The Multivariate Analysis of Factors Affecting Hospitalization Among Veterans at VHA Primary Care Clinics Across the United States and in King County, WA in 2015
| Variables | Odds Ratio; P-Value (95% CI) | |||||||
|---|---|---|---|---|---|---|---|---|
| United States | King County, WA | |||||||
| Model 1 | Model 2 | Model 3 | Model 4 | Model 1 | Model 2 | Model 3 | Model 4 | |
| Age, Years | 1.003; <.001 (1.003 to 1.0031) | 1.003; <.001 (1.002 to 1.0034) | 1.003; <.001 (1.003 to 1.0034) | 1.003; <.001 (1.003 to 1.0034) | 1.02; <.001 (1.01 to 1.028) | 1.02; <.001 (1.01 to 1.026) | 1.02; <.001 (1.01 to 1.029) | 1.05; <.001 (1.01 to 1.02) |
| Sex, female as reference | 1.17; <.001 (1.15 to 1.18) | 1.16; <.001 (1.14 to 1.18) | 1.16; <.001 (1.15 to 1.18) | 1.17; <.001 (1.15 to 1.18) | 1.18;.13 (0.95 to 1.47) | 1.18; .13 (0.95 to 1.47) | 1.17; .14 (0.95 to 1.46) | 1.18; .13 (0.95 to 1.46) |
| Reported race, non-white as reference | 0.85; <.001 (0.84 to 0.853) | 0.85; <.001 (0.84 to 0.86) | 0.85; <.001 (0.84 to 0.854) | 0.84; <.001 (0.83 to 0.85) | 0.91; .13 (0.81 to 1.03) | 0.91; .13 (0.81 to 1.03) | 0.91; .12 (0.81 to 1.03) | 0.92; .18 (0.82 to 1.04) |
| Gagne Comorbidity Score*, 0/ below 0 as Reference | 3.33; <.001 (3.30 to 3.35) | 3.33; <.001 (3.30 to 3.35) | 3.33; <.001 (3.30 to 3.35) | 3.33; <.001 (3.30 to 3.35) | 3.71; <.001 (3.33 to 4.14) | 3.72; <.001 (3.33 to 4.15) | 3.71; <.001 (3.20 to 4.14) | 3.69; <.001 (3.30 to 4.12) |
| NSES Index† | ||||||||
| 1st quartile as reference | ||||||||
| 2nd Quartile | 0.82; <.001 (0.81 to 0.83) | 0.81; <.001 (0.80 to 0.82) | 0.80; <.001 (0.79 to 0.81) | 0.80; <.001 (0.79 to 0.81) | 0.99; .95 (0.84 to 1.18) | 0.96; .67 (0.81 to 1.14) | 1.005; .94 (0.85 to 1.20) | 1.04; .64 (0.87 to 1.24) |
| 3rd Quartile | 0.74; <.001 (0.73 to 0.75) | 0.73; <.001 (0.72 to 0.735) | 0.71; <.001 (0.70 to 0.72) | 0.71; <.001 (0.70 to 0.72) | 0.89; .29 (0.74 to 1.06) | 0.84; <.05 (0.71 to 1.10) | 0.85; .84 (0.72 to 1.02) | 0.89; .21 (0.75 to 1.07) |
| 4th Quartile | 0.67; <.001 (0.66 to 0.68) | 0.66; <.001 (0.65 to 0.664) | 0.63; <.001 (0.631 to 0.64) | 0.63; <.001 (0.629 to 0.64) | 0.71; <.001 (0.59 to 0.85) | 0.65; <.001 (0.55 to 0.77) | 0.68; <.001 (0.58 to 0.81) | 0.70; <.001 (0.59 to 0.82) |
| Housing issues | ||||||||
| Housing instability‡ | 1.01; <.001 (1.00 to 1.012) | 1.01; <.001 (1.00 to 1.03) | ||||||
| Home vacancy rate§ | 1.07; <.001 (1.01 to 1.017) | 0.99; .73 (0.97 to 1.02) | ||||||
| Characteristics of the house | ||||||||
| Percentage of houses with no plumbing | 1.00; <.01 (1.001 to 1.008) | 1.07; <.05 (1.02 to 1.11) | ||||||
| Percentage of houses with no heating | 0.99; <.001 (0.98 to 0.992) | 1.10; <.05 (1.05 to 1.15) | ||||||
| QIC‖ | 2464233 | 2464261 | 2464533 | 2463986 | 9956.717 | 9960.148 | 9951.153 | 9943.414 |
↵* Gagne comorbidity score was presented as a binary variable (above 0 vs. 0 and below 0) in the GEE model.
↵† The NSES index was a summary measure of six geographic-level census-based variables linked to the census tract of a participant's residence. The higher values corresponded to higher socioeconomic status.
↵‡ Percentage of households that moved across census tracts in the past year and had an income below 100% poverty line.
↵§ Percentage of vacant houses in each census tract.
↵‖ The QIC (Quasi likelihood under the Independence model Criterion) statistic is analogous to the AIC (Akaike's Information Criterion) statistic used for comparing models fit with likelihood-based methods. Since the GEE method is not a likelihood-based method, the AIC statistic is not available. Smaller QIC value presents a better model.
Model 1. GEE Model—Patient-level characteristics, NSES index, housing instability.
Model 2. GEE Model—Patient-level characteristics, NSES index, home vacancy rate.
Model 3. GEE Model—Patient-level characteristics, NSES index, percentage of of houses with no plumbing.
Model 3. GEE Model—Patient-level characteristics, NSES index, percentage of of houses with no heating.
GEE, Generalized Estimating Equation; NSES, neighborhood socioeconomic status; VHA, Veterans Health Administration.