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Research ArticleCervical Spine

Incidence of Traumatic Spinal Injury Following Public Policy Update on Moped Usage in South Carolina

Samuel Wood, Danielle Harpen, Chase Gauthier, Richard Bidwell and Gregory Grabowski
International Journal of Spine Surgery February 2025, 19 (1) 104-109; DOI: https://doi.org/10.14444/8704
Samuel Wood
1 Department of Orthopedic Surgery, Prisma Health – Midlands, Columbia, SC, USA
MD
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Danielle Harpen
2 Department of Orthopedic Surgery, University of South Carolina School of Medicine Columbia, Columbia, SC, USA
BS
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Chase Gauthier
1 Department of Orthopedic Surgery, Prisma Health – Midlands, Columbia, SC, USA
MD
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  • For correspondence: chase.gauthier@und.edu
Richard Bidwell
1 Department of Orthopedic Surgery, Prisma Health – Midlands, Columbia, SC, USA
MD
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Gregory Grabowski
1 Department of Orthopedic Surgery, Prisma Health – Midlands, Columbia, SC, USA
MD
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  • Article
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Article Figures & Data

Tables

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    Table 1

    Demographic information of trauma cases involving a moped or scooter before and after increased regulation.

    CharacteristicPrelaw(N = 239)Postlaw(N = 111) P
    Age, y, mean (SD)43.2 (15)47.4 (12.9) 0.01
    BMI, mean (SD)26.5 (5.5)27.5 (6.4)0.3
    Race, n (%)
     White130 (54.4)63 (56.8)
     Black91 (38.1)41 (36.9)
     Other18 (7.5)7 (6.3)
    Gender, n (%)
     Men210 (87.9)106 (95.5) 0.03
     Women29 (12.1)5 (4.5)
    Patient ethnicity, n (%)
     Not Hispanic or Latino234 (97.9)107 (96.4)0.47
     Hispanic or Latino5 (2.1)4 (3.6)
    Incidence of vertebral fractures, n (%)
     Total47 (19.7)13 (11.7)0.09
     Cervical25 (10.5)10 (9)0.8
     Thoracic16 (6.7)3 (2.7)0.19
     Lumbar16 (6.7)2 (1.8)0.07
    Incidence of spinal cord injuries, n (%)
     Total7 (2.9%)0 (0%)0.1
    • Abbreviation: BMI, body mass index.

    • Note: Bolded values indicate a statistically significant finding with P < 0.05.

    • View popup
    Table 2

    Demographic information by vertebral fracture involving a moped or scooter.

    CharacteristicCervical (N = 35)Thoracic (N = 19)Lumbar (N = 18) P
    Prelaw, n (%)25 (71.4)16 (84.2)16 (88.9)0.31
    Postlaw, n (%)10 (28.6)3 (15.8)2 (11.1)
    Age, y, mean (SD)48.7 (13.6)51.5 (13)46.9 (17.3)0.62
    BMI, mean (SD)27.1 (6.3)28.7 (8)27.3 (5.4)0.72
    Race, n (%)
     White17 (48.6)16 (84.2)11 (61.1)<0.01
     Black18 (51.4)2 (10.5)5 (27.8)
     Other0 (0)1 (5.3)2 (11.1)
    Gender, n (%)
     Men32 (91.4)18 (94.7)13 (72.2)0.11
     Women3 (8.6)1 (5.3)5 (27.8)
    Patient ethnicity, n (%)
     Not Hispanic or Latino35 (100)19 (100)16 (88.9)0.06
     Hispanic or Latino0 (0)0 (0)2 (11.1)
    • Abbreviation: BMI, body mass index.

    • Note: Bolded values indicate a statistically significant finding with P < 0.05.

    • View popup
    Table 3

    Univariate logistic analysis of patient variables leading to traumatic spinal fractures involving a moped or scooter.

    CharacteristicTotalCervicalThoracicLumbar
    OR P OR P OR P OR P
    BMI (continuous)1.0020.571.0010.861.0020.211.0010.77
    Prelaw or not1.080.061.020.661.040.121.050.05
    Postlaw or not0.920.060.980.660.960.120.950.05
    Age (continuous) 1.002 0.04 1.0020.081.0020.031.0010.49
    Age >50 y1.060.181.040.191.040.081.010.59
    White1.020.570.970.42 1.07 0.01 1.010.59
    Black0.990.831.060.08 0.94 0.01 0.980.37
    Other0.950.480.90.080.980.751.030.5
    Women1.040.570.990.820.970.5 1.11 0.01
    Ethnicity1.050.680.90.310.950.47 1.19 0.02
    • Abbreviation: BMI, body mass index.

    • Note: Bolded values indicate a statistically significant finding with P < 0.05.

    • View popup
    Table 4

    Multivariate logistic analysis for independent predictors of traumatic vertebral fractures involving a moped or scooter.

    CharacteristicOR95% CI P
    Prelaw 2.08 1.09–4.23 0.03
    Age 1.03 1.01–1.05 0.01
    Female gender1.470.54–3.620.42
    White3.340.63–61.710.25
    Black2.850.52–53.30.32
    Hispanic or Latino4.630.36–113.450.25
    • Note: Bolded values indicate a statistically significant finding with P < 0.05.

    • View popup
    Table 5

    Multivariate logistic analysis for independent predictors of traumatic cervical vertebral fractures involving a moped or scooter.

    CharacteristicOR95% CI P
    Prelaw1.310.61–2.990.5
    Age1.020.99–1.050.1
    Female gender1.170.26–3.840.81
    WhiteNA due to singularities
    BlackNA due to singularities
    Hispanic or Latino0.990.00–2.83>0.99
    • Abbreviation: NA, not applicable.

    • Note: Bolded values indicate a statistically significant finding with P < 0.05.

    • View popup
    Table 6

    Multivariate logistic analysis for independent predictors of traumatic thoracic vertebral fractures involving a moped or scooter.

    CharacteristicOR95% CI P
    Prelaw3.020.96–13.390.09
    Age 1.04 1.01–1.08 0.02
    Female gender0.650.03–3.740.69
    White1.320.23–25.120.8
    Black0.20.02–4.550.21
    Hispanic or LatinoNA due to singularities
    • Abbreviation: NA, not applicable.

    • Note: Bolded values indicated a statistically significant finding with P < 0.05.

    • View popup
    Table 7

    Multivariate logistic analysis for independent predictors of traumatic lumbar vertebral fractures.

    CharacteristicOR95% CI P
    Prelaw4.151.1–27.120.07
    Age1.030.99–1.060.14
    Female gender 3.89 1.05–13.02 0.03
    WhiteNA due to singularities
    BlackNA due to singularities
    Hispanic or LatinoNA due to singularities
    • Abbreviation: NA, not applicable.

    • Note: Bolded values indicate a statistically significant finding with P < 0.05.

Supplementary Materials

  • Tables
  • Uncited TABLE S1.

    [8704supp001.docx]

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Incidence of Traumatic Spinal Injury Following Public Policy Update on Moped Usage in South Carolina
Samuel Wood, Danielle Harpen, Chase Gauthier, Richard Bidwell, Gregory Grabowski
International Journal of Spine Surgery Feb 2025, 19 (1) 104-109; DOI: 10.14444/8704

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Incidence of Traumatic Spinal Injury Following Public Policy Update on Moped Usage in South Carolina
Samuel Wood, Danielle Harpen, Chase Gauthier, Richard Bidwell, Gregory Grabowski
International Journal of Spine Surgery Feb 2025, 19 (1) 104-109; DOI: 10.14444/8704
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Keywords

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  • e-Scooter
  • spinal injury
  • South Carolina
  • cervical injury
  • thoracic injury
  • lumbar injury

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