Will you be covered during the next recession? Unequal safety-nets for private health insurance in the United States

Abstract

Health insurance coverage for working-age adults in the United States is still predominantly determined by their jobs or their spouse's jobs. This article revealed that SES disparities in access to a spouse's coverage as a safety-net significantly contributed to the inequities in coverage loss during economic instability. Using the longitudinal Survey of Income and Program Participation (1996–2012), this article examines insurance transitions between socioeconomic groups during the two most recent recessions in the United States. The SES disparity in private coverage spiked during periods of high job-loss. Higher SES men's and women's coverages were barely affected as they became insured by their spouses even as they lost their own. Wives' insurance plans played a large role in mitigating declines in higher SES men's coverages during the 2008 recession.

Highlights

• •Many lost their employer-based health insurance during recent recessions.
• •Higher SES adult maintained coverage by switching to their spouse's plans.
• •Disparities in access to a spouse's health plan exacerbated SES inequities.

Recent policy debates in the United States have introduced the idea of a government-funded single-payer system like the health care systems in Canada and Europe. Some frame health insurance as a citizen's right while others argue for the status quo of keeping health coverage dependent on employment. This article reminds the public that the current U.S. health care system not only links insurance to employment but also to marriage. It also reveals that the connection between insurance coverage and marriage becomes particularly salient in times of economic instability. Many working-age adults lost their jobs and its employment-based insurance during periods of high employment and job loss following the 2001 and 2008 recessions [1]. High socioeconomic status (SES) adults were less likely to become uninsured. This article shows that high SES adults were able to switch to their spouses' plans when they lost their own, whereas low SES adults and their families lost coverage altogether. The SES-disparity in insurance coverage was particularly high during the 2008 recession, and most of the inequality was driven by a difference in spousal insurance. These findings highlight how socioeconomic differences in marriage and employment interact within the current U.S. health care system to expand and exacerbate existing inequities.

1. Background

Adults between the ages of 25 and 65 predominantly gain access to private health coverage through their employers or their spouses' employers [2]. Their jobs or their spouses' jobs often determine a person's insurance plan. Disparate insurance coverage and its roots in inequalities in job quality and security is a well-studied topic [3., 4., [5], [6]]. Education is a particularly strong predictor of private health insurance coverage [7,8]. College graduates are more likely to be full-time employees in industries that offer employment-based health insurance and their rates of private coverage remained stable since the 1990s [2,[9], [10], [11]]. On the other hand, jobs available to people with less education shifted from industries with high offer-rates of employment-based coverage (i.e., manufacturing) to industries with low offer-rates (i.e., service sector) [9]. These jobs were more susceptible to economic downturns, and more low SES people lost their insurance coverage during 2001 and 2008 recessions [1,7,12,13]. The recessions amplified health coverage inequalities between education groups [11,14].

The literature is relatively sparse on how a spouse can affect insurance coverage despite the fact that over 79 million people were insured as a dependent in 2014 and more than half of married women were insured through their husbands [2,15]. Being married enabled access to their spouses' employment-based insurance plans, and many rely on their spouses' plan when they lose their own job-based coverage [[16], [17], [18], [19]]. The strong correlation between a person and their spouse's educational attainment [20] suggest that high SES people are more likely to have high SES spouses with jobs that also offer health insurance. If a one lost their job and insurance during a recession, presumably, they could have maintained coverage by switching over to their spouse's plan. This alternative safety-net may not have been as readily available for people with low SES.

Using nationally representative longitudinal data from the U.S., this article quantifies the degree to which access to a spouse's health insurance plan exacerbated the health coverage disparity between low and high SES people during the two most recent recessions.

2. Data

The study uses four panels of the Survey of Income and Program Participation (SIPP) to examine sources of insurance by gender and educational attainment among married people. The SIPP is a nationally representative series of longitudinal panels whose survey duration ranges from 2.5 to 4 years. The first SIPP panel was sampled in the early 1980s, and a new panel was re-sampled from the non-institutionalized population in the U.S. every one to four years. The analyses use the SIPP's 1996, 2001, 2004, and 2008 panels. The SIPP revisits respondent every four months and collects information on their insurance status for the preceding four months. Each four-month period is known as a wave. The 1996 panel collected its first wave in March 1996 and continued till its twelfth wave in February 2000. The 2001 panel lasted for nine waves from January 2001 to December 2003 encompassing the 2001 recession. The 2004 panel had twelve waves from January 2004 to December 2007. The final 2008 panel collected data throughout the 2008 recession. Its first wave was in August 2008, a month before the official start of the recession and it collected its last wave in March 2013. The analyses combine these longitudinal panels to examine patterns of insurance sources and transitions across 17 years. Due to the gaps between the four SIPP panels, some months are not represented in the data.

The study also utilizes specific waves from these SIPP panels to compare insurance transitions during periods of high- and low- job loss. Waves 11 and 12 from the 1996 panel (April–November 1999) coincide with a period of low job loss before the 2001 recession. The 2001 recession lasted eight months from March to November. The unemployment rate rose from 3.9% in December 2000 to 6.3% in June 2003 [21]. Job loss reached its peak during the third quarter of 2001 [21]. Waves 3 and 4 in the 2001 panel (June 2001–January 2002) coincide with a period of high job loss following the recession in 2001. Job loss was at a low during Waves 7 and 8 of SIPP's 2004 panel (October 2005–May 2006) and peaked during Waves 2 and 3 of the 2008 panel (September 2008–April 2009). The 2008 recession lasted longer and had a greater impact on the labor market. It lasted 18 months from the end of 2007 to June 2009. Job loss climbed from a low in early 2006 to its peak in early 2009 [21]. During the first quarter of 2009, about 2.7 million net jobs were lost [21]. Unemployment reached 10% in 2010 and did not return to its pre-recession levels until the end of 2015. The 2008 recession accompanied the highest rates of job loss with very low reemployment in full-time jobs compared to previous recessions [12]. The responses in each wave are weighted to represent the non-institutionalized population in the United States.

In addition to the same core questionnaire that the SIPP administered every wave, the SIPP includes topical modules containing a different theme. These topical modules contain detailed questions on selected topics, but the topics and questions differ across the duration of the panel. I utilized the Employer-Provided Health Benefits topical module to examine the sources of employer-sponsored health insurance and whether they are enrolled in those plans. This module was only administered once in each panel and is only available for years 1997, 2003, 2005, and 2010.

“Heaping” is a known problem in the SIPP; respondents are biased towards reporting changes to their insurance status at the beginning of each wave rather than at the actual month that the change occurred. While monthly insurance status is available in the SIPP, I have chosen to consider only the first reference month of each wave to evaluate respondents' insurance statuses. This method allows insurance status change to occur only once in a four-month period.

The analyses are limited to the sample of married adults aged 26 to 64 who are also married to adults in the same age range. Adults aged 65 and over are almost universally eligible for Medicare and health insurance coverage is less dependent on employment and marriage. In 2010, Young Adult Provisions' of the Affordable Care Act (ACA) allowed adults under age 26 to be insured as a dependent on their parents' plans. The study restricts the sample to couples who are not eligible to be insured by a parent or by Medicare without a medical need to limit the sources of private insurance to an individual or his or her spouse. It drops less than 2% of individuals who were married to someone absent from the household (institutionalized or living elsewhere). It also limits the sample to couples who remained married for at least two consecutive waves to calculate insurance transitions within an intact marriage. The final analysis sample comprised 131,999 individuals aged 26–64 in 79,128 marriages. If a household reference person divorced and remarried during the panel, this would be considered two separate marriages. Table 1 summarizes the descriptive statistics of this study's measures.

Table 1.

Education and insurance characteristics of married individuals and couples aged 26 to 64 in the 1996, 2001, 2004, and 2008 panels of the SIPP.

	1996–1999 panel	2001–2003 panel	2004–2007 panel	2008–2012 panel	Total
Number of married individuals	32,796	25,792	37,048	36,363	131,999
Educational attainment (percent of individuals)a
Less than High School	31.3	29.2	23.8	24.4	27.0
High school degree or GED	11.7	10.7	10.2	8.4	10.2
Some college	29.6	29.4	34.6	33.5	31.9
College degree	18.1	20.1	20.3	21.6	20.1
Postgraduate degree	9.2	10.7	11.1	12.1	10.8
Health insurance coverage (percent of individuals)a
Privately insured under own name	44.9	45.3	49.1	46.0	46.4
Privately insured as a dependent	40.4	40.1	34.4	32.8	36.7
Medicaid/Medicaid	4.4	4.4	5.8	6.4	5.3
Uninsured	10.3	10.3	10.7	14.8	11.6
Access to own private coverage (percent of individuals)b
Men	70.7	69.3	71.0	67.0	69.5
Women	40.9	41.5	46.3	45.4	43.6
Number of married couples3	20,313	14,990	21,891	21,934	79,128
Educational attainment (percent of couples)a
Both spouses have college degrees	18.2	20.8	21.7	23.0	21.1
Only the wife has a college degree	8.3	9.8	10.1	11.6	10.0
Only the husband has a college degree	11.4	11.6	11.0	10.5	11.1
Neither spouse has a college degree	62.1	57.8	57.2	54.9	57.8
Private health insurance coverage(percent of couples)b
Neither spouse has access to private coverage	14.4	14.9	12.9	16.0	14.5
Only one spouse has access to private coverage	59.6	59.5	56.9	55.6	57.9
Both spouses have access to private coverage independently	26.1	25.7	30.2	28.4	27.6

^aMeasured when first observed in each panel as a married individual aged over 25.

^bIncludes eligibility for employer-sponsored health plans whether or not the person is enrolled in them. Data is only available once during each panel in 1997, 2002, 2005, and 2010. Persons who were married at those specific times are included in the calculations. ³Includes pairs who were both aged 26–64 and were present in the SIPP household. Remarriages are counted as unique pairs. Percentages are weighted. Data Source: Survey of Income and Program Participation 1996, 2001, 2004, and 2008.

While some employers offer family health coverage to domestic partners, most limit eligibility to legally married spouses. Some states were beginning to recognize same-sex marriages between 1996 and 2012. However, same-sex couples did not appear in the SIPP panels as married spouses. Thus, the analyses here are limited to legally married, heterosexual couples.

2.1. Variables

2.1.1. Educational attainment

The study divides the population into two groups: persons with a four-year college degree (B.A. or equivalent) or higher and persons without a college degree. Educational attainment roughly captures a person's human capital and potential earning. Unlike income, another common measure of socioeconomic status, educational attainment is less sensitive to idiosyncratic employment decisions and macroeconomic shocks. Also, it generally remains stable after marriage. Using educational attainment as a measure of SES is particularly suited here as it remains constant throughout the major recessions, unlike jobs, income, and earnings. Using an alternative threshold for low- and high-SES groups (high school grad and below versus some college level education and above) did not yield meaningfully different results.

2.1.2. Health insurance status

I categorize individuals into three discrete insurance categories: privately insured by their own plan, privately insured as a dependent, and not privately insured. Private insurance includes both employer-sponsored plans and individually purchased plans. The analyses divide private insurance coverage into two categories—insured by their own plan and insured as a dependent—to observe how husbands and wives insure each other. The third category includes people with public coverage (Medicaid and Medicare) and the uninsured. The core multivariate analysis combines public coverage and uninsured to maintain an adequate number of observations in each group-insurance-period category. A descriptive analysis that separates public insurance from uninsurance shows that public insurance coverage among married men and women remained low throughout both recessions.

The SIPP's monthly core surveys do not ask dependents whether the primary subscribers of their insurance plans are their spouses. The SIPP however, asks who the primary subscriber is in their Employer-Provided Health Benefits topical module administered in 1997, 2002, 2005, and 2010. At each of these times, the vast majority (around 95%) of married dependents aged 26 to 64 were insured by their current spouses' plans. Therefore, I consider most dependents to be insured by their spouses throughout the entire study period. The Employer-Provided Health Benefits topical module also asks respondents not only their actual coverage but also whether they are eligible to enroll in their own employer-provided plans. For example, a person may be insured as a dependent on their spouse's plan while having the option to switch to another plan through their own employer. This once-per-panel topical module captures multiple sources of insurance coverage that some couples can draw upon to insure themselves and each other.

2.1.3. Socio-demographic controls

When comparing transitions between groups and across time periods, multivariate analyses control for characteristics that prior research has found to be related to insurance status: employment, race, Hispanic origin, age, and logged family income. Individuals who work full-time are more likely to have private coverage through their employers [2]. Racial and ethnic minorities are less likely to have insurance coverage, and private coverage increases with age and family income [2]. Employment and income are measured before insurance transitions.

3. Analytic strategy

The core analysis compared the insurance characteristics between a college graduate and non-graduate married individuals during periods of high unemployment associated with the 2001 and 2008 recessions accounting for baseline differences and possible confounding characteristics. I conducted separate analyses for men and women.

I examined each group's insurance gains and losses directly to better capture the sudden changes in insurance coverage conditions before and during the two recessions. Cross-sectional distributions react slowly to changes in transition conditions and can mask year-to-year shifts in how likely people are to lose and gain insurance. During the study period, people moved in and out of insurance groups becoming uninsured or switching coverage to their spouses' plans. Some years, people may be more likely to lose coverage, and in other years, people may be more likely to gain coverage.

I used multinomial logistic regressions to estimate probabilities of switching from one insurance category to another while controlling for covariates: age, race, Hispanic origin, employment, and logged family income. Separate regressions estimated transition probabilities for each gender, education, and staring insurance category. I then converted these estimated probabilities into annualized rates and used these rates to derive a distribution that would emerge if the rates remained constant for a long time (also known as a stationary distribution). I compared the changes in the stationary distribution before and during recessions between low and high SES men and women.

4. Results

4.1. Descriptive results

Table 1 summarizes the education and insurance characteristics of married couples aged 26 to 64 from four SIPP panels. The percentages are weighted to reflect the U.S. population.

The level of education among married people aged 26 to 64 increased between 1996 and 2008. These trends reflect the rise in educational attainment, particularly among women, as well as the increasingly positive association between education and marriage throughout this period. More than half of all married women were insured as a dependent, and about a third of married women were primary subscribers. Overall, about 46% of married individuals were the primary subscribers of their private health plans. Private coverage was lower among the more recent cohorts, and the proportion without private coverage peaked in the 2008 panel likely due to the recession. At the couple-level, more than half of couples had access to only one health insurance plan between the two of them (bottom panel of Table 1). More than a quarter of couples have two separate sources of private health coverage, whether they utilized both or not. The proportion of couples with either two or no sources of private coverage grew between 1997 and 2010.

Fig. 1, Fig. 2 show the growing disparity in private insurance coverage between married persons with and without a college degree between 1996 and 2012. These differences are calculated from group- and year- specific insurance transition rates controlling for sociodemographic characteristics. The total disparity in private coverage is decomposed into disparity due to the difference in coverage as the primary subscriber and difference in coverage as a dependent. Due to the gap between the 1996 and 2001 SIPP panels, data for 2000 in these figures are averages of 1999 and 2001 values.

Fig. 1.

Disparity in private insurance coverage between college graduate women and non-college graduate women due to differences in own coverage and coverage as a dependent (ages 26–64).

Notes: The two grey highlights represent the 2001 and 2008 recessions, respectively. Primary policy holders for dependent women are predominantly their husbands. Differences are calculated from stationary distributions of insurance states derived from annual insurance transitions between three states: privately insured under own plan, privately insured as a dependent, and no private insurance. Sample is restricted to married women aged 26 to 64. Data for 2000 is missing and is estimated as an average of 1999 and 2001. Data Source: Survey of Income and Program Participation 1996, 2001, 2004, and 2008, Bureau of Labor Statistics.

Fig. 2.

Disparity in private insurance coverage between college graduate men and non-college graduate men due to differences in own coverage and coverage as a dependent (ages 26–64).

Notes: The two grey highlights represent the 2001 and 2008 recessions respectively. Primary policy holders for dependent men are predominantly their wives. Differences are calculated from stationary distributions of insurance states derived from annual insurance transitions between four states: privately insured under own plan, privately insured as a dependent, and no private insurance. Sample is restricted to married men aged 26 to 64. Data for 2000 is missing and is estimated as an average of 1999 and 2001. Data Source: Survey of Income and Program Participation 1996, 2001, 2004, and 2008, Bureau of Labor Statistics.

In 1996, college-graduate women were more likely to have private insurance than their non-college counterparts by 14 percentage points. That difference grew to 25 percentage points in 2012 (Fig. 1). This rise in disparity was due to the growing gap in both own coverage and coverage through a spouse. The difference in having their own private coverage between college graduates and non-graduates was seven percentage points in 1996, and the difference increased to 15 percentage points in 2012. The difference in probability of being insured as a dependent was seven percentage points in 1996 and rose to 10 percentage points in 2012.

Disparities in private insurance coverage spiked during years when national job loss exceeded job gain. Job loss peaked during the third and fourth quarter of 2001 and the first quarter of 2009. These periods of high job loss coincided with the 2001 and 2008 recessions. During periods of low job loss before the two recessions (the first quarters of 1999 and 2006 respectively), 25% to 50% of the insurance coverage gap among married women is driven by college-graduate women's greater propensity to have her own insurance plan. When job loss rose, however, the difference in spousal insurance expanded the coverage gap between college-graduate and non-graduate women.

Spousal coverage was also a significant source of coverage inequality among married men (Fig. 2). Disparities in private insurance coverage between college-graduate and non-graduate men had been mostly driven by their differences in having their own plans. In fact, when job loss was low, and job gain was relatively high in 1999 and 2007, college-graduate men were less likely than their non-graduate counterparts to be insured as a dependent. During periods of high job loss, however, insurance coverage through a spouse's plan became a prominent driver of inequality. Coverage gap hovered around 14 percentage points during pre-recession periods. In 2009, a period of peak job loss in the United States, the coverage gap reached 25 percentage points, and 15% of that difference was due to spousal coverage.

The proportion of married non-college women with own insurance plans dropped by 12.1 percentage points from 54% to 41.9% during the 2001 recession. About half of those who lost their own insurance plan switched to their spouses' plans (Table 2) leaving the other half without any private coverage. During the 2008 recession, overall private coverage among women without a college degree fell 11.4 percentage points from 92.5% to 81.1%. Own insurance coverage fell by 24.7 percentage points, while spousal coverage increased by 13.4 percentage points. The recessions had a smaller impact on college-graduate women's insurance coverage (Table 2). The proportion of people with private insurance fell from 98.5% to 96.6% during the 2001 recession. While their own insurance coverage fell by 9.1 percentage points, spousal coverage increased by 7.2 percentage points offsetting almost 80% of the loss of their own plan. During the 2008 recession, college graduate women's own insurance coverage fell by 16.1 percentage points. Their coverage via a spouse increased by 13.1 percentage points, limiting the net drop in private coverage to 3.0 percentage points.

Table 2.

Changes in insurance coverage and disparity during periods of high job loss compared to periods of low job loss surrounding the 2001 and 2008 Recessions adjusted for socioeconomic and demographic characteristics.

		Total private insurance	Privately insured as primary subscriber	Privately insured as dependent	Percentage change explained by dependent coverage
		(1) = (2) + (3)	(2)	(3)	(3)/(1)
2001 Recessiona
Women	College	−1.9	−9.1	7.2
	Non-college	−5.4	−12.1	6.7
	Disparity	3.5	3.0	0.5	14.4
Men	College	0.0	−5.0	4.9
	Non-college	−3.6	−8.0	4.5
	Disparity	3.5	3.1	0.4	12.7
2008 Recessionb
Women	College	−3.0	−16.1	13.1
	Non-college	−11.4	−24.7	13.4
	Disparity	8.4	8.6	−0.3	−3.2
Men	College	−1.1	−14.7	13.6
	Non-college	−12.8	−21.1	8.3
	Disparity	11.7	6.4	5.4	45.7

Values are derived from transition rates that are adjusted for age, race, Hispanic origin, employment, and family income prior to the transition. Analysis is limited to married men and women between 26 and 64.

^aInsurance statuses during the high job loss period were calculated from 2001 Panel Waves 3 and 4 (June 2001–January 2002) and statuses during the low job loss period were calculated from 1996 Panel Waves 11 and 12 (April 1999–November 1999).

^bInsurance statuses during the high job loss period were calculated from 2008 Panel Waves 2 and 3 (September 2008–April 2009) and statuses during the low job loss period were calculated from 2004 Panel Waves 7 and 8 (October 2005–May 2006).

Spousal coverage also increased among married men during periods of high job loss even as their own private coverages fell. This pattern is observed for both college graduate and non-graduate men. Between 1999 and 2001, private coverage among non-college married men fell from 89.7 to 86.1%. Eight percent lost their own health coverage, but 4.5% gained insurance through their spouses resulting in a net decline in private coverage of 3.6 percentage points. College graduate men maintained their private coverage rate at 96.6 percent during the same period. Five percent lost their own insurance coverage, and 5% gained insurance through their spouses.

5. Discussion

The results collectively show the extent to which spousal insurance matters in expanding coverage inequality between education groups during periods of economic instability. Individuals with more education were less likely to lose their own coverage and were also more likely to be covered by a spouse during past economic crises. Additional analyses revealed that public health insurance (Medicaid) did not provide adequate safety nets for those losing private coverage during this period. Consequently, uninsurance rates were disproportionately greater among groups with less education. With the insurance coverage gap expanding along existing socioeconomic boundaries, the burden of poor health became disproportionately greater among already disadvantaged families.

This article examines insurance coverage between spouses during specific periods of unusually widespread economic instability. However, its findings can be cautiously generalizable to other periods and populations. First, spousal insurance acts as a safeguard against gaps in coverage in situations other than job loss during recessions. Individuals may rely on their spouses for insurance as they transition between schools and jobs or when engaging in self-employment. Spousal insurance allows people to pursue riskier opportunities with greater potential payout. Its role in coverage inequality, however, is reduced during periods of economic stability. In fact, the analyses find that more individuals without a college degree (especially men) relied on their spouses' plans during periods of low job loss and unemployment. When the economy is good, being able to share insurance plans between spouses helps lower SES families. Still, strong correlations between wages, job stability, and health benefits [2,22] make lower SES families more vulnerable to changes in economic cycles. And while components of the ACA provide some protection through Medicaid eligibility expansions and insurance exchanges, employers are still expected to remain the largest source of health insurance for non-elderly Americans [23].

Second, being able to share an insurance plan among immediate family members can prevent gaps in coverage for adult children and cohabiting partners as well as spouses. The Young Adults' Provision of the ACA allowed adults to be insured by their parents' private plans until age 26. Adult children of higher SES parents are more likely to have uninterrupted private coverage than their lower SES counterparts; they can switch to their parents' plans should they lose their own. The advantages of family-based insurance plans may also apply to cohabiting couples. While fewer employers extend benefits to domestic partners than to married spouses [24], a greater proportion of cohabiting households have two earners [25]. Family insurance plans may also be a sizable contributor to coverage inequality among those who are in cohabiting relationships. Unfortunately, as SIPP does not recognize cohabiting relationships, the analyses here are limited to married couples.

The results underestimate the full extent of spousal insurance's effect on coverage inequality. A person's access to private insurance plans can affect insurance coverage for their children as well. Children with parents with a college degree are more likely to have uninterrupted private coverage than their lower SES counterparts for the same reasons; when one parent lose access to coverage, everyone in the family will be more likely to be able to switch to the other parent's plan. While children have greater access to public insurance options such as Medicaid or SCHIP, one in twenty children under 18 are without insurance coverage [26], and transitions between private and public coverage can be cumbersome to navigate [27].

The greater precariousness of marriages among couples with less education [28,29] means that spousal insurance is even less reliable among lower SES individuals. The analyses exclusively examine insurance transitions of couples in intact marriages and exclude coverages of people who lost their spouse along with its privileges. Along similar lines, spousal coverage exacerbates coverage differences between married and single individuals. Single adults over 25 generally do not have another source of private coverage other than their own labor force participation. Positive selection into marriage means that the single population is more likely to have fewer resources and poorer health [[30], [31], [32]]. Without access to a secondary source of coverage, single people, especially those with less education, are already at high risk for experiencing the negative consequences of living without health insurance. The coverage gap between married people with a college degree and single people with less education is likely to be even greater during economic crises.

As the U.S. edged closer to the precipice of another recession due to the COVID-19 pandemic, extricating marriage from health insurance coverage gained new urgency [33]. In April 2020, more than 5 million people claimed unemployment claimed each week [34]. Loss of employer-sponsored insurance coverage following job loss is likely to be uneven across socioeconomic groups. Providing a viable way to continue insurance coverage for all newly unemployed workers is critical in curbing the long-standing injustices [35]. Throughout the pandemic, people with fewer resources were far more likely to be infected and were more likely to die from the novel coronavirus [36,37].

Since 2014, 40 U.S. states expanded Medicaid eligibility to cover more low-income adults regardless of pregnancy or marital status. Marketplace premium tax credits gave another means for health insurance coverage for people with moderate income—100 to 400% Federal Poverty Level (FPL)—who were not covered through an employer-sponsored plan. Expanding the coverage safety-net led to reductions in the SES disparity [38,39] in participating states, and may have lessened the impact of the COVID-19 pandemic. Conversely, states that did not expand Medicaid likely experienced surges in coverage inequity; many low-income people in these non-expansion states were left ineligible for Medicaid and Marketplace subsidies [40].

The current patchwork of programs that differs state by state and by eligibility criteria is inadequate in providing a reliable safety-net that mitigates the widening of the class gap that accompanied each recent economic crisis. Reducing inequity at the national level requires national action that prevents vulnerable people from falling through eligibility gaps.

Appendix A. Supplementary data

Supplementary material