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The purpose of this project was to measure and estimate the distribution of personal income and related economic factors in both rural and urban areas of the People's Republic of China. The principal investigators based their definition of income on cash payments and on a broad range of additional components. Data were collected through a series of questionnaire-based interviews conducted in rural and urban areas at the end of 2002. There are ten separate datasets. The first four datasets were derived from the urban questionnaire. The first contains data about individuals living in urban areas. The second contains data about urban households. The third contains individual-level economic variables copied from the initial urban interview form. The fourth contains household-level economic variables copied from the initial urban interview form. The fifth dataset contains village-level data, which was obtained by interviewing village leaders. The sixth contains data about individuals living in rural areas. The seventh contains data about rural households, as well as most of the data from a social network questionnaire which was presented to rural households. The eighth contains the rest of the data from the social network questionnaire and is specifically about the activities of rural school-age children. The ninth dataset contains data about individuals who have migrated from rural to urban areas, and the tenth dataset contains data about rural-urban migrant households. Dataset 1 contains 151 variables and 20,632 cases (individual urban household members). Dataset 2 contains 88 variables and 6,835 cases (urban households). Dataset 3 contains 44 variables and 27,818 cases, at least 6,835 of which are empty cases used to separate households in the file. The remaining cases from dataset 3 match those in dataset 1. Dataset 4 contains 212 variables and 6,835 cases, which match those in dataset 2. Dataset 5 contains 259 variables and 961 cases (villages). Dataset 6 contains 84 variables and 37,969 cases (individual rural household members). Dataset 7 contains 449 variables and 9,200 cases (rural households). Dataset 8 contains 38 variables and 8,121 cases (individual school-age children). Dataset 9 contains 76 variables and 5,327 cases (individual rural-urban migrant household members). Dataset 10 contains 129 variables and 2,000 cases (rural-urban migrant households).

The Chinese Household Income Project collected data in 1988, 1995, 2002, and 2007. ICPSR holds data from the first three collections, and information about these can be found on the series description page. Data collected in 2007 are available through the China Institute for Income Distribution.

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.

The overall goal of Wave VI was to better understand life course trajectories, determinants, and consequences of critical dimensions of aging, health, and health disparities among U.S. early midlife adults. Data collection took place from 2022 to 2025, with participants between the ages of 39 and 51, with an average age of 44. Beyond longitudinal survey measures, newly added questions included those on cumulative stress, discrimination, despair, work-life balance, memory, physical limitations, and caregiving. Continuing from previous waves, home exams collected physical measurements and biospecimens with most of the same measures as Wave V.

The National Survey of American Life Adolescent Supplement (NSAL-A), 2001-2004, was designed to estimate the lifetime-to-date and current prevalence, age-of-onset distributions, course, and comorbidity of DSM-IV disorders among African American and Caribbean adolescents in the United States; to identify risk and protective factors for the onset and persistence of these disorders; to describe patterns and correlates of service use for these disorders; and to lay the groundwork for subsequent follow-up studies that can be used to identify early expressions of adult mental disorders. In addition and similar to the NSAL adult dataset (Collaborative Psychiatric Epidemiology Surveys (CPES), 2001-2003 [United States] (ICPSR 20240)), the adolescent dataset contains detailed measures of health; social conditions; stressors; distress; racial identity; subjective, neighborhood conditions; activities and school; media; and social and psychological protective and risk factors. Numerous variables from the adult dataset have been merged into the adolescent dataset, as the NSAL adult and adolescent respondents reside in the same households. Some of these variables apply to the entire household (i.e. region, urbanicity, and family income), while others apply specifically to the NSAL adult respondent living in the adolescent's household (i.e. adult years of education, adult marital status, and adult nativity [foreign-born vs. US born]). The immigration measures were asked of Caribbean black adult respondents only. No comparable measures assess the immigration and generational status of the Caribbean black adolescent respondents. The adult dataset measures are merged into the adolescent dataset to assist in approximating these measures for adolescent respondents. The NSAL adolescent dataset also includes variables for other non-core and experimental disorders. These include tobacco use/nicotine dependence, premenstrual syndrome, minor depression, recurrent brief depression, hypomania, and hypomania sub-threshold. Demographic variables include age, race and ethnicity, ancestry or national origins, height, weight, marital status, income, and education level.

The Social Capital and Children's Development data were collected in a study of the causal effects of social capital on levels and inequalities of children's social and cognitive development during the early elementary years. The study included 52 schools in Phoenix and San Antonio, including 3,084 first graders and their families, and over 200 teachers, with half the schools randomly selected for the intervention and half serving as controls. Children from low-income Latino families were a special focus of the study. The experimental design of this study allowed for testing of the causal role of social capital. Social capital here refers to trust and shared expectations embedded in social networks of parents, teachers, and children. For young children, social capital operates primarily through their relationships with their parents, enhancing development through mechanisms of social support and social control.

The research design was experimental: social capital was manipulated through a well-tested randomized intervention, Families and Schools Together (FAST), that enhanced social capital among parents, teachers, and children through an intensive after-school program and a 2-year follow-up program. FAST is intended to reduce parental isolation, enhance family engagement with schools, and strengthen family functioning; that is, to increase social capital between families and schools, among families, and within families to improve children's education and life-long outcomes. Key aspects of child development were assessed, including (a) social skills and problem behavior from standardized behavioral ratings by parents and teachers, and (b) grade retention, attendance rates, and third-grade reading and mathematics scores from school records. Social capital was measured with repeated surveys of teachers and parents that address the extent of social networks, parent involvement, trust, and shared expectations among parents, between parents and schools, and between parents and children. Demographic variables of this study include native language, years in the United States, date of birth/age, race/ethnicity, gender, and household composition.