Please note this page provides neighborhood demographic data using 2010 Census tracts. For updated Neighborhood Demographics using 2020 Census tracts consistently across historical years, please refer to the Planning Department Research Division's Exploring Neighborhood Change Tool. The tool visualizes demographic, economic, and housing data for Boston's tracts and neighborhoods from 1950 to 2025 (with projections to 2035) using the most up-to-date 2020 Census tract-based Neighborhood boundaries.

Boston is a city defined by the unique character of its many neighborhoods. The historical tables created by the BPDA Research Division from U.S. Census Decennial data describe demographic changes in Boston’s neighborhoods from 1950 through 2010 using consistent tract-based geographies. For more analysis of these data, please see Historical Trends in Boston's Neighborhoods. The most recent available neighborhood demographic data come from the 5-year American Community Survey (ACS). The ACS tables also present demographic data for Census-tract approximations of Boston’s neighborhoods. For pdf versions of the data presented here plus earlier versions of the analysis, please see Boston in Context.

This layer shows the age statistics in Tucson by neighborhood, aggregated from block level data, between 2010-2019. For questions, contact GIS_IT@tucsonaz.gov. The data shown is from Esri's 2019 Updated Demographic estimates.Esri's U.S. Updated Demographic (2019/2024) Data - Population, age, income, sex, race, home value, and marital status are among the variables included in the database. Each year, Esri's Data Development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of U.S. geographies.Additional Esri Resources:Esri DemographicsU.S. 2019/2024 Esri Updated DemographicsEssential demographic vocabularyPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

Table from the American Community Survey (ACS) 5-year series on age and gender related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B01001 Sex by Age, B01002 Median Age by Sex. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.Table created for and used in the Neighborhood Profiles application.Vintages: 2023ACS Table(s): B01001, B01002Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estima

This file contains demographic, social, economic, and housing information from the "100-percent" and unweighted sample counts from the 1980 census for locally defined neighborhoods. The Neighborhood Publication Area (NPA) is the total area within which neighborhoods were defined by each participant in the Neighborhood Statistics Program (NSP), which was developed by the Census Bureau. Population items include age, race, sex, marital status, Spanish origin, employment status, and language spoken at home. Housing items include occupancy/vacancy status, tenure, contract rent, value, condominium status, number of rooms, and plumbing facilities.

Ages chart illustrates the age and gender trends across all age and gender groupings. A chart where the the covered area is primarily on the right describes a very young population while a chart where the the covered area is primarily on the left illustrates an aging population.

Comprehensive demographic dataset for Bay Area, Corpus Christi, TX, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

Contains data on Community Services Statistics for June 2025 and a provisional data file for July 2025 (note this is intended as an early view until providers submit a refresh of their data).

The focus of Fingal County Council’s Community Development Office (CDO) is to develop engaged and integrated communities across Fingal, and successfully delivering the fantastic amenity is testament to that collaboration between the CDO and the local communities. The CDO team will continue to actively engage with the local volunteer board to ensure the highest standards of governance and management of the Community Centers for the enjoyment of current and future generations across the County of FingalThe day-to-day operation of the facility will be undertaken on the Council’s behalf by a local voluntary Board of Management who represent many groups in the area and Facility Management Company.visit: our web page at : _ www.fingal.ie/search?keywords=community+centres for further information.

Financial overview and grant giving statistics of Association For Neighborhood & Housing Development

Comprehensive demographic dataset for Industrial Area West, Roseville, CA, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

12-04-19: Source for these data? [LA GeoHub, includes 97 NCs, date?]

Community Services Statistics, April 2023. This is a monthly report on publicly funded community services for people of all ages using data from the Community Services Data Set (CSDS) reported in England for April 2023. It has been developed to help achieve better outcomes and provide data that will be used to commission services in a way that improves health, reduces inequalities, and supports service improvement and clinical quality. These statistics are classified as experimental and should be used with caution. Experimental statistics are new official statistics undergoing evaluation. More information about experimental statistics can be found on the UK Statistics Authority website (linked at the bottom of this page). A provisional data file for May 2023 is now included in this publication. Please note this is intended as an early view until providers submit a refresh of their data, which will be published next month.

Dataset contains census usually resident population counts from the 2013, 2018, and 2023 Censuses, as well as the percentage change in the population count between the 2013 and 2018 Censuses, and between the 2018 and 2023 Censuses. Data is available by statistical area 2.

Map shows the percentage change in the census usually resident population count between the 2018 and 2023 Censuses.

Download lookup file from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.

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Footnotes

Geographical boundaries

Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

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Subnational census usually resident population

The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city.

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Caution using time series

Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).

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About the 2023 Census dataset

For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

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Data quality

The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

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Quality rating of a variable

The quality rating of a variable provides an overall evaluation of data quality for that variable, usually at the highest levels of classification. The quality ratings shown are for the 2023 Census unless stated. There is variability in the quality of data at smaller geographies. Data quality may also vary between censuses, for subpopulations, or when cross tabulated with other variables or at lower levels of the classification. Data quality ratings for 2023 Census variables has more information on quality ratings by variable.

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Census usually resident population count concept quality rating

The census usually resident population count is rated as very high quality.

Census usually resident population count – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Using data for good

Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.

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Confidentiality

The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

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Symbol

-998 Not applicable

About this dataset

Context

The dataset tabulates the data for the Bellefontaine Neighbors, MO population pyramid, which represents the Bellefontaine Neighbors population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey 5-Year estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Bellefontaine Neighbors, MO, is 27.5.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Bellefontaine Neighbors, MO, is 36.7.
• Total dependency ratio for Bellefontaine Neighbors, MO is 64.3.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Bellefontaine Neighbors, MO is 2.7.

Content

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

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Bellefontaine Neighbors population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Bellefontaine Neighbors for the selected age group is shown in the following column.
• Population (Female): The female population in the Bellefontaine Neighbors for the selected age group is shown in the following column.
• Total Population: The total population of the Bellefontaine Neighbors for the selected age group 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 Bellefontaine Neighbors Population by Age. You can refer the same here

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