SHADAC Staff

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Register Now: February 6th Webinar - Exploring Disparities Using SHADAC's State Health Compare

Exploring Disparities Using New and Updated Measures on SHADAC’s State Health Compare: State-Level Highlights for Unaffordable Rents, Unhealthy Days, and More
Date: February 6, 2019
Time: 1:00 p.m. – 2:00 p.m. Central
Register now.

Join us on Wednesday, February 6^th at 1:00 PM Central for a webinar introducing two new measures of health outcomes and social determinants of health on SHADAC’s State Health Compare—Unhealthy Days and Unaffordable Rents. This presentation, hosted by SHADAC researchers Brett Fried and Robert Hest, will examine these new measures and highlight how the estimates can be used to explore disparities between states and among sub-populations.

The webinar will also provide a virtual tour of some of the more than 40 state-level measures currently available on State Health Compare, highlighting recently updated data in particular. Mr. Fried and Mr. Hest will demonstrate how users can employ State Health Compare to easily create compelling maps, charts, and graphs, as well as download the raw estimates to perform deeper analyses and statistical testing.

SHADAC Staff

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e shadac@umn.edu

Adult Unhealthy Days: A New Measure on State Health Compare

Adult Unhealthy Days is a new measure on SHADAC’s State Health Compare that provides state-level estimates of the average number of days in the past 30 days that an adult’s mental or physical health was not good. The measure is available as a combination of physically and mentally unhealthy days and separately for physically unhealthy days and mentally unhealthy days. The measure is available for 2011 through 2017 and is produced using the Behavioral Risk Factor Surveillance System (BRFSS).

Highlighted Findings

Exhibit 1. Average Number of Days during the Past 30 Days when an Adult's Physical or Mental Health Was Not Good,
2017: Highlighted State Estimates for Combined Measure and Subcomponents*

* See notes section for why physically and mentally unhealthy days do not add up to the composite measure.

Exhibit 1 presents the top five and bottom five states for the average number of unhealthy days in 2017 by type of unhealthy days (physically or mentally unhealthy days; physically unhealthy days; and mentally unhealthy days). West Virginia has the highest average number of unhealthy days for each type of unhealthy day at 9.0, 5.7, and 5.2 days respectively. Minnesota has the lowest average number of physically or mentally unhealthy days at 5.3 days and the lowest average number of mentally unhealthy days at 3.0, while the District of Columbia has the lowest average number of physically unhealthy days at 2.6 days.

Available Breakdowns

The Adult Unhealthy Days measure and its subcomponents are available by the following breakdowns:

• Age (18–34, 35–54, 55–64, 65+, 18–64)
• Insurance Coverage Type (Insured, Uninsured)
• Disability Status (With a disability, No disability)
• Education (Less than high school, High school graduate, Some college or associate’s degree, Bachelor’s degree or higher)
• Household Income Categories (Less than $15,000; $15,000 to $24,999; $25,000 to $34,999; $35,000 to $49,999; $50,000 or more)
• Race/ethnicity (Hispanic/Latino, White, African-American/Black, Other/Multiple Races)

Importance of Examining Unhealthy Days by Age

The new age breakdown, in particular, is useful when making comparisons between states, since differences in the size of a state’s elderly or young adult populations may drive observed differences in healthy and unhealthy days: When considering all ages together, states with proportionately larger elderly populations may exhibit more unhealthy days than state with proportionally smaller elderly populations, and vice versa for young adult populations. Comparing states across age breakdowns provides a more apples-to-apples view of inter-state differences and similarities. Exhibit 2 shows the five states with the largest significant increases between 2015 and 2017 in mentally unhealthy days among those ages 18–34. Between 2015 and 2017, twenty-six states had statistically significant increases in the average number of mentally unhealthy days among those ages 18–34 (no states had significant decreases).

Exhibit 2. States with largest significant increases in average number of mentally unhealthy days among 18–34 year-olds, 2015–2017*

*All changes shown are significant at the 95% level.

Notes

Adult Unhealthy Days is a composite measure of physically unhealthy days and mentally unhealthy days. For each adult BRFSS respondent, the number of physically unhealthy days reported in the last 30 days is added to the number of mentally unhealthy days reported in the last 30 days. These numbers are then averaged across all individuals in each state. However, the composite measure is censored at 30 days. As a result, the composite measure is in some cases smaller than the actual sum of the average number of mentally unhealthy days and the average number of physically unhealthy days. For example, if an adult reported 17 mentally unhealthy days and 20 physically unhealthy days, this individual would be assigned the maximum of 30 physically or mentally unhealthy days. Please see the CDC document Measuring Healthy Days for more detail on methodology and validation and the 2017 BRFSS questionnaire for exact question wording.

The estimates presented in this post are for the civilian non-institutionalized population 18 years and over. All data in this post come from SHADAC’s analysis of the BRFSS public use files and can be found at statehealthcompare.shadac.org.

SHADAC Staff

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Now Available on State Health Compare: Updated data on measures of social determinants of health, health insurance coverage, and children’s health through 2017

SHADAC has updated seven measures on our State Health Compare site. Updated content includes:

• Health Insurance Coverage Type

This measure shows rates of uninsurance or coverage type and is now available for all states from 2008 through 2017, with breakdowns by age, citizenship, disability status, education, family income, limited English proficiency, marital status, poverty level, race/ethnicity, sex, and work status.

• Children Considered to be Poor

This measure indicates the percent of children who live in households with incomes below the Federal Poverty Guidelines (FPG) with breakdowns for race/ethnicity. This measure is now available for all states from 2008 through 2017.

• People with High Medical Care Cost Burden

This measure shows the percent of people who are in families where out-of-pocket spending on health care, including premiums, accounted for more than 10 percent of annual income. The measure can be broken down by income and race/ethnicity and is now available from 2013 through 2017.

• Medicaid Expenses as Percent of State Budget

This measure captures state and federal spending on Medicaid as a share of each state’s budget and is now available for all states from 2000 through 2017.

• Health Status

This measure indicates the percent of adults who report being in poor or fair health, and is now available for all states from 2005 through 2017.

• Child Vaccinations

This measure indicates the percent of children ages 19-35 months who received all recommended vaccines and is now available for all states from 2000 through 2017.

• Unaffordable Rents

This measure shows the percent of rental households that spend more than 30% of their households' monthly income on rent. Data for 2012-2017 is now available for all states, and can be broken down by income categories, Medicaid enrollment, and white/non-white status.

Explores these updated estimates on State Health Compare.

Data Sources

The State Health Compare estimates for coverage type, children considered to be poor, and unaffordable rents come from the U.S. Census Bureau American Community Survey (ACS); the people with high medical cost care burden measure comes from the U.S. Census Bureau Current Population Survey (CPS); the Medicaid expenses as percent of the state budget rates comes from National Association of State Budget Officers Reports (NASBO); and the child vaccinations measure comes from the Centers for Disease Control and Prevention (CDC) National Immunization Survey.

Leveraging 1332 State Innovation Waivers to Stabilize Individual Health Insurance Markets: Experiences of Alaska, Minnesota, & Oregon

Presentation by SHADAC Senior Research Fellow Emily Zylla at the 2018 Association for Public Policy Analysis & Management (APPAM) Fall Research Meeting in Washington, DC.

Download a PDF of the presentation slides.

Modeling State-based Reinsurance: One Option for Stabilization of the Individual Market

Presentation by SHADAC Director Lynn Blewett at the 2018  Association for Public Policy Analysis and Management (APPAM) Fall Research Conference in Washington, DC.

Download a PDF of the presentation slides.