Loading
Research data keyboard_double_arrow_right Dataset 2008 EnglishICPSR - Interuniversity Consortium for Political and Social Research NIH | The Collaborative Genetic..., NHMRC | Experience-dependent cell..., NIH | NICHD Population Center +204 projectsNIH| The Collaborative Genetic Study of Nicotine Dependence ,NHMRC| Experience-dependent cellular plasticity and cognitive deficits in mouse models of schizophrenia ,NIH| NICHD Population Center ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Statistical Methods for Network Epidemiology ,NIH| GENETIC INTERACTIONS CONTRIBUTING TO ALCOHOL AND NICOTINE DEPENDENCE ,NIH| Inflammation Genes and Lung Cancer Risk ,NIH| Economic Evaluation of Adolescent Alcohol Use and the Impact of Social Networks ,NIH| Health Disparities in Obesity: Partner Violence and its Psychosocial Pathways ,NIH| Role of Romantic Relationships in the Sexual Behavior of Obese and Non-Obese Girl ,NIH| Interracial Friendship and Romance Among Adolescents ,NIH| HEALTHY YOUTH DEVELOPMENT PREVENTION RESEARCH AND TRAINING CENTER ,NIH| Data Mgmt &Analysis Core - The NINDS International Stroke Genetics Consortium St ,NIH| A Center for GEI Association Studies ,NIH| Longtudinal Relations Between Internalizing Disorders and Substance Use Problems ,NIH| Adenocarinoma of the Lung in Women ,NSF| Neighborhoods and Schools, Education, and Heritability ,EC| TODO ,NIH| The Pathobiology of Nephrolithiasis ,NIH| Colorado Adoption/Twin Study of Lifespan behavioral development & cognitive aging (CATSLife) ,NIH| Adolescent Health and Academic Achievement ,NIH| The Social Marginalization of Adolescents in High School ,SSHRC ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Genetics of Early Onset-Stroke ,NIH| From GWAS loci to blood pressure genes, variants & mechanisms ,NIH| Containing Bioterroist and Emerging Infectious Diseases ,NIH| UNC Interdisciplinary Obesity Training (IDOT)(RMI) ,NIH| CUPC Admin Core ,NIH| Comprehensive Mapping of a Blood Pressure QTL on Chromosome 17 ,NIH| GENETICS OF ADOLESCENT ANTISOCIAL DRUG DEPENDENCE ,CIHR ,EC| DEPRIVEDHOODS ,NIH| Adolescent Alcohol Use: Disentangling Friend Selection &Influence ,NIH| Administrative and Research Support Core ,NIH| Socioeconomic Disparities in Young Adult Health ,EC| ENGAGE ,NIH| MECHANISMS AND PREVENTION OF ENVIRONMENTAL DISEASE ,NIH| PROSPECTIVE LONGITUDINAL STUDY OF ADOLESCENT HEALTH ,ARC| Elucidating the genetics of attention deficit hyperactivity disorder by integrating pathway and prediction analyses ,WT| Familial and other risk factors for adolescent substance use and abuse. ,NIH| COSTS AND BENEFITS OF ALCOHOL SERVICES &INTERVENTIONS ,NIH| Stressors and their impact on health related addictions: smoking, drinking, BMI ,NIH| Molecular Epidemiology of Alcoholism 2- Big Sibships ,NIH| Identifying essential network properties for disease spread ,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| JH/CIDR Genotyping for Genome-Wide Association Studies ,NIH| GENETICS OF COCAINE DEPENDENCE ,NIH| Research and Mentoring on Integrating Psychiatric Genetics and Neuroscience ,NIH| Translational studies of nicotinic receptor genes: alcohol and nicotine behaviors ,NIH| Human Subjects Core: Protocols, Statistics, Collaborative Method Development and ,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 ,NIH| University of Washington Reproductive, Perinatal and Pediatric Epidemiology ,NIH| MDMA and Other Hallucinogen Use: Onset and Abuse/Dependence ,NIH| Genetic Risk to Stroke in Smokers and Nonsmokers in Two Ethnic Groups ,NIH| Mapping Genes for comorbidity of SUDs and Depression ,NIH| Variants in CHRNA5/CHRNA3/CHRNB4 and nicotine dependence ,NSF| National Science Foundation Alan T. Waterman Award ,NIH| Outreach Core ,NIH| Social Support as a Facilitator of Adherence to HIV Pre-Exposure Prophylaxis Among Young MSM of Color ,NIH| Vitamin D metabolism related genetic variations and developmental origins of card ,AKA| Public Health Genomics to Practice in Cardiovascular Diseases / Consortium: PUBGENSENS ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN CANCER ,NIH| PROSTATE, LUNG, COLORECTAL &OVARIAN CANCER ,NIH| DIET, HORMONES AND RISK OF COLORECTAL CANCERS ,NIH| High Density Association Analysis of Lung Cancer ,NIH| Genetics of Alcohol Dependence in African-Americans ,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 ,EC| NBHCHOICE ,NIH| ECONOMICS OF AGING TRAINING PROGRAM -- EXTENSION ,NIH| Modeling HIV and STD in Drug User and Social Networks ,NIH| Genes, Environments & Interventions: Understanding and Addressing Alcohol Misuse ,NIH| Research Training Program in the Behavioral and Biomedical Sciences ,NIH| Computational Methods to Detect Epistasis ,NIH| Health Disparities Among a Vulnerable Population: A Longitudinal Analysis ,NIH| Population Research Center ,NIH| Carolina Population Center ,NIH| Understanding memory consolidation by studying pharmacologically enhanced naps ,NIH| Identifying Mediated Pathways of Risk for Substance Use in Sexual Minority Girls ,NIH| Genetic &environmental pathways to drug use, abuse &dependence ,NIH| The Role of Peer Networks in Youth Drug Use ,NIH| Social Demographic Moderation of Genome Wide Associations for Body Mass Index ,NIH| Age at First Sex, Genes, Religion, and Other Social and Demographic Context ,NIH| Cancer Center Support Grant ,NIH| DIETARY ETIOLOGIES OF HEART DISEASE AND CANCER ,NIH| Health Communication and Health Literacy Core ,NIH| Institute for Clinical and Translational Research (UL1) ,NIH| Study of Addiction: Genetics and Environment ,NIH| Population Research Training ,NIH| Center for Family and Demographic Research ,NIH| Genetics of Opioid Dependence ,NIH| Genetic Risk, Pathways to Adulthood, and Health Inequalities ,NIH| BEHAVIORAL PHARMACOGENETICS OF DRUG AND ALCOHOL ABUSE ,NIH| Economic Evaluation Methods: Development and Application ,NIH| Fine Mapping Susceptibility Loci for Nicotine Dependence ,NIH| Racial disparities in cancer outcomes: quantifying modifiable mechanisms ,NIH| Genetics of Adolescent Antisocial Drug Dependence ,WT ,NIH| Innovations in Pediatric Pain Research ,NIH| Phenotypic refinement of externalizing pathways to alcohol-related behaviors ,NIH| Social and Demographic Context and Heritability ,NIH| The University of Iowa Prevention Research Center ,NIH| Mentoring Clinical Investigators in Adolescent-onset Substance Use Disorders Research ,NIH| Smoking/Nicotine Dependence in Attention Deficit Hyperactivity Disorder (ADHD) ,NIH| Transitions to Adulthood and Health Risk Among U.S. Young Adults ,NIH| Response Inhibition and Dopamine Neurotransmission (RI) (4 of 8) ,AKA| Roles of inflammation, oxidation, sex hormones and genetic variation in vascular aging and the development of atherosclerosis over the life-course. ,NIH| TRAINING GRANT IN CANCER EPIDEMIOLOGY ,NIH| NYS FAMILY STUDY: PROBLEM ALCOHOL USE &PROBLEM BEHAVIOR ,NIH| Center on Antisocial Drug Dependence: The Genetics of HIV Risk Behaviors ,NIH| Administrative Core ,NIH| The Genetic Epidemiology of Nicotine Dependence ,NIH| Model-Based Clustering Methods of Medical Image ,NIH| SUBSTANCE USE AND DISORDERED WEIGHT BEHAVIORS IN SEXUAL MINORITY YOUTH CONTEXTS ,NIH| FLUORIDE AND OTHER FACTORS IN CHILDHOOD BONE DEVELOPMENT ,NIH| Pharmacogenetics of Nicotine Addiction Treatment ,NIH| Genome-Wide Associations Environmental Interactions in the Lung Health Study ,NIH| Alcohol Contextual Influences: Effects on Health Disparities and Mortality ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| Carolina Population Center ,NIH| Do active communities support activity or support active people? ,NIH| BIOBEHAVIORAL FACTORS IN CORONARY HEART DISEASE ,EC| DYNANETS ,NSF| CAREER: Model Fluid-Solid Interactions, Networks REUs, and BioCalculus ,NIH| GENETICS OF NICOTINE AND OTHER ABUSED SUBSTANCES ,NIH| GENETIC EPIDEMIOLOGY OF LUNG CANCER ,NIH| Washington University Institute of Clinical and Translational Sciences (KL2) ,NIH| Neuropharmacology of Response Inhibition in Comorbid ADHD and Nicotine Dependence ,NIH| Genome Wide Association Coordinating Center ,NIH| HIV in Young Adulthood: Pathways and Prevention ,NIH| Genes and Environment Initiatives in Type 2 Diabetes ,AKA| Sustainable Innovative Materials in High Tech Applications. An Interdisciplinary Approach to Design,Engineering Technology and Chemistry of Environmentally Sound Products and Production. ,NIH| Obesity and the Environment: The Transition to Adulthood ,NSF| Health Lifestyles and the Reproduction of Inequality ,NIH| SOCIAL DEMOGRAPHY ,NIH| MOTS: Modeling Obesity Through Simulation ,NIH| UIC Program for Interdisciplinary Careers in Womens Health Research ,NIH| Deciphering genes and pathways in nicotine dependence ,NIH| HUMAN GENETIC VARIATION IN SMOKING AND ADDICTION RISK ,NIH| The University of Colorado Population Center ,NIH| Sexual Behavior Trajectories from Adolescence to Adulthood ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| LONGITUDINAL STUDY OF SUBSTANCE USE, INCARCERATION, AND STI IN THE US ,NIH| YOUNG ADULT SUBSTANCE USE--PREDICTORS AND CONSEQUENCES ,NIH| Propensity Scores and Preventive Drug Use in the Elderly ,NIH| Population Research Institute ,NIH| Sexual Orientation and Obesity: Test of a Gendered Biopsychosocial Model ,NIH| Substance Abuse & Treatment Gaps in Asians, Pacific Islanders & Multiple-race Ind ,NIH| PERSISTENCE &CHANGE IN DRINKING HABITS: TWIN STUDY ,NSF| GSE/RES Gender Differences in Science and Math: Diversity and the Role of Social Context ,NIH| Epidemiology of Venous Thrombosis &Pulmonary Embolism ,AKA| Impact of childhood growth patterns and latent cardiovascular risk factors on the microcirculation in adult life: Cardiovascular risk in Young Finns Study ,NIH| Consortium for Neuropsychiatric Phenomics-Coordinating Center (1 of 8) ,NIH| Synthetic Information Systems for Better Informing Public Health Policymakers ,NIH| GENETICS OF VULNERABILITY TO NICOTINE ADDICTION ,NIH| Community Assist of Southern Arizona ,NIH| Training in Developmental Science to Improve Child Health and Well-Being ,NIH| Systematic Error and Confounding: Meta-Analyses of Alcohol and Disease ,NIH| GWA for Gene-Environment Interaction Effects Influencing CHD ,NIH| Longitudinal Study of Trauma, HIV Risk, and Criminal Justice Involvement ,NIH| Statistical Methods for Gene Environment Interactions In Lung Cancer ,ARC| Locating genes for elementary and complex cognitive abilities using genetic linkage and association analysis ,NIH| Molecular Epidemiology of Alcoholism 3 - EDAC Families ,NIH| Mid Southern Primary Care Networks Node ,NIH| High Risk Drug Use &HIV-Learning from the NYC Epidemic ,NSF| Science Achievement and Health Behavior: High School Curriculum, Social Context, and Opportunity to Learn ,NIH| PROSTATE, LUNG, COLORECTAL, AND OVARIAN (PLCO) CANCER ,NIH| VARIATION IN THE EFFECTS OF ALCOHOL ON LIVER FUNCTION ,NIH| Novel Use of Gwas for Improved Understanding of Nicotine Dependence ,NIH| Genes, early adversity, and sensitive periods in social-emotional development ,NIH| BEYOND RACE--EXPLAINING INEQUALITY MANIFESTED AS OBESITY ,NIH| Individual differences and health outcomes: A secondary data analysis in cognitiv ,NIH| Washington University Institute of Clinical and Translational Sciences (UL1) ,NIH| GENETICS AND CONSEQUENCES OF NICOTINE ADDICTION ,NIH| Physical Environment Dynamics, Inequality and Obesity ,NIH| Refining Phenotypic Measures of Nicotine Withdrawal ,EC| GMI ,NIH| Intergenerational Research on Obesity Prevention: From Correlates to Intervention ,NIH| Genome-Wide Association for Loci Influencing CHD and Other Heart, Lung and Blood ,NIH| Childhood Family Instability, Adult Stress Reactivity, and Consequences for Health ,NIH| Molecular Genetics and Behavior: Alcohol and Tobacco Use ,NSF| The Genetic Basis of Social Networks and Civic Engagement ,NSF| Machine learning techniques to model the impact of relational communication on distributed team effectiveness ,ARC| Maximising knowledge from dense SNP (single nucleotide polymorphisms) data using multi-locus analysis ,NIH| Nicotinic receptor genes &substance abuse: Functional studies of associated SNPs ,AKA| Center of Excellence in Complex Disease Genetics ,NIH| Data Core ,NIH| CORE--ADIPOSE TISSUE BIOLOGY AND BASIC MECHANISMS ,EC| ADDICTION ,AKA| The Cardiovascular Risk in Young Finns Study - the 27-year follow-up. ,NIH| University of Minnesota Clinical and Translational Science Institute (UMN CTSI) ,NIH| Exome Variants Underlying Weight Gain from Adolescence to Adulthood ,NIH| Obesity and Metabolic Risk Disparities: Underlying Food Environment Factors ,NIH| Genetic Epidemiology of Lung Cancer ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| PATHOLOGY MONITORING--F344 RAT COLONY ,NIH| FINANCIAL STATUS--RETIREMENT SAVING PROGRAMS ,NIH| A Nurse-Community Health Worker-Family Partnership Model to Increase COVID-19 Testing in Urban Underserved and Vulnerable Communities ,NIH| NATURAL HISTORY OF ALCOHOL USE &ABUSE--GENETIC MODELS ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| OPTIMIZING BEHAVIORAL INTERVENTIONS FOR DRUG ABUSE PREVENTION &TREATMENT ,NIH| Human Development: Interdisciplinary Research Training ,NIH| The Genetics of Vulnerability to Nicotine Addictions ,NIH| Linkage Disequilibrium Studies of Alcohol Dependence ,NIH| Birth Outcomes Among AdolescentsAuthors: Harris, Kathleen Mullan; Udry, J. Richard;Harris, Kathleen Mullan; Udry, J. Richard;doi: 10.3886/icpsr21600.v16 , 10.3886/icpsr21600.v4 , 10.3886/icpsr21600.v21 , 10.3886/icpsr21600.v15 , 10.3886/icpsr21600.v6 , 10.3886/icpsr21600.v17 , 10.3886/icpsr21600.v18 , 10.3886/icpsr21600.v20 , 10.3886/icpsr21600.v19 , 10.3886/icpsr21600.v12 , 10.3886/icpsr21600.v9 , 10.3886/icpsr21600.v22 , 10.3886/icpsr21600.v3 , 10.3886/icpsr21600.v11 , 10.3886/icpsr21600.v2 , 10.3886/icpsr21600.v14 , 10.3886/icpsr21600.v10 , 10.3886/icpsr21600.v1 , 10.3886/icpsr21600.v5 , 10.3886/icpsr21600.v8 , 10.3886/icpsr21600.v13 , 10.3886/icpsr21600.v7
doi: 10.3886/icpsr21600.v16 , 10.3886/icpsr21600.v4 , 10.3886/icpsr21600.v21 , 10.3886/icpsr21600.v15 , 10.3886/icpsr21600.v6 , 10.3886/icpsr21600.v17 , 10.3886/icpsr21600.v18 , 10.3886/icpsr21600.v20 , 10.3886/icpsr21600.v19 , 10.3886/icpsr21600.v12 , 10.3886/icpsr21600.v9 , 10.3886/icpsr21600.v22 , 10.3886/icpsr21600.v3 , 10.3886/icpsr21600.v11 , 10.3886/icpsr21600.v2 , 10.3886/icpsr21600.v14 , 10.3886/icpsr21600.v10 , 10.3886/icpsr21600.v1 , 10.3886/icpsr21600.v5 , 10.3886/icpsr21600.v8 , 10.3886/icpsr21600.v13 , 10.3886/icpsr21600.v7
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
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.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3886/icpsr21600.v16&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu65 citations 65 popularity Top 10% influence Top 10% impulse Top 10% 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.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3886/icpsr21600.v16&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019figshare SSHRC, CIHRSSHRC ,CIHRNaud, Daniel; Généreux, Mélissa; Jean-François Bruneau; Alauzet, Aline; Levasseur, Mélanie;Gender distribution by population size group. (XLSX 16 kb)
figshare 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.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.6084/m9.figshare.9641324.v1&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert figshare 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.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.6084/m9.figshare.9641324.v1&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2008 EnglishICPSR - Interuniversity Consortium for Political and Social Research NIH | Epidemiology of Venous Th..., AKA | Impact of childhood growt..., NIH | Consortium for Neuropsych... +193 projectsNIH| Epidemiology of Venous Thrombosis &Pulmonary Embolism ,AKA| Impact of childhood growth patterns and latent cardiovascular risk factors on the microcirculation in adult life: Cardiovascular risk in Young Finns Study ,NIH| Consortium for Neuropsychiatric Phenomics-Coordinating Center (1 of 8) ,NIH| JH/CIDR Genotyping for Genome-Wide Association Studies ,NIH| GENETICS OF COCAINE DEPENDENCE ,NIH| Research and Mentoring on Integrating Psychiatric Genetics and Neuroscience ,NIH| Translational studies of nicotinic receptor genes: alcohol and nicotine behaviors ,NIH| GENETICS OF VULNERABILITY TO NICOTINE ADDICTION ,NIH| Community Assist of Southern Arizona ,AKA| Public Health Genomics to Practice in Cardiovascular Diseases / Consortium: PUBGENSENS ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN CANCER ,NIH| Genetics of Early Onset-Stroke ,NIH| From GWAS loci to blood pressure genes, variants & mechanisms ,NIH| Containing Bioterroist and Emerging Infectious Diseases ,NIH| UNC Interdisciplinary Obesity Training (IDOT)(RMI) ,NIH| Comprehensive Mapping of a Blood Pressure QTL on Chromosome 17 ,NIH| GENETICS OF ADOLESCENT ANTISOCIAL DRUG DEPENDENCE ,CIHR ,NIH| Genes, Environments & Interventions: Understanding and Addressing Alcohol Misuse ,NIH| Computational Methods to Detect Epistasis ,NIH| Population Research Center ,NIH| Carolina Population Center ,NIH| Understanding memory consolidation by studying pharmacologically enhanced naps ,NIH| Social Demographic Moderation of Genome Wide Associations for Body Mass Index ,NIH| Age at First Sex, Genes, Religion, and Other Social and Demographic Context ,NIH| The Collaborative Genetic Study of Nicotine Dependence ,NIH| NICHD Population Center ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Statistical Methods for Network Epidemiology ,NIH| GENETIC INTERACTIONS CONTRIBUTING TO ALCOHOL AND NICOTINE DEPENDENCE ,NIH| Inflammation Genes and Lung Cancer Risk ,NIH| Economic Evaluation of Adolescent Alcohol Use and the Impact of Social Networks ,NIH| Health Disparities in Obesity: Partner Violence and its Psychosocial Pathways ,NIH| Role of Romantic Relationships in the Sexual Behavior of Obese and Non-Obese Girl ,NIH| Interracial Friendship and Romance Among Adolescents ,NIH| Genome-Wide Associations Environmental Interactions in the Lung Health Study ,NIH| Alcohol Contextual Influences: Effects on Health Disparities and Mortality ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| HEALTHY YOUTH DEVELOPMENT PREVENTION RESEARCH AND TRAINING CENTER ,NIH| Data Mgmt &Analysis Core - The NINDS International Stroke Genetics Consortium St ,NIH| A Center for GEI Association Studies ,NIH| Longtudinal Relations Between Internalizing Disorders and Substance Use Problems ,NIH| Adenocarinoma of the Lung in Women ,NSF| Neighborhoods and Schools, Education, and Heritability ,EC| TODO ,NIH| The Pathobiology of Nephrolithiasis ,NIH| Colorado Adoption/Twin Study of Lifespan behavioral development & cognitive aging (CATSLife) ,NIH| Carolina Population Center ,NIH| Do active communities support activity or support active people? ,NIH| Adolescent Health and Academic Achievement ,NIH| The Social Marginalization of Adolescents in High School ,NIH| BIOBEHAVIORAL FACTORS IN CORONARY HEART DISEASE ,EC| DYNANETS ,NSF| CAREER: Model Fluid-Solid Interactions, Networks REUs, and BioCalculus ,NIH| GENETICS OF NICOTINE AND OTHER ABUSED SUBSTANCES ,NIH| GENETIC EPIDEMIOLOGY OF LUNG CANCER ,NIH| Washington University Institute of Clinical and Translational Sciences (KL2) ,NIH| Neuropharmacology of Response Inhibition in Comorbid ADHD and Nicotine Dependence ,NIH| Center on Antisocial Drug Dependence: The Genetics of HIV Risk Behaviors ,NIH| Administrative Core ,NIH| The Genetic Epidemiology of Nicotine Dependence ,NIH| Model-Based Clustering Methods of Medical Image ,NIH| SUBSTANCE USE AND DISORDERED WEIGHT BEHAVIORS IN SEXUAL MINORITY YOUTH CONTEXTS ,NIH| FLUORIDE AND OTHER FACTORS IN CHILDHOOD BONE DEVELOPMENT ,NIH| Pharmacogenetics of Nicotine Addiction Treatment ,NIH| Human Subjects Core: Protocols, Statistics, Collaborative Method Development and ,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 ,NIH| University of Washington Reproductive, Perinatal and Pediatric Epidemiology ,NIH| MDMA and Other Hallucinogen Use: Onset and Abuse/Dependence ,NIH| Genetic Risk to Stroke in Smokers and Nonsmokers in Two Ethnic Groups ,NIH| Mapping Genes for comorbidity of SUDs and Depression ,NIH| Variants in CHRNA5/CHRNA3/CHRNB4 and nicotine dependence ,NSF| National Science Foundation Alan T. Waterman Award ,NIH| Outreach Core ,NIH| Social Support as a Facilitator of Adherence to HIV Pre-Exposure Prophylaxis Among Young MSM of Color ,NIH| Vitamin D metabolism related genetic variations and developmental origins of card ,NIH| PROSTATE, LUNG, COLORECTAL &OVARIAN CANCER ,NIH| Socioeconomic Disparities in Young Adult Health ,EC| ENGAGE ,NIH| MECHANISMS AND PREVENTION OF ENVIRONMENTAL DISEASE ,NIH| PROSPECTIVE LONGITUDINAL STUDY OF ADOLESCENT HEALTH ,NIH| Social and Demographic Context and Heritability ,NIH| Genome Wide Association Coordinating Center ,NIH| HIV in Young Adulthood: Pathways and Prevention ,NIH| Genes and Environment Initiatives in Type 2 Diabetes ,AKA| Sustainable Innovative Materials in High Tech Applications. An Interdisciplinary Approach to Design,Engineering Technology and Chemistry of Environmentally Sound Products and Production. ,NIH| Obesity and the Environment: The Transition to Adulthood ,ARC| Elucidating the genetics of attention deficit hyperactivity disorder by integrating pathway and prediction analyses ,WT| Familial and other risk factors for adolescent substance use and abuse. ,NIH| COSTS AND BENEFITS OF ALCOHOL SERVICES &INTERVENTIONS ,NIH| Stressors and their impact on health related addictions: smoking, drinking, BMI ,NIH| Molecular Epidemiology of Alcoholism 2- Big Sibships ,NIH| Identifying essential network properties for disease spread ,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| The University of Iowa Prevention Research Center ,NIH| Mentoring Clinical Investigators in Adolescent-onset Substance Use Disorders Research ,NIH| Smoking/Nicotine Dependence in Attention Deficit Hyperactivity Disorder (ADHD) ,WT ,SSHRC ,NIH| Molecular Genetics and Behavior: Alcohol and Tobacco Use ,NSF| The Genetic Basis of Social Networks and Civic Engagement ,NSF| Machine learning techniques to model the impact of relational communication on distributed team effectiveness ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| SOCIAL DEMOGRAPHY ,NIH| MOTS: Modeling Obesity Through Simulation ,NIH| Deciphering genes and pathways in nicotine dependence ,NIH| HUMAN GENETIC VARIATION IN SMOKING AND ADDICTION RISK ,NIH| The University of Colorado Population Center ,NIH| Sexual Behavior Trajectories from Adolescence to Adulthood ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| LONGITUDINAL STUDY OF SUBSTANCE USE, INCARCERATION, AND STI IN THE US ,NIH| YOUNG ADULT SUBSTANCE USE--PREDICTORS AND CONSEQUENCES ,NIH| Identifying Mediated Pathways of Risk for Substance Use in Sexual Minority Girls ,NIH| Genetic &environmental pathways to drug use, abuse &dependence ,NIH| The Role of Peer Networks in Youth Drug Use ,EC| GMI ,NIH| Intergenerational Research on Obesity Prevention: From Correlates to Intervention ,NIH| Genome-Wide Association for Loci Influencing CHD and Other Heart, Lung and Blood ,NIH| Longitudinal Study of Trauma, HIV Risk, and Criminal Justice Involvement ,NIH| Statistical Methods for Gene Environment Interactions In Lung Cancer ,ARC| Locating genes for elementary and complex cognitive abilities using genetic linkage and association analysis ,NIH| Molecular Epidemiology of Alcoholism 3 - EDAC Families ,NIH| FINANCIAL STATUS--RETIREMENT SAVING PROGRAMS ,NIH| A Nurse-Community Health Worker-Family Partnership Model to Increase COVID-19 Testing in Urban Underserved and Vulnerable Communities ,NIH| NATURAL HISTORY OF ALCOHOL USE &ABUSE--GENETIC MODELS ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| OPTIMIZING BEHAVIORAL INTERVENTIONS FOR DRUG ABUSE PREVENTION &TREATMENT ,NIH| Human Development: Interdisciplinary Research Training ,NIH| The Genetics of Vulnerability to Nicotine Addictions ,NIH| Linkage Disequilibrium Studies of Alcohol Dependence ,NIH| Birth Outcomes Among Adolescents ,NIH| DIET, HORMONES AND RISK OF COLORECTAL CANCERS ,NIH| High Density Association Analysis of Lung Cancer ,NIH| Genetics of Alcohol Dependence in African-Americans ,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 ,EC| NBHCHOICE ,NIH| ECONOMICS OF AGING TRAINING PROGRAM -- EXTENSION ,NIH| Modeling HIV and STD in Drug User and Social Networks ,NIH| Individual differences and health outcomes: A secondary data analysis in cognitiv ,NIH| Washington University Institute of Clinical and Translational Sciences (UL1) ,NIH| GENETICS AND CONSEQUENCES OF NICOTINE ADDICTION ,NIH| Physical Environment Dynamics, Inequality and Obesity ,NIH| Refining Phenotypic Measures of Nicotine Withdrawal ,EC| DEPRIVEDHOODS ,NIH| Adolescent Alcohol Use: Disentangling Friend Selection &Influence ,NIH| Administrative and Research Support Core ,NIH| Response Inhibition and Dopamine Neurotransmission (RI) (4 of 8) ,AKA| Roles of inflammation, oxidation, sex hormones and genetic variation in vascular aging and the development of atherosclerosis over the life-course. ,NIH| TRAINING GRANT IN CANCER EPIDEMIOLOGY ,NIH| NYS FAMILY STUDY: PROBLEM ALCOHOL USE &PROBLEM BEHAVIOR ,NIH| Training in Developmental Science to Improve Child Health and Well-Being ,NIH| Systematic Error and Confounding: Meta-Analyses of Alcohol and Disease ,NIH| GWA for Gene-Environment Interaction Effects Influencing CHD ,NIH| Propensity Scores and Preventive Drug Use in the Elderly ,NIH| Population Research Institute ,NIH| Sexual Orientation and Obesity: Test of a Gendered Biopsychosocial Model ,NIH| Substance Abuse & Treatment Gaps in Asians, Pacific Islanders & Multiple-race Ind ,NIH| PERSISTENCE &CHANGE IN DRINKING HABITS: TWIN STUDY ,NSF| GSE/RES Gender Differences in Science and Math: Diversity and the Role of Social Context ,NIH| Mid Southern Primary Care Networks Node ,NIH| High Risk Drug Use &HIV-Learning from the NYC Epidemic ,NSF| Science Achievement and Health Behavior: High School Curriculum, Social Context, and Opportunity to Learn ,NIH| PROSTATE, LUNG, COLORECTAL, AND OVARIAN (PLCO) CANCER ,NIH| VARIATION IN THE EFFECTS OF ALCOHOL ON LIVER FUNCTION ,NIH| Novel Use of Gwas for Improved Understanding of Nicotine Dependence ,NIH| Genes, early adversity, and sensitive periods in social-emotional development ,NIH| BEYOND RACE--EXPLAINING INEQUALITY MANIFESTED AS OBESITY ,NIH| CORE--ADIPOSE TISSUE BIOLOGY AND BASIC MECHANISMS ,EC| ADDICTION ,AKA| The Cardiovascular Risk in Young Finns Study - the 27-year follow-up. ,NIH| University of Minnesota Clinical and Translational Science Institute (UMN CTSI) ,NIH| Exome Variants Underlying Weight Gain from Adolescence to Adulthood ,NIH| Obesity and Metabolic Risk Disparities: Underlying Food Environment Factors ,NIH| Genetic Epidemiology of Lung Cancer ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| PATHOLOGY MONITORING--F344 RAT COLONY ,ARC| Maximising knowledge from dense SNP (single nucleotide polymorphisms) data using multi-locus analysis ,NIH| Nicotinic receptor genes &substance abuse: Functional studies of associated SNPs ,AKA| Center of Excellence in Complex Disease Genetics ,NIH| Data Core ,NIH| Cancer Center Support Grant ,NIH| DIETARY ETIOLOGIES OF HEART DISEASE AND CANCER ,NIH| Health Communication and Health Literacy Core ,NIH| Institute for Clinical and Translational Research (UL1) ,NIH| Study of Addiction: Genetics and Environment ,NIH| Population Research Training ,NIH| Center for Family and Demographic Research ,NIH| Genetics of Opioid Dependence ,NIH| Genetic Risk, Pathways to Adulthood, and Health Inequalities ,NIH| BEHAVIORAL PHARMACOGENETICS OF DRUG AND ALCOHOL ABUSE ,NIH| Economic Evaluation Methods: Development and Application ,NIH| Fine Mapping Susceptibility Loci for Nicotine Dependence ,NIH| Racial disparities in cancer outcomes: quantifying modifiable mechanisms ,NIH| Genetics of Adolescent Antisocial Drug DependenceAuthors: 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.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3886/icpsr21600.v23&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu8 citations 8 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3886/icpsr21600.v23&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019figshare SSHRC, CIHRSSHRC ,CIHRNaud, Daniel; Généreux, Mélissa; Jean-François Bruneau; Alauzet, Aline; Levasseur, Mélanie;Gender distribution by region. (XLSX 17 kb)
figshare 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.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.6084/m9.figshare.9641315.v1&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert figshare 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.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.6084/m9.figshare.9641315.v1&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu
Loading
Research data keyboard_double_arrow_right Dataset 2008 EnglishICPSR - Interuniversity Consortium for Political and Social Research NIH | The Collaborative Genetic..., NHMRC | Experience-dependent cell..., NIH | NICHD Population Center +204 projectsNIH| The Collaborative Genetic Study of Nicotine Dependence ,NHMRC| Experience-dependent cellular plasticity and cognitive deficits in mouse models of schizophrenia ,NIH| NICHD Population Center ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Statistical Methods for Network Epidemiology ,NIH| GENETIC INTERACTIONS CONTRIBUTING TO ALCOHOL AND NICOTINE DEPENDENCE ,NIH| Inflammation Genes and Lung Cancer Risk ,NIH| Economic Evaluation of Adolescent Alcohol Use and the Impact of Social Networks ,NIH| Health Disparities in Obesity: Partner Violence and its Psychosocial Pathways ,NIH| Role of Romantic Relationships in the Sexual Behavior of Obese and Non-Obese Girl ,NIH| Interracial Friendship and Romance Among Adolescents ,NIH| HEALTHY YOUTH DEVELOPMENT PREVENTION RESEARCH AND TRAINING CENTER ,NIH| Data Mgmt &Analysis Core - The NINDS International Stroke Genetics Consortium St ,NIH| A Center for GEI Association Studies ,NIH| Longtudinal Relations Between Internalizing Disorders and Substance Use Problems ,NIH| Adenocarinoma of the Lung in Women ,NSF| Neighborhoods and Schools, Education, and Heritability ,EC| TODO ,NIH| The Pathobiology of Nephrolithiasis ,NIH| Colorado Adoption/Twin Study of Lifespan behavioral development & cognitive aging (CATSLife) ,NIH| Adolescent Health and Academic Achievement ,NIH| The Social Marginalization of Adolescents in High School ,SSHRC ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Genetics of Early Onset-Stroke ,NIH| From GWAS loci to blood pressure genes, variants & mechanisms ,NIH| Containing Bioterroist and Emerging Infectious Diseases ,NIH| UNC Interdisciplinary Obesity Training (IDOT)(RMI) ,NIH| CUPC Admin Core ,NIH| Comprehensive Mapping of a Blood Pressure QTL on Chromosome 17 ,NIH| GENETICS OF ADOLESCENT ANTISOCIAL DRUG DEPENDENCE ,CIHR ,EC| DEPRIVEDHOODS ,NIH| Adolescent Alcohol Use: Disentangling Friend Selection &Influence ,NIH| Administrative and Research Support Core ,NIH| Socioeconomic Disparities in Young Adult Health ,EC| ENGAGE ,NIH| MECHANISMS AND PREVENTION OF ENVIRONMENTAL DISEASE ,NIH| PROSPECTIVE LONGITUDINAL STUDY OF ADOLESCENT HEALTH ,ARC| Elucidating the genetics of attention deficit hyperactivity disorder by integrating pathway and prediction analyses ,WT| Familial and other risk factors for adolescent substance use and abuse. ,NIH| COSTS AND BENEFITS OF ALCOHOL SERVICES &INTERVENTIONS ,NIH| Stressors and their impact on health related addictions: smoking, drinking, BMI ,NIH| Molecular Epidemiology of Alcoholism 2- Big Sibships ,NIH| Identifying essential network properties for disease spread ,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| JH/CIDR Genotyping for Genome-Wide Association Studies ,NIH| GENETICS OF COCAINE DEPENDENCE ,NIH| Research and Mentoring on Integrating Psychiatric Genetics and Neuroscience ,NIH| Translational studies of nicotinic receptor genes: alcohol and nicotine behaviors ,NIH| Human Subjects Core: Protocols, Statistics, Collaborative Method Development and ,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 ,NIH| University of Washington Reproductive, Perinatal and Pediatric Epidemiology ,NIH| MDMA and Other Hallucinogen Use: Onset and Abuse/Dependence ,NIH| Genetic Risk to Stroke in Smokers and Nonsmokers in Two Ethnic Groups ,NIH| Mapping Genes for comorbidity of SUDs and Depression ,NIH| Variants in CHRNA5/CHRNA3/CHRNB4 and nicotine dependence ,NSF| National Science Foundation Alan T. Waterman Award ,NIH| Outreach Core ,NIH| Social Support as a Facilitator of Adherence to HIV Pre-Exposure Prophylaxis Among Young MSM of Color ,NIH| Vitamin D metabolism related genetic variations and developmental origins of card ,AKA| Public Health Genomics to Practice in Cardiovascular Diseases / Consortium: PUBGENSENS ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN CANCER ,NIH| PROSTATE, LUNG, COLORECTAL &OVARIAN CANCER ,NIH| DIET, HORMONES AND RISK OF COLORECTAL CANCERS ,NIH| High Density Association Analysis of Lung Cancer ,NIH| Genetics of Alcohol Dependence in African-Americans ,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 ,EC| NBHCHOICE ,NIH| ECONOMICS OF AGING TRAINING PROGRAM -- EXTENSION ,NIH| Modeling HIV and STD in Drug User and Social Networks ,NIH| Genes, Environments & Interventions: Understanding and Addressing Alcohol Misuse ,NIH| Research Training Program in the Behavioral and Biomedical Sciences ,NIH| Computational Methods to Detect Epistasis ,NIH| Health Disparities Among a Vulnerable Population: A Longitudinal Analysis ,NIH| Population Research Center ,NIH| Carolina Population Center ,NIH| Understanding memory consolidation by studying pharmacologically enhanced naps ,NIH| Identifying Mediated Pathways of Risk for Substance Use in Sexual Minority Girls ,NIH| Genetic &environmental pathways to drug use, abuse &dependence ,NIH| The Role of Peer Networks in Youth Drug Use ,NIH| Social Demographic Moderation of Genome Wide Associations for Body Mass Index ,NIH| Age at First Sex, Genes, Religion, and Other Social and Demographic Context ,NIH| Cancer Center Support Grant ,NIH| DIETARY ETIOLOGIES OF HEART DISEASE AND CANCER ,NIH| Health Communication and Health Literacy Core ,NIH| Institute for Clinical and Translational Research (UL1) ,NIH| Study of Addiction: Genetics and Environment ,NIH| Population Research Training ,NIH| Center for Family and Demographic Research ,NIH| Genetics of Opioid Dependence ,NIH| Genetic Risk, Pathways to Adulthood, and Health Inequalities ,NIH| BEHAVIORAL PHARMACOGENETICS OF DRUG AND ALCOHOL ABUSE ,NIH| Economic Evaluation Methods: Development and Application ,NIH| Fine Mapping Susceptibility Loci for Nicotine Dependence ,NIH| Racial disparities in cancer outcomes: quantifying modifiable mechanisms ,NIH| Genetics of Adolescent Antisocial Drug Dependence ,WT ,NIH| Innovations in Pediatric Pain Research ,NIH| Phenotypic refinement of externalizing pathways to alcohol-related behaviors ,NIH| Social and Demographic Context and Heritability ,NIH| The University of Iowa Prevention Research Center ,NIH| Mentoring Clinical Investigators in Adolescent-onset Substance Use Disorders Research ,NIH| Smoking/Nicotine Dependence in Attention Deficit Hyperactivity Disorder (ADHD) ,NIH| Transitions to Adulthood and Health Risk Among U.S. Young Adults ,NIH| Response Inhibition and Dopamine Neurotransmission (RI) (4 of 8) ,AKA| Roles of inflammation, oxidation, sex hormones and genetic variation in vascular aging and the development of atherosclerosis over the life-course. ,NIH| TRAINING GRANT IN CANCER EPIDEMIOLOGY ,NIH| NYS FAMILY STUDY: PROBLEM ALCOHOL USE &PROBLEM BEHAVIOR ,NIH| Center on Antisocial Drug Dependence: The Genetics of HIV Risk Behaviors ,NIH| Administrative Core ,NIH| The Genetic Epidemiology of Nicotine Dependence ,NIH| Model-Based Clustering Methods of Medical Image ,NIH| SUBSTANCE USE AND DISORDERED WEIGHT BEHAVIORS IN SEXUAL MINORITY YOUTH CONTEXTS ,NIH| FLUORIDE AND OTHER FACTORS IN CHILDHOOD BONE DEVELOPMENT ,NIH| Pharmacogenetics of Nicotine Addiction Treatment ,NIH| Genome-Wide Associations Environmental Interactions in the Lung Health Study ,NIH| Alcohol Contextual Influences: Effects on Health Disparities and Mortality ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| Carolina Population Center ,NIH| Do active communities support activity or support active people? ,NIH| BIOBEHAVIORAL FACTORS IN CORONARY HEART DISEASE ,EC| DYNANETS ,NSF| CAREER: Model Fluid-Solid Interactions, Networks REUs, and BioCalculus ,NIH| GENETICS OF NICOTINE AND OTHER ABUSED SUBSTANCES ,NIH| GENETIC EPIDEMIOLOGY OF LUNG CANCER ,NIH| Washington University Institute of Clinical and Translational Sciences (KL2) ,NIH| Neuropharmacology of Response Inhibition in Comorbid ADHD and Nicotine Dependence ,NIH| Genome Wide Association Coordinating Center ,NIH| HIV in Young Adulthood: Pathways and Prevention ,NIH| Genes and Environment Initiatives in Type 2 Diabetes ,AKA| Sustainable Innovative Materials in High Tech Applications. An Interdisciplinary Approach to Design,Engineering Technology and Chemistry of Environmentally Sound Products and Production. ,NIH| Obesity and the Environment: The Transition to Adulthood ,NSF| Health Lifestyles and the Reproduction of Inequality ,NIH| SOCIAL DEMOGRAPHY ,NIH| MOTS: Modeling Obesity Through Simulation ,NIH| UIC Program for Interdisciplinary Careers in Womens Health Research ,NIH| Deciphering genes and pathways in nicotine dependence ,NIH| HUMAN GENETIC VARIATION IN SMOKING AND ADDICTION RISK ,NIH| The University of Colorado Population Center ,NIH| Sexual Behavior Trajectories from Adolescence to Adulthood ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| LONGITUDINAL STUDY OF SUBSTANCE USE, INCARCERATION, AND STI IN THE US ,NIH| YOUNG ADULT SUBSTANCE USE--PREDICTORS AND CONSEQUENCES ,NIH| Propensity Scores and Preventive Drug Use in the Elderly ,NIH| Population Research Institute ,NIH| Sexual Orientation and Obesity: Test of a Gendered Biopsychosocial Model ,NIH| Substance Abuse & Treatment Gaps in Asians, Pacific Islanders & Multiple-race Ind ,NIH| PERSISTENCE &CHANGE IN DRINKING HABITS: TWIN STUDY ,NSF| GSE/RES Gender Differences in Science and Math: Diversity and the Role of Social Context ,NIH| Epidemiology of Venous Thrombosis &Pulmonary Embolism ,AKA| Impact of childhood growth patterns and latent cardiovascular risk factors on the microcirculation in adult life: Cardiovascular risk in Young Finns Study ,NIH| Consortium for Neuropsychiatric Phenomics-Coordinating Center (1 of 8) ,NIH| Synthetic Information Systems for Better Informing Public Health Policymakers ,NIH| GENETICS OF VULNERABILITY TO NICOTINE ADDICTION ,NIH| Community Assist of Southern Arizona ,NIH| Training in Developmental Science to Improve Child Health and Well-Being ,NIH| Systematic Error and Confounding: Meta-Analyses of Alcohol and Disease ,NIH| GWA for Gene-Environment Interaction Effects Influencing CHD ,NIH| Longitudinal Study of Trauma, HIV Risk, and Criminal Justice Involvement ,NIH| Statistical Methods for Gene Environment Interactions In Lung Cancer ,ARC| Locating genes for elementary and complex cognitive abilities using genetic linkage and association analysis ,NIH| Molecular Epidemiology of Alcoholism 3 - EDAC Families ,NIH| Mid Southern Primary Care Networks Node ,NIH| High Risk Drug Use &HIV-Learning from the NYC Epidemic ,NSF| Science Achievement and Health Behavior: High School Curriculum, Social Context, and Opportunity to Learn ,NIH| PROSTATE, LUNG, COLORECTAL, AND OVARIAN (PLCO) CANCER ,NIH| VARIATION IN THE EFFECTS OF ALCOHOL ON LIVER FUNCTION ,NIH| Novel Use of Gwas for Improved Understanding of Nicotine Dependence ,NIH| Genes, early adversity, and sensitive periods in social-emotional development ,NIH| BEYOND RACE--EXPLAINING INEQUALITY MANIFESTED AS OBESITY ,NIH| Individual differences and health outcomes: A secondary data analysis in cognitiv ,NIH| Washington University Institute of Clinical and Translational Sciences (UL1) ,NIH| GENETICS AND CONSEQUENCES OF NICOTINE ADDICTION ,NIH| Physical Environment Dynamics, Inequality and Obesity ,NIH| Refining Phenotypic Measures of Nicotine Withdrawal ,EC| GMI ,NIH| Intergenerational Research on Obesity Prevention: From Correlates to Intervention ,NIH| Genome-Wide Association for Loci Influencing CHD and Other Heart, Lung and Blood ,NIH| Childhood Family Instability, Adult Stress Reactivity, and Consequences for Health ,NIH| Molecular Genetics and Behavior: Alcohol and Tobacco Use ,NSF| The Genetic Basis of Social Networks and Civic Engagement ,NSF| Machine learning techniques to model the impact of relational communication on distributed team effectiveness ,ARC| Maximising knowledge from dense SNP (single nucleotide polymorphisms) data using multi-locus analysis ,NIH| Nicotinic receptor genes &substance abuse: Functional studies of associated SNPs ,AKA| Center of Excellence in Complex Disease Genetics ,NIH| Data Core ,NIH| CORE--ADIPOSE TISSUE BIOLOGY AND BASIC MECHANISMS ,EC| ADDICTION ,AKA| The Cardiovascular Risk in Young Finns Study - the 27-year follow-up. ,NIH| University of Minnesota Clinical and Translational Science Institute (UMN CTSI) ,NIH| Exome Variants Underlying Weight Gain from Adolescence to Adulthood ,NIH| Obesity and Metabolic Risk Disparities: Underlying Food Environment Factors ,NIH| Genetic Epidemiology of Lung Cancer ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| PATHOLOGY MONITORING--F344 RAT COLONY ,NIH| FINANCIAL STATUS--RETIREMENT SAVING PROGRAMS ,NIH| A Nurse-Community Health Worker-Family Partnership Model to Increase COVID-19 Testing in Urban Underserved and Vulnerable Communities ,NIH| NATURAL HISTORY OF ALCOHOL USE &ABUSE--GENETIC MODELS ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| OPTIMIZING BEHAVIORAL INTERVENTIONS FOR DRUG ABUSE PREVENTION &TREATMENT ,NIH| Human Development: Interdisciplinary Research Training ,NIH| The Genetics of Vulnerability to Nicotine Addictions ,NIH| Linkage Disequilibrium Studies of Alcohol Dependence ,NIH| Birth Outcomes Among AdolescentsAuthors: Harris, Kathleen Mullan; Udry, J. Richard;Harris, Kathleen Mullan; Udry, J. Richard;doi: 10.3886/icpsr21600.v16 , 10.3886/icpsr21600.v4 , 10.3886/icpsr21600.v21 , 10.3886/icpsr21600.v15 , 10.3886/icpsr21600.v6 , 10.3886/icpsr21600.v17 , 10.3886/icpsr21600.v18 , 10.3886/icpsr21600.v20 , 10.3886/icpsr21600.v19 , 10.3886/icpsr21600.v12 , 10.3886/icpsr21600.v9 , 10.3886/icpsr21600.v22 , 10.3886/icpsr21600.v3 , 10.3886/icpsr21600.v11 , 10.3886/icpsr21600.v2 , 10.3886/icpsr21600.v14 , 10.3886/icpsr21600.v10 , 10.3886/icpsr21600.v1 , 10.3886/icpsr21600.v5 , 10.3886/icpsr21600.v8 , 10.3886/icpsr21600.v13 , 10.3886/icpsr21600.v7
doi: 10.3886/icpsr21600.v16 , 10.3886/icpsr21600.v4 , 10.3886/icpsr21600.v21 , 10.3886/icpsr21600.v15 , 10.3886/icpsr21600.v6 , 10.3886/icpsr21600.v17 , 10.3886/icpsr21600.v18 , 10.3886/icpsr21600.v20 , 10.3886/icpsr21600.v19 , 10.3886/icpsr21600.v12 , 10.3886/icpsr21600.v9 , 10.3886/icpsr21600.v22 , 10.3886/icpsr21600.v3 , 10.3886/icpsr21600.v11 , 10.3886/icpsr21600.v2 , 10.3886/icpsr21600.v14 , 10.3886/icpsr21600.v10 , 10.3886/icpsr21600.v1 , 10.3886/icpsr21600.v5 , 10.3886/icpsr21600.v8 , 10.3886/icpsr21600.v13 , 10.3886/icpsr21600.v7
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
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.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3886/icpsr21600.v16&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu65 citations 65 popularity Top 10% influence Top 10% impulse Top 10% 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.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3886/icpsr21600.v16&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019figshare SSHRC, CIHRSSHRC ,CIHRNaud, Daniel; Généreux, Mélissa; Jean-François Bruneau; Alauzet, Aline; Levasseur, Mélanie;Gender distribution by population size group. (XLSX 16 kb)
figshare 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.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.6084/m9.figshare.9641324.v1&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert figshare 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.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.6084/m9.figshare.9641324.v1&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2008 EnglishICPSR - Interuniversity Consortium for Political and Social Research NIH | Epidemiology of Venous Th..., AKA | Impact of childhood growt..., NIH | Consortium for Neuropsych... +193 projectsNIH| Epidemiology of Venous Thrombosis &Pulmonary Embolism ,AKA| Impact of childhood growth patterns and latent cardiovascular risk factors on the microcirculation in adult life: Cardiovascular risk in Young Finns Study ,NIH| Consortium for Neuropsychiatric Phenomics-Coordinating Center (1 of 8) ,NIH| JH/CIDR Genotyping for Genome-Wide Association Studies ,NIH| GENETICS OF COCAINE DEPENDENCE ,NIH| Research and Mentoring on Integrating Psychiatric Genetics and Neuroscience ,NIH| Translational studies of nicotinic receptor genes: alcohol and nicotine behaviors ,NIH| GENETICS OF VULNERABILITY TO NICOTINE ADDICTION ,NIH| Community Assist of Southern Arizona ,AKA| Public Health Genomics to Practice in Cardiovascular Diseases / Consortium: PUBGENSENS ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN CANCER ,NIH| Genetics of Early Onset-Stroke ,NIH| From GWAS loci to blood pressure genes, variants & mechanisms ,NIH| Containing Bioterroist and Emerging Infectious Diseases ,NIH| UNC Interdisciplinary Obesity Training (IDOT)(RMI) ,NIH| Comprehensive Mapping of a Blood Pressure QTL on Chromosome 17 ,NIH| GENETICS OF ADOLESCENT ANTISOCIAL DRUG DEPENDENCE ,CIHR ,NIH| Genes, Environments & Interventions: Understanding and Addressing Alcohol Misuse ,NIH| Computational Methods to Detect Epistasis ,NIH| Population Research Center ,NIH| Carolina Population Center ,NIH| Understanding memory consolidation by studying pharmacologically enhanced naps ,NIH| Social Demographic Moderation of Genome Wide Associations for Body Mass Index ,NIH| Age at First Sex, Genes, Religion, and Other Social and Demographic Context ,NIH| The Collaborative Genetic Study of Nicotine Dependence ,NIH| NICHD Population Center ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| Statistical Methods for Network Epidemiology ,NIH| GENETIC INTERACTIONS CONTRIBUTING TO ALCOHOL AND NICOTINE DEPENDENCE ,NIH| Inflammation Genes and Lung Cancer Risk ,NIH| Economic Evaluation of Adolescent Alcohol Use and the Impact of Social Networks ,NIH| Health Disparities in Obesity: Partner Violence and its Psychosocial Pathways ,NIH| Role of Romantic Relationships in the Sexual Behavior of Obese and Non-Obese Girl ,NIH| Interracial Friendship and Romance Among Adolescents ,NIH| Genome-Wide Associations Environmental Interactions in the Lung Health Study ,NIH| Alcohol Contextual Influences: Effects on Health Disparities and Mortality ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| HEALTHY YOUTH DEVELOPMENT PREVENTION RESEARCH AND TRAINING CENTER ,NIH| Data Mgmt &Analysis Core - The NINDS International Stroke Genetics Consortium St ,NIH| A Center for GEI Association Studies ,NIH| Longtudinal Relations Between Internalizing Disorders and Substance Use Problems ,NIH| Adenocarinoma of the Lung in Women ,NSF| Neighborhoods and Schools, Education, and Heritability ,EC| TODO ,NIH| The Pathobiology of Nephrolithiasis ,NIH| Colorado Adoption/Twin Study of Lifespan behavioral development & cognitive aging (CATSLife) ,NIH| Carolina Population Center ,NIH| Do active communities support activity or support active people? ,NIH| Adolescent Health and Academic Achievement ,NIH| The Social Marginalization of Adolescents in High School ,NIH| BIOBEHAVIORAL FACTORS IN CORONARY HEART DISEASE ,EC| DYNANETS ,NSF| CAREER: Model Fluid-Solid Interactions, Networks REUs, and BioCalculus ,NIH| GENETICS OF NICOTINE AND OTHER ABUSED SUBSTANCES ,NIH| GENETIC EPIDEMIOLOGY OF LUNG CANCER ,NIH| Washington University Institute of Clinical and Translational Sciences (KL2) ,NIH| Neuropharmacology of Response Inhibition in Comorbid ADHD and Nicotine Dependence ,NIH| Center on Antisocial Drug Dependence: The Genetics of HIV Risk Behaviors ,NIH| Administrative Core ,NIH| The Genetic Epidemiology of Nicotine Dependence ,NIH| Model-Based Clustering Methods of Medical Image ,NIH| SUBSTANCE USE AND DISORDERED WEIGHT BEHAVIORS IN SEXUAL MINORITY YOUTH CONTEXTS ,NIH| FLUORIDE AND OTHER FACTORS IN CHILDHOOD BONE DEVELOPMENT ,NIH| Pharmacogenetics of Nicotine Addiction Treatment ,NIH| Human Subjects Core: Protocols, Statistics, Collaborative Method Development and ,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 ,NIH| University of Washington Reproductive, Perinatal and Pediatric Epidemiology ,NIH| MDMA and Other Hallucinogen Use: Onset and Abuse/Dependence ,NIH| Genetic Risk to Stroke in Smokers and Nonsmokers in Two Ethnic Groups ,NIH| Mapping Genes for comorbidity of SUDs and Depression ,NIH| Variants in CHRNA5/CHRNA3/CHRNB4 and nicotine dependence ,NSF| National Science Foundation Alan T. Waterman Award ,NIH| Outreach Core ,NIH| Social Support as a Facilitator of Adherence to HIV Pre-Exposure Prophylaxis Among Young MSM of Color ,NIH| Vitamin D metabolism related genetic variations and developmental origins of card ,NIH| PROSTATE, LUNG, COLORECTAL &OVARIAN CANCER ,NIH| Socioeconomic Disparities in Young Adult Health ,EC| ENGAGE ,NIH| MECHANISMS AND PREVENTION OF ENVIRONMENTAL DISEASE ,NIH| PROSPECTIVE LONGITUDINAL STUDY OF ADOLESCENT HEALTH ,NIH| Social and Demographic Context and Heritability ,NIH| Genome Wide Association Coordinating Center ,NIH| HIV in Young Adulthood: Pathways and Prevention ,NIH| Genes and Environment Initiatives in Type 2 Diabetes ,AKA| Sustainable Innovative Materials in High Tech Applications. An Interdisciplinary Approach to Design,Engineering Technology and Chemistry of Environmentally Sound Products and Production. ,NIH| Obesity and the Environment: The Transition to Adulthood ,ARC| Elucidating the genetics of attention deficit hyperactivity disorder by integrating pathway and prediction analyses ,WT| Familial and other risk factors for adolescent substance use and abuse. ,NIH| COSTS AND BENEFITS OF ALCOHOL SERVICES &INTERVENTIONS ,NIH| Stressors and their impact on health related addictions: smoking, drinking, BMI ,NIH| Molecular Epidemiology of Alcoholism 2- Big Sibships ,NIH| Identifying essential network properties for disease spread ,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| The University of Iowa Prevention Research Center ,NIH| Mentoring Clinical Investigators in Adolescent-onset Substance Use Disorders Research ,NIH| Smoking/Nicotine Dependence in Attention Deficit Hyperactivity Disorder (ADHD) ,WT ,SSHRC ,NIH| Molecular Genetics and Behavior: Alcohol and Tobacco Use ,NSF| The Genetic Basis of Social Networks and Civic Engagement ,NSF| Machine learning techniques to model the impact of relational communication on distributed team effectiveness ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| SOCIAL DEMOGRAPHY ,NIH| MOTS: Modeling Obesity Through Simulation ,NIH| Deciphering genes and pathways in nicotine dependence ,NIH| HUMAN GENETIC VARIATION IN SMOKING AND ADDICTION RISK ,NIH| The University of Colorado Population Center ,NIH| Sexual Behavior Trajectories from Adolescence to Adulthood ,NIH| Cascades of Network Structure and Function: Pathways to Adolescent Substance Use ,NIH| LONGITUDINAL STUDY OF SUBSTANCE USE, INCARCERATION, AND STI IN THE US ,NIH| YOUNG ADULT SUBSTANCE USE--PREDICTORS AND CONSEQUENCES ,NIH| Identifying Mediated Pathways of Risk for Substance Use in Sexual Minority Girls ,NIH| Genetic &environmental pathways to drug use, abuse &dependence ,NIH| The Role of Peer Networks in Youth Drug Use ,EC| GMI ,NIH| Intergenerational Research on Obesity Prevention: From Correlates to Intervention ,NIH| Genome-Wide Association for Loci Influencing CHD and Other Heart, Lung and Blood ,NIH| Longitudinal Study of Trauma, HIV Risk, and Criminal Justice Involvement ,NIH| Statistical Methods for Gene Environment Interactions In Lung Cancer ,ARC| Locating genes for elementary and complex cognitive abilities using genetic linkage and association analysis ,NIH| Molecular Epidemiology of Alcoholism 3 - EDAC Families ,NIH| FINANCIAL STATUS--RETIREMENT SAVING PROGRAMS ,NIH| A Nurse-Community Health Worker-Family Partnership Model to Increase COVID-19 Testing in Urban Underserved and Vulnerable Communities ,NIH| NATURAL HISTORY OF ALCOHOL USE &ABUSE--GENETIC MODELS ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| OPTIMIZING BEHAVIORAL INTERVENTIONS FOR DRUG ABUSE PREVENTION &TREATMENT ,NIH| Human Development: Interdisciplinary Research Training ,NIH| The Genetics of Vulnerability to Nicotine Addictions ,NIH| Linkage Disequilibrium Studies of Alcohol Dependence ,NIH| Birth Outcomes Among Adolescents ,NIH| DIET, HORMONES AND RISK OF COLORECTAL CANCERS ,NIH| High Density Association Analysis of Lung Cancer ,NIH| Genetics of Alcohol Dependence in African-Americans ,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 ,EC| NBHCHOICE ,NIH| ECONOMICS OF AGING TRAINING PROGRAM -- EXTENSION ,NIH| Modeling HIV and STD in Drug User and Social Networks ,NIH| Individual differences and health outcomes: A secondary data analysis in cognitiv ,NIH| Washington University Institute of Clinical and Translational Sciences (UL1) ,NIH| GENETICS AND CONSEQUENCES OF NICOTINE ADDICTION ,NIH| Physical Environment Dynamics, Inequality and Obesity ,NIH| Refining Phenotypic Measures of Nicotine Withdrawal ,EC| DEPRIVEDHOODS ,NIH| Adolescent Alcohol Use: Disentangling Friend Selection &Influence ,NIH| Administrative and Research Support Core ,NIH| Response Inhibition and Dopamine Neurotransmission (RI) (4 of 8) ,AKA| Roles of inflammation, oxidation, sex hormones and genetic variation in vascular aging and the development of atherosclerosis over the life-course. ,NIH| TRAINING GRANT IN CANCER EPIDEMIOLOGY ,NIH| NYS FAMILY STUDY: PROBLEM ALCOHOL USE &PROBLEM BEHAVIOR ,NIH| Training in Developmental Science to Improve Child Health and Well-Being ,NIH| Systematic Error and Confounding: Meta-Analyses of Alcohol and Disease ,NIH| GWA for Gene-Environment Interaction Effects Influencing CHD ,NIH| Propensity Scores and Preventive Drug Use in the Elderly ,NIH| Population Research Institute ,NIH| Sexual Orientation and Obesity: Test of a Gendered Biopsychosocial Model ,NIH| Substance Abuse & Treatment Gaps in Asians, Pacific Islanders & Multiple-race Ind ,NIH| PERSISTENCE &CHANGE IN DRINKING HABITS: TWIN STUDY ,NSF| GSE/RES Gender Differences in Science and Math: Diversity and the Role of Social Context ,NIH| Mid Southern Primary Care Networks Node ,NIH| High Risk Drug Use &HIV-Learning from the NYC Epidemic ,NSF| Science Achievement and Health Behavior: High School Curriculum, Social Context, and Opportunity to Learn ,NIH| PROSTATE, LUNG, COLORECTAL, AND OVARIAN (PLCO) CANCER ,NIH| VARIATION IN THE EFFECTS OF ALCOHOL ON LIVER FUNCTION ,NIH| Novel Use of Gwas for Improved Understanding of Nicotine Dependence ,NIH| Genes, early adversity, and sensitive periods in social-emotional development ,NIH| BEYOND RACE--EXPLAINING INEQUALITY MANIFESTED AS OBESITY ,NIH| CORE--ADIPOSE TISSUE BIOLOGY AND BASIC MECHANISMS ,EC| ADDICTION ,AKA| The Cardiovascular Risk in Young Finns Study - the 27-year follow-up. ,NIH| University of Minnesota Clinical and Translational Science Institute (UMN CTSI) ,NIH| Exome Variants Underlying Weight Gain from Adolescence to Adulthood ,NIH| Obesity and Metabolic Risk Disparities: Underlying Food Environment Factors ,NIH| Genetic Epidemiology of Lung Cancer ,NIH| PROSTATE, LUNG, COLORECTAL AND OVARIAN (PLCO) CANCER ,NIH| PATHOLOGY MONITORING--F344 RAT COLONY ,ARC| Maximising knowledge from dense SNP (single nucleotide polymorphisms) data using multi-locus analysis ,NIH| Nicotinic receptor genes &substance abuse: Functional studies of associated SNPs ,AKA| Center of Excellence in Complex Disease Genetics ,NIH| Data Core ,NIH| Cancer Center Support Grant ,NIH| DIETARY ETIOLOGIES OF HEART DISEASE AND CANCER ,NIH| Health Communication and Health Literacy Core ,NIH| Institute for Clinical and Translational Research (UL1) ,NIH| Study of Addiction: Genetics and Environment ,NIH| Population Research Training ,NIH| Center for Family and Demographic Research ,NIH| Genetics of Opioid Dependence ,NIH| Genetic Risk, Pathways to Adulthood, and Health Inequalities ,NIH| BEHAVIORAL PHARMACOGENETICS OF DRUG AND ALCOHOL ABUSE ,NIH| Economic Evaluation Methods: Development and Application ,NIH| Fine Mapping Susceptibility Loci for Nicotine Dependence ,NIH| Racial disparities in cancer outcomes: quantifying modifiable mechanisms ,NIH| Genetics of Adolescent Antisocial Drug DependenceAuthors: 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.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3886/icpsr21600.v23&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu8 citations 8 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3886/icpsr21600.v23&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2019figshare SSHRC, CIHRSSHRC ,CIHRNaud, Daniel; Généreux, Mélissa; Jean-François Bruneau; Alauzet, Aline; Levasseur, Mélanie;Gender distribution by region. (XLSX 17 kb)
figshare 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.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.6084/m9.figshare.9641315.v1&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert figshare 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.
You have already added works in your ORCID record related to the merged Research product.