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.

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.

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.

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.

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

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.

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.