DATA and DATA SETS

Dementia and Cognitive Impairment:

Interagency Collaborative Data Collection Efforts

Since 2012, the Virginia Department for Aging and Rehabilitative Services (DARS) has been working with staff from other Virginia Health and Human Resources (HHR) agencies to compile available data on individuals with Alzheimer’s disease and other dementias and their caregivers. In July of 2013, DARS created a Dementia Services Coordinator to focus on the day-to-day implementation of Virginia’s Dementia State Plan, which, among other goals, emphasizes improved data collection and analysis.

Working with a team of experts from state HHR agencies, the Virginia Center on Aging, the Virginia Alzheimer’s Disease and Related Disorders Commission, and the Alzheimer’s Association, DARS identified data collection sources that may provide information about the prevalence of dementia and its service delivery impact on state agencies.

The report below presents the final results of that data collection and analysis.

DARS would like to thank all the state agencies, experts and advocates who contributed to the development of the report.

Any questions about the report should be directed to Devin Bowers with DARS at (804) 662-9154 or Devin.Bowers@dars.virginia.gov.

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Dementia and Cognitive Impairment: Interagency Collaborative Data Collection Efforts

Prevalence Data and Estimates

Page updated October 2016

Questions on the following sets of statistics may be directed to Devin Bowers, Virginia Department for Aging and Rehabilitative Services.

2012-2014 VA CMS Chronic Conditions:

Percentage of All Medicare Beneficiaries Diagnosed with Alzheimer’s Disease and Dementia

2007-2014 Medicare Beneficiaries Prevalence

Chronic Conditions Prevalence State/County – 2014

Chronic Conditions Prevalence State/County Table

Cognitive Decline in VA:

Data from the 2012 & 2013 Behavioral Risk Factor Surveillance System

Percentange of Long-Term Care Services Users with Diagnosed Alzheimer’s and 0ther Dementias, 2012

Percentange of Long-Term Care Services Users With Diagnosed Alzheimer's and Other Dementias, 2012

Alzheimer’s Association State by State Data

Alzheimer's Association State by State Data

2016 Alzheimer’s Association Statistics: Virginia

2016 Alzheimer's Association Statistics: Virginia

List of Publicly Available Data Sets on Alzheimer’s Disease and Related Dementias

Accelerating Medicine Project for Alzheimer’s Disease Knowledge Portal

The AMP-AD program is a precompetitive partnership between government, industry and non-profit foundations focused on the discovery of novel, clinically relevant therapeutic targets and the development of biomarkers to aid the validation of existing therapeutic targets.

The goal of the Target Discovery and Preclinical Validation project is to shorten the time between discovery of potential drug targets to development of new drugs for the treatment and prevention of Alzheimer’s disease, by integrating the analysis of large scale molecular data from human brain samples with network modeling approaches and experimental validation, and by enabling rapid and broad sharing of data and analytical tools.

The project is divided between academic teams, each of whom is generating high dimensional data from a postmortem brain sample cohort as well as from an animal or cellular model system over the course of a 5 year grant. These projects are structured such that human data will be generated and released in the first years of the grant with the model system data and analytical results to follow. Data is deposited by each partner on a quarterly basis, with data from one quarter set to go public in the release scheduled for the following quarter.

The AMP-AD Knowledge Portal is designed for the dissemination of data and analyses to the broader research community in a manner that enables transparency and reproducibility in research.

The content of this portal can be accessed through: https://www.synapse.org/#!Synapse:syn2580853.

Alzheimer’s Disease Neuroimaging Initiative (ADNI)

Ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of AD. The primary goal of ADNI has been to test whether serial magnetic resonance imaging (MRI), positron emission tomography (PET), biological markers, and clinical and neuropsychological assessment can be combined to assess the progression of MCI and early AD.

Genome Wide Association Study (GWAS) data are also available and whole genome sequencing data of 800 ADNI subjects will be available in the summer of 2013. Applications for ADNI data are reviewed by the ADNI Data Sharing and Publications Committee (DPC), usually within one week. Each application is reviewed to ensure investigator affiliation with a scientific or educational institution and to assess the proposed research. ADNI is funded by the NIA and other NIH Institutes and by the pharmaceutical and other industries and several foundations through the Foundation for the NIH (fNIH). ADNI is administered by NIH through a cooperative agreement grant to UCSF. FNIH coordinates the private partners, receives donations and convenes the Private Partner Scientific Board.

The ADNI database is administered by the ADNI Informatics Core, based at the Laboratory of Neuro Imaging (LONI) at UCLA.

Link: http://www.adni-info.org/

Information on this dataset was obtained from: http://geoffreybeenechallenge.org/mind-the-data/

C-Path Online Data Repository (CODR)

Database for Alzheimer’s disease created by the Coalition Against Major Diseases (CAMD). Contains de-identified longitudinal clinical data on 6,500 patients from the control arms of 24 clinical studies of AD including three studies on MCI. CAMD worked in conjunction with the Clinical Data Interchange Standards Consortium (CDISC) to develop Alzheimer’s-specific data standards following the CDISC Study Data Tabulation Model (SDTM). An understanding of the CDISC SDTM standard is essential to navigating this database.

This project is funded in part by the FDA and Science Foundation Arizona. More information on this open-source standard data format can be found at www.cdisc.org.

Link: http://c-path.org/programs/camd/camd-overview/

Information on this dataset was obtained from: http://geoffreybeenechallenge.org/mind-the-data/

Disability & Health Data System (DHDS)

Disability & Health Data System (DHDS) provides instant access to state-level health and demographic data about adults with disabilities. Most data displayed in DHDS come from the Behavioral Risk Factor Surveillance System (BRFSS). The BRFSS is a state-based telephone interview in which an interviewer asks questions on a variety of health risks and behaviors, chronic conditions, and demographics. For more information on the BRFSS, you can visit: http://www.cdc.gov/BRFSS/

Additional data sources used to calculate disability-associated healthcare expenditures are: the National Health Interview Survey (NHIS), the Medical Expenditure Panel Survey (MEPS), and the National Health Expenditure Accounts (NHEA). More information on these sources can be found in the following article: Anderson WL, Armour BS, Finkelstein EA, Wiener JM. Estimates of state-level health-care expenditures associated with disability. Public Health Rep. 2010;125:44–51.

DHDS contains three types of data: Disability Status and Types, Limitation Status, and Psychological Distress Status. Disability Status and Types data are available for a number of demographic and health indicators and can be viewed in Maps & Data Tables, State Profiles, and Dual Area Profiles. Limitation Status and Psychological Distress Status data are available for some of the indicators and can be viewed in State Profiles. Indicators are grouped into: Disability Estimates, Demographics, Health Risks & Behaviors, Prevention & Screenings, Barriers & Costs of Health Care, General Health Conditions, Chronic Conditions, and Mental & Emotional Health. DHDS also contains data on disability-associated healthcare expenditures.

DHDS provides information on cognitive, mobility, vision, self-care, and independent living types of disability, using data from BRFSS, which began collecting these data in 2013. Data are available at the state, division, region, and national levels as well. For questions about the data, please visit: http://dhds.cdc.gov/help/faq or email the DHDS team at dhds@cdc.gov

Healthy Aging Data

The Healthy Aging Data Portal is a compilation of numerous other reports published by the CDC that are intended to provide data on vital indicators and strategies for public health and aging professionals, researchers, healthcare providers, journalists, decision makers, and others interested in older adult health. While the data are a critical element, they are intended to be used as a basis for action.

Healthy People 2020:  Healthy People objectives have been implemented to measure the impact of prevention activities, encourage collaborations across communities and sectors, and empower individuals toward making informed health decisions. These objectives set specific targets to help guide states, communities, and professional organizations to identify, develop, and evaluate programs and policies that promote healthy aging.

This information can help to support:

  • Grant writing: The Healthy Aging Data Portal contains context and key statistics related to the health of older adults at the national, state and selected metropolitan/micropolitan levels, which can justify the need for proposed programs.
  • Program and strategic planning: State and local-level data can be used to identify particular areas of need and target resources to the most urgent health issues.
  • Health news reporting: The introductory material in each hard copy report, indicator data, and supporting informational resources, provide excellent background needed by journalists working at the national, state, and local levels. Data can be used to highlight particular areas of need or success stories. Spotlight topics and state and community examples illustrate potential solutions.

For more information, please visit: http://www.cdc.gov/aging/agingdata/index.html

Minnesota Population Center Data Sets

The Minnesota Population Center is home to the following data set series:

  • Integrated Public Use Microdata Series (IPUMS) USA: Provides individual-level samples of the U.S. censuses of 1850-2000 and the American Community Survey from 2000 onwards. Along with hundreds of variables on sociodemographic characteristics, work, migration, and housing, IPUMS-USA includes health variables on insurance coverage, births in the past 12 months, and multiple types of disability. Geographic identifies are available for states, MSAs, and sub-state areas with at least 100,000 or 400,000 population. Visit: http://usa.ipums.org.
  • IPUMS-Current Population Survey (CPS): Provides individual-level data from 1962 forward for the Annual Social and Economic Supplement of the Current Population Survey. Along with variables found in the census, the CPS data include hundreds of additional consistently-coded variables on employment, income, and health. Detailed information is available on disability income, types of disability, and health insurance. Geographic variables identify states and MSAs. Visit: http://cps.ipums.org.
  • IPUMS-International: Provides individual-level samples from over 200 censuses from across the world, for the 1960s to the present. For low resource countries, household variables often cover sanitation and births and deaths in the previous 12 months. For individuals, demographic, education, and work variables are broadly available; health variables on such topics of disability and access to health care are available for some counties. Subnational states or regions are usually identified, and some countries identify municipalities. Visit: http://international.ipums.org.
  • Integrated Health Interview Series (IHIS): Provides annual individual-level data from 1963 to the present, with national-level geography and data on children and adults. Based on the U.S. National Health Interview Survey, IHIS offers over 12,000 consistently-coded variables covering such topics as general health status, acute and chronic illnesses, functional limitations, access to and use of traditional and alternative medicine, insurance coverage, cancer family history, mental health, health behaviors, and mortality. IHIS allows researchers to investigate a half-century of dramatic change in U.S. public health. Visit: http://www.ihis.us.
  • National Historical Geographic Information System (NHGIS): Provides aggregate census data and GIS-compatible boundary files for the U.S. between 1790 and 2000. NHGIS includes statistical data for states and counties (for 1790-present), census tracts (for 1910-present), and many other geographic entities (for 1970-present). Users can create maps with NHGIS data by downloading boundary files and using them in a GIS. Aggregate data are available on a wide range of topics, including agriculture, housing, economic indicators, general population characteristics, and social and environmental indicators. Visit: http://www.nhgis.org.
  • American Time Use Survey (ATUS-X): Provides easy access to individual-level data from the American Time Use Survey, a time diary study from 2003 forward. ATUS-X users can create measures of time in user-defined activity aggregations. Along with state, MSA, sociodemographic characteristics, BMI, and general health, information is available on time spent in such health-related activities as eating and drinking, exercising, walking, sleeping, resting because of illness, and using health care services. Visit: http://www.atusdata.org.

Major funding for the Minnesota Population Center data projects provided by the National Science Foundation and the National Institutes of Health. MPC data and documentation are freely available via the web at http://usa.ipums.org. MPC datasets are available to researchers who complete an online registration form and agree to use the data responsibly. IPUMS-International data can be used only for scholarly or educational purposes, and the online application requires a short description of the researcher’s need for these data.

National Health and Aging Trends Study (NHATS)

NHATS was initiated in recognition of the shifting landscape of late-life and the need for a database to support the scientific study of how daily life changes as we age. Designed by an interdisciplinary team of researchers, and funded by the National Institute on Aging, with data collection by Westate, NHATS is intended as the primary platform for scientific inquiry to guide efforts to reduce disability, maximize functioning, and enhance quality of life of older Americans. NHATS has two primary scientific aims: 1) to promote scientific study of late-life disability trends and dynamics, and 2) to advance our understanding of the social and economic impact of late-life functional changes for older people, their families, and society. The NHATS sample is nationally representative of Medicare beneficiaries age 65 and older.

Over 8,000 people participated in the baseline 2-hour interview in 2011. NHATS administers a newly-developed validated disability protocol that includes self-reported measures of capacity; accommodations; the environments in which individuals live; mobility, self care, and household activities; and participation. These self reports are supplemented by performance-based measures of physical and cognitive capacity. Other study content captures measures of antecedents and consequences of disability. Participants will be re-interviewed annually. A survey of informal caregivers to NHATS participants who received assistance with mobility, household or self care activities was conducted as part of the 2011 baseline.

Funded by DHHS/ASPE, the National Study of Caregiving (NSOC) provides information on caregiver activities, support services, and effects of caregiving on work and family.

Go to: www.nhats.org for Round 1 data, study documentation, technical papers, and other study-related materials.

The National Institute on Aging Genetics of Alzheimer’s Disease Data Storage Site (NIAGADS)

The National Institute on Aging Genetics of Alzheimer’s Disease Data Storage Site (NIAGADS) provides qualified investigators with access to a national genetics data repository pertaining to late-onset Alzheimer’s disease (AD). All Genetic Data obtained by NIA funded studies is deposited at NIAGADS, another NIA approved website or both when possible.

The NIAGADS and other NIA approved sites will make Genetic Data, including DNA marker genotypes, DNA sequencing and RNA expression data, and Associated Phenotypic Data available for secondary analysis in accordance with guidelines from the NIA. Qualified investigators can submit proposals to request access to available data. The National Institutes of Health (NIH) works to make publicly funded research resources, including data, collected biological materials and important analysis methods, available for secondary data analysis, further research, development and application.

The NIAGADS aligns with this NIH policy, is supported by a five-year NIH/NIA grant and is a cooperative agreement between the University of Pennsylvania and the NIA. Proposals requesting access to datasets are reviewed by a Data Use Committee (DUC), which is also responsible for facilitating the sharing of AD research with the community.

For more information on the NIAGADS visit https://www.niagads.org/ .  

Panel Study of Income Dynamics (PSID)

The PSID is the world’s longest running nationally representative household panel survey. With more than 40 years of data on the same families and their descendents, the PSID is a cornerstone of the data infrastructure for empirically based social science research in the U.S.

The PSID gathers data on the family as a whole and on individuals residing within the family, emphasizing the dynamic and interactive aspects of family economics, demography, and health. PSID data were collected annually 1968-97 and biennially after 1997. Potential research areas include: inter- and intragenerational connections in health; socioeconomic status and health; life course modeling; contextual effects on social and economic outcomes; financial planning and well-being; changes in wealth holdings; and mortality modeling. A supplemental data collection (DUST) was conducted in 2009 and 2013 to investigate connections with disability, time use, and well-being among older couples. All waves of PSID are freely accessible through the web-based PSID Data Center.

The user-friendly Data Center provides options for automatic merges of data across all waves. PSID is sponsored by the National Science Foundation, the National Institute on Aging, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the Center on Philanthropy at Indiana University, the U.S. Department of Agriculture – Economic Research Services, the Office of the Assistant Secretary for Planning and Evaluation, Dept. of Health and Human Services, and the U.S. Department of Housing and Urban Development.

For more information, visit http://psidonline.isr.umich.edu/.

Information on this data was obtained from: http://psidonline.isr.umich.edu/.

UVA Weldon Cooper Center Demographics Research Group: Virginia Population Data

The University of Virginia Weldon Cooper Center population estimates, prepared annually, are the official figures for the commonwealth of Virginia. The estimates are based on changes since 2010 in housing stock, school enrollment, births, deaths and drivers’ license issuances. They are used by state and local government agencies in revenue sharing, funding allocations, planning and budgeting. The Demographics Research Group, within the Weldon Cooper Center, produces the official annual population estimates for Virginia and its localities; conducts practical and policy-oriented analysis of census and demographic data under contract; and communicates rigorous research and its policy implications to clients including state and local governments, employers, non-profit organizations, and the general public, through meaningful, intuitive publications, and presentations. Beginning with more than fifty years generating the official annual population estimates for the Commonwealth of Virginia, our researchers have advanced proficiency in:

  • formulating clear research questions that direct study toward strategic and actionable data
  • statistical analysis of data sets of all sizes and types
  • working with administrative record data you may provide as well as identifying other data sets to illuminate your questions
  • producing clear results (and recommendations, if desired)
  • developing materials to communicate trends and represent the answers to your questions
  • preparing and presenting accessible, easy-to-grasp data visualizations and reports
  • working with governments at the state, local, and federal levels
  • serving the needs of private companies and non-profit agencies and organization to understand and meet the needs of clients and customers

Professionals conduct custom-designed research and provide consulting services under contract for a wide variety of clients. Working in close communication with you, staff will develop a scope of work and an estimated cost for the project.

Contact Qian Cai (pronounced “Chien Tsai”), Director of the Demographics Research Group, for assistance: qian.cai@virginia.edu • 434-982-5581. To view annual populations reports from the Demographics Research Group, visit: http://www.coopercenter.org/demographics.

You can also call (434) 982-0812 or email demographics@virginia.edu.

Aging Integrated Database (AGID)

The Aging Integrated Database (AGID) is an on-line query system based on Administration on Aging(AoA)-related data files and surveys, and includes population characteristics from the Census Bureau for comparison purposes. The purpose of the system is to:

  • Provide a single, user friendly source for a variety of information on AoA supportive services and comprehensive systems of care for older people and their caregivers
  • Allow users to quickly produce tables, maps, and other summary information from AoA-related data files and surveys, supplemented by Census-based population and demographic characteristics
  • Provide users full access to results from national surveys of recipients of Older Americans Act services and AoA Special Tabulations produced by the Census Bureau

The four options or paths through AGID provide different levels of focus and aggregation of the data – from individual data elements within Data-at-a-Glance to full database access within Data Files. The four options or paths through AGID were designed to provide different levels of focus and aggregation of the data – from individual data elements within Data-at-a-Glance, to State-level summaries in State Profiles, to detailed, multi-year tables in Custom Tables, and finally, to full database access within Data Files.

  • Data-at-a-Glance: Single data element at a time access to all of AGID’s state-level databases. Excellent tool for data mining or exploration of the various databases and their content, along with producing quick tables and geographical representations of key data elements.
  • State Profiles: Provides pre-populated tables of key data elements from OAA Programs for the selected state. The user also has the ability to make comparisons between one state and another state or one state and the total U.S. In addition, the location of the State Unit on Aging (SUA), Area Agencies on Aging (AAA), and Tribal Organizations (where applicable) are displayed in both map and tabular form.
  • Custom Tables: Powerful tool for producing detailed, multi-year tables. Users have the ability to select only those data elements applicable to their needs, and to further refine their results based on demographic stratifiers or geographic locations that are meaningful to their application. In addition, multiple years of data can be selected to analyze trends across time, while simple sorting tools have been incorporated to rank individual data elements across both time and geography.
  • Data Files: Provides access to the AoA survey databases and AoA Special Tabulations conducted by the Census Bureau. The individual survey data files are provided in CSV or SAS format and are supplemented by survey instruments, reporting requirements documents, codebooks with variable listings and frequency counts and percentages of all individual data elements, and SAS programming statements for loading and processing the data in SAS. AoA Special Tabulation results are provided in both Excel and XML format.

The databases that are currently available in the system are listed below. These files are updated on a periodic basis as new data become available.

AOA-Related Files include: State Program Reports (SPR); National Ombudsman Reporting System (NORS); Title VI Services by Tribal Organization; National Survey of Older Americans Act (OAA) Participants; and National Survey of Area Agencies on Aging (AAA).

Census Files include: State Level Population Estimates Data; County and PSA Level Population Estimates Data; Decennial Census 2010 Summary File 1 (SF1); American Community Survey (ACS) Public Use Microdata Sample (PUMS) 1-Year Files; and American Community Survey 2005-2009 Special Tabulation. Future releases of AGID will include annual updates to existing data, along with the addition of new data sources. A number of new AoA Special Tabulations will be added to the site. In addition, as resources permit, new functionality will be added including enhanced mapping and charting capabilities and other analytic tools.

AGID can be found by visiting: http://www.agid.acl.gov/.

American Community Survey (ACS)

The American Community Survey (ACS) is an ongoing survey that provides vital information about the United States and its populace on a yearly basis. This includes information on demographic, social, economic, and housing characteristics. Information from the survey generates data that help determine how more than $400 billion in federal and state funds are dispersed each year.

Public officials, planners, and entrepreneurs use the information obtained through the ACS to assess the past and plan for the future. The information obtained through the ACS provides an important tool for communities to use to see how they are changing. Every year, the U.S. Census Bureau contacts over 3.5 million households across the country to participate in the ACS.

For more information, please visit: http://www.census.gov/programs-surveys/acs/

CMS Virtual Research Data Center (VRDC) and ResDAC

The CMS VRDC is a virtual research environment that provides timelier access to Medicare and Medicaid program data in a more efficient and cost effective manner.  Researchers working in the CMS VRDC will have direct access to approved data files and be able to conduct their analysis within the CMS secure environment.  They will also have the ability to download aggregated reports and results to their own personal workstation. CMS data available through the VRDC includes: Master Beneficiary Summary File; Medicare Part A, B and D claims; Medicare Provider Analysis and Review (MedPAR) file; Medicare-Medicaid Linked file; Medicaid (MAX) files; and Assessment files. The CMS VRDC:

  • Satisfies all CMS privacy and security requirements
  • Enables researchers to access and perform their own analysis and manipulation of CMS data using the CMS infrastructure
  • Enables researchers to upload external data files into their workspace to analyze with the approved CMS data files
  • Provides access to the Research Identifiable Files
  • Provides access through a Virtual Private Network and virtual desktop

User Requirements: Must be experienced with SAS programming language; must have a broadband internet connection; must have Java 6 or greater installed on local machine; must have MS Internet Explorer or Mozilla Firefox; and must have Windows XP or newer Windows operating system

Request Materials and Submission Information:Email all required request materials to resdac@umn.edu.

For the initial submission, please send draft documents only (no signatures). Following ResDAC review and appropriate revisions to your request, you will email final materials to ResDAC, and ResDAC will forward them to CMS on your behalf. Data request Privacy Board reviews will now be on a rolling basis.

ResDAC: The Research Data Assistance Center (ResDAC) is a CMS contractor (Contract Number HHSM-500-2005-00027I) that provides free assistance to academic, government and non-profit researchers interested in using Medicare and/or Medicaid data for their research. ResDAC is staffed by a consortium of epidemiologists, public health specialists, health services researchers, biostatisticians, and health informatics specialists from the University of Minnesota.

ResDAC can be found at: http://www.resdac.org/. Costs for the data vary.

For more information on the CMS VRDC, visit: http://www.resdac.org/cms-data/request/cms-data-request-center.

Genetic Epidemiology Research on Aging (GERA) through the Genotypes and Phenotypes (dbGap)

Researchers will now have access to genetic data linked to medical information on a diverse group of more than 78,000 people, enabling investigations into many diseases and conditions. The data, from one of the nation’s largest and most diverse genomics projects—Genetic Epidemiology Research on Aging (GERA)—have just been made available to qualified researchers through the database of Genotypes and Phenotypes (dbGaP), an online genetics database of the National Institutes of Health.

The GERA cohort—average age 63—was developed collaboratively by Kaiser Permanente and the University of California, San Francisco (UCSF). The addition of the data to dbGaP was made possible with $24.9 million in support from the National Institute on Aging (NIA) and the National Institute of Mental Health, and the Office of the Director, all at NIH. Catherine Schaefer, Ph.D., of Kaiser Permanente Northern California and Neil Risch, Ph.D., of UCSF are co-principal investigators for GERA. The GERA cohort is part of the Research Program on Genes, Environment, and Health (RPGEH), which includes more than 430,000 adult members of the Kaiser Permanente Northern California system. Data from this larger cohort include electronic medical records, behavioral and demographic information from surveys, and saliva samples from 200,000 participants obtained with informed consent for genomic and other analyses.

The RPGEH database was made possible largely through early support from the Robert Wood Johnson Foundation to accelerate such health research. In addition to diseases and conditions traditionally associated with aging, such as cardiovascular disease, cancer and osteoarthritis, researchers can explore the potential genetic underpinnings of a variety of diseases that affect people in adulthood, including depression, insomnia, diabetes, certain eye diseases and many others representing a variety of disease domains. Researchers will also be able to use the database to confirm or disprove other studies that use data from relatively small numbers of people, as well as to increase the size and power of their samples by adding participants from GERA to meta-analyses. The large cohort will also serve as a reference source of controls that researchers can compare to individuals with different conditions that they have studied. The dbGap database will be updated and refreshed as information is added to the Kaiser-UCSF database. dbGaP was developed and is managed by the National Center for Biotechnology Information, a division of the National Library of Medicine at NIH.

Investigators who are interested in applying for access to this database should follow the procedures on the dbGaP website (http://www.ncbi.nlm.nih.gov/gap?db=gap), and can also find specific information on the data (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000674.v1.p1).

Health and Retirement Study (HRS)

The University of Michigan Health and Retirement Study (HRS) is a longitudinal panel study that surveys a representative sample of more than 26,000 Americans over the age of 50 every two years. Supported by the National Institute on Aging 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. Since its launch in 1992, the study has collected 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.

Health and Retirement Study data products are available without cost to registered users; however certain conditions of use apply.

For more information, visit: http://hrsonline.isr.umich.edu/.

MRC Dementias Research Platform UK (DPUK)

The MRC Dementias Research Platform UK (DPUK) is a multi-million pound public-private partnership, developed and led by the Medical Research Council, to accelerate progress in, and open up, dementias research. The aim of the DPUK is to accelerate research progress and develop knowledge leading to new drug treatments and other therapies that could prevent or delay the onset and progression of dementias.

The DPUK is directed by Dr. John Gallacher at the University of Cardiff, together with an executive team of investigators drawn from seven universities (Cambridge, Edinburgh, Imperial College London (ICL), Oxford, Newcastle, University College London (UCL) and Swansea), including the UCL-based MRC Unit for Lifelong Health and Ageing. The clinical research infrastructure award links DPUK with further universities, Manchester and Bristol.

The DPUK is creating the world’s largest population study for use in dementias research, bringing together two million participants aged 50 and over, from 22 existing study groups within the UK. Included are people from the general population, people known to be at-risk of developing dementia, and people diagnosed with early-stage dementia. By adding to information that we already know about the participants (such as their diet, exercise habits and previous infections) we hope to identify cognitive, genetic, physiological and imaging measures (biomarkers) to understand who is at risk of developing dementia and why the progression of dementia varies from person to person.

Using the UK Dementias Research Platform: The DPUK is being set up for use as a research resource for the scientific community.

Researchers intending to access the DPUK should contact Dr. John Gallacher in the first instance. The DPUK will have a dedicated web site with a single portal for access which will be operational by autumn, 2014, a link to which will be provided on this page. There is also be a dedicated help line (08000 232000; Mon-Sat 8am-7pm). Data produced through research using the UK Dementias Research Platform will be made openly available to the scientific community as the project progresses.

Researchers should seek grant funding for their work through the usual MRC or other funding routes.

Contacts: For more information regarding DPUK please contact:

Dr. John Gallacher
Institute of Primary Care & Public Health
Cardiff University School of Medicine
Neuadd Meirionnydd
Heath Park
Cardiff CF14 4YS, UK

Dr. Stephen Meader
Medical Research Council
2nd Floor, David Phillips Building
Polaris House, North Star Avenue
Swindon SN2 1FL, UK

National Alzheimer’s Coordinating Center (NACC)

Established by the National Institute on Aging/NIH to facilitate collaborative research by collecting data from 29 NIA-funded Alzheimer’s Disease Centers. NACC includes approximately 25,000 subjects, roughly equal parts cognitively normal, MCI and demented. These subjects have been examined annually for up to 6 years following the standardized Uniform Data Set. Of these subjects, approximately 2,200 have had autopsy data with detailed neuropathological features included in the database.

NACC data includes more than 700 variables, representing demographics, behavioral status, cognitive testing, medical history, family history, clinical impressions, and diagnoses. Requests are vetted by answering online a few brief questions describing the project. A NACC liaison will respond within one business day to acknowledge the request and, if needed, ask for clarifications. NACC offers a telephone consultation (206-543-8637). Statistical consultations on analysis plans are also available upon request.

Link: http://www.alz.washington.edu/

Information on this dataset was obtained from: http://geoffreybeenechallenge.org/mind-the-data/

National Institute on Aging’s Baltimore Longitudinal Study of Aging (BLSA)

The National Institute on Aging’s Baltimore Longitudinal Study of Aging (BLSA) is America’s longest-running scientific study of human aging. It began in 1958, when gerontology—the study of aging—was still very much in its infancy. Today, the BLSA is world-renowned, having generated thousands of scientific papers and made major contributions to our understanding of what it means to get older. Unlike a clinical trial, no interventions are tested in the BLSA. The BLSA is an observational study. Researchers measure physical and cognitive changes associated with aging in real time among a dedicated group of BLSA participants who come in for testing at regular intervals over the course of their lives.

Presently, participants under age 60 are assessed every 4 years; those aged 60 to 79 years come every 2 years, and participants aged 80 and older are assessed annually. During the assessment, they receive comprehensive health, cognitive, and functional evaluations that take nearly 3 days to complete. A consortium of scientists collects and analyzes data from this study population with the aim of characterizing normal and exceptional aging, along with age-associated health issues, such as frailty.   The BLSA measures:

  • Changes that occur over the aging process
  • Biological, behavioral, genetic, and environmental factors that account for these changes, helping researchers to understand why the effects of aging differ in different individuals
  • Potential predictors and risk factors for specific diseases, frailty, and other end-points reflecting success or failure to adapt to aging
  • Possible targets for interventions that may positively affect several aspects of the aging process and prevent age-related diseases
  • Factors that predict healthy aging across the life span

Researchers can submit an analysis proposal to use the data. More information about the BLSA study design and the process for submitting analysis proposals for review is available on the BLSA website. BLSA data are most suited for addressing:

  • outstanding mechanistic questions about the interaction of diseases and aging affecting functional status and quality of life in older people
  • understanding the natural history of the transition from health to diseases in aging individuals
  • identifying at an early, still asymptomatic stage, biomarkers that predict the development of certain diseases or a condition, such as diabetes or dementia

It is also important to note some limitations of the BLSA data. Because the BLSA was designed around mechanistic questions focused on longitudinal stability and change, it is not a traditionally representative epidemiological study. Therefore, the data are not suited for investigations of prevalence and incidence.

For more information on how to obtain BLSA data, please visit: http://www.blsa.nih.gov/.

National Longitudinal Surveys (NLS)

The NLS are a set of surveys sponsored by the Bureau of Labor Statistics (BLS) of the U.S. Department of Labor. These surveys have gathered information at multiple points in time on the labor market and other significant life events of several groups of men and women.

Each of the NLS samples consists of several thousand individuals, many of whom have been surveyed over several decades. Detailed health data are available for three ongoing NLS cohorts: 1) 1979 National Longitudinal Survey of Youth (NLSY79), 2) NLSY79 Children and Young Adult, and 3) 1997 National Longitudinal Survey of Youth. Health data were also collected for all four original NLS cohorts (Mature Women, Young women, Older Men, and Young Men), although in less detail than for the ongoing cohorts. In addition to general health topics, several cohorts have data are available on aging related issues, such as retirement, income and assets, physical health, psychological well-being, and others. More specifically, the aging-related cognitive function topic has been covered in varying detail for Mature Women, Older Men, and NLSY79 and the caregiving to ill or disabled family members topic has been covered in varying detail for NLSY79, Child and Young Adult, Mature Women, and Young Women).

NLS data are made available to researchers through Investigator (www.nlsinfo.org/investigator). Investigator allows users to search for variables of interest for any NLS cohort, create simple tabulations of the data, extract data files for analysis, and access documentation. NLS public data are immediately available and free of charge.

Visit www.bls.gov/nls for online access to questionnaires and other documentation, a searchable, annotated bibliography of NLS research, news releases, updates, information on obtaining restricted-access data, and much more.

Additional data sources

Additional data sources have been identified in a recent publication with the citation provided below:

Bell, J.F., Fitzpatrick, A.L., Copeland, C., Chi, G. Steinman, L., Whitney, R.L., … Snowden, M. (2014). Existing data sets to support studies of dementia or significant cognitive impairment and comorbid chronic conditions. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, Vol. 11, Issue 6, p622-638. DOI: http://dx.doi.org/10.1016/j.jalz.2014.07.002

http://www.ncbi.nlm.nih.gov/pubmed/25200335