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.

Is Boston Metro, MA Safe? The B grade means the rate of crime is slightly lower than the average US metro area. Boston Metro is in the 69th percentile for safety, meaning 31% of metro areas are safer and 69% of metro areas are more dangerous. This analysis applies to the Boston metro area's proper boundaries only. See the table on nearby places below for nearby metro areas.

The rate of crime in the Boston metro area is 19.92 per 1,000 residents during a standard year. People who live in the Boston metro area generally consider the southwest part of the metro area to be the safest.

Your chance of being a victim of crime in the Boston metro area may be as high as 1 in 32 in the central neighborhoods, or as low as 1 in 92 in the southwest part of the metro area. See the section on interpreting the crime map, however, because comparing rates for crime or any other crime is not as intuitive as it may seem. It can help us answer?

Type of crime vs locations where the crime took place? If there is any change in criminal activities in past years? Which location is safe and which is unsafe? Interestingly one can peek - DO MORE BROKEN WINDOWS MEAN MORE CRIME?

Here is the theory:

Researchers theorized that graffiti, abandoned buildings, panhandling, and other signs of disorder in neighborhoods create an environment that leads people to commit more crime.

In the “broken windows theory,” as it has come to be known, such characteristics convey the message that these places aren’t monitored and crime will go unpunished. The theory has led police to crack down on minor crimes with the idea that this will prevent more serious crimes, and inspired research on how disorder affects people’s health.

Inspiration Is the crime incident related to the area in Boston? Is there any relationship between the region and the types of crime? Is there any specific time during a week, a month or a year will infect the crime?

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.

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.