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Supplemental Digital Content 2. Logistic regression models for odds of seeking health information PredictorBivariable Analysis (n = 996)OR [95% CI]Multivariable Analysis (n = 968)OR [95% CI]Age §18-35 years 0.66 [0.40, 1.09]0.26 [0.13, 0.53] ?36-49 years 0.76 [0.45, 1.29]0.37 [0.19, 0.73] ?50-64 years0.70 [0.43, 1.15]0.39 [0.21, 0.72] ?Female1.30 [0.95, 1.79] ??1.24 [0.88, 1.76]Race/ethnicity §Black0.48 [0.18, 1.29]0.42 [0.15, 1.19]Hispanic0.53 [0.20, 1.39]0.47 [0.16, 1.42]Asian0.55 [0.21, 1.46]0.45 [0.13, 1.62]Other0.40 [0.13, 1.22]0.34 [0.10, 1.13]Language §Spanish0.86 [0.59, 1.26]0.81 [0.43, 1.56]Chinese0.94 [0.64, 1.39]0.93 [0.38, 2.27]English proficient1.18 [0.85, 1.63]1.06 [0.63, 1.77]Education §High school graduate / equivalent1.10 [0.74, 1.64]1.09 [0.69, 1.73]Some college / vocational training1.67 [1.08, 2.57] ?1.49 [0.87, 2.54]College grad2.77 [1.59, 4.80] ?2.32 [1.17, 4.61] ?Household Income §10 to <20K1.26 [0.85, 1.86]1.14 [0.74, 1.75]20 to <35K1.52 [0.89, 2.61]1.27 [0.70, 2.28]35 to <50K1.70 [0.98, 2.97] ??1.19 [0.65, 2.18]50K1.83 [1.10, 3.04] ?1.18 [0.64, 2.17]US-born0.93 [0.69, 1.29]--Health literate1.62 [1.18, 2.23] ?1.33 [0.93, 1.91]Smartphone owner1.94 [1.38, 2.74] ?2.13 [1.38, 3.28] ?At least good health status1.34 [0.98, 1.88] ??1.18 [0.81, 1.71]At least one usual source of care1.91 [1.29, 2.82] ?1.59 [1.03, 2.45] ?English proficient * US-born ?----English proficient * Spanish ? ----English proficient * Chinese ?----English proficient * HS grad ?----English proficient * Some college ?----English proficient * College grad ?----? p < 0.05?? p < 0.10, therefore included in multivariable model§ The reference group for each variable is: age (65+ years); race/ethnicity (non-Hispanic White); language (English); education (less than high school graduate); and household income (<$10000)? An interaction term. None were significant in this model and therefore not included.Notes: Odds ratios (OR) and confidence intervals (CI) are only reported in the multivariable logistic regression for variables included in the model. ................
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