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. 2021 Mar 8;36(5):1292–1301. doi: 10.1007/s11606-021-06674-z

Table 4.

Relationship Between EQ-5D Utility Score and Select Respondent Characteristics, Estimated by OLS Regression Following Lasso

Predictor Estimate* Lower 97.5% CI* Upper 97.5% CI* Std. error* E-value E-value 95% CL
(Intercept) 0.851 0.709 0.975 0.059 66.702 41.220
Gender, male (Reference) (Reference) (Reference) (Reference) (Reference) (Reference)
Gender, female 0.002 −0.018 0.021 0.009 1.100 1.000
Gender, prefer not to say −0.082 −0.186 0.030 0.048 2.155 1.000
Gender, other −0.190 −0.445 0.083 0.118 3.808 1.000
Age group, 18–24 (Reference) (Reference) (Reference) (Reference) (Reference) (Reference)
Age group, 25–34 0.060 0.015 0.108 0.021 1.881 1.378
Age group, 35–44 0.071 0.025 0.120 0.021 2.017 1.517
Age group, 45–54 0.055 0.004 0.109 0.023 1.821 1.252
Age group, 55–64 0.066 0.019 0.117 0.022 1.955 1.430
Age group, ≥65 0.092 0.034 0.147 0.025 2.284 1.677
Race, White (Reference) (Reference) (Reference) (Reference) (Reference) (Reference)
Race, American Indian or Alaska Native 0.099 0.013 0.190 0.040 2.377 1.402
Race, Asian 0.025 −0.013 0.063 0.017 1.456 1.000
Race, Black or African American −0.016 −0.060 0.026 0.019 1.338 1.000
Race, multiple-race −0.030 −0.081 0.027 0.024 1.518 1.000
Race, Native Hawaiian or Other Pacific Islander −0.157 −0.520 0.217 0.164 3.234 1.000
Race, other 0.049 −0.042 0.132 0.039 1.748 1.000
Race, prefer not to say 0.068 −0.026 0.165 0.042 1.980 1.000
Hispanic ethnicity, no (Reference) (Reference) (Reference) (Reference) (Reference) (Reference)
Hispanic ethnicity, prefer not to say 0.013 −0.064 0.092 0.035 1.296 1.000
Hispanic ethnicity, yes −0.043 −0.081 0.001 0.018 1.676 1.216
Marital status, single (Reference) (Reference) (Reference) (Reference) (Reference) (Reference)
Marital status, divorced −0.008 −0.045 0.030 0.017 1.220 1.000
Marital status, married −0.044 −0.072 −0.017 0.012 1.688 1.399
Marital status, prefer not to say 0.018 −0.097 0.117 0.048 1.365 1.000
Marital status, separated −0.020 −0.145 0.098 0.054 1.392 1.000
Marital status, widowed 0.001 −0.057 0.062 0.026 1.069 1.000
Annual income, less than $20,000 (Reference) (Reference) (Reference) (Reference) (Reference) (Reference)
Annual income, $20,000 to $34,999 0.021 −0.020 0.064 0.019 1.405 1.000
Annual income, $35,000 to $49,999 0.024 −0.017 0.066 0.018 1.443 1.000
Annual income, $50,000 to $74,999 0.065 0.031 0.105 0.017 1.943 1.540
Annual income, $75,000 to $99,999 0.058 0.017 0.102 0.019 1.857 1.403
Annual income, $100,000 to $149,999 0.072 0.033 0.115 0.018 2.029 1.601
Annual income, over $150,000 0.115 0.076 0.162 0.019 2.597 2.102
Education, less than high school degree (Reference) (Reference) (Reference) (Reference) (Reference) (Reference)
Education, high school degree or equivalent (e.g., GED) 0.042 −0.082 0.180 0.058 1.664 1.000
Education, some college but no degree 0.026 −0.097 0.165 0.058 1.469 1.000
Education, associate degree 0.041 −0.088 0.175 0.059 1.652 1.000
Education, bachelor degree 0.014 −0.108 0.149 0.057 1.311 1.000
Education, graduate degree 0.024 −0.098 0.160 0.058 1.443 1.000
Live alone −0.035 −0.062 −0.007 0.012 1.579 1.275
Experienced COVID-19-like symptoms not serious enough to require hospitalization −0.023 −0.055 0.013 0.015 1.431 1.000
Has a family member diagnosed with COVID-19 −0.080 −0.145 −0.023 0.027 2.130 1.483
Knows someone with a COVID-19 diagnosis −0.005 −0.033 0.020 0.012 1.167 1.000
Fear of COVID-19’s impact on health (1–10 scale) −0.010 −0.013 −0.006 0.002 1.252 1.187
Fear of COVID-19’s impact on finances (1–10 scale) −0.002 −0.005 0.002 0.002 1.100 1.000
Arthritis −0.115 −0.151 −0.077 0.017 2.597 2.152
Diabetes −0.081 −0.126 −0.036 0.020 2.142 1.663
Depression −0.122 −0.147 −0.097 0.011 2.696 2.397
Fear of COVID-19’s impact on health (1–10 scale) * stroke −0.034 −0.062 −0.008 0.012 1.567 1.260
BMI category, underweight * California −0.263 −0.415 −0.109 0.068 5.375 2.813

Abbreviations: OLS ordinary least squares, CI confidence interval, CL confidence limit, BMI body mass index, COVID-19 Coronavirus disease 2019

*The coefficients given by this (post-lasso) OLS regression were bootstrapped to estimate standard errors, computed as the standard deviation of the bootstrap replicates. The standard errors were then used to construct Bonferroni-corrected normal-theory confidence intervals for the regression coefficients. In this table, we report the median bootstrap estimates as the model point estimates alongside the normal-theory bootstrap intervals