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This study evaluated the impact of atypical work hours on physiological indicators of health and chronic disease among law enforcement officers enrolled in the Buffalo Cardio-Metabolic Occupational Police Stress (BCOPS) study. Atypical work hours were defined as: work outside of a standard daytime work shift, the number of shift changes that occur over an extended period, the effect of cumulative overtime hours, and/or secondary employment. The data in this release include measures of global DNA methylation, which is an indicator of genomic instability and risk factor for several types of cancer; food logs documenting wake, sleep, and meal times during workdays and off-duty days; and survey data about psychosocial adaptive and maladaptive behaviors associated with atypical work hours.

The Chicago Community Adult Health Study (CCAHS) consists of four interrelated components that were conducted simultaneously: (1) a survey of adult health on a probability sample of 3,105 Chicago adults, including direct physical measurements of their blood pressure and heart rate and of height, weight, waist and hip circumference, and leg length; (2) a biomedical supplement which collected blood and/or saliva samples on a subset of 661 survey respondents; (3) a community survey in which individuals described aspects of the social environment of all survey respondents' neighborhoods; and (4) a systematic social observation (SSO) of the blocks in which potential survey respondents resided, including a lost letter drop (Milgram et al. 1965) as an unobtrusive measure of neighborhood social capital/sense of responsibility to help others. The latter two extend a community survey and SSO of neighborhoods carried out by the Project on Human Development in Chicago Neighborhoods (PHDCN) in 1995. The adult health survey and the community survey were conducted jointly through face-to-face interviews with a stratified, multistage probability sample of 3,105 individuals aged 18 and over and living in the city of Chicago, with a response rate of 72 percent that is about the highest currently attainable in large urban areas. In addition, blood pressure, heart rate, and physical measurements (of height, weight, waist and hips, and leg length) were collected during the survey interview, and blood and saliva samples from 661 respondents or 60 percent of those doing the survey in the 80 "focal" neighborhood clusters (NCs). SSOs were conducted on 1,663 of the 1,672 city blocks on which each respondent lived. The CCAHS is the largest of five projects under the NIH-funded Michigan Interdisciplinary Center on Social Inequalities, Mind and Body Mind (#P50HD38986), one of five Mind-Body Centers funded by the National Institutes of Health in late 1999. This study will advance the understanding of socioeconomic and racial/ethnic disparities in health, a major priority of the Public Health Service and the National Institutes of Health.

The PI-supplied summary mentions that the study is comprised of four components. However, for the purposes of this data release there are three distinct datasets. Demographic variables include age, birth year, race, ethnicity, number of children in the household, number of children living elsewhere, number of times the respondent has been married, and relationship status, religious preference, and sex.

The Common Cold Project began in 2011 with the aim of creating, documenting, and archiving a database that combines final research data from 5 prospective viral-challenge studies that were conducted over the preceding 25 years. The data collection includes the British Cold Study (BCS), which focused on psychological stress; the Pittsburgh Cold Study 1 (PCS1), which built on the BCS; the Pittsburgh Cold Study 2 (PCS2), which examined childhood socioeconomic status and personality; the Pittsburgh Mind-Body Center Cold Study (PMBC), which recorded detailed mood and behavior data over 14 days; the Pittsburgh Cold Study 3, which focused on childhood environment; the Pittsburg Cold Study 3 Social Rhythm Data (PCS3-SRM), which recorded daily interview data of mood, health behavior, and social interaction; and finally the 5 Study Aggregate, which was designed to facilitate analysis across studies. These studies assessed predictor (and hypothesized mediating) variables in healthy adults aged 18 to 55 years, experimentally exposed them to a virus that causes the common cold, and then monitored them for development of infection and signs and symptoms of illness. Standard control variables (covariates) included age, sex, socioeconomic status (SES), race/ethnicity, body mass index (BMI), season of the year, and specific antibody (Ab) titer to the challenge virus (specific immunity). Three of the studies also include daily evening interviews (conducted for 6 or 14 days before exposure to a virus and assessing daily social interactions, mood, health behaviors, and physical symptoms; and daily diaries collected during the quarantine period (1 day before and 5-6 days after viral exposure), including cold-specific and nonspecific symptoms, mood, and health behaviors. These data accompany datasets four, five, and seven.

Many common variables were collected across 2 or more studies, and all 5 studies include measures of upper respiratory infectious illness (URI) (e.g., infection, signs and symptoms of a cold, local [nasal mucosa] release of pro- and anti-inflammatory cytokines). Data were also collected on a broad assortment of health-related outcomes not specific to URI including anthropomorphic measures (such as body mass index and waist circumference), complete blood cell counts and differentials, measures of functional immunity, self-reported and objectively assessed health behaviors (smoking, alcohol consumption, physical activity, diet, and sleep), measures of functional physiology across several biological systems (such as pulmonary function, resting cardiovascular function, endocrine, and metabolic activity), and self-reported assessments of physical and psychological health and well-being. In addition, the 5 studies collected data on an extensive range of demographic, health behavior, psychological and social variables including adult SES and subjective social standing, childhood SES, major stressful life events and perceived stress, personality, psychological expectations and beliefs, social relationships, and state and trait affect.

The Costa Rican Longevity and Healthy Aging Study (CRELES, or Costa Rica Estudio de Longevidad y Envejecimiento Saludable) is a nationally representative longitudinal survey of health and lifecourse experiences of 2,827 Costa Ricans ages 60 and over in 2005, the baseline collection. CRELES-2 refers to the second wave of visits in this longitudinal study, and includes the results from these visits. The first wave of interviews, or baseline, of CRELES is also available at http://doi.org/10.3886/ICPSR26681. The second wave fieldwork was conducted from October 2006 to July 2008, with 2,364 surviving and contacted participants. The original sample was drawn from Costa Rican residents in the 2000 population census who were born in 1945 or before, with an over-sample of the oldest-old (ages 95 and over). Vital statistics indicate that Costa Rica has an unusually high life expectancy for a middle-income country, even higher than that of the United States, but CRELES is the first nationally representative survey to investigate adult health levels in Costa Rica. CRELES public use data files contain information on a broad range of topics including self-reported physical health, psychological health, living conditions, health behaviors, health care utilization, social support, and socioeconomic status. Objective health indicators include anthropometrics, observed mobility, and biomarkers from fasting blood samples (such as cholesterol, glycosylated hemoglobin, and C-reactive protein). Mortality events are tracked and conditions surrounding death are measured in a surviving family interview.

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.

The overall goal of this project was to understand the degradation characteristics of mRNA molecules in dried body fluid stains such that the relationship between degradation and the passage of time could be explored and used to develop a forensic tool to estimate the age of the stain (i.e., determine the time since deposition, TsD). Research has demonstrated that RNA degradation correlates with the passage of time in dried stains and have defined degradation kinetics for multiple mRNA transcripts present in dried blood, semen, and saliva stains. The current study collected detailed degradation kinetics for multiple transcripts in stains stored in real world environments with varying conditions of temperature, relative humidity, and sunlight exposure. Results suggest it may be possible to model degradation kinetics mathematically and develop an algorithm useful for estimating TsD in biological evidence recovered from crime scenes.

The Future of Families and Child Wellbeing Study (FFCWS, formerly known as the Fragile Families and Child Wellbeing Study) follows a cohort of nearly 5,000 children born in large, U.S. cities between 1998 and 2000. The study oversampled births to unmarried couples; and, when weighted, the data are representative of births in large U.S. cities at the turn of the century. The FFCWS was originally designed to address four questions of great interest to researchers and policy makers:

1. What are the conditions and capabilities of unmarried parents, especially fathers?
2. What is the nature of the relationships between unmarried parents?
3. How do children born into these families fare?
4. How do policies and environmental conditions affect families and children?

The FFCWS consists of interviews with mothers, fathers, and/or primary caregivers at birth and again when children are ages 1, 3, 5, 9, 15, and 22. The parent interviews collected information on attitudes, relationships, parenting behavior, demographic characteristics, health (mental and physical), economic and employment status, neighborhood characteristics, and program participation. Beginning at age 9, children were interviewed directly (either during the home visit or on the telephone). The direct child interviews collected data on family relationships, home routines, schools, peers, and physical and mental health, as well as health behaviors.

A collaborative study of the FFCWS, the In-Home Longitudinal Study of Pre-School Aged Children (In-Home Study) collected data from a subset of the FFCWS Core respondents at the Year 3 and 5 follow-ups to ask how parental resources in the form of parental presence or absence, time, and money influence children under the age of 5. The In-Home Study collected information on a variety of domains of the child's environment, including: the physical environment (quality of housing, nutrition and food security, health care, adequacy of clothing and supervision) and parenting (parental discipline, parental attachment, and cognitive stimulation). In addition, the In-Home Study also collected information on several important child outcomes, including anthropometrics, child behaviors, and cognitive ability. This information was collected through interviews with the child's primary caregiver, and direct observation of the child's home environment and the child's interactions with his or her caregiver.

Similar activities were conducted during the Year 9 follow-up. At the Year 15 follow-up, a condensed set of home visit activities were conducted with a subsample of approximately 1,000 teens. Teens who participated in the In-Home Study were also invited to participate in a Sleep Study and were asked to wear an accelerometer on their non-dominant wrist for seven consecutive days to track their sleep (Sleep Actigraphy Data) and that day's behaviors and mood (Daily Sleep Actigraphy and Diary Survey Data).

An additional collaborative study collected data from the child care provider (Year 3) and teacher (Years 9 and 15) through mail-based surveys. Saliva samples were collected at Year 9 and 15 (Biomarker file and Polygenic Scores). The Study of Adolescent Neural Development (SAND) COVID Study began data collection in May 2020 following the onset of the COVID-19 pandemic. It included online surveys with the young adult and their primary caregiver.

The FFCWS began its seventh wave of data collection in October 2020, around the focal child's 22nd birthday. Data collection and interviews continued through January 2024. The Year 22 wave included a young adult (YA) survey with the original focal child and a primary caregiver (PCG) survey. Data were also collected on the children of the original focal child (referred to as Generation 3, or G3).

In 2017, the FFCWS team announced the Fragile Families (FF) Challenge, a collaborative effort in which participants were tasked with using machine learning methods and FFCWS data (Baseline to Year 9) to build a model that would predict six key outcomes at Year 15. Materials used in the FF Challenge have been archived in this collection.

Documentation for these files is available on the FFCWS website under Data and Documentation. For details of updates made to the FFCWS data files, please see the project's Data Alerts page.

Data collection for the Future of Families and Child Wellbeing Study was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) of the National Institutes of Health under award numbers R01HD36916, R01HD39135, and R01HD40421, as well as a consortium of private foundations.

Below is the citation for use of the FFCWS data accessed through ICPSR. For information on additional citation requirements when using FFCWS in publications, please refer to this FAQ on the FFCWS project site.

The Los Angeles Family and Neighborhood Survey (L.A.FANS) is a two-wave study of adults and children in Los Angeles County and of the neighborhoods in which they live. The first wave (L.A.FANS-1), which was fielded between April 2000 and January 2002, interviewed adults and children living in 3,085 households in a stratified probability sample of 65 neighborhoods throughout Los Angeles County. The samples of neighborhoods and individuals were representative of neighborhoods and residents of Los Angeles County. Poorer neighborhoods and households with children were oversampled. In Wave 2 of L.A.FANS (L.A.FANS-2), Wave 1 respondents living in Los Angeles County were reinterviewed and updated information was collected on Wave 1 respondents who had moved away from Los Angeles County. A sample of individuals who moved into each sampled neighborhood between Waves 1 and 2 was also interviewed, for a total of 2,319 adults and 1,382 children (ages less than 18 years).

A new feature in L.A.FANS-2 was the collection of physiological health measures. Interviewers collected blood pressure, pulse, height, weight, hip and waist circumference, and a pulmonary function assessment (spirometry) from respondents. Saliva samples were collected from child respondents. 50% of L.A.FANS households were selected at random and respondents were asked to provide dried blood spot (DBS) samples. The initial release of L.A.FANS-2 data included only the blood pressure and anthropometry data. This collection contains the spirometry, saliva, and DBS data. The saliva and DBS datasets each have one record per respondent who completed the health module, while the spirometry dataset has one record for each trial.

Data in this study are designed for use with the public use data files for L.A.FANS, Wave 1 (study 1) and Wave 2 (study 2). Additional information on the project is available on the L.A.FANS series page and the RAND website.

Additional information on the project, survey design, sample, and variables are available from:

• Sastry, Narayan, Bonnie Ghosh-Dastidar, John Adams, and Anne R. Pebley (2006). The Design of a Multilevel Survey of Children, Families, and Communities: The Los Angeles Family and Neighborhood Survey, Social Science Research, Volume 35, Number 4, Pages 1000-1024
• The Users' Guides (Wave 1 and Wave 2)
• RAND Documentation Reports page

The Biomarker study is Project 4 of the Midlife in the United States (MIDUS) longitudinal study, a national survey of more than 7,000 Americans (aged 25 to 74) begun in 1994. The purpose of the larger study was to investigate the role of behavioral, psychological, and social factors in understanding age-related differences in physical and mental health. With support from the National Institute on Aging (NIA), a longitudinal follow-up of the original MIDUS samples [core sample (N = 3,487), metropolitan over-samples (N = 757), twins (N = 957 pairs), and siblings (N = 950)] was conducted in 2004-2006. Guiding hypotheses, at the most general level, were that behavioral and psychosocial factors are consequential for health (physical and mental). A description of the study and findings from it are available on the MIDUS website.

The Biomarker Project (Project 4) of MIDUS 2 contains data from 1,255 respondents. These respondents include two distinct subsamples, all of whom completed the Project 1 Survey: (1) longitudinal survey sample (n = 1,054) and (2) Milwaukee sample (n = 201). The Milwaukee group contained individuals who participated in the baseline MIDUS Milwaukee study, initiated in 2005. The purpose of the Biomarker Project (Project 4) was to add comprehensive biological assessments on a subsample of MIDUS respondents, thus facilitating analyses that integrate behavioral and psychosocial factors with biology. The broad aim is to identify biopsychosocial pathways that contribute to diverse health outcomes. A further theme is to investigate protective roles that behavioral and psychosocial factors have in delaying morbidity and mortality, or in fostering resilience and recovery from health challenges once they occur. The research was not disease-specific, given that psychosocial factors have relevance across multiple health endpoints.

Biomarker data collection was carried out at three General Clinical Research Centers (at UCLA, University of Wisconsin, and Georgetown University). The biomarkers reflect functioning of the hypothalamic-pituitary-adrenal axis, the autonomic nervous system, the immune system, cardiovascular system, musculoskeletal system, antioxidants, and metabolic processes. Our specimens (fasting blood draw, 12-hour urine, saliva) allow for assessment of multiple indicators within these major systems. The protocol also included assessments by clinicians or trained staff, including vital signs, morphology, functional capacities, bone densitometry, medication usage, and a physical exam. Project staff obtained indicators of heart-rate variability, beat to beat blood pressure, respiration, and salivary cortisol assessments during an experimental protocol that included both a cognitive and orthostatic challenge. Finally, to augment the self-reported data collected in Project 1, participants completed a medical history, self-administered questionnaire, and self-reported sleep assessments. For respondents at one site (UW-Madison), objective sleep assessments were also obtained with an Actiwatch(R) activity monitor.

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 MIDUS Refresher study Survey (2011-2014 ICPSR 36532) recruited a national probability sample of 3,577 adults, aged 25 to 74, designed to replenish the original MIDUS 1 baseline cohort and paralleling the five decadal age groups of the MIDUS 1 baseline survey (ICPSR 2760). The MIDUS Refresher survey employed the same comprehensive assessments as those assembled on the core longitudinal MIDUS sample, but with additional questions about impacts of the economic recession of 2008-09. The MIDUS Refresher Biomarker study (2012-2016) obtained data from 863 respondents (n=746 Main sample, n=117 African Americans from Milwaukee) who completed the MIDUS Refresher Survey.

The purpose of the Refresher Biomarker Project (Project 4) parallels that of the MIDUS 2 Biomarker project (ICPSR 29282), which collected comprehensive biological assessments on a subsample of MIDUS respondents, thus facilitating analyses that integrate behavioral and psychosocial factors with biological regulation/dysregulation, broadly defined. The aim was to use such data to explicate biopsychosocial pathways that contributed to diverse health outcomes. A further theme was to examine period effects on health (mental and physical) related to the economic recession by comparing the pre-recession MIDUS sample with the post-recession MIDUS Refresher sample. A further objective of the MIDUS Refresher sample was to strengthen cross-project analyses by increasing the sample sizes available for testing hypotheses regarding the interplay of key factors (e.g., socioeconomic status, gender, psychosocial factors, biological factors) in mid- and later-life health.

Biomarker data collection was carried out at hypothalamic-pituitary-adrenal axis, the autonomic nervous system, the immune system, cardiovascular system, musculoskeletal system, antioxidants, and three General Clinical Research Centers (at UCLA, University of Wisconsin, and Georgetown University). The biomarkers reflect functioning of the metabolic processes. Our specimens (fasting blood draw, 12-hour urine, saliva) allowed for assessment of multiple indicators within these major systems. The protocol also included assessments by clinicians or trained staff, including vital signs, morphology, functional capacities including 3 dimensional gait analysis, bone densitometry, body composition, ankle brachial index, medication usage, and a physical exam. Project staff obtained indicators of heart-rate variability, beat to beat blood pressure, respiration, and salivary cortisol assessments during an experimental protocol that included both a cognitive and orthostatic challenge. Finally, to augment the self-reported data collected in Survey (Project 1), participants completed a medical history, self-administered questionnaire, and self-reported sleep assessments. For respondents at one site (UW-Madison), objective sleep assessments were also obtained with an Actiwatch(R) activity monitor.

The National Institute on Drug Abuse (NIDA) funded RADAR in 2014 to collect multilevel, longitudinal data and biospecimens from an ethnically and racially diverse cohort of young, sexual and gender minorities (SGM; e.g., men who have sex with men (MSM), transgender women, gender non-conforming individuals) who were assigned male at birth (AMAB) (current core cohort n=1,113). The primary objective of this study is to apply a multilevel perspective to a syndemic of health issues associated with human immunodeficiency virus (HIV) in this population. The multilevel design focuses on individual, dyadic (i.e., sexual and romantic relationships), network (i.e., social, drug, and sexual connections) and biologic factors that may be associated with HIV. The cohort contains both HIV-negative and HIV-positive individuals, which allows for the development of a repository of biospecimens and HIV sequence data from both pre-infection and post-infection visits that will help facilitate future projects evaluating substance use, HIV risk, and pathogenesis.

A multiple cohort, accelerated longitudinal design was utilized by initially enrolling two existing SGM cohorts and then expanded through the use of convenience and snowball sampling methods. Enrollment criteria varied slightly based on the recruitment method, but overall inclusion criteria required participants to be AMAB, between 16 and 29 years of age, report having had sex with a man in the prior year or identify as a SGM, live in the Chicago metropolitan area, and be an English speaker. Study recruitment opened in February 2015. Participants are followed through the developmental period of late adolescence to early adulthood, which is a critical period of initiation and acceleration of sexual behavior and substance use. Study visits occur every six months.

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.

The Population Assessment of Tobacco and Health (PATH) Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). The study was launched in 2011 to inform the FDA's tobacco regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). For Wave 1 (baseline), the PATH Study sampled over 150,000 mailing addresses across the United States to create a national sample of people who use or do not use tobacco, yielding interviews with 45,971 adult and youth respondents.

45,971 adults and youth constitute the first (baseline) wave, Wave 1, of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent.

At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled PSUs and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the civilian, noninstitutionalized population at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort.

At Wave 7, a probability sample of 14,863 adults, youth, and shadow youth ages 9 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 7. This sample was recruited from residential addresses not selected for Wave 1 or Wave 4 in the same sampled PSUs and segments using similar within-household sampling procedures. This second replenishment sample was combined for estimation and analysis purposes with Wave 7 adult and youth respondents from the Wave 4 Cohort who were at least age 15 and in the civilian, noninstitutionalized population at the time of Wave 7. This combined set of Wave 7 participants, 46,169 participants in total, forms the Wave 7 Cohort

Please refer to the Restricted-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1, Wave 4, and Wave 7 Cohorts.

Biospecimen Collection

Each adult respondent, who completed the interview at Wave 1, was asked to provide at least two biospecimens. Providing biospecimens was voluntary and was not a condition of participation. Respondents were asked to report their use of all nicotine-containing products during the 3-day period prior to the time of any biospecimen collection (Nicotine Exposure Questions (NEQs)) to facilitate interpretation of biomarker results.

Of the 32,320 respondents who completed the Adult Interview at Wave 1, 21,801 (67.4 percent) provided a urine specimen and 14,520 (44.9 percent) provided a blood specimen. For the purposes of subsampling adults into the Wave 1 Biomarker Core, adult participants were grouped by tobacco product use at Wave 1 into nine mutually exclusive groups.

A sample of 11,522 adults who provided sufficient urine for the planned analyses were selected from the first six tobacco product use groups (see section 3.1 of the Biomarker Restricted-Use Files User Guide) representing people who never used tobacco, currently use tobacco, and formerly used tobacco (within the last 12 months). This group constitutes the original Wave 1 Biomarker Core. Of the 11,522 adults, 7,159 also provided a blood specimen. All urine and blood specimens provided by the Wave 1 Biomarker Core were sent for laboratory analysis.

Subsequent to this selection, an additional stratified probability sample of adults who completed the Wave 1 Adult Interview and provided a sufficient amount of urine for the planned analyses at Wave 1 (independent of whether they provided a blood specimen) was selected from the remaining three product use groups (see section 3.1 of the Biomarker Restricted-Use Files User Guide). Wave 1 blood and urine specimens from this expansion sample were also sent for laboratory analysis. The original and expansion samples together form the expanded Wave 1 Biomarker Core. The expansion sample did not provide urine specimens for laboratory analysis again until Wave 7.

Each youth who completed the Wave 4 interview was asked to provide a urine specimen. Each Wave 4 shadow youth (ages 10 and 11 at Wave 4) who completed the Wave 5 youth interview was also asked to provide a urine specimen. Providing this urine biospecimen was voluntary and was not a condition of participation.

Of the 14,798 respondents who completed the Youth Interview at Wave 4, 13,097 (88.5 percent) provided a urine specimen. A sample of 3,509 Wave 4 Cohort youth ages 12 to 17 who completed the Wave 4 Youth Interview and provided a sufficient amount of urine for the planned laboratory analyses was selected from a diverse mix of five tobacco product use and non-use groups. In addition, a sample of 528 Wave 4 shadow youth who completed a Wave 5 interview and provided a sufficient amount of urine for the planned laboratory analyses at Wave 5 was also selected. These 4,037 sampled youth and shadow youth constitute the Wave 4 Biomarker Core. All urine specimens provided by the Wave 4 Biomarker Core were sent for laboratory analysis.

As members of the Wave 1 and Wave 4 Biomarker Cores age over time, a new Wave 7 Biomarker Core was designed to provide nationally representative estimates for the U.S. civilian noninstitutionalized adult (ages 18 and older) population (CNP) at the time of Wave 7 (2022-2023). To that end, Aat the conclusion of Wave 7, a new biomarker core was selected from Wave 7 Cohort adults who completed an interview and provided a urine specimen at Wave 7. The Wave 7 Biomarker Core sample selection was a two-stage process. Prior to the start of data collection, a subsample of continuing participants expected to be adults at the time of their Wave 7 interview, including some participants who were part of the Wave 1 or Wave 4 Biomarker Cores, was selected and flagged for urine collection; additionally, a subsample of replenishment sample address was selected and flagged so that any Wave 7 Adult Interview respondents living at the selected addresses would be asked to provide a urine specimen. Of the 10,698 Adult Interview respondents from these subsamples, 9,187 (85.9 percent) provided a urine specimen. A sample of 7,750 Wave 7 Cohort adults who completed the Wave 7 Adult Interview and provided a sufficient amount of urine for the planned laboratory analyses was selected from six mutually exclusive and exhaustive tobacco use groups (see section 3.3 of the Biomarker Restricted-Use Files User Guide). All urine specimens provided by the Wave 7 Biomarker Core were sent for laboratory analysis.

Biomarker Restricted Use Files

Wave 1 Restricted-Use Biomarker Data Files (Biomarker RUF) consists of three different types of files for the Wave 1 Biomarker Core:

• 2 Collection and NEQ files for Urine (DS1001) and Blood (DS1101)
• 2 Biomarker Weight files including variables for use in variance estimation for Urine (DS1021) and Blood (DS1121). Both files are updated to include records for the expanded Wave 1 Biomarker Core.
• 8 Urine Panels (DS1031 to DS1038), 4 Serum Panels (DS1131 to DS1134) and 1 Plasma Panel (DS1231) containing biomarker assay results. 6 Urine Panels (DS1032, DS1033, DS1035, DS1036, DS1037, and DS1038) and 2 Serum Panels (DS1131 and DS1132) are updated to include records for the expanded Wave 1 Biomarker Core.

All files updated to include records for the expanded Wave 1 Biomarker Core contain an indicator R01_A_W1BC_TYPE (1 = Original, 2 = Expansion) to identify respondents in the Wave 1 Biomarker Core original and expansion subsamples.

For Wave 2, urine biospecimens were requested from the original Wave 1 Biomarker Core. Respondents were also asked to complete the NEQs prior to biospecimen collection.

The Wave 2 Biomarker RUF consists of three different types of files:

• 1 Collection and NEQ file for Urine (DS2001)
• 2 Biomarker Weight files including variables for use in variance estimation for Urine (DS2021) and F2PG2a (DS2022)
• 8 Urine Panels (DS2031 to DS2038) containing biomarker assay results.

For Wave 3, urine biospecimens were requested from the original Wave 1 Biomarker Core. Respondents were also asked to complete the NEQs prior to biospecimen collection.

The Wave 3 Biomarker RUF consists of three different types of files:

• 1 Collection and NEQ file for Urine (DS3001)
• 4 Biomarker Weight files including variables for use in variance estimation for Urine (DS3021 and DS3022) and F2PG2a (DS3023 and DS3024).
• 7 Urine Panels (DS3032 to DS3038) containing biomarker assay results.

For Wave 4, urine biospecimens were requested from the original Wave 1 Biomarker Core and all youth who completed the Wave 4 interview. Respondents were also asked to complete the NEQs prior to biospecimen collection.

The Wave 4 Biomarker RUF consists of the following files for each Biomarker Core:

Wave 1 Biomarker Core:

• 1 Collection and NEQ file for Urine (DS4001)
• 4 Biomarker Weight files including variables for use in variance estimation for Urine (DS4021 and DS4022) and F2PG2a (DS4023 and DS4024).
• 7 Urine Panels (DS4032, DS4033, DS4034, DS4035, DS4036, DS4037 and DS4038) containing biomarker assay results.

Wave 4 Biomarker Core:

• 1 Collection and NEQ file for Youth Urine (DS4011)
• 1 Biomarker Weight files including variables for use in variance estimation for Urine (DS4043)
• 7 Urine Panels (DS4051, DS4053, DS4054, DS4055, DS4056, DS4057 and DS4058) containing biomarker assay results.

For Wave 5, urine biospecimens were requested from the original Wave 1 Biomarker Core and the Wave 4 Biomarker Core. Respondents were also asked to complete the NEQs prior to biospecimen collection.

The Wave 5 Biomarker RUF consists of the following files for each Biomarker Core:

Wave 1 Biomarker Core:

• 1 Collection and NEQ file for Urine (DS5001)
• 4 Biomarker Weight files including variables for use in variance estimation for Urine (DS5021 and DS5022) and F2PG2a (DS5023 and DS5024)
• 6 Urine Panels (DS5032, DS5033, DS5035, DS5036, DS5037, and DS5038) containing biomarker assay results.

Wave 4 Biomarker Core:

• 1 Collection and NEQ file for Youth Urine (DS5011)
• 1 Collection and NEQ file for Adult Urine (DS5001)
• 1 Biomarker Weight file including variables for use in variance estimation for Urine (DS5042)
• 7 Urine Panels (DS5051, DS5053, DS5054, DS5055, DS5056, DS5057, and DS5058) containing biomarker assay results.

Note that the initial release of 3 Urine Panels and Biomarker weights for the Wave 4 Biomarker Core only included records for those among the 3,509 members who responded in Wave 5 and provided urine specimens in sufficient quantities for laboratory analyses. As of version 20, the Wave 5 biomarker data files and weights include data for all Wave 4 Biomarker Core members who provided urine specimens at Wave 5 in sufficient quantities for laboratory analyses, including the Wave 4 shadow youth who completed their first interviews at Wave 5. This means that records were added to previously released urine panel data files (DS5051, DS5053, and DS5056) and biomarker weights (DS5042) to include data for the Wave 4 shadow youth (N=528) who completed their first interviews at Wave 5. All panels released in version 20 and beyond will include records for the complete Wave 4 Biomarker Core.

Also note that the Collection and NEQ file for Adult Urine (DS5001) includes data for both the Wave 1 Biomarker Core and Wave 4 Biomarker Core.

For Wave 7, urine biospecimens were requested from the Wave 1 Biomarker Core, the Wave 4 Biomarker Core, and those in the subsample eligible for the Wave 7 biomarker Core. Respondents were also asked to complete the NEQs prior to biospecimen collection.

The Wave 7 Biomarker RUF consists of the following files for each Biomarker Core:

Wave 1 Biomarker Core:

• 1 Collection and NEQ file for Urine (DS7001)
• 4 Biomarker Weight files including variables for use in variance estimation for Urine (DS7021 and DS7022) and F2PG2a (DS7023 and DS7024)
• 6 Urine Panels (DS7032, DS7033, DS7035, DS7036, DS7037, and DS7038) containing biomarker assay results.

Wave 4 Biomarker Core:

• 1 Collection and NEQ file for Youth Urine (DS7011)
• 1 Collection and NEQ file for Adult Urine (DS7001)
• 2 Biomarker Weight files including variables for use in variance estimation for Urine (DS7041 and DS7042)
• 6 Urine Panels (DS7051, DS7053, DS7055, DS7056, DS7057, and DS7058) containing biomarker assay results.

Wave 7 Biomarker Core:

• 1 Collection and NEQ file for Urine (DS7001)
• 1 Biomarker Weight file including variables for use in variance estimation for Urine (DS7061)
• 6 Urine Panels (DS7072, DS7073, DS7075, DS7076, DS7077, and DS7078) containing biomarker assay results.

The Collection and NEQ file for Adult Urine (DS7001) includes data for the Wave 1 Biomarker Core, Wave 4 Biomarker Core, and Wave 7 Biomarker Core.

Please refer to the Biomarker Restricted-Use Files User Guide for additional information about the Biomarker Cores.

References to the collection of biospecimens will be specified by the collected specimen, i.e., urine and (whole) blood. However, references to biomarker analyses and analytes will be specified by the type of matrix (serum, plasma, or urine) used for the analysis.

The Social Environment and Biomarkers of Aging Study (SEBAS) in Taiwan, 2000 and 2006, provides information regarding the health and well-being of older persons in Taiwan. Taiwan has undergone rapid demographic, social, and economic changes, becoming a highly urbanized and industrial society with a growing population of persons age 65 or older. SEBAS explores the relationship between life challenges and mental and physical health, the impact of social environment on the health and well-being of the elderly, as well as biological markers of health and stress. The study collected self-reports of physical, psychological, and social well-being, plus extensive clinical data based on medical examinations and laboratory analyses. Examination of health outcomes included chronic illnesses, functional status, psychological well-being, and cognitive function. Questions regarding life challenges focused on perceived stress, economic difficulties, security and safety, and the consequences of a major earthquake. Biological markers were used to identify cardiovascular risk factors, metabolic process measures, immune-system activity, the hypothalamic-pituitary adrenal axis, and sympathetic nervous system activity. Two rounds of biomarker data collected in 2000 and 2006 were complemented by face-to-face interviews with the participants. Demographic and background variables included age, sex, education, ethnicity, occupation, and residency.

Additional information about the Social Environment and Biomarkers of Aging Study can be found at the Georgetown University Center for Populations and Health Web site.

A Webinar describing the Social Environment and Biomarkers of Aging Study (SEBAS) was presented June 20, 2016. All interested users can access the webinar here.

In 2008, with funding from the National Institute on Aging (NIA), baseline survey data were collected from a probability sample of Japanese adults (N=1,027) aged 30 to 79 from the Tokyo metropolitan area, resulting in the Survey of Midlife in Japan (MIDJA) [ICPSR 30822]. In 2009-2010, biomarker data was obtained from a subset (n=382) of these cases (MIDJA Biomarker) [ICPSR 34969].

The survey and biomarker measures obtained, parallel those in a national longitudinal sample of Americans known as Midlife in the United States (MIDUS) [ICPSR 4652: MIDUS 2 and ICPSR 2760: MIDUS 1]. The central objective was to compare the Japanese sample (MIDJA) with the United States sample (MIDUS) to test hypotheses about the role of psychosocial factors in the health (broadly defined) of mid- and later-life adults in Japan and the United States

In 2012, with additional support from NIA, a longitudinal follow-up of the MIDJA sample was conducted resulting in a second wave (N=657) of survey data (MIDJA 2) [ICPSR 36427].

This collection reflects data from 2013-2014, when a second wave of biomarker data was obtained from a sub-sample (n=328) of those who completed the MIDJA 2 survey. Among this group, about 75 percent (n=243) also completed the first wave of biomarker assessments.

Participants traveled to a clinic on the University of Tokyo campus where biomarker data (vital signs, morphometric assessments, blood assays, and medication data) were obtained. Participants also provided daily saliva samples for cortisol assessment and completed a self-administered medical history questionnaire, as well as a time preference questionnaire.

The medical history questionnaire included assessments of conditions and symptoms, major health and life events, nutrition/diet, and additional psychosocial measures (anxiety, depression, relationship quality, control, etc.).

The time preference questionnaire was used to collect respondents' opinions on management of money and assets given hypothetical scenarios.

Demographic variables include age, gender, and marital status.

The World Health Organization (WHO)'s Study on Global Ageing and Adult Health (SAGE) is a longitudinal follow-up of a cohort of ageing and older adults. SAGE has been built on the experience and standardized instruments of WHO's 2000/2001 Multi-country Survey Study (MCSS) and the 2002/2004 World Health Surveys (WHS).

These surveys focused on health and health-related outcomes and their determinants and impacts in nationally representative samples. These data will address data gaps on ageing, adult health and well-being in lower and middle income countries, whilst being comparable to surveys conducted in higher income countries (such as the United States' Health and Retirement Study (HRS), English Longitudinal Study of Ageing (ELSA), and the Survey of Health, Ageing and Retirement in Europe (SHARE)). One of the major drivers of this effort has been the lack of comparability of self-reported health status in international health surveys due to systematic biases in reporting, despite using similar instruments and attempts at making questions conceptually equivalent in translation. SAGE uses standard instruments developed over the last decade, a common design and training approach with explicit strategies for making data comparable to cover a wide range of issues that directly and indirectly impact health and well-being.

The survey methodology and research design has included a number of methods to address methods for detecting and correcting for systematic reporting biases in health interview surveys, including vignette methodologies, objective performance tests and biomarkers. A number of techniques have also been employed to improve data comparability, including using common definitions of concepts, common methods of data collection and translations, rigorous sample design and post hoc harmonization. The 2007-2010 SAGE Wave 1 data from six countries (China, Ghana, India, Mexico, Russia, and South Africa) is the follow-up survey project to the 2002-2004 WHO data, which constitutes Wave 0 of WHO's Study on Global Ageing and Adult Health (SAGE). A sample of these respondents from SAGE Wave 0 are included in this follow-up 2007-2010 SAGE Wave 1 in the six countries, with new respondents added to ensure a nationally representative sample.