Zhan Jiada James, Hodge Rebecca A, Dunlop Anne L, Lee Matthew M, Bui Linh, Liang Donghai, Ferranti Erin P
Nutrition & Health Sciences Doctoral Program, Laney Graduate School, Emory University, Atlanta, GA 30322, USA.
Department of Population Science, American Cancer Society, Kennesaw, GA 30144, USA.
bioRxiv. 2023 Aug 9:2023.08.07.548466. doi: 10.1101/2023.08.07.548466.
Few standardized and open-source tools exist for calculating dietary pattern indexes from dietary intake data in epidemiological and clinical studies. Miscalculations of dietary indexes, with suspected erroneous findings, are occasionally noted in the literature.
The primary aim is to develop and validate dietaryindex, a user-friendly and versatile R package that standardizes the calculation of dietary indexes.
Dietaryindex utilizes a two-step process: an initial calculation of serving size for each food and nutrient category, followed by the calculation of individual dietary indexes. It includes generic functions that accept any preprocessed serving sizes of food groups and nutrients, with the standard serving sizes defined according to the methodologies used in well-known prospective cohort studies. For ease of use, dietaryindex also offers one-step functions that directly reference common datasets and tools, including the National Health and Nutrition Examination Survey (NHANES) and Block Food Frequency Questionnaire, eliminating the need for data preprocessing. At least two independent researchers validated the serving size definitions and scoring algorithms of dietaryindex.
Dietaryindex can calculate multiple dietary indexes of high interest in research, including Healthy Eating Index (HEI) - 2020, Alternative Healthy Eating Index 2010, Dietary Approaches to Stop Hypertension Index, Alternate Mediterranean Diet Score, Dietary Inflammatory Index, American Cancer Society 2020 dietary index, and Planetary Health Diet Index from the EAT-Lancet Commission. In our validation process, dietaryindex demonstrated full accuracy (100%) in all generic functions with two-decimal rounding precision in comparison to hand-calculated results. Similarly, using NHANES 2017-2018 data and ASA24 and DHQ3 example data, the HEI2015 outputs from dietaryindex aligned (99.95%-100%) with results using the SAS codes from the National Cancer Institute.
Dietaryindex is a user-friendly, versatile, and validated informatics tool for standardized dietary index calculations. We have open-sourced all the validation files and codes with detailed tutorials on GitHub (https://github.com/jamesjiadazhan/dietaryindex).
在流行病学和临床研究中，用于根据饮食摄入数据计算饮食模式指数的标准化开源工具很少。文献中偶尔会提到饮食指数计算错误以及由此产生的可疑错误结果。
主要目的是开发并验证dietaryindex，这是一个用户友好且通用的R包，用于规范饮食指数的计算。
dietaryindex采用两步法：首先计算每种食物和营养类别的食用量，然后计算个体饮食指数。它包括通用函数，可接受任何经过预处理的食物组和营养素的食用量，标准食用量根据著名前瞻性队列研究中使用的方法定义。为便于使用，dietaryindex还提供一步函数，可直接引用常见数据集和工具，包括美国国家健康与营养检查调查（NHANES）和布洛克食物频率问卷，无需进行数据预处理。至少两名独立研究人员对dietaryindex的食用量定义和评分算法进行了验证。
dietaryindex可以计算研究中多个备受关注的饮食指数，包括2020年健康饮食指数（HEI）、2010年替代健康饮食指数、终止高血压饮食方法指数、替代地中海饮食评分、饮食炎症指数、美国癌症协会2020年饮食指数以及柳叶刀委员会饮食与健康委员会的行星健康饮食指数。在我们的验证过程中，与手工计算结果相比，dietaryindex在所有通用函数中均显示出完全准确性（100%），舍入精度为小数点后两位。同样，使用NHANES 2017 - 2018数据以及ASA24和DHQ3示例数据，dietaryindex输出的HEI2015与使用美国国家癌症研究所的SAS代码得出的结果一致（99.95% - 100%）。
dietaryindex是一种用户友好、通用且经过验证的信息学工具，用于标准化饮食指数计算。我们已在GitHub（https://github.com/jamesjiadazhan/dietaryindex）上开源了所有验证文件和代码以及详细教程。
