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Research ArticleOriginal Research

Patterns of Diabetes Screening and Prediabetes Treatment during Office Visits in the US

Kayce M. Shealy, Jun Wu, Jessica Waites, Nancy A. Taylor and G. Blair Sarbacker
The Journal of the American Board of Family Medicine March 2019, 32 (2) 209-217; DOI: https://doi.org/10.3122/jabfm.2019.02.180259
Kayce M. Shealy
Presbyterian College School of Pharmacy, Clinton, SC (KMS, JW, JW, NAT, GBS).
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Jun Wu
Presbyterian College School of Pharmacy, Clinton, SC (KMS, JW, JW, NAT, GBS).
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Jessica Waites
Presbyterian College School of Pharmacy, Clinton, SC (KMS, JW, JW, NAT, GBS).
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Nancy A. Taylor
Presbyterian College School of Pharmacy, Clinton, SC (KMS, JW, JW, NAT, GBS).
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G. Blair Sarbacker
Presbyterian College School of Pharmacy, Clinton, SC (KMS, JW, JW, NAT, GBS).
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    Figure 1.

    Study sample of eligible visits with risk factors for prediabetes, NAMCS 2012–2015. CVD, cardiovascular disease; HTN, hypertension; PCOS, polycystic ovarian syndrome.

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    Figure 2.

    Trend of diabetes screening prevalence in the study sample (2012 to 2015).

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    Figure 3.

    Prevalence of laboratory testing provided or ordered for diabetes screening at the visits (n = 8375).

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    Figure 4.

    Treatment provided during visits with prediabetes (n = 5406).

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    Table 1.

    Characteristics of Visit Sample and Factors Associated with Diabetes Screening (n = 105,721)

    VariableTotal No. (n = 105,721)Diabetes Screening (n = 8,375), N (weighted %)No Diabetes Screening (n = 97,346), N (weighted %)Adjusted OR of Screening (95% CI)
    Age (years)
        18 to 445,845 (6.8)653 (8.6)5,192 (6.6)1.00
        45 to 6452,100 (49.7)4,302 (53.6)47,798 (49.2)1.18 (0.96–1.46)
        ≥6547,776 (43.5)3,420 (37.8)44,356 (44.2)0.86 (0.69–1.06)
    Race
        White92,347 (83.8)7,043 (78.2)85,304 (84.5)1.00
        Black9,263 (10.5)918 (14.9)8,345 (9.9)1.28 (1.03–1.58)
        Other*4,111 (5.7)414 (7.0)3,697 (5.5)1.44 (1.14–1.82)
    Sex
        Female60,831 (58.5)4,633 (56.9)56,198 (58.7)1.00
        Male44,890 (41.5)3,742 (43.1)41,148 (41.3)0.99 (0.88–1.11)
    BMI
        <18.542,799 (36.1)1,451 (13.1)41,348 (39.1)1.00
        18.5 to 2516,062 (16.4)1,536 (19.8)14,526 (15.9)2.63 (2.15–3.21)
        25 to 3022,692 (23.6)2,703 (36.3)19,989 (21.9)3.17 (2.63–3.81)
        ≥3024,168 (24.0)2,685 (30.7)21,483 (23.1)2.08 (1.72–2.51)
    Primary payer
        Private46,101 (44.3)4,085 (50.5)42,016 (43.4)1.00
        Medicare/Medicaid46,584 (43.4)3,431 (40.3)43,153 (43.8)0.79 (0.69–0.91)
        Uninsured4,006 (4.6)164 (1.9)3,842 (5.0)0.52 (0.37–0.73)
        Other†9,030 (7.7)695 (7.4)8,335 (7.8)0.87 (0.61–1.25)
        Smoking13,764 (12.8)1,333 (15.7)12,431 (12.5)0.98 (0.87–1.10)
    Comorbidity
        Hypertension36,729 (37.1)4,512 (53.0)32,217 (35.0)1.05 (0.92–1.20)
        CHF3,365 (3.3)365 (3.4)3,000 (3.3)0.75 (0.58–0.96)
        CAD4,996 (5.4)740 (7.7)4,256 (5.1)0.97 (0.79–1.19)
        PCOS70 (0.08)19 (0.2)51 (0.1)—‡
    Abnormal lipids§1,323 (1.3)362 (3.2)961 (1.1)1.69 (1.30–2.20)
    Prediabetes5,406 (6.0)1,523 (16.7)3,883 (4.6)2.56 (2.19–3.00)
    Total no. of chronic conditions
        034,527 (30.5)1,241 (14.8)33,286 (32.6)1.00
        132,263 (30.2)2,102 (25.6)30,161 (30.8)1.56 (1.33–1.83)
        220,470 (20.0)2,362 (26.6)18,108 (19.0)2.26 (1.87–2.74)
        >218,461 (19.4)2,670 (33.0)15,791 (17.6)2.97 (2.37–3.72)
    Physician Specialty
        Family/Internal medicine18,378 (29.3)3,959 (62.8)14,419 (24.8)1.00
        CVD specialty3,730 (4.6)520 (5.0)3,210 (4.5)0.38 (0.25–0.58)
        Other83,613 (66.0)3,896 (32.2)79,717 (70.7)0.26 (0.22–0.31)
    Physician Office
        Metropolitan area93,411 (91.7)7,350 (92.3)86,061 (91.6)0.83 (0.67–1.03)
    Region
        Northeast15,449 (21.5)1,518 (27.5)13,931 (20.7)1.00
        Midwest28,363 (17.9)2,207 (16.9)26,156 (18.0)0.61 (0.48–0.78)
        South37,030 (37.4)2,972 (36.7)34,058 (37.5)0.67 (0.52–0.88)
        West24,879 (23.2)1,678 (18.9)23,201 (23.8)0.52 (0.40–0.67)
    • ↵* Other races include Hispanic, Asian, Native American, and multiple races.

    • ↵† Other sources of payments include worker's compensation, other, and unknown.

    • ↵‡ Not a reliable estimate due to a small number (<30) of patients with PCOS in the screening group.

    • ↵§ High density lipoprotein (HDL) <35 mg/dL or triglycerides (TG) >250 mg/dL

    • BMI, body mass index; CI, confidence interval; CVD, cardiovascular disease; OR, odds ratio; PCOS, polycystic ovarian syndrome; CHF congestive heart failure; CAD, coronary artery disease.

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The Journal of the American Board of Family     Medicine: 32 (2)
The Journal of the American Board of Family Medicine
Vol. 32, Issue 2
March-April 2019
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Patterns of Diabetes Screening and Prediabetes Treatment during Office Visits in the US
Kayce M. Shealy, Jun Wu, Jessica Waites, Nancy A. Taylor, G. Blair Sarbacker
The Journal of the American Board of Family Medicine Mar 2019, 32 (2) 209-217; DOI: 10.3122/jabfm.2019.02.180259

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Patterns of Diabetes Screening and Prediabetes Treatment during Office Visits in the US
Kayce M. Shealy, Jun Wu, Jessica Waites, Nancy A. Taylor, G. Blair Sarbacker
The Journal of the American Board of Family Medicine Mar 2019, 32 (2) 209-217; DOI: 10.3122/jabfm.2019.02.180259
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