The National Longitudinal Study of Adolescent to Adult Health (Add Health) Parent Study Public Use collection includes data gathered as part of the Add Health longitudinal survey of adolescents. The original Add Health survey is a longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-1995 school year. In Wave 1 of the Add Health Study (1994-1995), a parent of each Add Health Sample Member (AHSM) was interviewed. The Add Health Parent Study gathered social, behavioral, and health survey data in 2015-2017 from the parents of Add Health Sample members who were originally interviewed at Wave 1 (1994-1995). Wave 1 Parents were asked about their adolescent children, their relationships with them, and their own health. The Add Health Parent Study interview is a comprehensive survey of Add Health parents' family relations, education, religious beliefs, physical and mental health, social support, and community involvement experiences. In addition, survey data contains cognitive assessments, a medications log linked to a medications database lookup table, and household financial information collection. The survey also includes permission for administrative data linkages and includes data from a Family Health History Leave-Behind questionnaire. Interviews were conducted with parents' spouse/partner when available. Research domains targeted in the survey and research questions that may be addressed using the Add Health Parent Study data include: Health Behaviors and Risks Many health conditions and behaviors run in families; for example, cardiovascular disease, obesity and substance abuse. How are health risks and behaviors transmitted across generations or clustered within families? How can we use information on the parents' health and health behavior to better understand the determinants of their (adult) children's health trajectories? Cognitive Functioning and Non-Cognitive Personality Traits What role does the intergenerational transmission of personality and locus of control play in generating intergenerational persistence in education, family status, income and health? How do the personality traits of parents and children, and how they interact, influence the extent and quality of intergenerational relationships and the prevalence of assistance across generations? Decision-Making, Expectations, and Risk Preferences Do intergenerational correlations in risk preferences represent intergenerational transmission of preferences? If so, are the transmission mechanisms a factor in biological and environmental vulnerabilities? Does the extent of genetic liability vary in response to both family-specific and generation-specific environmental pressures? Family Support, Relationship Quality and Ties of Obligation How does family complexity affect intergenerational obligations and the strength of relationship ties? As parents near retirement: What roles do they play in their children's lives and their children in their lives? What assistance are they providing to their adult children and grandchildren? What do they receive in return? And how do these ties vary with divorce, remarriage and familial estrangement? Economic Status and Capacities What are the economic capacities of the parents' generation as they reach their retirement years? How have fared through the wealth and employment shocks of the Great Recession? Are parents able to provide for their own financial need? And, do they have the time and financial resources to help support their children and grandchildren and are they prepared to do so?

Add Health Parent Study (2015-2017) gathered social, behavioral, and health survey data in 2015-2017 on a probability sample of the "https://addhealth.cpc.unc.edu/" Target="_blank">Add Health parents who were originally interviewed in 1995. Data for 2,013 Wave I parents, ranging in age from 50-80 years and representing 2,244 Add Health sample members, are available. Add Health Parent Study Wave I Parents were the biological, adoptive, or stepparent of an Add Health child; not deceased or incarcerated at the time of Parents (2015-2017) sampling; and had at least one Add Health child who is also not deceased at the time of Parents (2015-2017) sampling. The Add Health Parent Study interview also gathered survey data on the current cohabiting Spouse or Partner of Wave I Parents who completed the interview. Nine hundred eighty-eight (988) current Spouse/Partner interviews are available. These data can be linked with Wave I parent data, and corresponding Add Health respondents at Waves I - V.

The Add Health Parent Study (2015-2017) interview is a comprehensive survey of Add Health parents' family relations, education, religious beliefs, physical and mental health, social support, and community involvement experiences. In particular, the study was designed to improve the understanding of the role that families play through socioeconomic channels in the health and well-being of the older, parent generation and that of their offspring. This unique data set supports the analyses of intergenerational transmissions of (dis)advantage that have not been possible to date. Add Health Parent Study data permits the examination of both short-term and long-term linkages and interactions between parents and their adult children.

For more information, please visit the Add Health Parent Study official website "https://addhealth.cpc.unc.edu/about/#studies-satellite" Target="_blank">here.

This file contains the weights for analysis of Add Health child-level data. The name of the file is "p2ahwgt" on official Add Health "https://www.cpc.unc.edu/projects/addhealth/documentation/restricteduse/datasets#parent_study_files" Target="_blank"> data documentation .

The National Longitudinal Study of Adolescent to Adult Health (Add Health) is a longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-95 school year. The Add Health cohort has been followed into young adulthood with four in-home interviews, the most recent 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, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. The fourth wave of interviews expanded the collection of biological data in Add Health to understand the social, behavioral, and biological linkages in health trajectories as the Add Health cohort ages through adulthood. Wave III The Wave III public use data are helpful in analyzing the transition between adolescence and young adulthood. A total of 4,882 of the original Wave I public-use respondent sample were re-interviewed between August 2001 and April 2002. Wave III respondents were between 18 and 26 years old. The Wave III public use dataset includes the following data files: Main Respondent File: includes the In-Home Questionnaire data, grand sampling weights, AHP VT scores, and biospecimen data for 4,882 respondents Relationship Table File Pregnancy Table File Relationship Detail File Completed Pregnancies File Current Pregnancies File Live Births File Children and Parenting File Education Data *17 respondents in the Wave IV public use sample were 33 years old at the time of the interview.

Longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-95 school year. Public data on about 21,000 people first surveyed in 1994 are available on the first phases of the study, as well as study design specifications. It also includes some parent and biomarker data. The Add Health cohort has been followed into young adulthood with four in-home interviews, the most recent 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, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. The fourth wave of interviews expanded the collection of biological data in Add Health to understand the social, behavioral, and biological linkages in health trajectories as the Add Health cohort ages through adulthood. The restricted-use contract includes four hours of free consultation with appropriate staff; after that, there''s a fee for help. Researchers can also share information through a listserv devoted to the database.

The "https://addhealth.cpc.unc.edu/" Target="_blank">National Longitudinal Study of Adolescent to Adult Health (Add Health) is a longitudinal study of a nationally representative sample of adolescents in grades seven through 12 in the United States. The Add Health cohort has been followed into adulthood (ages 31-42). 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, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. The fifth wave of data collection includes social and environmental data and continues to include biological data, like the fourth wave. This data file collects information on weights for Wave V.

For more complete information on the Add Health studies, please refer to the "https://addhealth.cpc.unc.edu/documentation/" Target="_blank">study's documentation.

The National Longitudinal Study of Adolescent Health (Add Health) is a longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-1995 school year. 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, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. Public-use biomarker data has been added.

Data is available from four instruments in Wave I (conducted from September 1994 through December 1995), two surveys in Wave II (conducted from April 1996 through August 1996), several sources in Wave III (collected from August 2001 through April 2002), and one in-home interview in Wave IV (conducted from January 2008 through February 2009). Data from Wave V, conducted during 2016-2018 as a mixed-mode survey to collect information on health status and indicators of chronic disease, is available upon application approval only.

Users can download or order data regarding adolescent health and well-being and the factors that influence the adolescent transition into adulthood. Background The Add Health Study, conducted by the Eunice Kennedy Shriver National Institute for Child Health and Human Development, began during the 1994-1995 school year with a nationally representative sample of students in grades 7-12. The cohort has been followed into adulthood. Participants' social, physical, economic and psychological information is ascertained within the contexts of their family, neighborhood, school, peer groups, friendships and romantic relationships. The original purpose of the study was to understand factors that may influence adolescent behaviors, but as the study has continued, it was evolved to gather information on the factors related to the transition into adulthood. User Functionality Users can download or order the CD-Rom of the public use data sets (which include only a subset of the sample). To do so, users must generate a free log in with Data Sharing for Demographic Research, which is part of the Inter-University Consortium for Political and Social Research, or users must contact Sociometrics. Links to both data warehouses are provided. Data Notes The study began in 1994; respondents were followed up with in 1996, 2001-2 002, and 2007-2008. In addition to the cohort members, parents, siblings, fellow students, school administrators, and romantic partners are also interviewed.

Abstract (en): The National Longitudinal Study of Adolescent Health (Add Health) is a longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-1995 school year. The Add Health cohort has been followed into young adulthood with four in-home interviews, the most recent 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, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. The fourth wave of interviews expanded the collection of biological data in Add Health to understand the social, behavioral, and biological linkages in health trajectories as the Add Health cohort ages through adulthood. This component of the Add Health restricted data is the Biomarker Data. The Glucose/HbA1c data file contains two measures of glucose homeostasis based on assays of the Wave IV dried blood spots: Glucose (mg/dl) and Hemoglobin A1c (HbA1c, %). Six additional constructed measures -- fasting duration, classification of fasting glucose, classification of non-fasting glucose, classification of HbA1c, diabetes medication, and a joint classification of glucose, HbA1c, self-reported history of diabetes, and anti-diabetic medication use -- are also included. The Lipids data file contains measures of triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol, and total cholesterol to high-density lipoprotein cholesterol ratio. Additional variables include, measurement method for triglycerides (TG), total cholesterol (TC), high-density lipoprotein choleserol (HDL-C), Antihyperlipidemic medication use, joint classification of self-reported history of Hyperlipidemia and Antihyperlipidemic medication use, and fasting duration. For more information, please see the study website. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Performed consistency checks.; Standardized missing values.; Checked for undocumented or out-of-range codes.. Adolescents in grades 7-12 and their families. Wave I, Stage 1 School sample: 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. Wave I, Stage 2: An in-home sample of 27,000 adolescents was drawn consisting 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. In addition, parents were asked to complete a questionnaire about family and relationships. The Wave II in-home interview sample is the same as the Wave I in-home interview sample, with a few exceptions. Information about neighborhoods/communities was gathered from a variety of previously published databases. Wave III: The in-home Wave III sample consists of Wave I respondents who could be located and re-interviewed six years later. Wave III also collected High School Transcript Release Forms as well as samples of urine and saliva. 2013-11-14 Public release of documentation guides and codebooks.2013-11-07 Part 4 was added and it includes new Biomarker Lipid Data.2013-03-08 Part 2 was updated following a resupply of the data by the Principal Investigators. Specifically, additional variables added to the data file, and CRP and EBV values have been recalculated, resulting in minimal changes to the data. The associated documentation and codebook files were also updated. Finally, a user guide describing measures of inflammation and immune function for Part 2 was also added.2012-11-07 The codebook associat...

This survey was mandated by Congress to collect data for the purpose of measuring the impact of the social environment on adolescent health. It examines the general health and well-being of adolescents in the United States, including, with respect to those adolescents: the behaviors that promote health and the behaviors that are detrimental to health; and the influence on health of factors particular to the communities in which adolescents reside. Some of the dependent variables include diet and nutrition, eating disorders, depression, violent behavior, intentional injury, unintentional injury, suicide, exercise, health services use, and health insurance coverage. Wave 1 was collected from students grade 7 through 12 and consists of responses to questions relating to the respondents' behaviors, friends, and parents. Parent data were also collected from one parent or parent-figure for each in-home sampled student. Wave 2 consists of follow-up interviews. Wave 3 consists of yet another follow-up, when the respondents were now between 18 and 26 years of age. The focus of Wave 3 was the issues faced in the transition from adolescence to adulthood, such as: the labor market, higher education, relationships, parenting, and community involvement.

The National Longitudinal Study of Adolescent Health (Add Health) was mandated by Congress to collect data for the purpose of measuring the impact of social environment on adolescent health. It examines the general health and well-being of adolescents in the United States, including, with respect to these adolescents, (1) the behaviors that promote health and the behaviors that are detrimental to health; and (2) the influence on health of factors particular to the communities in which adolescents reside. Dependent variables include diet and nutrition, eating disorders, depression, violent behavior, intentional injury, unintentional injury, suicide, exercise, health service use, and health insurance coverage.

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

Add Health Parent Study (2015-2017) gathered social, behavioral, and health survey data in 2015-2017 on a probability sample of the "https://addhealth.cpc.unc.edu/" Target="_blank">Add Health parents who were originally interviewed in 1995. Data for 2,013 Wave I parents, ranging in age from 50-80 years and representing 2,244 Add Health sample members, are available. Add Health Parent Study Wave I Parents were the biological, adoptive, or stepparent of an Add Health child; not deceased or incarcerated at the time of Parents (2015-2017) sampling; and had at least one Add Health child who is also not deceased at the time of Parents (2015-2017) sampling. The Add Health Parent Study interview also gathered survey data on the current cohabiting Spouse or Partner of Wave I Parents who completed the interview. Nine hundred eighty-eight (988) current Spouse/Partner interviews are available. These data can be linked with Wave I parent data, and corresponding Add Health respondents at Waves I - V.

The Add Health Parent Study (2015-2017) interview is a comprehensive survey of Add Health parents' family relations, education, religious beliefs, physical and mental health, social support, and community involvement experiences. In particular, the study was designed to improve the understanding of the role that families play through socioeconomic channels in the health and well-being of the older, parent generation and that of their offspring. This unique data set supports the analyses of intergenerational transmissions of (dis)advantage that have not been possible to date. Add Health Parent Study data permits the examination of both short-term and long-term linkages and interactions between parents and their adult children.

For more information, please visit the Add Health Parent Study official website "https://addhealth.cpc.unc.edu/about/#studies-satellite" Target="_blank">here.

This file is the main interview data collected from the Spouse or Partner of the Add Health Wave I Parent. The name of the file is "sp2" on official Add Health "https://www.cpc.unc.edu/projects/addhealth/documentation/restricteduse/datasets#parent_study_files" Target="_blank">data documentation.

The Add Health Parent Study or Parents (2015-2017), gathered social, behavioral, and health survey data in 2015-2017 on a probability sample of the parents of Add Health sample members who were originally interviewed at Wave I (1994-1995). Data for 966 Wave I Parents, ranging in age from 50-80 years and representing 988 Add Health sample members, are available in the Public-Use sample. Parents eligible for participation in this study were the biological parent, adoptive parent, or stepparent of an Add Health respondent at Wave I; not deceased or incarcerated at the time of Parents (2015-2017) sampling; and had at least one Add Health child who was also not deceased at the time of Parents (2015-2017) sampling. Spouse/Partner Interviews The Add Health Parent Study interview also gathered survey data on the current co-habiting Spouse or Partner of eligible parents who completed the interview. Four hundred eight-six (486) current Spouse/or Partner interviews are available in the Public-Use sample. Financial Respondent During the Wave I Parent interview, Wave I Parents who indicated having a Spouse or Partner were asked to identify whether they or their Spouse or Partner was most knowledgeable about household assets, debts and retirement planning. The person identified was flagged by the survey as the Financial Respondent. Only the Financial Respondent was asked to complete a more detailed set of questions on these topics. Family Health History A paper Family Health History (FHH) leave-behind questionnaire was given to each respondent (Wave I Parent and Spouse or Partner) at the end of the interview together with a self-addressed and stamped envelope. Health Histories for biological parents, siblings, aunts or uncles and grandparents are included in this FHH questionnaire. A total of 633 Wave I Parents and 316 Spouses or Partners, selected for inclusion in the Public-Use sample, completed and returned the FHH leave-behind questionnaire.

This dataset contains the do files for replicating the analyses in “Peers’ race in adolescence and voting behavior”. The paper uses data from the National Longitudinal Study of Adolescent to Adult Health (Add Health), a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available from the Add Health website (http://www.cpc.unc.edu/addhealth). No direct support was received from grant P01-HD31921 for this analysis. In order to (purchase the access to) the data, you need to contact the Carolina Population Center: http://www.cpc.unc.edu/projects/addhealth. While part of the data is accessible for free, in the paper we make use of restricted access data. We use the In-Home and In-School surveys for Wave 1 and the surveys in Waves III and IV. We also use the following additional data: from Wave I - School Network, Friend Files, School Distance Measures, and School Administrator Questionnaire; from Waves I and III - Contextual Files, Political Files; from Waves I, III and IV: Weight Files.

Robustness to unmeasured confounding (E-values) for the association between positive affect (3rd tertile vs. 1st tertile) in adolescence and subsequent health and well-being in adulthood (National Longitudinal Study of Adolescent to Adult Health [Add Health]).

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. This collection features secondary analyses of restricted-use data from the National Longitudinal Study of Adolescent to Adult Health (Add Health), a nationally representative longitudinal study of a sample of U.S. adolescents who were in grades 7-12 in the 1994-95 school year, who were interviewed at three key developmental junctures from adolescence to young adulthood. Self-reported data were used for both maltreatment (measured at the latter two time points) and delinquent or criminal behaviors (measured at all three time points). Linear mixed-effects analyses were used to model growth curves of the frequency of violent and non-violent offending, from ages 13 to 30. Next, maltreatment frequency was tested as a predictor, and then potential protective factors (at peer, family, school, and neighborhood levels) were tested as moderators. Sex, race/ethnicity, and sexual orientation were also tested as moderators of delinquent or criminal offense frequency, and as moderators of protective effects. The study collection includes 1 Stata (.do) syntax file (AddHealthOJJDPAnalysis_StataSyntax.do) that was used by the researcher in secondary analyses of restricted-use data. The restricted archival data from the Add Health survey series are not included as part of this release.

BackgroundThe low transcriptionally efficient short-allele of the 5HTTLPR serotonin transporter polymorphism has been implicated to moderate the relationship between the experience of stressful life events (SLEs) and depression. Despite numerous attempts at replicating this observation, results remain inconclusive.MethodsWe examined this relationship in young-adult Non-Hispanic white males and females between the ages of 22 and 26 (n = 4724) participating in the National Longitudinal Study of Adolescent to Adult Health (Add Health) with follow-up information every six years since 1995.ResultsLinear and logistic regression models, corrected for multiple testing, indicated that carriers of one or more of the S-alleles were more sensitive to stress than those with two L-alleles and at a higher risk for depression. This relationship behaved in a dose-response manner such that the risk for depression was greatest among those who reported experiencing higher numbers of SLEs. In post-hoc analyses we were not able to replicate an interaction effect for suicide ideation but did find suggestive evidence that the effects of SLEs and 5HTTLPR on suicide ideation differed for males and females. There were no effects of childhood maltreatment.DiscussionOur results provide partial support for the original hypothesis that 5-HTTLPR genotype interacts with the experience of stressful life events in the etiology of depression during young adulthood. However, even with this large sample, and a carefully constructed a priori analysis plan, the results were still not definitive. For the purposes of replication, characterizing the 5HTTLPR in other large data sets with extensive environmental and depression measures is needed.

Graph and download economic data for Value Added by Industry: Educational Services, Health Care, and Social Assistance as a Percentage of GDP (VAPGDPESHS) from Q1 2005 to Q1 2025 about social assistance, value added, health, private industries, education, percent, services, private, industry, GDP, and USA.

ObjectivePreventing suicide in US youth is of paramount concern, with rates increasing over 50% between 2007 and 2018. Statistical modeling using electronic health records may help identify at-risk youth before a suicide attempt. While electronic health records contain diagnostic information, which are known risk factors, they generally lack or poorly document social determinants (e.g., social support), which are also known risk factors. If statistical models are built incorporating not only diagnostic records, but also social determinants measures, additional at-risk youth may be identified before a suicide attempt.MethodsSuicide attempts were predicted in hospitalized patients, ages 10–24, from the State of Connecticut’s Hospital Inpatient Discharge Database (HIDD; N = 38943). Predictors included demographic information, diagnosis codes, and using a data fusion framework, social determinants features transferred or fused from an external source of survey data, The National Longitudinal Study of Adolescent to Adult Health (Add Health). Social determinant information for each HIDD patient was generated by averaging values from their most similar Add Health individuals (e.g., top 10), based upon matching shared features between datasets (e.g., Pearson’s r). Attempts were then modelled using an elastic net logistic regression with both HIDD features and fused Add Health features.ResultsThe model including fused social determinants outperformed the conventional model (AUC = 0.83 v. 0.82). Sensitivity and positive predictive values at 90 and 95% specificity were almost 10% higher when including fused features (e.g., sensitivity at 90% specificity = 0.48 v. 0.44). Among social determinants variables, the perception that their mother cares and being non-religious appeared particularly important to performance improvement.DiscussionThis proof-of-concept study showed that incorporating social determinants measures from an external survey database could improve prediction of youth suicide risk from clinical data using a data fusion framework. While social determinant data directly from patients might be ideal, estimating these characteristics via data fusion avoids the task of data collection, which is generally time-consuming, expensive, and suffers from non-compliance.

Recent studies have begun to uncover the genetic architecture of educational attainment. We build on this work using genome-wide data from siblings in the National Longitudinal Study of Adolescent to Adult Health (Add Health). We measure the genetic predisposition of siblings to educational attainment using polygenic scores. We then test how polygenic scores are related to social environments and educational outcomes. In Add Health, genetic predisposition to educational attainment is patterned across the social environment. Participants with higher polygenic scores were more likely to grow up in socially advantaged families. Even so, the previously published genetic associations appear to be causal. Among pairs of siblings, the sibling with the higher polygenic score typically went on to complete more years of schooling as compared to their lower-scored co-sibling. We found subtle differences between sibling fixed-effect estimates of the genetic effect versus those based on unrelated individuals.