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The 2010 Census Production Settings Demographic and Housing Characteristics Demonstration Noisy Measurement File (2023-04-03) is an intermediate output of the 2020 Census Disclosure Avoidance System (DAS) TopDown Algorithm (TDA) (as described in Abowd, J. et al [2022], and implemented in DAS 2020 Redistricting Production Code). The NMF was produced using the official "production settings," the final set of algorithmic parameters and privacy-loss budget allocations, that were used to produce the 2020 Census Redistricting Data (P.L. 94-171) Summary File and the 2020 Census Demographic and Housing Characteristics File. The NMF consists of the full set of privacy-protected statistical queries (counts of individuals or housing units with particular combinations of characteristics) of confidential 2010 Census data relating to the 2010 Demonstration Data Products Suite - Redistricting and Demographic and Housing Characteristics File - Production Settings (2023-04-03). These statistical queries, called "noisy measurements" were produced under the zero-Concentrated Differential Privacy framework (Bun, M. and Steinke, T [2016]; see also Dwork C. and Roth, A. [2014]) implemented via the discrete Gaussian mechanism (Cannone C., et al., [2023]), which added positive or negative integer-valued noise to each of the resulting counts. The noisy measurements are an intermediate stage of the TDA prior to the post-processing the TDA then performs to ensure internal and hierarchical consistency within the resulting tables. The Census Bureau has released these 2010 Census demonstration data to enable data users to evaluate the expected impact of disclosure avoidance variability on 2020 Census data. The 2010 Census Production Settings Demographic and Housing Characteristics (DHC) Demonstration Noisy Measurement File (2023-04-03) has been cleared for public dissemination by the Census Bureau Disclosure Review Board (CBDRB-FY22-DSEP-004).

The 2010 Census Production Settings Demographic and Housing Characteristics Demonstration Noisy Measurement File (2023-04-03) includes zero-Concentrated Differentially Private (zCDP) (Bun, M. and Steinke, T [2016]) noisy measurements, implemented via the discrete Gaussian mechanism. These are estimated counts of individuals and housing units included in the 2010 Census Edited File (CEF), which includes confidential data initially collected in the 2010 Census of Population and Housing. The noisy measurements included in this file were subsequently post-processed by the TopDown Algorithm (TDA) to produce the 2010 Census Production Settings Privacy-Protected Microdata File - Redistricting (P.L. 94-171) and Demographic and Housing Characteristics File (2023-04-03) (Demonstration Data Products Suite/2023-04-03/). As these 2010 Census demonstration data are intended to support study of the design and expected impacts of the 2020 Disclosure Avoidance System, the 2010 CEF records were pre-processed before application of the zCDP framework. This pre-processing converted the 2010 CEF records into the input-file format, response codes, and tabulation categories used for the 2020 Census, which differ in substantive ways from the format, response codes, and tabulation categories originally used for the 2010 Census.

The NMF provides estimates of counts of persons in the CEF by various characteristics and combinations of characteristics including their reported race and ethnicity, whether they were of voting age, whether they resided in a housing unit or one of 7 group quarters types, and their census block of residence after the addition of discrete Gaussian noise (with the scale parameter determined by the privacy-loss budget allocation for that particular query under zCDP). Noisy measurements of the counts of occupied and vacant housing units by census block are also included. Lastly, data on constraints--information into which no noise was infused by the Disclosure Avoidance System (DAS) and used by the TDA to post-process the noisy measurements into the 2010 Census Production Settings Privacy-Protected Microdata File - Redistricting (P.L. 94-171) and Demographic and Housing Characteristics File (2023-04-03) --are provided.

These data are available for download (i.e. not restricted access). Due to their size, they must be downloaded through the link on this metadata page and not through the standard ICPSR download. The link will take you to the Globus site where these data are housed. A README file is located in the Globus repository. Please refer to that for pertinent information. The Globus holding site requires users to create an account to access these data. Accounts can be created through existing institutional access and by personal access. Please see the Globus "How to get Started" page for more information.

The 2016 Latino Immigrant National Election Study (LINES) is a panel study of Latino foreign-born residents of the United States, with telephone surveys of nationally representative samples of respondents fielded in 3 waves over 2016-2017.

The first survey in the 2016 LINES took place during the general election campaign (August and September of 2016). Interviews (N = 1,800) were conducted in English and Spanish, although nearly all respondents opted for Spanish. Because many of the initial telephone numbers dialed were either out of service or otherwise unusable, the American Association for Public Opinion Research (AAPOR) "Response Rate 1" calculation is low (.034). However, in cases when an eligible immigrant was identified based on the initial screening questions, only 12 percent opted not to complete the survey. On average, an interview that fall lasted approximately 25 minutes.

After the 2016 election, 576 immigrants took part in the second survey wave, which was fielded during the presidential transition period (a 32 percent re-contact rate). At this time, an additional fresh sample of 260 Latino immigrants was added to the study, again to help gauge and ameliorate any potential respondent attrition biases. Finally, in the summer of 2017 (July through early-September), a third wave was conducted, with all 1,800 immigrants from the pre-election baseline survey being eligible for interviewing. In this period, 31 percent of these immigrants (N = 554) were surveyed; this included 321 respondents who had taken part in the second wave and 233 who had not. To increase the sample size at this time and address attrition over time, 500 fresh immigrants were surveyed. In total, 2,560 immigrants took part in the 2016-2017 LINES: 1,800 from before the election, 260 during the presidential transition period, and 300 in the summer of 2017.

The questionnaire instrumentation used in the study was largely adapted from item wordings in the 2012 American National Election Study (ANES). The survey focuses on immigrant civic engagement and political socialization, including items on immigrant attitudes, opinions and electoral and non-electoral political behavior.

The 2020 Census Demographic and Housing Characteristics Noisy Measurement File is an intermediate output of the 2020 Census Disclosure Avoidance System (DAS) TopDown Algorithm (TDA) (as described in Abowd, J. et al [2022], and implemented in DAS_2020_DHC_Production_Code/das_decennial/programs/engine/primitives.py at main uscensusbureau/DAS_2020_DHC_Production_Code (github.com) The 2020 Census Demographic and Housing Characteristics Noisy Measurement File includes zero-Concentrated Differentially Private (zCDP) (Bun, M. and Steinke, T [2016]) noisy measurements, implemented via the discrete Gaussian mechanism (Cannone C., et al., [2023] ), which added positive or negative integer-valued noise to each of the resulting counts. These are estimated counts of individuals and housing units included in the 2020 Census Edited File (CEF), which includes confidential data collected in the 2020 Census of Population and Housing.

The noisy measurements included in this file were subsequently post-processed by the TopDown Algorithm (TDA) to produce the Census Demographic and Housing Characteristics Summary File. In addition to the noisy measurements, constraints based on invariant calculations --- counts computed without noise --- are also included (with the exception of the state-level total populations, which can be sourced separately from data.census.gov).

The Noisy Measurement File was produced using the official "production settings," the final set of algorithmic parameters and privacy-loss budget allocations that were used to produce the 2020 Census Redistricting Data (P.L. 94-171) Summary File and the 2020 Census Demographic and Housing Characteristics File.

The noisy measurements are produced in an early stage of the TDA. Afterward, these noisy measurements are post-processed to ensure internal and hierarchical consistency within the resulting tables. The Census Bureau has released these noisy measurements to enable data users to evaluate the impact of disclosure avoidance variability on 2020 Census data. The 2020 Census Demographic and Housing Characteristics (DHC) Noisy Measurement File has been cleared for public dissemination by the Census Bureau Disclosure Review Board (CBDRB-FY22-DSEP-004).

These data are available for download (i.e. not restricted access). Due to their size, they must be downloaded through the link on this metadata page and not through the standard ICPSR download. The link will take you to the Globus site where these data are housed. A README file is located in the Globus repository. Please refer to that for pertinent information.

The Globus holding site requires users to create an account to access these data. Accounts can be created through existing institutional access and by personal access.

Please see the Globus "How to get Started" page for more information.

The 2020 Census Redistricting Data (P.L. 94-171) Noisy Measurement File is an intermediate output of the 2020 Census Disclosure Avoidance System (DAS) TopDown Algorithm (TDA) (as described in Abowd, J. et al [2022] https://doi.org/10.1162/99608f92.529e3cb9, and implemented in the DAS 2020 Redistricting Production Code). The 2020 Redistricting NMF was an intermediate output of the DAS during the execution of the algorithm to produce the 2020 Census Redistricting Data (P.L. 94-171) Summary File. The NMFs are intermediate privacy-protected outputs of the DAS; they were generated using the Census Bureau's implementation of the Discrete Gaussian Mechanism, calibrated to satisfy zero-Concentrated Differential Privacy with bounded neighbors. The NMF values, called "noisy measurements" are the output of applying the Discrete Gaussian Mechanism to counts from the 2020 Census Edited File (CEF). They are generally inconsistent with one another (for example, in a county composed of two tracts, the noisy measurement for the county's total population may not equal the sum of the noisy measurements of the two tracts' total population), and frequently negative (especially when the population being measured was small), but are integer-valued. The NMF was later post-processed as part of the DAS code to take the form of microdata and to satisfy various constraints. The NMF documented here contains both the noisy measurements themselves as well as the data needed to represent the DAS constraints; thus, the NMF could be used to reproduce the steps taken by the DAS code to produce microdata from the noisy measurements by applying the production code base.

The 2020 Census Redistricting Data (P.L. 94-171) Noisy Measurement File includes zero-Concentrated Differentially Private (zCDP) (Bun, M. and Steinke, T [2016]) noisy measurements, implemented via the discrete Gaussian mechanism. These are estimated counts of individuals and housing units included in the 2020 Census Edited File (CEF), which includes confidential data initially collected in the 2020 Census of Population and Housing. The noisy measurements included in this file were subsequently post-processed by the TopDown Algorithm (TDA) to produce the 2020 Census Redistricting Data (P.L. 94-171) Summary File.

The NMF provides estimates of counts of persons in the CEF by various characteristics and combinations of characteristics including their reported race and ethnicity, whether they were of voting age, whether they resided in a housing unit or one of 7 group quarters types, and their census block of residence after the addition of discrete Gaussian noise (with the scale parameter determined by the privacy-loss budget allocation for that particular query under zCDP). Noisy measurements of the counts of occupied and vacant housing units by census block are also included. Lastly, data on constraints--information into which no noise was infused by the Disclosure Avoidance System (DAS) and used by the TDA to post-process the noisy measurements into the 2020 Census Redistricting Data (P.L. 94-171) Summary File --are provided.

These data are available for download (i.e. not restricted access). Due to their size, they must be downloaded through the link on this metadata page and not through the standard ICPSR download. The link will take you to the Globus site where these data are housed. A README file is located in the Globus repository. Please refer to that for pertinent information.

The Globus holding site requires users to create an account to access these data. Accounts can be created through existing institutional access and by personal access.

Please see the Globus "How to get Started" page for more information.

This survey was designed to investigate whether having psychological connections to particular groups (ex: racial, ethnic, and national origin groups) and perceptions of discrimination lead to alienation from the structure and operation of representative democracy in the United States. The data allow for comparative ethnic analyses of people's views regarding the representative-constituent relationship and of the conditions under which group identifications and perceptions of discrimination matter.

The survey includes oversamples of Black, Latino, and Asian respondents. A Spanish version of the survey was available. Demographic information retrieved about respondents include age, race/ethnicity, gender, education (highest degree received), employment status, marital status, religion, household size and income. In addition, ancestry was assessed with the question, "From what countries or parts of the world did your ancestors come?" Respondents also reported United States citizenship status, primary home language, and nationality. Variables focusing on respondent perceived representation in the United States include political ideology and political party affiliation.

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index.

The CE program is comprised of two separate components (each with its own survey questionnaire and independent sample), the Diary Survey and the quarterly Interview Survey (ICPSR 34441). This data collection contains the Diary Survey data, which was designed to obtain data on frequently purchased smaller items, including food and beverages (both at home and in food establishments), gasoline, housekeeping supplies, tobacco, nonprescription drugs, and personal care products and services. Each consumer unit (CU) recorded its expenditures in a diary for two consecutive 1-week periods. Although the diary was designed to collect information on expenditures that could not be easily recalled over time, respondents were asked to report all expenses (except overnight travel) that the CU incurred during the survey week.

The microdata in this collection are available as SAS, SPSS, and STATA datasets or ASCII comma-delimited files. The 2011 Diary release contains five sets of data files (FMLY, MEMB, EXPN, DTBD, DTID) and three processing files. The FMLY, MEMB, EXPN, DTBD, and DTID files are organized by the quarter of the calendar year in which the data were collected. There are four quarterly datasets for each of these files.

The FMLY files contain CU characteristics, income, and summary level expenditures; the MEMB files contain member characteristics and income data; the EXPN files contain detailed weekly expenditures at the Universal Classification Code (UCC) level; the DTBD files contains the CU's reported annual income values or the mean of the five imputed income values in the multiple imputation method; and the DTID files contain the five imputed income values. Please note that the summary level expenditure and income information on the FMLY files permits the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files.

The three processing files enhance computer processing and tabulation of data, and provide descriptive information on item codes. The three processing files are: (1) an aggregation scheme file used in the published consumer expenditure tables (DSTUB), (2) a UCC file that contains UCCs and their abbreviated titles, identifying the expenditure, income, or demographic item represented by each UCC, and (3) a sample program file that contains the computer program used in Section VII. "MICRODATA VERIFICATION AND ESTIMATION METHODOLOGY" of the Diary User Guide. The processing files are further explained in Section III.F.6. "PROCESSING FILES" of the same User Guide documentation. There is also a second user guide, User's Guide to Income Imputation in the CE, which includes information on how to appropriately use the imputed income data.

Demographic and family characteristics data include age, sex, race, marital status, and CU relationships for each CU member. Income information, such as wage, salary, unemployment compensation, child support, and alimony, as well as information on the employment of each CU member age 14 and over was also collected.

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index.

The CE program is comprised of two separate components (each with its own questionnaire and independent sample), the quarterly Interview Survey and the Diary Survey (ICPSR 34442). This data collection contains the quarterly Interview Survey data, which was designed to collect data on major items of expense which respondents could be expected to recall for 3 months or longer. These included relatively large expenditures, such as those for property, automobiles, and major durable goods, and those that occurred on a regular basis, such as rent or utilities. The Interview Survey does not collect data on expenses for housekeeping supplies, personal care products, and nonprescription drugs, which contribute about 5 to 15 percent of total expenditures.

The microdata in this collection are available as SAS, SPSS, and STATA datasets or ASCII comma-delimited files. The 2011 Interview Survey release contains seven groups of Interview data files (FMLY, MEMB, MTBI, ITBI, ITII, FPAR, and MCHI), 50 EXPN files, and processing files.

The FMLY, MEMB, MTBI, ITBI, and ITII files are organized by the calendar quarter of the year in which the data were collected. There are five quarterly datasets for each of these files, running from the first quarter of 2011 through the first quarter of 2012. The FMLY file contains consumer unit (CU) characteristics, income, and summary level expenditures; the MEMB file contains member characteristics and income data; the MTBI file contains expenditures organized on a monthly basis at the Universal Classification Code (UCC) level; the ITBI file contains income data converted to a monthly time frame and assigned to UCCs; and the ITII file contains the five imputation variants of the income data converted to a monthly time frame and assigned to UCCs.

The FPAR and MCHI datasets are grouped as 2-year datasets (2010 and 2011), plus the first quarter of the 2012 and contain paradata about the Interview survey. The FPAR file contains CU level data about the Interview survey, including timing and record use. The MCHI file contains data about each interview contact attempt, including reasons for refusal and times of contact. Both FPAR and MCHI files contain five quarters of data.

The EXPN files contain expenditure data and ancillary descriptive information, often not available on the FMLY or MTBI files, in a format similar to the Interview questionnaire. In addition to the extra information available on the EXPN files, users can identify distinct spending categories easily and reduce processing time due to the organization of the files by type of expenditure. Each of the 50 EXPN files contains five quarters of data, directly derived from their respective questionnaire sections.

The processing files enhance computer processing and tabulation of data, and provide descriptive information on item codes. The processing files are: (1) aggregation scheme files used in the published consumer expenditure survey interview tables and integrated tables (ISTUB and INTSTUB), (2) a UCC file that contains UCCs and their abbreviated titles, identifying the expenditure, income, or demographic item represented by each UCC, (3) a vehicle make file (CAPIVEHI), and (4) files containing sample programs. The processing files are further explained in the Interview User Guide, Section III.G.8. "PROCESSING FILES." There is also a second user guide, User's Guide to Income Imputation in the CE, which includes information on how to appropriately use the imputed income data.

Demographic and family characteristics data include age, sex, race, marital status, and CU relationships for each CU member. Income information, such as wage, salary, unemployment compensation, child support, and alimony, as well as information on the employment of each CU member age 14 and over was also collected.

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers, including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index.

The CE program is comprised of two separate components (each with its own survey questionnaire and independent sample), the Diary Survey and the quarterly Interview Survey (ICPSR 36237). This data collection contains the Diary Survey component, which was designed to obtain data on frequently purchased smaller items, including food, housing, apparel and services, transportation, entertainment, and out-of-pocket health care costs. Each consumer unit (CU) recorded its expenditures in a diary for two consecutive 1-week periods. Although the diary was designed to collect information on expenditures that could not be easily recalled over time, respondents were asked to report all expenses (except overnight travel) that the CU incurred during the survey week.

The 2013 Diary Survey release contains five sets of data files (FMLD, MEMD, EXPD, DTBD, DTID), and one processing file (DSTUB). The FMLD, MEMD, EXPD, DTBD, and DTID files are organized by the quarter of the calendar year in which the data were collected. There are four quarterly datasets for each of these files.

The FMLD files contain CU characteristics, income, and summary level expenditures; the MEMD files contain member characteristics and income data; the EXPD files contain detailed weekly expenditures at the Universal Classification Code (UCC) level; the DTBD files contain the CU's reported annual income values or the mean of the five imputed income values in the multiple imputation method; and the DTID files contain the five imputed income values. Please note that the summary level expenditure and income information on the FMLD files permit the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files.

The DSTUB file provides the aggregation scheme used in the published consumer expenditure tables. The DSTUB file is further explained in Section III.F.6. "Processing Files" of the Diary Survey Users' Guide. A second documentation guide, the "Users' Guide to Income Imputation," includes information on how to appropriately use the imputed income data.

Demographic and family characteristics data include age, sex, race, marital status, and CU relationships for each CU member. Income information was also collected, such as wage, salary, unemployment compensation, child support, and alimony, as well as information on the employment of each CU member age 14 and over.

The unpublished integrated CE data tables produced by the BLS are available to download through NADAC (click on "Other" in the Dataset(s) section). The tables show average and percentile expenditures for detailed items, as well as the standard error and coefficient of variation (CV) for each spending estimate. The BLS unpublished integrated CE data tables are provided as an easy-to-use tool for obtaining spending estimates. However, users are cautioned to read the BLS explanatory letter accompanying the tables. The letter explains that estimates of average expenditures on detailed spending items (such as leisure and art-related categories) may be unreliable due to so few reports of expenditures for those items.

These data include county-level, net migration estimates by five-year age cohorts and sex, and by race and Hispanic origin, for the intercensal period from 2000 to 2010. The estimates were prepared using a vital statistics version of the forward cohort residual method. These estimates (and the net migration rates derivable from them) extend the set of decennial estimates of net migration that have been produced following each decennial census beginning with 1960 (net migration for the 1950s: Bowles and Tarver, 1965; 1960s: Bowles, Beale and Lee, 1975; 1970s: White, Mueser and Tierney, 1987; 1980s: Fuguitt, Beale, and Voss 2010; and 1990s: Voss, McNiven, Hammer, Johnson and Fuguitt, 2004).

Further information about this project is available on the Net Migration Patterns for US Counties Web site.

This randomized controlled trial evaluated a culturally appropriate intervention to improve the recognition and treatment of depression among Asian and Latino American primary care patients at Massachusetts General Hospital (MGH), using a culturally focused psychiatric (CFP) consultation with a team of mental health providers who were bilingual/bicultural, trained in culturally competent techniques, and familiar with the cultures and languages of the patients served. Targeted minority patients who screened positive for clinical depression were eligible to participate in the trial. The intervention patients were offered the CFP consultation at baseline and, if eligible, received the CFP patient toolkit as part of their treatment. The toolkit provided psychoeducation and tools for managing depression as well as information on community resources. The usual care patients were offered standard referrals to MGH mental health resources.

Questionnaires were administered to the patients at screening, baseline, two-week follow-up, and six month follow-up. The screening questionnaires included the two-item Public Health Questionnaire (PHQ-2) and demographic questions. Assessment measures administered to the intervention patients at baseline included the Mini International Neuropsychiatric Interview (MINI), Quick Inventory of Depressive Symptomatology-Self Rated Scale (QIDS-SR 16), Global Assessment of Functioning (GAF), Schwartz Outcome Scale (SOS-10), and a demographic questionnaire and resource utilization questionnaire. At six month follow-up, the intervention arm was administered a resource utilization questionnaire, patient satisfaction questionnaire (Treatment Satisfaction Scale), qualitative interview, and the QIDS-SR 16 and SOS-10. The SOS-10 was also administered to the intervention patients at two-week follow-up. In the usual care arm, the QIDS-SR 16 and resource utilization questionnaire was administered at baseline and six months, the qualitative interview at six months, and the demographic questionnaire at baseline or six-months. There was no two-week assessment for the usual care patients. Electronic medical record review was used for both arms at baseline and six months, as needed. In addition, qualitative interviews were conducted with project and practice staff at the end of the study.

The data file includes the responses to the questionnaires and variables describing the CFP consultation assessment (DSM-IV Axis I, II, III, IV, and V diagnoses), treatment recommendations made to the patients' primary care physicians (PCPs) after the CFP consultation, and study staff contacts with the patients' PCPs and mental health providers. ICPSR did not receive the data from the qualitative interviews or electronic medical record reviews.

The Future of Families and Child Wellbeing Study (FFCWS, formerly known as the Fragile Families and Child Wellbeing Study) follows a cohort of nearly 5,000 children born in large, U.S. cities between 1998 and 2000. The study oversampled births to unmarried couples; and, when weighted, the data are representative of births in large U.S. cities at the turn of the century. The FFCWS was originally designed to address four questions of great interest to researchers and policy makers:

1. What are the conditions and capabilities of unmarried parents, especially fathers?
2. What is the nature of the relationships between unmarried parents?
3. How do children born into these families fare?
4. How do policies and environmental conditions affect families and children?

The FFCWS consists of interviews with mothers, fathers, and/or primary caregivers at birth and again when children are ages 1, 3, 5, 9, 15, and 22. The parent interviews collected information on attitudes, relationships, parenting behavior, demographic characteristics, health (mental and physical), economic and employment status, neighborhood characteristics, and program participation. Beginning at age 9, children were interviewed directly (either during the home visit or on the telephone). The direct child interviews collected data on family relationships, home routines, schools, peers, and physical and mental health, as well as health behaviors.

A collaborative study of the FFCWS, the In-Home Longitudinal Study of Pre-School Aged Children (In-Home Study) collected data from a subset of the FFCWS Core respondents at the Year 3 and 5 follow-ups to ask how parental resources in the form of parental presence or absence, time, and money influence children under the age of 5. The In-Home Study collected information on a variety of domains of the child's environment, including: the physical environment (quality of housing, nutrition and food security, health care, adequacy of clothing and supervision) and parenting (parental discipline, parental attachment, and cognitive stimulation). In addition, the In-Home Study also collected information on several important child outcomes, including anthropometrics, child behaviors, and cognitive ability. This information was collected through interviews with the child's primary caregiver, and direct observation of the child's home environment and the child's interactions with his or her caregiver.

Similar activities were conducted during the Year 9 follow-up. At the Year 15 follow-up, a condensed set of home visit activities were conducted with a subsample of approximately 1,000 teens. Teens who participated in the In-Home Study were also invited to participate in a Sleep Study and were asked to wear an accelerometer on their non-dominant wrist for seven consecutive days to track their sleep (Sleep Actigraphy Data) and that day's behaviors and mood (Daily Sleep Actigraphy and Diary Survey Data).

An additional collaborative study collected data from the child care provider (Year 3) and teacher (Years 9 and 15) through mail-based surveys. Saliva samples were collected at Year 9 and 15 (Biomarker file and Polygenic Scores). The Study of Adolescent Neural Development (SAND) COVID Study began data collection in May 2020 following the onset of the COVID-19 pandemic. It included online surveys with the young adult and their primary caregiver.

The FFCWS began its seventh wave of data collection in October 2020, around the focal child's 22nd birthday. Data collection and interviews continued through January 2024. The Year 22 wave included a young adult (YA) survey with the original focal child and a primary caregiver (PCG) survey. Data were also collected on the children of the original focal child (referred to as Generation 3, or G3).

In 2017, the FFCWS team announced the Fragile Families (FF) Challenge, a collaborative effort in which participants were tasked with using machine learning methods and FFCWS data (Baseline to Year 9) to build a model that would predict six key outcomes at Year 15. Materials used in the FF Challenge have been archived in this collection.

Documentation for these files is available on the FFCWS website under Data and Documentation. For details of updates made to the FFCWS data files, please see the project's Data Alerts page.

Data collection for the Future of Families and Child Wellbeing Study was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) of the National Institutes of Health under award numbers R01HD36916, R01HD39135, and R01HD40421, as well as a consortium of private foundations.

Below is the citation for use of the FFCWS data accessed through ICPSR. For information on additional citation requirements when using FFCWS in publications, please refer to this FAQ on the FFCWS project site.

The study is comprised of interviews from 227 Hispanic males aged 45 or older living in the area of Houston, Texas to address the gaps in knowledge on the social factors and health consequences of injection heroin use among aging Mexican American males. Specifically, the study investigated how the life course transitions of incarceration and drug treatment and drug abuse and family trajectories affect both the heroin career status and health consequences of these aging Mexican American men.

The study used a cross-sectional, field-intensive outreach methodology augmented with respondent-driven sampling. Recruitment was focused in two Houston neighborhoods that are predominantly Mexican American areas with high rates of crime, poverty, and psychosocial challenges. Trained Outreach Specialists familiar with these communities identified community gatekeepers and gained their trust through continued presence in the community and ongoing dialogue about the study. These gatekeepers then helped identify individuals meeting the inclusion criteria: Mexican American men aged 45 years or older with a history of injection drug use for at least 3 years. The men were then classified into one of three groups: current injectors (current group), former injectors not in treatment (former group), or former injectors currently enrolled in methadone maintenance treatment programs (MMTP group).

The second part is a second survey asking questions about social networks the respondent participates in. Questions ask the respondent to answer on one individual in their network and answer questions about that person and their interaction with them. Questions include basic demographics, history injecting drugs and sexual contact with the person.

The Hispanic EPESE provides data on risk factors for mortality and morbidity in older Mexican Americans in order to contrast how these factors operate differently than in non-Hispanic Whites, African Americans, and other major ethnic groups.

The Wave 9 dataset comprises the eighth follow-up of the baseline Hispanic Established Populations for the Epidemiologic Studies of the Elderly, 1993-1994: [Arizona, California, Colorado, New Mexico, and Texas] (ICPSR 2851). The baseline Hispanic EPESE collected data on a representative sample of community-dwelling Mexican Americans, aged 65 years and older, residing in the five Southwestern states of Arizona, California, Colorado, New Mexico, and Texas.

The public-use data covers demographic characteristics (age, sex, type of Hispanic race, income, education, marital status, number of children, employment, and religion), height, weight, social and physical functioning, chronic conditions, related health problems, health behaviors, self-reported use of dental, hospital, and nursing home services, and depression. Subsequent follow-ups allow examination of the predictors of mortality, changes in health outcomes, institutionalization, changes in living arrangements, as well as changes in life situations and quality of life.

During this 9th Wave (Dataset 1), 2016, 480 re-interviews were conducted either in person or by proxy, with 283 of the original respondents interviewed in 1993-1994. This Wave also includes 197 re-interviews from the 902 new respondents added at Wave 5 in 2004-2005. All respondents were aged 85 and over at Wave 9.

The Wave 9 Informant Interviews dataset (Dataset 2) includes data from interviews with 460 respondents who provided information on themselves as well as the older respondents. The older respondents were asked to provide the name and contact information of the person they are "closer to" or they "depend on the most for help." These INFORMANTS, many of whom provide caregiving support to the older respondents, were contacted, and interviewed regarding the health, function, social situation, finances, and general well-being of the older Hispanic EPESE respondents. Information was also collected on the informant's health, function, and caregiver responsibilities and burden. This dataset includes information from the 460 informants, more than two-thirds of whom were children of the respective respondents. Thus, there are 460 respondent-informant dyads that provide opportunities for caregiving research.

The 2008 election offers a rare opportunity to analyze a significant event in American history - the election of the first African American president. Because the longitudinal panel series began in 2004, prior to the emergence of President Obama as a serious political candidate and nominee, the results from these surveys provide a rare vehicle for comparing data over time on important demographic, political, and, of particular interest given President Obama's racial background, racial and ethnic issues related to vote choice and political behavior. The wealth of data obtained from this survey will benefit scholars for many years to come.

This report provides a general overview of some of the key findings from the 2008 data collection. Topics covered include: demographic information of the population, work status, home ownership, political ideology, party identification, presidential choice, race relations, feeling thermometer data for a variety of political figures and relevant groups or organizations, and current events such as the Iraq War and same-sex marriage. Because differences among the racial and ethnic groups surveyed in this study are of political significance (Whites, African Americans, Hispanics, Asian Americans, and Caribbean Blacks), much of the data presented here is disaggregated by racial and ethnic group.

This study contains demographic variables for the the Sacramento Area Latino Study on Aging (SALSA) Series and can be used with ICPSR studies 22760, 29321, 29322, 29323. Demographic variables include gender, primary language, country of origin, state of birth, cause of death, 2000 census tract codes, birth date, date of death, and age given at follow-up visits.

About SALSA: The Sacramento Area Latino Study on Aging (SALSA Study) project tracked the incidence of physical and cognitive impairment as well as dementia and cardiovascular diseases in elderly Latinos in the Sacramento, California, region. The SALSA project aimed to assess cognitive, physical, and social functions, which include the ability to follow instructions, to perform certain movements, and to interact with others. The study explored the effects that cultural, nutritional, social, and cardiovascular risk factors have on overall health and dementia, and examined the association between diabetes and functional status.

The Sacramento Area Latino Study on Aging (SALSA Study) project tracked the incidence of physical and cognitive impairment as well as dementia and cardiovascular diseases in elderly Latinos in the Sacramento, California, region. The SALSA project aimed to assess cognitive, physical, and social functions, which include the ability to follow instructions, to perform certain movements, and to interact with others. The study explored the effects that cultural, nutritional, social, and cardiovascular risk factors have on overall health and dementia, and examined the association between diabetes and functional status. This study contains the neuroclinical exam data from the SALSA project. Demographic information includes age given at follow-up visits, country of birth, language, religion, marital status, educational level, occupation, household income, and size of household.

The Sacramento Area Latino Study on Aging (SALSA Study) was a longitudinal cohort study of 1,789 community-dwelling Mexican Americans residing in California's Sacramento Valley who were aged 60-101 years at baseline in 1998-1999. Participants were followed every 12-15 months via home visits that included clinical and cognitive assessments. A semiannual phone call was made to obtain updates on medications, health events, and some sociodemographic risk factors. This study, Semi-Annual Phone Call Data, contains data from the six-month follow-up calls of the SALSA project.

The SALSA project tracked the incidence of physical and cognitive impairment as well as dementia and cardiovascular diseases in elderly Latinos in the Sacramento, California region. The SALSA project aimed to assess cognitive, physical, and social functions, which include the ability to follow instructions, to perform certain movements, and to interact with others. The project explored the effects that cultural, nutritional, social, and cardiovascular risk factors have on overall health and dementia, and examined the association between diabetes and functional status.

Demographic information collected in these data includes language and age given at follow-up visits.