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Researchers can use data from electronic health records, or EHRs, in studies that compare two or more treatments. In these studies, researchers need to identify all patients with the same phenotype. Phenotypes are a person's known traits, like height and weight, or known health problems, like diabetes. However, in EHR data, some data on patient traits or health problems may be missing for some patients.

Missing data in EHRs make it hard to correctly identify all patients with the same phenotype. It's even harder when data are missing due to a patient's health status. For example, patients with uncontrolled diabetes may need more lab tests than patients with controlled diabetes. As a result, researchers who are looking at lab tests may not identify patients with controlled diabetes as having diabetes.

In this project, the research team developed and tested a new statistical method that accounts for missing EHR data to estimate patient phenotypes.

To access the methods and software, please visit the bias_correction GitHub repository.

Clinical notes in electronic health records, or EHRs, can help researchers study treatments. For example, EHR notes may contain information about whether patients take their medicines as directed. But it takes researchers a lot of time to find this information.

Natural language processing, or NLP, methods can help researchers find information in EHR notes. With NLP, computer programs read and identify written language to make it easier to sort and study. But current NLP methods don't work well to find and label text about medicine use.

In this study, the research team created and tested a new NLP method to find and label EHR notes on patients' medicine use.

Downloads of Add Health require submission of the following information, which is shared with the original producer of Add Health: supervisor name, supervisor email, and reason for download. A Data Guide for this study is available as a web page and for download.

The National Longitudinal Study of Adolescent to Adult Health (Add Health), 1994-2018 [Public Use] is a longitudinal study of a nationally representative sample of U.S. adolescents in grades 7 through 12 during the 1994-1995 school year. The Add Health cohort was followed into young adulthood with four in-home interviews, the most recent conducted in 2008 when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents' social, economic, psychological, and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships.

Add Health Wave I data collection took place between September 1994 and December 1995, and included both an in-school questionnaire and in-home interview. The in-school questionnaire was administered to more than 90,000 students in grades 7 through 12, and gathered information on social and demographic characteristics of adolescent respondents, education and occupation of parents, household structure, expectations for the future, self-esteem, health status, risk behaviors, friendships, and school-year extracurricular activities. All students listed on a sample school's roster were eligible for selection into the core in-home interview sample. In-home interviews included topics such as health status, health-facility utilization, nutrition, peer networks, decision-making processes, family composition and dynamics, educational aspirations and expectations, employment experience, romantic and sexual partnerships, substance use, and criminal activities. A parent, preferably the resident mother, of each adolescent respondent interviewed in Wave I was also asked to complete an interviewer-assisted questionnaire covering topics such as inheritable health conditions, marriages and marriage-like relationships, neighborhood characteristics, involvement in volunteer, civic, and school activities, health-affecting behaviors, education and employment, household income and economic assistance, parent-adolescent communication and interaction, parent's familiarity with the adolescent's friends and friends' parents.

Add Health data collection recommenced for Wave II from April to August 1996, and included almost 15,000 follow-up in-home interviews with adolescents from Wave I. Interview questions were generally similar to Wave I, but also included questions about sun exposure and more detailed nutrition questions. Respondents were asked to report their height and weight during the course of the interview, and were also weighed and measured by the interviewer.

From August 2001 to April 2002, Wave III data were collected through in-home interviews with 15,170 Wave I respondents (now 18 to 26 years old), as well as interviews with their partners. Respondents were administered survey questions designed to obtain information about family, relationships, sexual experiences, childbearing, and educational histories, labor force involvement, civic participation, religion and spirituality, mental health, health insurance, illness, delinquency and violence, gambling, substance abuse, and involvement with the criminal justice system. High School Transcript Release Forms were also collected at Wave III, and these data comprise the Education Data component of the Add Health study.

Wave IV in-home interviews were conducted in 2008 and 2009 when the original Wave I respondents were 24 to 32 years old. Longitudinal survey data were collected on the social, economic, psychological, and health circumstances of respondents, as well as longitudinal geographic data. Survey questions were expanded on educational transitions, economic status and financial resources and strains, sleep patterns and sleep quality, eating habits and nutrition, illnesses and medications, physical activities, emotional content and quality of current or most recent romantic/cohabiting/marriage relationships, and maltreatment during childhood by caregivers. Dates and circumstances of key life events occurring in young adulthood were also recorded, including a complete marriage and cohabitation history, full pregnancy and fertility histories from both men and women, an educational history of dates of degrees and school attendance, contact with the criminal justice system, military service, and various employment events, including the date of first and current jobs, with respective information on occupation, industry, wages, hours, and benefits. Finally, physical measurements and biospecimens were also collected at Wave IV, and included anthropometric measures of weight, height and waist circumference, cardiovascular measures such as systolic blood pressure, diastolic blood pressure, and pulse, metabolic measures from dried blood spots assayed for lipids, glucose, and glycosylated hemoglobin (HbA1c), measures of inflammation and immune function, including High sensitivity C-reactive protein (hsCRP) and Epstein-Barr virus (EBV).

Wave V data collection took place from 2016 to 2018, when the original Wave I respondents were 33 to 43 years old. For the first time, a mixed mode survey design was used. In addition, several experiments were embedded in early phases of the data collection to test response to various treatments. A similar range of data was collected on social, environmental, economic, behavioral, and health circumstances of respondents, with the addition of retrospective child health and socio-economic status questions. Physical measurements and biospecimens were again collected at Wave V, and included most of the same measures as at Wave IV.

The overall goal of Wave VI was to better understand life course trajectories, determinants, and consequences of critical dimensions of aging, health, and health disparities among U.S. early midlife adults. Data collection took place from 2022 to 2025, with participants between the ages of 39 and 51, with an average age of 44. Beyond longitudinal survey measures, newly added questions included those on cumulative stress, discrimination, despair, work-life balance, memory, physical limitations, and caregiving. Continuing from previous waves, home exams collected physical measurements and biospecimens with most of the same measures as Wave V.

Research that focuses on what's most important to patients can inform health decisions. Researchers use different methods to identify what's most important to patients.

In this study, the research team compared two methods for identifying what's most important to patients: one-on-one interviews and group concept mapping, or GCM. GCM is a three-round process that helps researchers get input from a group. In the first round, people brainstorm topics that are important to them. Next, people sort the topics into clusters based on similar ideas. Finally, researchers create a map to display and discuss the topics. Researchers can use the complete GCM process or the brainstorming round only.

The research team looked at one-on-one interviews versus GCM and compared the number of topics patients named and the amount of time and money required.

Patient-reported outcome measures are surveys that ask patients how they feel and what activities they can do. These surveys ask about things such as how well people sleep and how much their pain interferes with daily life.

In this study, the research team wanted to learn if two clinics could gather patient-reported outcome measures during routine care visits, and if patients with type 2 diabetes could use the results to set goals for improving their health. The research team also wanted to learn if patients and clinic staff saw value in using these measures.

Comparative effectiveness research compares two or more treatments to see which one works best for which patients. But patient traits, such as age or income, may affect patients' treatment choices. These traits may also affect patients' responses to treatments. As a result, researchers may have trouble telling whether a patient's traits, the treatment, or a mix of the two affected how well a treatment worked.

Statistical methods called matching methods can help address this problem when researchers use patient data to compare the effects of treatments. Matching methods help researchers find data from patients who had similar traits such as age or race and received different treatments. Because the patients are similar except for the treatment they receive, the differences in patients' health can more likely be credited to the treatment. Existing methods work well for comparing up to two treatments. But they may not work with three or more treatments.

In this study, the research team created two new matching methods to compare the effects of three or more treatments. The team then analyzed the new methods under different conditions to see how well each worked."

Patients with chronic health problems, such as diabetes, often need to change treatment plans over time to improve their health. To help with this process, doctors can monitor patients' health through follow-up clinic visits and lab tests. Doctors may also suggest changing a treatment plan in response to visits or lab test results. When a treatment plan changes in this way, it's called a dynamic treatment plan. In this study, the research team developed and tested new statistical methods to learn how dynamic treatment plans and choices about follow-up care affect patients' health. These methods use electronic health records, or EHRs. Using EHRs is helpful because they have data on

• What treatments patients have received over time
• How treatments have affected patients' health
• Follow-up information such as lab test results

But the data may differ for patients based on when and why they go to the doctor. These differences make it hard for researchers to accurately know the effect of dynamic treatment plans across many patients.

To access the methods and software, please visit the simcasual R Package.

Researchers often use surveys to learn about what patients prefer. The wording of survey questions may affect how patients answer.

In this study, the research team compared different ways of asking patients with type 2 diabetes questions in a national survey. The questions asked patients about managing their diabetes and the medicines they prefer. The team wanted to see how accurately the different ways of asking questions measured patients' preferences. The study looked at whether patients thought the different ways of asking questions:

• Were easy to understand and answer
• Led to answers that matched what patients really wanted

The National Study of Physician Organizations and the Management of Chronic Illness (NSPO) was designed to improve understanding of evidence-based care management processes (CMPs) as they relate to physician organizations (POs), that is, independent practice associations (IPAs) and medical groups. Since the first NSPO survey of physician organizations in 2000-2001 (NSPO1, archived as ICPSR 4455), considerable investments have been made by a number of different sources, including the Robert Wood Johnson Foundation, the California Healthcare Foundation, and The Commonwealth Fund, to bring about improved care for the chronically ill. This survey, the second NSPO survey of IPAs and medical groups (NSPO2), examined the extent to which the investments in quality improvement were translated into action. NSPO2 assessed the status of CMPs and preventive services use as well as their key drivers in 2006-2007 and the extent to which these factors have changed over time. As in the first NSPO survey, NSPO2 focused on the treatment of four chronic diseases: asthma, congestive heart failure (CHF), depression, and diabetes. Topics covered by the survey include practice type, size, age, ownership, and number of locations; clinical information systems; care management and clinical practice; activities of health insurance plans in chronic illness care; performance incentives; preventative care and health promotion; and organizational culture.

This collection has two data files. The first file contains the NSPO2 survey data, while the second contains a crosswalk between the NSPO1 and NSPO2 case identification numbers which can be used to link the data of the POs that responded to both surveys. Altogether, 369 of the 1,104 POs that responded to NSPO1 also responded to NSPO2.

Funded by the Robert Wood Johnson Foundation, the National Study of Small and Medium-sized Physician Practices (NSSMPP) was designed to provide information about physician practices with 1-19 physicians. The survey focused on the use of information technology and care management processes for four major chronic illnesses: asthma, congestive heart failure, depression, and diabetes. Other topics covered by the survey include practice type, size, ownership and the breakdown of patients by race and Hispanic origin; clinical preventative services and health promotion; health insurance plan activities in preventative care and care for patients with chronic illness; performance reporting and incentives; revenue sources and compensation methods; and organizational culture.

NSSMPP was also designed to assist the RWJF-funded Aligning Forces for Quality (AF4Q) project by providing baseline data about small and medium sized practices in the AF4Q sites. AF4Q was a national program that aimed to lift the quality of health care in 16 targeted communities, reduce racial and ethnic disparities in those communities and provide models for national reform.

NSSMPP built on two previous studies -- the National Study of Physician Organizations and the Management of Chronic Illness (NSPO), 2000-2001 (ICPSR 4455) and the National Study of Physician Organizations and the Management of Chronic Illness II (NSPO2), 2006-2007 (ICPSR 29801) -- which collected information about medical groups and independent practice associations (IPAs) with 20 or more physicians.

This study is a qualitative examination via in-depth interviews and focus groups of barriers and facilitators to receiving postpartum diabetes screenings. The target population is women aged 18-40 who had a history of gestational diabetes within the prior 10 years and received Medicaid during pregnancy. Perspectives from patients, health care providers, and health care staff were solicited for the study. Overall, the goal was to learn about the patient, provider, and staff experience after a pregnancy complicated by gestational diabetes in order to understand how health centers may better support patients receiving recommended follow-up screenings and preventing postpartum type 2 diabetes.

All healthcare providers and staff were recruited from federally qualified health centers (FQHCs) in Missouri and provided care for women during and after pregnancies with gestational diabetes. Patients were recruited via health care centers or other community sites in the St. Louis metropolitan area. Interview and focus group questions assessed understanding and education provided around gestational diabetes diagnosis and postpartum screening/prevention, as well as prominent barriers and facilitators to gestational diabetes management, postpartum diabetes screening, and diabetes prevention.

The Sacramento Area Latino Study on Aging (SALSA Study) project tracked the incidence of physical and cognitive impairment as well as dementia and cardiovascular diseases in elderly Latinos in the Sacramento, California, region. The SALSA project aimed to assess cognitive, physical, and social functions, which include the ability to follow instructions, to perform certain movements, and to interact with others. The study explored the effects that cultural, nutritional, social, and cardiovascular risk factors have on overall health and dementia, and examined the association between diabetes and functional status. This study contains the neuroclinical exam data from the SALSA project. Demographic information includes age given at follow-up visits, country of birth, language, religion, marital status, educational level, occupation, household income, and size of household.

The National Health and Nutrition Examination Surveys (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. The NHANES combines personal interviews and physical examinations, which focus on different population groups or health topics. These surveys have been conducted by the National Center for Health Statistics (NCHS) on a periodic basis from 1971 to 1994. In 1999 the NHANES became a continuous program with a changing focus on a variety of health and nutrition measurements which were designed to meet current and emerging concerns. The surveys examine a nationally representative sample of approximately 5,000 persons each year. These persons are located in counties across the United States, 15 of which are visited each year.

For NHANES 2003-2004, there were 12,761 persons selected for the sample, 10,122 of those were interviewed (79.3 percent) and 9,643 (75.6 percent) were examined in the mobile examination centers (MEC). Many of the NHANES 2003-2004 questions were also asked in NHANES II 1976-1980, Hispanic HANES 1982-1984, NHANES III 1988-1994, and NHANES 1999-2002. New questions were added to the survey based on recommendations from survey collaborators, NCHS staff, and other interagency work groups. As in past health examination surveys, data were collected on the prevalence of chronic conditions in the population. Estimates for previously undiagnosed conditions, as well as those known to and reported by survey respondents, are produced through the survey. Risk factors, those aspects of a person's lifestyle, constitution, heredity, or environment that may increase the chances of developing a certain disease or condition, were examined. Data on smoking, alcohol consumption, sexual practices, drug use, physical fitness and activity, weight, and dietary intake were collected. Information on certain aspects of reproductive health, such as use of oral contraceptives and breastfeeding practices, were also collected. The diseases, medical conditions, and health indicators that were studied include: anemia, cardiovascular disease, diabetes and lower extremity disease, environmental exposures, equilibrium, hearing loss, infectious diseases and immunization, kidney disease, mental health and cognitive functioning, nutrition, obesity, oral health, osteoporosis, physical fitness and physical functioning, reproductive history and sexual behavior, respiratory disease (asthma, chronic bronchitis, emphysema), sexually transmitted diseases, skin diseases, and vision. The sample for the survey was selected to represent the United States population of all ages. Special emphasis in the 2003-2004 NHANES was on adolescent health and the health of older Americans. To produce reliable statistics for these groups, adolescents aged 15-19 years and persons aged 60 years and older were over-sampled for the survey. African Americans and Mexican Americans were also over-sampled to enable accurate estimates for these groups. Several important areas in adolescent health, including nutrition and fitness and other aspects of growth and development, were addressed. Since the United States has experienced dramatic growth in the number of older people during the twentieth century, the aging population has major implications for health care needs, public policy, and research priorities. NCHS is working with public health agencies to increase the knowledge of the health status of older Americans. NHANES has a primary role in this endeavor. In the examination, all participants visit the physician who takes their pulse or blood pressure. Dietary interviews and body measurements are included for everyone. All but the very young have a blood sample taken and see the dentist. Depending upon the age of the participant, the rest of the examination includes tests and procedures to assess the various aspects of health listed above. Usually, the older the individual, the more extensive the examination. Some persons who are unable or unwilling to come to the examination center may be given a less extensive examination in their homes.

Demographic data file variables are grouped into three broad categories: (1) Status Variables: provide core information on the survey participant. Examples of the core variables include interview status, examination status, and sequence number. (Sequence number is a unique ID assigned to each sample person and is required to match the information on this demographic file to the rest of the NHANES 2003-2004 data). (2) Recoded Demographic Variables: these variables include age (age in months for persons through age 19 years, 11 months; age in years for 1- to 84-year-olds, and a top-coded age group of 85 years of age and older), gender, a race/ethnicity variable, current or highest grade of education completed, (less than high school, high school, and more than high school education), country of birth (United States, Mexico, or other foreign born), Poverty Income Ratio (PIR), income, and a pregnancy status variable (adjudicated from various pregnancy related variables). Some of the groupings were made due to limited sample sizes for the two-year data set. (3) Interview and Examination Sample Weight Variables: sample weights are available for analyzing NHANES 2003-2004 data. For a complete listing of survey contents for all years of the NHANES see the document -- Survey Content -- NHANES 1999-2010.

This collection has not been processed by NACDA or ICPSR, and data are released in the format provided by the principal investigators. Please report any data errors or problems to user support, and we will work with you to resolve any data-related issues.

Hawaii Aging with HIV Cardiovascular Study (HAHCS) enrolled HIV-infected volunteer adults age 40 and over, recruited from the state of Hawaii. A natural history longitudinal study, HAHCS followed a cohort of 150 HIV positive subjects for five years. The study is based on observations that, while HIV-infected individuals now live longer because of the availability of highly active antiretroviral therapy, these individuals may be at increased risk of cardiovascular (CV) morbidity and mortality. Rates of well-accepted traditional CV risk factors such as diabetes/hyperglycemia, body morphology changes and smoking are high in the HIV population. Furthermore, there is growing concern that HIV per se may also contribute to CV risk.

HAHCS evaluated the cross-sectional and longitudinal impact of oxidative stress and inflammation on the development of subclinical atherosclerosis. Researchers assessed subclinical atherosclerosis functionally by brachial artery flow mediated vasodilatation (FMD) and structurally by intima-media thickness (IMT) as well as coronary artery calcium score obtained by dual source CT. Data include behavioral health indicators, medical history information, and medical test results. Demographic data include age, sex, and race.

The Research on Early Life and Aging Trends and Effects (RELATE) study compiles cross-national data that contain information that can be used to examine the effects of early life conditions on older adult health conditions, including heart disease, diabetes, obesity, functionality, mortality, and self-reported health. The complete cross sectional/longitudinal dataset (n=147,278) was compiled from major studies of older adults or households across the world that in most instances are representative of the older adult population either nationally, in major urban centers, or in provinces. It includes over 180 variables with information on demographic and geographic variables along with information about early life conditions and life course events for older adults in low, middle and high income countries. Selected variables were harmonized to facilitate cross national comparisons.

In this first public release of the RELATE data, a subset of the data (n=88,273) is being released. The subset includes harmonized data of older adults from the following regions of the world: Africa (Ghana and South Africa), Asia (China, India), Latin America (Costa Rica, major cities in Latin America), and the United States (Puerto Rico, Wisconsin). This first release of the data collection is composed of 19 downloadable parts: Part 1 includes the harmonized cross-national RELATE dataset, which harmonizes data from parts 2 through 19. Specifically, parts 2 through 19 include data from Costa Rica (Part 2), Puerto Rico (Part 3), the United States (Wisconsin) (Part 4), Argentina (Part 5), Barbados (Part 6), Brazil (Part 7), Chile (Part 8), Cuba (Part 9), Mexico (Parts 10 and 15), Uruguay (Part 11), China (Parts 12, 18, and 19), Ghana (Part 13), India (Part 14), Russia (Part 16), and South Africa (Part 17).

The Health and Retirement Study (HRS) was also used in the compilation of the larger RELATE data set (HRS) (N=12,527), and these data are now available for public release on the HRS data products page. To access the HRS data that are part of the RELATE data set, please see the collection notes below.

CCPC's long term vision is to use pragmatic comparative effectiveness methods, linked to an extensive primary care practice data repository, to establish evidence about best practices for complex real world patients and deliver appropriate, real-time decision support at point of service for primary care practitioners (PCPs) in a way that will account for individualized management of conditions and choice of treatments in order to provide optimal care.

The primary aim of BICEP was to advance analytical methods of observational Comparative Effectiveness Research (CER) to support evidentiary needs of primary care practitioners in answering important questions related to care of patient populations with Multiple Complex Conditions (MCCs).

The secondary aim of BICEP was to conduct a pilot study to demonstrate the feasibility and value of using the analytic methods for conducting CER among complex patients.

BICEP sought to answer the following clinical research questions: In adults with Type 2 Diabetes Mellitus (T2DM) coupled with additional chronic diseases,

1. What is the comparative effectiveness of T2DM medications in achieving glycemic control?
2. What is the comparative effectiveness of T2DM medications on intermediate outcomes, adverse events, side effects, tolerability?
3. Does the effectiveness and safety of the diabetic treatment options differ across subgroups of patients based on patient demographic characteristics, complex co-morbidities, or the use of other concurrent therapies?

Overview: The goal of the project was to develop a unique database linking chronic disease clinical data from an electronic medical record (EMR) of a large academic healthcare system to multi-payer claims data. The longitudinal relational database can be used to study clinical effectiveness of many diagnostic and treatment interventions. The population of patients used consisted of those patients who were attributed to the University of Michigan Health System (UMHS) as continuing care patients, who are also in adjudicated and validated chronic disease registries.

Data Access: These data are not available from ICPSR. The data are restricted to use by the principal investigator and cannot be shared.

Purpose. The CoNNECT Project enables comparative effectiveness research on mental health, behavioral health, and substance use in primary care. CoNNECT tracked two main elements: (1) the number of patients identified with a comorbid mental health and physical health diagnosis; (2) the number of patients who initiate treatment secondary to a mental health diagnosis. CoNNECT created the capacity to build a base for mental health in primary care comparative effectiveness research using electronic connectivity to generate retrospective and in time prospective clinical data.

Data Access. CoNNECT data are not available from ICPSR. The data from this study are hosted at DARTNet.

Background. Medically underserved groups are more likely to have poorly-controlled chronic illness and to experience barriers in accessing health care. Traditional chronic disease management through the 20-minute clinic visit presents significant challenges for these patients. Health information technology (HIT) can be used to help patients manage chronic conditions outside the clinic setting. Text messaging has been associated with improved glycemic control when used to assist with diabetes case management, and high rates of cell phone access are reported among groups with low rates of computer and internet use (e.g. 71 percent among African Americans and 59 percent among Hispanics/Latinos).

Population. The study was conducted among adult diabetic patients in possession of cell phones who receive regular treatment at federally qualified community health centers in Denver, CO, which serves an urban population that is predominantly either uninsured (41 percent) or on Medicaid or Medicare (56 percent). A total of 133 patients were enrolled in the feasibility study, of which 65.5 percent were Latino, 8.5 percent were Black, and 25 percent were White. The majority of patients were over age 50 (70 percent), with more women (65 percent) than men (35 percent).

mHealth Infrastructure. A software platform, the Patient Relationship Manager (PRM), was created in partnership with EMC Consulting and Microsoft Corporation (MS Customer Relationship Management software- name, version number) to send and receive text messages reminding patients of upcoming appointments and requesting patient self-reported blood sugar measurements according to an automated schedule. Platform functionality was expanded with grant funding from the Agency for Healthcare Research and Quality (AHRQ), adding support for self-reported blood pressure and step count data and automated links to clinical laboratory and pharmacy data sources to support outreach to patients overdue for laboratory tests and medication refills. The PRM system transmitted regularly-scheduled outbound text messages and processed patient-provided text message responses. Response data were transformed by PRM into standard formats, integrated into the electronic medical record, and made available to providers at the point of care. Structured, de-identified research data were incorporated into a REDCap dataset to provide access via a platform used by 380 institutions to facilitate comparative effectiveness research. Misformatted responses and home measurements outside established ranges were automatically flagged by PRM and added to a work queue for review and follow-up action by clinical personnel. A registered nurse reviewed all flagged messages, coordinated with primary care providers, and contacted patients by telephone for follow-up according to clinical guidelines.

Design and Methods. In an initial pilot study, patients (N=47) received text message prompts over a three month period. Blood sugar readings were requested 3 times per week (MWF), and appointment reminders were sent 7, 3, and 1 day(s) prior to each scheduled appointment.

A subsequent 6-month feasibility study (N=133) offered support for patients to report up to 3 different types of home measurements (blood sugars, blood pressures, and step counts) up to 5 days per week, according to patient preferences, and automated outreach to patients late for medication refills and overdue for laboratory tests. Review of text message data gauged the accuracy of home measurement prompts and automated outreach based on laboratory and pharmacy clinical datasets.

Three focus groups were conducted among feasibility study participants in English and Spanish, with group composition purposively structured based on patients' primary language and frequency of text message response.

Data Access. These data are not available from ICPSR. The data from this study are hosted at REDCap and require the signature on a data use agreement with Denver Health. To access these data, users must complete and submit the attached data use agreement to Dr. Henry Fischer ([email protected]) or Susan Moore ([email protected]).

Documentation files, however, including the data dictionary and the Stanford Self-Efficacy Scale, can be found on the ICPSR site.

This study contains demographic variables for the the Sacramento Area Latino Study on Aging (SALSA) Series and can be used with ICPSR studies 22760, 29321, 29322, 29323. Demographic variables include gender, primary language, country of origin, state of birth, cause of death, 2000 census tract codes, birth date, date of death, and age given at follow-up visits.

About SALSA: The Sacramento Area Latino Study on Aging (SALSA Study) project tracked the incidence of physical and cognitive impairment as well as dementia and cardiovascular diseases in elderly Latinos in the Sacramento, California, region. The SALSA project aimed to assess cognitive, physical, and social functions, which include the ability to follow instructions, to perform certain movements, and to interact with others. The study explored the effects that cultural, nutritional, social, and cardiovascular risk factors have on overall health and dementia, and examined the association between diabetes and functional status.

The Sacramento Area Latino Study on Aging (SALSA Study) project tracked the incidence of physical and cognitive impairment as well as dementia and cardiovascular diseases in elderly Latinos in the Sacramento, California, region. The SALSA project aimed to assess cognitive, physical and social functions, which include the ability to follow instructions, to perform certain movements, and to interact with others. The study explored the effects that cultural, nutritional, social and cardiovascular risk factors have on overall health and dementia, and examined the association between diabetes and functional status. Demographic information includes age given at follow-up visits, country of birth, language, religion, marital status, educational level, occupation, household income, and size of household.