Research ArticleOriginal Research

The Association Between Neighborhood Socioeconomic and Housing Characteristics with Hospitalization: Results of a National Study of Veterans

Elham Hatef, Hadi Kharrazi, Karin Nelson, Philip Sylling, Xiaomeng Ma, Elyse C. Lasser, Kelly M. Searle, Zachary Predmore, Adam J. Batten, Idamay Curtis, Stephan Fihn and Jonathan P. Weiner
The Journal of the American Board of Family Medicine November 2019, 32 (6) 890-903; DOI: https://doi.org/10.3122/jabfm.2019.06.190138

Article Figures & Data

Figures

  • Figure 1.
    Figure 1.

    Spatial analysis for Hospitalization and NSES Index. Map a: Unadjusted hospitalization rate and Map b: NSES mean per census tract in King County, WA. NSES: neighborhood socioeconomic status.

  • Figure 2.
    Figure 2.
    Figure 2.

    Spatial analysis for housing issues. Maps for (a) housing instability rate; (b) home vacancy rate; (c) percent of houses with no plumbing; (d) percentage of houses with no fuel-based heating.

Tables

  • Table 1.

    The Descriptive Analysis of Factors Affecting Hospitalization Among Veterans at VHA Primary Care Clinics Across the United States and in King County, WA in 2015*

    HospitalizationUnited StatesKing County, WA
    YesNoYesNo
    Number of Patients (%)360,527 (6.63)5,080,516 (93.38)1087 (5.84)17022 (91.47)
    Age, Mean (SD)64.46 (13.86)62.7 (16.50)63.69 (14.03)58.83 (17.21)
    Sex, (%)336,617 (93.40)4,681,449 (92.15)1,003 (92.27)15,545 (91.32)
    Race, (%)246,558 (68.39)3,695,482 (72.74)749 (69.42)12156 (72.33)
    Gagne Comorbidity Score, Mean (SD)2.07 (2.07)0.33 (1.24)1.25 (1.95)0.34 (1.14)
    NSES index†, Mean (SD)0.67 (0.11)0.69 (0.10)0.72 (0.08)0.74 (0.08)
    Housing issues (Median, Range)
        Housing instability‡2.55 (0.00, 100.00)2.90 (0.00, 41.89)
        Home vacancy rate§3.34 (0.00, 100.00)1.77 (0.00, 9.56)
        Characteristics of the House
            Percentage of houses with no plumbing0.00 (0.00, 62.71)0.00 (0.00, 6.74)
            Percentage of houses with no heating0.00 (0.00, 95.28)0.00 (0.00, 16.67)

    • SD, standard deviation.

    • ↵* The demographic data had a high completeness rate with less than 1% of data missing among the entire veteran population. Percentages might not add to 100% due to rounding and the missing data.

    • ↵† The NSES index was a summary measure of six geographic-level census-based variables that 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.

    • NSES, Neighborhood Socio-economic Status, VHA, Veterans Health Administration.

  • Table 2.

    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

    VariablesOdds Ratio; P-Value (95% CI)
    United StatesKing County, WA
    Model 1Model 2Model 3Model 1Model 2Model 3
    Age, years1.0032; <.001 (1.003 to 1.0034)1.0032; <.001 (1.003 to 1.0035)1.02; <.001 (1.01 to 1.026)1.02; <.001 (1.01 to 1.029)
    Sex, female as reference1.17; <.001 (1.15 to 1.18)1.16; <.001 (1.15 to 1.18)1.18; .13 (0.95 to 1.47)1.17; .15 (0.94 to 1.46)
    Reported Race, non-white as reference0.85; <.001 (0.84 to 0.853)0.84; <.001 (0.83 to 0.85)0.91; .13 (0.81 to 1.03)0.92; .17 (0.81 to 1.04)
    Gagne Comorbidity Score*, 0/ below 0 as Reference3.33; <.001 (3.31 to 3.35)3.32; <.001 (3.30 to 3.35)3.72; <.001 (3.34 to 4.15)3.68; <.001 (3.30 to 4.11)
    NSES Index†
        1st Quartile as reference
        2nd Quartile0.80; <.001 (0.79 to 0.81)0.83; <.001 (0.82 to 0.84)0.96; 0.66 (0.81 to 1.14)1.06; 0.49 (0.89 to 1.27)
        3rd Quartile0.71; <.001 (0.70 to 0.72)0.75; <.001 (0.74 to 0.76)0.84; .05 (0.70 to 0.99)0.90; .27 (0.75 to 1.08)
        4th Quartile0.64; <.001 (0.63 to 0.643)0.69; <.001 (0.68 to 0.70)0.65; <.001 (0.55 to 0.77)0.71; <.001 (0.59 to 0.86)
    Housing issues
        Housing instability‡1.03; <.001 (1.027 to 1.029)1.01; <.001 (1.007 to 1.014)1.02; <.001 (1.00 to 1.03)1.0003; .96 (0.99 to 1.01)
        Home vacancy rate§1.02; <.001 (1.018 to 1.020)1.01; <.001 (1.005 to 1.017)1.003; .085 (0.97 to 1.03)0.99; .52 (0.96 to 1.02)
        Characteristics of the house
        Percentage of houses with no plumbing1.01; <.001 (1.010 to 1.015)1.004; <.01 (1.001 to 1.007)1.06; <.05 (1.01 to 1.11)1.05; .05 (0.99 to 1.10)
        Percentage of houses with no heating0.991; <.001 (0.99 to 0.992)0.99; <.001 (0.98 to 0.996)1.08; <.05 (1.03 to 1.13)1.09; <.001 (1.04 to 1.14)
    QIC‖26105272464538246344510813.39958.2489945.153

    • ↵* 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 or 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—housing characteristics only.

    • Model 2. GEE Model—patient-level characteristics and NSES index.

    • Model 3. GEE Model—patient-level characteristics, NSES index, housing issues.

    • GEE, Generalized Estimating Equation; NSES, neighborhood socio-economic status; QIC, quasi likelihood under the Independence Model Criterion; VHA, Veterans Health Administration; CI, confidence interval.

  • Appendix Table 1.

    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

    VariablesOdds Ratio; P-Value (95% CI)
    United StatesKing County, WA
    Model 1Model 2Model 3Model 4Model 1Model 2Model 3Model 4
    Age, Years1.003; <.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 reference1.17; <.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 reference0.85; <.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 Reference3.33; <.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 Quartile0.82; <.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 Quartile0.74; <.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 Quartile0.67; <.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 plumbing1.00; <.01 (1.001 to 1.008)1.07; <.05 (1.02 to 1.11)
        Percentage of houses with no heating0.99; <.001 (0.98 to 0.992)1.10; <.05 (1.05 to 1.15)
    QIC‖24642332464261246453324639869956.7179960.1489951.1539943.414

    • ↵* 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.

  • Appendix Table 2.

    Variance Inflation Factor Presented for 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

    VariablesVariance Inflation Factor* (Degree of Freedom)
    United StatesKing County, WA
    Model 1Model 2Model 1Model 2
    Age1.068765 (1)1.071784 (1)1.068765 (1)1.071784 (1)
    Sex1.032169 (1)1.032579 (1)1.032169 (1)1.032579 (1)
    Reported Race1.053327 (1)1.055482 (1)1.053327 (1)1.055482 (1)
    Gagne Comorbidity Score1.014003 (1)1.015308 (1)1.014003 (1)1.015308 (1)
    NSES Index1.036799 (3)1.438241 (3)1.036799 (3)1.438241 (3)
    Housing Issues
        Housing Instability1.582049 (1)1.582049 (1)
        Home Vacancy Rate1.025891 (1)1.025891 (1)
        Characteristics of the House
        Percentage of houses with no plumbing1.253458 (1)1.253458 (1)
        Percentage of houses with no heating1.248236 (1)1.248236 (1)

    • ↵* Variance Inflation Factor close to 1 presents least collinearity among variables in a model.

    • Model 1. GEE Model—Patient-level characteristics and NSES index.

    • Model 2. GEE Model—Patient-level characteristics, NSES index, and housing issues.

    • NSES, Neighborhood socioeconomic status; VHA, Veterans Health Administration.

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