The Future of Families and Child Wellbeing Study (FFCWS), Public Use, United States, 1998-2024 (ICPSR 31622)
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:
- What are the conditions and capabilities of unmarried parents, especially fathers?
- What is the nature of the relationships between unmarried parents?
- How do children born into these families fare?
- 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.
Development of the Patient-Reported Outcomes Measurement Information System Pediatric Sleep Health Item Banks [Methods Study], United States, 2014-2018 (ICPSR 39510)
Healthy sleep is important for a child's well-being, school performance, and mood. Doctors can ask children about their sleep health to identify and treat sleep problems. However, few reliable surveys are available for doctors to use to ask children about their sleep.
In this study, the research team created sets of survey questions that asked children or their parents about sleep health. The team interviewed children and their parents to make sure they could understand the questions and that the questions included sleep health topics important to them.
Developing, Implementing, and Evaluating a Police Fatigue Risk-Management Strategy for the Seattle Police Department, Washington, 2020-2023 (ICPSR 39029)
The goal of the project was to improve police officers' sleep, health, safety, and wellness, thus improving the quality of police services. Using a multi-phase, mixed method approach, the core objectives included:
Measure the effects of work schedules and sleep loss on Seattle Police Department (SPD) officer health, wellness, safety, and quality of life.
Develop a fatigue risk management strategy, informed by the data collected during objective one.
Using a randomized control trial design, implement the resulting fatigue risk management strategy across the SPD, which is a large municipal police department (approximately 1,500 sworn officers)
Measure the effectiveness of the fatigue risk management strategy.
The main research questions the study sought to address were as follows:
What are the effects of shift work, work hours, sleep loss, and fatigue on police officers' safety, health, and quality of life?
Can a fatigue risk management strategy influence these effects?
Variables include measures of officers' sleep patterns and sleep quality, physical and mental health metrics, descriptions of the officers' role at the SPD, and demographic variables including age, gender, and race/ethnicity.
Midlife in the United States (MIDUS 3): Biomarker Project, 2017-2022 (ICPSR 38837)
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).
Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa [HAALSI]: Agincourt, South Africa, 2015-2022 (ICPSR 36633)
The Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa (HAALSI) study is a population-based survey that aims to examine and characterize a population of older men and women in rural South Africa with respect to health, physical and cognitive function, aging, and well-being, in harmonization with other Health and Retirement Studies.
The baseline survey was conducted among 5,059 men and women aged 40 years or older, who were sampled from within the existing framework of the Agincourt health and socio-demographic surveillance system (AHDSS), in rural Mpumalanga province, South Africa. Survey data were collected on cognitive and physical functioning, social networks, cardiometabolic disease and risk factors, HIV and HIV risk, and economic well-being. The survey also included anthropometric measures and point-of-care blood tests for hemoglobin, glucose and lipids. Dried bloodspots (DBS) were collected at the survey and later tested for HIV, HIV viral load, glucose and CRP. A sub-sample had more extensive laboratory follow-up testing, which will be available in future data releases. A second wave of the survey was administered in 2018 through 2019, and a third wave of the survey was administered in 2021 through 2022.
Demographic information includes age, sex, income, education, marital status, number of children, and employment.
Harvard dataverse hosts an additional restricted-use dataset which compliments this collection, the HAALSI Baseline HIV Biomarker Data; users interested in obtaining these data must request access based on the terms outlined in the data use agreement.
Temporal Trends in Racial and Ethnic Disparities in Sleep Duration in the United States: A National Health Interview Survey Analysis from 2004–2018 (ICPSR 152741)
Midlife in the United States (MIDUS Refresher 1): Biomarker Project, 2012-2016 (ICPSR 36901)
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.
National Poll on Healthy Aging (NPHA), [United States], April 2017 (ICPSR 37305)
By tapping into the perspectives of older adults and their caregivers, the University of Michigan National Poll on Healthy Aging (NPHA) helps inform the public, health care providers, policymakers, and advocates on issues related to health, health care and health policy affecting Americans 50 years of age and older.
The poll is designed as a recurring, nationally representative household survey of U.S. adults, which allows assessment of issues in a timely fashion.
Launched in spring 2017, the NPHA is modeled after the highly successful University of Michigan C.S. Mott Children's Hospital National Poll on Children's Health. The NPHA grew out of a strong interest in aging-related issues among many members of the University of Michigan Institute for Healthcare Policy and Innovation (IHPI), which brings together more than 600 faculty who study health, health care and the impacts of health policy. IHPI directs the poll which is sponsored by AARP and Michigan Medicine, the University of Michigan academic medical center.
More waves of the NPHA data can be found on the NACDA-OAR site:
- National Poll on Healthy Aging (NPHA), [United States], October 2017
- National Poll on Healthy Aging (NPHA), [United States], March 2018
- National Poll on Healthy Aging (NPHA), [United States], October 2018
- National Poll on Healthy Aging (NPHA), [United States], May 2019
The various waves of NPHA represent separate samples of participants and cannot be joined or merged.
Survey of Midlife in Japan (MIDJA 2): Biomarker Project, 2013-2014 (ICPSR 36530)
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.
Los Angeles Metropolitan Area Surveys [LAMAS] 6, 1973 (ICPSR 36615)
The Los Angeles Metropolitan Area Studies [LAMAS] 6, 1973 collection reflects data gathered in 1973 as part of the Los Angeles Metropolitan Area Studies (LAMAS). The LAMAS, beginning in the spring of 1970, are a shared-time omnibus survey of Los Angeles County community members, usually repeated twice annually. The LAMAS were conducted ten times between 1970 and 1976 in an effort to develop a set of standard community profile measures appropriate for use in the planning and evaluation of public policy.
The LAMAS instruments, indexes, and scales used to track the development and course of social indicators (including social, psychological, health, and economic variables) and the impact of public policy on the community. Questions in this year of the LAMAS cover respondents' attitudes toward the following topics: air pollution, health care services in the community, local government politics, police relations, recreation and leisure time. In addition, participating researchers were given the option of submitting questions to be asked in addition to the core items. These additional question topics include: sleep habits, the true self, impact of computers, job seeking behavior, and mental health and psychological factors.
Demographic variables in this collection include sex, age, race, ethnicity, education, occupation, income, religion, marital status, birth place, and housing type.
Online Sleep Survey Data (ICPSR 100375)
Risky Choice and Sleep Data (2008 NSF project) (ICPSR 100343)
Bayes task data from NSF 2008 Project (Sleep and Decisions) (ICPSR 100344)
Sleep Protocol data from 2012 NSF project (no decision task data) (ICPSR 100345)
Sleep after treatment for panic disorder in emergency department patients consulting for chest pain (ICPSR 36134)
Objective
A significant number of patients with unexplained chest pain (UCP) have panic disorder (PD), and most individuals with panic disorder (PD) report poor sleep, including insomnia and nocturnal panic attacks (NPA). The objective of the study was to examine the impact of treatment for PD on sleep problems and to assess the influence of pre-treatment insomnia on post-treatment persistence of PD diagnosis and pain severity.
Methods
Secondary analyses were conducted on sleep data collected from 42 PD patients consulting emergency departments (ED) for UCP. In this quasi-experimental design, cohorts of participants were randomly assigned to one of four conditions: (1) seven sessions of cognitive-behavior therapy (CBT) for PD, (2) a one-session panic management intervention, (3) pharmacotherapy, or (4) usual care. Data from clinical interviews performed by trained assistants and from self-report questionnaires were collected before and after treatment. Results after treatment, 35 percent of participants still met the diagnostic criteria for insomnia, and 20 percent of the sample still reported NPA. The presence of insomnia was a predictor of post-treatment pain severity (B = 1.336, SE B = .483, p = .009), regardless of the severity of pre-treatment anxiety and depressive symptoms or of assignation to an active PD treatment.
Conclusions
Treatment for PD had a small effect on sleep, and residual sleep difficulties persisted after treatment. More importantly, the presence of insomnia was a significant predictor of persistent pain after treatment. The results highlight the importance of careful assessment of sleep before and during treatment for PD in UCP patients.