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Healthcare disparities in adolescent idiopathic scoliosis: the impact of socioeconomic factors on Cobb angle

Spine Deformity volume 8, pages 605–611 (2020)Cite this article

A Letter to the Editor to this article was published on 02 November 2020

Abstract

Study design

Retrospective chart review.

Objectives

The aim of this study is to assess the role of insurance type, geographic socioeconomic status, and ethnicity in AIS disease severity in a state with mandated scoliosis screenings.

Summary of background data

Early detection of adolescent idiopathic scoliosis (AIS) is associated with reduced curve progression, surgical treatment, and long-term sequelae. Type of insurance, ethnicity, and socioeconomic status are important determinants in healthcare access.

Methods

Data were obtained for 561 AIS patients aged 10–18 years, living within a single county, and presenting to a single healthcare system for initial evaluation of AIS between 2010 and 2016 that met inclusion criteria. Demographic data including gender, age, self-reported ethnicity, insurance, and zip code were collected. Outcome measures included Cobb angle, curve severity, and referral delay. A single fellowship-trained pediatric orthopedic surgeon calculated presenting Cobb angle for each case. Zip code was used as a proxy for household income level. Independent sample t tests, analysis of variance and covariance, and χ2 analysis were used to determine the significant differences and correlations.

Results

Female patients (n = 326, CA = 22.4°) had significantly greater Cobb angle measurements compared with male patients (n = 117, CA = 18.1°). Patients with government-supported insurance had significantly higher Cobb angles (CA = 22.1°) than privately insured patients (CA = 19.2°) but were both classified within the “mild” range clinically, and are likely not clinically significant. There was no correlation between income level and Cobb angle. Referral delay and Cobb angle severity did not vary by age, income, or insurance. A χ2 analysis showed no association between Cobb angle and race.

Conclusions

Cobb angle severity was not influenced by SES factors, including ethnicity and household income.

Level of evidence

Level-II.

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Fig. 1

References

  1. Zavatsky JM, Peters AJ, Nahvi FA, Bharucha NJ, Trobisch PD, Kean KE et al (2015) Disease severity and treatment in adolescent idiopathic scoliosis: the impact of race and economic status. Spine J 15(5):939–943

    Article  PubMed  Google Scholar 

  2. Goldstein RY, Joiner ER, Skaggs DL (2015) Insurance status does not predict curve magnitude in adolescent idiopathic scoliosis at first presentation to an orthopaedic surgeon. J Pediatr Orthop 35(1):39–42

    Article  PubMed  Google Scholar 

  3. Johnson JP, Daniels AH, Grabel ZJ, Miller SM, Eberson CP (2016) Referral for adolescent idiopathic scoliosis by pediatric primary care providers. Clin Pediatr 56(1):20–25

    Article  Google Scholar 

  4. Raudenbush BL, Gurd DP, Goodwin RC, Kuivila TE, Ballock RT (2017) Cost analysis of adolescent idiopathic scoliosis surgery: early discharge decreases hospital costs much less than intraoperative variables under the control of the surgeon. J Spine Surg 3(1):50–57

    Article  PubMed  PubMed Central  Google Scholar 

  5. Texas Department of State Health Services. Spinal Screening Program [Internet]. Texas Department of State Health Services. https://dshs.texas.gov/spinal/default.shtm. Accessed 1 Feb 2019

  6. Beauséjour M, Goulet L, Feldman DE, Silva RBD, Pineault R, Rossignol M et al (2015) Pathways of healthcare utilisation in patients with suspected adolescent idiopathic scoliosis: a cross-sectional study. BMC Health Serv Res. https://doi.org/10.1186/s12913-015-1152-1

    Article  PubMed  PubMed Central  Google Scholar 

  7. Bunnell WP (1993) Outcome of spinal screening. Spine 18(12):1572–1580

    CAS  Article  PubMed  Google Scholar 

  8. Grossman TW, Mazur JM, Cummings RJ (1995) An evaluation of the adams forward bend test and the scoliometer in a scoliosis school screening setting. J Pediatr Orthop 15(4):535–538

    CAS  Article  PubMed  Google Scholar 

  9. Berman S, Dolins J, Tang SF, Yudkowsky B (2002) Factors that influence the willingness of private primary care pediatricians to accept more medicaid patients. Pediatrics 110(2):239–248

    Article  PubMed  PubMed Central  Google Scholar 

  10. Slover J, Gibson J, Tosteson T, Smith B, Koval K (2005) Racial and economic disparity and the treatment of pediatric fractures. J Pediatr Orthop 25(6):717–721

    Article  PubMed  Google Scholar 

  11. Verma K, Lonner B, Hoashi JS, Lafage V, Dean L, Engel I et al (2010) Demographic factors affect scoliosis research society-22 performance in healthy adolescents. Spine 35(24):2134–2139

    Article  PubMed  Google Scholar 

  12. Skinner AC, Mayer ML (2007) Effects of insurance status on childrens access to specialty care: a systematic review of the literature. BMC Health Serv Res. https://doi.org/10.1186/1472-6963-7-194

    Article  PubMed  PubMed Central  Google Scholar 

  13. Lafata JE, Pladevall M, Divine G, Ayoub M, Philbin EF (2004) Are there race/ethnicity differences in outpatient congestive heart failure management, hospital use, and mortality among an insured population? Med Care 42(7):680–689

    Article  PubMed  Google Scholar 

  14. Jablonski KA, Guagliardo MF (2005) Pediatric appendicitis rupture rate: a national indicator of disparities in healthcare access. Popul Health Metr. https://doi.org/10.1186/1478-7954-3-4

    Article  PubMed  PubMed Central  Google Scholar 

  15. Fiscella K, Franks P, Doescher MP, Saver BG (2002) Disparities in health care by race, ethnicity, and language among the insured. Med Care 40(1):52–59

    Article  PubMed  PubMed Central  Google Scholar 

  16. Fiscella K, Franks P, Gold MR, Clancy CM (2000) Inequality in quality. JAMA 283(19):2579

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  17. Weissman JS (1991) Delayed access to health care: risk factors, reasons, and consequences. Ann Intern Med 114(4):325

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  18. Mutchler JE, Burr JA (1991) Racial differences in health and health care service utilization in later life: the effect of socioeconomic status. J Health Soc Behav 32(4):342

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  19. Cho SK, Egorova NN (2015) The association between insurance status and complications, length of stay, and costs for pediatric idiopathic scoliosis. Spine 40(4):247–256

    Article  PubMed  PubMed Central  Google Scholar 

  20. Fletcher ND, Lazarus DE, Desai MJ, Patel NN, Bruce RW Jr (2015) Medicaid insurance is associated with larger curves in patients who require scoliosis surgery. Am J Orthop 44(11):E454–E457

    PubMed  Google Scholar 

  21. Skaggs DL (2003) Less access to care for children with Medicaid. Orthopedics 26(12):1184–1186

    PubMed  Google Scholar 

  22. Skaggs DL, Lehmann CL, Rice C et al (2006) Access to orthopaedic care for children with Medicaid versus private insurance: results of a national survey. J Pediatr Orthop 26(3):400–404

    Article  PubMed  Google Scholar 

  23. Skaggs DL, Oda JE, Lerman L et al (2007) Insurance status and delay in orthotic treatment in children. J Pediatr Orthop 27(1):94–97

    Article  PubMed  Google Scholar 

  24. Kasper MJ, Robbins L, Root L, Peterson M, Allegrante JP (1993) A musculo-skeletal outreach screening, treatment, and education program for urban minority children. Arthritis Care Res 6(3):126–133

    CAS  Article  PubMed  Google Scholar 

  25. Thomas AJ, Eberly LE, Smith G et al (2006) ZIP-code based versus tract based income measures as long term risk adjusted mortality predictors. Am J Epidemiol 164(6):586–590

    Article  PubMed  Google Scholar 

  26. Berkowitz SA, Traore CY, Singer SE et al (2015) Evaluating area based socioeconomic status indicators for monitoring disparities within health care systems: results from a primary care network. Health Serv Res 50(2):398–417

    Article  PubMed  PubMed Central  Google Scholar 

  27. Link-Gelles R, Westreich D, Aiello AE et al (2016) Bias with respect to socioeconomic status: a closer look at zip code matching in a pneumococcal vaccine effectiveness study. SSM Popul Health 2:587–594

    Article  PubMed  PubMed Central  Google Scholar 

  28. Jolly M, Mikolaitis RA, Shakoor N et al (2010) Education, zip code-based annualized household income, and health outcomes in patients with systemic lupus erythematosus. J Rheumatol 37(6):1150–1157

    Article  PubMed  Google Scholar 

  29. U.S. Census Bureau QuickFacts: Bexar County, Texas [Internet]. Census bureau quickfacts. United States census bureau. https://www.census.gov/quickfacts/fact/table/bexarcountytexas/INC110215. Accessed 12 Feb 2018

  30. Weinstein SL, Dolan LA, Wright JG, Dobbs MB (2013) Effects of bracing in adolescents with idiopathic scoliosis. N Engl J Med 369(16):1512–1521

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  31. Health Insurance Coverage [Internet]. Texmed. https://www.texmed.org/Template.aspx?id=42282. Accessed 28 Nov 2017

  32. Nuno M, Drazin DG, Acosta FL (2013) Differences in treatments and outcomes for idiopathic scoliosis patients treated in the United States from 1998 to 2007: impact of socioeconomic variables and ethnicity. Spine 13(2):116–123

    Article  Google Scholar 

  33. Beausejour M, Roy-Beaudry M, Goulet L, Labelle H (2007) Patient characteristics at the initial visit to a scoliosis clinic. Spine 32(12):1349–1354

    Article  PubMed  Google Scholar 

  34. Asher MA, Burton DC (2006) Adolescent idiopathic scoliosis: natural history and long term treatment effects. Scoliosis 1(1):2–12

    Article  PubMed  PubMed Central  Google Scholar 

  35. Wiznia DH, Nwachuku E, Roth A, Kim CY, Save A, Anandasivam NS, Medvecky M, Pelker R (2017) The influence of medical insurance on patient access to orthopaedic surgery sports medicine appointments under the affordable care act. Orthop J Sports Med. https://doi.org/10.1177/2325967117714140

    Article  PubMed  PubMed Central  Google Scholar 

  36. Miller NH (1999) Cause and natural history of adolescent idiopathic scoliosis. Orthop Clin North Am 30(3):343–352

    CAS  Article  PubMed  PubMed Central  Google Scholar 

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Funding

This study was funded by institutional Dielmann Endowment Fund.

Author information

Affiliations

  1. University of Texas Health Science Center at San Antonio, San Antonio, TX, USA

    Taylor Russell, Anand Dharia, Ryan Folsom, Mohamad Kaki, Emile Shumbusho, Roberto Jose Fajardo, Kush Shah, Ventrice Shillingford-Cole & Grant D. Hogue

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  1. Taylor Russell
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  2. Anand Dharia
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  3. Ryan Folsom
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  9. Grant D. Hogue
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Contributions

TR: conception, data acquisition, analysis, interpretation, drafting, revision, final approval. AD: data acquisition, analysis, interpretation, drafting, revision, final approval. RF: data acquisition, revision, final approval. MK: data acquisition, revision, final approval. ES: data acquisition, revision, final approval. RJF: conception, revision, final approval. KS: analysis, drafting, revision, final approval. VSC: conception, revision, final approval. GDH: conception, analysis, interpretation, drafting, final approval.

Corresponding author

Correspondence to Grant D. Hogue.

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Ethical approval

This study was performed with approval from local IRB.

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Russell, T., Dharia, A., Folsom, R. et al. Healthcare disparities in adolescent idiopathic scoliosis: the impact of socioeconomic factors on Cobb angle. Spine Deform 8, 605–611 (2020). https://doi.org/10.1007/s43390-020-00097-2

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  • DOI: https://doi.org/10.1007/s43390-020-00097-2

Keywords

  • Adolescent idiopathic scoliosis
  • AIS
  • Socioeconomic factors
  • Healthcare disparities
  • Cobb angle