Care for Chiari malformation type I: the role of socioeconomic disadvantage and race

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  • 1 Department of Neurosurgery,
  • | 2 Department of Pediatrics, and
  • | 3 Department of Internal Medicine, University of Alabama at Birmingham School of Medicine, Birmingham, Alabama
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OBJECTIVE

There is little research on the effect of social determinants of health on Chiari malformation type I (CM-I). The authors analyzed data on all children evaluated for CM-I at a single institution to assess how socioeconomic factors and race affect the surgical treatment of this population.

METHODS

Medical records of patients treated for CM-I at the authors’ institution between 1992 and 2017 were reviewed. Area Deprivation Index (ADI) and Rural-Urban Commuting Area (RUCA) codes for each patient were used to measure neighborhood disadvantage. Non-Hispanic White patients were compared to non-White patients and Hispanic patients of any race (grouped together as non-White in this study) in terms of insurance status, ADI, and RUCA. Patients with initially benign CM-I, defined as not having undergone surgery within 9 months of their initial visit, were then stratified by having delayed symptom presentation or not, and compared on these same measures.

RESULTS

The sample included 665 patients with CM-I: 82% non-Hispanic White and 18% non-White. The non-White patients were more likely to reside in disadvantaged (OR 3.4, p < 0.001) and urban (OR 4.66, p < 0.001) neighborhoods and to have public health insurance (OR 3.11, p < 0.001). More than one-quarter (29%) of patients underwent surgery. The non-White and non-Hispanic White patients had similar surgery rates (29.5% vs 28.9%, p = 0.895) at similar ages (8.8 vs 9.7 years, p = 0.406). There were no differences by race/ethnicity for symptoms at presentation. Surgical and nonsurgical patients had similar ADI scores (3.9 vs 4.2, p = 0.194), RUCA scores (2.1 vs 2.3, p = 0.252), and private health insurance rates (73.6% vs 74.2%, p = 0.878). A total of 153 patients underwent surgery within 9 months of their initial visit. The remaining 512 were deemed to have benign CM-I. Of these, 40 (7.8%) underwent decompression surgery for delayed symptom presentation. Patients with delayed symptom presentation were from less disadvantaged (ADI 3.2 vs 4.2; p = 0.025) and less rural (RUCA 1.8 vs 2.3; p = 0.023) areas than those who never underwent surgery.

CONCLUSIONS

Although non-White patients were more likely to be socioeconomically disadvantaged, race and socioeconomic disadvantage were not associated with undergoing surgical treatment. However, among patients with benign CM-I, those undergoing decompression for delayed symptom presentation resided in more affluent and urban areas.

ABBREVIATIONS

ADI = Area Deprivation Index; CM-I = Chiari malformation type I; PFD = posterior fossa decompression without duraplasty; PFDD = PFD with duraplasty; RUCA = Rural-Urban Commuting Area; SM = syringomyelia.

Image from Jeon et al. (pp 319–324).

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  • 1

    Holly LT, Batzdorf U. Chiari malformation and syringomyelia. J Neurosurg Spine. 2019;31(5):619628.

  • 2

    Pindrik J, Johnston JM Jr. Clinical presentation of Chiari I malformation and syringomyelia in children. Neurosurg Clin N Am. 2015;26(4):509514.

  • 3

    Alexander H, Tsering D, Myseros JS, Magge SN, Oluigbo C, Sanchez CE, Keating RF. Management of Chiari I malformations: a paradigm in evolution. Childs Nerv Syst. 2019;35(10):18091826.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 4

    Koueik J, Sandoval-Garcia C, Kestle JRW, Rocque BG, Frim DM, Grant GA, et al. Outcomes in children undergoing posterior fossa decompression and duraplasty with and without tonsillar reduction for Chiari malformation type I and syringomyelia: a pilot prospective multicenter cohort study. J Neurosurg Pediatr. 2020;25(1):2129.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 5

    Zhao JL, Li MH, Wang CL, Meng W. A systematic review of Chiari I malformation: techniques and outcomes. World Neurosurg. 2016;88:714.

  • 6

    Brown ZD, Bey AK, Bonfield CM, Westrick AC, Kelly K, Kelly K, Wellons JC III. Racial disparities in health care access among pediatric patients with craniosynostosis. J Neurosurg Pediatr. 2016;18(3):269274.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7

    Zavatsky JM, Peters AJ, Nahvi FA, Bharucha NJ, Trobisch PD, Kean KE, et al. Disease severity and treatment in adolescent idiopathic scoliosis: the impact of race and economic status. Spine J. 2015;15(5):939943.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8

    Shweikeh F, Sunjaya D, Nuno M, Drazin D, Adamo MA. National trends, complications, and hospital charges in pediatric patients with Chiari malformation type I treated with posterior fossa decompression with and without duraplasty. Pediatr Neurosurg. 2015;50(1):3137.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9

    Leon TJ, Kuhn EN, Arynchyna AA, Smith BP, Tubbs RS, Johnston JM, et al. Patients with "benign" Chiari I malformations require surgical decompression at a low rate. J Neurosurg Pediatr. 2019;23(4):498506.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 10

    Krieger N, Williams DR, Moss NE. Measuring social class in US public health research: concepts, methodologies, and guidelines. Annu Rev Public Health. 1997;18:341378.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11

    Oakes JM, Rossi PH. The measurement of SES in health research: current practice and steps toward a new approach. Soc Sci Med. 2003;56(4):769784.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12

    Sampson R, Morenoff J, Gannon-Rowley T. Assessing “neighborhood effects”: social processes and new directions in research. Annu Rev Sociol. 2002;28:443478.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 13

    Diez-Roux AV, Kiefe CI, Jacobs DR Jr, Haan M, Jackson SA, Nieto FJ, et al. Area characteristics and individual-level socioeconomic position indicators in three population-based epidemiologic studies. Ann Epidemiol. 2001;11(6):395405.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14

    Carroll-Scott A, Gilstad-Hayden K, Rosenthal L, Peters SM, McCaslin C, Joyce R, Ickovics JR. Disentangling neighborhood contextual associations with child body mass index, diet, and physical activity: the role of built, socioeconomic, and social environments. Soc Sci Med. 2013;95:106114.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15

    Kranjac AW, Denney JT, Kimbro RT, Moffett BS, Lopez KN. Neighborhood and social environmental influences on child chronic disease prevalence. Popul Environ. 2018;40(2):93114.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16

    Kind AJH, Buckingham WR. Making neighborhood-disadvantage metrics accessible - the Neighborhood Atlas. N Engl J Med. 2018;378(26):24562458.

  • 17

    University of Wisconsin School of Medicine and Public Health. 2015 Area Deprivation Index v2.0. Accessed October 6, 2021. https://www.neighborhoodatlas.medicine.wisc.edu

    • Search Google Scholar
    • Export Citation
  • 18

    Kind AJH, Jencks S, Brock J, Yu M, Bartels C, Ehlenbach W, et al. Neighborhood socioeconomic disadvantage and 30-day rehospitalization: a retrospective cohort study. Ann Intern Med. 2014;161(11):765774.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19

    Nkoy FL, Stone BL, Knighton AJ, Fassl BA, Johnson JM, Maloney CG, Savitz LA. Neighborhood deprivation and childhood asthma outcomes, accounting for insurance coverage. Hosp Pediatr. Published online on January 9, 2018.doi: 10.1542/hpeds.2017-0032

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20

    Oates GR, Harris WT, Rowe SM, Solomon GM, Dey S, Zhu A, et al. Area Deprivation as a risk factor for methicillin-resistant Staphylococcus aureus infection in pediatric cystic fibrosis. Pediatr Infect Dis J. 2019;38(11):e285e289.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21

    Oates G, Rutland S, Juarez L, Friedman A, Schechter MS. The association of area deprivation and state child health with respiratory outcomes of pediatric patients with cystic fibrosis in the United States. Pediatr Pulmonol. 2021;56(5):883890.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22

    Oluyomi A, Aldrich KD, Foster KL, Badr H, Kamdar KY, Scheurer ME, et al. Neighborhood deprivation index is associated with weight status among long-term survivors of childhood acute lymphoblastic leukemia. J Cancer Surviv. 2021;15(5):767775.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23

    Schraw JM, Peckham-Gregory EC, Rabin KR, Scheurer ME, Lupo PJ, Oluyomi A. Area deprivation is associated with poorer overall survival in children with acute lymphoblastic leukemia. Pediatr Blood Cancer. 2020;67(9):e28525.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24

    US Department of Agriculture Economic Research Service. Rural-Urban Commuting Area Codes. US Department of Agriculture. Accessed October 5, 2021. https://www.ers.usda.gov/data-products/rural-urban-commuting-area-codes/

    • Search Google Scholar
    • Export Citation
  • 25

    Rogers W. Regression standard errors in clustered samples. Stata J. 1994;3(13):sg17.

  • 26

    Kang H. The prevention and handling of the missing data. Korean J Anesthesiol. 2013;64(5):402406.

  • 27

    Kaiser Family Foundation. Health Insurance Coverage of Children 0-18. KFF; 2019.Accessed August 1, 2021. https://www.kff.org/other/state-indicator/children-0-18/

    • Search Google Scholar
    • Export Citation
  • 28

    QuickFacts Alabama. US Census Bureau. Accessed August 1, 2021. https://www.census.gov/quickfacts/AL

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