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Research data keyboard_double_arrow_right Dataset 2008 EnglishPublisher:ICPSR - Interuniversity Consortium for Political and Social Research Funded by:NIH | Training in Developmental..., ARC | Maximising knowledge from..., NIH | HIV in Young Adulthood: P... +209 projectsNIH| Training in Developmental Science to Improve Child Health and Well-Being ,ARC| Maximising knowledge from dense SNP (single nucleotide polymorphisms) data using multi-locus analysis ,NIH| HIV in Young Adulthood: Pathways and Prevention ,NIH| Neuropharmacology of Response Inhibition in Comorbid ADHD and Nicotine Dependence ,NIH| Pharmacogenetics of Nicotine Addiction Treatment ,NIH| The Collaborative Genetic Study of Nicotine Dependence ,NIH| Fine Mapping Susceptibility Loci for Nicotine Dependence ,NIH| Transitions to Adulthood and Health Risk Among U.S. Young Adults ,NIH| Adolescent Health and Academic Achievement ,NIH| Alcohol Contextual Influences: Effects on Health Disparities and Mortality ,EC| ENGAGE ,NIH| Institute for Clinical and Translational Research (UL1) ,NIH| DIETARY ETIOLOGIES OF HEART DISEASE AND CANCER ,NIH| High Risk Drug Use &HIV-Learning from the NYC Epidemic ,NIH| Inflammation Genes and Lung Cancer Risk ,EC| TODO ,NIH| Synthetic Information Systems for Better Informing Public Health Policymakers ,NSF| CAREER: Model Fluid-Solid Interactions, Networks REUs, and BioCalculus ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN CANCER ,NIH| LONGITUDINAL STUDY OF SUBSTANCE USE, INCARCERATION, AND STI IN THE US ,NIH| Center for Family and Demographic Research ,NIH| GENETIC EPIDEMIOLOGY OF LUNG CANCER ,AKA| The Cardiovascular Risk in Young Finns Study - the 27-year follow-up. ,NIH| Age at First Sex, Genes, Religion, and Other Social and Demographic Context ,NIH| Human Genetics of Addiction: A Study of Common and Specific Factors ,NIH| The effects of heavy alcohol use on weight gain in college freshmen: Examining an overlooked calorie source ,NIH| Refining Phenotypic Measures of Nicotine Withdrawal ,NIH| Phenotypic refinement of externalizing pathways to alcohol-related behaviors ,NIH| NICHD Population Center ,NIH| A Nurse-Community Health Worker-Family Partnership Model to Increase COVID-19 Testing in Urban Underserved and Vulnerable Communities ,NIH| Human Subjects Core: Protocols, Statistics, Collaborative Method Development and ,NIH| University of Washington Reproductive, Perinatal and Pediatric Epidemiology ,NIH| MDMA and Other Hallucinogen Use: Onset and Abuse/Dependence ,NIH| Mapping Genes for comorbidity of SUDs and Depression ,NIH| Epidemiology of Venous Thrombosis &Pulmonary Embolism ,NIH| CORE--ADIPOSE TISSUE BIOLOGY AND BASIC MECHANISMS ,NIH| Washington University Institute of Clinical and Translational Sciences (UL1) ,AKA| Impact of childhood growth patterns and latent cardiovascular risk factors on the microcirculation in adult life: Cardiovascular risk in Young Finns Study ,NIH| ECONOMICS OF AGING TRAINING PROGRAM -- EXTENSION ,NIH| COSTS AND BENEFITS OF ALCOHOL SERVICES &INTERVENTIONS ,NIH| The Pathobiology of Nephrolithiasis ,ARC| Locating genes for elementary and complex cognitive abilities using genetic linkage and association analysis ,NIH| The Role of Peer Networks in Youth Drug Use ,NIH| Adolescent Alcohol Use: Disentangling Friend Selection &Influence ,NIH| Nicotinic receptor genes &substance abuse: Functional studies of associated SNPs ,NIH| Dietary Etiologies of Heart Disease ,NIH| FLUORIDE AND OTHER FACTORS IN CHILDHOOD BONE DEVELOPMENT ,WT ,NIH| Consortium for Neuropsychiatric Phenomics-Coordinating Center (1 of 8) ,NIH| Sexual Behavior Trajectories from Adolescence to Adulthood ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| YOUNG ADULT SUBSTANCE USE--PREDICTORS AND CONSEQUENCES ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| Social and Demographic Context and Heritability ,NIH| BEHAVIORAL PHARMACOGENETICS OF DRUG AND ALCOHOL ABUSE ,NIH| The Genetics of Vulnerability to Nicotine Addictions ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Deciphering genes and pathways in nicotine dependence ,NIH| HEALTHY YOUTH DEVELOPMENT PREVENTION RESEARCH AND TRAINING CENTER ,NSF| Machine learning techniques to model the impact of relational communication on distributed team effectiveness ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| JH/CIDR Genotyping for Genome-Wide Association Studies ,AKA| Sustainable Innovative Materials in High Tech Applications. An Interdisciplinary Approach to Design,Engineering Technology and Chemistry of Environmentally Sound Products and Production. ,EC| ADDICTION ,NIH| Modeling HIV and STD in Drug User and Social Networks ,NIH| Economic Evaluation Methods: Development and Application ,NIH| GENETIC INTERACTIONS CONTRIBUTING TO ALCOHOL AND NICOTINE DEPENDENCE ,NIH| MOTS: Modeling Obesity Through Simulation ,NIH| GENETICS OF COCAINE DEPENDENCE ,NIH| Population Research Training ,NIH| High Density Association Analysis of Lung Cancer ,NIH| UIC Program for Interdisciplinary Careers in Womens Health Research ,NIH| GENETICS OF NICOTINE AND OTHER ABUSED SUBSTANCES ,NIH| SUBSTANCE USE AND DISORDERED WEIGHT BEHAVIORS IN SEXUAL MINORITY YOUTH CONTEXTS ,AKA| Center of Excellence in Complex Disease Genetics ,NIH| OPTIMIZING BEHAVIORAL INTERVENTIONS FOR DRUG ABUSE PREVENTION &TREATMENT ,NIH| Exome Variants Underlying Weight Gain from Adolescence to Adulthood ,NIH| Health Disparities in Obesity: Partner Violence and its Psychosocial Pathways ,NIH| Vitamin D metabolism related genetic variations and developmental origins of card ,SSHRC ,NIH| Study of Addiction: Genetics and Environment ,NIH| The Genetic Epidemiology of Nicotine Dependence ,AKA| MSDs@LIFECOURSE CONSORTIU Subproject: Shared Risk Factors Study Group Turku University Central Hospital / Consortium: MSDs@LIFE ,ARC| Quantitative and Molecular Genetic Analysis of Cognition ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Propensity Scores and Preventive Drug Use in the Elderly ,NIH| Computational Methods to Detect Epistasis ,NIH| Center on Antisocial Drug Dependence: The Genetics of HIV Risk Behaviors ,NIH| Individual differences and health outcomes: A secondary data analysis in cognitiv ,NIH| Human Development: Interdisciplinary Research Training ,NIH| Health Disparities Among a Vulnerable Population: A Longitudinal Analysis ,AKA| Role of early life risk factors in associations between work, cardiovascular disease and depression: A life course approach based on two prospective cohorts. / Consortium: ELRFWCDD ,EC| SOCIOGENOME ,NIH| Data Mgmt &Analysis Core - The NINDS International Stroke Genetics Consortium St ,NIH| Genetic Risk, Pathways to Adulthood, and Health Inequalities ,NIH| Genetic &environmental pathways to drug use, abuse &dependence ,NSF| Social Inequality and Status Attainment ,NIH| GWA for Gene-Environment Interaction Effects Influencing CHD ,NIH| Do active communities support activity or support active people? ,NSF| The Genetic Basis of Social Networks and Civic Engagement ,AKA| Roles of inflammation, oxidation, sex hormones and genetic variation in vascular aging and the development of atherosclerosis over the life-course. ,NIH| Genes, early adversity, and sensitive periods in social-emotional development ,NSF| GSE/RES Gender Differences in Science and Math: Diversity and the Role of Social Context ,NIH| Colorado Adoption/Twin Study of Lifespan behavioral development & cognitive aging (CATSLife) ,NIH| VARIATION IN THE EFFECTS OF ALCOHOL ON LIVER FUNCTION ,NSF| Science Achievement and Health Behavior: High School Curriculum, Social Context, and Opportunity to Learn ,NIH| Comprehensive Mapping of a Blood Pressure QTL on Chromosome 17 ,NIH| CUPC Admin Core ,NIH| Physical Environment Dynamics, Inequality and Obesity ,NIH| Social Support as a Facilitator of Adherence to HIV Pre-Exposure Prophylaxis Among Young MSM of Color ,NIH| Genetics of Adolescent Antisocial Drug Dependence ,NIH| PATHOLOGY MONITORING--F344 RAT COLONY ,NIH| Role of Romantic Relationships in the Sexual Behavior of Obese and Non-Obese Girl ,NIH| Statistical Methods for Network Epidemiology ,NIH| GENETICS AND CONSEQUENCES OF NICOTINE ADDICTION ,NIH| Washington University Institute of Clinical and Translational Sciences (KL2) ,CIHR ,NIH| Carolina Population Center ,NIH| Mid Southern Primary Care Networks Node ,NIH| Carolina Population Center ,NIH| SOCIAL DEMOGRAPHY ,NIH| Birth Outcomes Among Adolescents ,NIH| TRAINING GRANT IN CANCER EPIDEMIOLOGY ,NIH| Translational studies of nicotinic receptor genes: alcohol and nicotine behaviors ,NIH| Identifying essential network properties for disease spread ,NIH| Genetic Epidemiology of Lung Cancer ,NIH| Population Research Center ,EC| NBHCHOICE ,NIH| Molecular Epidemiology of Alcoholism 3 - EDAC Families ,NIH| PROSTATE, LUNG, COLORECTAL &OVARIAN CANCER ,NIH| Identifying Mediated Pathways of Risk for Substance Use in Sexual Minority Girls ,NIH| Genetic Risk to Stroke in Smokers and Nonsmokers in Two Ethnic Groups ,NIH| From GWAS loci to blood pressure genes, variants & mechanisms ,ARC| Elucidating the genetics of attention deficit hyperactivity disorder by integrating pathway and prediction analyses ,NIH| Systematic Error and Confounding: Meta-Analyses of Alcohol and Disease ,NIH| Novel Use of Gwas for Improved Understanding of Nicotine Dependence ,NIH| University of Minnesota Clinical and Translational Science Institute (UMN CTSI) ,AKA| Public Health Genomics to Practice in Cardiovascular Diseases / Consortium: PUBGENSENS ,NIH| PERSISTENCE &CHANGE IN DRINKING HABITS: TWIN STUDY ,NIH| The University of Colorado Population Center ,NIH| Childhood Family Instability, Adult Stress Reactivity, and Consequences for Health ,NIH| BEYOND RACE--EXPLAINING INEQUALITY MANIFESTED AS OBESITY ,NIH| HUMAN GENETIC VARIATION IN SMOKING AND ADDICTION RISK ,NIH| GENETICS OF ADOLESCENT ANTISOCIAL DRUG DEPENDENCE ,NIH| GENETICS OF VULNERABILITY TO NICOTINE ADDICTION ,NIH| Community Assist of Southern Arizona ,NIH| Genes and Environment Initiatives in Type 2 Diabetes ,NIH| DIET, HORMONES AND RISK OF COLORECTAL CANCERS ,NIH| PROSPECTIVE LONGITUDINAL STUDY OF ADOLESCENT HEALTH ,NIH| The Washington University Center for Diabetes Translation Research ,NIH| Variants in CHRNA5/CHRNA3/CHRNB4 and nicotine dependence ,NIH| Model-Based Clustering Methods of Medical Image ,NIH| University of Colorado Population Center ,NIH| Smoking/Nicotine Dependence in Attention Deficit Hyperactivity Disorder (ADHD) ,NIH| Molecular Genetics and Behavior: Alcohol and Tobacco Use ,WT| Familial and other risk factors for adolescent substance use and abuse. ,NIH| Stressors and their impact on health related addictions: smoking, drinking, BMI ,NSF| Neighborhoods and Schools, Education, and Heritability ,NIH| Substance Abuse & Treatment Gaps in Asians, Pacific Islanders & Multiple-race Ind ,NIH| Economic Evaluation of Adolescent Alcohol Use and the Impact of Social Networks ,NIH| Outreach Core ,NIH| Innovations in Pediatric Pain Research ,NIH| NYS FAMILY STUDY: PROBLEM ALCOHOL USE &PROBLEM BEHAVIOR ,NIH| Research Training Program in the Behavioral and Biomedical Sciences ,NIH| Obesity and Metabolic Risk Disparities: Underlying Food Environment Factors ,NIH| The Social Marginalization of Adolescents in High School ,NIH| Socioeconomic Disparities in Young Adult Health ,NIH| A Center for GEI Association Studies ,NIH| Longtudinal Relations Between Internalizing Disorders and Substance Use Problems ,NIH| Genetics of Early Onset-Stroke ,NIH| Obesity and the Environment: The Transition to Adulthood ,NIH| Mentoring Clinical Investigators in Adolescent-onset Substance Use Disorders Research ,NIH| Molecular Epidemiology of Alcoholism 2- Big Sibships ,NIH| Genome-Wide Association for Loci Influencing CHD and Other Heart, Lung and Blood ,NSF| Health Lifestyles and the Reproduction of Inequality ,NIH| Sexual Orientation and Obesity: Test of a Gendered Biopsychosocial Model ,NIH| PROSTATE, LUNG, COLORECTAL, AND OVARIAN (PLCO) CANCER ,NIH| Longitudinal Study of Trauma, HIV Risk, and Criminal Justice Involvement ,NSF| National Science Foundation Alan T. Waterman Award ,NIH| Interracial Friendship and Romance Among Adolescents ,NIH| Genetics of Opioid Dependence ,NIH| Linkage Disequilibrium Studies of Alcohol Dependence ,NIH| MECHANISMS AND PREVENTION OF ENVIRONMENTAL DISEASE ,NIH| Understanding memory consolidation by studying pharmacologically enhanced naps ,NIH| Administrative and Research Support Core ,NIH| Data Core ,NIH| Administrative Core ,NIH| Adenocarinoma of the Lung in Women ,NIH| Social Demographic Moderation of Genome Wide Associations for Body Mass Index ,NIH| Response Inhibition and Dopamine Neurotransmission (RI) (4 of 8) ,NIH| Racial disparities in cancer outcomes: quantifying modifiable mechanisms ,NIH| Research and Mentoring on Integrating Psychiatric Genetics and Neuroscience ,NIH| Cancer Center Support Grant ,NIH| The University of Iowa Prevention Research Center ,NIH| BIOBEHAVIORAL FACTORS IN CORONARY HEART DISEASE ,EC| DEPRIVEDHOODS ,NHMRC| Experience-dependent cellular plasticity and cognitive deficits in mouse models of schizophrenia ,NIH| Genes, Environments & Interventions: Understanding and Addressing Alcohol Misuse ,NIH| FINANCIAL STATUS--RETIREMENT SAVING PROGRAMS ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| NATURAL HISTORY OF ALCOHOL USE &ABUSE--GENETIC MODELS ,NIH| Genome Wide Association Coordinating Center ,NIH| Health Communication and Health Literacy Core ,NIH| Genome-Wide Associations Environmental Interactions in the Lung Health Study ,EC| GMI ,NIH| Intergenerational Research on Obesity Prevention: From Correlates to Intervention ,NIH| Genetics of Alcohol Dependence in African-Americans ,NIH| Containing Bioterroist and Emerging Infectious Diseases ,NIH| UNC Interdisciplinary Obesity Training (IDOT)(RMI) ,NIH| Population Research Institute ,EC| DYNANETS ,NIH| Statistical Methods for Gene Environment Interactions In Lung CancerAuthors: Harris, Kathleen Mullan; Udry, J. Richard;Harris, Kathleen Mullan; Udry, J. Richard;doi: 10.3886/icpsr21600.v16 , 10.3886/icpsr21600.v4 , 10.3886/icpsr21600.v6 , 10.3886/icpsr21600.v20 , 10.3886/icpsr21600.v19 , 10.3886/icpsr21600.v9 , 10.3886/icpsr21600.v15 , 10.3886/icpsr21600.v8 , 10.3886/icpsr21600.v12 , 10.3886/icpsr21600.v22 , 10.3886/icpsr21600.v14 , 10.3886/icpsr21600.v10 , 10.3886/icpsr21600.v17 , 10.3886/icpsr21600.v13 , 10.3886/icpsr21600.v11 , 10.3886/icpsr21600.v18 , 10.3886/icpsr21600.v21 , 10.3886/icpsr21600.v3 , 10.3886/icpsr21600.v1 , 10.3886/icpsr21600.v5 , 10.3886/icpsr21600.v7 , 10.3886/icpsr21600.v2
doi: 10.3886/icpsr21600.v16 , 10.3886/icpsr21600.v4 , 10.3886/icpsr21600.v6 , 10.3886/icpsr21600.v20 , 10.3886/icpsr21600.v19 , 10.3886/icpsr21600.v9 , 10.3886/icpsr21600.v15 , 10.3886/icpsr21600.v8 , 10.3886/icpsr21600.v12 , 10.3886/icpsr21600.v22 , 10.3886/icpsr21600.v14 , 10.3886/icpsr21600.v10 , 10.3886/icpsr21600.v17 , 10.3886/icpsr21600.v13 , 10.3886/icpsr21600.v11 , 10.3886/icpsr21600.v18 , 10.3886/icpsr21600.v21 , 10.3886/icpsr21600.v3 , 10.3886/icpsr21600.v1 , 10.3886/icpsr21600.v5 , 10.3886/icpsr21600.v7 , 10.3886/icpsr21600.v2
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), 1994-2008 [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). Datasets: DS0: Study-Level Files DS1: Wave I: In-Home Questionnaire, Public Use Sample DS2: Wave I: Public Use Contextual Database DS3: Wave I: Network Variables DS4: Wave I: Public Use Grand Sample Weights DS5: Wave II: In-Home Questionnaire, Public Use Sample DS6: Wave II: Public Use Contextual Database DS7: Wave II: Public Use Grand Sample Weights DS8: Wave III: In-Home Questionnaire, Public Use Sample DS9: Wave III: In-Home Questionnaire, Public Use Sample (Section 17: Relationships) DS10: Wave III: In-Home Questionnaire, Public Use Sample (Section 18: Pregnancies) DS11: Wave III: In-Home Questionnaire, Public Use Sample (Section 19: Relationships in Detail) DS12: Wave III: In-Home Questionnaire, Public Use Sample (Section 22: Completed Pregnancies) DS13: Wave III: In-Home Questionnaire, Public Use Sample (Section 23: Current Pregnancies) DS14: Wave III: In-Home Questionnaire, Public Use Sample (Section 24: Live Births) DS15: Wave III: In-Home Questionnaire, Public Use Sample (Section 25: Children and Parenting) DS16: Wave III: Public Use Education Data DS17: Wave III: Public Use Graduation Data DS18: Wave III: Public Use Education Data Weights DS19: Wave III: Add Health School Weights DS20: Wave III: Peabody Picture Vocabulary Test (PVT), Public Use DS21: Wave III: Public In-Home Weights DS22: Wave IV: In-Home Questionnaire, Public Use Sample DS23: Wave IV: In-Home Questionnaire, Public Use Sample (Section 16B: Relationships) DS24: Wave IV: In-Home Questionnaire, Public Use Sample (Section 16C: Relationships) DS25: Wave IV: In-Home Questionnaire, Public Use Sample (Section 18: Pregnancy Table) DS26: Wave IV: In-Home Questionnaire, Public Use Sample (Section 19: Live Births) DS27: Wave IV: In-Home Questionnaire, Public Use Sample (Section 20A: Children and Parenting) DS28: Wave IV: Biomarkers, Measures of Inflammation and Immune Function DS29: Wave IV: Biomarkers, Measures of Glucose Homeostasis DS30: Wave IV: Biomarkers, Lipids DS31: Wave IV: Public Use Weights Wave I: The Stage 1 in-school sample was a stratified, random sample of all high schools in the United States. A school was eligible for the sample if it included an 11th grade and had a minimum enrollment of 30 students. A feeder school -- a school that sent graduates to the high school and that included a 7th grade -- was also recruited from the community. The in-school questionnaire was administered to more than 90,000 students in grades 7 through 12. The Stage 2 in-home sample of 27,000 adolescents consisted of a core sample from each community, plus selected special over samples. Eligibility for over samples was determined by an adolescent's responses on the in-school questionnaire. Adolescents could qualify for more than one sample.; Wave II: The Wave II in-home interview surveyed almost 15,000 of the same students one year after Wave I.; Wave III: The in-home Wave III sample consists of over 15,000 Wave I respondents who could be located and re-interviewed six years later.; Wave IV: All original Wave I in-home respondents were eligible for in-home interviews at Wave IV. At Wave IV, the Add Health sample was dispersed across the nation with respondents living in all 50 states. Administrators were able to locate 92.5% of the Wave IV sample and interviewed 80.3% of eligible sample members. ; For additional information on sampling, including detailed information on special oversamples, please see the Add Health Study Design page. Add Health was developed in response to a mandate from the U.S. Congress to fund a study of adolescent health. Waves I and II focused on the forces that may influence adolescents' health and risk behaviors, including personal traits, families, friendships, romantic relationships, peer groups, schools, neighborhoods, and communities. As participants aged into adulthood, the scientific goals of the study expanded and evolved. Wave III explored adolescent experiences and behaviors related to decisions, behavior, and health outcomes in the transition to adulthood. Wave IV expanded to examine developmental and health trajectories across the life course of adolescence into young adulthood, using an integrative study design which combined social, behavioral, and biomedical measures data collection. Response Rates: Response rates for each wave were as follows: Wave I: 79 percent; Wave II: 88.6 percent; Wave III: 77.4 percent; Wave IV: 80.3 percent; Adolescents in grades 7 through 12 during the 1994-1995 school year. Respondents were geographically located in the United States. audio computer-assisted self interview (ACASI) computer-assisted personal interview (CAPI) computer-assisted self interview (CASI) paper and pencil interview (PAPI) face-to-face interview
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2008 EnglishPublisher:ICPSR - Interuniversity Consortium for Political and Social Research Funded by:WT, NIH | Population Research Train..., NIH | High Density Association ... +197 projectsWT ,NIH| Population Research Training ,NIH| High Density Association Analysis of Lung Cancer ,NIH| OPTIMIZING BEHAVIORAL INTERVENTIONS FOR DRUG ABUSE PREVENTION &TREATMENT ,NIH| GENETIC EPIDEMIOLOGY OF LUNG CANCER ,AKA| The Cardiovascular Risk in Young Finns Study - the 27-year follow-up. ,NIH| Age at First Sex, Genes, Religion, and Other Social and Demographic Context ,NIH| Human Genetics of Addiction: A Study of Common and Specific Factors ,NIH| The effects of heavy alcohol use on weight gain in college freshmen: Examining an overlooked calorie source ,NIH| Refining Phenotypic Measures of Nicotine Withdrawal ,NIH| Statistical Methods for Network Epidemiology ,NIH| GENETICS AND CONSEQUENCES OF NICOTINE ADDICTION ,NIH| Washington University Institute of Clinical and Translational Sciences (KL2) ,NIH| Alcohol Contextual Influences: Effects on Health Disparities and Mortality ,EC| ENGAGE ,NIH| Institute for Clinical and Translational Research (UL1) ,NIH| DIETARY ETIOLOGIES OF HEART DISEASE AND CANCER ,NIH| High Risk Drug Use &HIV-Learning from the NYC Epidemic ,NIH| Inflammation Genes and Lung Cancer Risk ,EC| TODO ,NSF| CAREER: Model Fluid-Solid Interactions, Networks REUs, and BioCalculus ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN CANCER ,NIH| LONGITUDINAL STUDY OF SUBSTANCE USE, INCARCERATION, AND STI IN THE US ,NIH| Identifying Mediated Pathways of Risk for Substance Use in Sexual Minority Girls ,NIH| Genetic Risk to Stroke in Smokers and Nonsmokers in Two Ethnic Groups ,NIH| From GWAS loci to blood pressure genes, variants & mechanisms ,ARC| Elucidating the genetics of attention deficit hyperactivity disorder by integrating pathway and prediction analyses ,NIH| Systematic Error and Confounding: Meta-Analyses of Alcohol and Disease ,NIH| Novel Use of Gwas for Improved Understanding of Nicotine Dependence ,NIH| University of Minnesota Clinical and Translational Science Institute (UMN CTSI) ,AKA| Public Health Genomics to Practice in Cardiovascular Diseases / Consortium: PUBGENSENS ,NIH| PERSISTENCE &CHANGE IN DRINKING HABITS: TWIN STUDY ,NIH| The University of Colorado Population Center ,NIH| HUMAN GENETIC VARIATION IN SMOKING AND ADDICTION RISK ,NIH| GENETICS OF ADOLESCENT ANTISOCIAL DRUG DEPENDENCE ,NIH| Genome-Wide Associations Environmental Interactions in the Lung Health Study ,CIHR ,EC| GMI ,NIH| Intergenerational Research on Obesity Prevention: From Correlates to Intervention ,NIH| Genetics of Alcohol Dependence in African-Americans ,NIH| Containing Bioterroist and Emerging Infectious Diseases ,NIH| UNC Interdisciplinary Obesity Training (IDOT)(RMI) ,NIH| Population Research Institute ,EC| DYNANETS ,NIH| Statistical Methods for Gene Environment Interactions In Lung Cancer ,NIH| Administrative Core ,NIH| Adenocarinoma of the Lung in Women ,NIH| Social Demographic Moderation of Genome Wide Associations for Body Mass Index ,NIH| BEYOND RACE--EXPLAINING INEQUALITY MANIFESTED AS OBESITY ,NIH| Carolina Population Center ,NIH| Mid Southern Primary Care Networks Node ,NIH| Carolina Population Center ,NIH| SOCIAL DEMOGRAPHY ,NIH| Birth Outcomes Among Adolescents ,NIH| TRAINING GRANT IN CANCER EPIDEMIOLOGY ,NIH| Translational studies of nicotinic receptor genes: alcohol and nicotine behaviors ,NIH| Identifying essential network properties for disease spread ,NIH| Genetic Epidemiology of Lung Cancer ,NIH| Study of Addiction: Genetics and Environment ,NIH| The Genetic Epidemiology of Nicotine Dependence ,AKA| MSDs@LIFECOURSE CONSORTIU Subproject: Shared Risk Factors Study Group Turku University Central Hospital / Consortium: MSDs@LIFE ,ARC| Quantitative and Molecular Genetic Analysis of Cognition ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Propensity Scores and Preventive Drug Use in the Elderly ,NIH| Response Inhibition and Dopamine Neurotransmission (RI) (4 of 8) ,NIH| Racial disparities in cancer outcomes: quantifying modifiable mechanisms ,NIH| Research and Mentoring on Integrating Psychiatric Genetics and Neuroscience ,NIH| Computational Methods to Detect Epistasis ,NIH| Center on Antisocial Drug Dependence: The Genetics of HIV Risk Behaviors ,NIH| Individual differences and health outcomes: A secondary data analysis in cognitiv ,NIH| Human Development: Interdisciplinary Research Training ,AKA| Role of early life risk factors in associations between work, cardiovascular disease and depression: A life course approach based on two prospective cohorts. / Consortium: ELRFWCDD ,EC| SOCIOGENOME ,NIH| Data Mgmt &Analysis Core - The NINDS International Stroke Genetics Consortium St ,NIH| Genetic Risk, Pathways to Adulthood, and Health Inequalities ,NIH| Genetic &environmental pathways to drug use, abuse &dependence ,NSF| Social Inequality and Status Attainment ,NIH| GWA for Gene-Environment Interaction Effects Influencing CHD ,NIH| Do active communities support activity or support active people? ,NSF| The Genetic Basis of Social Networks and Civic Engagement ,AKA| Roles of inflammation, oxidation, sex hormones and genetic variation in vascular aging and the development of atherosclerosis over the life-course. ,NIH| Genes, early adversity, and sensitive periods in social-emotional development ,NSF| GSE/RES Gender Differences in Science and Math: Diversity and the Role of Social Context ,NIH| Colorado Adoption/Twin Study of Lifespan behavioral development & cognitive aging (CATSLife) ,NIH| VARIATION IN THE EFFECTS OF ALCOHOL ON LIVER FUNCTION ,NSF| Science Achievement and Health Behavior: High School Curriculum, Social Context, and Opportunity to Learn ,NIH| Comprehensive Mapping of a Blood Pressure QTL on Chromosome 17 ,NIH| Physical Environment Dynamics, Inequality and Obesity ,NIH| Social Support as a Facilitator of Adherence to HIV Pre-Exposure Prophylaxis Among Young MSM of Color ,NIH| Genetics of Adolescent Antisocial Drug Dependence ,NIH| PATHOLOGY MONITORING--F344 RAT COLONY ,NIH| Role of Romantic Relationships in the Sexual Behavior of Obese and Non-Obese Girl ,NIH| GENETICS OF VULNERABILITY TO NICOTINE ADDICTION ,NIH| Community Assist of Southern Arizona ,NIH| Center for Family and Demographic Research ,NIH| Sexual Orientation and Obesity: Test of a Gendered Biopsychosocial Model ,NIH| PROSTATE, LUNG, COLORECTAL, AND OVARIAN (PLCO) CANCER ,NIH| Longitudinal Study of Trauma, HIV Risk, and Criminal Justice Involvement ,NSF| National Science Foundation Alan T. Waterman Award ,NIH| Interracial Friendship and Romance Among Adolescents ,NIH| Understanding memory consolidation by studying pharmacologically enhanced naps ,NIH| Administrative and Research Support Core ,NIH| Data Core ,NIH| Population Research Center ,EC| NBHCHOICE ,NIH| Molecular Epidemiology of Alcoholism 3 - EDAC Families ,NIH| PROSTATE, LUNG, COLORECTAL &OVARIAN CANCER ,NIH| NICHD Population Center ,NIH| A Nurse-Community Health Worker-Family Partnership Model to Increase COVID-19 Testing in Urban Underserved and Vulnerable Communities ,NIH| Human Subjects Core: Protocols, Statistics, Collaborative Method Development and ,NIH| University of Washington Reproductive, Perinatal and Pediatric Epidemiology ,NIH| MDMA and Other Hallucinogen Use: Onset and Abuse/Dependence ,NIH| Mapping Genes for comorbidity of SUDs and Depression ,NIH| Epidemiology of Venous Thrombosis &Pulmonary Embolism ,NIH| CORE--ADIPOSE TISSUE BIOLOGY AND BASIC MECHANISMS ,NIH| Washington University Institute of Clinical and Translational Sciences (UL1) ,AKA| Impact of childhood growth patterns and latent cardiovascular risk factors on the microcirculation in adult life: Cardiovascular risk in Young Finns Study ,NIH| ECONOMICS OF AGING TRAINING PROGRAM -- EXTENSION ,NIH| COSTS AND BENEFITS OF ALCOHOL SERVICES &INTERVENTIONS ,NIH| The Pathobiology of Nephrolithiasis ,ARC| Locating genes for elementary and complex cognitive abilities using genetic linkage and association analysis ,NIH| The Role of Peer Networks in Youth Drug Use ,NIH| Adolescent Alcohol Use: Disentangling Friend Selection &Influence ,NIH| Nicotinic receptor genes &substance abuse: Functional studies of associated SNPs ,NIH| Dietary Etiologies of Heart Disease ,NIH| FLUORIDE AND OTHER FACTORS IN CHILDHOOD BONE DEVELOPMENT ,NIH| Consortium for Neuropsychiatric Phenomics-Coordinating Center (1 of 8) ,NIH| Sexual Behavior Trajectories from Adolescence to Adulthood ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| YOUNG ADULT SUBSTANCE USE--PREDICTORS AND CONSEQUENCES ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| Deciphering genes and pathways in nicotine dependence ,NIH| Cancer Center Support Grant ,NIH| The University of Iowa Prevention Research Center ,NIH| BIOBEHAVIORAL FACTORS IN CORONARY HEART DISEASE ,NIH| Obesity and Metabolic Risk Disparities: Underlying Food Environment Factors ,EC| DEPRIVEDHOODS ,NIH| The Social Marginalization of Adolescents in High School ,NIH| Genes, Environments & Interventions: Understanding and Addressing Alcohol Misuse ,NIH| FINANCIAL STATUS--RETIREMENT SAVING PROGRAMS ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| NATURAL HISTORY OF ALCOHOL USE &ABUSE--GENETIC MODELS ,NIH| Genome Wide Association Coordinating Center ,NIH| Health Communication and Health Literacy Core ,NIH| Genetics of Opioid Dependence ,NIH| Linkage Disequilibrium Studies of Alcohol Dependence ,NIH| The Collaborative Genetic Study of Nicotine Dependence ,NIH| Fine Mapping Susceptibility Loci for Nicotine Dependence ,NIH| Adolescent Health and Academic Achievement ,NIH| HEALTHY YOUTH DEVELOPMENT PREVENTION RESEARCH AND TRAINING CENTER ,NIH| MECHANISMS AND PREVENTION OF ENVIRONMENTAL DISEASE ,NSF| Machine learning techniques to model the impact of relational communication on distributed team effectiveness ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| JH/CIDR Genotyping for Genome-Wide Association Studies ,AKA| Sustainable Innovative Materials in High Tech Applications. An Interdisciplinary Approach to Design,Engineering Technology and Chemistry of Environmentally Sound Products and Production. ,EC| ADDICTION ,NIH| Modeling HIV and STD in Drug User and Social Networks ,NIH| Economic Evaluation Methods: Development and Application ,NIH| GENETIC INTERACTIONS CONTRIBUTING TO ALCOHOL AND NICOTINE DEPENDENCE ,NIH| MOTS: Modeling Obesity Through Simulation ,NIH| GENETICS OF COCAINE DEPENDENCE ,NIH| GENETICS OF NICOTINE AND OTHER ABUSED SUBSTANCES ,NIH| SUBSTANCE USE AND DISORDERED WEIGHT BEHAVIORS IN SEXUAL MINORITY YOUTH CONTEXTS ,AKA| Center of Excellence in Complex Disease Genetics ,NIH| Exome Variants Underlying Weight Gain from Adolescence to Adulthood ,NIH| Health Disparities in Obesity: Partner Violence and its Psychosocial Pathways ,NIH| Vitamin D metabolism related genetic variations and developmental origins of card ,NIH| Training in Developmental Science to Improve Child Health and Well-Being ,ARC| Maximising knowledge from dense SNP (single nucleotide polymorphisms) data using multi-locus analysis ,NIH| HIV in Young Adulthood: Pathways and Prevention ,NIH| Neuropharmacology of Response Inhibition in Comorbid ADHD and Nicotine Dependence ,NIH| Pharmacogenetics of Nicotine Addiction Treatment ,NIH| Smoking/Nicotine Dependence in Attention Deficit Hyperactivity Disorder (ADHD) ,NIH| Molecular Genetics and Behavior: Alcohol and Tobacco Use ,WT| Familial and other risk factors for adolescent substance use and abuse. ,NIH| Stressors and their impact on health related addictions: smoking, drinking, BMI ,NSF| Neighborhoods and Schools, Education, and Heritability ,NIH| Substance Abuse & Treatment Gaps in Asians, Pacific Islanders & Multiple-race Ind ,NIH| Economic Evaluation of Adolescent Alcohol Use and the Impact of Social Networks ,NIH| Outreach Core ,NIH| NYS FAMILY STUDY: PROBLEM ALCOHOL USE &PROBLEM BEHAVIOR ,NIH| Socioeconomic Disparities in Young Adult Health ,NIH| A Center for GEI Association Studies ,NIH| Longtudinal Relations Between Internalizing Disorders and Substance Use Problems ,NIH| Genetics of Early Onset-Stroke ,NIH| Obesity and the Environment: The Transition to Adulthood ,NIH| Mentoring Clinical Investigators in Adolescent-onset Substance Use Disorders Research ,NIH| Molecular Epidemiology of Alcoholism 2- Big Sibships ,NIH| Genome-Wide Association for Loci Influencing CHD and Other Heart, Lung and Blood ,NIH| Social and Demographic Context and Heritability ,NIH| BEHAVIORAL PHARMACOGENETICS OF DRUG AND ALCOHOL ABUSE ,NIH| The Genetics of Vulnerability to Nicotine Addictions ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Genes and Environment Initiatives in Type 2 Diabetes ,NIH| DIET, HORMONES AND RISK OF COLORECTAL CANCERS ,NIH| PROSPECTIVE LONGITUDINAL STUDY OF ADOLESCENT HEALTH ,NIH| The Washington University Center for Diabetes Translation Research ,NIH| Variants in CHRNA5/CHRNA3/CHRNB4 and nicotine dependence ,NIH| Model-Based Clustering Methods of Medical Image ,SSHRCAuthors: Harris, Kathleen Mullan; Udry, J. Richard;Harris, Kathleen Mullan; Udry, J. Richard;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. Datasets: DS0: Study-Level Files DS1: Wave I: In-Home Questionnaire, Public Use Sample DS2: Wave I: Public Use Contextual Database DS3: Wave I: Network Variables DS4: Wave I: Public Use Grand Sample Weights DS5: Wave II: In-Home Questionnaire, Public Use Sample DS6: Wave II: Public Use Contextual Database DS7: Wave II: Public Use Grand Sample Weights DS8: Wave III: In-Home Questionnaire, Public Use Sample DS9: Wave III: In-Home Questionnaire, Public Use Sample (Section 17: Relationships) DS10: Wave III: In-Home Questionnaire, Public Use Sample (Section 18: Pregnancies) DS11: Wave III: In-Home Questionnaire, Public Use Sample (Section 19: Relationships in Detail) DS12: Wave III: In-Home Questionnaire, Public Use Sample (Section 22: Completed Pregnancies) DS13: Wave III: In-Home Questionnaire, Public Use Sample (Section 23: Current Pregnancies) DS14: Wave III: In-Home Questionnaire, Public Use Sample (Section 24: Live Births) DS15: Wave III: In-Home Questionnaire, Public Use Sample (Section 25: Children and Parenting) DS16: Wave III: Public Use Education Data DS17: Wave III: Public Use Graduation Data DS18: Wave III: Public Use Education Data Weights DS19: Wave III: Add Health School Weights DS20: Wave III: Peabody Picture Vocabulary Test (PVT), Public Use DS21: Wave III: Public In-Home Weights DS22: Wave IV: In-Home Questionnaire, Public Use Sample DS23: Wave IV: In-Home Questionnaire, Public Use Sample (Section 16B: Relationships) DS24: Wave IV: In-Home Questionnaire, Public Use Sample (Section 16C: Relationships) DS25: Wave IV: In-Home Questionnaire, Public Use Sample (Section 18: Pregnancy Table) DS26: Wave IV: In-Home Questionnaire, Public Use Sample (Section 19: Live Births) DS27: Wave IV: In-Home Questionnaire, Public Use Sample (Section 20A: Children and Parenting) DS28: Wave IV: Biomarkers, Measures of Inflammation and Immune Function DS29: Wave IV: Biomarkers, Measures of Glucose Homeostasis DS30: Wave IV: Biomarkers, Lipids DS31: Wave IV: Public Use Weights DS32: Wave V: Mixed-Mode Survey, Public Use Sample DS33: Wave V: Mixed-Mode Survey, Public Use Sample (Section 16B: Pregnancy, Live Births, Children and Parenting) DS34: Wave V: Biomarkers, Anthropometrics DS35: Wave V: Biomarkers, Cardiovascular Measures DS36: Wave V: Biomarkers, Demographics DS37: Wave V: Biomarkers, Measures of Glucose Homeostasis DS38: Wave V: Biomarkers, Measures of Inflammation and Immune Function DS39: Wave V: Biomarkers, Lipids DS40: Wave V: Biomarkers, Medication Use DS41: Wave V: Biomarkers, Renal Function DS42: Wave V: Public Use Weights Wave I: The Stage 1 in-school sample was a stratified, random sample of all high schools in the United States. A school was eligible for the sample if it included an 11th grade and had a minimum enrollment of 30 students. A feeder school -- a school that sent graduates to the high school and that included a 7th grade -- was also recruited from the community. The in-school questionnaire was administered to more than 90,000 students in grades 7 through 12. The Stage 2 in-home sample of 27,000 adolescents consisted of a core sample from each community, plus selected special over samples. Eligibility for over samples was determined by an adolescent's responses on the in-school questionnaire. Adolescents could qualify for more than one sample. Wave II: The Wave II in-home interview surveyed almost 15,000 of the same students one year after Wave I. Wave III: The in-home Wave III sample consists of over 15,000 Wave I respondents who could be located and re-interviewed six years later. Wave IV: All original Wave I in-home respondents were eligible for in-home interviews at Wave IV. At Wave IV, the Add Health sample was dispersed across the nation with respondents living in all 50 states. Administrators were able to locate 92.5% of the Wave IV sample and interviewed 80.3% of eligible sample members. Wave V: All Wave I respondents who were still living were eligible at Wave V, yielding a pool of 19,828 persons. This pool was split into three stratified random samples for the purposes of survey design testing. For additional information on sampling, including detailed information on special oversamples, please see the Add Health Study Design page. audio computer-assisted self interview (ACASI); computer-assisted personal interview (CAPI); computer-assisted self interview (CASI); face-to-face interview; mixed mode; paper and pencil interview (PAPI); telephone interviewWave V data files were minimally processed by ICPSR. For value labeling, missing value designation, and question text (where applicable), please see the available P.I. Codebook/Questionnaires. The study-level documentation (Data Guide, User Guide) does not include Wave V datasets.Documentation for Waves prior to Wave V may use an older version of the study title.Users should be aware that version history notes dated prior to 2015-11-09 do not apply to the current organization of the datasets.Please note that dates present in the Summary and Time Period fields are taken from the Add Health Study Design page. The Date of Collection field represents the range of interview dates present in the data files for each wave.Wave I and Wave II field work was conducted by the National Opinion Research Center at the University of Chicago.Wave III, Wave IV, and Wave V field work was conducted by the Research Triangle Institute.For the most updated list of related publications, please see the Add Health Publications Web site.Additional information on the National Longitudinal Study of Adolescent to Adult Health (Add Health) series can be found on the Add Health Web site. Add Health was developed in response to a mandate from the U.S. Congress to fund a study of adolescent health. Waves I and II focused on the forces that may influence adolescents' health and risk behaviors, including personal traits, families, friendships, romantic relationships, peer groups, schools, neighborhoods, and communities. As participants aged into adulthood, the scientific goals of the study expanded and evolved. Wave III explored adolescent experiences and behaviors related to decisions, behavior, and health outcomes in the transition to adulthood. Wave IV expanded to examine developmental and health trajectories across the life course of adolescence into young adulthood, using an integrative study design which combined social, behavioral, and biomedical measures data collection. Wave V aimed to track the emergence of chronic disease as the cohort aged into their 30s and early 40s. Add health is a school-based longitudinal study of a nationally-representative sample of adolescents in grates 7-12 in the United States in 1945-45. Over more than 20 years of data collection, data have been collected from adolescents, their fellow students, school administrators, parents, siblings, friends, and romantic partners through multiple data collection components. In addition, existing databases with information about respondents' neighborhoods and communities have been merged with Add Health data, including variables on income poverty, unemployment, availability and utilization of health services, crime, church membership, and social programs and policies. The data files are not weighted. However, the collection features a number of weight variables contained within the following datasets: DS4: Wave I: Public Use Grand Sample Weights DS7: Wave II: Public Use Grand Sample Weights DS18: Wave III: Public Use Education Data Weights DS19: Wave III: Add Health School Weights DS21: Wave III: Public In-Home Weights DS31: Wave IV: Public Use Weights DS42: Wave V: Public Use Weights Please note that these weights files do not apply to the Biomarker data files. For additional information on the application of weights for data analysis, please see the ICPSR User Guide, or the Guidelines for Analyzing Add Health Data. Response Rates: Response rates for each wave were as follows: Wave I: 79 percent Wave II: 88.6 percent Wave III: 77.4 percent Wave IV: 80.3 percent Wave V: 71.8 percent Adolescents in grades 7 through 12 during the 1994-1995 school year. Respondents were geographically located in the United States.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 1999 EnglishPublisher:Inter-university Consortium for Political and Social Research (ICPSR) Funded by:NIH | TRAINING IN RESEARCH ON M..., NIH | Midlife Health in Japan (..., AKA | Work stress and risk of c... +92 projectsNIH| TRAINING IN RESEARCH ON MENTAL HEALTH AND AGING ,NIH| Midlife Health in Japan (MIDJA) and the U.S. (MIDUS) ,AKA| Work stress and risk of coronary heart disease: Does a healthy life style eliminate the adverse effect? Pooled analysis of 6 major prospective cohort studies from Europe ,NHMRC| The Older Australian Twins Study (OATS) of healthy brain ageing and age-related neurocognitive disorders ,NIH| Daily Stress and Well-Being during Adulthood ,CIHR ,NIH| SOCIAL AND OCCUPATIONAL INFLUENCES ON HEALTH AND ILLNESS ,AKA| Oxygenology of soil ,NIH| Gene-Environment Interplay of Social Contexts and Aging-Related Outcomes ,NIH| Postdoctoral Training in Geriatric Psychiatry Research ,NIH| ORIGINS OF VARIANCE IN THE OLD-OLD: OCTOGENARIAN TWINS ,NIH| Self-regulation as a Health-Protective Factor in Adverse Socioeconomic Conditions ,NIH| Health behaviors over the adult lifecourse and cognitive aging ,NIH| GENETIC &ENVIRONMENTAL INFLUENCES--BIOBEHAVIORAL AGING ,NIH| Sexuality, Aging and Heart Disease: Translating from Population to Patient ,NIH| Wisconsin Longitudinal Study: Tracking the Life Course ,NIH| OLDEST-OLD MORTALITY AND DISABILITY AMONG DANISH TWINS ,NIH| Stress, Aging and Working Memory ,NIH| CONTROL BELIEFS, MEMORY, AND AGING ,NIH| Biological Embedding of Early-Life SES ,UKRI| Offshore Platform for Energy Competitiveness (OPEC) ,AKA| Genomic epidemiology of addictions and their consequences - national, Nordic and international dimensions. ,AKA| Work, well-being and health - a life course perspective: British arm of Academy of Finland consortia 10190 and 10187 / Consortium: ELRFWCDD ,AKA| Genomic epidemiology of addictions and their consequences - national, Nordic and international dimensions ,NIH| Sleep and Divorce: Identifying Bidirectional Vulnerability and Resilience ,NIH| CTSA INFRASTRUCTURE FOR CLINICAL TRIALS ,NIH| Sex differences in the relationship between APOE and AD: Role of sexual differentiation ,NIH| GENETIC AND ENVIRONMENTAL INFLUENCES IN BEHAVIORAL AGING ,NIH| SES health gradients in late life: testing models of gene-environment interplay in an international twin consortium ,NIH| Clarifying risk and protective factors for dementia with the Interplay of Genes and Environment in Multiple Studies (IGEMS) consortium ,NIH| Risk for Alzheimer's Disease and Cognitive Decline in Project TALENT ,NIH| Optimizing Couple-Oriented Interventions for Chronic Illness ,NIH| Implementing World Health Assembly Resolution 60.26 ???Workers' Health: Global Pl ,ARC| Discovery Projects - Grant ID: DP200100876 ,AKA| Center of Excellence in Complex Disease Genetics-from Discovery to Precision Medicine / Consortium: CoECDG ,NIH| Integrative Pathways to Health and Illness ,NIH| Personality and Well-Being Trajectories in Adulthood ,NIH| CHANGES IN HEALTH--SOCIOECONOMIC STATUS AND PATHWAYS ,NIH| 1995 SUMMER INSTITUTE IN GERIATRIC MEDICINE ,NIH| AGING AND INTRAINDIVIDUAL COGNITIVE VARIABILITY ,NIH| CORE--PROGRAM DEVELOPMENT ,NHMRC| Gene-environment interaction in healthy brain ageing and age related neurodegeneration ,AKA| Center of Excellence in Complex Disease Genetics ,NIH| DEMOGRAPHY ,NIH| Integrative Pathways to Health and Illness ,SSHRC ,AKA| CoE in Complex Disease Genetics ,NIH| Integrative Analysis of Change in Cognition and Health ,NIH| UCLA OLDER AMERICANS INDEPENDENCE CENTER ,NHMRC| Australian Centre of Excellence in Twin Research ,NHMRC| The genetic and environmental determinants of amyloid deposition in older individuals: an amyloid imaging study using the twin design ,NIH| The VETSA Longitudinal MRI Twin Study of Aging ,AKA| Determinants of Early Exit from Work Force: An International Multicohort Study. ,NIH| Daily stressor reactivity and profiles of physical health across adulthood ,NIH| Genes, Enivronment and the Adjustment of Family Members ,AKA| Determinants of labour market participation and prognosis of common chronic diseases in working populations: a study of cohorts in Finland, United Kingdom and France ,NSF| IBSS: Understanding Long-Term Effects on Children in Economic Distress ,AKA| Heterogeneity of depression at symptom level: Specific versus general patterns in etiology, development, and disability ,NIH| Infrastructure for the Office of Population Research ,NIH| Histories of Social Engagement and Cognitive Functioning ,NIH| Vulnerability to Drug Use & HIV: Advancing Prevention for Rural African Americans ,NIH| WISCONSIN LONGITUDINAL STUDY ,EC| ENGAGE ,NIH| The Population Research Institute ,NWO| Genetische en omgevingsinvloeden op psychopathologie en geluk tijdens de adolescentie ,NIH| TWIN STUDY OF NORMAL AGING ,AKA| Midlife predictors of dementia, frailty and disability at older ages ,NIH| A Longitudinal Twin Study of Cognition and Personality ,NIH| Biopsychosocial Pathways to Type 2 Diabetes ,NIH| Integrative Pathways to Health and Illness ,NWO| A Twin-sibling Study of Adolescent Wellness ,NIH| The VETSA Longitudinal Twin Study of Cortisol and Aging ,NIH| Informing anti-tobacco communications with affective and decision science: Application of the Appraisal Tendency Framework ,NIH| The Greatest Generation: The NAS-NRC WWII Twin Registry as a Scientific Resource ,NIH| A 55-Year Follow-up Study of Project TALENT Twins and Siblings ,AKA| Genetic and environmental predictors of tobacco, drug and alcohol addiction in adolescence and young adulthood ¿ a lifecourse twin and population approach / Consortium: addictgene ,NIH| Aging, Emotional Well-being, and Physical Health ,NIH| AGING AND HEALTH TRAJECTORIES AMONG BLACK &WHITE ADULTS ,NIH| GCRC ,NIH| MEASUREMENT OF ESTRADIOL AND OTHER RELATED HORMONES BY TANDEM MASS SPECTROSCOPY ,NIH| Social Regulation of Gene Expression ,NIH| HEALTH AND PSYCHOSOCIAL FACTORS IN OLDER BLACK TWINS ,UKRI| RootDetect: Remote Detection and Precision Management of Root Health ,NIH| A Longitudinal Twin Study of Cognition and Aging ,NIH| Social and Economic Analysis of Demographic Change ,NIH| Research Training Program in the Behavioral and Biomedical Sciences ,UKRI| Centre for Cognitive Ageing & Cognitive Epidemiology ,AKA| Determinants of labour market participation and prognosis of common chronic diseases in working populations: a study of cohorts in Finland, United Kingdom and France ,AKA| Indicators of marginalization - Role of cognition, substance use and mental health disorders: Longitudinal studies from childhood to end of adolescence ,NIH| Causal Effects of Schooling on Adult and Child Health ,NIH| Institutional Clinical and Translational Science Award ,NIH| Genetic Moderators of Divorce Adjustment: A Pilot Investigation ,NIH| Bio-social Determinants of Fertility &Related Behaviors ,NIH| IMSD Program at Wayne State University ,AKA| Predictors, neuropsychological correlates, and consequences of cannabis and alcohol use among Finnish young adults. A twin and population approachBrim, Orville Gilbert; Baltes, Paul B.; Bumpass, Larry L.; Cleary, Paul D.; Featherman, David L.; Hazzard, William R.; Kessler, Ronald C.; Lachman, Margie E.; Markus, Hazel Rose; Marmot, Michael G.; Rossi, Alice S.; Ryff, Carol D.; Shweder, Richard A.;doi: 10.3886/icpsr02760.v11 , 10.3886/icpsr02760.v1 , 10.3886/icpsr02760.v17 , 10.3886/icpsr02760.v5 , 10.3886/icpsr02760.v10 , 10.3886/icpsr02760.v19 , 10.3886/icpsr02760.v14 , 10.3886/icpsr02760.v7 , 10.3886/icpsr02760.v8 , 10.3886/icpsr02760.v16 , 10.3886/icpsr02760.v12 , 10.3886/icpsr02760.v4 , 10.3886/icpsr02760.v13 , 10.3886/icpsr02760.v6 , 10.3886/icpsr02760.v3 , 10.3886/icpsr02760.v18 , 10.3886/icpsr02760.v15 , 10.3886/icpsr02760.v2 , 10.3886/icpsr02760.v9 , 10.3886/icpsr02760
doi: 10.3886/icpsr02760.v11 , 10.3886/icpsr02760.v1 , 10.3886/icpsr02760.v17 , 10.3886/icpsr02760.v5 , 10.3886/icpsr02760.v10 , 10.3886/icpsr02760.v19 , 10.3886/icpsr02760.v14 , 10.3886/icpsr02760.v7 , 10.3886/icpsr02760.v8 , 10.3886/icpsr02760.v16 , 10.3886/icpsr02760.v12 , 10.3886/icpsr02760.v4 , 10.3886/icpsr02760.v13 , 10.3886/icpsr02760.v6 , 10.3886/icpsr02760.v3 , 10.3886/icpsr02760.v18 , 10.3886/icpsr02760.v15 , 10.3886/icpsr02760.v2 , 10.3886/icpsr02760.v9 , 10.3886/icpsr02760
The Midlife in the United States (MIDUS) is a collaborative, interdisciplinary investigation of patterns, predictors, and consequences of midlife development in the areas of physical health, psychological well-being, and social responsibility. A description of the study and findings from it are available at http://www.midus.wisc.edu. The first wave of the MIDUS study (MIDUS 1 or M1) collected survey data from a total of 7,108 participants. The baseline sample was comprised of individuals from four subsamples: (1) a national RDD (random digit dialing) sample (n=3,487); (2) oversamples from five metropolitan areas in the U.S. (n=757); (3) siblings of individuals from the RDD sample (n=950); and (4) a national RDD sample of twin pairs (n=1,914). All eligible participants were non-institutionalized, English-speaking adults in the coterminous United States, aged 25 to 74. Data from the samples were collected primarily in 1995/96. The survey (Project 1) dataset contains responses from a 30-minute Phone interview and two 50-page Self-Administered Questionnaire (SAQ) instruments. Of the 7,108 respondents who completed the Phone interview, 6,325 also completed the SAQ. This updated version of the study is comprised of three primary datasets: Dataset 1, Main, Siblings, and Twin Data, contains responses from the main survey of 7,108 respondents. Respondents were asked to provide extensive information on their physical and mental health throughout their adult lives, and to assess the ways in which their lifestyles, including relationships and work-related demands, contributed to the conditions experienced. Those queried were asked to describe their histories of physical ailments, including heart-related conditions and cancer, as well as the treatment and/or lifestyle changes they went through as a result. A series of questions addressed alcohol, tobacco, and illegal drug use, and focused on history of use, regularity of use, attempts to quit, and how the use of those substances affected respondents' physical and mental well-being. Additional questions addressed respondents' sense of control over their health, their awareness of changes in their medical conditions, commitment to regular exercise and a healthy diet, experience with menopause, the decision-making process used to deal with health concerns, experiences with nontraditional remedies or therapies, and history of attending support groups. Respondents were asked to compare their overall well-being with that of their peers and to describe social, physical, and emotional characteristics typical of adults in their 20's, 40's, and 60's. Information on the work histories of respondents and their significant others was also elicited, with items covering the nature of their occupations, work-related physical and emotional demands, and how their personal health had correlated to their jobs. An additional series of questions focusing on childhood queried respondents regarding the presence/absence of their parents, religion, rules/punishments, love/affection, physical/verbal abuse, and the quality of their relationships with their parents and siblings. Respondents were also asked to consider their personal feelings of accomplishment, desire to learn, sense of control over their lives, interests, and hopes for the future. The Datasets previously numbered 2 and 3 have been removed to avoid redundancies, and all datasets have been renumbered. Please refer to the readme file. Dataset 2, Twin Screener Data, provides the first national sample of twin pairs ascertained randomly via the telephone. Dataset 3, Coded Text Responses, describes how open-ended textual responses in the MIDUS 1 Computer-Assisted Telephone Interview (CATI) and Self-Administered Questionnaire (SAQ) were transformed into categorical numeric codes. These codes are included in a stand-alone dataset containing only those cases (N=3,950) that contained text data in their responses. Online Analysis Only: Datasets 1, 2, and 3 were merged together by the SU_ID variable to form "Merged Data with Weights (Online Analysis Only)" (Dataset 4) for online analysis capabilities. MIDUS also maintains a Colectica portal, which allows users to interact with variables across waves and create customized subsets. Registration is required. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created online analysis version with question text.; Performed recodes and/or calculated derived variables.; Checked for undocumented or out-of-range codes.. Presence of Common Scales: Generalized Anxiety Disorder (GAD) Scale; Somatic Amplification Scale; The Alcohol Screening Test; The Conflict Tactics (CT) Scales; The Revised Conflict Tactics Scales (CTS2); Loyola Generativity Scale (LGS); Many scales were constructed for use in the Midlife in the United States (MIDUS 1), 1995-1996 Study. For additional information on scale construction and sources, please refer to the scale documentation included with the data collection. Respondents were drawn from a nationally representative random-digit-dial sample of non-institutionalized, English-speaking adults, aged 25-74, selected from working telephone banks in the coterminous United States. Those queried participated in an initial telephone interview and responded to a mail questionnaire. Please see the Descriptions of Midlife in the United Sates (MIDUS) Samples documentation provided by ICPSR for more detailed information. Respondents were drawn from a nationally representative random-digit-dial sample of non-institutionalized, English-speaking adults, aged 25-74, selected from working telephone banks in the coterminous United States. Those queried participated in an initial telephone interview and responded to a mail questionnaire. Smallest Geographic Unit: None Datasets: DS0: Study-Level Files DS1: Main, Siblings and Twin Data DS2: Twin Screener Data DS3: Coded Text Data DS4: Merged Data with Weights (Online Analysis Only) DS6: Midlife in the United States (MIDUS 1), 1995-1996, Merged Data with Weights (Online Analysis Only) Response Rates: The response rate for the national Random-Digit Dialing (RDD) sample was 70 percent. The Self-Administered Questionnaire (SAQ) follow-up response rate was 89 percent. computer-assisted telephone interview (CATI) Midlife in the United States (MIDUS) Series self-enumerated questionnaire mail questionnaire
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2007 EnglishPublisher:ICPSR - Interuniversity Consortium for Political and Social Research Funded by:AKA | Social ties as predictors..., NIH | GCRC, NIH | OST DOCTORAL TRAINING IN ... +46 projectsAKA| Social ties as predictors of health behaviour and health service outcomes measured as medication adherence, avoidable secondary care and amenable mortality / Consortium: Social ties and health ,NIH| GCRC ,NIH| OST DOCTORAL TRAINING IN EMOTION RESEARCH ,NIH| Integrative Pathways to Health and Illness ,NIH| Biopsychosocial Pathways to Type 2 Diabetes ,NIH| Health Disparities Research Scholars T32 ,NIH| Aging, Emotional Well-being, and Physical Health ,EC| SOCIOGENOME ,NIH| ADMINISTRATION CORE ,NIH| CTSA INFRASTRUCTURE FOR CLINICAL TRIALS ,NIH| Aging: Sleep and Inflammatory Mechanisms in Depression Prevention ,NIH| Optimizing Couple-Oriented Interventions for Chronic Illness ,NIH| MEASUREMENT OF ESTRADIOL AND OTHER RELATED HORMONES BY TANDEM MASS SPECTROSCOPY ,WT ,NIH| UCLA OLDER AMERICANS INDEPENDENCE CENTER ,NIH| Biobehavioral Influences and the Ovarian Tumor Microenvironment ,NIH| CORE--ANIMAL CARE AND BREEDING ,NIH| TRAINING IN RESEARCH ON MENTAL HEALTH AND AGING ,NIH| Midlife Health in Japan (MIDJA) and the U.S. (MIDUS) ,NIH| POSTGRADUATE TRAINING PROGRAM IN PSYCHOEUROIMMUNOLOGY ,NIH| Late life sleep disturbances: Effects on cell stress, telomerase, inflammation ,NIH| Daily Stress and Well-Being during Adulthood ,NIH| Social Isolation and Sleep Disturance in Aging: Inflammatory Mechanisms ,NIH| Mentoring and research in patient-oriented medicine ,NIH| Biodemography of Health, Social Factors and Life Challenge ,NIH| Tai Chi Effects on Chronic Insomnia in Breast Cancer Survivors: Immune Mechanisms ,SSHRC ,NIH| UCLA Clinical and Translational Science Institute ,NIH| AGING AND INTRAINDIVIDUAL COGNITIVE VARIABILITY ,NIH| Mechanisms of Sleep Disruption Hyperalgesia ,CIHR ,NIH| Stress, Aging and Working Memory ,NIH| CONTROL BELIEFS, MEMORY, AND AGING ,NIH| Integrative Analysis of Change in Cognition and Health ,NIH| Biodemography of Health, Social Factors &Life Challenge ,UKRI| Assessment of biomedical risk factors and disease outcomes in the British 1958 cohort ,AKA| Determinants of labour market participation and prognosis of common chronic diseases in working populations: a study of cohorts in Finland, United Kingdom and France ,NIH| Training in Behavioral &Preventive Medicine ,NIH| Histories of Social Engagement and Cognitive Functioning ,NIH| Chronic Moderate Sleep Restriction in Older Long and Older Average Sleepers ,NIH| Cardiovascular Behavioral Medicine Research Training ,NIH| Infrastructure for Population Research ,NIH| Sleep, Inflamation, and Depression Occurrence in Breast Cancer Survivors ,UKRI| RootDetect: Remote Detection and Precision Management of Root Health ,NIH| Research Training in Complementary and Alternative Medicine ,NIH| IMPACT: INFLUENCING MEDIA & PUBLIC AGENDA ON CANCER & TOBACCO DISPARITIES ,NIH| EMOTIONAL REACTIVITY AND ANTERIOR BRAIN ASYMMETRY ,AKA| Determinants of labour market participation and prognosis of common chronic diseases in working populations: a study of cohorts in Finland, United Kingdom and France ,EC| EMOTION AND AGEINGRyff, Carol; Almeida, David M.; Ayanian, John; Carr, Deborah S.; Cleary, Paul D.; Coe, Christopher; Davidson, Richard; Krueger, Robert F.; Lachman, Marge E.; Marks, Nadine F.; Mroczek, Daniel K.; Seeman, Teresa; Seltzer, Marsha Mailick; Singer, Burton H.; Sloan, Richard P.; Tun, Patricia A.; Weinstein, Maxine; Williams, David;In 1995-1996, the MacArthur Midlife Research Network carried out a national survey of 7,108 Americans aged 25 to 74 (MIDLIFE IN THE UNITED STATES (MIDUS), 1995-1996 [ICPSR 2760]). The purpose of the study was to investigate the role of behavioral, psychological, and social factors in understanding age-related differences in physical and mental health. The study was innovative for its broad scientific scope, its diverse samples (which included twins and the siblings of main sample respondents), and its creative use of in-depth assessments in key areas (e.g., daily stress and cognitive functioning). A description of the study and findings from it are available at http://www.midus.wisc.edu. With support from the National Institute on Aging, a longitudinal follow-up of the original MIDUS samples: core sample (N = 3,487), metropolitan over-samples (N = 757), twins (N = 925 complete pairs), and siblings (N = 950), was conducted in 2004-2006. Guiding hypotheses for it, at the most general level, were that behavioral and psychosocial factors are consequential for physical and mental health. MIDUS II respondents were aged 35 to 86. Data collection largely repeated baseline assessments (e.g., phone interview and extensive self-administered questionnaire), with additional questions in selected areas (e.g., cognitive functioning, optimism and coping, stressful life events, and caregiving). To add refinements to MIDUS II, an African American sample (N = 592) was recruited from Milwaukee, Wisconsin, who participated in a personal interview and completed a questionnaire paralleling the above assessments. Also administered was a modified form of the mail questionnaire, via telephone, to respondents who did not complete a self-administered questionnaire. audio computer-assisted self interview (ACASI), computer-assisted personal interview (CAPI), computer-assisted telephone interview (CATI), mail questionnaire, telephone interview The data in this collection can be linked to the following MIDUS studies by using the variable M2ID: ICPSR 2760, 22840, 25281, 26841, 28683, and 29282.The missing value assignments for the following variables have been reduced from 9-10 digits in length to a maximum of 8 digits in length due to a limitation in Stata: B1SG17A, B1SG18A, B1SG18B, B1SG19A, B1SG21B, BASG22A, B1SG24A, B1SG25A, B1SG25B, B1SG25C, B1SG25D, B1SG25E, B1SG25F, B1SG25G, B1SG25H, AND B1SG25I.The DDI codebook (PDF file) and the XML file (contained in a zip package) released by ICPSR were provided by MIDUS and were not changed in any way by ICPSR. These original files do not reflect any of the processing done by ICPSR.The online analysis (SDA) file is a merged file comprised of the four datasets within this data collection. The files were merged using the variable M2ID. Users of this merged file should review the information in the "Documentation of Post-stratification Weights Created at MIDUS II," available through the ICPSR and NACDA Web sites, prior to analysis.A document pertaining to the naming conventions for this study has been added to the collection.The title of this study was changed from National Survey of Midlife Development in the United States (MIDUS II), 2004-2006, to Midlife in the United States (MIDUS 2), 2004-2006, on May 9, 2017. The respondents to this study were first interviewed as part of the NATIONAL SURVEY OF MIDLIFE DEVELOPMENT IN THE UNITED STATES (MIDUS), 1995-1996 (ICPSR 2760). MIDUS was based on a nationally representative random-digit-dial (RDD) sample of noninstitutionalized, English-speaking adults, aged 25 to 74, selected from working telephone banks in the coterminous United States. Predesignated households were selected in random replicates, one-fourth of which included a special nonrespondent incentive component. Contact persons were informed that the survey was being carried out through the Harvard Medical School and that it was designed to study health and well-being during the middle years of life. After explaining the study to the informant, a household listing was generated of people in the age range of 25 to 74, and a random respondent was selected. Oversampling of older people and men was achieved by varying the probability of carrying out the interview at this stage as a joint function of the age and sex of the randomly selected respondent. No other person in the household was selected if the respondent did not complete the interview. There was no additional sampling of cases for the longitudinal component of MIDUS II -- it was a follow-up study and attempted to recontact original MIDUS participants. More information about the MIDUS II sample can be found in the document "Descriptions of MIDUS Samples," available for download through the ICPSR and NACDA Web sites. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Standardized missing values.; Created online analysis version with question text.; Checked for undocumented or out-of-range codes.. Response Rates: Detailed information regarding the response rates for various aspects of the MIDUS II data collection is located in the following documents: "Descriptions of MIDUS Samples" and "Field Report for MIDUS II Longitudinal Sample." These documents are available for download through the ICPSR and NACDA Web sites. Presence of Common Scales: See the document "Documentation of Psychosocial Constructs and Composite Variables in MIDUS II Project 1" available through the ICPSR and NACDA Web sites for complete information regarding the scales for the MIDUS II data collection. Datasets: DS0: Study-Level Files DS1: M2_P1_Aggregate Data DS2: M2_P1_Disposition Codes DS3: M2_P1_Main Weights Data DS4: M2_P1_Coded Text Data The noninstitutionalized, English-speaking population of the United States. Midlife in the United States (MIDUS) Series
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For further information contact us at helpdesk@openaire.eu61 citations 61 popularity Top 10% influence Top 10% impulse Average Powered by BIP!more_vert Inter-university Con... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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Research data keyboard_double_arrow_right Dataset 2008 EnglishPublisher:ICPSR - Interuniversity Consortium for Political and Social Research Funded by:NIH | Training in Developmental..., ARC | Maximising knowledge from..., NIH | HIV in Young Adulthood: P... +209 projectsNIH| Training in Developmental Science to Improve Child Health and Well-Being ,ARC| Maximising knowledge from dense SNP (single nucleotide polymorphisms) data using multi-locus analysis ,NIH| HIV in Young Adulthood: Pathways and Prevention ,NIH| Neuropharmacology of Response Inhibition in Comorbid ADHD and Nicotine Dependence ,NIH| Pharmacogenetics of Nicotine Addiction Treatment ,NIH| The Collaborative Genetic Study of Nicotine Dependence ,NIH| Fine Mapping Susceptibility Loci for Nicotine Dependence ,NIH| Transitions to Adulthood and Health Risk Among U.S. Young Adults ,NIH| Adolescent Health and Academic Achievement ,NIH| Alcohol Contextual Influences: Effects on Health Disparities and Mortality ,EC| ENGAGE ,NIH| Institute for Clinical and Translational Research (UL1) ,NIH| DIETARY ETIOLOGIES OF HEART DISEASE AND CANCER ,NIH| High Risk Drug Use &HIV-Learning from the NYC Epidemic ,NIH| Inflammation Genes and Lung Cancer Risk ,EC| TODO ,NIH| Synthetic Information Systems for Better Informing Public Health Policymakers ,NSF| CAREER: Model Fluid-Solid Interactions, Networks REUs, and BioCalculus ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN CANCER ,NIH| LONGITUDINAL STUDY OF SUBSTANCE USE, INCARCERATION, AND STI IN THE US ,NIH| Center for Family and Demographic Research ,NIH| GENETIC EPIDEMIOLOGY OF LUNG CANCER ,AKA| The Cardiovascular Risk in Young Finns Study - the 27-year follow-up. ,NIH| Age at First Sex, Genes, Religion, and Other Social and Demographic Context ,NIH| Human Genetics of Addiction: A Study of Common and Specific Factors ,NIH| The effects of heavy alcohol use on weight gain in college freshmen: Examining an overlooked calorie source ,NIH| Refining Phenotypic Measures of Nicotine Withdrawal ,NIH| Phenotypic refinement of externalizing pathways to alcohol-related behaviors ,NIH| NICHD Population Center ,NIH| A Nurse-Community Health Worker-Family Partnership Model to Increase COVID-19 Testing in Urban Underserved and Vulnerable Communities ,NIH| Human Subjects Core: Protocols, Statistics, Collaborative Method Development and ,NIH| University of Washington Reproductive, Perinatal and Pediatric Epidemiology ,NIH| MDMA and Other Hallucinogen Use: Onset and Abuse/Dependence ,NIH| Mapping Genes for comorbidity of SUDs and Depression ,NIH| Epidemiology of Venous Thrombosis &Pulmonary Embolism ,NIH| CORE--ADIPOSE TISSUE BIOLOGY AND BASIC MECHANISMS ,NIH| Washington University Institute of Clinical and Translational Sciences (UL1) ,AKA| Impact of childhood growth patterns and latent cardiovascular risk factors on the microcirculation in adult life: Cardiovascular risk in Young Finns Study ,NIH| ECONOMICS OF AGING TRAINING PROGRAM -- EXTENSION ,NIH| COSTS AND BENEFITS OF ALCOHOL SERVICES &INTERVENTIONS ,NIH| The Pathobiology of Nephrolithiasis ,ARC| Locating genes for elementary and complex cognitive abilities using genetic linkage and association analysis ,NIH| The Role of Peer Networks in Youth Drug Use ,NIH| Adolescent Alcohol Use: Disentangling Friend Selection &Influence ,NIH| Nicotinic receptor genes &substance abuse: Functional studies of associated SNPs ,NIH| Dietary Etiologies of Heart Disease ,NIH| FLUORIDE AND OTHER FACTORS IN CHILDHOOD BONE DEVELOPMENT ,WT ,NIH| Consortium for Neuropsychiatric Phenomics-Coordinating Center (1 of 8) ,NIH| Sexual Behavior Trajectories from Adolescence to Adulthood ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| YOUNG ADULT SUBSTANCE USE--PREDICTORS AND CONSEQUENCES ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| Social and Demographic Context and Heritability ,NIH| BEHAVIORAL PHARMACOGENETICS OF DRUG AND ALCOHOL ABUSE ,NIH| The Genetics of Vulnerability to Nicotine Addictions ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Deciphering genes and pathways in nicotine dependence ,NIH| HEALTHY YOUTH DEVELOPMENT PREVENTION RESEARCH AND TRAINING CENTER ,NSF| Machine learning techniques to model the impact of relational communication on distributed team effectiveness ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| JH/CIDR Genotyping for Genome-Wide Association Studies ,AKA| Sustainable Innovative Materials in High Tech Applications. An Interdisciplinary Approach to Design,Engineering Technology and Chemistry of Environmentally Sound Products and Production. ,EC| ADDICTION ,NIH| Modeling HIV and STD in Drug User and Social Networks ,NIH| Economic Evaluation Methods: Development and Application ,NIH| GENETIC INTERACTIONS CONTRIBUTING TO ALCOHOL AND NICOTINE DEPENDENCE ,NIH| MOTS: Modeling Obesity Through Simulation ,NIH| GENETICS OF COCAINE DEPENDENCE ,NIH| Population Research Training ,NIH| High Density Association Analysis of Lung Cancer ,NIH| UIC Program for Interdisciplinary Careers in Womens Health Research ,NIH| GENETICS OF NICOTINE AND OTHER ABUSED SUBSTANCES ,NIH| SUBSTANCE USE AND DISORDERED WEIGHT BEHAVIORS IN SEXUAL MINORITY YOUTH CONTEXTS ,AKA| Center of Excellence in Complex Disease Genetics ,NIH| OPTIMIZING BEHAVIORAL INTERVENTIONS FOR DRUG ABUSE PREVENTION &TREATMENT ,NIH| Exome Variants Underlying Weight Gain from Adolescence to Adulthood ,NIH| Health Disparities in Obesity: Partner Violence and its Psychosocial Pathways ,NIH| Vitamin D metabolism related genetic variations and developmental origins of card ,SSHRC ,NIH| Study of Addiction: Genetics and Environment ,NIH| The Genetic Epidemiology of Nicotine Dependence ,AKA| MSDs@LIFECOURSE CONSORTIU Subproject: Shared Risk Factors Study Group Turku University Central Hospital / Consortium: MSDs@LIFE ,ARC| Quantitative and Molecular Genetic Analysis of Cognition ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Propensity Scores and Preventive Drug Use in the Elderly ,NIH| Computational Methods to Detect Epistasis ,NIH| Center on Antisocial Drug Dependence: The Genetics of HIV Risk Behaviors ,NIH| Individual differences and health outcomes: A secondary data analysis in cognitiv ,NIH| Human Development: Interdisciplinary Research Training ,NIH| Health Disparities Among a Vulnerable Population: A Longitudinal Analysis ,AKA| Role of early life risk factors in associations between work, cardiovascular disease and depression: A life course approach based on two prospective cohorts. / Consortium: ELRFWCDD ,EC| SOCIOGENOME ,NIH| Data Mgmt &Analysis Core - The NINDS International Stroke Genetics Consortium St ,NIH| Genetic Risk, Pathways to Adulthood, and Health Inequalities ,NIH| Genetic &environmental pathways to drug use, abuse &dependence ,NSF| Social Inequality and Status Attainment ,NIH| GWA for Gene-Environment Interaction Effects Influencing CHD ,NIH| Do active communities support activity or support active people? ,NSF| The Genetic Basis of Social Networks and Civic Engagement ,AKA| Roles of inflammation, oxidation, sex hormones and genetic variation in vascular aging and the development of atherosclerosis over the life-course. ,NIH| Genes, early adversity, and sensitive periods in social-emotional development ,NSF| GSE/RES Gender Differences in Science and Math: Diversity and the Role of Social Context ,NIH| Colorado Adoption/Twin Study of Lifespan behavioral development & cognitive aging (CATSLife) ,NIH| VARIATION IN THE EFFECTS OF ALCOHOL ON LIVER FUNCTION ,NSF| Science Achievement and Health Behavior: High School Curriculum, Social Context, and Opportunity to Learn ,NIH| Comprehensive Mapping of a Blood Pressure QTL on Chromosome 17 ,NIH| CUPC Admin Core ,NIH| Physical Environment Dynamics, Inequality and Obesity ,NIH| Social Support as a Facilitator of Adherence to HIV Pre-Exposure Prophylaxis Among Young MSM of Color ,NIH| Genetics of Adolescent Antisocial Drug Dependence ,NIH| PATHOLOGY MONITORING--F344 RAT COLONY ,NIH| Role of Romantic Relationships in the Sexual Behavior of Obese and Non-Obese Girl ,NIH| Statistical Methods for Network Epidemiology ,NIH| GENETICS AND CONSEQUENCES OF NICOTINE ADDICTION ,NIH| Washington University Institute of Clinical and Translational Sciences (KL2) ,CIHR ,NIH| Carolina Population Center ,NIH| Mid Southern Primary Care Networks Node ,NIH| Carolina Population Center ,NIH| SOCIAL DEMOGRAPHY ,NIH| Birth Outcomes Among Adolescents ,NIH| TRAINING GRANT IN CANCER EPIDEMIOLOGY ,NIH| Translational studies of nicotinic receptor genes: alcohol and nicotine behaviors ,NIH| Identifying essential network properties for disease spread ,NIH| Genetic Epidemiology of Lung Cancer ,NIH| Population Research Center ,EC| NBHCHOICE ,NIH| Molecular Epidemiology of Alcoholism 3 - EDAC Families ,NIH| PROSTATE, LUNG, COLORECTAL &OVARIAN CANCER ,NIH| Identifying Mediated Pathways of Risk for Substance Use in Sexual Minority Girls ,NIH| Genetic Risk to Stroke in Smokers and Nonsmokers in Two Ethnic Groups ,NIH| From GWAS loci to blood pressure genes, variants & mechanisms ,ARC| Elucidating the genetics of attention deficit hyperactivity disorder by integrating pathway and prediction analyses ,NIH| Systematic Error and Confounding: Meta-Analyses of Alcohol and Disease ,NIH| Novel Use of Gwas for Improved Understanding of Nicotine Dependence ,NIH| University of Minnesota Clinical and Translational Science Institute (UMN CTSI) ,AKA| Public Health Genomics to Practice in Cardiovascular Diseases / Consortium: PUBGENSENS ,NIH| PERSISTENCE &CHANGE IN DRINKING HABITS: TWIN STUDY ,NIH| The University of Colorado Population Center ,NIH| Childhood Family Instability, Adult Stress Reactivity, and Consequences for Health ,NIH| BEYOND RACE--EXPLAINING INEQUALITY MANIFESTED AS OBESITY ,NIH| HUMAN GENETIC VARIATION IN SMOKING AND ADDICTION RISK ,NIH| GENETICS OF ADOLESCENT ANTISOCIAL DRUG DEPENDENCE ,NIH| GENETICS OF VULNERABILITY TO NICOTINE ADDICTION ,NIH| Community Assist of Southern Arizona ,NIH| Genes and Environment Initiatives in Type 2 Diabetes ,NIH| DIET, HORMONES AND RISK OF COLORECTAL CANCERS ,NIH| PROSPECTIVE LONGITUDINAL STUDY OF ADOLESCENT HEALTH ,NIH| The Washington University Center for Diabetes Translation Research ,NIH| Variants in CHRNA5/CHRNA3/CHRNB4 and nicotine dependence ,NIH| Model-Based Clustering Methods of Medical Image ,NIH| University of Colorado Population Center ,NIH| Smoking/Nicotine Dependence in Attention Deficit Hyperactivity Disorder (ADHD) ,NIH| Molecular Genetics and Behavior: Alcohol and Tobacco Use ,WT| Familial and other risk factors for adolescent substance use and abuse. ,NIH| Stressors and their impact on health related addictions: smoking, drinking, BMI ,NSF| Neighborhoods and Schools, Education, and Heritability ,NIH| Substance Abuse & Treatment Gaps in Asians, Pacific Islanders & Multiple-race Ind ,NIH| Economic Evaluation of Adolescent Alcohol Use and the Impact of Social Networks ,NIH| Outreach Core ,NIH| Innovations in Pediatric Pain Research ,NIH| NYS FAMILY STUDY: PROBLEM ALCOHOL USE &PROBLEM BEHAVIOR ,NIH| Research Training Program in the Behavioral and Biomedical Sciences ,NIH| Obesity and Metabolic Risk Disparities: Underlying Food Environment Factors ,NIH| The Social Marginalization of Adolescents in High School ,NIH| Socioeconomic Disparities in Young Adult Health ,NIH| A Center for GEI Association Studies ,NIH| Longtudinal Relations Between Internalizing Disorders and Substance Use Problems ,NIH| Genetics of Early Onset-Stroke ,NIH| Obesity and the Environment: The Transition to Adulthood ,NIH| Mentoring Clinical Investigators in Adolescent-onset Substance Use Disorders Research ,NIH| Molecular Epidemiology of Alcoholism 2- Big Sibships ,NIH| Genome-Wide Association for Loci Influencing CHD and Other Heart, Lung and Blood ,NSF| Health Lifestyles and the Reproduction of Inequality ,NIH| Sexual Orientation and Obesity: Test of a Gendered Biopsychosocial Model ,NIH| PROSTATE, LUNG, COLORECTAL, AND OVARIAN (PLCO) CANCER ,NIH| Longitudinal Study of Trauma, HIV Risk, and Criminal Justice Involvement ,NSF| National Science Foundation Alan T. Waterman Award ,NIH| Interracial Friendship and Romance Among Adolescents ,NIH| Genetics of Opioid Dependence ,NIH| Linkage Disequilibrium Studies of Alcohol Dependence ,NIH| MECHANISMS AND PREVENTION OF ENVIRONMENTAL DISEASE ,NIH| Understanding memory consolidation by studying pharmacologically enhanced naps ,NIH| Administrative and Research Support Core ,NIH| Data Core ,NIH| Administrative Core ,NIH| Adenocarinoma of the Lung in Women ,NIH| Social Demographic Moderation of Genome Wide Associations for Body Mass Index ,NIH| Response Inhibition and Dopamine Neurotransmission (RI) (4 of 8) ,NIH| Racial disparities in cancer outcomes: quantifying modifiable mechanisms ,NIH| Research and Mentoring on Integrating Psychiatric Genetics and Neuroscience ,NIH| Cancer Center Support Grant ,NIH| The University of Iowa Prevention Research Center ,NIH| BIOBEHAVIORAL FACTORS IN CORONARY HEART DISEASE ,EC| DEPRIVEDHOODS ,NHMRC| Experience-dependent cellular plasticity and cognitive deficits in mouse models of schizophrenia ,NIH| Genes, Environments & Interventions: Understanding and Addressing Alcohol Misuse ,NIH| FINANCIAL STATUS--RETIREMENT SAVING PROGRAMS ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| NATURAL HISTORY OF ALCOHOL USE &ABUSE--GENETIC MODELS ,NIH| Genome Wide Association Coordinating Center ,NIH| Health Communication and Health Literacy Core ,NIH| Genome-Wide Associations Environmental Interactions in the Lung Health Study ,EC| GMI ,NIH| Intergenerational Research on Obesity Prevention: From Correlates to Intervention ,NIH| Genetics of Alcohol Dependence in African-Americans ,NIH| Containing Bioterroist and Emerging Infectious Diseases ,NIH| UNC Interdisciplinary Obesity Training (IDOT)(RMI) ,NIH| Population Research Institute ,EC| DYNANETS ,NIH| Statistical Methods for Gene Environment Interactions In Lung CancerAuthors: Harris, Kathleen Mullan; Udry, J. Richard;Harris, Kathleen Mullan; Udry, J. Richard;doi: 10.3886/icpsr21600.v16 , 10.3886/icpsr21600.v4 , 10.3886/icpsr21600.v6 , 10.3886/icpsr21600.v20 , 10.3886/icpsr21600.v19 , 10.3886/icpsr21600.v9 , 10.3886/icpsr21600.v15 , 10.3886/icpsr21600.v8 , 10.3886/icpsr21600.v12 , 10.3886/icpsr21600.v22 , 10.3886/icpsr21600.v14 , 10.3886/icpsr21600.v10 , 10.3886/icpsr21600.v17 , 10.3886/icpsr21600.v13 , 10.3886/icpsr21600.v11 , 10.3886/icpsr21600.v18 , 10.3886/icpsr21600.v21 , 10.3886/icpsr21600.v3 , 10.3886/icpsr21600.v1 , 10.3886/icpsr21600.v5 , 10.3886/icpsr21600.v7 , 10.3886/icpsr21600.v2
doi: 10.3886/icpsr21600.v16 , 10.3886/icpsr21600.v4 , 10.3886/icpsr21600.v6 , 10.3886/icpsr21600.v20 , 10.3886/icpsr21600.v19 , 10.3886/icpsr21600.v9 , 10.3886/icpsr21600.v15 , 10.3886/icpsr21600.v8 , 10.3886/icpsr21600.v12 , 10.3886/icpsr21600.v22 , 10.3886/icpsr21600.v14 , 10.3886/icpsr21600.v10 , 10.3886/icpsr21600.v17 , 10.3886/icpsr21600.v13 , 10.3886/icpsr21600.v11 , 10.3886/icpsr21600.v18 , 10.3886/icpsr21600.v21 , 10.3886/icpsr21600.v3 , 10.3886/icpsr21600.v1 , 10.3886/icpsr21600.v5 , 10.3886/icpsr21600.v7 , 10.3886/icpsr21600.v2
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), 1994-2008 [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). Datasets: DS0: Study-Level Files DS1: Wave I: In-Home Questionnaire, Public Use Sample DS2: Wave I: Public Use Contextual Database DS3: Wave I: Network Variables DS4: Wave I: Public Use Grand Sample Weights DS5: Wave II: In-Home Questionnaire, Public Use Sample DS6: Wave II: Public Use Contextual Database DS7: Wave II: Public Use Grand Sample Weights DS8: Wave III: In-Home Questionnaire, Public Use Sample DS9: Wave III: In-Home Questionnaire, Public Use Sample (Section 17: Relationships) DS10: Wave III: In-Home Questionnaire, Public Use Sample (Section 18: Pregnancies) DS11: Wave III: In-Home Questionnaire, Public Use Sample (Section 19: Relationships in Detail) DS12: Wave III: In-Home Questionnaire, Public Use Sample (Section 22: Completed Pregnancies) DS13: Wave III: In-Home Questionnaire, Public Use Sample (Section 23: Current Pregnancies) DS14: Wave III: In-Home Questionnaire, Public Use Sample (Section 24: Live Births) DS15: Wave III: In-Home Questionnaire, Public Use Sample (Section 25: Children and Parenting) DS16: Wave III: Public Use Education Data DS17: Wave III: Public Use Graduation Data DS18: Wave III: Public Use Education Data Weights DS19: Wave III: Add Health School Weights DS20: Wave III: Peabody Picture Vocabulary Test (PVT), Public Use DS21: Wave III: Public In-Home Weights DS22: Wave IV: In-Home Questionnaire, Public Use Sample DS23: Wave IV: In-Home Questionnaire, Public Use Sample (Section 16B: Relationships) DS24: Wave IV: In-Home Questionnaire, Public Use Sample (Section 16C: Relationships) DS25: Wave IV: In-Home Questionnaire, Public Use Sample (Section 18: Pregnancy Table) DS26: Wave IV: In-Home Questionnaire, Public Use Sample (Section 19: Live Births) DS27: Wave IV: In-Home Questionnaire, Public Use Sample (Section 20A: Children and Parenting) DS28: Wave IV: Biomarkers, Measures of Inflammation and Immune Function DS29: Wave IV: Biomarkers, Measures of Glucose Homeostasis DS30: Wave IV: Biomarkers, Lipids DS31: Wave IV: Public Use Weights Wave I: The Stage 1 in-school sample was a stratified, random sample of all high schools in the United States. A school was eligible for the sample if it included an 11th grade and had a minimum enrollment of 30 students. A feeder school -- a school that sent graduates to the high school and that included a 7th grade -- was also recruited from the community. The in-school questionnaire was administered to more than 90,000 students in grades 7 through 12. The Stage 2 in-home sample of 27,000 adolescents consisted of a core sample from each community, plus selected special over samples. Eligibility for over samples was determined by an adolescent's responses on the in-school questionnaire. Adolescents could qualify for more than one sample.; Wave II: The Wave II in-home interview surveyed almost 15,000 of the same students one year after Wave I.; Wave III: The in-home Wave III sample consists of over 15,000 Wave I respondents who could be located and re-interviewed six years later.; Wave IV: All original Wave I in-home respondents were eligible for in-home interviews at Wave IV. At Wave IV, the Add Health sample was dispersed across the nation with respondents living in all 50 states. Administrators were able to locate 92.5% of the Wave IV sample and interviewed 80.3% of eligible sample members. ; For additional information on sampling, including detailed information on special oversamples, please see the Add Health Study Design page. Add Health was developed in response to a mandate from the U.S. Congress to fund a study of adolescent health. Waves I and II focused on the forces that may influence adolescents' health and risk behaviors, including personal traits, families, friendships, romantic relationships, peer groups, schools, neighborhoods, and communities. As participants aged into adulthood, the scientific goals of the study expanded and evolved. Wave III explored adolescent experiences and behaviors related to decisions, behavior, and health outcomes in the transition to adulthood. Wave IV expanded to examine developmental and health trajectories across the life course of adolescence into young adulthood, using an integrative study design which combined social, behavioral, and biomedical measures data collection. Response Rates: Response rates for each wave were as follows: Wave I: 79 percent; Wave II: 88.6 percent; Wave III: 77.4 percent; Wave IV: 80.3 percent; Adolescents in grades 7 through 12 during the 1994-1995 school year. Respondents were geographically located in the United States. audio computer-assisted self interview (ACASI) computer-assisted personal interview (CAPI) computer-assisted self interview (CASI) paper and pencil interview (PAPI) face-to-face interview
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2008 EnglishPublisher:ICPSR - Interuniversity Consortium for Political and Social Research Funded by:WT, NIH | Population Research Train..., NIH | High Density Association ... +197 projectsWT ,NIH| Population Research Training ,NIH| High Density Association Analysis of Lung Cancer ,NIH| OPTIMIZING BEHAVIORAL INTERVENTIONS FOR DRUG ABUSE PREVENTION &TREATMENT ,NIH| GENETIC EPIDEMIOLOGY OF LUNG CANCER ,AKA| The Cardiovascular Risk in Young Finns Study - the 27-year follow-up. ,NIH| Age at First Sex, Genes, Religion, and Other Social and Demographic Context ,NIH| Human Genetics of Addiction: A Study of Common and Specific Factors ,NIH| The effects of heavy alcohol use on weight gain in college freshmen: Examining an overlooked calorie source ,NIH| Refining Phenotypic Measures of Nicotine Withdrawal ,NIH| Statistical Methods for Network Epidemiology ,NIH| GENETICS AND CONSEQUENCES OF NICOTINE ADDICTION ,NIH| Washington University Institute of Clinical and Translational Sciences (KL2) ,NIH| Alcohol Contextual Influences: Effects on Health Disparities and Mortality ,EC| ENGAGE ,NIH| Institute for Clinical and Translational Research (UL1) ,NIH| DIETARY ETIOLOGIES OF HEART DISEASE AND CANCER ,NIH| High Risk Drug Use &HIV-Learning from the NYC Epidemic ,NIH| Inflammation Genes and Lung Cancer Risk ,EC| TODO ,NSF| CAREER: Model Fluid-Solid Interactions, Networks REUs, and BioCalculus ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN CANCER ,NIH| LONGITUDINAL STUDY OF SUBSTANCE USE, INCARCERATION, AND STI IN THE US ,NIH| Identifying Mediated Pathways of Risk for Substance Use in Sexual Minority Girls ,NIH| Genetic Risk to Stroke in Smokers and Nonsmokers in Two Ethnic Groups ,NIH| From GWAS loci to blood pressure genes, variants & mechanisms ,ARC| Elucidating the genetics of attention deficit hyperactivity disorder by integrating pathway and prediction analyses ,NIH| Systematic Error and Confounding: Meta-Analyses of Alcohol and Disease ,NIH| Novel Use of Gwas for Improved Understanding of Nicotine Dependence ,NIH| University of Minnesota Clinical and Translational Science Institute (UMN CTSI) ,AKA| Public Health Genomics to Practice in Cardiovascular Diseases / Consortium: PUBGENSENS ,NIH| PERSISTENCE &CHANGE IN DRINKING HABITS: TWIN STUDY ,NIH| The University of Colorado Population Center ,NIH| HUMAN GENETIC VARIATION IN SMOKING AND ADDICTION RISK ,NIH| GENETICS OF ADOLESCENT ANTISOCIAL DRUG DEPENDENCE ,NIH| Genome-Wide Associations Environmental Interactions in the Lung Health Study ,CIHR ,EC| GMI ,NIH| Intergenerational Research on Obesity Prevention: From Correlates to Intervention ,NIH| Genetics of Alcohol Dependence in African-Americans ,NIH| Containing Bioterroist and Emerging Infectious Diseases ,NIH| UNC Interdisciplinary Obesity Training (IDOT)(RMI) ,NIH| Population Research Institute ,EC| DYNANETS ,NIH| Statistical Methods for Gene Environment Interactions In Lung Cancer ,NIH| Administrative Core ,NIH| Adenocarinoma of the Lung in Women ,NIH| Social Demographic Moderation of Genome Wide Associations for Body Mass Index ,NIH| BEYOND RACE--EXPLAINING INEQUALITY MANIFESTED AS OBESITY ,NIH| Carolina Population Center ,NIH| Mid Southern Primary Care Networks Node ,NIH| Carolina Population Center ,NIH| SOCIAL DEMOGRAPHY ,NIH| Birth Outcomes Among Adolescents ,NIH| TRAINING GRANT IN CANCER EPIDEMIOLOGY ,NIH| Translational studies of nicotinic receptor genes: alcohol and nicotine behaviors ,NIH| Identifying essential network properties for disease spread ,NIH| Genetic Epidemiology of Lung Cancer ,NIH| Study of Addiction: Genetics and Environment ,NIH| The Genetic Epidemiology of Nicotine Dependence ,AKA| MSDs@LIFECOURSE CONSORTIU Subproject: Shared Risk Factors Study Group Turku University Central Hospital / Consortium: MSDs@LIFE ,ARC| Quantitative and Molecular Genetic Analysis of Cognition ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Propensity Scores and Preventive Drug Use in the Elderly ,NIH| Response Inhibition and Dopamine Neurotransmission (RI) (4 of 8) ,NIH| Racial disparities in cancer outcomes: quantifying modifiable mechanisms ,NIH| Research and Mentoring on Integrating Psychiatric Genetics and Neuroscience ,NIH| Computational Methods to Detect Epistasis ,NIH| Center on Antisocial Drug Dependence: The Genetics of HIV Risk Behaviors ,NIH| Individual differences and health outcomes: A secondary data analysis in cognitiv ,NIH| Human Development: Interdisciplinary Research Training ,AKA| Role of early life risk factors in associations between work, cardiovascular disease and depression: A life course approach based on two prospective cohorts. / Consortium: ELRFWCDD ,EC| SOCIOGENOME ,NIH| Data Mgmt &Analysis Core - The NINDS International Stroke Genetics Consortium St ,NIH| Genetic Risk, Pathways to Adulthood, and Health Inequalities ,NIH| Genetic &environmental pathways to drug use, abuse &dependence ,NSF| Social Inequality and Status Attainment ,NIH| GWA for Gene-Environment Interaction Effects Influencing CHD ,NIH| Do active communities support activity or support active people? ,NSF| The Genetic Basis of Social Networks and Civic Engagement ,AKA| Roles of inflammation, oxidation, sex hormones and genetic variation in vascular aging and the development of atherosclerosis over the life-course. ,NIH| Genes, early adversity, and sensitive periods in social-emotional development ,NSF| GSE/RES Gender Differences in Science and Math: Diversity and the Role of Social Context ,NIH| Colorado Adoption/Twin Study of Lifespan behavioral development & cognitive aging (CATSLife) ,NIH| VARIATION IN THE EFFECTS OF ALCOHOL ON LIVER FUNCTION ,NSF| Science Achievement and Health Behavior: High School Curriculum, Social Context, and Opportunity to Learn ,NIH| Comprehensive Mapping of a Blood Pressure QTL on Chromosome 17 ,NIH| Physical Environment Dynamics, Inequality and Obesity ,NIH| Social Support as a Facilitator of Adherence to HIV Pre-Exposure Prophylaxis Among Young MSM of Color ,NIH| Genetics of Adolescent Antisocial Drug Dependence ,NIH| PATHOLOGY MONITORING--F344 RAT COLONY ,NIH| Role of Romantic Relationships in the Sexual Behavior of Obese and Non-Obese Girl ,NIH| GENETICS OF VULNERABILITY TO NICOTINE ADDICTION ,NIH| Community Assist of Southern Arizona ,NIH| Center for Family and Demographic Research ,NIH| Sexual Orientation and Obesity: Test of a Gendered Biopsychosocial Model ,NIH| PROSTATE, LUNG, COLORECTAL, AND OVARIAN (PLCO) CANCER ,NIH| Longitudinal Study of Trauma, HIV Risk, and Criminal Justice Involvement ,NSF| National Science Foundation Alan T. Waterman Award ,NIH| Interracial Friendship and Romance Among Adolescents ,NIH| Understanding memory consolidation by studying pharmacologically enhanced naps ,NIH| Administrative and Research Support Core ,NIH| Data Core ,NIH| Population Research Center ,EC| NBHCHOICE ,NIH| Molecular Epidemiology of Alcoholism 3 - EDAC Families ,NIH| PROSTATE, LUNG, COLORECTAL &OVARIAN CANCER ,NIH| NICHD Population Center ,NIH| A Nurse-Community Health Worker-Family Partnership Model to Increase COVID-19 Testing in Urban Underserved and Vulnerable Communities ,NIH| Human Subjects Core: Protocols, Statistics, Collaborative Method Development and ,NIH| University of Washington Reproductive, Perinatal and Pediatric Epidemiology ,NIH| MDMA and Other Hallucinogen Use: Onset and Abuse/Dependence ,NIH| Mapping Genes for comorbidity of SUDs and Depression ,NIH| Epidemiology of Venous Thrombosis &Pulmonary Embolism ,NIH| CORE--ADIPOSE TISSUE BIOLOGY AND BASIC MECHANISMS ,NIH| Washington University Institute of Clinical and Translational Sciences (UL1) ,AKA| Impact of childhood growth patterns and latent cardiovascular risk factors on the microcirculation in adult life: Cardiovascular risk in Young Finns Study ,NIH| ECONOMICS OF AGING TRAINING PROGRAM -- EXTENSION ,NIH| COSTS AND BENEFITS OF ALCOHOL SERVICES &INTERVENTIONS ,NIH| The Pathobiology of Nephrolithiasis ,ARC| Locating genes for elementary and complex cognitive abilities using genetic linkage and association analysis ,NIH| The Role of Peer Networks in Youth Drug Use ,NIH| Adolescent Alcohol Use: Disentangling Friend Selection &Influence ,NIH| Nicotinic receptor genes &substance abuse: Functional studies of associated SNPs ,NIH| Dietary Etiologies of Heart Disease ,NIH| FLUORIDE AND OTHER FACTORS IN CHILDHOOD BONE DEVELOPMENT ,NIH| Consortium for Neuropsychiatric Phenomics-Coordinating Center (1 of 8) ,NIH| Sexual Behavior Trajectories from Adolescence to Adulthood ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| YOUNG ADULT SUBSTANCE USE--PREDICTORS AND CONSEQUENCES ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| Deciphering genes and pathways in nicotine dependence ,NIH| Cancer Center Support Grant ,NIH| The University of Iowa Prevention Research Center ,NIH| BIOBEHAVIORAL FACTORS IN CORONARY HEART DISEASE ,NIH| Obesity and Metabolic Risk Disparities: Underlying Food Environment Factors ,EC| DEPRIVEDHOODS ,NIH| The Social Marginalization of Adolescents in High School ,NIH| Genes, Environments & Interventions: Understanding and Addressing Alcohol Misuse ,NIH| FINANCIAL STATUS--RETIREMENT SAVING PROGRAMS ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| NATURAL HISTORY OF ALCOHOL USE &ABUSE--GENETIC MODELS ,NIH| Genome Wide Association Coordinating Center ,NIH| Health Communication and Health Literacy Core ,NIH| Genetics of Opioid Dependence ,NIH| Linkage Disequilibrium Studies of Alcohol Dependence ,NIH| The Collaborative Genetic Study of Nicotine Dependence ,NIH| Fine Mapping Susceptibility Loci for Nicotine Dependence ,NIH| Adolescent Health and Academic Achievement ,NIH| HEALTHY YOUTH DEVELOPMENT PREVENTION RESEARCH AND TRAINING CENTER ,NIH| MECHANISMS AND PREVENTION OF ENVIRONMENTAL DISEASE ,NSF| Machine learning techniques to model the impact of relational communication on distributed team effectiveness ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| JH/CIDR Genotyping for Genome-Wide Association Studies ,AKA| Sustainable Innovative Materials in High Tech Applications. An Interdisciplinary Approach to Design,Engineering Technology and Chemistry of Environmentally Sound Products and Production. ,EC| ADDICTION ,NIH| Modeling HIV and STD in Drug User and Social Networks ,NIH| Economic Evaluation Methods: Development and Application ,NIH| GENETIC INTERACTIONS CONTRIBUTING TO ALCOHOL AND NICOTINE DEPENDENCE ,NIH| MOTS: Modeling Obesity Through Simulation ,NIH| GENETICS OF COCAINE DEPENDENCE ,NIH| GENETICS OF NICOTINE AND OTHER ABUSED SUBSTANCES ,NIH| SUBSTANCE USE AND DISORDERED WEIGHT BEHAVIORS IN SEXUAL MINORITY YOUTH CONTEXTS ,AKA| Center of Excellence in Complex Disease Genetics ,NIH| Exome Variants Underlying Weight Gain from Adolescence to Adulthood ,NIH| Health Disparities in Obesity: Partner Violence and its Psychosocial Pathways ,NIH| Vitamin D metabolism related genetic variations and developmental origins of card ,NIH| Training in Developmental Science to Improve Child Health and Well-Being ,ARC| Maximising knowledge from dense SNP (single nucleotide polymorphisms) data using multi-locus analysis ,NIH| HIV in Young Adulthood: Pathways and Prevention ,NIH| Neuropharmacology of Response Inhibition in Comorbid ADHD and Nicotine Dependence ,NIH| Pharmacogenetics of Nicotine Addiction Treatment ,NIH| Smoking/Nicotine Dependence in Attention Deficit Hyperactivity Disorder (ADHD) ,NIH| Molecular Genetics and Behavior: Alcohol and Tobacco Use ,WT| Familial and other risk factors for adolescent substance use and abuse. ,NIH| Stressors and their impact on health related addictions: smoking, drinking, BMI ,NSF| Neighborhoods and Schools, Education, and Heritability ,NIH| Substance Abuse & Treatment Gaps in Asians, Pacific Islanders & Multiple-race Ind ,NIH| Economic Evaluation of Adolescent Alcohol Use and the Impact of Social Networks ,NIH| Outreach Core ,NIH| NYS FAMILY STUDY: PROBLEM ALCOHOL USE &PROBLEM BEHAVIOR ,NIH| Socioeconomic Disparities in Young Adult Health ,NIH| A Center for GEI Association Studies ,NIH| Longtudinal Relations Between Internalizing Disorders and Substance Use Problems ,NIH| Genetics of Early Onset-Stroke ,NIH| Obesity and the Environment: The Transition to Adulthood ,NIH| Mentoring Clinical Investigators in Adolescent-onset Substance Use Disorders Research ,NIH| Molecular Epidemiology of Alcoholism 2- Big Sibships ,NIH| Genome-Wide Association for Loci Influencing CHD and Other Heart, Lung and Blood ,NIH| Social and Demographic Context and Heritability ,NIH| BEHAVIORAL PHARMACOGENETICS OF DRUG AND ALCOHOL ABUSE ,NIH| The Genetics of Vulnerability to Nicotine Addictions ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Genes and Environment Initiatives in Type 2 Diabetes ,NIH| DIET, HORMONES AND RISK OF COLORECTAL CANCERS ,NIH| PROSPECTIVE LONGITUDINAL STUDY OF ADOLESCENT HEALTH ,NIH| The Washington University Center for Diabetes Translation Research ,NIH| Variants in CHRNA5/CHRNA3/CHRNB4 and nicotine dependence ,NIH| Model-Based Clustering Methods of Medical Image ,SSHRCAuthors: Harris, Kathleen Mullan; Udry, J. Richard;Harris, Kathleen Mullan; Udry, J. Richard;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. Datasets: DS0: Study-Level Files DS1: Wave I: In-Home Questionnaire, Public Use Sample DS2: Wave I: Public Use Contextual Database DS3: Wave I: Network Variables DS4: Wave I: Public Use Grand Sample Weights DS5: Wave II: In-Home Questionnaire, Public Use Sample DS6: Wave II: Public Use Contextual Database DS7: Wave II: Public Use Grand Sample Weights DS8: Wave III: In-Home Questionnaire, Public Use Sample DS9: Wave III: In-Home Questionnaire, Public Use Sample (Section 17: Relationships) DS10: Wave III: In-Home Questionnaire, Public Use Sample (Section 18: Pregnancies) DS11: Wave III: In-Home Questionnaire, Public Use Sample (Section 19: Relationships in Detail) DS12: Wave III: In-Home Questionnaire, Public Use Sample (Section 22: Completed Pregnancies) DS13: Wave III: In-Home Questionnaire, Public Use Sample (Section 23: Current Pregnancies) DS14: Wave III: In-Home Questionnaire, Public Use Sample (Section 24: Live Births) DS15: Wave III: In-Home Questionnaire, Public Use Sample (Section 25: Children and Parenting) DS16: Wave III: Public Use Education Data DS17: Wave III: Public Use Graduation Data DS18: Wave III: Public Use Education Data Weights DS19: Wave III: Add Health School Weights DS20: Wave III: Peabody Picture Vocabulary Test (PVT), Public Use DS21: Wave III: Public In-Home Weights DS22: Wave IV: In-Home Questionnaire, Public Use Sample DS23: Wave IV: In-Home Questionnaire, Public Use Sample (Section 16B: Relationships) DS24: Wave IV: In-Home Questionnaire, Public Use Sample (Section 16C: Relationships) DS25: Wave IV: In-Home Questionnaire, Public Use Sample (Section 18: Pregnancy Table) DS26: Wave IV: In-Home Questionnaire, Public Use Sample (Section 19: Live Births) DS27: Wave IV: In-Home Questionnaire, Public Use Sample (Section 20A: Children and Parenting) DS28: Wave IV: Biomarkers, Measures of Inflammation and Immune Function DS29: Wave IV: Biomarkers, Measures of Glucose Homeostasis DS30: Wave IV: Biomarkers, Lipids DS31: Wave IV: Public Use Weights DS32: Wave V: Mixed-Mode Survey, Public Use Sample DS33: Wave V: Mixed-Mode Survey, Public Use Sample (Section 16B: Pregnancy, Live Births, Children and Parenting) DS34: Wave V: Biomarkers, Anthropometrics DS35: Wave V: Biomarkers, Cardiovascular Measures DS36: Wave V: Biomarkers, Demographics DS37: Wave V: Biomarkers, Measures of Glucose Homeostasis DS38: Wave V: Biomarkers, Measures of Inflammation and Immune Function DS39: Wave V: Biomarkers, Lipids DS40: Wave V: Biomarkers, Medication Use DS41: Wave V: Biomarkers, Renal Function DS42: Wave V: Public Use Weights Wave I: The Stage 1 in-school sample was a stratified, random sample of all high schools in the United States. A school was eligible for the sample if it included an 11th grade and had a minimum enrollment of 30 students. A feeder school -- a school that sent graduates to the high school and that included a 7th grade -- was also recruited from the community. The in-school questionnaire was administered to more than 90,000 students in grades 7 through 12. The Stage 2 in-home sample of 27,000 adolescents consisted of a core sample from each community, plus selected special over samples. Eligibility for over samples was determined by an adolescent's responses on the in-school questionnaire. Adolescents could qualify for more than one sample. Wave II: The Wave II in-home interview surveyed almost 15,000 of the same students one year after Wave I. Wave III: The in-home Wave III sample consists of over 15,000 Wave I respondents who could be located and re-interviewed six years later. Wave IV: All original Wave I in-home respondents were eligible for in-home interviews at Wave IV. At Wave IV, the Add Health sample was dispersed across the nation with respondents living in all 50 states. Administrators were able to locate 92.5% of the Wave IV sample and interviewed 80.3% of eligible sample members. Wave V: All Wave I respondents who were still living were eligible at Wave V, yielding a pool of 19,828 persons. This pool was split into three stratified random samples for the purposes of survey design testing. For additional information on sampling, including detailed information on special oversamples, please see the Add Health Study Design page. audio computer-assisted self interview (ACASI); computer-assisted personal interview (CAPI); computer-assisted self interview (CASI); face-to-face interview; mixed mode; paper and pencil interview (PAPI); telephone interviewWave V data files were minimally processed by ICPSR. For value labeling, missing value designation, and question text (where applicable), please see the available P.I. Codebook/Questionnaires. The study-level documentation (Data Guide, User Guide) does not include Wave V datasets.Documentation for Waves prior to Wave V may use an older version of the study title.Users should be aware that version history notes dated prior to 2015-11-09 do not apply to the current organization of the datasets.Please note that dates present in the Summary and Time Period fields are taken from the Add Health Study Design page. The Date of Collection field represents the range of interview dates present in the data files for each wave.Wave I and Wave II field work was conducted by the National Opinion Research Center at the University of Chicago.Wave III, Wave IV, and Wave V field work was conducted by the Research Triangle Institute.For the most updated list of related publications, please see the Add Health Publications Web site.Additional information on the National Longitudinal Study of Adolescent to Adult Health (Add Health) series can be found on the Add Health Web site. Add Health was developed in response to a mandate from the U.S. Congress to fund a study of adolescent health. Waves I and II focused on the forces that may influence adolescents' health and risk behaviors, including personal traits, families, friendships, romantic relationships, peer groups, schools, neighborhoods, and communities. As participants aged into adulthood, the scientific goals of the study expanded and evolved. Wave III explored adolescent experiences and behaviors related to decisions, behavior, and health outcomes in the transition to adulthood. Wave IV expanded to examine developmental and health trajectories across the life course of adolescence into young adulthood, using an integrative study design which combined social, behavioral, and biomedical measures data collection. Wave V aimed to track the emergence of chronic disease as the cohort aged into their 30s and early 40s. Add health is a school-based longitudinal study of a nationally-representative sample of adolescents in grates 7-12 in the United States in 1945-45. Over more than 20 years of data collection, data have been collected from adolescents, their fellow students, school administrators, parents, siblings, friends, and romantic partners through multiple data collection components. In addition, existing databases with information about respondents' neighborhoods and communities have been merged with Add Health data, including variables on income poverty, unemployment, availability and utilization of health services, crime, church membership, and social programs and policies. The data files are not weighted. However, the collection features a number of weight variables contained within the following datasets: DS4: Wave I: Public Use Grand Sample Weights DS7: Wave II: Public Use Grand Sample Weights DS18: Wave III: Public Use Education Data Weights DS19: Wave III: Add Health School Weights DS21: Wave III: Public In-Home Weights DS31: Wave IV: Public Use Weights DS42: Wave V: Public Use Weights Please note that these weights files do not apply to the Biomarker data files. For additional information on the application of weights for data analysis, please see the ICPSR User Guide, or the Guidelines for Analyzing Add Health Data. Response Rates: Response rates for each wave were as follows: Wave I: 79 percent Wave II: 88.6 percent Wave III: 77.4 percent Wave IV: 80.3 percent Wave V: 71.8 percent Adolescents in grades 7 through 12 during the 1994-1995 school year. Respondents were geographically located in the United States.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 1999 EnglishPublisher:Inter-university Consortium for Political and Social Research (ICPSR) Funded by:NIH | TRAINING IN RESEARCH ON M..., NIH | Midlife Health in Japan (..., AKA | Work stress and risk of c... +92 projectsNIH| TRAINING IN RESEARCH ON MENTAL HEALTH AND AGING ,NIH| Midlife Health in Japan (MIDJA) and the U.S. (MIDUS) ,AKA| Work stress and risk of coronary heart disease: Does a healthy life style eliminate the adverse effect? Pooled analysis of 6 major prospective cohort studies from Europe ,NHMRC| The Older Australian Twins Study (OATS) of healthy brain ageing and age-related neurocognitive disorders ,NIH| Daily Stress and Well-Being during Adulthood ,CIHR ,NIH| SOCIAL AND OCCUPATIONAL INFLUENCES ON HEALTH AND ILLNESS ,AKA| Oxygenology of soil ,NIH| Gene-Environment Interplay of Social Contexts and Aging-Related Outcomes ,NIH| Postdoctoral Training in Geriatric Psychiatry Research ,NIH| ORIGINS OF VARIANCE IN THE OLD-OLD: OCTOGENARIAN TWINS ,NIH| Self-regulation as a Health-Protective Factor in Adverse Socioeconomic Conditions ,NIH| Health behaviors over the adult lifecourse and cognitive aging ,NIH| GENETIC &ENVIRONMENTAL INFLUENCES--BIOBEHAVIORAL AGING ,NIH| Sexuality, Aging and Heart Disease: Translating from Population to Patient ,NIH| Wisconsin Longitudinal Study: Tracking the Life Course ,NIH| OLDEST-OLD MORTALITY AND DISABILITY AMONG DANISH TWINS ,NIH| Stress, Aging and Working Memory ,NIH| CONTROL BELIEFS, MEMORY, AND AGING ,NIH| Biological Embedding of Early-Life SES ,UKRI| Offshore Platform for Energy Competitiveness (OPEC) ,AKA| Genomic epidemiology of addictions and their consequences - national, Nordic and international dimensions. ,AKA| Work, well-being and health - a life course perspective: British arm of Academy of Finland consortia 10190 and 10187 / Consortium: ELRFWCDD ,AKA| Genomic epidemiology of addictions and their consequences - national, Nordic and international dimensions ,NIH| Sleep and Divorce: Identifying Bidirectional Vulnerability and Resilience ,NIH| CTSA INFRASTRUCTURE FOR CLINICAL TRIALS ,NIH| Sex differences in the relationship between APOE and AD: Role of sexual differentiation ,NIH| GENETIC AND ENVIRONMENTAL INFLUENCES IN BEHAVIORAL AGING ,NIH| SES health gradients in late life: testing models of gene-environment interplay in an international twin consortium ,NIH| Clarifying risk and protective factors for dementia with the Interplay of Genes and Environment in Multiple Studies (IGEMS) consortium ,NIH| Risk for Alzheimer's Disease and Cognitive Decline in Project TALENT ,NIH| Optimizing Couple-Oriented Interventions for Chronic Illness ,NIH| Implementing World Health Assembly Resolution 60.26 ???Workers' Health: Global Pl ,ARC| Discovery Projects - Grant ID: DP200100876 ,AKA| Center of Excellence in Complex Disease Genetics-from Discovery to Precision Medicine / Consortium: CoECDG ,NIH| Integrative Pathways to Health and Illness ,NIH| Personality and Well-Being Trajectories in Adulthood ,NIH| CHANGES IN HEALTH--SOCIOECONOMIC STATUS AND PATHWAYS ,NIH| 1995 SUMMER INSTITUTE IN GERIATRIC MEDICINE ,NIH| AGING AND INTRAINDIVIDUAL COGNITIVE VARIABILITY ,NIH| CORE--PROGRAM DEVELOPMENT ,NHMRC| Gene-environment interaction in healthy brain ageing and age related neurodegeneration ,AKA| Center of Excellence in Complex Disease Genetics ,NIH| DEMOGRAPHY ,NIH| Integrative Pathways to Health and Illness ,SSHRC ,AKA| CoE in Complex Disease Genetics ,NIH| Integrative Analysis of Change in Cognition and Health ,NIH| UCLA OLDER AMERICANS INDEPENDENCE CENTER ,NHMRC| Australian Centre of Excellence in Twin Research ,NHMRC| The genetic and environmental determinants of amyloid deposition in older individuals: an amyloid imaging study using the twin design ,NIH| The VETSA Longitudinal MRI Twin Study of Aging ,AKA| Determinants of Early Exit from Work Force: An International Multicohort Study. ,NIH| Daily stressor reactivity and profiles of physical health across adulthood ,NIH| Genes, Enivronment and the Adjustment of Family Members ,AKA| Determinants of labour market participation and prognosis of common chronic diseases in working populations: a study of cohorts in Finland, United Kingdom and France ,NSF| IBSS: Understanding Long-Term Effects on Children in Economic Distress ,AKA| Heterogeneity of depression at symptom level: Specific versus general patterns in etiology, development, and disability ,NIH| Infrastructure for the Office of Population Research ,NIH| Histories of Social Engagement and Cognitive Functioning ,NIH| Vulnerability to Drug Use & HIV: Advancing Prevention for Rural African Americans ,NIH| WISCONSIN LONGITUDINAL STUDY ,EC| ENGAGE ,NIH| The Population Research Institute ,NWO| Genetische en omgevingsinvloeden op psychopathologie en geluk tijdens de adolescentie ,NIH| TWIN STUDY OF NORMAL AGING ,AKA| Midlife predictors of dementia, frailty and disability at older ages ,NIH| A Longitudinal Twin Study of Cognition and Personality ,NIH| Biopsychosocial Pathways to Type 2 Diabetes ,NIH| Integrative Pathways to Health and Illness ,NWO| A Twin-sibling Study of Adolescent Wellness ,NIH| The VETSA Longitudinal Twin Study of Cortisol and Aging ,NIH| Informing anti-tobacco communications with affective and decision science: Application of the Appraisal Tendency Framework ,NIH| The Greatest Generation: The NAS-NRC WWII Twin Registry as a Scientific Resource ,NIH| A 55-Year Follow-up Study of Project TALENT Twins and Siblings ,AKA| Genetic and environmental predictors of tobacco, drug and alcohol addiction in adolescence and young adulthood ¿ a lifecourse twin and population approach / Consortium: addictgene ,NIH| Aging, Emotional Well-being, and Physical Health ,NIH| AGING AND HEALTH TRAJECTORIES AMONG BLACK &WHITE ADULTS ,NIH| GCRC ,NIH| MEASUREMENT OF ESTRADIOL AND OTHER RELATED HORMONES BY TANDEM MASS SPECTROSCOPY ,NIH| Social Regulation of Gene Expression ,NIH| HEALTH AND PSYCHOSOCIAL FACTORS IN OLDER BLACK TWINS ,UKRI| RootDetect: Remote Detection and Precision Management of Root Health ,NIH| A Longitudinal Twin Study of Cognition and Aging ,NIH| Social and Economic Analysis of Demographic Change ,NIH| Research Training Program in the Behavioral and Biomedical Sciences ,UKRI| Centre for Cognitive Ageing & Cognitive Epidemiology ,AKA| Determinants of labour market participation and prognosis of common chronic diseases in working populations: a study of cohorts in Finland, United Kingdom and France ,AKA| Indicators of marginalization - Role of cognition, substance use and mental health disorders: Longitudinal studies from childhood to end of adolescence ,NIH| Causal Effects of Schooling on Adult and Child Health ,NIH| Institutional Clinical and Translational Science Award ,NIH| Genetic Moderators of Divorce Adjustment: A Pilot Investigation ,NIH| Bio-social Determinants of Fertility &Related Behaviors ,NIH| IMSD Program at Wayne State University ,AKA| Predictors, neuropsychological correlates, and consequences of cannabis and alcohol use among Finnish young adults. A twin and population approachBrim, Orville Gilbert; Baltes, Paul B.; Bumpass, Larry L.; Cleary, Paul D.; Featherman, David L.; Hazzard, William R.; Kessler, Ronald C.; Lachman, Margie E.; Markus, Hazel Rose; Marmot, Michael G.; Rossi, Alice S.; Ryff, Carol D.; Shweder, Richard A.;doi: 10.3886/icpsr02760.v11 , 10.3886/icpsr02760.v1 , 10.3886/icpsr02760.v17 , 10.3886/icpsr02760.v5 , 10.3886/icpsr02760.v10 , 10.3886/icpsr02760.v19 , 10.3886/icpsr02760.v14 , 10.3886/icpsr02760.v7 , 10.3886/icpsr02760.v8 , 10.3886/icpsr02760.v16 , 10.3886/icpsr02760.v12 , 10.3886/icpsr02760.v4 , 10.3886/icpsr02760.v13 , 10.3886/icpsr02760.v6 , 10.3886/icpsr02760.v3 , 10.3886/icpsr02760.v18 , 10.3886/icpsr02760.v15 , 10.3886/icpsr02760.v2 , 10.3886/icpsr02760.v9 , 10.3886/icpsr02760
doi: 10.3886/icpsr02760.v11 , 10.3886/icpsr02760.v1 , 10.3886/icpsr02760.v17 , 10.3886/icpsr02760.v5 , 10.3886/icpsr02760.v10 , 10.3886/icpsr02760.v19 , 10.3886/icpsr02760.v14 , 10.3886/icpsr02760.v7 , 10.3886/icpsr02760.v8 , 10.3886/icpsr02760.v16 , 10.3886/icpsr02760.v12 , 10.3886/icpsr02760.v4 , 10.3886/icpsr02760.v13 , 10.3886/icpsr02760.v6 , 10.3886/icpsr02760.v3 , 10.3886/icpsr02760.v18 , 10.3886/icpsr02760.v15 , 10.3886/icpsr02760.v2 , 10.3886/icpsr02760.v9 , 10.3886/icpsr02760
The Midlife in the United States (MIDUS) is a collaborative, interdisciplinary investigation of patterns, predictors, and consequences of midlife development in the areas of physical health, psychological well-being, and social responsibility. A description of the study and findings from it are available at http://www.midus.wisc.edu. The first wave of the MIDUS study (MIDUS 1 or M1) collected survey data from a total of 7,108 participants. The baseline sample was comprised of individuals from four subsamples: (1) a national RDD (random digit dialing) sample (n=3,487); (2) oversamples from five metropolitan areas in the U.S. (n=757); (3) siblings of individuals from the RDD sample (n=950); and (4) a national RDD sample of twin pairs (n=1,914). All eligible participants were non-institutionalized, English-speaking adults in the coterminous United States, aged 25 to 74. Data from the samples were collected primarily in 1995/96. The survey (Project 1) dataset contains responses from a 30-minute Phone interview and two 50-page Self-Administered Questionnaire (SAQ) instruments. Of the 7,108 respondents who completed the Phone interview, 6,325 also completed the SAQ. This updated version of the study is comprised of three primary datasets: Dataset 1, Main, Siblings, and Twin Data, contains responses from the main survey of 7,108 respondents. Respondents were asked to provide extensive information on their physical and mental health throughout their adult lives, and to assess the ways in which their lifestyles, including relationships and work-related demands, contributed to the conditions experienced. Those queried were asked to describe their histories of physical ailments, including heart-related conditions and cancer, as well as the treatment and/or lifestyle changes they went through as a result. A series of questions addressed alcohol, tobacco, and illegal drug use, and focused on history of use, regularity of use, attempts to quit, and how the use of those substances affected respondents' physical and mental well-being. Additional questions addressed respondents' sense of control over their health, their awareness of changes in their medical conditions, commitment to regular exercise and a healthy diet, experience with menopause, the decision-making process used to deal with health concerns, experiences with nontraditional remedies or therapies, and history of attending support groups. Respondents were asked to compare their overall well-being with that of their peers and to describe social, physical, and emotional characteristics typical of adults in their 20's, 40's, and 60's. Information on the work histories of respondents and their significant others was also elicited, with items covering the nature of their occupations, work-related physical and emotional demands, and how their personal health had correlated to their jobs. An additional series of questions focusing on childhood queried respondents regarding the presence/absence of their parents, religion, rules/punishments, love/affection, physical/verbal abuse, and the quality of their relationships with their parents and siblings. Respondents were also asked to consider their personal feelings of accomplishment, desire to learn, sense of control over their lives, interests, and hopes for the future. The Datasets previously numbered 2 and 3 have been removed to avoid redundancies, and all datasets have been renumbered. Please refer to the readme file. Dataset 2, Twin Screener Data, provides the first national sample of twin pairs ascertained randomly via the telephone. Dataset 3, Coded Text Responses, describes how open-ended textual responses in the MIDUS 1 Computer-Assisted Telephone Interview (CATI) and Self-Administered Questionnaire (SAQ) were transformed into categorical numeric codes. These codes are included in a stand-alone dataset containing only those cases (N=3,950) that contained text data in their responses. Online Analysis Only: Datasets 1, 2, and 3 were merged together by the SU_ID variable to form "Merged Data with Weights (Online Analysis Only)" (Dataset 4) for online analysis capabilities. MIDUS also maintains a Colectica portal, which allows users to interact with variables across waves and create customized subsets. Registration is required. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created online analysis version with question text.; Performed recodes and/or calculated derived variables.; Checked for undocumented or out-of-range codes.. Presence of Common Scales: Generalized Anxiety Disorder (GAD) Scale; Somatic Amplification Scale; The Alcohol Screening Test; The Conflict Tactics (CT) Scales; The Revised Conflict Tactics Scales (CTS2); Loyola Generativity Scale (LGS); Many scales were constructed for use in the Midlife in the United States (MIDUS 1), 1995-1996 Study. For additional information on scale construction and sources, please refer to the scale documentation included with the data collection. Respondents were drawn from a nationally representative random-digit-dial sample of non-institutionalized, English-speaking adults, aged 25-74, selected from working telephone banks in the coterminous United States. Those queried participated in an initial telephone interview and responded to a mail questionnaire. Please see the Descriptions of Midlife in the United Sates (MIDUS) Samples documentation provided by ICPSR for more detailed information. Respondents were drawn from a nationally representative random-digit-dial sample of non-institutionalized, English-speaking adults, aged 25-74, selected from working telephone banks in the coterminous United States. Those queried participated in an initial telephone interview and responded to a mail questionnaire. Smallest Geographic Unit: None Datasets: DS0: Study-Level Files DS1: Main, Siblings and Twin Data DS2: Twin Screener Data DS3: Coded Text Data DS4: Merged Data with Weights (Online Analysis Only) DS6: Midlife in the United States (MIDUS 1), 1995-1996, Merged Data with Weights (Online Analysis Only) Response Rates: The response rate for the national Random-Digit Dialing (RDD) sample was 70 percent. The Self-Administered Questionnaire (SAQ) follow-up response rate was 89 percent. computer-assisted telephone interview (CATI) Midlife in the United States (MIDUS) Series self-enumerated questionnaire mail questionnaire
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2007 EnglishPublisher:ICPSR - Interuniversity Consortium for Political and Social Research Funded by:AKA | Social ties as predictors..., NIH | GCRC, NIH | OST DOCTORAL TRAINING IN ... +46 projectsAKA| Social ties as predictors of health behaviour and health service outcomes measured as medication adherence, avoidable secondary care and amenable mortality / Consortium: Social ties and health ,NIH| GCRC ,NIH| OST DOCTORAL TRAINING IN EMOTION RESEARCH ,NIH| Integrative Pathways to Health and Illness ,NIH| Biopsychosocial Pathways to Type 2 Diabetes ,NIH| Health Disparities Research Scholars T32 ,NIH| Aging, Emotional Well-being, and Physical Health ,EC| SOCIOGENOME ,NIH| ADMINISTRATION CORE ,NIH| CTSA INFRASTRUCTURE FOR CLINICAL TRIALS ,NIH| Aging: Sleep and Inflammatory Mechanisms in Depression Prevention ,NIH| Optimizing Couple-Oriented Interventions for Chronic Illness ,NIH| MEASUREMENT OF ESTRADIOL AND OTHER RELATED HORMONES BY TANDEM MASS SPECTROSCOPY ,WT ,NIH| UCLA OLDER AMERICANS INDEPENDENCE CENTER ,NIH| Biobehavioral Influences and the Ovarian Tumor Microenvironment ,NIH| CORE--ANIMAL CARE AND BREEDING ,NIH| TRAINING IN RESEARCH ON MENTAL HEALTH AND AGING ,NIH| Midlife Health in Japan (MIDJA) and the U.S. (MIDUS) ,NIH| POSTGRADUATE TRAINING PROGRAM IN PSYCHOEUROIMMUNOLOGY ,NIH| Late life sleep disturbances: Effects on cell stress, telomerase, inflammation ,NIH| Daily Stress and Well-Being during Adulthood ,NIH| Social Isolation and Sleep Disturance in Aging: Inflammatory Mechanisms ,NIH| Mentoring and research in patient-oriented medicine ,NIH| Biodemography of Health, Social Factors and Life Challenge ,NIH| Tai Chi Effects on Chronic Insomnia in Breast Cancer Survivors: Immune Mechanisms ,SSHRC ,NIH| UCLA Clinical and Translational Science Institute ,NIH| AGING AND INTRAINDIVIDUAL COGNITIVE VARIABILITY ,NIH| Mechanisms of Sleep Disruption Hyperalgesia ,CIHR ,NIH| Stress, Aging and Working Memory ,NIH| CONTROL BELIEFS, MEMORY, AND AGING ,NIH| Integrative Analysis of Change in Cognition and Health ,NIH| Biodemography of Health, Social Factors &Life Challenge ,UKRI| Assessment of biomedical risk factors and disease outcomes in the British 1958 cohort ,AKA| Determinants of labour market participation and prognosis of common chronic diseases in working populations: a study of cohorts in Finland, United Kingdom and France ,NIH| Training in Behavioral &Preventive Medicine ,NIH| Histories of Social Engagement and Cognitive Functioning ,NIH| Chronic Moderate Sleep Restriction in Older Long and Older Average Sleepers ,NIH| Cardiovascular Behavioral Medicine Research Training ,NIH| Infrastructure for Population Research ,NIH| Sleep, Inflamation, and Depression Occurrence in Breast Cancer Survivors ,UKRI| RootDetect: Remote Detection and Precision Management of Root Health ,NIH| Research Training in Complementary and Alternative Medicine ,NIH| IMPACT: INFLUENCING MEDIA & PUBLIC AGENDA ON CANCER & TOBACCO DISPARITIES ,NIH| EMOTIONAL REACTIVITY AND ANTERIOR BRAIN ASYMMETRY ,AKA| Determinants of labour market participation and prognosis of common chronic diseases in working populations: a study of cohorts in Finland, United Kingdom and France ,EC| EMOTION AND AGEINGRyff, Carol; Almeida, David M.; Ayanian, John; Carr, Deborah S.; Cleary, Paul D.; Coe, Christopher; Davidson, Richard; Krueger, Robert F.; Lachman, Marge E.; Marks, Nadine F.; Mroczek, Daniel K.; Seeman, Teresa; Seltzer, Marsha Mailick; Singer, Burton H.; Sloan, Richard P.; Tun, Patricia A.; Weinstein, Maxine; Williams, David;In 1995-1996, the MacArthur Midlife Research Network carried out a national survey of 7,108 Americans aged 25 to 74 (MIDLIFE IN THE UNITED STATES (MIDUS), 1995-1996 [ICPSR 2760]). The purpose of the study was to investigate the role of behavioral, psychological, and social factors in understanding age-related differences in physical and mental health. The study was innovative for its broad scientific scope, its diverse samples (which included twins and the siblings of main sample respondents), and its creative use of in-depth assessments in key areas (e.g., daily stress and cognitive functioning). A description of the study and findings from it are available at http://www.midus.wisc.edu. With support from the National Institute on Aging, a longitudinal follow-up of the original MIDUS samples: core sample (N = 3,487), metropolitan over-samples (N = 757), twins (N = 925 complete pairs), and siblings (N = 950), was conducted in 2004-2006. Guiding hypotheses for it, at the most general level, were that behavioral and psychosocial factors are consequential for physical and mental health. MIDUS II respondents were aged 35 to 86. Data collection largely repeated baseline assessments (e.g., phone interview and extensive self-administered questionnaire), with additional questions in selected areas (e.g., cognitive functioning, optimism and coping, stressful life events, and caregiving). To add refinements to MIDUS II, an African American sample (N = 592) was recruited from Milwaukee, Wisconsin, who participated in a personal interview and completed a questionnaire paralleling the above assessments. Also administered was a modified form of the mail questionnaire, via telephone, to respondents who did not complete a self-administered questionnaire. audio computer-assisted self interview (ACASI), computer-assisted personal interview (CAPI), computer-assisted telephone interview (CATI), mail questionnaire, telephone interview The data in this collection can be linked to the following MIDUS studies by using the variable M2ID: ICPSR 2760, 22840, 25281, 26841, 28683, and 29282.The missing value assignments for the following variables have been reduced from 9-10 digits in length to a maximum of 8 digits in length due to a limitation in Stata: B1SG17A, B1SG18A, B1SG18B, B1SG19A, B1SG21B, BASG22A, B1SG24A, B1SG25A, B1SG25B, B1SG25C, B1SG25D, B1SG25E, B1SG25F, B1SG25G, B1SG25H, AND B1SG25I.The DDI codebook (PDF file) and the XML file (contained in a zip package) released by ICPSR were provided by MIDUS and were not changed in any way by ICPSR. These original files do not reflect any of the processing done by ICPSR.The online analysis (SDA) file is a merged file comprised of the four datasets within this data collection. The files were merged using the variable M2ID. Users of this merged file should review the information in the "Documentation of Post-stratification Weights Created at MIDUS II," available through the ICPSR and NACDA Web sites, prior to analysis.A document pertaining to the naming conventions for this study has been added to the collection.The title of this study was changed from National Survey of Midlife Development in the United States (MIDUS II), 2004-2006, to Midlife in the United States (MIDUS 2), 2004-2006, on May 9, 2017. The respondents to this study were first interviewed as part of the NATIONAL SURVEY OF MIDLIFE DEVELOPMENT IN THE UNITED STATES (MIDUS), 1995-1996 (ICPSR 2760). MIDUS was based on a nationally representative random-digit-dial (RDD) sample of noninstitutionalized, English-speaking adults, aged 25 to 74, selected from working telephone banks in the coterminous United States. Predesignated households were selected in random replicates, one-fourth of which included a special nonrespondent incentive component. Contact persons were informed that the survey was being carried out through the Harvard Medical School and that it was designed to study health and well-being during the middle years of life. After explaining the study to the informant, a household listing was generated of people in the age range of 25 to 74, and a random respondent was selected. Oversampling of older people and men was achieved by varying the probability of carrying out the interview at this stage as a joint function of the age and sex of the randomly selected respondent. No other person in the household was selected if the respondent did not complete the interview. There was no additional sampling of cases for the longitudinal component of MIDUS II -- it was a follow-up study and attempted to recontact original MIDUS participants. More information about the MIDUS II sample can be found in the document "Descriptions of MIDUS Samples," available for download through the ICPSR and NACDA Web sites. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Standardized missing values.; Created online analysis version with question text.; Checked for undocumented or out-of-range codes.. Response Rates: Detailed information regarding the response rates for various aspects of the MIDUS II data collection is located in the following documents: "Descriptions of MIDUS Samples" and "Field Report for MIDUS II Longitudinal Sample." These documents are available for download through the ICPSR and NACDA Web sites. Presence of Common Scales: See the document "Documentation of Psychosocial Constructs and Composite Variables in MIDUS II Project 1" available through the ICPSR and NACDA Web sites for complete information regarding the scales for the MIDUS II data collection. Datasets: DS0: Study-Level Files DS1: M2_P1_Aggregate Data DS2: M2_P1_Disposition Codes DS3: M2_P1_Main Weights Data DS4: M2_P1_Coded Text Data The noninstitutionalized, English-speaking population of the United States. Midlife in the United States (MIDUS) Series
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For further information contact us at helpdesk@openaire.eu61 citations 61 popularity Top 10% influence Top 10% impulse Average Powered by BIP!more_vert Inter-university Con... arrow_drop_down add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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