6 datasets found
  1. NHANES 1988-2018

    • figshare.com
    application/gzip
    Updated Feb 18, 2025
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    Lauren Y. M. Middleton; Neil Zhao; Lei Huang; Eliseu Verly; Jacob Kvasnicka; Luke Sagers; Chirag Patel; Justin Colacino; Olivier Jolliet (2025). NHANES 1988-2018 [Dataset]. http://doi.org/10.6084/m9.figshare.21743372.v2
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    application/gzipAvailable download formats
    Dataset updated
    Feb 18, 2025
    Dataset provided by
    figshare
    Authors
    Lauren Y. M. Middleton; Neil Zhao; Lei Huang; Eliseu Verly; Jacob Kvasnicka; Luke Sagers; Chirag Patel; Justin Colacino; Olivier Jolliet
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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. csv Data Record: 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”). R Data Record: 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”).

  2. D

    DQS NHANES Select Infectious Diseases Prevalence Estimates

    • data.cdc.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated Sep 17, 2024
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    NCHS/DHANES (2024). DQS NHANES Select Infectious Diseases Prevalence Estimates [Dataset]. https://data.cdc.gov/NCHS/DQS-NHANES-Select-Infectious-Diseases-Prevalence-E/be3w-4inw
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    application/rdfxml, csv, xml, application/rssxml, tsv, jsonAvailable download formats
    Dataset updated
    Sep 17, 2024
    Dataset authored and provided by
    NCHS/DHANES
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Description

    These data represent prevalence estimates of select infectious diseases from the National Health and Nutrition Examination Survey (NHANES). This version of the NHANES dataset is specific to visualization within the NCHS DQS. Search, visualize, and download these and other estimates from over 120 health topics with the NCHS Data Query System (DQS), available from: https://www.cdc.gov/nchs/dataquery/index.htm.

  3. D

    DQS NHANES Select Chronic Conditions Prevalence Estimates

    • data.cdc.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated Oct 24, 2024
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    NCHS/DHANES (2024). DQS NHANES Select Chronic Conditions Prevalence Estimates [Dataset]. https://data.cdc.gov/w/mvup-dmxz/tdwk-ruhb?cur=0k-0Xapjq9F&from=v5pclZ3gwY7
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    application/rssxml, xml, csv, json, tsv, application/rdfxmlAvailable download formats
    Dataset updated
    Oct 24, 2024
    Dataset authored and provided by
    NCHS/DHANES
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Description

    These data represent prevalence estimates of select chronic conditions from the National Health and Nutrition Examination Survey (NHANES). This version of the dataset is specific for use by the NCHS DQS. Search, visualize, and download these and other estimates from over 120 health topics with the NCHS Data Query System (DQS), available from: https://www.cdc.gov/nchs/dataquery/index.htm.

  4. DQS NHANES Select Oral Health Prevalence Estimates

    • data.virginia.gov
    • healthdata.gov
    • +1more
    csv, json, rdf, xsl
    Updated Sep 17, 2024
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    Centers for Disease Control and Prevention (2024). DQS NHANES Select Oral Health Prevalence Estimates [Dataset]. https://data.virginia.gov/dataset/dqs-nhanes-select-oral-health-prevalence-estimates
    Explore at:
    csv, json, xsl, rdfAvailable download formats
    Dataset updated
    Sep 17, 2024
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    These data represent prevalence estimates of select oral health topics from the National Health and Nutrition Examination Survey (NHANES). Search, visualize, and download these and other estimates from over 120 health topics with the NCHS Data Query System (DQS), available from: https://www.cdc.gov/nchs/dataquery/index.htm.

  5. d

    Data from: Food and Nutrient Database for Dietary Studies (FNDDS)

    • catalog.data.gov
    • agdatacommons.nal.usda.gov
    • +1more
    Updated Mar 30, 2024
    + more versions
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    Agricultural Research Service (2024). Food and Nutrient Database for Dietary Studies (FNDDS) [Dataset]. https://catalog.data.gov/dataset/food-and-nutrient-database-for-dietary-studies-fndds-f9910
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    Dataset updated
    Mar 30, 2024
    Dataset provided by
    Agricultural Research Service
    Description

    [Note: Integrated as part of FoodData Central, April 2019.] USDA's Food and Nutrient Database for Dietary Studies (FNDDS) is a database that is used to convert food and beverages consumed in What We Eat In America (WWEIA), National Health and Nutrition Examination Survey (NHANES) into gram amounts and to determine their nutrient values. Because FNDDS is used to generate the nutrient intake data files for WWEIA, NHANES, it is not required to estimate nutrient intakes from the survey. FNDDS is made available for researchers using WWEIA, NHANES to review the nutrient profiles for specific foods and beverages as well as their associated portions and recipes. Such detailed information makes it possible for researchers to conduct enhanced analysis of dietary intakes. FNDDS can also be used in other dietary studies to code foods/beverages and amounts eaten and to calculate the amounts of nutrients/food components in those items. FNDDS is released every two-years in conjunction with the WWEIA, NHANES dietary data release. The FNDDS is available for free download from the FSRG website. Resources in this dataset:Resource Title: Website Pointer to Food and Nutrient Database for Dietary Studies. File Name: Web Page, url: https://www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-human-nutrition-research-center/food-surveys-research-group/docs/fndds/ USDA's Food and Nutrient Database for Dietary Studies (FNDDS) is a database that is used to convert food and beverages consumed in What We Eat In America (WWEIA), National Health and Nutrition Examination Survey (NHANES) into gram amounts and to determine their nutrient values.

  6. DQS NHANES Select Mean Dietary Intake Estimates

    • data.virginia.gov
    • healthdata.gov
    • +1more
    csv, json, rdf, xsl
    Updated Nov 1, 2024
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    Centers for Disease Control and Prevention (2024). DQS NHANES Select Mean Dietary Intake Estimates [Dataset]. https://data.virginia.gov/dataset/dqs-nhanes-select-mean-dietary-intake-estimates
    Explore at:
    xsl, json, csv, rdfAvailable download formats
    Dataset updated
    Nov 1, 2024
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Description

    These data represent mean intake, on a given day, estimates of nutrients from foods and beverages from the National Health and Nutrition Examination Survey (NHANES). Search, visualize, and download these and other estimates from over 120 health topics with the NCHS Data Query System (DQS), available from: https://www.cdc.gov/nchs/dataquery/index.htm.

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Lauren Y. M. Middleton; Neil Zhao; Lei Huang; Eliseu Verly; Jacob Kvasnicka; Luke Sagers; Chirag Patel; Justin Colacino; Olivier Jolliet (2025). NHANES 1988-2018 [Dataset]. http://doi.org/10.6084/m9.figshare.21743372.v2
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NHANES 1988-2018

Explore at:
69 scholarly articles cite this dataset (View in Google Scholar)
application/gzipAvailable download formats
Dataset updated
Feb 18, 2025
Dataset provided by
figshare
Authors
Lauren Y. M. Middleton; Neil Zhao; Lei Huang; Eliseu Verly; Jacob Kvasnicka; Luke Sagers; Chirag Patel; Justin Colacino; Olivier Jolliet
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

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. csv Data Record: 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”). R Data Record: 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”).

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