. Using these more precise nutrient measurements in studies may result in more consistent results. It may also lead to more trustworthy recommendations for consumers.