Data on obesity among children and adolescents aged 2-19 years by selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions, and changes over time. SOURCE: NCHS, National Health and Nutrition Examination Survey. For more information on the National Health and Nutrition Examination Survey, see the corresponding Appendix entry at https://www.cdc.gov/nchs/data/hus/hus19-appendix-508.pdf.

The goal of this study was to test specific hypotheses illustrating the relationships among serious victimization experiences, the mental health effects of victimization, substance abuse/use, and delinquent behavior in adolescents. The study assessed familial and nonfamilial types of violence. It was designed as a telephone survey of American youth aged 12-17 living in United States households and residing with a parent or guardian. One parent or guardian in each household was interviewed briefly to establish rapport, secure permission to interview the targeted adolescent, and to ensure the collection of comparative data to examine potential nonresponse bias from households without adolescent participation. All interviews with both parents and adolescents were conducted using Computer-Assisted Telephone Interviewing (CATI) technology. From the surveys of parents and adolescents, the principal investigators created one data file by attaching the data from the parents to the records of their respective adolescents. Adolescents were asked whether violence and drug abuse were problems in their schools and communities and what types of violence they had personally witnessed. They were also asked about other stressful events in their lives, such as the loss of a family member, divorce, unemployment, moving to a new home or school, serious illness or injury, and natural disaster. Questions regarding history of sexual assault, physical assault, and harsh physical discipline elicited a description of the event and perpetrator, extent of injuries, age at abuse, whether alcohol or drugs were involved, and who was informed of the incident. Information was also gathered on the delinquent behavior of respondents and their friends, including destruction of property, assault, theft, sexual assault, and gang activity. Other questions covered history of personal and family substance use and mental health indicators, such as major depression, post-traumatic stress disorders, weight changes, sleeping disorders, and problems concentrating. Demographic information was gathered from the adolescents on age, race, gender, number of people living in household, and grade in school. Parents were asked whether they were concerned about violent crime, affordable child care, drug abuse, educational quality, gangs, and the safety of their children at school. In addition, they were questioned about their own victimization experiences and whether they discussed personal safety issues with their children. Parents also supplied demographic information on gender, marital status, number of children, employment status, education, race, and income.

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 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 fifth wave of data collection is planned to begin in 2016.

Initiated in 1994 and supported by three program project grants from the "https://www.nichd.nih.gov/" Target="_blank">Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) with co-funding from 23 other federal agencies and foundations, Add Health is the largest, most comprehensive longitudinal survey of adolescents ever undertaken. Beginning with an in-school questionnaire administered to a nationally representative sample of students in grades seven through 12, the study followed up with a series of in-home interviews conducted in 1995, 1996, 2001-02, and 2008. Other sources of data include questionnaires for parents, siblings, fellow students, and school administrators and interviews with romantic partners. Preexisting databases provide information about neighborhoods and communities.

Add Health was developed in response to a mandate from the U.S. Congress to fund a study of adolescent health, and Waves I and II focus 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 have aged into adulthood, however, the scientific goals of the study have expanded and evolved. Wave III, conducted when respondents were between 18 and 26** years old, focuses on how adolescent experiences and behaviors are related to decisions, behavior, and health outcomes in the transition to adulthood. At Wave IV, respondents were ages 24-32* and assuming adult roles and responsibilities. Follow up at Wave IV has enabled researchers to study developmental and health trajectories across the life course of adolescence into adulthood using an integrative approach that combines the social, behavioral, and biomedical sciences in its research objectives, design, data collection, and analysis.

* 52 respondents were 33-34 years old at the time of the Wave IV interview.
** 24 respondents were 27-28 years old at the time of the Wave III interview.

Wave IV was designed to study the developmental and health trajectories across the life course of adolescence into young adulthood. Biological data was gathered in an attempt to acquire a greater understanding of pre-disease pathways, with a specific focus on obesity, stress, and health risk behavior. Included in this dataset are the Wave IV in-home questionnaire data.

States report information from two reporting populations: (1) The Served Population which is information on all youth receiving at least one independent living services paid or provided by the Chafee Program agency, and (2) Youth completing the NYTD Survey. States survey youth regarding six outcomes: financial self-sufficiency, experience with homelessness, educational attainment, positive connections with adults, high-risk behaviors, and access to health insurance. States collect outcomes information by conducting a survey of youth in foster care on or around their 17th birthday, also referred to as the baseline population. States will track these youth as they age and conduct a new outcome survey on or around the youth's 19th birthday; and again on or around the youth's 21st birthday, also referred to as the follow-up population. States will collect outcomes information on these older youth at ages 19 or 21 regardless of their foster care status or whether they are still receiving independent living services from the State. Depending on the size of the State's foster care youth population, some States may conduct a random sample of the baseline population of the 17-year-olds that participate in the outcomes survey so that they can follow a smaller group of youth as they age. All States will collect and report outcome information on a new baseline population cohort every three years. Units of Response: Current and former youth in foster care Type of Data: Administrative Tribal Data: No Periodicity: Annual Demographic Indicators: Ethnicity;Race;Sex SORN: Not Applicable Data Use Agreement: https://www.ndacan.acf.hhs.gov/datasets/request-dataset.cfm Data Use Agreement Location: https://www.ndacan.acf.hhs.gov/datasets/order_forms/termsofuseagreement.pdf Granularity: Individual Spatial: United States Geocoding: FIPS Code

In 2022, around 20.3 percent of teenagers between ages 16 and 19 were employees while enrolled at school in the United States. This is an increase from the previous year, when 19.4 percent of teenagers were working while in school.

The PATH Study was launched in 2011 to inform the Food and Drug Administration's regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). The PATH Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). The study sampled over 150,000 mailing addresses across the United States to create a national sample of people who use or do not use tobacco. 45,971 adults and youth constitute the first (baseline) wave, Wave 1, of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent. At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population (CNP) at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled Primary Sampling Unit (PSU)s and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the CNP at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort. At Wave 7, a probability sample of 14,863 adults, youth, and shadow youth ages 9 to 11 was selected from the CNP at the time of Wave 7. This sample was recruited from residential addresses not selected for Wave 1 or Wave 4 in the same sampled PSUs and segments using similar within-household sampling procedures. This "second replenishment sample" was combined for estimation and analysis purposes with the Wave 7 adult and youth respondents from the Wave 4 Cohorts who were at least age 15 and in the CNP at the time of Wave 7. This combined set of Wave 7 participants, 46,169 participants in total, forms the Wave 7 Cohort. Please refer to the Restricted-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1, Wave 4, and Wave 7 Cohorts. Dataset 0002 (DS0002) contains the data from the State Design Data. This file contains 7 variables and 82,139 cases. The state identifier in the State Design file reflects the participant's state of residence at the time of selection and recruitment for the PATH Study. Dataset 1011 (DS1011) contains the data from the Wave 1 Adult Questionnaire. This data file contains 2,021 variables and 32,320 cases. Each of the cases represents a single, completed interview. Dataset 1012 (DS1012) contains the data from the Wave 1 Youth and Parent Questionnaire. This file contains 1,431 variables and 13,651 cases. Dataset 1411 (DS1411) contains the Wave 1 State Identifier data for Adults and has 5 variables and 32,320 cases. Dataset 1412 (DS1412) contains the Wave 1 State Identifier data for Youth (and Parents) and has 5 variables and 13,651 cases. The same 5 variables are in each State Identifier dataset, including PERSONID for linking the State Identifier to the questionnaire and biomarker data and 3 variables designating the state (state Federal Information Processing System (FIPS), state abbreviation, and full name of the state). The State Identifier values in these datasets represent participants' state of residence at the time of Wave 1, which is also their state of residence at the time of recruitment. Dataset 1611 (DS1611) contains the Tobacco Universal Product Code (UPC) data from Wave 1. This data file contains 32 variables and 8,601 cases. This file contains UPC values on the packages of tobacco products used or in the possession of adult respondents at the time of Wave 1. The UPC values can be used to identify and validate the specific products used by respondents and augment the analyses of the characteristics of tobacco products used

United States US: Adolescents Out of School: % of Lower Secondary School Age data was reported at 0.949 % in 2015. This records a decrease from the previous number of 1.855 % for 2014. United States US: Adolescents Out of School: % of Lower Secondary School Age data is updated yearly, averaging 0.949 % from Dec 1987 (Median) to 2015, with 11 observations. The data reached an all-time high of 6.755 % in 1987 and a record low of 0.010 % in 1994. United States US: Adolescents Out of School: % of Lower Secondary School Age data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Education Statistics. Adolescents out of school are the percentage of lower secondary school age adolescents who are not enrolled in school.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Comprehensive dataset containing 875 verified Youth group businesses in United States with complete contact information, ratings, reviews, and location data.

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?

Users can customize tables, graphs and maps on data related to children in a specific state or in the United States as a whole. Comparisons can be made between states. Background KIDS COUNT Data Center is part of the Annie E. Casey Foundation and serves to provide information on the status of children in America. The ten core indicators of interest under "Data by State" are: percent of low birth weight babies, infant mortality rate, child death rate, rate of teen deaths by accident, suicide and homicide, teen birth rate, percent of children living with parents who do not have full-time year-round employment, percent of teens who are high school drop outs, percent of teens not working and not in school, percent of children in poverty, and percent of families with children headed by a single parent. A number of other indicators, plus demographic and income information, are also included. "Data across States" is grouped into the following broad categories: demographics, education, economic well-being, family and community, health, safety and risk behaviors, and other. User Functionality Users can determine the view of the data- by table, line graph or map and can print or email the results. Data is available by state and across states. Data Across States allows users to access the raw data. Data is often present over a number of years. For a number of indicators under "Data Across States," users can view results by age, gender/ sex, or race/ ethnicity. Data Notes KIDS COUNT started in 1990. The most recent year of data is 2009 (or 2008 depending on the state, with some data available from 2010). Data is available on the national and state level, and for some states, at the county and city level.

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

United States US: Share of Youth Not in Education, Employment or Training: Male: % of Male Youth Population data was reported at 15.630 % in 2012. This records a decrease from the previous number of 16.200 % for 2011. United States US: Share of Youth Not in Education, Employment or Training: Male: % of Male Youth Population data is updated yearly, averaging 16.590 % from Dec 2009 (Median) to 2012, with 4 observations. The data reached an all-time high of 17.330 % in 2010 and a record low of 15.630 % in 2012. United States US: Share of Youth Not in Education, Employment or Training: Male: % of Male Youth Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Employment and Unemployment. Share of youth not in education, employment or training (NEET) is the proportion of young people who are not in education, employment, or training to the population of the corresponding age group: youth (ages 15 to 24); persons ages 15 to 29; or both age groups.; ; International Labour Organization, ILOSTAT database. Data retrieved in November 2017.; Weighted Average;

This map shows the access to mental health providers in every county and state in the United States according to the 2024 County Health Rankings & Roadmaps data for counties, states, and the nation. It translates the numbers to explain how many additional mental health providers are needed in each county and state. According to the data, in the United States overall there are 319 people per mental health provider in the U.S. The maps clearly illustrate that access to mental health providers varies widely across the country.The data comes from this County Health Rankings 2024 layer. An updated layer is usually published each year, which allows comparisons from year to year. This map contains layers for 2024 and also for 2022 as a comparison.County Health Rankings & Roadmaps (CHR&R), a program of the University of Wisconsin Population Health Institute with support provided by the Robert Wood Johnson Foundation, draws attention to why there are differences in health within and across communities by measuring the health of nearly all counties in the nation. This map's layers contain 2024 CHR&R data for nation, state, and county levels. The CHR&R Annual Data Release is compiled using county-level measures from a variety of national and state data sources. CHR&R provides a snapshot of the health of nearly every county in the nation. A wide range of factors influence how long and how well we live, including: opportunities for education, income, safe housing and the right to shape policies and practices that impact our lives and futures. Health Outcomes tell us how long people live on average within a community, and how people experience physical and mental health in a community. Health Factors represent the things we can improve to support longer and healthier lives. They are indicators of the future health of our communities.Some example measures are:Life ExpectancyAccess to Exercise OpportunitiesUninsuredFlu VaccinationsChildren in PovertySchool Funding AdequacySevere Housing Cost BurdenBroadband AccessTo see a full list of variables, definitions and descriptions, explore the Fields information by clicking the Data tab here in the Item Details of this layer. For full documentation, visit the Measures page on the CHR&R website. Notable changes in the 2024 CHR&R Annual Data Release:Measures of birth and death now provide more detailed race categories including a separate category for ‘Native Hawaiian or Other Pacific Islander’ and a ‘Two or more races’ category where possible. Find more information on the CHR&R website.Ranks are no longer calculated nor included in the dataset. CHR&R introduced a new graphic to the County Health Snapshots on their website that shows how a county fares relative to other counties in a state and nation. Data Processing:County Health Rankings data and metadata were prepared and formatted for Living Atlas use by the CHR&R team. 2021 U.S. boundaries are used in this dataset for a total of 3,143 counties. Analytic data files can be downloaded from the CHR&R website.

Youth data for the seventh wave of the National Youth Survey are contained in this collection. This research project, designed to gain a better understanding of both conventional and deviant types of behavior by youths, involved collecting information from a representative sample of young people in the United States. The first wave of this survey was conducted in 1976 (ICPSR 8375), the second in 1977 (ICPSR 8424), the third in 1978 (ICPSR 8506), the fourth in 1979 (ICPSR 8917), the fifth in 1980 (ICPSR 9112), and the sixth in 1983 (ICPSR 9948). For this wave, young adults were interviewed in early 1987 about events and behavior occurring in calendar year 1986, when they were 20 to 29 years of age. Data are available on the demographic and socioeconomic status of respondents, parents and friends, neighborhood problems, education, employment, skills, aspirations, encouragement, normlessness, attitudes toward deviance, exposure to delinquent peers, self-reported depression, delinquency, drug and alcohol use, victimization, pregnancy, abortion, use of mental health and outpatient services, violence by respondent and acquaintances, use of controlled drugs, and sexual activity.

This dataset assembles all final birth data for females aged 15–19, 15–17, and 18–19 for the United States and each of the 50 states.

Data are based on 100% of birth certificates filed in all 50 states. All the teen birth rates in this dashboard reflect the latest revisions to Census populations (i.e., the intercensal populations) and thus provide a consistent series of accurate rates for the past 25 years. The denominators of the teen birth rates for 1991–1999 have been revised to incorporate the results of the 2000 Census. The denominators of the teen birth rates for 2001–2009 have revised to incorporate the results of the 2010 Census.

United States US: Adolescents Out of School: Female: % of Female Lower Secondary School Age data was reported at 1.159 % in 2014. This records an increase from the previous number of 1.100 % for 2013. United States US: Adolescents Out of School: Female: % of Female Lower Secondary School Age data is updated yearly, averaging 1.159 % from Dec 1987 (Median) to 2014, with 7 observations. The data reached an all-time high of 5.578 % in 1987 and a record low of 0.421 % in 1993. United States US: Adolescents Out of School: Female: % of Female Lower Secondary School Age data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Education Statistics. Adolescents out of school are the percentage of lower secondary school age adolescents who are not enrolled in school.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

United States US: Adolescents Out of School: Male: % of Male Lower Secondary School Age data was reported at 2.521 % in 2014. This records an increase from the previous number of 1.051 % for 2013. United States US: Adolescents Out of School: Male: % of Male Lower Secondary School Age data is updated yearly, averaging 2.141 % from Dec 1987 (Median) to 2014, with 7 observations. The data reached an all-time high of 7.861 % in 1987 and a record low of 0.007 % in 1993. United States US: Adolescents Out of School: Male: % of Male Lower Secondary School Age data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Education Statistics. Adolescents out of school are the percentage of lower secondary school age adolescents who are not enrolled in school.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Data on obesity among children and adolescents aged 2-19 years in the United States, by selected characteristics, including sex, age, race, Hispanic origin, and poverty level. Data are from Health, United States. SOURCE: National Center for Health Statistics, National Health and Nutrition Examination Survey. Search, visualize, and download these and other estimates from over 120 health topics with the NCHS Data Query System (DQS), available from: https://www.cdc.gov/nchs/dataquery/index.htm.

The Survey of Youth in Residential Placement (SYRP) is the only national survey that gathers data directly from youth in the juvenile justice system. The Office of Juvenile Justice and Delinquency Prevention (OJJDP) designed the survey in 2000 and 2001 to survey offender youth between the ages of 10 and 20. SYRP asks the youth about their backgrounds, offense histories and problems; the facility environment; experiences in the facility; experiences with alcohol and drugs; experiences of victimization in placement; medical needs and services received; and their expectations for the future. SYRP research provides answers to a number of questions about the characteristics and experiences of youth in custody including: Who are the youth in placement? What are their offenses? What are their family backgrounds? What are their expectations for the future? How are youth grouped in living units and programs? What activities are available in each facility? How accessible are social, emotional, and legal supports? What is the quality of the youth-staff relationships? How clear are the facility's rules? How clear is the facility's commitment to justice and due process? What methods of control and discipline do staff use? SYRP's findings are based on anonymous interviews with a nationally representative sample of youth in custody during the spring of 2003 using audio computer-assisted self-interview (ACASI) technology. SYRP is the latest addition to two ongoing data collections that OJJDP designed and implemented in the 1990s. It joins the Census of Juveniles in Residential Placement and the Juvenile Residential Facility Census to provide updated statistics on youth in custody in the juvenile justice system. SYRP bulletins, reports, and a simplified online analysis tool are available from the SYRP Project Web site.

Vaccination Coverage among Adolescents (13-17 Years)

  Description

Vaccination Coverage among Adolescents (13-17 Years) • Data on adolescent vaccination coverage and selected sociodemographic characteristics by State, HHS Region, and the United States from the National Immunization Survey-Teen (NIS-Teen). • Additional information available at https://www.cdc.gov/vaccines/imz-managers/coverage/teenvaxview/index.html

  Dataset Details

Publisher: Centers for… See the full description on the dataset page: https://huggingface.co/datasets/HHS-Official/vaccination-coverage-among-adolescents-13-17-years.