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Health Care Coverage and Access Among Children, Adolescents, and Young Adults, 2010–2016: Implications for Future Health Reforms

      Abstract

      Purpose

      We examine changes to health insurance coverage and access to health care among children, adolescents, and young adults since the implementation of the Affordable Care Act.

      Methods

      Using the National Health Interview Survey, bivariate and logistic regression analyses were conducted to compare coverage and access among children, young adolescents, older adolescents, and young adults between 2010 and 2016.

      Results

      We show significant improvements in coverage among children, adolescents, and young adults since 2010. We also find some gains in access during this time, particularly reductions in delayed care due to cost. While we observe few age-group differences in overall trends in coverage and access, our analysis reveals an age-gradient pattern, with incrementally worse coverage and access rates for young adolescents, older adolescents, and young adults.

      Conclusions

      Prior analyses often group adolescents with younger children, masking important distinctions. Future reforms should consider the increased coverage and access risks of adolescents and young adults, recognizing that approximately 40% are low income, over a third live in the South, where many states have not expanded Medicaid, and over 15% have compromised health.

      Keywords

      See Related Editorial on p. 641
      Implications and Contribution
      Analyses of coverage and access often group adolescents with younger children, masking important distinctions. This analysis reveals an age-gradient pattern, with incrementally worse coverage and access for young adolescents, older adolescents, and young adults. Future health reforms should consider the vulnerabilities of both adolescents and young adults.
      Reports of health insurance coverage and access to health care typically provide separate rates for children and nonelderly and elderly adults, and it is well documented that young adults are among those at highest risk of uninsurance [
      • Rhoades J.A.
      Health insurance status of young adults, ages 19–25, 2013.
      ,
      • Barnette J.C.
      • Vornovitsky M.S.
      Health insurance coverage in the United States: 2015.
      ]. From birth through young adulthood, however, important shifts in insurance availability occur from “aging out” of public programs and changes in residence and income, among other factors [
      • Ham J.C.
      • Xianghong L.
      • Shore-Sheppard L.D.
      The dynamics of children's health insurance, 1986–1999.
      ,
      • Fairlie R.W.
      • London R.A.
      The dynamics of health insurance coverage: Identifying trigger events for insurance loss and gain.
      ,
      • Adams S.H.
      • Newacheck P.W.
      • Park M.J.
      • et al.
      Health insurance across vulnerable ages: Patterns and disparities from adolescence to the early 30s.
      ,
      • Larson K.
      • Cull W.L.
      • Racine A.D.
      • Olson L.M.
      Trends in access to health services for US children: 2000–2014.
      ]. During this formative period, access to care also shifts due to insurance fluctuations, changing health needs, and challenges in transitioning from pediatric to adult care, including delays in finding a new usual source of care [
      • Larson K.
      • Cull W.L.
      • Racine A.D.
      • Olson L.M.
      Trends in access to health services for US children: 2000–2014.
      ,
      • Lau J.S.
      • Adams S.H.
      • Boscardin W.J.
      • Irwin C.E.
      Young adults' health care utilization and expenditures prior to the Affordable Care Act.
      ,
      • Lassman D.
      • Sisko A.M.
      • Catlin A.
      • et al.
      Health spending by state 1991–2014: Measuring per capita spending by payers and programs.
      ,
      • Cole R.
      • Ashok D.
      • Razack A.
      • et al.
      Evaluation of outcomes in outcomes in adolescent inflammatory bowel disease patients following transfer from pediatric to adult health care services: Case for transition.
      ]. Linkages to insurance and care during childhood positively affect health and predict future adult health outcomes [
      • Institute of Medicine and National Research Council
      ,
      • Forrest C.B.
      • Riley A.W.
      Childhood origins of adult health: A basis for life-course health policy.
      ,
      • Wherry L.R.
      • Miller S.
      • Kaestner R.
      • Meyer B.D.
      Childhood Medicaid coverage and later life health care utilization.
      ]. The National Academy of Medicine, in their groundbreaking studies on adolescent [
      • Committee on Adolescent Health Care Services and Models of Care for Treatment, Prevention, and Healthy Development
      Adolescent health services: Missing opportunities.
      ] and young adult health [
      • Institute of Medicine and National Research Council
      ], acknowledged the significance and volatility of the ages from 10 to 26 and called for greater attention to the many transitions that result in gaps in insurance coverage and needed health care.
      Several provisions of the Affordable Care Act (ACA) sought to improve continuity in coverage and access to care for young people. Starting in 2010, the ACA enabled individuals with employer-sponsored insurance to continue coverage of dependent children until the age of 26. The ACA also eliminated preventive care cost sharing and pre-existing condition requirements, banned annual and lifetime limits on coverage, and offered small business tax credits to make coverage more affordable. In 2011, new investments were made to increase the number of primary care practitioners and community and school-based health centers. Most other ACA expansions went into full effect in 2014, including premium subsidies for non–group health insurance purchased via marketplaces, state Medicaid expansions that some states initiated as early as 2011 to childless adults and children ages 6–18 with incomes below 133% of the Federal Poverty Level (FPL), extended Medicaid eligibility for former foster care youth, elimination of Children's Health Insurance Program (CHIP) waiting periods, and an increased federal CHIP match rate [
      • UC Berkeley Labor Center
      ].
      Much has been written about the effects of the ACA, with studies documenting positive effects for both children and young adults [
      • Alker J.
      • Chester A.
      Children's health insurance rates in 2014: ACA results in significant improvements.
      ,
      • Barbaresco S.
      • Courtemanche C.J.
      • Qi Y.
      Impacts of the Affordable Care Act dependent coverage provision on health-related outcomes of young adults.
      ,
      • Garrett B.
      • Gangopadhyaya A.
      Who gained health insurance coverage under the ACA, and where do they live?.
      ,
      • Gates J.A.
      • Karpman M.
      • Kenney G.M.
      • McMorrow S.
      Uninsurance among children, 1997–2015: Long-term trends and recent patterns.
      ,
      • Johnston E.M.
      • Gates J.A.
      • Kenney G.M.
      Medicaid and CHIP for children.
      ,
      • Kenney G.M.
      • Haley J.M.
      • Pan C.
      • et al.
      Medicaid/CHIP participation rates rose among children and parents in 2015.
      ,
      • Kotagal M.
      • Carle A.C.
      • Kessler L.G.
      • Flum D.R.
      Limited impact on health and access to care for 19–25 years-olds following the patient protection and Affordable Care Act.
      ,
      • Lau J.S.
      • Adams S.H.
      • Boscardin W.J.
      • Irwin C.E.
      Improvement in preventive care of young adults after the Affordable Card Act.
      ,
      • McMorrow S.
      • Kenney G.M.
      • Long S.K.
      • Anderson N.
      Uninsurance among young adults continues to decline, particularly in Medicaid expansion states.
      ,
      • Miller S.
      • Wherry L.R.
      Health and access to care during the first 2 years of the ACA Medicaid expansions.
      ,
      • Pilkey D.
      • Skopec L.
      • Gee E.
      • et al.
      The Affordable Care Act and adolescents. ASPE research brief.
      ,
      • Sommers B.D.
      • Buchmueller T.
      • Decker S.L.
      • et al.
      The Affordable Care Act has led to significant gains in health insurance and access to care for young adults.
      ,
      • Sommers B.D.
      • Gunja M.Z.
      • Finegold K.
      • Musco T.
      Changes in self-reported insurance coverage, access to care, and health under the Affordable Care Act.
      ,
      • Wong C.A.
      • Ford C.A.
      • French B.
      • Rubin D.M.
      Changes in young adult primary care under the Affordable Care Act.
      ]. Although there is pre-ACA research using 2009 data from the Medical Expenditure Panel Survey [
      • Lau J.S.
      • Adams S.H.
      • Boscardin W.J.
      • Irwin C.E.
      Young adults' health care utilization and expenditures prior to the Affordable Care Act.
      ] and 2002 and 2003 data from the National Health Interview Survey (NHIS) [
      • Adams S.H.
      • Newacheck P.W.
      • Park M.J.
      • et al.
      Health insurance across vulnerable ages: Patterns and disparities from adolescence to the early 30s.
      ] examining access to coverage and health-care utilization among subgroups of children and young adults, there are no recently published studies that examine coverage and access differences among children, young adolescents, older adolescents, and young adults following ACA implementation.
      With respect to ACA impacts on individuals under 18 years of age in general, published studies using nationally representative survey data from the American Community Survey and NHIS have consistently found reductions in uninsurance, increases in Medicaid/CHIP participation, and improvements in medical and dental care use [
      • Alker J.
      • Chester A.
      Children's health insurance rates in 2014: ACA results in significant improvements.
      ,
      • Garrett B.
      • Gangopadhyaya A.
      Who gained health insurance coverage under the ACA, and where do they live?.
      ,
      • Gates J.A.
      • Karpman M.
      • Kenney G.M.
      • McMorrow S.
      Uninsurance among children, 1997–2015: Long-term trends and recent patterns.
      ,
      • Kenney G.M.
      • Haley J.M.
      • Pan C.
      • et al.
      Medicaid/CHIP participation rates rose among children and parents in 2015.
      ]. As Urban Institute and Georgetown researchers noted, reductions in uninsurance among children began well in advance of the ACA, but new public and private insurance options for adults have had a strong “spillover effect” on continued coverage and access improvements for children [
      • Alker J.
      • Chester A.
      Children's health insurance rates in 2014: ACA results in significant improvements.
      ,
      • Kenney G.M.
      • Haley J.M.
      • Pan C.
      • et al.
      Medicaid/CHIP participation rates rose among children and parents in 2015.
      ]. With respect to ACA impacts on young adults, published studies based on the American Community Survey, the Medical Expenditure Panel Survey, and NHIS data have documented solid reductions in uninsurance and mixed effects related to access to care associated with expansions in dependent private coverage, Medicaid, and non–group insurance through marketplace exchanges [
      • Barbaresco S.
      • Courtemanche C.J.
      • Qi Y.
      Impacts of the Affordable Care Act dependent coverage provision on health-related outcomes of young adults.
      ,
      • Kotagal M.
      • Carle A.C.
      • Kessler L.G.
      • Flum D.R.
      Limited impact on health and access to care for 19–25 years-olds following the patient protection and Affordable Care Act.
      ,
      • Lau J.S.
      • Adams S.H.
      • Boscardin W.J.
      • Irwin C.E.
      Improvement in preventive care of young adults after the Affordable Card Act.
      ,
      • Sommers B.D.
      • Buchmueller T.
      • Decker S.L.
      • et al.
      The Affordable Care Act has led to significant gains in health insurance and access to care for young adults.
      ].
      We analyze trends in the level of coverage and access for young children, young adolescents, older adolescents, and young adults since the initial ACA implementation in 2010 through 2016, 3 years following full implementation. We highlight findings for adolescent and young adult age groups compared with younger children and discuss implications for future health reform. As insurance reforms unfold in the current policy environment, attention to the distinctive needs of these age groups is warranted.

      Methods

      We used 2010–2016 data from the NHIS, an annual health survey of a representative sample of the U.S. civilian, noninstitutionalized population [
      • Centers for Disease Control and Prevention
      About the National Health Interview Survey.
      ]. The data were drawn from the IPUMS Health Surveys: National Health Interview Survey, a harmonized, multiyear version of the NHIS public-use files [
      • Blewett L.A.
      • Drew J.A.
      • Griffin R.
      • et al.
      IPUMS health surveys: National Health Interview Survey, version 6.2.
      ]. The sample included individuals aged 0–25 years, totaling up to 39,399 sample members per survey year. The sample was divided into four age groups: young children (0–9 years), young adolescents (10–14 years), older adolescents (15–18 years), and young adults (19–25 years). These age groups correspond closely with the World Health Organization's definition of early and late adolescence [
      • Patton G.C.
      • Sawyer S.M.
      • Santelli J.S.
      • et al.
      Our future: A Lancet commission on adolescent health and wellbeing.
      ] and align with the young adult coverage provision associated with the ACA, which provides protections for individuals through the age of 25.
      Study outcomes included point-in-time health insurance coverage and three measures of health-care access. Individuals were coded as being uninsured, having private coverage (i.e., employer-based or nongroup), or having public insurance (e.g., Medicaid or CHIP). Very few individuals (approximately 1%) had both private and public sources of insurance, and they were combined with those with public coverage. Health-care access measures included whether an individual has a usual source of care, had a doctor/provider visit (general practice, family medicine, internal medicine) in the past year, and needed but delayed care due to costs in the past year. Other variables used in the analysis were gender, race/ethnicity, percent of FPL, region, self-reported health status, and having a limitation of activity. All variables were available for all members of sampled households, with the exception of usual source of care and past year doctor visit, which were collected only for one randomly selected adult and child within a sampled household. A responsible/knowledgeable adult completes the NHIS questionnaire for children aged 17 and younger [
      • U.S. Department of Health and Human Services
      Design and estimation for the National Health Interview Survey, 2006–2015.
      ].
      All analyses were based on weighted data and accounted for the complex sample design of the NHIS using SAS 9.4 software (SAS Institute Inc., Cary, NC) and Stata 14 software (StataCorp, College Station, TX). Bivariate analyses using z-tests of significance were conducted to compare unadjusted rates of health insurance coverage and access among age groups over time. Specifically, we compared rates of coverage and access between subsequent years in the study period and between 2010 and 2016. We fit multivariable logistic regression models to predict insurance coverage as a function of age group categories, year dummies, and their interaction, controlling for gender, race/ethnicity, percent of FPL, region, health status, and activity limitation. The interaction terms were included to test differences in trends between age groups. We fit an identical model to predict each of the three access outcomes, except that we added insurance coverage as a covariate. Standard errors were estimated clustered at the sampling strata of the NHIS to obtain estimates that were robust to the presence of heteroskedasticity and autocorrelation. Since we introduce interaction terms and our estimation was not linear, it may not be straightforward to interpret the estimated coefficients. Thus, we show the marginal effects for the age groups and year dummies. These marginal effects were estimated using the margins command in Stata (StataCorp), which takes into account the interaction terms included in the model [
      • Karaca-Mandic P.
      • Norton E.C.
      • Dowd B.
      Interaction terms in nonlinear models.
      ]. The marginal effects indicate the change in the probability of the outcome (measured in percentage points) of a specific age group or year in comparison with the reference group (children aged 0–9 or year 2010).
      There are several limitations to the data and methods used in our analyses. The NHIS is a cross-sectional survey, and therefore, we were unable to monitor change in outcomes for the same individuals over time. The NHIS sampling plan is adjusted following every decennial census, and its most recent redesign took effect during our study period, in the 2016 survey [
      • Centers for Disease Control and Prevention
      About the National Health Interview Survey.
      ]. Measures derived from the NHIS are based on self-reported data, and it is possible that respondent reporting of health-care access may have included inaccuracies due to challenges in recall over an extended time (i.e., in the past 12 months). Our analysis also used respondents' health insurance coverage as reported at the time of the survey, and it is possible that a person's coverage may have shifted during a given year. Finally, it is important to note that our analyses do not identify the causes of changes in coverage and access over the study period.
      The data used in the analyses are de-identified and publicly available. Based on a worksheet furnished by the University of Minnesota Institutional Review Board (IRB), the analyses did not meet the IRB's definition of human subjects research, and no IRB review was required.

      Results

      Sample characteristics

      Table 1 presents demographic and health characteristics of the 2016 study population. Because these characteristics were generally consistent between 2010 and 2016, we report data for the most recent year. For each age group, gender was evenly split; over half were non-Hispanic white, approximately two fifths lived in families with incomes below 200% of FPL, and over a third lived in the South. Health status was generally high but did vary by age group. While 86% of young children were rated as being in excellent or very good health, this percentage was lower for the older age groups, especially young adults, of whom 78% rated their health highly.
      Table 1Demographic and health characteristics of children, adolescents, and young adults (percentages), 2016
      Selected characteristicsAge 0–9Age 10–14Age 15–18Age 19–25
      Gender
       Male51.051.250.950.8
       Female49.048.849.149.2
      Race/ethnicity
       Hispanic25.824.322.921.8
       White, non-Hispanic52.153.955.456.4
       Black, non-Hispanic14.714.414.714.8
       Other, non-Hispanic7.47.47.07.0
      Poverty level
        < 200% FPL45.341.1
      Statistically significant difference with the age group immediately younger at the 95% confidence level.
      39.444.7
      Statistically significant difference with the age group immediately younger at the 95% confidence level.
        ≥ 200% FPL54.758.9
      Statistically significant difference with the age group immediately younger at the 95% confidence level.
      60.655.3
      Statistically significant difference with the age group immediately younger at the 95% confidence level.
      Region
       Northeast17.218.118.818.4
       Midwest21.821.520.621.7
       South37.436.636.135.8
       West23.623.824.524.1
      Health status
       Excellent/very good86.283.1
      Statistically significant difference with the age group immediately younger at the 95% confidence level.
      81.577.7
      Statistically significant difference with the age group immediately younger at the 95% confidence level.
       Good12.515.0
      Statistically significant difference with the age group immediately younger at the 95% confidence level.
      16.118.2
      Statistically significant difference with the age group immediately younger at the 95% confidence level.
       Fair/poor1.31.9
      Statistically significant difference with the age group immediately younger at the 95% confidence level.
      2.44.1
      Statistically significant difference with the age group immediately younger at the 95% confidence level.
      Limitation of activity
       Has limitation8.011.3
      Statistically significant difference with the age group immediately younger at the 95% confidence level.
      9.0
      Statistically significant difference with the age group immediately younger at the 95% confidence level.
      5.5
      Statistically significant difference with the age group immediately younger at the 95% confidence level.
       No limitation92.088.7
      Statistically significant difference with the age group immediately younger at the 95% confidence level.
      91.0
      Statistically significant difference with the age group immediately younger at the 95% confidence level.
      94.5
      Statistically significant difference with the age group immediately younger at the 95% confidence level.
      Source: Author analysis of IPUMS Health Surveys: National Health Interview Survey data, 2016. Accessed through the Minnesota Population Center and State Health Access Data Assistance Center: Version 6.2. Minneapolis: University of Minnesota, 2016. Results presented are from bivariate analyses using z-tests of significance.
      FPL = Federal Poverty Level.
      a Statistically significant difference with the age group immediately younger at the 95% confidence level.

      Health insurance coverage

      Between 2010 and 2016, all four age groups experienced decreases in uninsurance, with some year-to-year comparisons reaching statistical significance, particularly in 2014 and 2015 (Table 2). Low rates of uninsurance for young children were associated with high rates of both private and public coverage. For young adolescents aged 10–14, a reduced uninsurance rate in 2015 and 2016 was the result of an increase in public coverage over time, which also offset a decline in private coverage during the 7-year period. For older adolescents aged 15–18, an overall decline in uninsurance was associated with an overall increase in public coverage, with private coverage stable during this period. For young adults, the sizeable decline in uninsurance was primarily the result of increases in private coverage over time. Although young adults had lower rates of public coverage than other age groups, their public coverage increased significantly in 2014, which marked full ACA implementation, and again in 2016. Overall, young children were the only group not to experience a significant increase in public coverage between 2010 and 2016, and young adults were the only group to experience an increase in private coverage during this time period.
      Table 2Health insurance coverage among children, adolescents, and young adults (percentages), 2010–2016
      Coverage by age2010201120122013201420152016Change from 2010 to 2016
      Age 0–9
       Uninsured6.75.75.15.34.4
      Statistically significant change from the prior year at the 95% confidence interval.
      3.6
      Statistically significant change from the prior year at the 95% confidence interval.
      4.5
      Statistically significant change from the prior year at the 95% confidence interval.
      −2.2
      Statistically significant change from 2010 to 2016 at the 95% confidence interval.
       Private51.450.850.950.652.252.652.1 +.7
       Public41.943.543.944.143.443.843.4+1.5
      Age 10–14
       Uninsured8.27.87.57.56.3
      Statistically significant change from the prior year at the 95% confidence interval.
      5.1
      Statistically significant change from the prior year at the 95% confidence interval.
      5.3−2.9
      Statistically significant change from 2010 to 2016 at the 95% confidence interval.
       Private59.958.056.557.456.157.056.7−3.2
      Statistically significant change from 2010 to 2016 at the 95% confidence interval.
       Public31.934.235.935.137.6
      Statistically significant change from the prior year at the 95% confidence interval.
      37.838.0+6.1
      Statistically significant change from 2010 to 2016 at the 95% confidence interval.
      Age 15–18
       Uninsured12.411.310.910.78.3
      Statistically significant change from the prior year at the 95% confidence interval.
      7.37.6−4.8
      Statistically significant change from 2010 to 2016 at the 95% confidence interval.
       Private60.460.259.960.060.661.261.3+.9
       Public27.228.629.229.331.131.431.1+3.9
      Statistically significant change from 2010 to 2016 at the 95% confidence interval.
      Age 19–25
       Uninsured33.827.9
      Statistically significant change from the prior year at the 95% confidence interval.
      26.326.719.7
      Statistically significant change from the prior year at the 95% confidence interval.
      16.0
      Statistically significant change from the prior year at the 95% confidence interval.
      13.9
      Statistically significant change from the prior year at the 95% confidence interval.
      −19.9
      Statistically significant change from 2010 to 2016 at the 95% confidence interval.
       Private53.158.0
      Statistically significant change from the prior year at the 95% confidence interval.
      59.560.463.6
      Statistically significant change from the prior year at the 95% confidence interval.
      67.1
      Statistically significant change from the prior year at the 95% confidence interval.
      67.1+14.0
      Statistically significant change from 2010 to 2016 at the 95% confidence interval.
       Public13.214.114.212.916.7
      Statistically significant change from the prior year at the 95% confidence interval.
      16.919.1
      Statistically significant change from the prior year at the 95% confidence interval.
      +5.9
      Statistically significant change from 2010 to 2016 at the 95% confidence interval.
      Source: Author analysis of IPUMS Health Surveys: National Health Interview Survey data, 2010–2016. Accessed through the Minnesota Population Center and State Health Access Data Assistance Center: Version 6.2. Minneapolis: University of Minnesota, 2016. Individuals with both public and private insurance coverage were classified under public. Results presented are from bivariate analyses using z-tests of significance.
      a Statistically significant change from the prior year at the 95% confidence interval.
      b Statistically significant change from 2010 to 2016 at the 95% confidence interval.
      Despite across-the-board coverage gains over time, uninsurance rates were higher for each older age group, with adolescents and young adults most likely to lack insurance. In 2016, for example, 14% of young adults were uninsured. While this rate was nearly double the rate for older adolescents, it was more than three times the rate for young children.
      Our regression analysis confirms the patterns described above: a significant decrease in uninsurance observed between 2010 and 2016 and an age gradient of lower to higher uninsurance from younger to older age groups. Specifically, the marginal effects shown in Table 3 indicate that not only was each older age group more likely to be uninsured than young children (reference group), each older age group was more likely to be uninsured than the age group immediately younger after controlling for covariates. Young adults were over 13 percentage points more likely to be uninsured than older adolescents, older adolescents were over three percentage points more likely to be uninsured than young adolescents, and young adolescents were two percentage points more likely to be uninsured than young children. After controlling for the other variables in the model, children, adolescents, and young adults were almost eight percentage points less likely to be uninsured in 2016 compared with 2010. Regression results reinforce that this overall decline in uninsurance relative to 2010 was similar across all age groups with the exception of young adults, who had a significantly larger decrease in uninsurance in 2014, 2015, and 2016 (see Table A1 in the Appendix).
      Table 3Uninsurance Among Children, Adolescents, and Young Adults, 2010–2016: Estimates of Marginal Effects
      Variables(1)(2)(3)(4)(5)
      Estimate (percent points)Standard error (percent points)Lower bound (95% CI)Upper bound (95% CI)p value
      Age 10–142.18.171.852.52.000
      Age 15–185.41.234.965.86.000
      Age 19–2518.70.4117.9019.50.000
      Year 2011−2.40.38−3.14−1.66.000
      Year 2012−3.28.33−3.93−2.62.000
      Year 2013−3.04.39−3.80−2.27.000
      Year 2014−5.89.35−6.58−5.19.000
      Year 2015−7.47.39−8.23−6.71.000
      Year 2016−7.56.53−8.60−6.53.000
      Observations252,656
      Source: Author analysis of IPUMS Health Surveys: National Integrated Health Survey, 2010–2016. Accessed through the Minnesota Population Center and State Health Access Data Assistance Center: Version 6.2. Minneapolis: University of Minnesota, 2016. Results presented are from logistic regression analysis using the margins command in Stata 14 (StataCorp).
      Marginal effects presented in percent point units.
      The reference groups were (1) children ages 0–9 and (2) year 2010.
      Other covariates were gender, race/ethnicity, percent of FPL, region, health status, and activity limitation. In addition, interaction terms between the age cohorts and years were included in the estimation.
      CI = confidence interval; FPL = Federal Poverty Level.

      Health-care access

      Access to health care among young people advanced somewhat between 2010 and 2016, with improvements in at least one measure of access observed for children and adolescents and in all measures for young adults during the 7-year period (Table 4). Reports of delayed care due to costs fell for all age groups between 2010 and 2016. The percentage of young adults who had a doctor visit in the past year and who had a usual source of care increased over time as well.
      Table 4Health Care Access Among Children, Adolescents, and Young Adults (Percentages), 2010–2016
      Health care access by age2010201120122013201420152016Change from 2010 to 2016
      Age 0–9
       Has usual source of care95.997.1
      Statistically significant change from the prior year at the 95% confidence interval.
      97.096.897.196.696.0+.1
       Had doctor/provider visit in past year86.184.885.985.987.7
      Statistically significant change from the prior year at the 95% confidence interval.
      87.985.9
      Statistically significant change from the prior year at the 95% confidence interval.
      −.2
       Needed but delayed care due to cost3.42.82.42.12.22.11.7−1.7
      Statistically significant change from 2010 to 2016 at the 95% confidence interval.
      Age 10–14
       Has usual source of care93.694.995.496.096.295.095.1+1.5
       Had doctor/provider visit in past year80.079.780.181.582.381.181.3+1.3
       Needed but delayed care due to cost4.43.83.32.6
      Statistically significant change from the prior year at the 95% confidence interval.
      2.72.22.4−2.0
      Statistically significant change from 2010 to 2016 at the 95% confidence interval.
      Age 15–18
       Has usual source of care89.892.2
      Statistically significant change from the prior year at the 95% confidence interval.
      91.589.592.6
      Statistically significant change from the prior year at the 95% confidence interval.
      91.690.4+.6
       Had doctor/provider visit in past year74.375.573.674.573.575.976.9+2.6
       Needed but delayed care due to cost5.24.44.14.43.53.43.2−2.0
      Statistically significant change from 2010 to 2016 at the 95% confidence interval.
      Age 19–25
       Has usual source of care67.670.569.069.473.7
      Statistically significant change from the prior year at the 95% confidence interval.
      72.674.6+7.0
      Statistically significant change from 2010 to 2016 at the 95% confidence interval.
       Had doctor/provider visit in past year50.652.450.853.157.4
      Statistically significant change from the prior year at the 95% confidence interval.
      53.7
      Statistically significant change from the prior year at the 95% confidence interval.
      56.0+5.4
      Statistically significant change from 2010 to 2016 at the 95% confidence interval.
       Needed but delayed care due to cost12.511.1
      Statistically significant change from the prior year at the 95% confidence interval.
      9.5
      Statistically significant change from the prior year at the 95% confidence interval.
      9.67.8
      Statistically significant change from the prior year at the 95% confidence interval.
      7.26.9−5.6
      Statistically significant change from 2010 to 2016 at the 95% confidence interval.
      Source: Author analysis of IPUMS Health Surveys: National Health Interview Survey, 2010–2016. Accessed through the Minnesota Population Center and State Health Access Data Assistance Center: Version 6.2. Minneapolis: University of Minnesota, 2016. Results presented are from bivariate analyses using z-tests of significance.
      a Statistically significant change from the prior year at the 95% confidence interval.
      b Statistically significant change from 2010 to 2016 at the 95% confidence interval.
      Access was incrementally worse for each older age group for all three indicators, with more young children and fewer young adolescents, older adolescents, and young adults having good access reported (Table 4). While few young children had delayed care due to costs and almost all had a usual care source and provider visit, this was true for fewer young adolescents, older adolescents, and especially young adults.
      The age gradient described above was confirmed for all three access measures in the regression analyses (see Table 5). Adolescents and young adults were significantly less likely than young children (reference group) to have reported access, and each age group had incrementally lower access than the group immediately younger. For example, young adults were about 18 percentage points less likely than older adolescents to have had a doctor visit in the past year, and older adolescents were over four percentage points less likely to have a doctor visit than young adolescents.
      Table 5Health Care Access Among Children, Adolescents, and Young Adults, 2010–2016: Estimates of Marginal Effects
      Variables(1)(2)(3)(4)(5)
      Estimate (percent points)Standard error (percent points)Lower bound (95% CI)Upper bound (95% CI)p value
      Usual source of care
      Age 10–14−1.73.19−2.10−1.35.000
      Age 15–18−4.48.25−4.97−3.98.000
      Age 19–25−19.70.43−20.50−18.90.000
      Year 20111.30.33.651.95.000
      Year 2012.56.39−.211.32.153
      Year 2013.42.40−.371.20.300
      Year 2014.85.41.041.66.039
      Year 2015−.37.41−1.18.44.373
      Year 2016−.44.42−1.26.39.303
      Observations112,095
      Doctor visit in past year
      Age 10–14−5.91.40−6.68−5.13.000
      Age 15–18−10.00.44−10.90−9.17.000
      Age 19–25−28.20.52−29.20−27.20.000
      Year 2011.23.58−.901.36.690
      Year 2012−.57.62−1.79.64.356
      Year 2013.23.62−.981.44.707
      Year 20141.33.65.052.61.041
      Year 2015.00.67−1.311.32.995
      Year 2016.19.74−1.261.64.797
      Observations111,645
      Delayed care due to cost
      Age 10–14.41.13.16.65.001
      Age 15–181.01.15.711.31.000
      Age 19–253.22.172.883.56.000
      Year 2011−.45.22−.89−.02.042
      Year 2012−1.01.23−1.47−.56.000
      Year 2013−1.12.23−1.58−.67.000
      Year 2014−1.23.23−1.69−.77.000
      Year 2015−1.22.23−1.68−.77.000
      Year 2016−1.43.26−1.93−.93.000
      Observations252,541
      Source: Author analysis of IPUMS Health Surveys: National Health Interview Survey, 2010–2016. Accessed through the Minnesota Population Center and State Health Access Data Assistance Center: Version 6.2. Minneapolis: University of Minnesota, 2016. Results presented are from logistic regression analyses using the margins command in Stata 14 (StataCorp).
      Marginal effects presented in percent point units.
      The reference groups were (1) children ages 0–9 and (2) year 2010.
      Other covariates were gender, race/ethnicity, percent of FPL, region, health status, activity limitation, and type of health insurance coverage. In addition, interaction terms between the age cohorts and years were included in the estimation.
      CI = confidence interval; FPL = Federal Poverty Level.
      For the full sample, the regression results show lower levels of delayed care in each year compared with 2010, whereas improvements in having a usual source of care and doctor visit relative to 2010 are only evident in 2011 (usual source of care) and 2014 (both measures). For all three measures of access, however, we observe no significant year-to-year fluctuations. In most cases, these overall trends did not vary by age group. There were a few exceptions, including a positive interaction term for young adolescents in 2016 for usual source of care, positive interaction terms for older adolescents in 2013 for delayed care due to cost and in 2016 for doctor visit, and positive interaction terms for young adults in 2013 and 2016 for delayed care due to cost and negative interaction terms for usual source of care in 2013 and 2014 (see Tables A2–A4 in the Appendix).

      Discussion

      This analysis demonstrates significant improvements in health insurance coverage and some gains in health-care access among children, adolescents, and young adults following ACA implementation between 2010 and 2016. While overall trends in coverage and access during this time frame were generally similar across the age groups, there was variation in the timing, type, and extent of changes in coverage and access among children, adolescents, and young adults. An increase in private coverage was first observed in 2011 for young adults (following the implementation of the young adult provision allowing young adults to stay on their parents' insurance through the age of 25) but also in public coverage in 2014 and 2016, suggesting an added impact of the Medicaid expansion for childless adults. Improvements in young adults' access to care correlated somewhat with coverage improvements, with increases in access rates observed particularly in 2014. In contrast, for children and adolescents, improvements in coverage rates were observed in 2014 and 2015 following the full implementation of Medicaid expansions and the implementation of coverage and premium subsidies available through federal and state marketplaces. Whereas the uninsurance rate for young adults dropped again in 2016, uninsurance stayed about the same for adolescents but increased for young children in 2016. Despite gains in public coverage between 2010 and 2016, both young and older adolescents experienced fewer rate increases in access to health care over time than young adults.
      Analyses of coverage and access often group adolescents with younger children, masking potentially important distinctions among individuals younger than 18 years of age. Generally speaking, we find very few age group differences in overall trends in coverage and access relative to 2010. Our analysis highlights, however, a persistent age gradient among adolescents, with incrementally worse coverage and access for young adolescents and older adolescents, peaking among young adults. Future reforms should consider the vulnerabilities of both adolescents and young adults. The gravity of these vulnerabilities is magnified when one considers that approximately 40% live below 200% of poverty, over a third live in the South, where 10 states have not expanded Medicaid [], and over 15% reported poor/fair/good health in 2016 (see Table 1).
      As youth age, transitions in their access to and type of coverage occur [
      • Ham J.C.
      • Xianghong L.
      • Shore-Sheppard L.D.
      The dynamics of children's health insurance, 1986–1999.
      ,
      • Fairlie R.W.
      • London R.A.
      The dynamics of health insurance coverage: Identifying trigger events for insurance loss and gain.
      ,
      • Adams S.H.
      • Newacheck P.W.
      • Park M.J.
      • et al.
      Health insurance across vulnerable ages: Patterns and disparities from adolescence to the early 30s.
      ,
      • Larson K.
      • Cull W.L.
      • Racine A.D.
      • Olson L.M.
      Trends in access to health services for US children: 2000–2014.
      ]. Changes in Medicaid eligibility, delays in CHIP reauthorization, and elimination of premium subsidies to purchase private health insurance will likely have an adverse impact on the age groups studied here. Putting in place mechanisms for identifying youth and young adults losing coverage and providing outreach with timely and affordable coverage options will be important to sustaining coverage gains.
      Attention to the age gradient in access to care is also warranted, including youth transitions from pediatric to adult health care. Given that young adults fare worse than adolescents on many health indicators [
      • Park M.J.
      • Scott J.T.
      • Adams S.H.
      • et al.
      Adolescent and young adult health in the United States in the past decade: Little improvement and young adults remain worse off than adolescents.
      ], the lack of connections to care is troubling. Despite a growing emphasis on continuity of care into adulthood, strategies to ensure a solid connection have been limited [
      • White P.
      • McManus M.
      Facilitating the transition from pediatric-oriented to adult-oriented primary care.
      ]. Expanded efforts are needed to ensure a planned transition to adult care starting in adolescence. This entails increasing self-care skills to prepare for adult care, assisting in the identification of adult providers, preparing and sharing current medical information for transfer, and facilitating integration into adult care [
      • Cooley W.C.
      • Sagerman P.J.
      American Academy of Pediatrics, American Academy of Family Physicians, and American College of Physicians, Transitions Clinical Report Authoring Group. Clinical report: Supporting the health care transition from adolescence to adulthood in the medical home.
      ].
      Finally, future studies examining health insurance coverage and access to health care should consider stratified analysis of children, adolescents, and young adults to monitor and design policy and practice strategies that reflect distinctive age group patterns among young people.

      Supplementary Data

      The following is the supplementary data to this article:

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      Linked Article

      • Using the Social-Ecological Model to Improve Access to Care for Adolescents and Young Adults
        Journal of Adolescent HealthVol. 62Issue 6
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          Spencer et al.'s analysis of National Health Interview Survey data between 2010 and 2016 highlights promising reductions in the number of uninsured adolescents and young adults, with pronounced declines in coverage over the course of adolescent development [1]. Insurance coverage is critically important for young people who need preventive services or face serious health issues. Recent Centers for Disease Control and Prevention data indicate that 17% of children and 21% of adolescents are obese, which is linked to chronic health effects such as diabetes, heart disease, and depression [2].
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