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.

Key quality of life indicators.

This statistic shows a ranking of the best U.S. federal states to live in, according to selected metrics and based on a survey among more than 530,000 Americans. The survey was conducted between January 2011 and June 2012. The findings are presented as index scores composed of the scores regarding various parameters*. According to this index, Utah is the city with the highest liveability and life quality, as it scored 7.5 points.

This EnviroAtlas dataset portrays the percentage of population within different household income ranges for each Census Block Group (CBG), a threshold estimated to be an optimal household income for quality of life, and the percentage of households with income below this threshold. Data were compiled from the Census ACS (American Community Survey) 5-year Summary Data (2008-2012). This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

This survey, conducted by Gallup across the United States in January 2014, shows the extent of satisfaction among the U.S. population with various aspects regarding American life. 32 percent of respondents were satisfied with the income and wealth distribution, whereas 74 percent were satisfied in the overall quality of life in the United States.

In 2024, across all states in the United States, Minnesota was ranked first with a health index score of 67.38, followed by Rhode Island and South Dakota. The health index score was calculated by measuring 42 healthcare metrics relevant to health costs, access, and outcome.

Analysis of ‘Choose Maryland: Compare States - Quality Of Life’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/0cc0cfcc-9617-4946-abe7-38d3ab9525a9 on 27 January 2022.

--- Dataset description provided by original source is as follows ---

Key quality of life indicators.

--- Original source retains full ownership of the source dataset ---

The U.S. Census defines Asian Americans as individuals having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent (U.S. Office of Management and Budget, 1997). As a broad racial category, Asian Americans are the fastest-growing minority group in the United States (U.S. Census Bureau, 2012). The growth rate of 42.9% in Asian Americans between 2000 and 2010 is phenomenal given that the corresponding figure for the U.S. total population is only 9.3% (see Figure 1). Currently, Asian Americans make up 5.6% of the total U.S. population and are projected to reach 10% by 2050. It is particularly notable that Asians have recently overtaken Hispanics as the largest group of new immigrants to the U.S. (Pew Research Center, 2015). The rapid growth rate and unique challenges as a new immigrant group call for a better understanding of the social and health needs of the Asian American population.

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This dataset tracks the updates made on the dataset "Choose Maryland: Compare States - Quality Of Life" as a repository for previous versions of the data and metadata.

This online application gives manufacturers the ability to compare Iowa to other states on a number of different topics including: business climate, education, operating costs, quality of life and workforce.

In 2022, the United States' E-infrastructure index amounted to 0.1944. By contrast, the Internet affordability index was only 0.0326.

Users can obtain descriptions, maps, profiles, and ranks of U.S. metropolitan areas pertaining to quality of life, diversity, and opportunities for racial and ethnic groups in the U.S. BackgroundThe Diversity Data project operates a website for users to explore how U.S. metropolitan areas perform on evidence-based social measures affecting quality of life, diversity and opportunity for racial and ethnic groups in the United States. These indicators capture a broad definition of quality of life and health, including opportunities for good schools, housing, jobs, wages, health and social services, and safe neighborhoods. This is a useful resource for people inter ested in advocating for policy and social change regarding neighborhood integration, residential mobility, anti-discrimination in housing, urban renewal, school quality and economic opportunities. The Diversity Data project is an ongoing project of the Harvard School of Public Health (Department of Society, Human Development and Health). User FunctionalityUsers can obtain a description, profile and rank of U.S. metropolitan areas and compare ranks across metropolitan areas. Users can also generate maps which demonstrate the distribution of these measures across the United States. Demographic information is available by race/ethnicity. Data NotesData are derived from multiple sources including: the U.S. Census Bureau; National Center for Health Statistics' Vital Statistics Natality Birth Data; Natio nal Center for Education Statistics; Union CPS Utilities Data CD; National Low Income Housing Coalition; Freddie Mac Conventional Mortgage Home Price Index; Neighborhood Change Database; Joint Center for Housing Studies of Harvard University; Federal Financial Institutions Examination Council Home Mortgage Disclosure Act (HMD); Dr. Russ Lopez, Boston University School of Public Health, Department of Environmental Health; HUD State of the Cities Data Systems; Agency for Healthcare Research and Quality; and Texas Transportation Institute. Years in which the data were collected are indicated with the measure. Information is available for metropolitan areas. The website does not indicate when the data are updated.

This statistic shows the results of a survey in 22 states asking respondents who they think has a better life in their country - men or women. The survey was conducted in 2010. 39 percent of respondents from the United States thought that men had a better life in their country, while 23 percent thought that a woman's life in the United States is better than a man's. 24 percent of American respondents thought the life quality of men and women in the United States is the same.

Population Health (BRFSS: HRQOL)

Examining Trends, Disparities and Determinants of Health in the US Population

By Health [source]

About this dataset

The Behavioral Risk Factor Surveillance System (BRFSS) offers an expansive collection of data on the health-related quality of life (HRQOL) from 1993 to 2010. Over this time period, the Health-Related Quality of Life dataset consists of a comprehensive survey reflecting the health and well-being of non-institutionalized US adults aged 18 years or older. The data collected can help track and identify unmet population health needs, recognize trends, identify disparities in healthcare, determine determinants of public health, inform decision making and policy development, as well as evaluate programs within public healthcare services.

The HRQOL surveillance system has developed a compact set of HRQOL measures such as a summary measure indicating unhealthy days which have been validated for population health surveillance purposes and have been widely implemented in practice since 1993. Within this study's dataset you will be able to access information such as year recorded, location abbreviations & descriptions, category & topic overviews, questions asked in surveys and much more detailed information including types & units regarding data values retrieved from respondents along with their sample sizes & geographical locations involved!

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How to use the dataset

This dataset tracks the Health-Related Quality of Life (HRQOL) from 1993 to 2010 using data from the Behavioral Risk Factor Surveillance System (BRFSS). This dataset includes information on the year, location abbreviation, location description, type and unit of data value, sample size, category and topic of survey questions.

Using this dataset on BRFSS: HRQOL data between 1993-2010 will allow for a variety of analyses related to population health needs. The compact set of HRQOL measures can be used to identify trends in population health needs as well as determine disparities among various locations. Additionally, responses to survey questions can be used to inform decision making and program and policy development in public health initiatives.

Research Ideas

• Analyzing trends in HRQOL over the years by location to identify disparities in health outcomes between different populations and develop targeted policy interventions.
• Developing new models for predicting HRQOL indicators at a regional level, and using this information to inform medical practice and public health implementation efforts.
• Using the data to understand differences between states in terms of their HRQOL scores and establish best practices for healthcare provision based on that understanding, including areas such as access to care, preventative care services availability, etc

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: rows.csv | Column name | Description | |:-------------------------------|:----------------------------------------------------------| | Year | Year of survey. (Integer) | | LocationAbbr | Abbreviation of location. (String) | | LocationDesc | Description of location. (String) | | Category | Category of survey. (String) | | Topic | Topic of survey. (String) | | Question | Question asked in survey. (String) | | DataSource | Source of data. (String) | | Data_Value_Unit | Unit of data value. (String) | | Data_Value_Type | Type of data value. (String) | | Data_Value_Footnote_Symbol | Footnote symbol for data value. (String) | | Data_Value_Std_Err | Standard error of the data value. (Float) | | Sample_Size | Sample size used in sample. (Integer) | | Break_Out | Break out categories used. (String) | | Break_Out_Category | Type break out assessed. (String) | | **GeoLocation*...

Harmonized data file as the basis for comparative analysis of quality of life in the Candidate Countries and the European Union member states, based on seven different data sets, one Eurobarometer survey covering 13 Candidate Countries with an identical set of variables conducted in April 2002, the other six Standard Eurobarometer of different subjects and fielded in different years, each with another set of questions identical with the CC Eurobarometer. Selected aggregate indicators of quality of life ... describing the social situation in the EU15 and Candidate Countries.

The countries are tentatively grouped according to affinities following a families of nations logic. The indicators were drawn from various sources, mainly provided by supranational organisations. They are grouped into six categories and recorded in the technical report (page 12 ff.):
(1) economy and employment;
(2) health;
(3) population and family;
(4) inequality and social problems;
(5) modernisation;
(6) political system.

Most indicators refer to the year 2000. Deviations from this rule are explained in the list of indicators, together with definitions, coding, and sources. The indicators are added to the harmonized EB data file for all 28 countries in order to provide an opportunity for multi-level analysis. Selected comprehensive indicators and relevant indices have been defined and constructed for quality of life and subjective well-being as well as for poverty and deprivation measures.

The CC-Eurobarometer contains several questions on the perceived income situation of a household and on the availability or lack of certain consumer goods. It also provides information on the perception of social integration and general acceptance.
(Source: Alber, Jens; Böhnke, Petra; Delhey, Jan; Fliegner, Florian; Gauckler, Britta; Habich, Roland; Keck, Wolfgang; Kohler, Ulrich; Nauenburg, Ricarda; Schiller, Sabine: Quality of Life in the European Union and the Candidate Countries. Technical Report. Results of data inspection, establishing a harmonized data file, recoding procedure and preparation of analysis. Hand-out for the first researchers’ meeting, Brussels, 4-5 March 2003.).

Luxembourg stands out as the European leader in quality of life for 2025, achieving a score of 220 on the Quality of Life Index. The Netherlands follows closely behind with 211 points, while Albania and Ukraine rank at the bottom with scores of 104 and 115 respectively. This index provides a thorough assessment of living conditions across Europe, reflecting various factors that shape the overall well-being of populations and extending beyond purely economic metrics. Understanding the quality of life index The quality of life index is a multifaceted measure that incorporates factors such as purchasing power, pollution levels, housing affordability, cost of living, safety, healthcare quality, traffic conditions, and climate, to measure the overall quality of life of a Country. Higher overall index scores indicate better living conditions. However, in subindexes such as pollution, cost of living, and traffic commute time, lower values correspond to improved quality of life. Challenges affecting life satisfaction Despite the fact that European countries register high levels of life quality by for example leading the ranking of happiest countries in the world, life satisfaction across the European Union has been on a downward trend since 2018. The EU's overall life satisfaction score dropped from 7.3 out of 10 in 2018 to 7.1 in 2022. This decline can be attributed to various factors, including the COVID-19 pandemic and economic challenges such as high inflation. Rising housing costs, in particular, have emerged as a critical concern, significantly affecting quality of life. This issue has played a central role in shaping voter priorities for the European Parliamentary Elections in 2024 and becoming one of the most pressing challenges for Europeans, profoundly influencing both daily experiences and long-term well-being.

Quality of Life Index (higher is better) is an estimation of overall quality of life by using an empirical formula which takes into account purchasing power index (higher is better), pollution index (lower is better), house price to income ratio (lower is better), cost of living index (lower is better), safety index (higher is better), health care index (higher is better), traffic commute time index (lower is better) and climate index (higher is better).

Current formula (written in Java programming language):

index.main = Math.max(0, 100 + purchasingPowerInclRentIndex / 2.5 - (housePriceToIncomeRatio * 1.0) - costOfLivingIndex / 10 + safetyIndex / 2.0 + healthIndex / 2.5 - trafficTimeIndex / 2.0 - pollutionIndex * 2.0 / 3.0 + climateIndex / 3.0);

For details how purchasing power (including rent) index, pollution index, property price to income ratios, cost of living index, safety index, climate index, health index and traffic index are calculated please look up their respective pages.

Formulas used in the past

Formula used between June 2017 and Decembar 2017

We decided to decrease weight from costOfLivingIndex in this formula:

index.main = Math.max(0, 100 + purchasingPowerInclRentIndex / 2.5 - (housePriceToIncomeRatio * 1.0) - costOfLivingIndex / 5 + safetyIndex / 2.0 + healthIndex / 2.5 - trafficTimeIndex / 2.0 - pollutionIndex * 2.0 / 3.0 + climateIndex / 3.0);

The World Happiness 2017, which ranks 155 countries by their happiness levels, was released at the United Nations at an event celebrating International Day of Happiness on March 20th. The report continues to gain global recognition as governments, organizations and civil society increasingly use happiness indicators to inform their policy-making decisions. Leading experts across fields – economics, psychology, survey analysis, national statistics, health, public policy and more – describe how measurements of well-being can be used effectively to assess the progress of nations. The reports review the state of happiness in the world today and show how the new science of happiness explains personal and national variations in happiness.

The scores are based on answers to the main life evaluation question asked in the poll. This question, known as the Cantril ladder, asks respondents to think of a ladder with the best possible life for them being a 10 and the worst possible life being a 0 and to rate their own current lives on that scale. The scores are from nationally representative samples for 2017 and use the Gallup weights to make the estimates representative. The columns following the happiness score estimate the extent to which each of six factors – economic production, social support, life expectancy, freedom, absence of corruption, and generosity – contribute to making life evaluations higher in each country than they are in Dystopia, a hypothetical country that has values equal to the world’s lowest national averages for each of the six factors. They have no impact on the total score reported for each country, but they do explain why some countries rank higher than others.

Quality of life index, link: https://www.numbeo.com/quality-of-life/indices_explained.jsp

Happiness store, link: https://www.kaggle.com/unsdsn/world-happiness/home

ABSTRACT Objective: To evaluate the quality of life and health of elderly in rural areas of Minas Gerais State’s center-west. Method: Cross-sectional study, in four municipalities of Minas Gerais State, by interviewing elderly people. Associations between socio-demographic and quality of life variables were tested, separated into “satisfactory”/“unsatisfactory” with values from the median of positive answers. It was used the chi-square test, Fisher’s test and regression. Results: 182 elderly answered the questions and showed a relation with the “satisfactory” quality of life - bivariate (p < 0.05): age by 69 years (61.6%), married (61.7%), living by 54 years in rural areas (68%), with no financial support (59.5%), living with someone else (61%), non-smoker (60%), presenting good health (76.7%), satisfied with life (69.6%); regression: not having financial support, living with someone else and not smoking. Conclusion: Elderly people in rural areas present good quality of life/health in the cognitive aspect, access to services, goods, habits, but awareness must be constant due to their weakness.

In an April 2024 online survey, an overwhelming majority of respondents in the United States said that **** U.S. dollars per hour is not enough for the average American worker to have a decent quality of life. The U.S. federal minimum wage has not been raised since 2009. Since then, many states have raised the wage, with a number of states having more than doubled the federal minimum.