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Include the following information:

Your names

Name of datasets

Link to datasets

Organizations that created/monitor data set

Description of what they are looking at

How does this represent a social determinant of health?

One interesting data you’ve noticed from each dataset

Photo (optional)

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https://www.bls.gov/web/laus/lauhsthl.htm

Local Area Unemployment Statistics, is a dataset monitored and maintained by the Bureau of Labor Statistics. They monitor unemployment rates by numerous different metrics, including by state. Unemployment can play a critical role and be a social determinant of health in itself, as it affects a person's ability to fund a living for themselves or pay for access to food, shelter, and healthcare. One interesting thing we noticed for the dataset, when looking at unemployment rates by state, rates were record high in almost all states in April 2020, which is when the Covid-19 pandemic began. Now, especially last year around spring 2023, some states are hitting record lows, a big difference from when the pandemic began.

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Syra Frankel, Alhambra Helmi, Amanda Amgalan

North Carolina Violent Crime (2012-2022)

https://cde.ucr.cjis.gov/LATEST/webapp/#/pages/explorer/crime/crime-trend

The organization that creates and monitors these data sets on the site is the FBI

In this data set, they are focusing on trend rate of violent crime in the state of North Carolina from 2012-2022 and comparing it with the United States trend rate of the same crimes during the same time period. The data set itself is then broken down into catergories of different demographics.

This represents a SDoH because it displayed shows the state and quality of the neighborhood and built envrionment that the people live. It shows that the environment has become less safe over time with an increased rate of violent crime as well as how one demographic is targeted and commiting these crimes over others.

One interesting data we noticed was the relationship link between the violent crime. While 4,399 crimes were of unknown relationships, the second highest was 3,847 in domestic between partners in a relationship.

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Meena, Kat, Makena, Raghad

The name of the dataset is The Climate and Economic Justice Tool. President Joe Biden worked alongside the Council on Environmental Quality to create this dataset that works to serve underserved and underdeveloped communities that could be suffering from long-term, pollution, disasters, climate change, and much more. The main goal is to use this dataset to issue 40% of the investments catered towards a cleaner planet, to these struggling communities. Social Determinants of Health are social factors that can impact an individual's and community's health. By addressing the environmental factors of these disadvantaged communities, they aim to improve the community's health hence why this is a representation of SDoH. One interesting fact that I noticed from the dataset is that 16% of the city of Fairfax are 64 years or older.

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Austin & Matthew

County Health Ranking & Roadmaps

Fairfax, Virginia | County Health Rankings & Roadmaps

University of Wisconsin Population Health Institute (Publisher)

Comparison of different counties throughout America, more specifically the different health factors/risks.

It ranks and compares the health outcomes and health factors of different counties to each other within the US. Detailing county percentages and shows it compares to the national average.

Within Fairfax county there is 100% access to exercise opportunities—4% higher Alcohol-impaired driving deaths.

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Isabella & Ana

Local Area Unemployment Statistics

https://www.bls.gov/lau/

U.S. Bureau of Labor Statistics (BLS)

The BLS is produces monthly and annual employment, unemployment, and labor force data for Census regions and divisions, States, counties, and many cities, by place of residence

Where there is a lot of unemployment, there's more poverty and an increase and negative impacts on a persons quality of health (mental, physical health, substance use, etc.)

I looked at Nevada and they had a rating of 5.4%

Food Environment Atlas

https://www.ers.usda.gov/data-products/food-environment-atlas/

U.S. Department of Agriculture (USDA), Economic Research Service (ERS)

This dataset looks at the number of fast food restaurants in 2011 versus 2016 in different counties in the country.

The availability of fast food, or type of food in general in an area is a big contributor to SDoH. If the only food around you is unhealthy. it makes it very hard to change your eating habits to something more nutritious.

In 2011, the number of fast food restaurants in Richmond, VA was 179. There was a 5.02% increase from 2011-2016, where there were 188.

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The Local Area Unemployment Statistics (LAUS) program produces monthly and annual employment, unemployment, and labor force data for Census regions and divisions, States, counties, metropolitan areas, and many cities, by place of residence. More "

Announcements

For information on the implementation of an outlier treatment improvement affecting data comparability between August and September 2021 Read More "

For information on changes to model-based estimation Read More "

For information on implementation plans of the federal-state cooperative programs for new metropolitan and micropolitan area delineations Read More "

How can I apply for unemployment insurance?

The Bureau of Labor Statistics does not administer or oversee unemployment insurance (UI) programs. You should contact your State workforce agency for information, using the Department of Labor's Career Onestop Service Locator.

Next Releases:

The State Employment and Unemployment data for January 2022 are scheduled to be released on March 14, 2022, at 10:00 A.M. Eastern Time.

The Metropolitan Area Employment and Unemployment data for January 2022 are scheduled to be released on March 18, 2022, at 10:00 A.M. Eastern Time.

December jobless rates down in 42 states; payroll jobs up in 17 states

In December, unemployment rates were lower in 42 states and the District of Columbia and stable in 8 states. Nonfarm payroll employment increased in 17 states and was essentially unchanged in 33 states and the District.
HTML | PDF | RSS | Charts

Dec. jobless rates down over the year in 375 of 389 metro areas; payroll jobs up in 108

Jobless rates were lower in December than a year earlier in 375 of the 389 metropolitan areas, higher in 13, and unchanged in 1. Nonfarm payroll employment was up in 108 metropolitan areas over the year and essentially unchanged in 281.
HTML | PDF | RSS | Charts

Current

State Employment and Unemployment (HTML) (PDF)

Metropolitan Area Employment and Unemployment (HTML) (PDF)

Subscribe to the BLS News Service- receive BLS economic news releases by e-mail.

Schedule of Upcoming Releases

Annual

Annual average unemployment rates increased in all 50 states and the District of Columbia in 2020. Employment-population ratios decreased in all 50 states and the District.
HTML | PDF | RSS

Archived
Caution: data in many archived news releases have been revised in subsequent releases.

Please note that the "Get Detailed LAUS Statistics" tools for data retrieval will be unavailable from 10:00 AM to approximately 10:30 AM on the day of a Local Area Unemployment Statistics release because the LAUS database is updated during that time. Schedules of upcoming release dates are available as follows:

Instructions for Extracting Data--Quick, easy instructions on how to extract Local Area Unemployment Statistics (LAUS) data.

Databases

Create Customized Maps

Maps

Mapping Unemployment Rates (States and Counties)

Series Report -Already know the series identifier for the statistic you want? Use this shortcut to retrieve your data.

Monthly

STATEWIDE DATA

METROPOLITAN AREA DATA

COUNTY DATA

Table

Labor force data by county, not seasonally adjusted, latest 14 months (TXT) (ZIP 1,847KB)

Map

Unemployment rates by county, latest 12-month averages (GIF) (PDF)

Annual Average

STATEWIDE DATA

Tables

Maps

Latest annual average State unemployment rates (GIF) (PDF)

Latest over-the-year change in unemployment rates by State (GIF) (PDF)

Latest employment-population ratios by State (GIF) (PDF)

Historical State unemployment rate maps (ZIP) (PDF)
How to View Zip Files

METROPOLITAN AREA DATA

Tables

Maps

Latest annual average metropolitan area unemployment rates (GIF) (PDF)

Historical metropolitan area unemployment rates (ZIP 1.8M) (PDF 1.9M)

How to View Zip Files
COUNTY DATA

Tables

Labor force data by county, 2020 annual averages (TXT, XLS)

Labor force data by county, 2019 annual averages (TXT, XLS)

Labor force data by county, 2018 annual averages (TXT, XLS)

Labor force data by county, 2017 annual averages (TXT, XLS)

Labor force data by county, 2016 annual averages (TXT, XLS)

Labor force data by county, 2015 annual averages (TXT, XLS)

Labor force data by county, 2014 annual averages (TXT, XLS)

Labor force data by county, 2013 annual averages (TXT, XLS)

Labor force data by county, 2012 annual averages (TXT, XLS)

Labor force data by county, 2011 annual averages (TXT, XLS)

Labor force data by county, 2010 annual averages (TXT, XLS)

Labor force data by county, 2009 annual averages (TXT, XLS)

Labor force data by county, 2008 annual averages (TXT, XLS)

Labor force data by county, 2007 annual averages (TXT, XLS)

Labor force data by county, 2006 annual averages (TXT, XLS)

Labor force data by county, 2005 annual averages (TXT, XLS)

Labor force data by county, 2004 annual averages (TXT, XLS)

Labor force data by county, 2003 annual averages (TXT, XLS)

Labor force data by county, 2002 annual averages (TXT, XLS)

Labor force data by county, 2001 annual averages (TXT, XLS)

Labor force data by county, 2000 annual averages (TXT, XLS)

Labor force data by county, 1999 annual averages (TXT, XLS)

Labor force data by county, 1998 annual averages (TXT, XLS)

Labor force data by county, 1997 annual averages (TXT, XLS)

Labor force data by county, 1996 annual averages (TXT, XLS)

Labor force data by county, 1995 annual averages (TXT, XLS)

Labor force data by county, 1994 annual averages (TXT, XLS)

Labor force data by county, 1993 annual averages (TXT, XLS)

Labor force data by county, 1992 annual averages (TXT, XLS)

Labor force data by county, 1991 annual averages (TXT, XLS)

Labor force data by county, 1990 annual averages (TXT, XLS)

Maps

CITY DATA

Tables

Other BLS Programs

Labor Force Statistics from the Current Population Survey-national data on employment, unemployment, earnings, and other labor market topics by demographic characteristics.

Employment, Hours, and Earnings from the Current Employment Statistics survey (National)-monthly national data by detailed industry on employment, hours, and earnings of workers on the payrolls of nonfarm establishments.

Employment, Hours, and Earnings from the Current Employment Statistics survey (State and Metro Area)-monthly data on employment, hours, and earnings by industry and geographic area.

Quarterly Census of Employment and Wages-comprehensive employment and wage data by industry and geographic area for workers covered by State Unemployment Insurance laws.

Job Openings and Labor Turnover Survey (JOLTS)-monthly data on job openings, hires, and separations that serve as demand-side indicators of labor shortages at the national level.

Occupational Employment Statistics-data on employment and wages for over 800 occupations and for about 400 nonfarm industries for the nation, plus occupational data for States and metropolitan areas.

National Longitudinal Surveys-several surveys gathering information at multiple points in time about the labor market and life experiences of six groups of American men, women, and youth.

Mass Layoff Statistics-reports on mass layoff actions that result in workers being separated from their jobs.

Other Useful Links

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Local Area Unemployment Statistics Home Page

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The Local Area Unemployment Statistics (LAUS) program produces monthly and annual employment, unemployment, and labor force data for Census regions and divisions, States, counties, metropolitan areas, and many cities, by place of residence.

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Data Base #51 (Iris Zhang & Adriana Lazo) 

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Data Base #51 (Iris Zhang & Adriana Lazo) 

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-Name of datasets

Opioid Overdose Death Rates and All Drug Overdose Death Rates per 100,000 Population (Age-Adjusted)

-Link to datasets

https://www.kff.org/other/state-indicator/opioid-overdose-death-rates/?currentTimeframe=0&sortModel=%7B%22colId%22:%22Location%22,%22sort%22:%22asc%22%7D

-Organizations that created/monitor data set

Kaiser Family Foundation

-Description of what they are looking at

They are looking at the opioid overdose death rate & all drug overdose death rates among all the states

-How does this represent a social determinant of health?

Showed significant regional differences by comparing  the opioid overdose death rate & all drug overdose death rates among all the states per 100,000 Population in the U.S.,

-One interesting data you’ve noticed from each dataset

The state that has the highest opioid & all drug overdose death rate is West Virginia.

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Nelly Vilchez, El Shaddai, Laila Angulo 

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Nelly Vilchez, El Shaddai, Laila Angulo 

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Atlas of Rural and Small-Town America

• Data: https://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america/

Economic Research Service and U.S Department of Agriculture

They are looking at socioeconomic factors such as People, jobs, county classifications, income, and veterans in rural areas and small towns in America.

Social, economic factors affect health outcomes for this populations.

One interesting piece of data that the article contains is that the US maps showing the rural places, it shows the unemployment/employment estimates in the rural areas.

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Mikayla Jimenez, Paris Stephens, Madeleine Pineda

Name of dataset: Incidence Rate Report for Breast Cancer in Asian American/Pacific Islander Women <50 years

Link: State Cancer Profiles > Incidence Rates Table

Organization: National Cancer Institute

Description: In Fairfax County, there is an average annual count of 32; The recent trend has been stable, but has been projected to be decreasing in recent 5 year trends.

Social Determinant: Fairfax county is one of the well-funded urban counties, which is why the prevalence is low.

One interesting fact we found is that Fairfax County has one of the lowest rates of breast cancer in the United States.

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State Cancer Profiles > Incidence Rates Table

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Data base exploration!  Adriana Lazo & Iris Zhang

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Data base exploration!  Adriana Lazo & Iris Zhang

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Name of date set: Map the Meal Gap

Link: https://www.feedingamerica.org/research/map-the-meal-gap/how-we-got-the-map-data?s_src=WXXX1MTMG&_ga=2.104619904.1850497459.1590978449-310630678.1590978449

Organization: Feeding America

Description: This data helps generate estimates for local food insecurities for target groups, local federal program eligibility among those experiencing food insecurity, as well as food spending and budget shortfalls.

Representation of SDoH: It represents because the data focuses on a condition that affects a wide range of outcomes and risk. For example, food insecurity can lead to malnutrition, decrease in quality of life, among many other factors in target groups.

Interesting data: Food tax rates by state for grocery stores broken into those that levy and those that don't

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Map the Meal Gap generates the following estimates:

1. Local food insecurity among all individuals and children, and by select races/ethnicities

2. Local federal program eligibility among all individuals and children experiencing food insecurity

3. Additional dollars needed among people estimated to be food insecure (a.k.a., food budget shortfall)

4. Food spending by people who are food secure (a.k.a., average meal cost)

This page offers an overview of the Map the Meal Gap methodology and links to technical briefs that provide greater detail about the methods and data. Read the most recent technical brief for the latest Map the Meal Gap study released in 2024 and reflecting 2022 data and an overview of the available data part of the study.

Food insecurity rates and numbers

The relationship between food insecurity and its closely linked indicators (poverty, unemployment, homeownership, disability prevalence, etc.) are first analyzed at the state level. Then, the coefficient estimates from this analysis are used with the same variables for every county and congressional district. Together, these variables can generate estimated food insecurity rates for individuals and children at the local level.

Food budget shortfall

Responses from food insecure households to the Current Population Survey questions about a food budget shortfall are calculated at the individual level and then averaged to create a weekly food budget shortfall. This national average weekly shortfall can be annualized by multiplying the estimate by 52 (weeks per year) and again by 7/12 (the average number of months in a year that food-insecure households experience food insecurity per the U.S. Department of Agriculture).

Cost-of-food index

NielsenIQ assigns every sale of UPC-coded food items in a county to one of the food categories in the USDA Thrifty Food Plan (TFP) and then weights those categories based on actual pounds purchased per week. We then apply county and sales tax rates to the NielsenIQ market basket prices to create a relative price index that, when applied to the national average meal cost and national food budget shortfall, reveals differences in the cost of food at the local level.

National average meal cost

The average dollar amount spent on food per week by food-secure individuals is divided by 21 (assuming 3 meals per day and 7 days per week). Reported food expenditures by food-secure individuals are used to ensure that the result best reflects the cost of an adequate diet. We then adjust the national average cost per meal by a relative food cost index to derive a local estimate.

Annual Technical Briefs

Since 2013, Feeding America has released an annual Map the Meal Gap report that featured data on both child and overall food insecurity.

In 2011 and 2012, Feeding America released separate Map the Meal Gap reports for overall and child food insecurity.

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Map the Meal Gap Methodology | Feeding America

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Map the Meal Gap presents crucial facts about food insecurity across the country. Learn more about how we got the data & join the fight against hunger.

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Names:

Alaa

Nallely

Names of Datasets:

Food Environment Atlas

Link to Datasets:

https://www.ers.usda.gov/data-products/food-environment-atlas/data-access-and-documentation-downloads/

Organization that monitor data set:

U.S. Department of Agriculture (USDA)

Description of what they are looking at:

They oversee multiple sectors related to foods such as store/restaurants proximity, cost of food, monitor food assistance programs such as SNAP.

Observe food choices and diet quality based on environment.

How this represents Social Determinants of health:

Diet and Nutrition effect your physical health greatly and your neighborhood effects your choices. For example living in food deserts will effect your health negatively because you do not have a variety of choices that are affordable, nutritious, or cultural foods.

Interesting data:

The data on supplemental programs by state was very interesting. The states that had the most people enrolled in these programs were the states with the greatest populations and it did not matter whether the state is typically a red or blue state.

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The current version of the Food Environment Atlas has more than 280 variables, including new indicators on food banks and nutrition assistance program participation rates. All of the data included in the Atlas are aggregated into an Excel spreadsheet for easy download. These data come from a variety of sources and cover varying years and geographic levels. The documentation for each version of the data provides complete information on definitions and data sources.

In the downloadable Excel spreadsheets:

State and county Federal information processing standards (FIPS) codes are provided.

The variable lookup file links the short field descriptions (indicator names) used in the data file with the longer indicator names used in the Atlas.

Unless otherwise noted with asterisks on the longer indicator names (in the variable lookup file), indicators are county-level measures. A single asterisk * denotes a State-level indicator, while a double asterisk ** denotes a regional-level indicator.

"No data" fields are empty or referenced with "-9999".

Supplemental data are provided in additional tabs (State- and county-level data are provided separately).

Errata: On September 10, 2020, the Food Environment Atlas data files were reposted after duplicate county records were removed from the Local category. The two counties that had duplicate records were Chester, PA (FIPS code = 42029) and Mecklenburg, NC (FIPS code = 37119).

No other values were affected.

The current version of the Food Environment Atlas data file and documentation, along with six previous versions of the data and documentation, are available:

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All of the data included in the Atlas are aggregated into Excel spreadsheets for easy download. These data are from a variety of sources and cover varying years and geographic levels. Definitions, descriptions of data, and data sources for food environment indicators are provided in the documentation.