The following datasets are based on the children and youth (under age 21) beneficiary population and consist of aggregate Mental Health Service data derived from Medi-Cal claims, encounter, and eligibility systems. These datasets were developed in accordance with California Welfare and Institutions Code (WIC) § 14707.5 (added as part of Assembly Bill 470 on 10/7/17). Please contact BHData@dhcs.ca.gov for any questions or to request previous years’ versions of these datasets. Note: The Performance Dashboard AB 470 Report Application Excel tool development has been discontinued. Please see the Behavioral Health reporting data hub at https://behavioralhealth-data.dhcs.ca.gov/ for access to dashboards utilizing these datasets and other behavioral health data.

About this dataset

Context

The dataset tabulates the Many population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Many. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 1,228 (55.77% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Many population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Many is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Many is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Many Population by Age. You can refer the same here

Children And Adults

## Overview

Children And Adults is a dataset for object detection tasks - it contains Chilren And Adults annotations for 450 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Child and Adult Care Food Participation plays a vital role in improving the quality of day care for children and elderly adults by making care more affordable for many low-income families. Through CACFP, nearly 3 million children and 90,000 adults receive nutritious meals and snacks each day as part of the day care they receive. The data set contains participation; meals served, and cash payments to states.

About this dataset

Context

The dataset tabulates the Clifton population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Clifton. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 55,513 (62.20% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Clifton population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Clifton is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Clifton is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Clifton Population by Age. You can refer the same here

The WIC Infant and Toddler Feeding Practices Study–2 (WIC ITFPS-2) (also known as the “Feeding My Baby Study”) is a national, longitudinal study that captures data on caregivers and their children who participated in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) around the time of the child’s birth. The study addresses a series of research questions regarding feeding practices, the effect of WIC services on those practices, and the health and nutrition outcomes of children on WIC. Additionally, the study assesses changes in behaviors and trends that may have occurred over the past 20 years by comparing findings to the WIC Infant Feeding Practices Study–1 (WIC IFPS-1), the last major study of the diets of infants on WIC. This longitudinal cohort study has generated a series of reports. These datasets include data from caregivers and their children during the prenatal period and during the children’s first five years of life (child ages 1 to 60 months). A full description of the study design and data collection methods can be found in Chapter 1 of the Second Year Report (https://www.fns.usda.gov/wic/wic-infant-and-toddler-feeding-practices-st...). A full description of the sampling and weighting procedures can be found in Appendix B-1 of the Fourth Year Report (https://fns-prod.azureedge.net/sites/default/files/resource-files/WIC-IT...). Processing methods and equipment used Data in this dataset were primarily collected via telephone interview with caregivers. Children’s length/height and weight data were objectively collected while at the WIC clinic or during visits with healthcare providers. The study team cleaned the raw data to ensure the data were as correct, complete, and consistent as possible. Study date(s) and duration Data collection occurred between 2013 and 2019. Study spatial scale (size of replicates and spatial scale of study area) Respondents were primarily the caregivers of children who received WIC services around the time of the child’s birth. Data were collected from 80 WIC sites across 27 State agencies. Level of true replication Unknown Sampling precision (within-replicate sampling or pseudoreplication) This dataset includes sampling weights that can be applied to produce national estimates. A full description of the sampling and weighting procedures can be found in Appendix B-1 of the Fourth Year Report (https://fns-prod.azureedge.net/sites/default/files/resource-files/WIC-IT...). Level of subsampling (number and repeat or within-replicate sampling) A full description of the sampling and weighting procedures can be found in Appendix B-1 of the Fourth Year Report (https://fns-prod.azureedge.net/sites/default/files/resource-files/WIC-IT...). Study design (before–after, control–impacts, time series, before–after-control–impacts) Longitudinal cohort study. Description of any data manipulation, modeling, or statistical analysis undertaken Each entry in the dataset contains caregiver-level responses to telephone interviews. Also available in the dataset are children’s length/height and weight data, which were objectively collected while at the WIC clinic or during visits with healthcare providers. In addition, the file contains derived variables used for analytic purposes. The file also includes weights created to produce national estimates. The dataset does not include any personally-identifiable information for the study children and/or for individuals who completed the telephone interviews. Description of any gaps in the data or other limiting factors Please refer to the series of annual WIC ITFPS-2 reports (https://www.fns.usda.gov/wic/infant-and-toddler-feeding-practices-study-2-fourth-year-report) for detailed explanations of the study’s limitations. Outcome measurement methods and equipment used The majority of outcomes were measured via telephone interviews with children’s caregivers. Dietary intake was assessed using the USDA Automated Multiple Pass Method (https://www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-h...). Children’s length/height and weight data were objectively collected while at the WIC clinic or during visits with healthcare providers. Resources in this dataset:Resource Title: ITFP2 Year 5 Enroll to 60 Months Public Use Data CSV. File Name: itfps2_enrollto60m_publicuse.csvResource Description: ITFP2 Year 5 Enroll to 60 Months Public Use Data CSVResource Title: ITFP2 Year 5 Enroll to 60 Months Public Use Data Codebook. File Name: ITFPS2_EnrollTo60m_PUF_Codebook.pdfResource Description: ITFP2 Year 5 Enroll to 60 Months Public Use Data CodebookResource Title: ITFP2 Year 5 Enroll to 60 Months Public Use Data SAS SPSS STATA R Data. File Name: ITFP@_Year5_Enroll60_SAS_SPSS_STATA_R.zipResource Description: ITFP2 Year 5 Enroll to 60 Months Public Use Data SAS SPSS STATA R DataResource Title: ITFP2 Year 5 Ana to 60 Months Public Use Data CSV. File Name: ampm_1to60_ana_publicuse.csvResource Description: ITFP2 Year 5 Ana to 60 Months Public Use Data CSVResource Title: ITFP2 Year 5 Tot to 60 Months Public Use Data Codebook. File Name: AMPM_1to60_Tot Codebook.pdfResource Description: ITFP2 Year 5 Tot to 60 Months Public Use Data CodebookResource Title: ITFP2 Year 5 Ana to 60 Months Public Use Data Codebook. File Name: AMPM_1to60_Ana Codebook.pdfResource Description: ITFP2 Year 5 Ana to 60 Months Public Use Data CodebookResource Title: ITFP2 Year 5 Ana to 60 Months Public Use Data SAS SPSS STATA R Data. File Name: ITFP@_Year5_Ana_60_SAS_SPSS_STATA_R.zipResource Description: ITFP2 Year 5 Ana to 60 Months Public Use Data SAS SPSS STATA R DataResource Title: ITFP2 Year 5 Tot to 60 Months Public Use Data CSV. File Name: ampm_1to60_tot_publicuse.csvResource Description: ITFP2 Year 5 Tot to 60 Months Public Use Data CSVResource Title: ITFP2 Year 5 Tot to 60 Months Public Use SAS SPSS STATA R Data. File Name: ITFP@_Year5_Tot_60_SAS_SPSS_STATA_R.zipResource Description: ITFP2 Year 5 Tot to 60 Months Public Use SAS SPSS STATA R DataResource Title: ITFP2 Year 5 Food Group to 60 Months Public Use Data CSV. File Name: ampm_foodgroup_1to60m_publicuse.csvResource Description: ITFP2 Year 5 Food Group to 60 Months Public Use Data CSVResource Title: ITFP2 Year 5 Food Group to 60 Months Public Use Data Codebook. File Name: AMPM_FoodGroup_1to60m_Codebook.pdfResource Description: ITFP2 Year 5 Food Group to 60 Months Public Use Data CodebookResource Title: ITFP2 Year 5 Food Group to 60 Months Public Use SAS SPSS STATA R Data. File Name: ITFP@_Year5_Foodgroup_60_SAS_SPSS_STATA_R.zipResource Title: WIC Infant and Toddler Feeding Practices Study-2 Data File Training Manual. File Name: WIC_ITFPS-2_DataFileTrainingManual.pdf

Families of tax filers; Census families with children by age of children and children by age groups (final T1 Family File; T1FF).

Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve.

The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj.

The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 .

The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 .

The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed.

COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken out by age group. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the daily COVID-19 update.

Data are reported daily, with timestamps indicated in the daily briefings posted at: portal.ct.gov/coronavirus. Data are subject to future revision as reporting changes.

Starting in July 2020, this dataset will be updated every weekday.

Additional notes: A delay in the data pull schedule occurred on 06/23/2020. Data from 06/22/2020 was processed on 06/23/2020 at 3:30 PM. The normal data cycle resumed with the data for 06/23/2020.

A network outage on 05/19/2020 resulted in a change in the data pull schedule. Data from 5/19/2020 was processed on 05/20/2020 at 12:00 PM. Data from 5/20/2020 was processed on 5/20/2020 8:30 PM. The normal data cycle resumed on 05/20/2020 with the 8:30 PM data pull. As a result of the network outage, the timestamp on the datasets on the Open Data Portal differ from the timestamp in DPH's daily PDF reports.

Starting 5/10/2021, the date field will represent the date this data was updated on data.ct.gov. Previously the date the data was pulled by DPH was listed, which typically coincided with the date before the data was published on data.ct.gov. This change was made to standardize the COVID-19 data sets on data.ct.gov.

GUI14 - Respondents aged 25 years who may or may not have children. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Respondents aged 25 years who may or may not have children...

This table contains data on the number of licensed day care center slots (facility capacity) per 1,000 children aged 0-5 years in California, its regions, counties, cities, towns, and census tracts. The table contains 2015 data, and includes type of facility (day care center or infant center). Access to child care has become a critical support for working families. Many working families find high-quality child care unaffordable, and the increasing cost of child care can be crippling for low-income families and single parents. These barriers can impact parental choices of child care. Increased availability of child care facilities can positively impact families by providing more choices of child care in terms of price and quality. Estimates for this indicator are provided for the total population, and are not available by race/ethnicity. More information on the data table and a data dictionary can be found in the Data and Resources section. The licensed day care centers table is part of a series of indicators in the Healthy Communities Data and Indicators Project (HCI) of the Office of Health Equity. The goal of HCI is to enhance public health by providing data, a standardized set of statistical measures, and tools that a broad array of sectors can use for planning healthy communities and evaluating the impact of plans, projects, policy, and environmental changes on community health. The creation of healthy social, economic, and physical environments that promote healthy behaviors and healthy outcomes requires coordination and collaboration across multiple sectors, including transportation, housing, education, agriculture and others. Statistical metrics, or indicators, are needed to help local, regional, and state public health and partner agencies assess community environments and plan for healthy communities that optimize public health. More information on HCI can be found here: https://www.cdph.ca.gov/Programs/OHE/CDPH%20Document%20Library/Accessible%202%20CDPH_Healthy_Community_Indicators1pager5-16-12.pdf

The format of the licensed day care centers table is based on the standardized data format for all HCI indicators. As a result, this data table contains certain variables used in the HCI project (e.g., indicator ID, and indicator definition). Some of these variables may contain the same value for all observations.

During the school year, many children receive free and reduced-price breakfast and lunch through the School Breakfast and National School Lunch Programs. What happens when school lets out? Hunger is one of the most severe roadblocks to the learning process. Lack of nutrition during the summer months may set up a cycle for poor performance once school begins again. Hunger also may make children more prone to illness and other health issues. The Summer Food Service Program is designed to fill that nutrition gap and make sure children can get the nutritious meals they need. This data set contains information on summer food service participation, meals served and cash payments provided by state.

Abstract copyright UK Data Service and data collection copyright owner.The Active Lives Children and Young People Survey, which was established in September 2017, provides a world-leading approach to gathering data on how children engage with sport and physical activity. This school-based survey is the first and largest established physical activity survey with children and young people in England. It gives anyone working with children aged 5-16 key insight to help understand children's attitudes and behaviours around sport and physical activity. The results will shape and influence local decision-making as well as inform government policy on the PE and Sport Premium, Childhood Obesity Plan and other cross-departmental programmes. More general information about the study can be found on the Sport England Active Lives Survey webpage and the Active Lives Online website, including reports and data tables. The Active Lives Children and Young People Survey, 2019-2020 began as the usual school-based survey (i.e. completed at school as part of lessons). From 20 March 2020, schools, colleges and nurseries were closed in the UK due to the COVID-19 pandemic and remained closed until 1 June 2020, when there was a phased reopening for reception, and Years 1 and 6. The Active Lives survey fieldwork in Spring term finished two weeks early before the end of term, in line with the school closures. Due to the closure of schools, the survey had to be adapted for at home completion. The adaptions involved minor questionnaire changes (e.g. to ensure the wording was appropriate for both the new lockdown situation and to account for the new survey completion method at home) and communication changes. For further details on the changes, please see the accompanying technical report. The circumstances and adaptations resulted in a delay to survey fieldwork re-starting. This means that the data does not cover the full lockdown period, and instead re-starts from mid-May 2020 (when the survey was relaunched). Sample targets were also reduced as a result of the pandemic, resulting in a smaller proportion of summer term responses for 2019-20 when compared to previous years. As part of Sport England’s official publication, an additional Coronavirus report was produced, which outlines changes during the ‘easing restrictions’ phase of lockdown from mid-May to the end of July, comparing the summer term in 2020 with summer 2019. Due to the reduced summer term sample, it is recommended to analyse within term and/or school phase for academic year 2019-20. The survey identifies how participation varies across different activities and sports, by regions of England, between school types and terms, and between different demographic groups in the population. The survey measures levels of activity (active, fairly active and less active), attitudes towards sport and physical activity, swimming capability, the proportion of children and young people that volunteer in sport, sports spectating, and wellbeing measures such as happiness and life satisfaction. The questionnaire was designed to enable analysis of the findings by a broad range of variables, such as gender, family affluence and school year. The following datasets have been provided: Main dataset: includes responses from children and young people from school years 3 to 11, as well as responses from parents of children in years 1-2. The parents of children in years 1-2 provide behavioural answers about their child’s activity levels, they do not provide attitudinal information. Using this main dataset, full analyses can be carried out into sports and physical activity participation, levels of activity, volunteering (years 5 to 11), etc. Weighting is required when using this dataset (wt_gross / wt_gross.csplan files are available for SPSS users who can utilise them).Year 1-2 dataset: includes responses from children in school years 1-2 directly, providing their attitudinal responses (e.g. whether they like playing sport and find it easy). Analysis can be carried out into feelings towards swimming, enjoyment for being active, happiness etc. Weighting is required when using this dataset (wt_gross / wt_gross.csplan files are available for SPSS users who can utilise them).Teacher dataset – this .sav file includes response from the teachers at schools selected for the survey. Analysis can be carried out into school facilities available, length of PE lessons, whether swimming lessons are offered, etc. Weighting was formerly not available, however, as Sport England have started to publish the Teacher data, from December 2023 we decide to apply weighting to the data. The Teacher dataset now includes weighting by applying the ‘wt_teacher’ weighting variable. For further information about the variables available for analysis, and the relevant school years asked survey questions, please see the supporting documentation. Please read the documentation before using the datasets. More general information about the study can be found on the Sport England Active Lives Survey webpages.Latest edition informationFor the second edition (January 2024), the Teacher dataset now includes a weighting variable (‘wt_teacher’). Previously, weighting was not available for these data.

Interpretation of Electrocardiograms (ECG) is increasingly complemented by algorithms. These algorithms are based on large datasets. This ECG database consists of children and adults with congenital heart defects (CHD) including many arrhythmia annotations. This dataset, notable for its manual annotations and inclusion of intracardiac electrograms alongside traditional 12-lead ECGs, offers 1075.85 minutes of recordings (in total 113924 annotated beats) that capture various cardiac rhythms and arrhythmias such as supraventricular tachycardia and ventricular tachycardia. The data were meticulously collected from patients undergoing electrophysiological studies, with subsequent annotations by expert reviewers using the LightWAVE® software. The significance of this database lies in its focus on pediatric arrhythmias and arrhythmias of patients with congenital heart defect areas currently underrepresented in existing datasets, which predominantly feature adult pathologies. This resource aims to enhance algorithmic development for ECG interpretation, leveraging machine learning to improve diagnosis and treatment outcomes in these sensitive groups. The dataset not only serves as a critical tool for developing precision medicine but also sets a precedent for future expansions to include a broader spectrum of congenital heart defects conditions, thereby supporting the evolution of cardiac care through advanced computational techniques.

The Early Head Start-Child Care Partnerships (EHS-CCP) datasets contains data from two studies: (1) the 2016 National Descriptive Study (the NDS), which collected information about the 2015 EHS-CC Partnerships grantees and their child care partners (including child care centers and family child care providers) and the activities they engaged in to develop and maintain partnerships and meet the Head Start Program Performance Standards, assess their quality improvement needs, and support high quality caregiving and learning environments for infants and toddlers; and (2) the 2022 EHS-CCP Sustainability Study (the Sustainability Study), a follow-up study of the 2016 NDS, which collected information about how partnerships from the first round of grants had fared as of 2022 and factors that supported or impeded partnership sustainability. Both studies were conducted by Mathematica. The NDS collected data through web-based surveys of grantee directors and a sample of child care directors and family child care providers. The Sustainability Study collected data using web-based surveys of EHS program directors and child care providers in sustained and dissolved partnerships. It also collected qualitative data using semi-structured interviews to provide more in-depth information from purposively selected providers in sustained and dissolved partnerships. (Both NDS and Sustainability Study analyses of EHS programs are conducted at the grant level, with information about partnerships between providers and any delegate agencies rolled up to the level of the EHS-CCP grant. The term "program" is used in the Sustainability Study. Previously, in the NDS, "grantee" was used to refer to the same level of analysis.) The responses to the survey of grantees and their delegate agencies produced three NDS datasets. The first dataset, Partnership Grantee and Delegate Agency Director Survey, contains data from a survey of Early Head Start grantees and their delegate agencies. This dataset contains questions answered by the grantee or delegate agencies about themselves and contains one observation per grantee. Datasets two and three are also associated with the grantee and delegate agency survey. The second dataset, Grantee and Delegate Agencies Partner Characteristics, contains responses to the initial survey from the grantee or delegate regarding characteristics of all of their child care partners. This dataset was used to create a random sampling of approximately 20 percent of the child care partners for additional questions as well as a separate Child Care Partner survey, which were used to create both datasets three and four. Dataset three, Grantee and Delegate Agencies Randomly Sampled Partner Characteristics, contains responses from grantee and delegate agencies regarding the partners identified by the random sampling created from dataset two. The second survey conducted by Mathematica was of these selected child care partners, and dataset four, Child Care Partner Survey, is comprised of responses to questions asked of the child care partners about themselves. Demographic information contained in these datasets includes education level, degree field, length of occupation, and occupation. The Sustainability Study examined how partnerships from the first round of grants had fared as of 2022 and factors that supported or impeded partnership sustainability. The Sustainability Study also looks at features of sustained partnerships (partnerships from the NDS that were still in place at the time of the Sustainability Study) as well as active partnerships (which include sustained partnerships as well as those that are new since the NDS, and regardless of whether they are funded through an EHS-CC Partnerships grant). There are four Sustainability Study data files. Two program director survey files (one at the program level, and one at the provider level, for information about individual child care providers reported by the program director), one child care provider survey file, and one file containing transcripts of semi-structured interviews with dissolved and sustained partnership providers. Citation Skidmore, S., Clochard, A., Carlson, B., Doran, E., Cannon, J., Bernstein, S., Albanese, S., Del Grosso, P., and Xue, Y. (2023). Early Head Start-Child Care Partnerships Sustainability Study Data Documentation. Washington, DC: Office of Planning, Res

Patterns of educational attainment vary greatly across countries, and across population groups within countries. In some countries, virtually all children complete basic education whereas in others large groups fall short. The primary purpose of this database, and the associated research program, is to document and analyze these differences using a compilation of a variety of household-based data sets: Demographic and Health Surveys (DHS); Multiple Indicator Cluster Surveys (MICS); Living Standards Measurement Study Surveys (LSMS); as well as country-specific Integrated Household Surveys (IHS) such as Socio-Economic Surveys.As shown at the website associated with this database, there are dramatic differences in attainment by wealth. When households are ranked according to their wealth status (or more precisely, a proxy based on the assets owned by members of the household) there are striking differences in the attainment patterns of children from the richest 20 percent compared to the poorest 20 percent.In Mali in 2012 only 34 percent of 15 to 19 year olds in the poorest quintile have completed grade 1 whereas 80 percent of the richest quintile have done so. In many countries, for example Pakistan, Peru and Indonesia, almost all the children from the wealthiest households have completed at least one year of schooling. In some countries, like Mali and Pakistan, wealth gaps are evident from grade 1 on, in other countries, like Peru and Indonesia, wealth gaps emerge later in the school system.The EdAttain website allows a visual exploration of gaps in attainment and enrollment within and across countries, based on the international database which spans multiple years from over 120 countries and includes indicators disaggregated by wealth, gender and urban/rural location. The database underlying that site can be downloaded from here.

The data tracks how many children in customary care and the care of children's aid societies are eligible for RESPs and how many RESPs have been established for eligible children.

The dataset is broken down by:

• children's aid society

• ministry fiscal year

  *[RESP]: Registered Education Savings Plan

This data provides historical summaries of total participation and meals served as part of the USDA's Food and Nutrition Service (FNS) School Breakfast Program. The summary data begins in 1969, the year that FNS was established to administer USDA's nutrition assistance program. The School Breakfast Program is a federally assisted meal program operating in public and nonprofit private schools and residential child care institutions. It began as a pilot project in 1966, and was made permanent in 1975. The School Breakfast Program is administered at the Federal level by the Food and Nutrition Service. At the State level, the program is usually administered by State education agencies, which operate the program through agreements with local school food authorities in more than 89,000 schools and institutions. School districts and independent schools that choose to take part in the breakfast program receive cash subsidies from the USDA for each meal they serve. In return, they must serve breakfasts that meet Federal requirements, and they must offer free or reduced price breakfasts to eligible children. Any child at a participating school may purchase a meal through the School Breakfast Program. Children from families with incomes at or below 130 percent of the Federal poverty level are eligible for free meals. Those with incomes between 130 percent and 185 percent of the poverty level are eligible for reduced-price meals. Resources in this dataset:Resource Title: School Breakfast Participation and Meals Served Data. File Name: sbsummar.xlsResource Description: Data are provided by federal fiscal year rather than calendar or school year. This includes the months of October through September. The total participation numbers for this data is based on a nine month average: October - May plus September.Resource Title: School Breakfast Participation and Meals Served Data. File Name: SchoolBreakfasts2.csvResource Description: Data are provided by federal fiscal year rather than calendar or school year. This includes the months of October through September. The total participation numbers for this data is based on a nine month average: October - May plus September. Participation and meals served numbers are counted in millions, and the free/reduced price meals is a percentage of total meals. 2] in the reduced price column indicates that these numbers were included with the free participation numbers. Resource Title: Data Dictionary. File Name: Data Dictionary_SchoolBreakfastParticipationMealsServed.csv

The data (name, year of birth, sex, and number) are from a 100 percent sample of Social Security card applications for 1880 onward.

About this dataset

Context

The dataset tabulates the Moscow town population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Moscow town. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 - 64 years with a poulation of 408 (60.71% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Moscow town population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Moscow town is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Moscow town is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Moscow town Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Elizabethton population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Elizabethton. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 8,602 (59.89% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Elizabethton population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Elizabethton is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Elizabethton is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Elizabethton Population by Age. You can refer the same here