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. Author manuscript; available in PMC: 2016 Jun 23.
Published in final edited form as: Pediatrics. 2013 Nov 18;132(6):e1584–e1591. doi: 10.1542/peds.2013-1470

TABLE 3.

Factors Associated With Being Uninsured Compared With Medicaid/Medicare and Commercial Insurance, Among Children Seen at a CHC in the OCHIN Network (January 1, 2010–December 31, 2011)

Covariates Medicaid/Medicare Commercial


Unadjusted Odds of
Being Uninsured
P Adjusted Odds of
Being Uninsured
P Unadjusted Odds of
Being Uninsured
P Adjusted Odds of
Being Uninsured
P
Gender
  Boy 1.00 1.00 1.00 1.00
  Girl 1.07 (1.05–1.09) <.001 0.98 (0.96–1.00) .073 0.97 (0.94–1.00) .088 0.98 (0.95–1.01) .201
Age, y
  0–14 1.00 1.00 1.00 1.00
  15–18 2.21 (2.16–2.26) <.001 1.87 (1.82–1.92) <.001 0.82 (0.79–0.84) <.001 0.81 (0.78–0.84) <.001
Race/ethnicity
  White, Non-Hispanic 1.00 1.00 1.00 1.00
  Nonwhite and/or Hispanic 0.57 (0.55–0.58) <.001 0.73 (0.71–0.75) <.001 3.00 (2.90–3.09) <.001 1.50 (1.44–1.56) <.001
  Missing 0.83 (0.79–0.87) <.001 0.84 (0.80–0.89) <.001 1.54 (1.44–1.65) <.001 1.19 (1.11–1.28) <.001
Language
  English 1.00 1.00 1.00 1.00
  Other than English 0.66 (0.65–0.68) <.001 0.96 (0.93–0.99) .003 3.75 (3.61–3.90) <.001 1.87 (1.78–1.96) <.001
  Missing 4.37 (4.20–4.55) <.001 4.04 (3.86–4.22) <.001 1.94 (1.85–2.04) <.001 1.22 (1.16–1.28) <.001
Income
  >100% federal poverty level 1.00 1.00 1.00 1.00
  At or below 100% federal poverty level 0.94 (0.92–0.96) <.001 0.87 (0.85–0.89) <.001 1.60 (1.55–1.66) <.001 1.62 (1.56–1.68) <.001
  Missing 0.69 (0.67–0.71) <.001 0.84 (0.82–0.86) <.001 1.06 (1.02–1.10) .002 1.08 (1.04–1.12) <.001
Location
  Urban 1.00 1.00 1.00 1.00
  Rural 0.93 (0.90–0.95) <.001 0.89 (0.87 –0.92) <.001 0.16 (0.16–0.17) <.001 0.22 (0.21–0.23) <.001
Clinic type
  Primary care clinic 1.00 1.00 1.00 1.00
  School-based health center 3.91 (3.80–4.04) <.001 3.39 (3.28–3.50) <.001 1.23 (1.19–1.29) <.001 1.06 (1.01–1.10) .011

Adjusted odds ratios are based on multivariable generalized estimating equation logistic regression models accounting for visits nested in children and children nested in clinics. Multivariable models were adjusted for gender, age, race, ethnicity, language, income, rural/urban health center location, and clinic type.