Blog & News
State Health Compare Users Can Now Explore Unemployment by Race/Ethnicity
November 18th, 2020:SHADAC has updated our State Health Compare online data tool to provide estimates of unemployment according to race and ethnicity. Previously, State Health Compare users could analyze unemployment nationwide and at the state level for years 2000 to 2019, but subgroup analyses were not possible. Now, users can explore State Health Compare’s unemployment estimates, which come from the federal Bureau of Labor Statistics, by four racial/ethnic breakdowns: Hispanic/Latino, African-American/Black, Asian and White.
Why This Change Matters
Racial/ethnic breakdowns provide an important lens for analyzing unemployment as a social determinant of health, with unemployment often varying widely across racial/ethnic categories in a way that can be masked by a consideration of population-wide unemployment numbers. We see this scenario at the national level, where the overall unemployment rate in 2019 was 3.7%, but an examination of unemployment for racial/ethnic subgroups reveals 2.7% unemployment among Asian Americans, 3.3% unemployment among Whites, 4.3% unemployment among Hispanics/Latinos, and 6.1% unemployment among African-Americans/Blacks.
Minnesota provides a state case that parallels the national picture on this point. If we look at statewide unemployment in 2019, we find that Minnesota’s unemployment rate was 3.2%, which is 0.5 percentage points below the national rate of 3.7%. However, if we look at the numbers sorted by race/ethnicity, a different picture emerges: The rate for Asians in Minnesota is 2.4%, Whites are at 3.0%, Hispanics/Latinos are at 5.0%, and African-Americans/Blacks are at 5.5%. Not only do Hispanics/Latinos and African-Americans/Blacks have higher unemployment rates than Whites and Hispanics/Latinos, but their rates are also above the broader Minnesota state average, as well as the national average. Thus, what looks at first glance like a state doing well on unemployment turns out to be a state with major disparities in unemployment for certain racial/ethnic subgroups.
An examination of trends in unemployment over time confirms that the 2019 data for Minnesota are not an anomaly. Though unemployment numbers for Asians in Minnesota were less stable from year to year, White Minnesotans consistently had unemployment rates below those of Hispanic/Latino Minnesotans each year during the 10-year period from 2009 to 2019, and African-American and Black Minnesotans consistently had the highest unemployment rates of any analyzed racial/ethnic group during this time (Figure 1.)
Figure 1. Unemployment in Minnesota by Race/Ethnicity, 2009-2019
The Importance of Considering Individual States
Additionally, it is worth exploring both overall and racial/ethnic subgroup numbers within each individual state, as there is considerable variation both across states and between states and the nation. Washington state, for example, saw an overall unemployment rate of 4.3%, or 0.6 percentage points above the national rate. And among racial/ethnic subgroups, Washington’s numbers followed a different pattern than that seen nationally, with African-Americans/Blacks having the second lowest unemployment rate (4.2%), Whites having the third lowest rate (4.3%), and Hispanics/Latinos having the highest rate (5.7%).
Nevada is another state that had 2019 unemployment numbers that differed from the national story when looking at racial/ethnic breakdowns. Like Washington, Nevada’s state’s overall unemployment rate of 3.9% was above the national rate. However, unemployment in Nevada was second lowest among Hispanics/Latinos (3.8%), third lowest among Whites (3.9%), and highest among African-Americans/Blacks (5.9%).
Figure 2. Unemployment in by Race/Ethnicity, 2019: United States, Nevada, Washington
Taking these state variations into consideration, it’s clear that efforts to analyze and/or address disparities in unemployment by race/ethnicity would potentially look different in Washington and Nevada, or even going to back our example in Minnesota, based on their respective divergences in overall and subgroup numbers.
Discussion: Unemployment as a Social Determinant of Health
Unemployment has important implications for health and health care, as employment affects access to stable housing, food, and health insurance coverage and care. At the same time, unemployment can also have a number of direct negative health consequences, including depression, anxiety, and stress-related illness such as high blood pressure, stroke, heart attack, heart disease, and arthritis.1-7
An examination of unemployment that takes into consideration important nuances in unemployment numbers among subgroups reveals the need for critical, targeted attention to unemployment, even in states where unemployment appears to be trending well overall. Consideration of interstate variation of unemployment by race/ethnicity reveals that policy levers to address unemployment that take race/ethnicity into consideration will require state-specific modifications as well.
Explore the Data
Visit State Health Compare to learn more about unemployment by race/ethnicity within and across the states.
About the Estimates
State Health Compare’s estimates of unemployment are produced using data from the federal Bureau of Labor Statistics and represent the percent of the civilian labor force (age 16 and older) that was unemployed. State refers to place of residence.
1 Avendano, M., Berkman, L. F. (2014). Labor markets, employment policies, and health. In L. F. Berkman, I. Kawachi, & M. Glymour (Eds.), Social Epidemiology (2nd ed., pp. 182-233). Open University Press.
2 Murray, L. R. (2003). Sick and tired of being sick and tired: scientific evidence, methods, and research implications for racial and ethnic disparities in occupational health. Am J Public Health, 93(2), 221-226.
3 Kasl, S. V., Cobb, S. (1970). Blood pressure changes in men undergoing job loss: a preliminary report. Psychosom Med, 32(1), 19-38.
4 Frumkin, H. E., Walker, D., Friedman-Jiménez, G. (1999). Minority workers and communities. Occup Med, 14(3), 495-517.
5 James, S. A., LaCroix, A. Z., Kleinbau, D. G., Strogatz, D. S. (1984). John Henryism and blood pressure differences among black men. II. The role of occupational stressors. J Behav Med, 7(3), 259-275.
6 Robert Wood Johnson Foundation. (2013). How does employment—or unemployment—affect health? Health policy snapshot. Available from http://www.rwjf.org/content/dam/farm/reports/issue_briefs/2013/rwjf403360
7 U.S. Department of Labor, Bureau of Labor Statistics. (2012). A profile of the working poor, 2010. News release. Available from https://www.bls.gov/opub/reports/working-poor/archive/workingpoor_2010.pdf
Blog & News
November 10th Webinar - "Overdose Crisis in Transition: Changing Trends in a Widening Drug Death Epidemic"
November 24, 2020:Mr. Planalp was joined by SHADAC Research Fellow Robert Hest, who explained how to access and use the data on opioid-related overdose deaths and sales of opioid painkillers through SHADAC’s State Health Compare website. Slides from the presentation, as well as a list of further SHADAC resources regarding the opioid crisis can be found at the bottom of this page.
Speakers
Colin Planalp, MPA
SHADAC Senior Research Fellow
Robert Hest, MPP
SHADAC Research Fellow
Event Resources
The Opioid Epidemic (SHADAC Resource Page)
Overdose Crisis in Transition: Changing National and State Trends in a Widening Drug Death Epidemic (Briefs)
50-State Analysis of Drug Overdose Trends: The Evolving Opioid Crisis Across the States (Infographics)
After drop in 2018, newer data indicate a resurgence in drug overdose deaths
Blog & News
October 21st Webinar - Rising Suicide Rates: Examining Trends and Variations through State-level Data
October 26, 2020:Over the past two decades, the rise in suicide death rates has continued along an accelerating climb. According to new vital statistics data from the Centers for Disease Control and Prevention (CDC), the United States suicide rate reached another historic high of 14.2 per 100,000 people in 2018, up from 14.0 in the previous year.
This increase in suicide deaths has not followed a consistent trend; rather, growth has accelerated more recently. From 2000 to 2009 the suicide death rate grew by 13 percent, but from 2009 to 2018 the rate grew by 21 percent. While these trends predate the COVID-19 pandemic, early evidence has indicated this crisis is taking a significant toll on mental health, and these data therefore represent an important baseline from which the effects of the pandemic will be measured.
During the webinar, SHADAC Research Fellow Carrie Au-Yeung used national and state-level data on suicide deaths to examine this growing public health issue, highlighting concerning trends and variations in suicide deaths by geographic locations such as regions, states, and metropolitan areas, as well as by specific subpopulation groups such as age, sex, and race/ethnicity.
Ms. Au-Yeung was also joined by SHADAC Research Fellow Robert Hest, who explained how to access and use the data on suicide deaths through SHADAC’s State Health Compare website. Senior Research Fellow Colin Planalp also joined the webinar for a question and discussion session following the presentation.
Related Resources
Suicide Rates on the Rise: Examining Continuing Trends and Variation across the Nation and in the States from 2000 to 2018 (Briefs)
U.S. Suicide Death Rate Reached Record High in 2018: SHADAC Briefs Examine the Numbers among Subgroups and States
State Health Compare Data Offer Baseline for Measuring Pandemic's Impact on Suicide, Drug Overdose Death Rates
National Suicide Prevention Lifeline: 1-800-273-8255
If you’re thinking about suicide, are worried about a friend or loved one, or would like emotional support, the Lifeline network is available 24/7 across the United States. For more suicide prevention resources, visit https://suicidepreventionlifeline.org/
Blog & News
Eleven Updated Measures are Now Available on State Health Compare
October 5, 2020:Estimates for a majority of measures from several categories (Access to Care, Cost of Care, Health Behaviors, and Health Outcomes) have now been updated on SHADAC’s State Health Compare web tool, from two related surveys conducted by the Centers for Disease Control and Prevention—the Youth Risk Behavior Surveillance System (YRBSS), which surveys U.S. middle and high school students (age 13-17), and the Behavior Risk Factor Surveillance System (BRFSS), which surveys U.S. adults (age 18+).
Measures that have been updated from the YRBSS include:
High School Obesity
This measure indicates the percent of high school students (grades 9-12) in each state who were considered obese (i.e., > 95th percentile for body mass index, based on sex- and age-specific reference data from 2000 CDC growth charts).
Estimates are available for all states from 2001 through 2019.
High School Smoking
Estimates for this measure denote the percent of high school students (grades 9-12) in each state who have smoked at least one cigarette in the past 30 days; data are available from 2001 through 2019.
High School Physical Activity
This measure provides estimates of the percentage of high school students (grades 9-12) who did engage in the recommended guideline of at least 60 minutes of activity each day, in the previous five days. Data are available for all states from 2011 through 2019.
Measures that have been updated from the BRFSS include:
Adults Who Forgo Needed Medical Care*
The measure indicates the percent of adults (18+) in each state who could not get needed medical care due to cost. Breakdowns by education level and race/ethnicity are available for all states from 2005 through 2010 and 2011 through 2019.
Adults With No Personal Doctor*
This measure presents the percent of adults without a personal doctor and is now available for all states from 2005 through 2010 and 2011 through 2019. Breakdowns by education level and race/ethnicity are also available.
Chronic Disease Prevalence*
Data for this measure captures the percent of adults who reported having one or more common chronic conditions such as diabetes, cardiovascular disease, heart attack, stroke, and asthma, in each state. Estimates are now available for all states from 2005 through 2010 and 2011 through 2019.
Adult Unhealthy Days
There are a multitude of options for this measure, which shows the average number of days when an adult's physical health or mental health was not good during the past 30 days. Users can view estimates solely by reported mentally unhealthy days, physically unhealthy days, or a composite of both—though the combination of both physical and mental unhealthy days is capped at a total of 30 days. Estimates for each version of this measure are available for 2011 to 2019 and possible breakdowns include age, health insurance coverage, household income categories, disability status, education levels, and race/ethnicity.
Activities Limited due to Health Difficulty*
This measure reports the average number of days (in the last 30 days) for which an adult indicated their activity were limited stemming from either mental or physical health difficulties, and data is available for all states from 2005 through 2010 and 2011 through 2019.
Adult Obesity*
The measure is an indication of the prevalence of obesity (defined for adults as a Body Mass Index [BMI] > 30) among the U.S. population 18 years of age and over. It is now available for all states from 2005 through 2010 and 2011 through 2019.
Adult Binge Drinking*
This measure indicates the percent of adults who have consumed at least four drinks (women) or five (men) or more on one occasion during the past 30 days. Now available for all states from 2005 through 2010 and 2011 through 2019, the measure includes breakdowns by education level and race/ethnicity.
Adult Smoking*
This measure indicates the percent of adults over 18 years of age who have smoked 100 or more cigarettes in their lifetime, and who currently smoke at least some days or every day. Estimates are available for all states from 2005 through 2010, and 2011 through 2019, with breakdowns by education level and race/ethnicity.
Notes
All measures marked with an “*”: This indicates a break in series due to the BRFSS implementing cell phone sampling and an advanced weighting method in 2011.
Click here to explore these updated estimates on State Health Compare!
Blog & News
New Subsidized Marketplace Data and Other Data Tables Now Available from the 2019 American Community Survey (ACS)
September 23, 2020:The U.S. Census Bureau recently released 2019 estimates of income, poverty, and health insurance coverage from both the Current Population Survey Annual Social and Economic Supplement (CPS ASEC) and the American Community Survey (ACS).
Along with the new estimates, several new data sets and features from the surveys are also now available for this year, including new estimates of subsidized marketplace insurance coverage, which is the main subject of this post.
New Data
In 2019, for the first time, the American Community Survey (ACS) asked respondents if they or a family member received a “tax credit or subsidy based on family income” to help pay for their coverage.1 These subsidies are only available through the Affordable Care Act (ACA) marketplaces for individuals who are eligible based on their family income. By adding this question, researchers at the Census Bureau and other data users are now able to create estimates for the number and percent of the population who receive subsidized ACA marketplace coverage.
As part of a high-level analysis, SHADAC researchers found that at the national level, approximately 1.6% of the civilian noninstitutionalized population reported having subsidized marketplace coverage—representing nearly 5.3 million individuals.
Across the states, rates of subsidized marketplace coverage ranged significantly from a low of 0.7% in West Virginia and D.C. to a high of 3.4% in Florida and Utah.
The five states with the largest populations of individuals with subsidized marketplace coverage were California, Florida New York, North Carolina, and Texas. More than 40% of total marketplace enrollees lived in one of these five states, and of that subsection of enrollees, nearly 3 in 5 lived in either California or Florida.
Eleven states (Florida, Idaho, Maine, Montana, Nebraska, North Carolina, South Carolina, South Dakota, Utah, Wisconsin, and Wyoming) had rates of subsidized marketplace coverage that were significantly higher than the national rate in 2019. Of these states, only Montana and Maine had implemented Medicaid expansion for the majority of 2019, which expands the portion of the population eligible for ACA subsidies. (Montana implemented Medicaid expansion as of January 1, 2019, and Maine implemented expansion on January 10, 2019.)
Twenty states (Alaska, Arizona, Arkansas, Connecticut, Delaware, Hawaii, Iowa, Illinois, Indiana, Kentucky, Louisiana, Massachusetts, Maryland, Minnesota, Mississippi, New Mexico, New York, Ohio, Washington, and West Virginia) and D.C. had rates of subsidized marketplace coverage that were significantly lower than the national rate in 2019. Of these 20 states and D.C., only Mississippi had chosen not to expand Medicaid as of January 1, 2019.
Nineteen states had rates of subsidized marketplace coverage that were not statistically different from the national rate.
New Data Tables and Geographic Breakdowns
Along with the new question and corresponding data table on subsidized coverage discussed above, other new data tables available from the ACS this year include:
- Population: a new table on place of birth shows the year of entry among the foreign-born population for the nine largest country of birth groups. Estimates are divided between year of entry before 2010 and year of entry beginning 2010 and later.
- Households and Families: two new tables provide information regarding (1) couples who live together with biological children, stepchildren, or adopted children of the main householder who are under 18 and have not been married; and (2) married couples, cohabiting couples, and single householders (male or female) with no spouse or partner present who also live with either relatives or their own children under 18.
- Quality Measure: this new table provides the unweighted total population sample for the nation, states, counties, and places.
Extensive modifications have also been made to existing ACS data tables, a full listing of which can be found here.
In addition to data table changes, the Census Bureau has also created an updated posting regarding geographic entities of varying sizes and designations (cities, towns, townships, school districts, Native American reservations, etc.) that have either come into existence, been absorbed into other entities, or have been dissolved in 2019. A full listing of all new, modified, or removed geographic breakdowns used for the 2019 ACS estimates can be found here.
Related Materials:
- 2019 ACS: Rising National Uninsured Rate Echoed Across 19 States; Virginia Only State to See Decrease (Infographics)
- 2019 ACS: Insurance Coverage Overall Fell Nationwide and among the States, with Private and Public Coverage Declines Seen at the State Level
- 2019 ACS Tables: State and County Uninsured Rates, with Comparison Year 2018
Note: All differences described here are significant at the 90% confidence level
Reference:
1 U.S. Census Bureau. (2018, August 2.) The American Community Survey: Questionnaire. Retrieved from https://www2.census.gov/programs-surveys/acs/methodology/questionnaires/2019/quest19.pdf