Stewart, Andrea
Research Fellow

p 612-624-4850
e astewart@umn.edu

Five-Year Review Shows Rising Trends in Adult E-Cigarette Use: 2017 to 2021

Though COVID-19 remains a focal point of concern as the official public health emergency (PHE) is extended, public health researchers and workers have slowly begun to resume attentions to other ongoing and emergent public health crises such as the long-running opioid epidemic, increases in alcohol-related behaviors such as binge drinking and heavy drinking, and e-cigarette use and smoking rates, especially among young adults.

The recent ban and removal of all JUUL e-cigarette products by the U.S. Food and Drug Administration (FDA) is one of the biggest moves to address this issue at the federal level. Additionally, as of June 2022, all 50 states, the District of Columbia, and nearly all U.S. territories have enacted legislation banning sales of e-cigarettes to underage individuals (under age 21). These actions at the federal and state level are aimed at curbing an alarming and persistent rise in e-cigarette usage, especially flavored e-cigarettes, among high-school and middle-school-aged children, as shown in a recent study conducted by the FDA and the Centers for Disease Control and Prevention (CDC). However, the issue of rising e-cigarette use is not limited to only teens and young adults.

Significant Increases Across the States

Nationally, the rate of adult e-cigarette use in 2021 was 6.6 percent. Across the states, e-cigarette use among adults in 2021 ranged from a high of 9.4 percent in Oklahoma to a low of 4.5 percent in Maryland.

Rates of E-Cigarette Use Among Adults, Top Five and Bottom Five States, 2021

While these rates may initially seem low, a comparison to a previous SHADAC analysis on e-cigarette use shows that in just five years the overall rate of adults reporting using e-cigarettes has increased significantly by over two percentage points (PP) from 4.4 percent in 2017.

The range of e-cigarette usage reported by adults across the states has experienced similar trends. From 2017 to 2021*, Oklahoma remained the state with the highest rate of adult e-cigarette use, rising significantly to 9.4 percent in 2021 from 7.1 percent in 2017. The state with the lowest rate of adult e-cigarette use shifted from the District of Columbia (D.C.) in 2017, with a rate of just 2.5 percent, to Maryland in 2021, with a rate of 4.5 percent. Again, the difference between the two lowest rates was statistically significant, indicating an overall increase in e-cigarette use by adults during this time period.

Overall, the states ranking in the top and bottom five for e-cigarette use among adults remained largely unchanged from 2017 to 2021. Kentucky, Oklahoma, and Tennessee remained among the states with the highest rates of reported adult e-cigarette use, with Alabama and Louisiana in 2021 replacing Indiana and Wyoming. Connecticut, Maryland, Vermont, and D.C. remained among the states with the lowest rates of reported e-cigarette use from 2017 to 2021, with New Hampshire in 2021 replacing California.

E-Cigarette Use by Age Group

Most efforts toward curbing rising e-cigarette use have been aimed at teen and young adult age groups, and as the figure below shows, it is easy to see why.

While rates of e-cigarette usage rose across all age groups over the past five years, the highest increases were seen among younger adults age 18-24 and 25-34.

Adult E-Cigarette Use by Age Group from 2017 to 2021

The rate of e-cigarette use among adults age 18-24 nearly doubled, rising by over 8 percentage points from 10.1 percent in 2017 to 18.5 percent in 2021, a statistically significant difference. Similarly, the rates for adults age 25-34 increased significantly from 6.6 percent in 2017 to 11.1 percent in 2021. In fact, all age groups except adults age 45-64 saw significant increases in the rate of e-cigarette use from 2017 to 2021.

Conclusion

In 2019, the CDC began tracking the number of lung injuries and related deaths associated with vaping and e-cigarette use. By early 2020, they revealed that all 50 states, D.C., and several territories were submitting pertinent data to CDC and that the number of lung injuries across the nation had been recorded at 2,807 with deaths recorded at 68. According to recent research from Johns Hopkins University, many of these deaths have not come from regulated market products, but from black market modifications to devices or to vaping liquids—mirroring concerns about current trends in the opioid crisis, which has shifted from prescription (i.e., regulated market) opioid painkillers to unregulated fentanyl that traffickers mix into drugs, leaving consumers unaware of the exact makeup or potency of the product they are purchasing.

While the true effectiveness of state legislations and the FDA ban on e-cigarette products will be revealed with time, they are solid steps towards curbing rising rates of e-cigarette use across a number of age groups in the U.S.

Source: SHADAC Analysis of 2017-2021 Behavioral Risk Factor Surveillance System (BRFSS) public use files. 

Notes: * 2019 data is not available. Statistically significant changes at the 95% confidence level unless otherwise noted.

Hest, Robert
Senior Research Fellow

p 612-624-5507
e hestx005@umn.edu

BRFSS Estimates Show Potential Break in Series for Usual Source of Care: New Data on State Health Compare

A change to the 2021 BRFSS’ “personal doctor” question has led to large changes in the share of respondents reporting having no personal doctor

The Center for Disease Control’s (CDC) Behavioral Risk Factor Surveillance System (BRFSS) is a long-running, telephone-based state survey designed to monitor trends in adults’ health-related risk behaviors, chronic health conditions, and use of preventive services. SHADAC uses the BRFSS to produce state-level estimates of a number of different measures of health care access and affordability, health behaviors, and outcomes. These measures are posted on State Health Compare and are available by subgroup and over time.

Among these measures is Adults with No Personal Doctor, which quantifies the share of adults who report having no personal doctor. SHADAC tracks this measure because adults with a personal doctor are thought to have better access to care than those with no personal doctor.

The 2021 estimates of those reporting no personal doctor shifted dramatically and across nearly every measured subgroup and state. Notably, these large shifts in estimates corresponded with a change in how the BRFSS asks respondents if they have a personal doctor.

This blog post describes changes to the “personal doctor” question and presents evidence of the impact this change had on estimates across the states and relevant subpopulations.

Changes to the “personal doctor” question structure

The table below compares the text of the “personal doctor” question asked in the BRFSS between 2000 and 2020 and the text of the question asked in the 2021 BRFSS. The main difference is that in 2021, the question broadens the concept of “personal doctor” by suggesting respondents consider groups of doctors when identifying whether they have a personal doctor. Specifically, the 2021 question specifically prompts the respondent if there is “one person or a group of doctors” (emphasis added) providing care whereas the question asked through 2020 only asks if there is more than one person who they think of as a personal doctor if the respondent has already indicated they don’t have one person they think of as their personal doctor.

Fewer people say they have “no personal doctor” using the 2021 question than in previous years

The primary result of this questionnaire change is that fewer people report having “no personal doctor” or other health care provider under the 2021 question compared with the question asked through 2020. This effect is nearly universal among many groups and across nearly every state. This type of change is uncommon and typically results from an update to the survey or its methods rather than from a true change in the population.

As shown below, the 2021 rate of 16.7% was far outside the range of estimates observed since 2011,¹ which have been as high as 23.8% in 2013 and as low as 21.5% in 2015.

Percent reporting "no personal doctor" in the 2021 BRFSS was the lowest it has been in 10 years

The figures below present estimates of the share of the adult population who report having no personal doctor, comparing estimates from the 2020 and 2021 BRFSS. As shown in the figure on the left, the total percent of adults reporting no personal doctor was 6.4 percentage points (PP) lower in the 2021 survey (16.7%) compared to the 2020 survey (23.1%). Similar differences were observed across all measured groups (except for uninsured adults), with PP differences ranging from 2.5 PP among adults age 65 or older to 10.0 PP among adults age 25 to 34. As shown in the figure on the right, this was also true across the states, with a smaller share of adults reporting “no personal doctor” in the 2021 BRFSS compared to the 2020 survey in all but Delaware and Oregon. The difference ranged from 2.9 PP in Massachusetts to 13.4 PP in North Dakota.

Percent reporting "no personal doctor" dropped among most groups and nearly all states in the 2021 BRFSS

Further, these results hold when controlling for multiple factors in a multivariate analysis. In a variety of models, all controlling for the factors shown in the previous figures, respondents to the 2021 BRFSS were significantly less likely to report having no personal doctor than respondents to the 2020 BRFSS, with effects ranging from 4.1 PP (Model B) to 4.9 PP (Model C).

Multivariate analysis of rates of “no personal doctor” in 2021 BRFSS vs. 2020 BRFSS

Visit State Health Compare to explore this measure further!

Exploring 2021 State Public Health Funding Estimates Using State Health Compare

October 2022:

This updated SHADAC brief on state-provided public health funding estimates highlights newly-available 2021 data as well as trends over the past decade (2012–2021). These estimates come from SHADAC’s State Health Compare measure, “Public Health Funding”, which provides annual estimates of per-capita state public health funding starting in 2005 (with the exception of data year 2006, for which no estimates are available).

State governments are the predominant source of public health funding in the United States, raising public health funds from their own revenues (e.g., state-generated revenue from taxes, fees, fines) and also serving as an important link between the federal and local levels of the U.S. public health system by directing funds from federal agencies to county and city health departments. Tracking data on state public health funding can help identify which states are well-positioned to absorb potential decreases in federal funding (assuming no recourse to additional state-level funding) and improve efforts to distribute scarce public health resources most effectively nationwide. Persistent gaps in public health funding among the states raise questions about why some states consistently spend far more public health dollars per person compared to other states and signal a need to bolster public health funding in different parts of the country.

Linked below are previous versions of this brief:

Assessing State Public health funding (data years 2011–2020) - Published June 2021

Exploring Public Health Indicators with State Health Compare: Public Health Funding (data years 2015-2019) - Published May 2020

 

Hest, Robert
Senior Research Fellow

p 612-624-5507
e hestx005@umn.edu

Assessing Physician Acceptance of Medicaid Patients Using State Health Compare

In order for the more than 80 million Medicaid beneficiaries to access needed care in a timely manner, there must be a sufficient number of health care providers to serve these patients. There has long been concern that providers are less likely to accept Medicaid patients than patients with other types of health insurance coverage, making it difficult for individuals with Medicaid coverage to get health care when they need it. In the U.S., nearly all physicians accept new patients with private insurance, but only about three quarters accept new patients with Medicaid coverage. Though this trend is clear nationally, there is a large degree of variation across the states in how likely physicians are to accept new patients with Medicaid coverage compared to other forms of insurance.

SHADAC’s State Health Compare has two state-level measures related to physician acceptance of new Medicaid patients, allowing users to compare rates of physician acceptance of new patients by coverage type (Medicaid, Private, and Medicare) and to compare rates of physician acceptance of new Medicaid patients by characteristics of the physician’s practice, along with more than 40 other state-level measures of health insurance coverage; health behaviors; access, affordability, and use of care; public health; and related social and economic factors.

Nationally, in 2014–2017, while more than 95 percent of physicians said they accepted new patients with private insurance, only 74 percent accepted new patients with Medicaid coverage (among physicians accepting new patients), a greater than 20 percentage-point gap.

This gap was much larger in some states than others. For example, in New Jersey, Florida, Louisiana, and California, physicians were more than 30 percentage-points less likely to accept new patients with Medicaid coverage than those with private insurance. And in New Jersey, less than half of physicians said they accepted new patients with Medicaid (42.2%). However, in twelve states, physicians were no more than five percentage points less likely to accept Medicaid patients than private patients, and in Wisconsin, Minnesota, and North Dakota, there was essentially no difference between physicians’ acceptance of Medicaid versus private insurance.

Though the Affordable Care Act (ACA) led to important policy changes that could have prompted shifts in the share of physicians who accept Medicaid patients, rates of acceptance of Medicaid patients have been stable over time nationally and in most states, both before most ACA coverage policies were implemented (2011–2013) and after these policies were in force (2014–2017).

Nationally, the percentage of physicians accepting new Medicaid patients was statistically unchanged between 2011–2013 and 2014–2017, remaining between 73 and 74 percent. Six states—Idaho, Massachusetts, Missouri, Ohio, Vermont, and West Virginia—saw significant increases in the percent of physicians accepting Medicaid patients. Of these states, Missouri saw the largest increase, with 78 percent of physicians accepting Medicaid-covered patients in 2014–2017 compared to less than 69 percent in 2011–2013, a greater than nine percentage-point increase.

Six states saw increases in the share of physicians accepting new Medicaid patients
 

Visit SHADAC’s State Health Compare to dive deeper into state-level trends for these two measures: 

• Physician acceptance of new patients by coverage type
• Factors associated with physician acceptance of Medicaid patients 

Related Resource
SHADAC brief summarizing Dr. Hannah Neprash’s study examining the effects of Medicaid expansion on physician participation

Notes
Estimates in this post are representative of non-federally employed office-based physicians who are primarily engaged in direct patient care and reported accepting new patients. Data years 2011–2013 and 2014–2017 were merged to improve sample sizes and facilitate the production of state-level estimates. Estimates represent a weighted average of the years in these periods.

Differences between physician acceptance of Medicaid versus private insurance were not evaluated for statistical significance. All described differences in physician acceptance of Medicaid coverage over time were statistically significant at the 95% confidence level.

All data in this post come from SHADAC analysis of the 2011–2017 National Electronic Health Records Survey (NEHRS) data, produced by the National Center for Health Statistics (NCHS). The analysis was performed by SHADAC under contract with the Medicaid and CHIP Payment and Access Commission (MACPAC). The findings, statements, and views expressed here are those of SHADAC and do not necessarily reflect those of MACPAC. Data were analyzed at the University of Minnesota's Census Research Data Center. Data for 2016 are not available.

Stewart, Andrea
Research Fellow

p 612-624-4850
e astewart@umn.edu

2022 NHIS Early Release: Estimates from Quarter 1 (January-March) show potential post-pandemic rebounds in health insurance coverage

The National Center for Health Statistics (NCHS) has released quarterly estimates of health insurance coverage beginning in January 2021 through March 2022 from the National Health Interview Survey (NHIS) as part of the NHIS Early Release Program.

After disruptions to data collection operations due to COVID-19 in 2020 and 2021, NHIS quarterly estimates for 2022 were able to collect and produced as usual.¹ Estimates for each included category of insurance coverage (uninsured, public, and private) have been disaggregated by age group and family incomes as a percentage of the federal poverty level (FPL), reported race and ethnicity categories, and by geographic region.²

Uninsured rate saw significant decreases while public and private coverage remain stable

As the United States emerges from the height of the COVID-19 pandemic, estimates from the NHIS indicate positive trends for health insurance rates across coverage types thus far in 2022.

The uninsured rate dropped significantly across all age groups, decreasing by an incredible 1.5 percentage points (PP) from 9.5% during Q1 2021 to a historic low of just 8.0% during Q1 2022.

While public and private insurance coverage rates showed no statistically significant changes between the Quarter 1 time periods (measuring at 40.0% in 2021 and 39.1% in 2022 and 59.7% in 2021 and 61.8% in 2022, respectively), the potential shifts in coverage that are hinted at by the NHIS data offer hope toward a continuing post-pandemic recovery. A possible rise in private insurance coverage would indicate the potential for a resurgence in employer-sponsored insurance (ESI) due to a prospective rise in employment (unemployment rates fell sharply to 5.3% in 2021 from 8.1% in 2020).³ Consequently, this potential rise in private insurance coverage appears to be possibly offset by a reduction in public insurance coverage, indicating a consequent reduction in the portion of the national population needing to rely on safety net public insurance programs such as Medicaid. Again, our analysis of the NHIS insurance estimates did not find the year-to-year changes in public and private coverage to be statistically significant; therefore, these data will require further monitoring to see if these possible trends bear out.

Falling uninsured rates across demographic groups

Examining the NHIS  coverage estimates for Q1 (January-March) 2022 revealed further good news in that a number of demographic subgroups saw a significant reduction in uninsured rates: by age, by race and ethnicity, and by geographic region.

Findings by age group

Our analysis showed not only a significant drop in uninsurance across all age groups from 2021 to 2022 (9.5% to 8.0%, respectively), but this decrease was underscored by rates for individuals under 65 (11.3% to 9.6%) and for nonelderly adults age 18-64 (13.8% to 11.8%). Rates for children (age 0-17) remained stable between the two years’ first quarters.

Findings by race and ethnicity

Uninsured rates also decreased significantly for Hispanic nonelderly adults (age 18-64)—dropping from 31.1% in Q1 2021 to 25.7% in Q1 2022—and for Non-Hispanic, White nonelderly adults (age 18-64) —dropping from 8.7% in Q1 2021 to 6.9% in Q1 2022.

Findings by geographic region

While uninsured rates in most regions remained stable between January-March of 2021 and 2022, NHIS data showed a significant drop in uninsurance for nonelderly adults (age 18-64) in the South, a region that traditionally has seen higher rates of uninsurance, falling to 15.7% in 2022 from 20.1% in 2021.⁴

Overall, data from Q1 of 2022 indicated positive trends in health insurance coverage, with uninsured rates falling significantly for a number of population subgroups and a potential (though not significant) recovery for private insurance and a lessening of public insurance coverage.

About the Numbers
The above estimates provide a point-in-time measure of health insurance coverage, indicating the percent of individuals with (or without) a specific type of coverage at the time of the interview. The estimates discussed in this blog are only from Q1 (January-March) 2022 and the same period in 2021.

Differences in estimates are statistically significant at the 95% confidence level unless otherwise specified.