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. Author manuscript; available in PMC: 2016 Jul 19.
Published in final edited form as: Contraception. 2016 Jan 21;93(5):386–391. doi: 10.1016/j.contraception.2016.01.003

Health insurance coverage among women of reproductive age before and after implementation of the affordable care act

Rachel K Jones a,*, Adam Sonfield b
PMCID: PMC4951091  NIHMSID: NIHMS796650  PMID: 26802569

Abstract

Objectives

The Affordable Care Act's expansions to Medicaid and private coverage are of particular importance for women of childbearing age, who have numerous preventive care and reproductive health care needs.

Study design

We conducted two national surveys, one in 2012 and one in 2015, collecting information about health insurance coverage and access to care from 8000 women aged 18–39. We examine type of insurance and continuity of coverage between time periods, including poverty status and whether or not women live in a state that expanded Medicaid coverage.

Results

The proportion of women who were uninsured declined by almost 40% (from 19% to 12%), though several groups, including US-born and foreign-born Latinas, experienced no significant declines. Among low-income women in states that expanded Medicaid, the proportion uninsured declined from 38% to 15%, largely due to an increase in Medicaid coverage (from 40% to 62%). Declines in uninsurance in nonexpansion states were only marginally significant.

Conclusions

Despite substantial improvements in health insurance coverage, significant gaps remain, particularly in states that have not expanded Medicaid and for Latinas.

Implications

This analysis examines changes in insurance coverage that occurred after the Affordable Care Act was implemented. While coverage has improved for many populations, sizeable gaps in coverage remain for Latinas and women in states that did not expand Medicaid.

Keywords: Health insurance, Affordable Care Act, Medicaid, Poverty

1. Introduction

The Affordable Care Act (ACA) included two major expansions to coverage that started in 2014: an expansion in Medicaid eligibility up to 138% of the federal poverty level and subsidized private coverage through new health insurance marketplaces [1]. As of May 2015, 22 states had opted not to implement a Medicaid expansion under the ACA [2]. In these states, individuals at or above 100% of the federal poverty level may be eligible for subsidized marketplace coverage, but many below poverty fall into a coverage gap.

In addition to that gap, many lawfully present immigrants are ineligible for Medicaid for the first 5 years of legal residency [3] and undocumented immigrants are generally barred from public coverage and prohibited from purchasing any coverage, with or without subsidies, through the federal and state marketplaces.

The ACA's coverage expansions are of particular importance for reproductive age women, who have numerous preventive and reproductive health care needs — including contraceptive services, maternity care, abortion care and cervical cancer screening — that are important to their health and well-being and to the health and well-being of their families. In 2013, prior to the ACA's major expansions, 18% of women aged 15–44 were uninsured, with particularly high levels among those who were poor (32%) and foreign born (37%) [4].

Multiple studies and reports have found evidence that Medicaid and private insurance coverage have increased substantially under the ACA and that uninsurance has decreased substantially — particularly in states that have initiated the ACA's Medicaid expansion [5,6,7].

In this analysis, we attempt to gauge the impact of the ACA specifically for reproductive age women. We examine changes in insurance status and differences in these changes according to whether the woman's state has expanded Medicaid. We also explore which sociodemographic groups were still uninsured.

2. Materials and methods

2.1. Survey design

Data for the analyses come from two national surveys, both developed by the Guttmacher Institute and administered by the online recruitment company GfK. The first study gathered data from a national sample of women aged 18–39 in 2012. The second survey collected information from a national sample of women aged 18–39 in 2015.

GfK administered both surveys using their Knowledge-Panel, and each panel was composed of approximately 50,000–55,000 individuals intended to be representative of the US population. GfK obtains informed consent from all individuals, and we obtained expedited approval from the Institutional Review Board of the Guttmacher Institute for both surveys. Surveys were available in English and Spanish.

The purpose of both surveys was to understand pregnancy attitudes and contraceptive use among women within the context of access to health care, including the potential impact of health care reform [8,9]. Both surveys were restricted to women aged 18–39 who had ever had vaginal sex with a man, were not pregnant at the time of the survey, had not had a tubal ligation and whose main male sexual partner had not had a vasectomy. Both surveys utilized the full GfK sample of women aged 18–39. Over a 3-week period in November and December 2012, 11,365 women aged 18–39 were invited to participate in the initial study. Of those, 6658 answered the four screening items, yielding a response rate of 59%; of the 4647 eligible respondents, 4634 completed the full survey. For the second study, 9539 women aged 18–39 were invited to participate over a 3-week period in May and June of 2015; 5029 answered the four screening items yielding a response rate of 53%; all of the 3428 respondents eligible for the survey filled it out. For both samples, GfK provided weights to account for survey nonresponse [10], and weighted data were used for all analyses.

2.2. Analysis

Our analysis focuses on type of health insurance coverage and lack of coverage. For both surveys, women were asked which type of health insurance they currently had: private, Medicaid, some other type of health insurance or no insurance. For the 2015 survey, women were also given the option of indicating that they had obtained coverage from their state-specific health insurance marketplace and whether this coverage was provided through their state-specific Medicaid program. The 62 women who did not provide information about type of health insurance were excluded from all analyses.

Women who currently had insurance were asked if they had had coverage all of the last 6 months. Women who were currently uninsured or had been uninsured any of the last 6 months were asked for how many of these months they had been uninsured.

Demographic characteristics used in the analyses include age group, race and ethnicity, union status, number of children, employment status and educational degree. We also used income, divided into two groups: at or below 138% of poverty or above that cutoff, chosen to let us most directly look at the impact of the ACA's Medicaid expansion. We also examined several measures according to whether or not the woman resided in a Medicaid expansion state. States that had not expanded Medicaid at the time of the 2015 survey included Alabama, Alaska, Florida, Georgia, Idaho, Kansas, Louisiana, Maine, Mississippi, Missouri, Montana, Nebraska, North Carolina, Oklahoma, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Wisconsin and Wyoming. All demographic information was provided by GfK, with the exception of union status.

We first compared the demographic profiles of the two samples. We next examined differences in type of insurance coverage and gaps in coverage during the two time periods, and then assessed whether changes in type of insurance coverage differed according to income and whether or not the woman lived in a Medicaid expansion state.

We relied on simple (bivariable) logistic regression to determine whether changes in dichotomous and categorical outcomes (e.g., percentage uninsured) were statistically significant, using time period as the independent variable. We used multivariable logistic regression to examine whether living in a Medicaid expansion state moderated change between the two time periods in the probability of being insured, adjusting for respondents’ demographic characteristics. All analyses were conducted using Stata 14.0.

3. Results

The 2012 sample was larger by 1206 women, presumably due to a larger sampling frame and the slightly lower response rate of the more recent study, and the two samples, after weighting, differed slightly on a few characteristics (Table 1). A higher proportion of women had no children and was employed full-time in 2015, and a lower proportion was employed part time; this latter difference could be due to fluctuations in the labor market. In addition, the proportion of women without a high school degree was higher in the 2015 sample.

Table 1.

Demographic profile of respondents in the 2012 and 2015 study samples

2012 2015a p value
Unweighted N 4593 3407
Age
    18–24 30.9 28.0 0.072
    25–29 26.8 26.4 0.750
    30–34 23.0 25.1 0.134
    35–39 19.2 20.6 0.285
Marital status
    Married 47.7 45.3 0.146
    Not married 52.4 54.7 0.146
Number of births
    0 48.4 51.6 0.048
    1 21.6 20.6 0.440
    2+ 30.0 27.8 0.127
Race and ethnicity
    White, Non-Hispanic 58.7 56.9 0.263
    Black, Non-Hispanic 13.6 13.8 0.890
    Other, Non-Hispanic 8.5 9.4 0.409
    Hispanic 19.2 20.0 0.069
        Born in US 10.3 12.1 0.286
        Not born in US 8.9 8.0 0.525
Employment status
    Not employed 37.7 34.9 0.075
    Part time (1–34 h) 22.8 19.1 0.006
    Full time (35+ h) 39.5 46.0 0.000
Highest degree
    Less than high school 5.8 9.6 0.000
    High school 23.4 19.4 0.007
    Some college 36.2 34.8 0.353
    Bachelor's degree or higher 34.5 36.2 0.235
Income status
    ≤ 138% of poverty 22.4 22.1 0.765
    139 + % 77.6 78.0 0.765
Lived in Medicaid expansion state
    Yes 58.8 60.4 0.324
    No 41.2 39.6 0.324
a

Simple logistic regression using year as the independent variable was used to assess differences between the two samples.

The proportion of women who were currently uninsured declined from 18.9% in 2012 to 11.5% in 2015 (Table 2), due to increased coverage in both private insurance and Medicaid. A larger proportion of women had been insured all of the last 6 months in 2015 than in 2012 (83.4% vs. 77.1%), and any reported gaps were more likely to be short ones.

Table 2.

Percentage distribution of type of health insurance, continuity of coverage and gaps in coverage, 2012 and 2015

2012 2015a p value
Unweighted N 4593 3407
Type of health insurance
    Uninsured 18.9 11.5 0.000
    Private 66.1 69.5 0.033
        Obtained through the exchange na 5.3
    Medicaid 14.2 18.2 0.001
    Other 0.8 0.8 0.939
Insured all of last 6 months 77.1 83.4 0.000
Among those without insurance in any of last 6 months
Unweighted N 1036 506
How long without insurance (months)
    1 7.7 15.9 0.002
    2 5.5 5.7 0.888
    3 7.8 9.4 0.423
    4 6.7 6.6 0.954
    5 2.6 7.2 0.011
    6 69.7 55.1 0.000

na = not applicable.

a

Simple logistic regression using year as the independent variable was used to assess differences between the two samples.

While women in 2015 were more likely to have insurance, we did not find any changes in their access to care as measured on our survey. In both time periods, similar proportions of women had a regular health care provider (79%) or had made a visit in the last 6 months for a general health exam (47%–48%) or because they were sick (44%– 45%) (not shown). Women in the most recent survey were asked how satisfied they were with their health care coverage and did not differ significantly in whether they were satisfied (rating of five or six on a 6-point scale) according to whether they had Medicaid (65.3%) or private coverage (69.5%, p = .178).

There were important differences in type of coverage according to poverty status and whether or not the woman resided in a state that had adopted the Medicaid expansion (Table 3). Women at or below 138% of poverty showed substantial declines in the proportion uninsured, 40.0% to 24.6%, due to increased Medicaid coverage. Substantially fewer women with incomes greater than 138% were uninsured in 2015 than in 2012. This group also experienced slight increases in both types of coverage, but neither was statistically significant.

Table 3.

Type of insurance coverage by poverty status, by whether the respondent lived in a Medicaid expansion state and by both, 2012 and 2015

Expansion state Nonexpansion state ≤ 138% poverty
≤ 138% poverty p 139 + % poverty p p p Expansion state p Nonexpansion state p

2012 2015a 2012 2015a 2012 2015a 2012 2015a 2012 2015a 2012 2015a
Unweighted N 1337 908 3256 2499 2846 2109 1788 1319 803 563 534 345
Uninsured 40.0 24.6 0.000 12.8 7.8 0.000 16.5 7.3 0.000 22.3 18.0 0.052 37.6 15.1 0.000 43.1 38.5 0.382
Private 23.4 28.1 0.088 78.5 81.2 0.103 66.3 68.2 0.350 65.9 71.4 0.027 21.2 22.6 0.659 26.1 36.3 0.040
Exchange na 5.6 na 4.5 na 4.5 na 6.6 na 1.7 na 8.5
Medicaid 34.8 46.3 0.000 8.2 10.2 0.088 16.3 23.5 0.000 11.2 10.1 0.520 39.9 61.8 0.000 28.4 23.3 0.261
Other 1.8 1.1 0.334 0.5 0.7 0.480 0.9 1.0 0.773 0.6 0.5 0.672 1.3 0.5 0.207 2.4 1.9 0.731
a

Simple logistic regression using year as the independent variable was used to assess differences between the two samples.

Even prior to the implementation of the ACA, women in states that did not adopt the Medicaid expansion were more likely to be uninsured, 22.3% compared to 16.5% (p=.002, significance not shown). In Medicaid expansion states, there was a significant decline in the proportion of women who were uninsured due to an increase in Medicaid coverage. The decline in the proportion of women who were uninsured in nonexpansion states was only marginally significant (p= .052), though there was a significant increase in private coverage.

Among women at or below 138% of poverty residing in expansion states, the proportion uninsured decreased from 37.6% to 15.1%, as Medicaid coverage increased from 39.9% to 61.8%. In nonexpansion states, the proportion of women at or below 138% of poverty with private insurance increased from 26.1% to 36.3%. (Many of those between 100% and 138% of poverty were eligible for subsidized marketplace coverage in states that had not expanded Medicaid.)

The proportion of women who were uninsured declined significantly for all but a few groups when looking at additional demographic characteristics (Table 4). The exceptions were nonsignificant changes in the proportion uninsured for women aged 35–39, women without a high school degree and Latinas. Still, substantial disparities in uninsurance remained in 2015, particularly for non-White women, those employed less than full time and those with lower levels of education.

Table 4.

Percent of women uninsured, by selected characteristics and multivariable logistic regression model for uninsured status

% Currently uninsured
Odds ratios
2012 2015a p 95% Confidence interval p values
Unweighted N 4593 3407 7984
Total 18.9 11.5 0.000
Age
    18–24 20.3 11.0 0.000 1.00
    25–29 19.7 10.7 0.000 1.58 1.17–2.12 0.003
    30–34 17.7 11.6 0.015 1.54 1.09–2.18 0.014
    35–39 16.8 13.2 0.153 1.47 1.04–2.09 0.031
Marital status
    Married 16.0 9.8 0.000 0.71 0.55–0.92 0.009
    Not married 21.6 13.0 0.000 1.00
Number of births
    0 17.4 9.9 0.000 1.00
    1 17.3 9.6 0.002 0.66 0.50–0.89 0.006
    2+ 22.1 16.0 0.010 0.63 0.47–0.86 0.003
Race and ethnicity
    White, Non-Hispanic 12.8 6.3 0.000 1.00
    Black, Non-Hispanic 22.6 12.1 0.013 1.30 0.91–1.87 0.147
    Other, Non-Hispanic 16.1 4.4 0.007 1.25 0.80–1.95 0.327
    Hispanic 37.0 29.2 0.052 na
        Born in US 26.2 19.4 0.090 2.20 1.67–2.90 0.000
        Not born in US 47.3 44.2 0.593 4.57 3.37–6.20 0.000
Employment
    Not employed 24.8 18.8 0.013 1.00
    1–34 h 21.4 12.8 0.003 1.00 0.76–1.30 0.987
    35 or more hours 11.8 5.5 0.000 0.57 0.43–0.76 0.000
Highest degree
    Less than high school 44.1 33.3 0.098 1.00
    High school 30.1 18.7 0.001 0.81 0.57–1.17 0.258
    Some college 19.2 10.0 0.000 0.49 0.34–0.71 0.000
    Bachelor's or higher 6.8 3.4 0.004 0.22 0.14–0.33 0.000
Income status
    < 139% of poverty 40.0 24.6 0.000 2.12 1.67–2.69 0.000
    139 + % 12.8 7.8 0.000 1.00
Lived in Medicaid expansion state
    Yes 16.5 7.3 0.000 1.00
    No 22.3 18.0 0.052 2.01 1.64–2.47 0.000
Time period
    2012 na na 1.00
    2015 na na 0.50 0.40–0.61 0.000
Intercept na na 0.25 0.16–0.39 0.000
a

Simple logistic regression using year as the independent variable was used to assess differences between the two samples.

We used logistic regression to simultaneously examine associations between all characteristics and uninsured status. Relative to young adults, women in all other age groups were more likely to be uninsured once other factors were taken into account. Compared to White women, Latina women born in the US had twice the odds of being uninsured, and the odds for foreign-born Latinas were more than four times as high.

Women who lived in a nonexpansion state had twice the odds of being uninsured. After taking individual characteristics into account, the odds of being uninsured were reduced by half for women in 2015 compared to 2012.

Finally, in order to better understand factors associated with lack of insurance coverage among Latinas, we ran logistic regression models limited to this subgroup (not shown). The odds of being uninsured were about twice as high for immigrant women (odds ratio [OR], 1.88) compared to those born in the United States. Compared to Latinas in nonexpansion states in 2012, those in expansion states had .59 the odds of being uninsured during the same time period, and this difference became even more pronounced by 2015 (OR, .23, p<.001). However, in 2015, Latinas in nonexpansion states were no more or less likely to be uninsured than they were in 2012.

4. Discussion

This study provides further evidence that the ACA is increasing health care coverage and for women of reproductive age specifically. The proportion of women who were uninsured declined by nearly 40% between fall 2012 and spring 2015, driven by increases in both Medicaid and private coverage. These findings echo those of other studies looking at the broader US population [5,6,7].

Moreover, more women reported 6 months of continuous coverage, and among those reporting a gap, the gap was more likely in 2015 to last only 1 month. Reducing this “churn” promotes continuity of care and helps women afford care — including often time-sensitive reproductive health care — when they need it.

This study also makes it clear that states’ decisions about whether to expand Medicaid matter greatly for health insurance coverage among women of reproductive age. Among women at or below 138% of poverty in states that implemented the ACA's Medicaid expansion, the proportion uninsured dropped by 60%, while the proportion with Medicaid coverage increased by 55%. By contrast, we found no significant increase in coverage among low-income women in states that had not expanded Medicaid, although some of them obtained subsidized private coverage on the new marketplaces. Our regression analyses points to the same conclusion: The ACA has had a particularly strong effect in states that have expanded Medicaid. On a related note, women were roughly just as likely be satisfied with Medicaid as with private coverage, contrary to frequent criticisms of Medicaid's quality by ACA opponents.

In our study, women aged 18–24 were substantially less likely to be uninsured than older women, after controlling for other demographic factors. This finding echoes earlier studies, which estimated that an ACA provision allowing individuals to remain on a parent's health plan until age 26 helped insure more than 2 million young adults [11].

Although nearly every demographic group has seen improvements in coverage since the ACA was implemented, real disparities persist. The trends for Latinas are particularly notable: They did not experience a significant increase in insurance coverage between 2012 and 2015. We also found that US-born Latinas had twice the odds of being uninsured as White women, and foreign-born Latinas had more than four times the odds. Taken together, our findings strongly suggest that federal restrictions on immigrant women's eligibility for Medicaid and marketplace coverage are interfering with many Latinas’ ability to obtain coverage. Those restrictions may have indirect effects even for women who are eligible for coverage. For example, some US citizens and lawfully present residents may be wary of signing up for coverage because they fear that it will put undocumented family members at risk of deportation, despite assurances from the federal government to the contrary [12].

We are aware of several potential shortcomings. Both samples were limited to women aged 18–39 and attempted to capture women most likely to be at risk of unintended pregnancy. Moreover, while GfK maintains that its panel is nationally representative, only 53%–59% of eligible women aged 18–39 answered the four screening items that determined if they were eligible to participate in the study. Thus our samples cannot be considered to be nationally representative. Still, our findings are based on two national samples totaling 8000 women combined, and patterns are likely real and applicable to the national population of women of reproductive age. In addition, prior studies have documented that self-reported health insurance status is prone to measurement error [13], and this may be even more pronounced as individuals adjust to the ACA. However, patterns in private and Medicaid coverage follow those we would generally expect, suggesting many people answered the items correctly. In addition, we expect our measurement of uninsured is largely accurate as most individuals generally know whether they have coverage or not.

Overall, our findings provide evidence that the ACA has greatly expanded Medicaid and private coverage for reproductive age women and has reduced disparities in coverage, particularly for low-income women. This means that many more US women now have comprehensive coverage to help them afford a wide range of care.

Despite this progress, significant gaps remain, particularly in states that have not expanded Medicaid and for Latina women. These gaps would be reduced if all states took up the ACA's Medicaid expansion, Congress removed eligibility restrictions for immigrants and policymakers at the state and national levels took other steps to address barriers to eligibility and enrollment for Latinas, immigrants and other disadvantaged groups.

Acknowledgements

Data collection (of both surveys), analyses and summary of the findings were supported by The JPB Foundation. We thank our colleagues Rachel Benson Gold and Lawrence Finer, both from the Guttmacher Institute, for reviewing earlier drafts of this manuscript.

References

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