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The Filter Cart provides a powerful way to query and access data for which you may be interested.  

A few points related to the filter cart are important to understand with the NDA Query/Filter implementation: 

First, the filter cart is populated asyncronously.  So, when you run a query, it may take a moment to populate but this will happen in the background so you can define other queries during this time.  

When you are adding your first filter, all data associated with your query will be added to the filter cart (whether it be a collection, a concept, a study, a data structure/elment or subjects). Not all data structures or collections will necessarily be displayed.  For example, if you select the NDA imaging structure image03, and further restrict that query to scan_type fMRI, only fMRI images will appear and only the image03 structure will be shown.  To see other data structures, select "Find All Subject Data" which will query all data for those subjects. When a secord or third filter is applied, an AND condition is used.  A subject must exist in all filters.  If the subject does not appear in any one filter, that subjects data will not be included in your filter cart. If that happens, clear your filter cart, and start over.  

It is best to package more data than you need and access those data using other tools, independent of the NDA (e.g. miNDAR snapshot), to limit the data selected.  If you have any questions on data access, are interested in using avaialble web services, or need help accessing data, please contact us for assistance.  

Frequently Asked Questions

Glossary

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NDA provides a single access to de-identified autism research data. For permission to download data, you will need an NDA account with approved access to NDA or a connected repository (AGRE, IAN, or the ATP). For NDA access, you need to be a research investigator sponsored by an NIH recognized institution with federal wide assurance. See Request Access for more information.

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Household Demographics and Medication History

hdmh

01

Household Demographics and Medication history of subject

Download Definition as
Download Submission Template as
Element NameData TypeSizeRequiredDescriptionValue RangeNotesAliases
subjectkeyGUIDRequiredThe NDAR Global Unique Identifier (GUID) for research subjectNDAR*
src_subject_idString20RequiredSubject ID how it's defined in lab/projectclinical_barcode
interview_dateDateRequiredDate on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYYRequired fieldbl_visit_date, date_demographics
interview_ageIntegerRequiredAge in months at the time of the interview/test/sampling/imaging.0 :: 1260Age 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.ch_age
sexString20RequiredSex of the subject
M;F
M = Male; F = Femalech_sex, gender
raceString30RequiredRace of study subject
American Indian/Alaska Native; Asian; Hawaiian or Pacific Islander; Black or African American; White; More than one race; Unknown or not reported
race_dem
ethnic_groupString255RecommendedEthnic groupethnicity_dem
ca243IntegerRecommendedWhat handedness do you consider yourself?1::31=Right; 2=Left; 3=Mixedoverall_handedness
dmg_q54IntegerRecommendedtotal number of full siblings0::990 - 99full_sib_total
dmg_q55IntegerRecommendedtotal number of half siblings0::990 - 99half_sib_total
otherraceString100Recommendedspecify other raceThe following questions are about you or the child's family.race_other_dem
fh07IntegerRecommended7. Subject adopted0;1;9dem_adopted
das1msString200RecommendedMarital statusdem_marital_status
dmg_curlvcirIntegerRecommendedchild current living circumstances1::81=Parental home (at least one parent) 2=Relatives (other than parents) 3=With (child's) boyfriend/girlfriend or spouse (includes common law arrangement) 4=With unrelated adults 5=Foster home 6=Group home 7=Institution 8=Othersubject_living_dem
ses1jobString100RecommendedHead of Household: Job Titledem_head_job_title
occupationIntegerRecommended(or OCCUP); Hollingshead Status - HEAD OF HOUSEHOLD1::91 = Farm Laborers/Menial Service Workers, Welfare Recipients; 2 = Unskilled Workers; 3 = Machine Operators, Semi-Skilled Workers; 4 = Smaller Business Owners, Skilled Manual Workers, Craftsmen, Tenant Farmers; 5 = Clerical and Sales Workers, Small Farm and Business Owners; 6 = Technicians, Semi-Professionals and Small Business Owners; 7 = Smaller Business Owners, Farm Owners, Managers, Minor Professionals; 8 = Administrators, Lesser Professionals, Proprietors of Medium-Sized Businesses; 9 = Higher Executives, Proprietors of Large Businesses, Major Professionalsdem_head_hollingshead
emplyIntegerRecommendedHEAD OF HOUSEHOLD Presently Employed0;1;2;70 = NO; 1 = YES - PART TIME; 2 = YES - FULL TIME; 7 = RETIREDdem_head_employed
ses2jobString50RecommendedSpouse/Significant Other: Job Titledem_spouse_job_title
ses2educIntegerRecommendedSpouse/Significant Other: Education1::71 = Less than 7th Grade; 2 = Jr. High School (7th/8th/9th grade); 3 = Some High School (10th/11th/12th grade); 4 = High School Graduate; 5 = Some College (at least 1 year); 6 = Standard College Degree; 7 = Graduate Professional Trainingdem_spouse_education
occupationspIntegerRecommended(or OCCUPSP); Hollingshead Status - SPOUSE1::91 = Farm Laborers/Menial Service Workers, Welfare Recipients; 2 = Unskilled Workers; 3 = Machine Operators, Semi-Skilled Workers; 4 = Smaller Business Owners, Skilled Manual Workers, Craftsmen, Tenant Farmers; 5 = Clerical and Sales Workers, Small Farm and Business Owners; 6 = Technicians, Semi-Professionals and Small Business Owners; 7 = Smaller Business Owners, Farm Owners, Managers, Minor Professionals; 8 = Administrators, Lesser Professionals, Proprietors of Medium-Sized Businesses; 9 = Higher Executives, Proprietors of Large Businesses, Major Professionals; 88 = not applicable; 99 = missingdem_spouse_hollingshead
spouse_emplIntegerRecommendedIs your spouse currently employed0::2; 70=No; 1=Yes part-time; 2=Yes full-time; 7=Retireddem_spouse_employed
educIntegerRecommendedHEAD OF HOUSEHOLD Education1::71 = Less than 7th Grade; 2 = Jr. High School (9th Grade); 3 = Some High School (10th or 11th Grade); 4 = High School Graduate; 5 = Some College (at least 1 year); 6 = Standard College Degree; 7 = Graduate Professional Trainingdem_head_education
respondentString20RecommendedRespondentMother;Father;Both; Child; Other; Parentinformant_dem
suptIntegerRecommendedReceives support if parent's divorced or separated?0; 10 = No; 1 = Yesdem_divorced_support
demo6IntegerRecommendedSisters0::90=none in home; 1= one in home; 2= two in home; 9=9 in homesisters_dem
d6c1IntegerRecommendedNumber of full sistersfull_sist_total
d6e1IntegerRecommendedNumber of half sistershalf_sis_total
demo5IntegerRecommendedBrothers0::90=none in home; 1= one in home; 2= two in home; 9=9 in homebrothers_dem
d6b1IntegerRecommendedNumber of full brothersfull_bro_total
d6f1IntegerRecommendedNumber of adopted brothershalf_bro_total
medication1_nameString500RecommendedName first medication that the participant has taken0 = No medication; 999= Legitimately skippedmed_1
medication2_nameString200RecommendedName second medication that the participant has taken0 = No medication; 999= Legitimately skippedmed_2
medication3_nameString150RecommendedName third medication that the participant has taken0 = No medication; 999= Legitimately skippedmed_3
medication4_nameString100RecommendedName fourth medication that the participant has taken0 = No medication; 999= Legitimately skippedmed_4
medication5_nameString500RecommendedName fifth medication that the participant has taken0 = No medication; 999= Legitimately skippedmed_5
medication6_nameString500RecommendedName sixth medication that the participant has taken0 = No medication; 999= Legitimately skippedmed_6
medication7_nameString100RecommendedName seventh medication that the participant has taken0 = No medication; 999= Legitimately skippedmed_7
medication8_nameString100RecommendedName eighth medication that the participant has taken0 = No medication; 999= Legitimately skippedmed_8
medication9_nameString100RecommendedName ninth medication that the participant has takenmed_9
medication10_nameString100RecommendedName tenth medication that the participant has takenmed_10
medication11_nameString100RecommendedMedication 11 namemed_11
medication12_nameString100RecommendedMed name12med_12
medication13_nameString100RecommendedMedication 13 namemed_13
medication14_nameString100RecommendedMedication 14 namemed_14
medication15_nameString100RecommendedMedication 15 namemed_15
medication16_nameString100RecommendedMed name16med_16
medication17_nameString100RecommendedMed name17med_17
medication18_nameString100RecommendedMed name18med_18
medication19_nameString100Recommendedmedication name 19med_19
medication20_nameString100Recommendedmedication name 20med_20
medication21_nameString100Recommendedmedication name 21med_21
medication22_nameString100Recommendedmedication name 22med_22
medication23_nameString100Recommendedmedication name 23med_23
medication24_nameString100Recommendedmedication name 24med_24
medication25_nameString100Recommendedmedication name 25med_25
medication26_nameString100Recommendedmedication name 26med_26
medication27_nameString100Recommendedmedication name 27med_27
medication28_nameString100Recommendedmedication name 28med_28
medication29_nameString100Recommendedmedication name 29med_29
medication30_nameString100Recommendedmedication name 30med_30
basline_medsIntegerRecommendedHas participant taken medications (including OTC) at screening/baseline visit?0::10= No; 1= Yes
six_mo_medsIntegerRecommendedHas participant taken medications (including OTC) between baseline and 6 months follow up?0::10= No; 1= Yes
twentyfour_mo_medsIntegerRecommendedHas participant taken medications (including OTC) between 6 month and 24 month follow up?0::10= No; 1= Yes
sesIntegerRecommendedHollingshead SES ScoreSES at age of entry to studydem_social_status_num
sestotIntegerRecommendedSocio-Economic Status (SES)1::51 = SES score of 08 to 19;2 = SES score of 20 to 29;3 = SES score of 30 to 39;4 = SES score of 40 to 54;5 = SES score of 55 to 66dem_social_status_range
education_level_demIntegerRecommendedLevel of Education - Subject0::14; 99; 9990= Kindergarten; 1= First grade; 2= Second grade; 3= Third grade; 4= Fourth grade; 5= Fifth grade; 6= Sixth grade; 7= Seventh grade; 8= Eighth grade; 9= Ninth grade; 10= Tenth grade; 11= Eleventh grade; 12= Twelfth grade; 13= Special school; 14= Out of school; 99= Other; 999= Unknown
srs_respond_detail_oth_specString250RecommendedRespondent detail, specify otherinformant_other_dem
living_other_demString25RecommendedIf subject is living with other person, please specify
demo_siblingscountIntegerRecommendedNumber of siblings888 = not applicable; 999 = missingtotal_sib_dem
fh13IntegerRecommendedBirth order0::13; 9999 = Missing valuebirth_order_dem
dem_adopted_relatedIntegerRecommendedIf subject is adopted, are adoptive parent(s) also biologically related to subject?0::10= No; 1= Yes
dem_adoptive_relationshipIntegerRecommendedIf subject's adoptive parents are biologically related, please specify relationship:1::131= Maternal Grandmother only; 2= Maternal Grandfather only; 3= Both Maternal Grandparents; 4= Paternal Grandmother only; 5= Paternal Grandfather only; 6= Both Paternal Grandparents; 7= Maternal Aunt only; 8= Maternal Uncle only; 9= Both Maternal Aunt and Uncle; 10= Paternal Aunt only; 11= Paternal Uncle only; 12= Both Paternal Aunt and Uncle; 13= Other relative
dem_adoptive_related_otherString50RecommendedIf subject's adoptive parents are other relatives, please specify
p002_specifyString500RecommendedDescribe Allergych_allergies
upregIntegerRecommendedPregnant - Urine test1::3; 91=Positive; 2=Negative; 3=Not done; 9=Equivocal (Must retest)ch_pregnancy_baseline
mnstrdtDateRecommendedDate of Last Menstrual Periodlast_period_date_baseline
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.

Distribution for DataStructure: hdmh01 and Element:
Chart Help

Filters enable researchers to view the data shared in NDA before applying for access or for selecting specific data for download or NDA Study assignment. For those with access to NDA shared data, you may select specific values to be included by selecting an individual bar chart item or by selecting a range of values (e.g. interview_age) using the "Add Range" button. Note that not all elements have appropriately distinct values like comments and subjectkey and are not available for filtering. Additionally, item level detail is not always provided by the research community as indicated by the number of null values given.

Filters for multiple data elements within a structure are supported. Selections across multiple data structures will be supported in a future version of NDA.