Quality of Life by State 2024

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This dataset provides insights into the quality of life across different states in the United States for the year 2024. Quality of life, encompassing aspects like comfort, health, and happiness, is evaluated through various metrics including affordability, economy, education, and safety. Dive into this dataset to understand how different states fare in terms of overall quality of life and its individual components.

Columns Description

• State: The name of the U.S. state.
• QualityOfLifeTotalScore: The total score representing the overall quality of life for the respective state. This score is calculated based on various quality of life metrics.
• QualityOfLifeQualityOfLife: The score representing the quality of life aspect for the respective state. This aspect may include subjective factors related to happiness, satisfaction, and overall well-being. Higher scores may indicate a higher level of subjective well-being, happiness, or overall satisfaction among residents. Lower scores could suggest lower levels of subjective well-being.
• QualityOfLifeAffordability: The score representing the affordability aspect of the quality of life for the respective state. This aspect evaluates factors such as cost of living, housing affordability, and income levels. Higher scores typically indicate greater affordability of housing, cost of living, and basic necessities. Lower scores may suggest that these essentials are less accessible or more expensive for residents.
• QualityOfLifeEconomy: The score representing the economic aspect of the quality of life for the respective state. This aspect assesses factors such as employment opportunities, economic growth, and income distribution. Higher scores may reflect a stronger economy with more job opportunities, higher incomes, and lower levels of poverty. Lower scores might indicate economic challenges such as unemployment or income inequality.
• QualityOfLifeEducationAndHealth: The score representing the education and health aspect of the quality of life for the respective state. This aspect considers factors such as access to quality education, healthcare facilities, and overall public health indicators. Higher scores generally signify better access to quality education, healthcare services, and overall public health. Lower scores may indicate deficiencies in these areas, such as limited access to healthcare or lower educational attainment levels.
• QualityOfLifeSafety: The score representing the safety aspect of the quality of life for the respective state. This aspect evaluates factors such as crime rates, public safety measures, and community well-being initiatives. Higher scores suggest lower crime rates, better community safety, and a higher sense of security among residents. Lower scores may indicate higher crime rates or concerns about safety.

These descriptions provide an overview of what each column represents and the specific aspects of quality of life they assess for each U.S. state.

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

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).

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.

The dataset contains US counties ranking data based on measures of health outcomes and health determinants. The measures used to establish counties ranks are related to length and quality of life for health outcomes and to health behavior, clinical care, socioeconomic and physical environment factors for health determinants. US counties are described along with their FIPS (Federal Information Processing Standard) code and the US state they belong.

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.

Behavioral Risk Factors: HRQOL

Analyzing Health-Related Quality of Life in the United States

By Health [source]

About this dataset

The Behavioral Risk Factor Surveillance System (BRFSS) is an annual state-based, telephone survey of adults in the United States. It collects a variety of health-related data, including Health Related Quality of Life (HRQOL). This dataset contains results from the HRQOL survey within a range of locations across the US for the year indicated.

This dataset includes 14 columns which summarize and quantify different aspects concerning HRQOL topics. The year, location abbreviation, description and geo-location provide background contextual information which help define each row. The question column indicates the response provided to by respondents, while category classifies it into overarching groupings. Additionally there are columns covering sample size and data value attributes such as standard error, unit and type all evidence chipping away at informative insights into how Americans’ quality of life is changing over time — all cleverly presented in this one concise dataset!

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How to use the dataset

In order to analyze this dataset, it is important have a good understanding of the columns included in it. The columns provide various pieces of information about the data such as year collected, location abbreviation, location name and type of data value collected. Furthermore, understanding what each column means is essential for proper interpretation and analysis; for example knowing that ‘Data_Value %’ indicates what percentage responded a certain way or that ‘Sample_Size’ shows how many people were surveyed can help you make better decisions when looking at patterns within the data set.

Once you understand the general structure behind this dataset one should also familiarize themselves with some basic statistical analysis tools such as mean/median/mode calculations comparative/correlative analysis so they can really gain insights into how health-related quality of life affects different populations across countries or regions.. To get even more meaningful results you might also want to consider adding other variables or datasets into your report that correlate with HRQOL - like poverty rate or average income level - so you can make clearer conclusions about potential contributing factors towards certain insights you uncover while using this dataset alone.

Research Ideas

• Identifying trends between geolocation and health-related quality of life indicators to better understand how environmental factors may impact specific communities.
• Visualizing the correlations between health-related quality of life variables across different locations over time to gain insights on potential driving developmental or environmental issues.
• Monitoring the effects of public health initiatives dealing with qualitative health data such as those conducted by CDC, Department of Health and Human Services, and other organizations by tracking changes in different aspects of HRQOL measures over time across multiple locations

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 when the data was collected. (Integer) | | LocationAbbr | Abbreviations of various locations where data was recorded. (String) | | LocationDesc | Full names of states whose records are included in this survey. (String) | | Category | Particular topic chosen for research such as “Healthy People 2010 Topics” or “Older Adults Issues”. (String) | | Question | Each question corresponds to metrics tracked within each topic. (String) | | DataSource | Source from which survey responses were collected. (String) | | Data_Value_Unit | Units taken for recording survey types...

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.

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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Featured Notebooks

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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*...

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 dataset is a continuation of one created seven years earlier, QUALITY OF AMERICAN LIFE, 1971 (ICPSR 3508). In the 1978 study, a national sample was drawn that included many respondents from the 1971 study. The purpose of the study was to survey Americans about their perceived quality of life by measuring their perceptions of their socio-psychological condition, their needs and expectations from life, and the degree to which those needs were satisfied. The data, similar in scope and content of that in the 1971 survey, were collected via personal interviews from a nationwide probability sample of 3,692 persons 18 years of age and older during the summer of 1978. Closed and open-ended questions were used to probe respondents' satisfactions, dissatisfactions, aspirations, and disappointments in a variety of life domains, such as dwelling/neighborhood, local services (e.g., police, roads, and schools), public transportation, present personal life, life in the United States, education, occupation, job history/expectation, work life, housework, leisure activities, organizational affiliations, religious affiliation, health problems, financial situation, marriage (including widowhood, divorce, and separation), children/family life, and relationships with family and friends. In addition to broad questions about satisfaction with each of these domains and their importance to the respondents, specific sources of gratification and frustration were explored. Other questions focused on life as a whole and about the extent to which respondents felt they had control over their lives (e.g., rating of various aspects of life, (dis)satisfaction with life, personal efficacy, and social desirability measures). A major difference between this study and the earlier study is that the 1978 respondents were asked more detailed questions concerning their perceived financial status relative to their family, friends, and past personal financial status. Personal data include sex, age, race, ethnic background, childhood family stability, military service, and father's occupation and education. Observational data are included on housing and neighborhood characteristics as well as respondents' appearance, intelligence, and sincerity.

In 2023, Uruguay and Chile had the highest Digital Quality of Life index in Latin America and the Caribbean region, at **** and **** points on a scale from zero to one, respectively. In comparison, Venezuela and Honduras scored the lowest index among the presented countries. The index ranks the quality of digital wellbeing in a country.

This is an EnviroAtlas (https://www.epa.gov/enviroatlas) web service supporting research, education, and decision-making. EnviroAtlas includes a user-friendly interactive map for data discovery, https://enviroatlas.epa.gov/enviroatlas/interactivemap.Access Data Fact Sheet: Fact SheetAccess Full Metadata: CONUSAccess Web Service: https://services.arcgis.com/cJ9YHowT8TU7DUyn/arcgis/rest/services/Threshold_income_for_quality_of_life_Household_$_per_year/FeatureServerTo cite these data, please use this format: United States Environmental Protection Agency. EnviroAtlas. Threshold income for quality of life (Household $ per year). Accessed: [Month, Day, Year] from https://www.epa.gov/enviroatlas.Please contact us with any questions!

BackgroundDisparities in healthcare access, driven by socioeconomic status and social determinants of health (SDOH), contribute to poor health outcomes. While prior studies established the relationship between SDOH and care access, fewer have explored their joint relationships with social satisfaction and health challenges across the lifespan. Rather than assessing direct associations between dental care utilization and physical or mental difficulties, this study examines broader interrelationships among SDOH, access to oral health care, and self-reported health challenges.MethodsA cross-sectional study using a lifespan approach–by examining participants within discrete age groups–was conducted on 127,886 individuals aged 18 years and older who participated in the All of Us research program and completed the “Basics”, “Overall Health” and “Health Care Access and Utilization” questionnaires. The distribution of participants' SDOH and self-reported health difficulties was presented and stratified by dental care utilization, income group and age across the lifespan. Multivariate logistic regression analyses were performed to assess the associations between SDOH and access to oral health care.ResultsAcross age groups, a consistent trend of disadvantaged social determinants associated with lacking oral health care utilization was noted. Young participants (18–35 years old) were the most likely to report not having received oral health care within the past 12 months (32.2%), worse mental health (29.6%, fair/poor), emotional problems (31.8%), and difficulties in concentrating or remembering (18%). Notably, young adults who did not visit a dentist within 12 months were also more likely to report not visiting a medical doctor (18.1%), being unable to afford copayment (69%), and more frequently using emergency or urgent care (20.2%). No insurance coverage [odds ratio (OR) = 1.67, 95% confidence interval (CI): 1.52–1.84], annual income less than $35,000 (OR = 3.79, 95% CI: 3.58–4.01), and housing instability (OR = 1.38, 95% CI: 1.32–1.44) were all significantly associated with lack of dental care.ConclusionThis study confirms that SDOH—particularly income and housing instability—significantly impact individuals' ability to afford and access healthcare services, including dental care. These disparities were most pronounced among the youngest age group. Our findings support future policy interventions aimed at integrating dental care into overall healthcare, especially during early adulthood.

In 2022, approximately 47 percent of survey respondents who had been diagnosed with chronic obstructive pulmonary disease (COPD) in the United States said that COPD had negatively impacted their social life/relationships with friends. A further 43 percent stated experiencing a negative impact on their mood due to the disease.

In an April 2024 online survey, an overwhelming majority of respondents in the United States, regardless of which political party they identified with, 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.

The social environment represents the external conditions under which people engage in social activity within their community. It includes aspects of social opportunity, leisure and recreation, education, access to health services, health status and participation in democratic processes. Fourteen indicators have been used to assess aspects of quality of the social environment.

This is an EnviroAtlas (https://www.epa.gov/enviroatlas) web service supporting research, education, and decision-making. EnviroAtlas includes a user-friendly interactive map for data discovery, https://enviroatlas.epa.gov/enviroatlas/interactivemap. Access Data Fact Sheet: Fact Sheet Access Full Metadata: CONUS Access Web Service To cite these data, please use this format: United States Environmental Protection Agency. EnviroAtlas. Percentage of households below the quality of life threshold income. Accessed: [Month, Day, Year] from https://www.epa.gov/enviroatlas. Please contact us with any questions!

Key quality of life indicators - housing costs, arts.