In 2023, the population of the Boston-Cambridge-Newton metropolitan area in the United States was about 4.92 million people. This is a slight increase when compared with last year's population, which was about 4.9 million people.

Graph and download economic data for Resident Population in Boston-Cambridge-Newton, MA-NH (MSA) (BOSPOP) from 2000 to 2024 about Boston, NH, MA, residents, population, and USA.

Historical dataset of population level and growth rate for the Boston metro area from 1950 to 2025.

The gross domestic product (GDP) of the Greater Boston metro area has increased significantly since 2001. In 2022, the area's GDP amounted to ***** billion chained 2017 U.S. dollars, compared to ***** billion U.S. dollars in 2001.

About this dataset

Context

The dataset tabulates the Boston population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Boston across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Boston was 653,833, a 0.09% increase year-by-year from 2022. Previously, in 2022, Boston population was 653,243, a decline of 0.61% compared to a population of 657,283 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Boston increased by 62,272. In this period, the peak population was 694,661 in the year 2019. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Boston is shown in this column.
• Year on Year Change: This column displays the change in Boston population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

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 Boston Population by Year. You can refer the same here

This statistic displays the average physician-to-population ratio in select U.S. metropolitan areas as of 2013. During this year, there was an average of ***** physicians per 100,000 population in Detroit. Boston has one of the overall highest average wait times for a physician appointment. The average cumulative wait time is approximately **** days in 2014, which has decreased since 2004.

This map shows the percent of people who have low incomes who live in the Boston Region Metropolitan Planning Organization (MPO) area. The low-income population includes those whose family income is less than or equal to 200% of the poverty level for their family size. The data are from the 2010-14 American Community Survey, and are distributed to transportation analysis zones (TAZs) within the Boston MPO region. TAZs are approximately the size of Census block groups, but whose boundaries align more closely to roadways. They were developed for use in the Boston MPO's travel demand model, and are used for other MPO purposes as well, such as mapping.

HAZUS is an abbreviation for Hazards United States, and was developed by FEMA. The HAZUS dataset was designed to estimate the potential physical, economic and social losses during hazardous events such as flooding or earthquakes. To Measure the social impact of these events HAZUS includes detailed demographic data for the United States. This dataset pulls out the housing and real estate data from the demographic files, at the census block level for the New Hampshire section of the Boston, MA Metropolitan Statistic Area (MSA). Data attributes for housing include owner occupied single family units, owner occupied multi-family units, renter occupied single family units, vacant single family units along with others. Demographics data was recent as of May 2006. Source: http://www.fema.gov/plan/prevent/hazus/index.shtm

This dataverse repository contains data from May to November of 2014 at fifteen locations across Metropolitan Boston for (1) throughfall nitrogen, (2) fossil fuel carbon dioxide emissions, (3) human population density, (4) land cover class, (5) ISA, (6) soil solution nitrogen and soil nitrogen cycling rates (mineralization and nitrification) and (7) soil respiration. Details of the methodology are provided in the following publications. Decina SM, PH Templer, LR Hutyra, CK Gately, P Rao. 2017. Variability, drivers, and effects of atmospheric nitrogen inputs across an urban area: emerging patterns among human activities, the atmosphere and soils. Science of the Total Environment 609:1524-1534. https://doi.org/10.1016/j.scitotenv.2017.07.166 Decina S, LR Hutyra, CK Gately, JM Getson, AB Reinmann, AG Short Gianotti, and PH Templer. 2016. Soil respiration contributes significantly to urban carbon fluxes. Environmental Pollution 212:433-439. https://doi.org/10.1016/j.envpol.2016.01.012

Census block groups are created by the U.S. Census Bureau as statistical geographic subdivisions of a census tract defined for the tabulation and presentation of data from the decennial census and the American Community Survey. Block groups generally contain between 600 and 3,000 people. Census block groups are split or merged every 10 years, depending on population change, with local feedback through the Participant Statistical Areas Program (PSAP). These shapefiles provide the boundaries for the 2020 block groups for Boston.

About this dataset

Context

The dataset presents the median household income across different racial categories in Boston township. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Boston township population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 89.18% of the total residents in Boston township. Notably, the median household income for White households is $79,444. Interestingly, despite the White population being the most populous, it is worth noting that Two or More Races households actually reports the highest median household income, with a median income of $118,456. This reveals that, while Whites may be the most numerous in Boston township, Two or More Races households experience greater economic prosperity in terms of median household income.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Boston township.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

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 Boston township median household income by race. You can refer the same here

Recent advances in quantitative tools for examining urban morphology enable the development of morphometrics that can characterize the size, shape, and placement of buildings; the relationships between them; and their association with broader patterns of development. Although these methods have the potential to provide substantial insight into the ways in which neighborhood morphology shapes the socioeconomic and demographic characteristics of neighborhoods and communities, this question is largely unexplored. Using building footprints in five of the ten largest U.S. metropolitan areas (Atlanta, Boston, Chicago, Houston, and Los Angeles) and the open-source R package, foot, we examine how neighborhood morphology differs across U.S. metropolitan areas and across the urban-exurban landscape. Principal components analysis, unsupervised classification (K-means), and Ordinary Least Squares regression analysis are used to develop a morphological typology of neighborhoods and to examine its association with the spatial, socioeconomic, and demographic characteristics of census tracts. Our findings illustrate substantial variation in the morphology of neighborhoods, both across the five metropolitan areas as well as between central cities, suburbs, and the urban fringe within each metropolitan area. We identify five different types of neighborhoods indicative of different stages of development and distributed unevenly across the urban landscape: these include low-density neighborhoods on the urban fringe; mixed use and high-density residential areas in central cities; and uniform residential neighborhoods in suburban cities. Results from regression analysis illustrate that the prevalence of each of these forms is closely associated with variation in socioeconomic and demographic characteristics such as population density, the prevalence of multifamily housing, and income, race/ethnicity, homeownership, and commuting by car. We conclude by discussing the implications of our findings and suggesting avenues for future research on neighborhood morphology, including ways that it might provide insight into issues such as zoning and land use, housing policy, and residential segregation.

How racially diverse are residents in Massachusetts? This topic shows the demographic breakdown of residents by race/ethnicity and the increases in the Non-white population since 2010.

The Healthy Neighborhoods Study (HNS) aimed to better understand the relationship between urban development, neighborhood conditions, and population health in Boston. More specifically, the research completed was the planning and baseline phase for a longer 9 year longitudinal study with two overarching aims: to determine how to measure and evaluate the mid- to long-term impacts of transit-oriented development on neighborhood conditions and population health, and to better understand the drivers and mechanisms that mediate the relationship between neighborhoods and health. The study tracks measures in health, development, neighborhood conditions and resident experiences in nine urban centers in the Boston-metro area.

About this dataset

Context

The dataset presents the median household income across different racial categories in South Boston. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of South Boston population by race & ethnicity, the population is predominantly Black or African American. This particular racial category constitutes the majority, accounting for 55.65% of the total residents in South Boston. Notably, the median household income for Black or African American households is $35,369. Interestingly, despite the Black or African American population being the most populous, it is worth noting that Asian households actually reports the highest median household income, with a median income of $96,150. This reveals that, while Black or African Americans may be the most numerous in South Boston, Asian households experience greater economic prosperity in terms of median household income.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in South Boston.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

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 South Boston median household income by race. You can refer the same here

This map shows a simple summary of the social vulnerability of populations in the United States. Using Census 2010 information, the map answers the question “Where are the areas of relatively greater potential impact from disaster events within the U.S.?” from the perspective of social vulnerability to hazards. In other words, all areas of the U.S. are assessed relative to each other. Local and regional assessments of social vulnerability should apply the same model to their multi-county or multi-state region. For emergency response planning and hazard mitigation, populations can be assessed by their vulnerability to various hazards (fire, flood, etc). Physical vulnerability refers to a population’s exposure to specific potential hazards, such as living in a designated flood plain. There are various methods for calculating the potential or real geographic extents for various types of hazards. Social vulnerability refers to sensitivity to this exposure due to population and housing characteristics: age, low income, disability, home value or other factors. The social vulnerability score presented in this web service is based upon a 2000 article from the Annals of the Association of American Geographers which sums the values of 8 variables as a surrogate for "social vulnerability". For example, low-income seniors may not have access to a car to simply drive away from an ongoing hazard such as a flood. A map of the flood’s extent can be overlaid on the social vulnerability layer to allow planners and responders to better understand the demographics of the people affected by the hazard. This map depicts social vulnerability at the block group level. A high score indicates an area is more vulnerable. This web service provides a simplistic view of social vulnerability. There are more recent methods and metrics for determining and displaying social vulnerability, including the Social Vulnerability Index (SoVI) which capture the multi-dimensional nature of social vulnerability across space. See www.sovius.org for more information on SoVI. The refereed journal article used to guide the creation of the model in ModelBuilder was: Cutter, S. L., J. T. Mitchell, and M. S. Scott, 2000. "Revealing the Vulnerability of People and Places: A Case Study of Georgetown County, South Carolina." Annals of the Association of American Geographers 90(4): 713-737. Additionally, a white paper used to guide creation of the model in ModelBuilder was "Handbook for Conducting a GIS-Based Hazards Assessment at the County Level" by Susan L. Cutter, Jerry T. Mitchell, and Michael S. Scott.Off-the-shelf software and data were used to generate this index. ModelBuilder in ArcGIS 10.1 was used to connect the data sources and run the calculations required by the model.-------------------------The Civic Analytics Network collaborates on shared projects that advance the use of data visualization and predictive analytics in solving important urban problems related to economic opportunity, poverty reduction, and addressing the root causes of social problems of equity and opportunity. For more information see About the Civil Analytics Network.

The map is based on output from a HAZUS flood model for 100 year coastal flood scenario. The data shows the count of buildings by censusblock that could be inundated by 100 year coastal floods. http://www.fema.gov/plan/prevent/hazus/

About this dataset

Context

The dataset presents the median household income across different racial categories in Boston Heights. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Boston Heights population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 95.06% of the total residents in Boston Heights. Notably, the median household income for White households is $124,792. Interestingly, despite the White population being the most populous, it is worth noting that Asian households actually reports the highest median household income, with a median income of $250,001. This reveals that, while Whites may be the most numerous in Boston Heights, Asian households experience greater economic prosperity in terms of median household income.

Content

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

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Boston Heights.
• Median household income: Median household income, adjusting for inflation, presented in 2023-inflation-adjusted dollars

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 Boston Heights median household income by race. You can refer the same here

The map is based on 10 year return coastal floods simulation run on HAZUS. The data includes number of residential, commercial, Goverment, schools and colleges by census block that may be inundated by the 10 year floods (measured in feet). http://www.fema.gov/plan/prevent/hazus/