West Virginia and Kansas had the lowest cost of living across all U.S. states, with composite costs being half of those found in Hawaii. This was according to a composite index that compares prices for various goods and services on a state-by-state basis. In West Virginia, the cost of living index amounted to **** — well below the national benchmark of 100. Virginia— which had an index value of ***** — was only slightly above that benchmark. Expensive places to live included Hawaii, Massachusetts, and California. Housing costs in the U.S. Housing is usually the highest expense in a household’s budget. In 2023, the average house sold for approximately ******* U.S. dollars, but house prices in the Northeast and West regions were significantly higher. Conversely, the South had some of the least expensive housing. In West Virginia, Mississippi, and Louisiana, the median price of the typical single-family home was less than ******* U.S. dollars. That makes living expenses in these states significantly lower than in states such as Hawaii and California, where housing is much pricier. What other expenses affect the cost of living? Utility costs such as electricity, natural gas, water, and internet also influence the cost of living. In Alaska, Hawaii, and Connecticut, the average monthly utility cost exceeded *** U.S. dollars. That was because of the significantly higher prices for electricity and natural gas in these states.

Quality of life is a measure of comfort, health, and happiness by a person or a group of people. Quality of life is determined by both material factors, such as income and housing, and broader considerations like health, education, and freedom. Each year, US & World News releases its “Best States to Live in” report, which ranks states on the quality of life each state provides its residents. In order to determine rankings, U.S. News & World Report considers a wide range of factors, including healthcare, education, economy, infrastructure, opportunity, fiscal stability, crime and corrections, and the natural environment. More information on these categories and what is measured in each can be found below:

Healthcare includes access, quality, and affordability of healthcare, as well as health measurements, such as obesity rates and rates of smoking. Education measures how well public schools perform in terms of testing and graduation rates, as well as tuition costs associated with higher education and college debt load. Economy looks at GDP growth, migration to the state, and new business. Infrastructure includes transportation availability, road quality, communications, and internet access. Opportunity includes poverty rates, cost of living, housing costs and gender and racial equality. Fiscal Stability considers the health of the government's finances, including how well the state balances its budget. Crime and Corrections ranks a state’s public safety and measures prison systems and their populations. Natural Environment looks at the quality of air and water and exposure to pollution.

In 2024, the annual cost for a private room in an assisted living facility in the U.S. amounted to ****** U.S. dollars. However, costs varied greatly from one state to another. The most expensive states for a private room in assisted living was found in Hawaii, followed by Alaska and DC.

In the United States, Hawaii was the state with the most expensive housing, with the typical value of single-family homes in the 35th to 65th percentile range exceeding ******* U.S. dollars. Unsurprisingly, Hawaii also ranked top as the state with the highest cost of living. Meanwhile, a property was the least expensive in West Virginia, where it cost under ******* U.S. dollars to buy the typical single-family home. Single-family home prices increased across most states in the United States between December 2023 and December 2024, except in Louisiana, Florida, and the District of Colombia. According to the Federal Housing Association, house appreciation in 13 states exceeded **** percent in 2023.

The US Family Budget Dataset provides insights into the cost of living in different US counties based on the Family Budget Calculator by the Economic Policy Institute (EPI).

This dataset offers community-specific estimates for ten family types, including one or two adults with zero to four children, in all 1877 counties and metro areas across the United States.

Interesting Task Ideas:

1. See how family budgets compare to the federal poverty line and the Supplemental Poverty Measure in different counties.
2. Look into the money challenges faced by different types of families using the budgets provided.
3. Find out which counties have the most affordable places to live, food, transportation, healthcare, childcare, and other things people need.
4. Explore how the average income of families relates to the overall cost of living in different counties.
5. Investigate how family size affects the estimated budget and find counties where bigger families have higher costs.
6. Create visuals showing how the cost of living varies across different states and big cities.
7. Check whether specific counties are affordable for families of different sizes and types.
8. Use the dataset to compare living standards and economic security in different US counties.

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Alaska, Hawaii, and Connecticut were the states with the highest average monthly utility costs in the United States in 2023. Residents paid about ****** U.S. dollars for their electricity bills in Hawaii, while the average monthly bill for natural gas came to *** U.S. dollars. This was significantly higher than in any other state. Bigger homes have higher utility costs Despite regional variations, single-family homes in the United States have grown bigger in size since 1975. This trend also means that, unless homeowners invest in energy savings measures, they will have to pay more for their utility costs. Which are the most affordable states to live in? According to the cost of living index, the three most affordable states to live in are Mississippi, Kansas, and Oklahoma. At the other end of the scale are Hawaii, District of Columbia, and New York. The index is based on housing, utilities, grocery items, transportation, health care, and miscellaneous goods and services. To buy a median priced home in Kansas City, a prospective home buyer will have to earn an annual salary of about ****** U.S. dollars.

VITAL SIGNS INDICATOR Poverty (EQ5)

FULL MEASURE NAME The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED December 2018

DESCRIPTION Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE U.S Census Bureau: Decennial Census http://www.nhgis.org (1980-1990) http://factfinder2.census.gov (2000)

U.S. Census Bureau: American Community Survey Form C17002 (2006-2017) http://api.census.gov

METHODOLOGY NOTES (across all datasets for this indicator) The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. Poverty rates do not include unrelated individuals below 15 years old or people who live in the following: institutionalized group quarters, college dormitories, military barracks, and situations without conventional housing. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or noncash benefits (such as public housing, Medicaid, and food stamps). For the national poverty level definitions by year, see: https://www.census.gov/hhes/www/poverty/data/threshld/index.html For an explanation on how the Census Bureau measures poverty, see: https://www.census.gov/hhes/www/poverty/about/overview/measure.html

For the American Community Survey datasets, 1-year data was used for region, county, and metro areas whereas 5-year rolling average data was used for city and census tract.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

Of the most populous cities in the U.S., San Jose, California had the highest annual income requirement at ******* U.S. dollars annually for homeowners to have an affordable and comfortable life in 2024. This can be compared to Houston, Texas, where homeowners needed an annual income of ****** U.S. dollars in 2024.

This table contains data on the percent of households paying more than 30% (or 50%) of monthly household income towards housing costs for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Department of Housing and Urban Development (HUD), Consolidated Planning Comprehensive Housing Affordability Strategy (CHAS) and the U.S. Census Bureau, American Community Survey (ACS). The table is part of a series of indicators in the [Healthy Communities Data and Indicators Project of the Office of Health Equity] Affordable, quality housing is central to health, conferring protection from the environment and supporting family life. Housing costs—typically the largest, single expense in a family's budget—also impact decisions that affect health. As housing consumes larger proportions of household income, families have less income for nutrition, health care, transportation, education, etc. Severe cost burdens may induce poverty—which is associated with developmental and behavioral problems in children and accelerated cognitive and physical decline in adults. Low-income families and minority communities are disproportionately affected by the lack of affordable, quality housing. More information about the data table and a data dictionary can be found in the Attachments.

VITAL SIGNS INDICATOR
Poverty (EQ5)

FULL MEASURE NAME
The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED
January 2023

DESCRIPTION
Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE
U.S Census Bureau: Decennial Census - http://www.nhgis.org
1980-2000

U.S. Census Bureau: American Community Survey - https://data.census.gov/
2007-2021
Form C17002

CONTACT INFORMATION
vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator)
The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or non-cash benefits (such as public housing, Medicaid and food stamps).

For the national poverty level definitions by year, see: US Census Bureau Poverty Thresholds - https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-thresholds.html.

For an explanation on how the Census Bureau measures poverty, see: How the Census Bureau Measures Poverty - https://www.census.gov/topics/income-poverty/poverty/guidance/poverty-measures.html.

American Community Survey (ACS) 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

The cost of living is spiraling. Prices are going up, household expenses are rising, and the U.S. inflation rate reached a 40-year record high in 2023. Many consumers are looking for new ways to deal with this situation and refer to social media for support. So, which social media platforms have the most helpful content to deal with the current cost of living crisis in the U.S.? According to an exclusive survey by We Are Social and Statista Q, around 61 percent of TikTok users in the United States find helpful content there. Coming on number second is YouTube, as 56 percent of YouTube users find life hacks, tricks, money saving tips and other suitable advice to deal with inflation in 2023.

88,8 (Index, higher means higher cost of living) in 2024Q3.

Consumer Price Index CPI in the United States increased to 321.47 points in May from 320.80 points in April of 2025. This dataset provides the latest reported value for - United States Consumer Price Index (CPI) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

In 2024, the annual median cost for long-term care in the United States ranged from ****** to ******* U.S. dollars, depending on the type of service. This significant financial burden highlights the importance of planning for future healthcare needs, as many older adults may face substantial out-of-pocket costs for extended care services. Nursing homes and assisted living facilities Nursing homes represent the most expensive long-term care option, with private rooms costing an estimated ****** U.S. dollars per month in 2024. Semi-private rooms are slightly more affordable at ***** U.S. dollars monthly. Assisted living facilities offer a less costly alternative, with annual expenses for a private room averaging ****** U.S. dollars. However, these costs can vary dramatically by location, with states like Hawaii, Alaska, and Washington D.C. commanding the highest prices for assisted living accommodations. Home care services and future projections For those preferring to receive care at home, the hourly rates for long-term home care services in 2024 were ** U.S. dollars for homemaker services and ** U.S. dollars for home health aide services. These costs are expected to rise significantly in the coming decades, with projections suggesting home health aide services could approach *** U.S. dollars per hour by 2060. The increasing expense of long-term care is evident across all service types, with assisted living facilities experiencing a ** percent cost increase from 2023 to 2024, while nursing home rates for semi-private and private rooms rose by * and * percent, respectively.

As of September 2024, Mumbai had the highest cost of living among other cities in the country, with an index value of ****. Gurgaon, a satellite city of Delhi and part of the National Capital Region (NCR) followed it with an index value of ****.  What is cost of living? The cost of living varies depending on geographical regions and factors that affect the cost of living in an area include housing, food, utilities, clothing, childcare, and fuel among others. The cost of living is calculated based on different measures such as the consumer price index (CPI), living cost indexes, and wage price index. CPI refers to the change in the value of consumer goods and services. The wage price index, on the other hand, measures the change in labor services prices due to market pressures. Lastly, the living cost indexes calculate the impact of changing costs on different households. The relationship between wages and costs determines affordability and shifts in the cost of living. Mumbai tops the list Mumbai usually tops the list of most expensive cities in India. As the financial and entertainment hub of the country, Mumbai offers wide opportunities and attracts talent from all over the country. It is the second-largest city in India and has one of the most expensive real estates in the world.

108.1 (Index, higher means higher cost of living) in 2022Q3.

VITAL SIGNS INDICATOR Poverty (EQ5)

FULL MEASURE NAME The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED December 2018

DESCRIPTION Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE U.S Census Bureau: Decennial Census http://www.nhgis.org (1980-1990) http://factfinder2.census.gov (2000)

U.S. Census Bureau: American Community Survey Form C17002 (2006-2017) http://api.census.gov

METHODOLOGY NOTES (across all datasets for this indicator) The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. Poverty rates do not include unrelated individuals below 15 years old or people who live in the following: institutionalized group quarters, college dormitories, military barracks, and situations without conventional housing. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or noncash benefits (such as public housing, Medicaid, and food stamps). For the national poverty level definitions by year, see: https://www.census.gov/hhes/www/poverty/data/threshld/index.html For an explanation on how the Census Bureau measures poverty, see: https://www.census.gov/hhes/www/poverty/about/overview/measure.html

For the American Community Survey datasets, 1-year data was used for region, county, and metro areas whereas 5-year rolling average data was used for city and census tract.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

This dataset contains replication files for "The Fading American Dream: Trends in Absolute Income Mobility Since 1940" by Raj Chetty, David Grusky, Maximilian Hell, Nathaniel Hendren, Robert Manduca, and Jimmy Narang. For more information, see https://opportunityinsights.org/paper/the-fading-american-dream/. A summary of the related publication follows. One of the defining features of the “American Dream” is the ideal that children have a higher standard of living than their parents. We assess whether the U.S. is living up to this ideal by estimating rates of “absolute income mobility” – the fraction of children who earn more than their parents – since 1940. We measure absolute mobility by comparing children’s household incomes at age 30 (adjusted for inflation using the Consumer Price Index) with their parents’ household incomes at age 30. We find that rates of absolute mobility have fallen from approximately 90% for children born in 1940 to 50% for children born in the 1980s. Absolute income mobility has fallen across the entire income distribution, with the largest declines for families in the middle class. These findings are unaffected by using alternative price indices to adjust for inflation, accounting for taxes and transfers, measuring income at later ages, and adjusting for changes in household size. Absolute mobility fell in all 50 states, although the rate of decline varied, with the largest declines concentrated in states in the industrial Midwest, such as Michigan and Illinois. The decline in absolute mobility is especially steep – from 95% for children born in 1940 to 41% for children born in 1984 – when we compare the sons’ earnings to their fathers’ earnings. Why have rates of upward income mobility fallen so sharply over the past half-century? There have been two important trends that have affected the incomes of children born in the 1980s relative to those born in the 1940s and 1950s: lower Gross Domestic Product (GDP) growth rates and greater inequality in the distribution of growth. We find that most of the decline in absolute mobility is driven by the more unequal distribution of economic growth rather than the slowdown in aggregate growth rates. When we simulate an economy that restores GDP growth to the levels experienced in the 1940s and 1950s but distributes that growth across income groups as it is distributed today, absolute mobility only increases to 62%. In contrast, maintaining GDP at its current level but distributing it more broadly across income groups – at it was distributed for children born in the 1940s – would increase absolute mobility to 80%, thereby reversing more than two-thirds of the decline in absolute mobility. These findings show that higher growth rates alone are insufficient to restore absolute mobility to the levels experienced in mid-century America. Under the current distribution of GDP, we would need real GDP growth rates above 6% per year to return to rates of absolute mobility in the 1940s. Intuitively, because a large fraction of GDP goes to a small fraction of high-income households today, higher GDP growth does not substantially increase the number of children who earn more than their parents. Of course, this does not mean that GDP growth does not matter: changing the distribution of growth naturally has smaller effects on absolute mobility when there is very little growth to be distributed. The key point is that increasing absolute mobility substantially would require more broad-based economic growth. We conclude that absolute mobility has declined sharply in America over the past half-century primarily because of the growth in inequality. If one wants to revive the “American Dream” of high rates of absolute mobility, one must have an interest in growth that is shared more broadly across the income distribution.

The United States senior living market, valued at $112.93 billion in 2025, is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 5.86% from 2025 to 2033. This expansion is fueled by several key drivers. The aging population, particularly the baby boomer generation, is a significant factor, creating an increasing demand for assisted living, independent living, memory care, and nursing care facilities. Furthermore, rising disposable incomes and increasing awareness of the benefits of senior living communities contribute to market growth. Technological advancements in senior care, such as telehealth and remote monitoring, are also enhancing the quality of life for residents and boosting market appeal. However, the market faces some restraints, including the rising costs of healthcare and senior care services, potentially limiting accessibility for some segments of the population. Furthermore, staffing shortages within the industry represent a significant challenge. The market is segmented by property type, with assisted living, independent living, and memory care facilities representing the largest segments. Key states driving market growth include New York, Illinois, California, North Carolina, and Washington, reflecting higher concentrations of the senior population and higher disposable incomes. Major players in the market such as Ensign Group Inc, Sunrise Senior Living, Brookdale Senior Living Inc, and Atria Senior Living Inc, compete fiercely, driving innovation and service improvements. The forecast period (2025-2033) anticipates continued growth, driven by the ongoing demographic shifts and increased demand for high-quality senior care options. Strategic partnerships, acquisitions, and investments in technology are likely to shape the competitive landscape in the coming years. The industry will continue to adapt to meet the evolving needs of the aging population, focusing on personalized care, innovative technologies, and cost-effective solutions. This comprehensive report provides an in-depth analysis of the booming United States senior living market, covering the period from 2019 to 2033. With a base year of 2025 and a forecast period spanning 2025-2033, this report is an invaluable resource for investors, industry professionals, and anyone seeking to understand the dynamics of this rapidly evolving sector. The report leverages extensive data analysis to provide insightful projections and uncover key trends shaping the future of senior care in the US. Expect detailed breakdowns of key segments, including assisted living, independent living, memory care, and nursing care, across major states like California, New York, Illinois, North Carolina, and Washington. Recent developments include: July 2023: Spring Cypress senior living site expansion is set to open at the end of 2024 and will consist of three phases. The first phase of the expansion will include 19 independent-living, two-bedroom cottages. The second phase will include 24 townhomes. The third phase will feature 95 apartments. The final phase will feature a resort with several luxury amenities., Apr 2023: For seniors looking for innovative, high-quality care, Avista Senior Living is transitioning away from its SafelyYou partnership to empower safer, more personalized dementia care with real-time, AI video and remote clinical experts 24/7.. Key drivers for this market are: 4., Increase in Aging Population Driving the Market4.; Healthcare and Long-term Care Needs Driving the Market. Potential restraints include: 4., High Affordability and Cost of Care Affecting the Market4.; Staffing and Workforce Challenges Affecting the Market. Notable trends are: Senior Housing Witnessing Increased Demand.

Project Cost: PR8-2QP2620: Residential Building: High: Espírito Santo data was reported at 1,340.040 BRL/sq m in Jun 2019. This records an increase from the previous number of 1,316.480 BRL/sq m for May 2019. Project Cost: PR8-2QP2620: Residential Building: High: Espírito Santo data is updated monthly, averaging 756.785 BRL/sq m from Jan 1999 (Median) to Jun 2019, with 246 observations. The data reached an all-time high of 1,340.040 BRL/sq m in Jun 2019 and a record low of 287.230 BRL/sq m in Jan 1999. Project Cost: PR8-2QP2620: Residential Building: High: Espírito Santo data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Construction and Properties Sector – Table BR.EB042: Project Cost per Square Meter: Residential Building (PR8-2QP2620): by Standard of Finishing: High: by State. PR8-2QP2620: Residential building (PR), pillars (P), 8-story, living room, 2 bedrooms, traffic flow, bathroom, kitchen, laundry room, maid’s bedroom and bathroom.