ID

45040

Description

Principal Investigator: David Weir, PhD, University of Michigan, Ann Arbor, MI, USA MeSH: Aging,Neoplasms,Arthritis,Lung Diseases, Obstructive,Dementia,Heart Diseases,Heart Failure,Hypertension,Myocardial Infarction,Diabetes Mellitus,Hypercholesterolemia,Obesity,Body Weight,Mobility Limitation,Pain,Cholesterol,Hemoglobin A, Glycosylated,C-Reactive Protein,Cystatin C,Depression,Alcohol Drinking,Smoking,Personality,Life Style,Cognition,Demography,Ethnic Groups,Health Status,Population Groups,Housing,Independent Living,Socioeconomic Factors,Career Mobility,Educational Status,Employment,Family Characteristics,Income,Occupations,Poverty,Social Change,Social Class,Social Conditions,Risk Factors https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000428 *Introduction to V2: *This data release comprises data from the V1 release combined with approximately 3,000 additional samples, collected during the HRS 2010 field period. The 2010 data include samples from a random half of the new cohort enrolled in 2010 along with a significant expansion of the minority sample. *Description:* The University of Michigan Health and Retirement Study (HRS) is a longitudinal panel study that surveys a representative sample of approximately 20,000 people in America over the age of 50 every two years. Supported by the National Institute on Aging (NIA U01AG009740) and the Social Security Administration, the HRS explores the changes in labor force participation and the health transitions that individuals undergo toward the end of their work lives and in the years that follow. The study collects information about income, work, assets, pension plans, health insurance, disability, physical health and functioning, cognitive functioning, and health care expenditures. Through its unique and in-depth interviews, the HRS provides an invaluable and growing body of multidisciplinary data that researchers can use to address important questions about the challenges and opportunities of aging. Because of its innovation and importance, the HRS has become the model and hub for a growing network of harmonized longitudinal aging studies around the world. *Origins of the HRS.* As the population ages it is increasingly important to obtain reliable data about aging and topics that are relevant to a range of policy issues in aging. To address this need, the National Institutes on Aging (NIA) established a cooperative agreement with the University of Michigan Institute for Social Research to collect such data. The HRS launched data collection in 1992 and has re-interviewed the original sample of respondents every two years since then. By adding new cohorts and refreshing the sample, the HRS has grown to become the largest, most representative longitudinal panel study of Americans 50 years and older. *HRS Study Design.* The target population for the original HRS cohort includes all adults in the contiguous United States born during the years 1931-1941 who reside in households, with a 2:1 oversample of African-American and Hispanic populations. The original sample is refreshed with new birth cohorts (51-56 years of age) every six years. The sample has been expanded over the years to include a broader range of birth cohorts as well. The target population for the AHEAD survey consists of United States household residents who were born in 1923 or earlier. Children of the Depression (CODA) recruits households born 1924-1930, War Babies 1942-47, Early Boomers 1948-53, and Mid-Boomers 1954-59. Data collection includes a mixed mode design combining in-person, telephone, mail, and Internet. For consenting respondents, HRS data are linked at the individual level to administrative records from Social Security and Medicare claims. *Genetic Research in the HRS.* The HRS has genotyped 2.5 million single nucleotide polymorphisms (SNPs) on respondents using Illumina's Human Omni2.5-Quad (Omni2.5) BeadChip. The genotyping was performed by the NIH Center for Inherited Disease Research (CIDR). Saliva was collected on half of the HRS sample each wave starting in 2006. In 2006, saliva was collected using a mouthwash collection method. From 2008 onward, the data collection method switched to the Oragene kit. Saliva completion rates were 83% in 2006, 84% in 2008, and 80% in 2010 among new cohort enrollees. HRS Phenotypic data. Phenotypic data are available on a variety of dimensions. Health measures include physical/psychological self-report, various health conditions, disabilities, cognitive performance, health behaviors (smoking, drinking, exercise), physical performance and anthropomorphic measures, and biomarkers (HbA1c, Total Cholesterol, HDL, CRP, Cystatin-C). Data are also available on health services including utilization, insurance and out-of-pocket spending with linkage to Medicare records. Economic measures include employment status/history, earnings, disability, retirement, type of work, income by source, wealth by asset type, capital gains/debt, consumption, linkage to pensions, Social Security earnings/benefit histories. There is also extensive information on family structure, proximity, transfers to/from of money, time, social and psychological characteristics, as well as a wide range of demographics. Performance on a cognitive test combining immediate and delayed word recall was selected as an example trait for the dbGaP data release. In the immediate word recall task the interviewer reads a list of 10 nouns to the respondent and asks the respondent to recall as many words as possible from the list in any order. After approximately five minutes of asking other survey questions, the respondent is asked to recall the nouns previously presented as part of the immediate recall task. The total recall score is the sum of the correct answers to these two tasks, with a range of 0 to 20. Researchers who wish to link to other HRS measures not in dbGaP will be able to apply for access from HRS. A separate Data Use Agreement (DUA) will be required for linkage to the HRS data. See the HRS website (http://hrsonline.isr.umich.edu/gwas) for details.

Link

https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000428

Keywords

  1. 7/31/22 7/31/22 - Simon Heim
Copyright Holder

David Weir, PhD, University of Michigan, Ann Arbor, MI, USA

Uploaded on

July 31, 2022

DOI

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License

Creative Commons BY 4.0

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dbGaP phs000428 Health and Retirement Study (HRS)

Subject ID, consent group, subject source, and source subject ID of participants involved in the "Health and Retirement Study (HRS)" project.

pht002612
Description

pht002612

SUBJID as local subject identifier
Description

SUBJECT_ID

Data type

text

Alias
UMLS CUI [1,1]
C2348585
'Coriell' for HapMap samples, NA otherwise
Description

SUBJECT_SOURCE

Data type

text

Alias
UMLS CUI [1,1]
C3178913
UMLS CUI [1,2]
C2347026
Coriell ID for HapMap samples, NA otherwise
Description

SOURCE_SUBJECT_ID

Data type

text

Alias
UMLS CUI [1,1]
C3178913
UMLS CUI [1,2]
C1299222
Subject consent group.
Description

CONSENT

Data type

text

Alias
UMLS CUI [1,1]
C0021430
UMLS CUI [1,2]
C1257890

Similar models

Subject ID, consent group, subject source, and source subject ID of participants involved in the "Health and Retirement Study (HRS)" project.

Name
Type
Description | Question | Decode (Coded Value)
Data type
Alias
Item Group
pht002612
SUBJECT_ID
Item
SUBJID as local subject identifier
text
C2348585 (UMLS CUI [1,1])
SUBJECT_SOURCE
Item
'Coriell' for HapMap samples, NA otherwise
text
C3178913 (UMLS CUI [1,1])
C2347026 (UMLS CUI [1,2])
SOURCE_SUBJECT_ID
Item
Coriell ID for HapMap samples, NA otherwise
text
C3178913 (UMLS CUI [1,1])
C1299222 (UMLS CUI [1,2])
Item
Subject consent group.
text
C0021430 (UMLS CUI [1,1])
C1257890 (UMLS CUI [1,2])
Code List
Subject consent group.
CL Item
Subjects did not participate in the study, did not complete a consent document and are included only for the pedigree structure and/or genotype controls, such as HapMap subjects (0)
CL Item
Non-profit research use only (NPR) (1)

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