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This is a U.S. Government computer system, which may be accessed and used only for authorized Government business by authorized personnel. Unauthorized access or use of this computer system may subject violators to criminal, civil, and/or administrative action. All information on this computer system may be intercepted, recorded, read, copied, and disclosed by and to authorized personnel for official purposes, including criminal investigations. Such information includes sensitive data encrypted to comply with confidentiality and privacy requirements. Access or use of this computer system by any person, whether authorized or unauthorized, constitutes consent to these terms. There is no right of privacy in this system.

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Filter Cart

Viewable at the top right of NDA pages, the Filter Cart is a temporary holder for filters and data they select. Filters are added to the Workspace first, before being submitted to The Filter Cart. Data selected by filters in the Filter Cart can be added to a Data Package or an NDA Study from the Data Packaging Page, by clicking the 'Create Data Package / Add Data to Study' button.

The filter cart supports combining multiple filters together, and depending on filter type will use "AND" or "OR" when combining filters.

Multiple selections from the same filter type will result in those selections being applied with an ‘OR’ condition. For example, if you add an NDA Collection Filter with selections for both collections 2112 and 2563 to an empty Workspace, the subjects from NDA Collection 2112 ‘OR’ NDA Collection 2563 will be added to your Workspace even if a subject is in both NDA Collections. You can then add other NDA Collections to your Workspace which further extends the ‘OR’ condition.

If a different filter type is added to your Workspace, or a filter has already been submitted to the Filter Cart, the operation then performs a logical ‘AND’ operation. This means that given the subjects returned from the first filter, only those subjects that matched the first filter are returned by the second filter (i.e., subjects that satisfied both filters).

When combining other filters with the GUID filter, please note the GUID filter should be added last. Otherwise, preselected data may be lost. For example, a predefined filter from Featured Datasets may select a subset of data available for a subject. When combined with a GUID filter for the same subject, the filter cart will contain all data available from that subject, data structure, and dataset; this may be more data than was selected in the predefined filter for that subject. Again, you should add the GUID Filter as the last filter to your cart. This ensures 'AND' logic between filters and will limit results to the subjects, data structures, and datasets already included in your filter cart.

Note that only the subjects specific to your filter will be added to your Filter Cart and only on data shared with the research community. Other data for those same subjects may exist (i.e., within another NDA Collection, associated with a data structure that was not requested in the query, etc.). So, users should select ‘Find all Subjects Data’ to identify all data for those specific subjects.

Additional Tips:

  • You may query the data without an account, but to gain access you will need to create an NDA user account and apply for access. Most data access requires that you or your lab are sponsored by an NIH recognized institution with Federal Wide Assurance (FWA). Without access, you will not be able to obtain individual-level data.

Once you have selected data of interest you can:

  • Create a data package - This allows you to specify format for access/download
  • Assign to Study Cohort - Associate the data to an NDA Study allowing for a DOI to be generated and the data to be linked directly to a finding, publication, or data release.
  • Find All Subject Data - Depending on filter types being used, not all data associated with a subject will be selected. Data may be restricted by data structure, NDA Collection, or outcome variables (e.g., NDA Study). ‘Find All Data’ expands the filter criteria by replacing all filters in your Filter Cart with a single Query by GUID filter for all subjects selected by those filters.

Please Note:

  • When running a query, it may take a moment to populate the Filter Cart. Queries happen in the background so you can define other queries during this time.
  • When you add your first filter, all data associated with your query will be added to the Filter Cart (e.g., a Concept, an NDA Collection, a Data Structure/Element, etc.). As you add additional filters, they will also display in the Filter Cart. Only the name of filter will be shown in the Filter Cart, not the underlying structures.
  • Information about the contents of the Filter Cart can be seen by clicking "Edit”.
  • Once your results appear in the Filter Cart, you can create a data package or assign subjects to a study by selecting the 'Package/Assign to Study' option. You can also 'Edit' or 'Clear' filters.

Frequently Asked Questions

  • What is a Filter Cart?
    Viewable at the top right of NDA pages, the Filter Cart is a temporary holder of data identified by the user, through querying or browsing, as being of some potential interest. The Filter Cart is where you send the data from your Workspace after it has been filtered.
  • What do I do after filters are added to the Filter Cart?
    After filters are added to the Filter Cart, users have options to ‘Create a Package’ for download, ‘Associate to Study Cohort’, or ‘Find All Subject Data’. Selecting ‘Find All Subject Data’ identifies and pulls all data for the subjects into the Filter Cart. Choosing ‘Create a Package’ allows users to package and name their query information for download. Choosing ‘Associate to Study Cohort’ gives users the opportunity to choose the Study Cohort they wish to associate this data.
  • Are there limitations on the amount of data a user can download?

    NDA limits the rate at which individual users can transfer data out of Amazon Web Services (AWS) S3 Object storage to non-AWS internet addresses. All users have a download limit of 20 Terabytes. This limit applies to the volume of data an individual user can transfer within a 30-day window. Only downloads to non-AWS internet addresses will be counted against the limit.

  • How does Filter Cart Boolean logic work?

    The Filter Cart currently employs basic AND/OR Boolean logic. A single filter may contain multiple selections for that filter type, e.g., a single NDA Study filter might contain NDA Study 1 and NDA Study 2. A subject that is in EITHER 1 OR 2 will be returned. Adding multiple filters to the cart, regardless of type, will AND the result of each filter. If NDA Study 1 and NDA Study 2 are added as individual filters, data for a subject will only be selected if the subject is included in BOTH 1 AND 2.

    When combining other filters with the GUID filter, please note the GUID filter should be added last. Otherwise, preselected data may be lost. For example, a predefined filter from Featured Datasets may select a subset of data available for a subject. When combined with a GUID filter for the same subject, the filter cart will contain all data available from that subject, data structure, and dataset; this may be more data than was selected in the predefined filter for that subject. Again, you should add the GUID Filter as the last filter to your cart. This ensures 'AND' logic between filters and will limit results to the subjects, data structures, and datasets already included in your filter cart.

Glossary

  • Workspace
    The Workspace within the General Query Tool is a holding area where you can review your pending filters prior to adding them to Filter Cart. Therefore, the first step in accessing data is to select one or more items and move it into the Workspace.
  • Filter Cart
    Viewable at the top right of NDA pages, the Filter Cart is a temporary holder of data identified by the user through querying or browsing as being of some potential interest. The Filter Cart adds data using an AND condition. The opportunity to further refine data to determine what will be downloaded or sent to a miNDAR is available on the Data Packaging Page, the next step after the Filter Cart. Subsequent access to data is restricted by User Permission or Privilege; however Filter Cart use is not.
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Food Frequency Questionnaire (FFQ)

0 Shared Subjects

The Food Frequency Questionnaire (FFQ) assess the amount of different foods the participant consumes which was used to estimate iron intake.
Clinical Assessments
Food
06/01/2021
ffq01
06/22/2021
View Change History
01
Definition
Submission Template
Query Element Name Data Type Size Required Description Value Range Notes Aliases
subjectkey GUID Required The NDAR Global Unique Identifier (GUID) for research subject NDAR*
src_subject_id String 20 Required Subject ID how it's defined in lab/project
interview_date Date Required Date on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYY
interview_age Integer Required Age in months at the time of the interview/test/sampling/imaging. 0 :: 1260 Age is rounded to chronological month. If the research participant is 15-days-old at time of interview, the appropriate value would be 0 months. If the participant is 16-days-old, the value would be 1 month.
sex String 20 Required Sex of subject at birth M;F; O; NR M = Male; F = Female; O=Other; NR = Not reported
ironic_servg_meat_liver Float Recommended Liver (pork, beef, calf, poultry), pork kidney/Serving size reference: 100 g (palm of small hand) Number of servings in a typical week. 0 = None
ironic_servg_meat_pork Float Recommended Other pork offal, poultry stomach/ Serving size reference: 100 g (palm of small hand) Number of servings in a typical week. 0 = None
ironic_servg_meat_beef Float Recommended Beef, calf, lamb, horse, goose, duck meat/Serving size reference: 100 g (palm of small hand) Number of servings in a typical week. 0 = None
meat_port Float Recommended Pork meat/Serving size reference: 100 g (palm of small hand) Number of servings in a typical week. 0 = None
meat_poultry Float Recommended Poultry meat/Serving size reference: 100 g (palm of small hand) Number of servings in a typical week. 0 = None
meat_broth Float Recommended Broth/Serving size reference: 250 g (1 glass)-Number of servings in a typical week Number of servings in a typical week. 0 = None
ironic_servg_meat_bloodpudding Float Recommended Blood pudding sausage/Serving size reference: 25 g (e.g. 1/2 of wiener, medium slice of ham, 5 slices of sausage) Number of servings in a typical week. 0 = None
ironic_servg_meat_otheroffal Float Recommended Other offal cold cuts/Serving size reference: 25 g (e.g. 1/2 of wiener, medium slice of ham, 5 slices of sausage) Number of servings in a typical week. 0 = None
ironic_servg_meat_loincoldcuts Float Recommended Loin cold cuts, ham, poultry sausages/Serving size reference: 25 g (e.g. 1/2 of wiener, medium slice of ham, 5 slices of sausage) Number of servings in a typical week. 0 = None
ironic_servg_othersausages Float Recommended Other sausages, wiener, smoked gammon, spam, pate, salami, brawn cold cut, bacon/Serving size reference: 25 g (e.g. 1/2 of wiener, medium slice of ham, 5 slices of sausage) Number of servings in a typical week. 0 = None
ironic_servg_egg Float Recommended Eggs/Serving size reference: 50 g (1 egg) Number of servings in a typical week. 0 = None
ironic_servg_fish_sardines Float Recommended Fish-Sardines/Serving size reference: 50 g (deck of cards) Number of servings in a typical week. 0 = None
ironic_servg_fish_other Float Recommended Other fish and fish products/Serving size reference: 50 g (deck of cards) Number of servings in a typical week. 0 = None
ironic_servg_dairy_milk Float Recommended Milk and milk beverages (yoghurt, kefir, buttermilk, cream)/Serving size reference: 250 g (1 glass) Number of servings in a typical week. 0 = None
ironic_servg_dairy_cottage Float Recommended Cottage cheese/Serving size reference: 50 g (1 thick slice, 2 tablespoons) Number of servings in a typical week. 0 = None
ironic_servg_dairy_rennet Float Recommended Rennet and processed cheese/Serving size reference: 25 g (1 slice, 1 triangle serving) Number of servings in a typical week. 0 = None
ironic_servg_cereal_whitemeat Float Recommended White wheat and rye bread, bakery wares/Serving size reference: 35 g (1 slice, small roll) Number of servings in a typical week. 0 = None
ironic_servg_cereal_darkbread Float Recommended Dark bread, wholemeal, with grains, graham bread, pumpernickel bread/Serving size reference: 35 g (1 slice, small roll) Number of servings in a typical week. 0 = None
ironic_servg_cereal_crispbread Float Recommended Crispbread/Serving size reference: 10 g (1 slice) Number of servings in a typical week. 0 = None
ironic_servg_cereal_wheatbran Float Recommended Wheat bran, wheat germs/Serving size reference: 10 g (1 spoon) Number of servings in a typical week. 0 = None
ironic_servg_cereal_cornflakes Float Recommended Iron-fortified corn flakes and cereals/Serving size reference: 35 g (1 glass) Number of servings in a typical week. 0 = None
ironic_servg_cereal_other Float Recommended Other cereal products (uncooked)/100 g (e.g. 1 glass of pasta or oatmeal, 1/2 glass of rice or groats) Number of servings in a typical week. 0 = None
ironic_servg_fruit_fresh Float Recommended Fresh fruits/Serving size reference: 100 g (1 medium piece, 1 glass) Number of servings in a typical week. 0 = None
ironic_servg_fruit_dry Float Recommended Dried fruits/Serving size reference: 50 g (handful) Number of servings in a typical week. 0 = None
ironic_servg_veget_dry Float Recommended Vegetables-Dry legumes/Serving size reference: 100 g (1/2 of glass) Number of servings in a typical week. 0 = None
ironic_servg_veget_other Float Recommended Vegetables-Other vegetables/Serving size reference: 100 g (1 medium piece, 1 glass) Number of servings in a typical week. 0 = None
ironic_servg_potato Float Recommended Serving size reference: 100 g (1 large piece) Number of servings in a typical week. 0 = None
ironic_servg_fats Float Recommended Fats/Serving size reference: 10 g (1 spoon)-Number of servings in a typical week Number of servings in a typical week. 0 = None
ironic_servg_nuts_poppy Float Recommended Nuts/Seeds-Poppy, pumpkin and flaxseed/Serving size reference: 30 g (handful, 3 spoons of seeds) Number of servings in a typical week. 0 = None
ironic_servg_nuts_other Float Recommended Nuts/Seeds-Other nuts and seeds/Serving size reference: 30 g (handful, 3 spoons of seeds) Number of servings in a typical week. 0 = None
ironic_servg_cocoa Float Recommended Cocoa/Serving size reference: 10 g (1 spoon) Number of servings in a typical week. 0 = None
ironic_servg_chocolate Float Recommended Chocolate/Serving size reference: 20 g (1/5 of bar) Number of servings in a typical week. 0 = None
Data Structure

This page displays the data structure defined for the measure identified in the title and structure short name. The table below displays a list of data elements in this structure (also called variables) and the following information:

  • Element Name: This is the standard element name
  • Data Type: Which type of data this element is, e.g. String, Float, File location.
  • Size: If applicable, the character limit of this element
  • Required: This column displays whether the element is Required for valid submissions, Recommended for valid submissions, Conditional on other elements, or Optional
  • Description: A basic description
  • Value Range: Which values can appear validly in this element (case sensitive for strings)
  • Notes: Expanded description or notes on coding of values
  • Aliases: A list of currently supported Aliases (alternate element names)
  • For valid elements with shared data, on the far left is a Filter button you can use to view a summary of shared data for that element and apply a query filter to your Cart based on selected value ranges

At the top of this page you can also:

  • Use the search bar to filter the elements displayed. This will not filter on the Size of Required columns
  • Download a copy of this definition in CSV format
  • Download a blank CSV submission template prepopulated with the correct structure header rows ready to fill with subject records and upload

Please email the The NDA Help Desk with any questions.