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The National Social Life, Health and Aging Project (NSHAP) is a population-based study of health and social factors on a national scale, aiming to understand the well-being of older, community-dwelling Americans by examining the interactions among physical health, illness, medication use, cognitive function, emotional health, sensory function, health behaviors, and social connectedness. It is designed to provide health providers, policy makers, and individuals with useful information and insights into these factors, particularly on social and intimate relationships.

The study team collected data for Round 4 of this study from 2021 through 2023 and covered the following subjects: bereavement, caregiving, elder mistreatment, employment, functional health, health behaviors, mental and physical health, cognitive function, neighborhood information, sexual interest and activity, social activity, and familial and friend support.

The National Social Life, Health and Aging Project (NSHAP) is a population-based study of health and social factors on a national scale, aiming to understand the well-being of older, community-dwelling Americans by examining the interactions among physical health, illness, medication use, cognitive function, emotional health, sensory function, health behaviors, and social connectedness. It is designed to provide health providers, policy makers, and individuals with useful information and insights into these factors, particularly on social and intimate relationships.

The National Opinion Research Center (NORC), along with Principal Investigators at the University of Chicago, conducted more than 3,000 interviews during 2005 and 2006 with a nationally representative sample of adults aged 57 to 85. Face-to-face interviews and biomeasure collection took place in respondents' homes. Round 3 was conducted from September 2015 through November 2016, where 2,409 surviving Round 2 respondents were re-interviewed, and a New Cohort consisting of adults born between 1948 and 1965 together with their spouses or co-resident partners was added. All together, 4,777 respondents were interviewed in Round 3. The following files constitute Round 3: Core Data, Social Networks Data, Disposition of Returning Respondent Partner Data, and Proxy Data.

Included in the Core files (Datasets 1 and 2) are demographic characteristics, such as gender, age, education, race, and ethnicity. Other topics covered respondents' social networks, social and cultural activity, physical and mental health including cognition, well-being, illness, history of sexual and intimate partnerships and patient-physician communication, in addition to bereavement items. In addition data on a panel of biomeasures including, weight, waist circumference, height, and blood pressure was collected. The Social Networks (Datasets 3 and 4) files detail respondents' current relationship status with each person identified on the network roster. The Disposition of Returning Respondent Partner (Datasets 5 and 6) files detail information derived from Section 6A items regarding the partner from Rounds 1 and 2 within the questionnaire. This provides a complete history for respondent partners across both rounds. The Proxy (Datasets 7 and 8) files contain final health data for Round 1 and Round 2 respondents who could not participate in NSHAP due to disability or death.

The COVID-19 sub-study, administered to NSHAP R3 respondents in the Fall of 2020, was a brief self-report questionnaire that probed how the coronavirus pandemic changed older adults' lives. The COVID-19 sub-study questionnaire was limited to assessing specific domains in which respondents may have been affected by the coronavirus pandemic, including: (1) COVID experiences, (2) health and health care, (3) job and finances, (4) social support, (5) marital status and relationship quality, (6) social activity and engagement, (7) living arrangements, (8) household composition and size, (9) mental health, (10) elder mistreatment, (11) health behaviors, and (12) positive impacts of the coronavirus pandemic. Questions about engagement in racial justice issues since the death of George Floyd in police custody were also added to facilitate analysis of the independent and compounding effects of both the COVID-19 pandemic and reckoning with longstanding racial injustice in America.

The Biomarker Project is one of multiple projects that comprise the MIDUS 3 (M3) "Integrative Pathways to Health and Illness" study. For the past two decades, the overarching objective of MIDUS has been to investigate linkages between sociodemographic, psychosocial, behavioral, and neurobiological variables to account for unfolding profiles of morbidity and mortality across the decades of adult life as well as the maintenance of good health and functional capacities. The study has facilitated analyses that pay attention simultaneously to age, gender, race, and socioeconomic variation in how psychosocial and neurobiological variables are linked. In addition, the M3 data permit longitudinal assessment of the impact of ongoing historical events, such as the 2008 economic recession, on the health of diverse-aged adults, which was also included in the MIDUS Refresher 1 (MR1) assessments. M3 included recruitment of additional twins to facilitate genomic analysis.

The M3 Biomarker Project (P4) includes assessment of multiple indicators of physiological regulation/dysregulation and health according to the basic protocol implemented in the MR1 study, which repeated and expanded the M2 biomarker protocol. The M3 protocol included bone density and body composition assessments at all sites and expansion of Actigraphy, Ankle Brachial Index (ABI) and Gait assessments to all three sites. Data were collected during a 24-hour stay at one of three Clinical Research Units (CRU).

The research team sought to create a methodology and software that allows for identification of deceased individuals based on iris patterns, with computer- and human-driven components. Using a dataset of post-mortem and peri-mortem iris images (acquired in near infrared and visible light) representing 259 cases, the research team engineered a software package, PMExpert, that incorporated three post-mortem specific iris matching algorithms. To understand what features humans believe to be useful in post-mortem iris matching, participants analyzed pairs of post-mortem samples, classified them as those originating from the same or different eyes, and annotated features supporting the decision.

Iris Images:

After the curation of all data collected by the Dutchess County Medical Examiner's Office, NY, iris images from 259 cases were selected for the final dataset release, and for analyses carried out in this project. This data corpus consists of 5,770 NIR and 4,643 RGB images, including images for one peri-mortem case with corresponding post-mortem samples after demise.

Human Examination Data:

The researchers conducted an experiment to collect annotation data on what humans believe to be distinctive features useful for post-mortem iris matching. Initial participants were recruited through the University of Notre Dame to complete study tasks in-person on-site. Due to the COVID-19 pandemic, the study design was later modified to be an online experiment recruiting participants through Amazon Mechanical Turk.

This data acquisition took place in two rounds:

1. The first round was the initial collection of annotation data wherein participants had no prior knowledge of the task or previous decisions.
2. The second round, called the verification step, is where the annotations collected in the first round were presented to future participants for them to either agree with or disagree with along with supporting annotations.

Software Package:

A software tool called PMExpert was created to provide a simple unified interface for all recognition methods, allowing them to be used in an operational setting.

PMExpert consists of two main components: a command line interface (CLI) and a graphical user interface (GUI). Both components are meant to allow examiners to use post-mortem iris recognition methods on images that are collected in their routine operations, offering not only similarity scores and decisions, but also additional information to equip examiners to make their final decision.

The Oregon Youth Substance Use Project (OYSUP) began in 1998, with the recruitment of 1,075 first through fifth graders within a single school district in a working class community in western Oregon. Youth were followed from early childhood (1st through 5th grade), through adolescence, and into emerging adulthood (at age 20-22), with additional data collection at age 20 to 26. The primary objective of OYSUP was to identify risk and protective factors predictive of or comorbid with the development of substance use and at-risk sexual behaviors. OYSUP consisted of a multi-method annual assessment of etiological factors across numerous contextual (e.g., family, peer, neighborhood and school) and individual (personality, biological) domains, predictive of children's cognitions regarding substance use, their own substance use and their at-risk sexual behaviors (beginning in middle school). This unique study follows a representative sample of youth with approximately annual assessments from early childhood, through adolescence, and into emerging adulthood (at age 20-22). The primary objective of the original project and its renewals is to identify risk and protective factors predictive of or comorbid with the development of substance use and at-risk sexual behaviors.

Quantitative survey data was collected from each respondent from 1998 to 2014. Within the aims of the original OYSUP study and the three subsequent renewals, participants and their parents were followed annually until they were one-year post-high school, with an additional intensive assessment at age 20-22. In each year, the target participant and their parents completed assessments. The intensive assessment at age 20-22 included a diagnostic interview with the target participants and an assessment of cortisol reactivity in response to acute stress. During the school years, teachers completed assessments assessing their student's behavior, and school records for most students were obtained each year. In addition, principals in elementary schools completed school climate assessments and census data is used to obtain measures of neighborhood climate. In the third renewal, questionnaires and interviews were given across a two-year span, when participants were aged 20 to 26. The goal of this supplement was to investigate the factors leading to e-cigarette use and and use of other novel tobacco products across two years. Finally, respondents' demographic information was also collected.

This study consists of a two-group, randomized, controlled comparative effectiveness trial with 300 individuals from Appalachian Kentucky who do not have a primary care provider (and thus are not able to receive the standard of care without intercession) and who are at risk for CVD (cardiovascular disease) by virtue of having two or more modifiable CVD risk factors. The researchers compared (1) the standard of care alone, referral to a primary care provider for management of CVD risk factors, with (2) standard of care supplemented by patient-centered, culturally appropriate, self-care CVD risk reduction intervention (HeartHealth) designed to improve multiple CVD risk factors while overcoming barriers to success.

The researchers compared the 4 month (short-term) and 1 year (long-term) impact of the interventions on: 1) CVD risk factors selected by patients (i.e., tobacco use, blood pressure, lipid profile, HgA1c for diabetics, body mass index, waist circumference, depressive symptoms, or physical activity level); 2) all CVD risk factors for each patient; 3) quality of life; 4) patient and healthcare provider satisfaction; 5) desirability and adoptability by assessing adherence to recommended CVD risk reduction protocols, and retention of recruited individuals.

Demographic variables include gender, age, ethnicity, marital status, employment status, and level of education.

Overview

The Florida Department of Health and the Florida Cancer Data System (FCDS) collaborated with a hospital network composed of nine clinical facilities, to capture electronic medical records (EMR) data of patients who were diagnosed with or treated for invasive breast cancer from 2007 to 2010. Certain hospital data elements were available throughout 2006. An additional year of 2011 follow-up data was also available for a subset of patients receiving medication treatment. The purpose of the data capture was to advance patient-centered outcomes research to reduce the morbidity and mortality of cancer and other comorbidities.

A breast cancer pilot study was also conducted from a subset of all transmitted EMR records, consisting of admission records with a principal and/or secondary ICD-9-CM diagnosis between 174.0 and 174.9. The subset dataset was then linked to the central cancer registry using patient social security number, first and last name, and date of birth. Using a deterministic matching algorithm a total of 11,506 unique patients were matched to a patient in the FCDS database, resulting in 12,804 primary tumors and 53,940 unique hospital admission records. While the hospital EMR defined the patient dataset, all registry records for that patient were included in the final breast cancer pilot database, regardless of the reporting hospital or the date of diagnosis. This was to ensure capture of the entire diagnostic and treatment profile for each breast cancer patient.

Data Access

These data are not available from ICPSR. The data contain confidential information that can directly identify a patient. There are also reporting facility data. Therefore, to obtain these data, researchers will need to follow the Florida Cancer Data System data-sharing agreement process, as outlined on the FCDS data sharing request.