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 George Worthington with DARS at (804) 662-9154 or george.worthington@dars.virginia.gov.

Prevalence Data and Estimates

Page updated June 2019

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

Alzheimer’s Disease Facts and Figures, Alzheimer’s Association

2018 Alzheimer’s Association Statistics: US

2016 Alzheimer’s Association Statistics: Virginia

Cognitive Decline: Data from the Behavioral Risk Factor Surveillance System (BRFSS)

Dementia caregiving in VA 2015

2015 Alzheimer’s Association Data by State

Cognitive decline in VA 2012

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

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: https://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: https://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: https://www.resdac.org/. Costs for the data vary.

For more information on the CMS VRDC, visit: https://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 (https://www.ncbi.nlm.nih.gov/gap?db=gap), and can also find specific information on the data (https://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: https://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: https://www.alz.washington.edu/

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

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: https://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: https://dx.doi.org/10.1016/j.jalz.2014.07.002

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