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Brief ReportBrief Report

Associations of Race, Insurance, and Zip Code-Level Income with Nonadherence Diagnoses in Primary and Specialty Diabetes Care

Sourik Beltrán, Daniel J. Arenas, Itzel J. López-Hinojosa, Elizabeth L. Tung and Peter F. Cronholm
The Journal of the American Board of Family Medicine September 2021, 34 (5) 891-897; DOI: https://doi.org/10.3122/jabfm.2021.05.200639
Sourik Beltrán
From the Department of Medicine, Massachusetts General Hospital, Boston, MA (SB); Perelman School of Medicine, University of Pennsylvania Philadelphia, PA (DJA); Department of Medical Ethics and Health Policy, University of Pennsylvania (SB); Pritzker School of Medicine, University of Chicago, Chicago, IL (IJLH); Department of Medicine, Section of General Internal Medicine, University of Chicago (ELT); Chicago Center for Diabetes Translation Research, University of Chicago (ELT); Department of Family Medicine and Community Health, University of Pennsylvania (PFC); Center for Public Health Initiatives, University of Pennsylvania (PFC); Leonard Davis Institute of Health Economics, University of Pennsylvania (PFC).
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Daniel J. Arenas
From the Department of Medicine, Massachusetts General Hospital, Boston, MA (SB); Perelman School of Medicine, University of Pennsylvania Philadelphia, PA (DJA); Department of Medical Ethics and Health Policy, University of Pennsylvania (SB); Pritzker School of Medicine, University of Chicago, Chicago, IL (IJLH); Department of Medicine, Section of General Internal Medicine, University of Chicago (ELT); Chicago Center for Diabetes Translation Research, University of Chicago (ELT); Department of Family Medicine and Community Health, University of Pennsylvania (PFC); Center for Public Health Initiatives, University of Pennsylvania (PFC); Leonard Davis Institute of Health Economics, University of Pennsylvania (PFC).
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Itzel J. López-Hinojosa
From the Department of Medicine, Massachusetts General Hospital, Boston, MA (SB); Perelman School of Medicine, University of Pennsylvania Philadelphia, PA (DJA); Department of Medical Ethics and Health Policy, University of Pennsylvania (SB); Pritzker School of Medicine, University of Chicago, Chicago, IL (IJLH); Department of Medicine, Section of General Internal Medicine, University of Chicago (ELT); Chicago Center for Diabetes Translation Research, University of Chicago (ELT); Department of Family Medicine and Community Health, University of Pennsylvania (PFC); Center for Public Health Initiatives, University of Pennsylvania (PFC); Leonard Davis Institute of Health Economics, University of Pennsylvania (PFC).
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Elizabeth L. Tung
From the Department of Medicine, Massachusetts General Hospital, Boston, MA (SB); Perelman School of Medicine, University of Pennsylvania Philadelphia, PA (DJA); Department of Medical Ethics and Health Policy, University of Pennsylvania (SB); Pritzker School of Medicine, University of Chicago, Chicago, IL (IJLH); Department of Medicine, Section of General Internal Medicine, University of Chicago (ELT); Chicago Center for Diabetes Translation Research, University of Chicago (ELT); Department of Family Medicine and Community Health, University of Pennsylvania (PFC); Center for Public Health Initiatives, University of Pennsylvania (PFC); Leonard Davis Institute of Health Economics, University of Pennsylvania (PFC).
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Peter F. Cronholm
From the Department of Medicine, Massachusetts General Hospital, Boston, MA (SB); Perelman School of Medicine, University of Pennsylvania Philadelphia, PA (DJA); Department of Medical Ethics and Health Policy, University of Pennsylvania (SB); Pritzker School of Medicine, University of Chicago, Chicago, IL (IJLH); Department of Medicine, Section of General Internal Medicine, University of Chicago (ELT); Chicago Center for Diabetes Translation Research, University of Chicago (ELT); Department of Family Medicine and Community Health, University of Pennsylvania (PFC); Center for Public Health Initiatives, University of Pennsylvania (PFC); Leonard Davis Institute of Health Economics, University of Pennsylvania (PFC).
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  • Appendix Figure 1.
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    Appendix Figure 1.

    Flowchart demonstrating subject counts for inclusion and exclusion from study.

Tables

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    Table 1.

    Sample Characteristics with Crude Risk Ratios (RRs) for Nonadherence Labeling

    Overall (N = 6072)Labeled (N = 759)Non-Labeled (N = 5313)
    VariableMedian [IQR]Median [IQR]Median [IQR]β [95% CI]P value
    Age, years57 [49, 63]56 [48, 62]57 [49, 63]−0.0013 [−0.0021, −0.0005].001
    HbA1c, %7.5 [6.6, 9.1]8.3 [6.8, 10.0]7.5 [6.5, 8.9]0.019 [0.015, 0.023]<.001
    BMI, kg/m232.3 [27.8, 37.9]32.5 [27.5, 38.9]32.3 [27.8, 37.8]0.0007 [−0.0003, 0.002].53
    n (%)n (%)n (%)RR [95% CI]P value
    Biological sex
        Male2909 (47.9)333 (43.8)2576 (48.4)RefRef
        Female3163 (52.1)426 (56.1)2737 (51.5)1.17 [1.03, 1.35].017
    Race
        White1941 (31.9)106 (14.0)1835 (34.5)RefRef
        Black3753 (61.8)623 (82.1)3130 (58.9)3.04 [2.49, 3.71]<.001
        Asian229 (3.8)10 (1.3)219 (4.1)0.80 [0.42, 1.51].49
    Ethnicity
        Non-Hispanic5906 (97.3)739 (97.4)5167 (97.3)RefRef
        Hispanic166 (2.7)20 (2.6)146 (2.7)0.96 [0.63, 1.46].85
    Insurance payor
        Private3536 (58.2)335 (44.1)3201 (60.2)RefRef
        Medicaid1082 (17.8)222 (29.2)860 (16.2)2.17 [1.85, 2.52]<.001
        Medicare1454 (23.9)202 (26.6)1252 (23.6)1.44 [1.23, 1.70]<.001
    Care site
        Primary care2657 (43.8)376 (49.5)2281 (42.9)RefRef
        Specialty care3415 (56.2)383 (50.5)3032 (57.1)0.79 [0.69, 0.91]<.001
    • BMI, body mass index; CI, confidence interval; HbA1c, hemoglobin A1C; IQR, interquartile range.

    • View popup
    Table 2.

    Adjusted Risk Ratios (ARRs) for Nonadherence Labeling by Demographics in HbA1c and Care Site Strata*

    VariableOverall (N = 6072) (Labeled = 759)Subgroup HbA1c ≤7% (N = 2349) (Labeled = 222)Subgroup HbA1c >7% (N = 3723) (Labeled = 537)Subgroup Primary Care (N = 2657) (Labeled = 376)Subgroup Specialty Care(N = 3415) (Labeled = 383)
    βadj [95% CI]βadj [95% CI]βadj [95% CI]βadj [95% CI]βadj [95% CI]
    Age−0.006 [−0.014, 0.002]−0.014 [−0.029, 0.001]−0.025 [−0.012, 0.007]0.009 [−0.0035, 0.020]−0.019 [−0.030, −0.008]
    HbA1c0.11 [0.08, 0.15]−0.14 [−0.43, 0.17]0.11 [0.05, 0.16]0.09 [0.04, 0.14]0.14 [0.087, 0.19]
    BMI−0.0027 [−0.0126, 0.007]0.074 [−0.010, 0.024]−0.008 [−0.02, 0.003]−0.002 [−0.016, 0.011]−0.002 [−0.016, 0.012]
    ARR [95% CI]ARR [95% CI]ARR [95% CI]ARR [95% CI]ARR [95% CI]
    Biological sex
        MaleRefRefRefRefRef
        Female1.02 [0.87, 1.18]0.93 [0.73, 1.19]1.06 [0.88, 1.28]1.05 [0.83, 1.30]0.98 [0.78, 1.20]
    Race
        WhiteRefRefRefRefRef
        Black2.48 [2.01, 3.04]2.87 [1.94, 4.27]2.16 [1.72, 2.76]2.56 [1.66, 3.97]2.45 [1.90, 3.16]
        Asian0.75 [0.33, 1.26]1.39 [0.31, 2.85]0.53 [0.11, 1.05]0.23 [0.00, 0.84]1.07 [0.42, 1.84]
    Ethnicity
        Non-HispanicRefRefRefRefRef
        Hispanic1.22 [0.71, 1.83]1.14 [0.25, 2.19]1.24 [0.62, 1.99]1.21 [0.31, 2.55]1.27 [0.64, 2.03]
    Insurance payor
        PrivateRefRefRefRefRef
        Medicaid1.82 [1.50, 2.18]1.75 [1.23, 2.40]1.83 [1.46 2.26]2.16 [1.66, 2.76]1.50 [1.11, 1.97]
        Medicare1.61[1.32, 1.93]1.68 [1.19, 2.31]1.55 [1.21, 1.95]1.41 [1.02, 1.90]1.74 [1.34, 2.21]
    Care site
        Primary careRefRefRefNot applicableNot applicable
        Specialty care1.00 [0.85, 1.16]0.91 [0.69, 1.17]1.04 [0.86, 1.24]Not applicableNot applicable
    • BMI, body mass index; CI, confidence interval; HbA1c, hemoglobin A1C.

    • ↵* ARRs for categorical variables, and beta coefficients for continuous variables, were calculated with a logistic regression model using all the following potentially confounding variables: age, sex, race, BMI, ethnicity, insurance status, and HbA1c. Additional calculations using the adjusted odd ratio are presented in the supplementary document (S1.5); no changes in significance were observed across the 2 model choices.

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    Table 3.

    Adjusted Risk Ratios (ARRs) for Nonadherence Labeling by Demographics in HbA1c and Care Site Strata with Adjustment by Zip Code Median Household Income*

    VariablePhiladelphia County (N = 3591) (Labeled = 580)Subgroup HbA1c ≤7% (N = 1298) (Labeled = 169)Subgroup HbA1c >7% (N = 2293) (Labeled = 411)Subgroup Primary Care (N = 2016) (Labeled = 315)Subgroup Specialty Care (N = 1575) (Labeled = 265)
    βadj [95% CI]βadj [95% CI]βadj [95% CI]βadj [95% CI]βadj [95% CI]
    HbA1c0.085 [0.043, 0.126]−0.20 [−0.54, 0.14]−0.013 [−0.03, 0.004]0.082 [0.03, 0.14]0.09 [0.03, 0.15]
    Zip code Median Income, $1000 units−0.027 [−0.041, −0.014]−0.031 [−0.056, −0.006]−0.026 [−0.042, −0.01]−0.019 [−0.038, −0.001]−0.041 [−0.061, −0.021]
    ARR [95% CI]ARR [95% CI]ARR [95% CI]ARR [95% CI]ARR [95% CI]
    Race
        WhiteRefRefRefRefRef
        Black1.70 [1.28, 2.30]2.01 [1.23, 3.72]1.55 [1.12, 2.21]2.78 [1.55, 5.14]1.37 [1.01, 1.97]
    Insurance payor
        PrivateRefRefRefRefRef
        Medicaid1.71 [1.39, 2.07]1.44 [1.03, 2.03]1.81 [1.40, 2.30]2.08 [1.54, 2.76]1.36 [1.03, 1.79]
        Medicare1.61[1.29, 1.99]1.52 [1.06, 2.21]1.61 [1.21, 1.98]1.48 [1.02, 2.08]1.60 [1.22, 2.12]
    • BMI, body mass index; CI, confidence interval; HbA1c, hemoglobin A1C.

    • ↵* In addition to zip-code median income, the logistic regression model also included the following potentially confounding variables: age, sex, race, BMI, ethnicity, insurance status, and HbA1c.

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    Appendix Table 1.

    Unadjusted prevalences of nonadherence labeling among all racial categories

    TotalNot LabeledLabeledPrevalence
    Overall723264058270.114
    Black415234876650.160
    White222421111130.051
    Asian260250100.038
    Other222211110.050
    Hispanic /Latino—White116106100.086
    Hispanic /Latino—Black6251110.177
    East Indian716740.056
    American Indian191900.000
    Patient declined111100.000
    Pacific Islander4400.000
    Unknown race918830.033
    • View popup
    Appendix Table 2.

    Adjusted Odd Ratios for Nonadherence Labeling by Demographics in Hemoglobin A1c and Care Site Strata*

    VariableOverall
    (n = 6072) (Labeled = 759)
    Subgroup
    HbA1c ≤7% (n = 2349) (Labeled = 222)
    Subgroup
    HbA1c >7%
    (n = 3723)
    (Labeled = 537)
    Subgroup
    Primary Care
    (n = 2657)
    (Labeled = 376)
    Subgroup
    Specialty Care
    (n = 3415)
    (Labeled = 383)
    βadj [95% CI]βadj [95% CI]βadj [95% CI]βadj [95% CI]βadj [95% CI]
    Age, years−0.006 [−0.014, 0.002]−0.014 [−0.029, 0.001]−0.025 [−0.012, 0.007]0.009 [−0.0035, 0.020]−0.019 [−0.030, −0.008]
    HbA1c, %0.11 [0.08, 0.15]−0.14 [−0.43, 0.17]0.11 [0.05, 0.16]0.09 [0.04, 0.14]0.14 [0.087, 0.19]
    BMI, kg/m2−0.0027 [−0.0126, 0.007]0.074 [−0.010, 0.024]−0.008 [−0.02, 0.003]−0.002 [−0.016, 0.011]−0.002 [−0.016, 0.012]
    AOR [95% CI]AOR [95% CI]AOR [95% CI]AOR [95% CI]AOR [95% CI]
    Biological sex
     Malerefrefrefrefref
     Female1.01 [0.87, 1.18]0.93 [0.69, 1.23]1.03 [0.87, 1.28]1.04 [0.82, 1.30]0.97 [0.77, 1.21]
    Race
     Whiterefrefrefrefref
     Black2.77 [2.22, 3.48]3.23 [2.15, 4.97]2.53 [1.94, 3.33]2.71 [1.76, 4.37]2.76 [2.12, 3.60]
     Asian0.73 [0.35, 1.36]1.39 [0.46, 3.39]0.50 [0.17, 1.16]0.21 [0.01, 1.02]1.05 [0.48, 2.05]
    Ethnicity
     Non-Hispanicrefrefrefrefref
     Hispanic0.73 [0.35, 1.36]1.39 [0.46, 3.39]0.50 [0.17, 1.16]0.21 [0.01, 1.02]1.05 [0.48, 2.05]
    Insurance
     Privaterefrefrefrefref
     Medicaid1.87 [1.54, 2.26]1.83 [1.27, 2.62]1.86 [1.48, 2.33]2.16 [1.66, 2.79]1.53 [1.14, 2.04]
     Medicare1.64 [1.34, 1.99]1.78 [1.25, 2.52]1.56 [1.22, 1.99]1.41 [1.04, 1.90]1.81 [1.39, 2.35]
    Care site
     Primary carerefrefrefNot applicableNot applicable
     Specialty care1.00 [0.85, 1.17]0.89 [0.65, 1.22]1.04 [0.85, 1.26]Not applicableNot applicable
    • AOR, adjusted odd ratio; BMI, body mass index; HbA1c, hemoglobin A1c.

    • * AORs for categorical variables, and beta coefficients for continuous variables, were calculated with a log-binomial regression model using all of the following potentially confounding variables: age, sex, race, BMI, ethnicity, insurance status, and HbA1c. Results from both models did not change any of the conclusions.

    • View popup
    Appendix Table 3.

    Subgroup Analyses Exploring Different Hemoglobin A1c Cutoffs: 7% and 9%

    Overall
    (n = 6072) (Labeled = 759)
    HbA1c ≤7% (n = 2349) (Labeled = 222)HbA1c >7% (n = 3723) (Labeled = 537)HbA1c ≤9% (n = 4546) (Labeled = 479)HbA1c >9% (n = 1526) (Labeled = 280)
    ARR [95% CI]ARR [95% CI]ARR [95% CI]ARR [95% CI]ARR [95% CI]
    Whiterefrefrefrefref
    Black2.38 [1.93, 3.02]2.76 [1.85, 4.17]2.08 [1.63, 2.74]2.41 [1.78, 3.14]1.82 [1.25, 2.54]
    • ARR, adjusted risk ratio; HbA1c, hemoglobin A1c.

    • View popup
    Appendix Table 4.

    Sample Characteristics by Care Site*

    Primary Care
    (n = 2657)
    Specialty Care
    (n = 3415)
    P Value
    Mean (SD)Mean (SD)
    Age, years54.0 (10.0)55.1 (10.1)4.7 × 10-6
    BMI, kg/m234.1 (8.4)33.1 (8.0)1.9 × 10-6
    HbA1c, %8.0 (2.0)8.1 (1.9)9.9 × 10-8
    n (%)n (%)
    Biological sex
     Male1185 (44.6%)1724 (50.4 %)ref
     Female1472 (55.4%)1691 (49.6%)6.0 × 10-6
    Race
     White401 (15.1%)1635 (47.9%)ref
     Black2173 (81.8%)1634 (47.8%)2.2 × 10-6
     Asian83 (3.1%)146 (4.3%)1.1 × 10-8
    Ethnicity
     Non-Hispanic2599 (97.8%)3307 (96.8%)ref
     Hispanic58 (2.2%)108 (3.2%)0.025
    Insurance status
     Private1557 (58.6%)1979 (58.0%)ref
     Medicaid576 (21.7%)506 (14.8%)1.3 × 10-7
     Medicare524 (19.7%)930 (27.2%)2.3 × 10-7
    • BMI, body mass index; HbA1c, hemoglobin A1c.

    • * P values for the continuous variables were calculated using the nonparametric Wilcox test. P values for the categorical variables were calculated using the chi square test; in case of more than 2 categories, 1 category is shown as reference (eg, “White”).

    • View popup
    Appendix Table 5.

    Subgroup Analysis Exploring Primary/Specialty Care Strata

    Group 1: Primary Care (n = 2657)
    (Labeled = 376)
    Group 2: Specialty Care (n = 3415)
    (Labeled = 383)
    ARR [95% CI]ARR [95% CI]
    Race
     Whiterefref
     Black2.65 [1.71, 4.29]2.19 [1.68, 2.86]
     Asian0.21 [0.00, 0.77]1.02 [0.46, 1.64]
    Ethnicity
     Non-Hispanicrefref
     Hispanic0.31 [0.00, 0.97]1.39 [0.26, 3.21]
    Biological sex
     Malerefref
     Female1.04 [0.84, 1.29]0.97 [0.80, 1.17]
    BMI
     Normalrefref
     Overweight0.62 [0.41, 0.91]0.75 [0.55, 1.01]
     Obese0.67 [0.47, 0.93]0.76 [0.57, 1.01]
    Insurance status
     Privaterefref
     Medicaid2.13 [1.61, 2.73]1.50 [1.16, 1.93]
     Medicare1.38 [1.00, 1.85]1.63 [1.30, 2.04]
    • ARR, adjusted risk ratio; BMI, body mass index.

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Associations of Race, Insurance, and Zip Code-Level Income with Nonadherence Diagnoses in Primary and Specialty Diabetes Care
Sourik Beltrán, Daniel J. Arenas, Itzel J. López-Hinojosa, Elizabeth L. Tung, Peter F. Cronholm
The Journal of the American Board of Family Medicine Sep 2021, 34 (5) 891-897; DOI: 10.3122/jabfm.2021.05.200639

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Associations of Race, Insurance, and Zip Code-Level Income with Nonadherence Diagnoses in Primary and Specialty Diabetes Care
Sourik Beltrán, Daniel J. Arenas, Itzel J. López-Hinojosa, Elizabeth L. Tung, Peter F. Cronholm
The Journal of the American Board of Family Medicine Sep 2021, 34 (5) 891-897; DOI: 10.3122/jabfm.2021.05.200639
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