NHANES 1988-2018

The National Health and Nutrition Examination Survey (NHANES) provides data on the health and environmental exposure of the non-institutionalized US population. Such data have considerable potential to understand how the environment and behaviors impact human health. These data are also currently leveraged to answer public health questions such as prevalence of disease. However, these data need to first be processed before new insights can be derived through large-scale analyses. NHANES data are stored across hundreds of files with multiple inconsistencies. Correcting such inconsistencies takes systematic cross examination and considerable efforts but is required for accurately and reproducibly characterizing the associations between the exposome and diseases (e.g., cancer mortality outcomes). Thus, we developed a set of curated and unified datasets and accompanied code by merging 614 separate files and harmonizing unrestricted data across NHANES III (1988-1994) and Continuous (1999-2018), totaling 134,310 participants and 4,740 variables. The variables convey 1) demographic information, 2) dietary consumption, 3) physical examination results, 4) occupation, 5) questionnaire items (e.g., physical activity, general health status, medical conditions), 6) medications, 7) mortality status linked from the National Death Index, 8) survey weights, 9) environmental exposure biomarker measurements, and 10) chemical comments that indicate which measurements are below or above the lower limit of detection. We also provide a data dictionary listing the variables and their descriptions to help researchers browse the data. We also provide R markdown files to show example codes on calculating summary statistics and running regression models to help accelerate high-throughput analysis of the exposome and secular trends on cancer mortality. <strong>csv Data Record:</strong> The curated NHANES datasets and the data dictionaries includes 13 .csv files and 1 excel file. The curated NHANES datasets involves 10 .csv formatted files, one for each module and labeled as the following: 1) mortality, 2) dietary, 3) demographics, 4) response, 5) medications, 6) questionnaire, 7) chemicals, 8) occupation, 9) weights, and 10) comments. The eleventh file is a dictionary that lists the variable name, description, module, category, units, CAS Number, comment use, chemical family, chemical family shortened, number of measurements, and cycles available for all 4,740 variables in NHANES ("dictionary_nhanes.csv"). The 12th csv file contains the harmonized categories for the categorical variables ("dictionary_harmonized_categories.csv"). The 13th file contains the dictionary for descriptors on the drugs codes (“dictionary_drug_codes.csv”). The 14th file is an excel file that contains the cleaning documentation, which records all the inconsistencies for all affected variables to help curate each of the NHANES datasets (“nhanes_inconsistencies_documentation.xlsx”). <strong>R Data Record:</strong> For researchers who want to conduct their analysis in the R programming language, the curated NHANES datasets and the data dictionaries can be downloaded as a .zip file which include an .RData file and an .R file. We provided an .RData file that contains all the aforementioned datasets as R data objects (“w - nhanes_1988_2018.RData”). Also in this .RData file, we make available all R scripts on customized functions that were written to curate the data. We also provide an .R file that shows how we used the customized functions (i.e. our pipeline) to curate the data (“m - nhanes_1988_2018.R”).

美国国家健康与营养检查调查（National Health and Nutrition Examination Survey, NHANES）收录了美国非制度化人群的健康状况与环境暴露相关数据。此类数据为揭示环境与行为因素对人类健康的影响机制提供了重要研究潜力，当前亦被用于解答诸多公共卫生议题，例如疾病患病率相关研究。但如若要通过大规模分析获取全新研究见解，需先对这些数据进行预处理。

NHANES的数据分散存储于数百个文件中，且存在多处不一致之处。修正此类不一致需要开展系统性交叉核查并投入大量工作，但为了能够准确且可复现地表征暴露组（exposome）与疾病（如癌症死亡率结局）之间的关联，该步骤必不可少。

为此，我们整合了NHANES Ⅲ（1988-1994年）与连续调查周期（1999-2018年）的614个独立文件，对无限制原始数据进行统一化处理，构建了一套经整理的标准化数据集，并配套提供相关代码。该数据集涵盖134310名参与者与4740个变量。

上述变量涵盖以下10类信息：1）人口统计学资料；2）膳食摄入情况；3）体格检查结果；4）职业史；5）问卷条目（如体力活动、总体健康状况、疾病史）；6）用药情况；7）源自国家死亡索引（National Death Index）的死亡状态数据；8）调查权重；9）环境暴露生物标志物检测结果；10）化学物质注释，用于标注哪些检测结果低于或高于检测下限。

我们还配套提供了数据字典，列出所有变量及其说明，以辅助研究人员浏览数据集。此外，我们还提供R Markdown文件，展示用于计算汇总统计量与构建回归模型的示例代码，以助力研究人员加速开展暴露组与癌症死亡率长期趋势的高通量分析。

<strong>CSV数据记录：</strong>整理后的NHANES数据集与数据字典包含13个CSV文件与1个Excel文件。其中10个CSV格式文件对应前述10类数据模块，分别命名为：1）死亡率模块；2）膳食模块；3）人口统计学模块；4）应答模块；5）用药模块；6）问卷模块；7）化学物质模块；8）职业史模块；9）权重模块；10）注释模块。第11个文件为变量字典文件"dictionary_nhanes.csv"，列出了NHANES全部4740个变量的变量名、说明、所属模块、类别、单位、CAS编号、注释用途、化学家族、缩写化学家族、检测次数与可用调查周期。第12个CSV文件"dictionary_harmonized_categories.csv"包含分类变量的标准化分类体系。第13个CSV文件"dictionary_drug_codes.csv"为药物代码描述字典。第14个为Excel文件"nhanes_inconsistencies_documentation.xlsx"，其中记录了所有受影响变量的不一致情况，用于辅助NHANES各数据集的整理工作。

<strong>R数据记录：</strong>对于希望使用R编程语言开展分析的研究人员，整理后的NHANES数据集与数据字典可通过ZIP压缩包下载，压缩包内含一个RData文件与一个R脚本文件。我们提供的RData文件"w - nhanes_1988_2018.RData"包含前述所有数据集的R数据对象，同时内置了所有用于整理数据的自定义R函数脚本。此外，我们还提供R脚本文件"m - nhanes_1988_2018.R"，演示了如何使用这些自定义函数（即我们的数据整理流程）完成数据集的标准化处理。