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）提供了美国非制度化人群的健康状况与环境暴露相关数据。此类数据对于解析环境与行为因素如何影响人类健康具有极高研究价值，当前也被广泛用于解答公共卫生领域的诸多问题，例如疾病患病率相关研究。

不过，在通过大规模分析挖掘新的研究洞见之前，这类数据需要先完成预处理工作。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的交叉核查并投入大量工作，但这是精准且可复现地表征暴露组（exposome）与疾病（例如癌症死亡结局）之间关联的必要前提。

为此，本研究整合了NHANES Ⅲ（1988-1994年）与连续调查周期（1999-2018年）的614个独立文件，对非限制性数据进行统一化处理，最终构建了一套经过整理与标准化的数据集，并配套提供相应代码。本数据集涵盖134310名参与者与4740个变量，变量类型涵盖以下10类：1）人口统计学信息；2）膳食摄入情况；3）体格检查结果；4）职业信息；5）问卷条目（例如体力活动、总体健康状况、疾病史）；6）用药情况；7）美国国家死亡索引关联的死亡状态；8）调查权重；9）环境暴露生物标志物检测结果；10）用于标注检测结果是否低于或高于检测下限的化学注释信息。

我们还提供了数据字典，列明所有变量及其说明，以帮助研究人员检索与浏览数据。此外，我们提供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，助力暴露组与癌症死亡结局长期趋势的高通量分析工作。

<strong>CSV 数据记录：</strong>经整理的NHANES数据集与数据字典共包含13个CSV文件与1个Excel文件。其中10个CSV文件对应前述10类数据模块，分别命名为：1）死亡结局；2）膳食摄入；3）人口统计学信息；4）应答情况；5）用药记录；6）问卷数据；7）化学检测数据；8）职业信息；9）调查权重；10）注释信息。第11个文件为"dictionary_nhanes.csv"，即NHANES全部4740个变量的数据字典，列明变量名、变量说明、所属模块、分类、单位、CAS编号、注释用途、化学家族、简化化学家族、检测次数与可用调查周期。第12个CSV文件为"dictionary_harmonized_categories.csv"，包含分类变量的标准化分类体系。第13个CSV文件为"dictionary_drug_codes.csv"，即药物代码描述字典。第14个Excel文件为"nhanes_inconsistencies_documentation.xlsx"，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压缩包下载，其中包含一个RData文件与一个R脚本文件。我们提供的"w - nhanes_1988_2018.RData"文件包含前述所有数据集的R数据对象，同时内置了所有用于数据整理的自定义R函数。此外，我们还提供"m - nhanes_1988_2018.R"脚本文件，展示了如何使用这些自定义函数（即本研究的数据整理流程）完成数据整理工作。