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. Author manuscript; available in PMC: 2019 Sep 14.
Published in final edited form as: N C Med J. 2019 Sep-Oct;80(5):269–275. doi: 10.18043/ncm.80.5.269

TABLE 2.

Health Care Access and Health Status, Adjusted

Health care access Above-poverty
% [95% CI]		 Traditional Medicaid
% [95% CI]		 Medicaid gap
%[95% CI]
No regular source of care 22.1%
[21.0%, 23.2%]		 19.3%
[17.4%,21.2%]		 48.0%^
[44.7%,51.4%]
Last check up more than a year ago 25.9%
[24.8%,27.0%]		 23.5%
[21.4%,25.7%]		 52.1%^
[48.6%,55.7%]
Could not see doctor due to cost 12.8%
[11.9%,13.6%]		 21.1%*
[19.1%,23.1%]		 50.2%^
[46.5%,53.9%]
Skipped Rx due to cost1 9.7%
[8.4%,10.9%]		 17.7%
[14.6%,20.7%]		 33.9%^
[28.4%,39.3%]
Preventive Care
Dental visit in previous year1 69.1%
[67.5%,70.7%]		 61.7%*
[58.5%,64.9%]		 37.7%^
[33.1%,42.2%]
Pap smear in past 3 years2 87.3%
[85.4%,89.3%]		 84.9%
[81.3%,88.5%]		 73.4%^
[67.2%,79.6%]
Cholesterol check in past 5 years1 84.0%
[82.6%,85.5%]		 83.4%
[80.8%,86.0%]		 66.1%^
[61.5%,70.8%]
Flu shot in previous year 42.6%
[41.3%,43.8%]		 43.0%
[40.4%,45.7%]		 25.7%^
[22.7%,28.8%]
Ever had HIV test 49.1%
[47.8%,50.3%]		 52.0%
[49.3%,54.8%]		 53.2%
[49.6%,56.9%]
Health Status
Functional disability 15.7%
[14.8%,16.6%]		 38.0%*
[35.7%,40.3%]		 34.4%*
[31.2%,37.6%]
Multiple chronic conditions 17.3%
[16.5%,18.2%]		 35.0%*
[32.7%,37.2%]		 27.1%^
[24.0%,30.2%]
Health status fair/poor 10.9%
[10.2%,11.7%]		 29.5%*
[27.4%,31.6%]		 29.9%*
[26.9%,32.9%]
Current smoker 18.5%
[17.5%,19.5%]		 27.8%*
[25.6%,30.0%]		 29.8%*
[26.7%,32.8%]
Binge drinking 17.6%
[16.6%,18.6%]		 12.7%*
[10.9%,14.5%]		 14.5%
[11.9%,17.1%]
Healthy Days
Days in poor physical health 2.7
[2.6,2.9]		 6.2*
[5.6,6.7]		 5.7*
[4.9,6.6]
Days in poor mental health 3.2
[3.1,3.4]		 5.9*
[5.4,6.3]		 5.9*
[5.2,6.6]
Days when poor health kept you from your regular activities 1.8
[1.6,1.9]		 4.6*
[4.1,5.1]		 4.1*
[3.5,4.8]

Note. HIV – Human Immunodeficiency Virus; CI – confidence interval

*

Significantly different from above-poverty

+

Significantly different from both above-poverty and traditional Medicaid

Estimates are from logistic regression models (access, prevention, and health status variables) or negative binomial regression models (healthy days) adjusted for age, gender, race, ethnicity, having dependent children, education, and marital status

1

Data only available for 2 years

2

Only includes females, data only available for 2 years