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开发和验证一种用于耐力运动员碳水化合物摄入量的饮食筛查工具。

Development and validation of a dietary screener for carbohydrate intake in endurance athletes.

机构信息

Institute of Nutrition and Functional Foods (INAF), Pavillon des Services, Laval University, 2440, Hochelaga Boulevard, Quebec City, G1V 0A6, Canada.

School of Nutrition, Laval University, Quebec, G1V 0A6, Canada.

出版信息

J Int Soc Sports Nutr. 2018 Sep 14;15(1):44. doi: 10.1186/s12970-018-0250-y.

DOI:10.1186/s12970-018-0250-y
PMID:30217199
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6137928/
Abstract

BACKGROUND

Studies have shown that the majority of endurance athletes do not achieve the minimal recommended carbohydrate (CHO) intake of 6 g/kg of body weight (BW), with potentially negative impacts on recovery and performance. The purpose of this study was to develop and validate a rapid and easy to use dietary screener to identify athletes who do and do not achieve a CHO intake > 6 g/kg BW in the context of endurance sports.

METHODS

The dietary screener was developed using multiple logistic regression modeling of data from a sample of 1571 non-athlete adults (826 women and 745 men, mean age 44.75 ± 14.2 years) among whom dietary intake was assessed using a validated web-based food frequency questionnaire (web-FFQ). Three models were developed based on whole food intake using the 5, 10 and 15 most significant variables predicting CHO intake. The three models were then validated in a target population of non-elite endurance athletes having taken part in multisport events (n = 175, 64 women and 111 men, mean age 37.1 ± 11.3 years) and compared using sensitivity, specificity, positive and negative predictive values (PPV and NPV, respectively) and c-statistics.

RESULTS

The 15-variables model provided significantly better accuracy in predicting CHO intake adequacy in non-elite endurance athletes (c-statistic = 0.94) compared with the 10- and 5-variables model (c-statistic = 0.90 and 0.71 respectively). The 15-variables model predicts CHO intake adequacy in the target population of endurance athlete with a sensitivity of 89.5%, a specificity of 87.3% and PPV and NPV of 77.3 and 94.5%, respectively.

CONCLUSION

We have successfully developed a short and valid dietary screener that identifies endurance athletes at risk of not achieving a CHO intake > 6 g/kg BW. Use of this rapid screener may help alleviate the highly prevalent issue of suboptimal CHO consumption in the endurance sports realm.

摘要

背景

研究表明,大多数耐力运动员的碳水化合物(CHO)摄入量未达到 6g/kg 体重的最低推荐摄入量,这可能对恢复和表现产生负面影响。本研究的目的是开发和验证一种快速易用的饮食筛查工具,以确定在耐力运动中摄入 CHO 量>6g/kg BW 的运动员和未摄入 CHO 量>6g/kg BW 的运动员。

方法

使用 1571 名非运动员成年人(826 名女性和 745 名男性,平均年龄 44.75±14.2 岁)的数据,采用多逻辑回归建模方法开发了饮食筛查工具,其中饮食摄入量采用经过验证的基于网络的食物频率问卷(web-FFQ)进行评估。基于全食物摄入量,使用预测 CHO 摄入量的 5、10 和 15 个最重要变量,分别开发了三个模型。然后,在参加多运动项目的非精英耐力运动员(n=175,64 名女性和 111 名男性,平均年龄 37.1±11.3 岁)的目标人群中对这三个模型进行了验证,并比较了它们的敏感性、特异性、阳性预测值(PPV)和阴性预测值(NPV)以及 c 统计量。

结果

与 10 变量和 5 变量模型(c 统计量分别为 0.90 和 0.71)相比,15 变量模型在预测非精英耐力运动员的 CHO 摄入充足性方面具有更高的准确性(c 统计量=0.94)。15 变量模型预测目标人群中耐力运动员的 CHO 摄入充足性的敏感性为 89.5%,特异性为 87.3%,PPV 和 NPV 分别为 77.3%和 94.5%。

结论

我们成功开发了一种简短有效的饮食筛查工具,可识别摄入 CHO 量<6g/kg BW 风险较高的耐力运动员。使用这种快速筛查工具可能有助于缓解耐力运动领域普遍存在的 CHO 摄入不足的问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aef2/6137928/4062c4936f84/12970_2018_250_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aef2/6137928/276cb9fdbd14/12970_2018_250_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aef2/6137928/4062c4936f84/12970_2018_250_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aef2/6137928/276cb9fdbd14/12970_2018_250_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aef2/6137928/4062c4936f84/12970_2018_250_Fig2_HTML.jpg

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