The disparate impact of the ACA-dependent expansion across population subgroups.

Young adults are less likely to have insurance than other age groups; 29.7 percent of people aged 19–25 were uninsured in 2010 as compared with 16.3 percent of all people (DeNavas-Walt, Proctor, and Smith 2011). Also, young adults are at the least risk of needing medical services; compared with the population 25 years and older, young adults are healthier and do not consume as many medical services (O'Hara and Caswell 2012). Therefore, at least in some health reform scenarios, expanding employer-provided coverage to dependent young adults is not very costly (Cantor et al. 2012). Thirty-seven states encouraged the expansion of private health insurance for younger adults before the national health insurance reform of 2010 for young adults. For instance, states regulated the private coverage market to increase dependents by using age caps, student status, or financial dependency (National Conference of State Legislatures 2010). Most of the studies that examined the state expansions found no statistical evidence that uninsurance decreased (Long, Yemane, and Stockley 2010; Levine, McKnight, and Heep 2011; Monheit et al. 2011; Blum et al. 2012). Section 2714 of the Patient Protection and Affordable Care Act of 2010 (ACA) targets this issue of insurance coverage among young adults aged 19–25 (P.L. 111-148 2010). The provision, which took effect on September 23, 2010, allows holders of private family plans to add children under the age of 26 to the policy, regardless of the child's circumstance. For example, a young adult can be in school, married, employed, or have his or her own children and also be on a parent's family plan (Kaiser Family Foundation 2010). Consistent with the law, private insurance coverage increased for young adults in 2011. Different survey data sources show wide variation in estimates of the magnitude of the policy's effect. The Annual Social and Economic Supplement to the Current Population Survey (CPS ASEC) estimated that between 2009 and 2010, there were 400,000 newly insured young adults (DeNavas-Walt, Proctor, and Smith 2011). The American Community Survey (ACS) estimated 700,000 newly insured between 2009 and 2011 (Rodean 2012). Turning to private insurance, research using the CPS ASEC data found that the change associated with the ACA was a 2.5 percentage point drop in own employer-sponsored coverage and a 4.3 percentage point gain in dependent employer-sponsored coverage for young adults aged 19–25 (Sommers and Kronick 2012). These changes amounted to a net 2.9 percentage point decrease in the uninsured rate and a 2.8 percentage point increase in private coverage. The National Health Interview Survey estimated 3 million newly insured young adults, comparing September 2010 versus December 2011 (Sommers 2012). Other research using the CPS ASEC found similar changes in dependent coverage, but slightly higher decreases in the uninsured rate (Cantor et al. 2012). This study also found greater impacts of the ACA in states with prior reforms. Prior research has also showed impacts for selected population subgroups, but sample size has limited the power to detect differences between groups (Sommers et al. 2013). In addition to expanding coverage to young adults, the ACA set a goal of reducing disparities in health care through provisions aimed at improving coverage, access, and outcomes. With this in mind, this research looks at how subgroups were differentially affected by the changes in dependent coverage using data from the ACS; the ACS is a large sample survey with power to detect these differences. Following Sommers and Kronick (2012) and Cantor et al. (2012), we focus on the coverage rate between two different age groups (aged 19–25 and aged 26–29) before and after the dependent coverage took effect. This article adds to the literature by examining coverage rates by state, gender, race, Hispanic origin, English-speaking ability, and citizenship status. In doing so, we provide group-specific and state-specific estimates of the policy's impact. Results are presented as both tabular and regression-based difference-in-difference estimates.