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Neurologic Complications of Poverty: the Associations Between Poverty as a Social Determinant of Health and Adverse Neurologic Outcomes

  • Neurology of Systemic Diseases (J. Biller, Section Editor)
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A Correction to this article was published on 24 June 2021

This article has been updated

Abstract

Purpose of Review

Increasing attention has been paid in recent decades to social determinants of health as a risk factor for disease development and disease severity. While traditionally heart disease, family history, lipid profile, and tobacco use have all been associated with increased risk of neurological disease, numerous studies now show that the influence of poverty may be just as strong a risk factor. This study summarizes the recent literature on poverty as it contributes to neurological disease.

Recent Findings

Children growing up in poverty have increased risk for cognitive deficits and behavioral disorders as reported by Noble et al. (Dev Sci. 9(6):642–54, 2006) and Farah et al. (Brain Res. 1110(1):166–74, 2006) as well as worse outcomes when it comes to epilepsy management and disease course as discussed by Camfield et al. (Epilepsia. 57(11):1826–33, 2016). In adulthood, as the number of social determinants of health increases, the incidence of stroke and severe stroke increases significantly as reported by Reshetnyak et al. (Stroke. 51:2445–53, 2020) as does exposure to neurologically significant infectious diseases and incidence of dementia as reported by Sumilo et al. (Rev Med Virol. 18(2):81–95, 2008) and Zuelsdorff et al. (Alzheimer’s Dement. 6(1):e12039, 2020).

Summary

Social determinants of health including poverty should be considered a risk factor for disease. More attention is needed from clinicians as well as from a public health perspective to address this disparity.

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References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Noble KG, Wolmetz ME, Ochs LG, Farah MJ, McCandliss BD. Brain-behavior relationships in reading acquisition are modulated by socioeconomic factors. Dev Sci. 2006;9(6):642–54. https://doi.org/10.1111/j.1467-7687.2006.00542.x.

    Article  PubMed  Google Scholar 

  2. Farah MJ, Shera DM, Savage JH, Betancourt L, Giannetta JM, Brodsky NL, et al. Childhood poverty: specific associations with neurocognitive development. Brain Res. 2006;1110(1):166–74. https://doi.org/10.1016/j.brainres.2006.06.072.

    Article  CAS  PubMed  Google Scholar 

  3. Reshetnyak E, Ntamatungiro M, Pinheiro LC, Howard VJ, Carson AP, Martin KD, et al. Impact of multiple social determinants of health on incident stroke. Stroke. 2020;51:2445–53. https://doi.org/10.1161/STROKEAHA.120.028530Excellent analysis of the impact of social determinants of health on stroke incidence and severity. This study looked at over 27,000 participants and specifically examined the impact of social determinant of health (SDOH) on stroke incidence. 10 SDOH were examined related to influences from economic, educational, social and health care contexts. Increase in the number of SDOH were independently associated with higher incident stroke risk in adults aged <75 years of age.

  4. Powell WR, Buckingham WR, Larson JL, Vilen L, Yu M, Salamat MS, et al. Association of neighborhood-level disadvantage with Alzheimer disease neuropathology. JAMA Netw Open. 2020;3(6):e207559. https://doi.org/10.1001/jamanetworkopen.2020.7559Cross-sectional study correlating neighborhoods risk factors with presence of Alzheimer’s pathology. This cross-sectional study examined the neuropathology of brains donated to Alzheimer disease research centers in California and Wisconsin between 1990 and 2016 and correlated pathologic disease with known neighborhood factors of the patients. Researchers demonstrated that “living in a disadvantaged neighborhood at the time of death was associated with an increased risk of presence of Alzheimer disease neuropathology when adjusting for age, sex, and year of death”.

  5. Stiles J, Jernigan TL. The basics of brain development. Neuropsychol Rev. 2010;20(4):327–48. https://doi.org/10.1007/s11065-010-9148-4.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Kim DJ, Davis EP, Sandman CA, Glynn L, Sporns O, O’Donnell BF, et al. Childhood poverty and the organization of structural brain connectome. Neuroimage. 2019;184:409–16. https://doi.org/10.1016/j.neuroimage.2018.09.041Excellent investigation of associations between the socioeconomic disparities and structural brain network organization in children. This study investigated associations between the socioeconomic disparities and structural brain network organization in children. Results showed that poverty was associated with increased network inefficiency in multiple cortical regions suggesting that childhood poverty may result in wide-spread neurologic disruptions, particularly at the lowest levels of socioeconomic disparity.

  7. Hair NL, Hanson JL, Wolfe BL, Pollak SD. Association of child poverty, brain development, and academic achievement. JAMA Pediatr. 2015;169(9):822–9. https://doi.org/10.1001/jamapediatrics.2015.1475.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Noble KG, Houston SM, Brito NH, Bartsch H, Kan E, Kuperman JM, et al. Family income, parental education and brain structure in children and adolescents. Nat Neurosci. 2015;18(5):773–8. https://doi.org/10.1038/nn.3983.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Hanson JL, Hair N, Shen DG, Shi F, Gilmore JH, Wolfe BL, et al. Family poverty affects the rate of human infant brain growth. PLoS One. 2013;8(12):e80954. https://doi.org/10.1371/journal.pone.0080954.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Luby J, Belden A, Botteron K, Marrus N, Harms MP, Babb C, et al. The effects of poverty on childhood brain development: the mediating effects of caregiving and stressful life events. JAMA Pediatr. 2013;167(12):1135–42. https://doi.org/10.1001/jamapediatrics.2013.3139.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Taylor RL, Cooper SR, Jackson JJ, Barch DM. Assessment of neighborhood poverty, cognitive function, and prefrontal hippocampal volumes in children. JAMA Netw Open. 2020;3(11):e2023774. https://doi.org/10.1001/jamanetworkopen.2020.23774Study of over 11,000 children which showed neighborhood poverty correlates with decreased cognitive performance and brain volume changes on imaging. The study explored whether neighborhood poverty, independent of individual household socioeconomic status, affected cognitive performance and outcomes in children. More than 11,000 children were included in this study which included imaging data and cognitive testing. Results showed that greater levels of neighborhood poverty correlate with lower scores across multiple cognitive domains and decreased brain volume based on imaging studies.

  12. Kim P, Evans GW, Angstadt M, Ho SS, Sripada CS, Swain JE, et al. Effects of childhood poverty and chronic stress on emotion and regulatory brain function in adulthood. PNAS. 2013;110(46):18442–7. https://doi.org/10.1073/pnas.1308240110.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Smith JR, Brooks-Gunn J, Klebanov P. The consequences of living in poverty for young children’s cognitive and verbal ability and early school achievement. In: Duncan GJ, Brooks-Gunn J, editors. Consequences of growing up poor. New York: Russell Sage; 1997.

    Google Scholar 

  14. Duval ER, Garfinkel SN, Swain JE, Evans GW, Blackburn EK, Angstadt M, et al. Childhood poverty is associated with altered hippocampal function and visuospatial memory in childhood. Dev Cogn Neurosci. 2017;23:39–44. https://doi.org/10.1016/j.dcn.2016.11.006.

    Article  PubMed  Google Scholar 

  15. Hackman DA, Farah MJ, Meaney MJ. Socioeconomic status and the brain: mechanistic insights from human and animal research. Nat Rev Neurosci. 2010;11(9):651–9. https://doi.org/10.1038/nrn2897.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Kishiyama MM, Boyce WT, Jimenez AM, Perry LM, Knight RT. Socioeconomic disparities affect prefrontal function in children. J Cogn Neurosci. 2009;21(6):1106–15. https://doi.org/10.1162/jocn.2009.21101.

    Article  PubMed  Google Scholar 

  17. Kolb B, Gibb R. Childhood poverty and brain development. Hum Dev. 2015;58:215–7. https://doi.org/10.1159/000438766.

    Article  Google Scholar 

  18. Noble KG, Norman MF, Farah MJ. Neurocognitive correlates of socioeconomic status in kindergarten children. Dev Sci. 2004;8(1):74–87. https://doi.org/10.1111/j.1467-7687.2005.00394.x.

    Article  Google Scholar 

  19. Duyme M, Dumaret AC, Tomkiewicz S. How can we boost IQs of “dull children”? a late adoption study. PNAS. 1999;96(15):8790–4. https://doi.org/10.1073/pnas.96.15.8790.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Duncan GJ, Brooks-Gunn J, Klebanov PK. Economic deprivation and early childhood development. Child Dev. 1994;65(2):296–318. https://doi.org/10.2307/1131385.

    Article  CAS  PubMed  Google Scholar 

  21. Russell AE, Ford T, Williams R, Russell G. The association between socioeconomic disadvantage and Attention Deficit/Hyperactivity Disorder (ADHD): a systematic review. Child Psychiatry Hum Dev. 2016;47(3):440–58. https://doi.org/10.1007/s10578-015-0578-3.

    Article  PubMed  Google Scholar 

  22. Hart B, Risley TR. Meaningful differences in the everyday experience of young american children. Baltimore: Paul H Brookes Publishing Co.; 1995.

    Google Scholar 

  23. Boo NY, Ong LC, Lye MS, Chadran V, Teaoh SL, Zamratol S, et al. Comparison of morbidities in very low birthweight and normal birthweight infants during the first year of life in a developing country. J Paediatr Child Health. 1996;32(5):439–44. https://doi.org/10.1111/j.1440-1754.1996.tb00946.x.

    Article  CAS  PubMed  Google Scholar 

  24. Ballot D, Potterton J, Chirwa T, Hilburn N, Cooper P. Development outcome of very low birth weight infants in a developing country. BMC Pediatr. 2012;12:11. 10.1186-1471-2431-12-11.

  25. Stoinska B, Gadzinowski J. Neurological and developmental disabilities in ELBW and VLBW: follow-up at 2 years of age. J Perinatol. 2011;31(2):137–42. https://doi.org/10.1038/jp.2010.75.

    Article  CAS  PubMed  Google Scholar 

  26. Mukhopadhyay K, Prahbhjot M, Mahajan R, Narang A. Neurodevelopmental and behavioral outcome of very low birth weight babies at the corrected age of 2 years. Indian J Pediatr. 2010;77(9):963–7. https://doi.org/10.1007/s12098-010-0149-3.

    Article  PubMed  Google Scholar 

  27. Souza WV, Albuquerque MFPM, Vazquez E, Bezerra LCA, Mendes ADCG, Lyra TM, et al. Microcephaly epidemic related to the Zika virus and living conditions in Recife, Northeast Brazil. BMC Public Health. 2018;18(1):130. https://doi.org/10.1186/s12889-018-5039-z.

    Article  PubMed  PubMed Central  Google Scholar 

  28. de Araújo TVB, Ximenes RAA, Miranda-Filho DB, Souza WV, Montarroyos UR, de Melo APL, et al. Association between microcephaly, Zika virus infection and other risk factors in Brazil: final report of a case-control study. Lancet Infect Dis. 2018;18(3):328–36. https://doi.org/10.1016/S1473-3099(17)30727-2.

    Article  PubMed  Google Scholar 

  29. Manjunathachar HV, Singh KN, Chouksey V, Kumar R, Sharma RK, Barde PV. Prevalence of Torch Infections and its associated poor outcome in high-risk pregnant women of Central India: time to think for prevention strategies. Indian J Med Microbiol. 2020;38(3&4):379–84. https://doi.org/10.4103/ijmm.IJMM_20_136.

    Article  CAS  PubMed  Google Scholar 

  30. Prasoona KR, Srinadh B, Sunitha T, Sujatha M, Deepika MLN, Vijaya Lakshmi B, et al. Seroprevalence and influence of torch infections in high risk pregnant women: a large study from South India. J Obstet Gynaecol India. 2015;65(5):301–9. https://doi.org/10.1007/s13224-014-0615-3.

    Article  PubMed  Google Scholar 

  31. Birbeck GL. Epilepsy care in developing countries: part I of II. Epilepsy Curr. 2010;10(4):75–9. https://doi.org/10.1111/j.1535-7511.2010.01362.x.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Singh G, Sander JW. The global burden of epilepsy report: implications for low- and middle-income countries. Epilepsy Behav. 2020;105:106949. https://doi.org/10.1016/j.yebeh.2020.106949.

    Article  PubMed  Google Scholar 

  33. Trinka E, Kwan P, Lee B, Dash A. Epilepsy in Asia: Disease burden, management barriers, and challenges. Epilepsia. 2019;60(S1):7–21. https://doi.org/10.1111/epi.14458Meta-analysis showing epilepsy burdens in Asia as related to access to resources. This meta-analysis reviewed data collected from papers published in English from 1996 to 2016 related to epilepsy disease burden in Asia. It revealed a comprehensive picture of access to epilepsy treatment and variances based on country and regional income level. It showed that access to resources and treatment can explain a lot of the disparities in disease burden of epilepsy in Asia.

  34. Dolo H, Mandro M, Wonya’Rossi D, Ngave F, Fraeyman J, Siewe JN, et al. Community perceptions of epilepsy and its treatment in an onchocerciasis endemic region in Ituri, Democratic Republic of Congo. Infect Dis Poverty. 2018;7:115. https://doi.org/10.1186/s40249-018-0498-0.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Camfield C, Camfield P, Smith B. Poor versus rich children with epilepsy have the same clinical course and remission rates but a less favorable social outcome: a population-based study with 25 years of follow-up. Epilepsia. 2016;57(11):1826–33. https://doi.org/10.1111/epi.13576.

    Article  PubMed  Google Scholar 

  36. Anguzu R, Akun P, Katario T, Abbo C, Ningwa A, Ogwang R, et al. Household poverty, schooling, stigma, and quality of life in adolescents with epilepsy in rural Uganda. Epilepsy Behav. 2020;11:107584. https://doi.org/10.1016/j.yebeh.2020.107584.

    Article  Google Scholar 

  37. Hotez PJ. Neglected infections of poverty in the United States and their effects on the brain. JAMA Psychiatry. 2014;71(10):1099–100. https://doi.org/10.1001/jamapsychiatry.2014.1045.

    Article  PubMed  Google Scholar 

  38. Sumilo D, Bormane A, Asokliene L, Vasilenko V, Golovljova I, Avsic-Zupanc T, et al. Socio-economic factors in the differential upsurge of tick-borne encephalitis in Central and Eastern Europe. Rev Med Virol. 2008;18(2):81–95. https://doi.org/10.1002/rmv.566.

    Article  PubMed  Google Scholar 

  39. Barry MA, Bezek S, Serpa JA, Hotez PJ, Woc-Colburn L. Neglected infections of poverty in Texas and the rest of the United States: management and treatment options. Clin Pharmacol Ther. 2012;92(2):170–81. https://doi.org/10.1038/clpt.2012.85.

    Article  CAS  PubMed  Google Scholar 

  40. Harrigan RJ, Thomassen HA, Buermann W, Cummings RF, Kahn ME, Smith TB. Economic conditions predict prevalence of West Nile virus. PLoS One. 2010;5(11):e15437. https://doi.org/10.1371/journal.pone.0015437.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Markus HS, Brainin M, Fisher M. Tracking the global burden of stroke and dementia: World Stroke Day 2020. Int J Stroke. 2020;15(8):817–8. https://doi.org/10.1177/1747493020959186.

    Article  PubMed  Google Scholar 

  42. Tsivgoulis G, Safouris A, Kim DE, Alexandrov AV. Recent advances in primary and secondary prevention of atherosclerotic stroke. J Stroke. 2018;20(2):145–66. https://doi.org/10.5853/jos.2018.00773.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Kleindorfer DO, Khoury J, Moomaw CJ, Alwell K, Woo D, Flaherty ML, et al. Stroke incidence is decreasing in whites but not in blacks: a population–based estimate of temporal trends in stroke incidence from the Greater Cincinnati/Northern Kentucky Stroke Study. Stroke. 2010;41(7):1326–31. https://doi.org/10.1161/STROKEAHA.109.575043.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Gardener H, Sacco RL, Rundek T, Battistella V, Cheung YK, Elkind MSV. Race and ethnic disparities in stroke incidence in the Northern Manhattan study. Stroke. 2020;51:1064–9. https://doi.org/10.1161/STROKEAHA.119.028806.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Tang X, Laskowitz DT, He L, Østbye T, Bettger JP, Cao Y, et al. Neighborhood socioeconomic status and the prevalence of stroke and coronary heart disease in rural China: a population-based study. Int J Stroke. 2015;10:388–95. https://doi.org/10.1111/ijs.12343.

    Article  PubMed  Google Scholar 

  46. Szőcs I, Bereczki D, Ajtay A, Oberfrank F, Vastagh I. Socioeconomic gap between neighborhoods of Budapest: striking impact on stroke and possible explanations. PLoS One. 2019;14(2):e0212519. https://doi.org/10.1371/journal.pone.0212519.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Pennlert J, Asplund K, Glader EL, Norrving B, Eriksson M. Socioeconomic status and the risk of stroke recurrence: persisting gaps observed in a nationwide Swedish study 2001 to 2012. Stroke. 2017;48:1519–23. https://doi.org/10.1161/STROKEAHA.116.015643.

    Article  Google Scholar 

  48. Zhou LW, Panenka WJ, Jones AA, Gicas KM, Thornton AE, Heran MKS, et al. Prevalence and risk factors of brain infarcts and associations with cognitive performance in tenants of marginal housing. J Am Heart Assoc. 2019;8:e011412. https://doi.org/10.1161/JAHA.118.011412.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Tawakol A, Osborne MT, Wang Y, Hammed B, Tung B, Patrich T, et al. Stress-associated neurobiological pathway linking socioeconomic disparities to cardiovascular disease. J Am Coll Cardiol. 2019;73(25):3243–55. https://doi.org/10.1016/j.jacc.2019.04.042.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Alzheimer’s Association. 2019 Alzheimer’s disease facts and figures. Chicago: Alzheimer’s Association; 2019.

    Book  Google Scholar 

  51. Zuelsdorff M, Larson JL, Hunt JFV, Kim AJ, Koscik RL, Buckingham WR, et al. The area deprivation index: a novel tool for harmonizable risk assessment in Alzheimer’s disease research. Alzheimers Dement. 2020;6(1):e12039. https://doi.org/10.1002/trc2.12039.

    Article  Google Scholar 

  52. Hunt JFV, Buckingham W, Kim AJ, Oh J, Vogt NM, Jonaitis EM, et al. Association of neighborhood-level disadvantage with cerebral and hippocampal volume. JAMA Neurol. 2020;77(4):451–60. https://doi.org/10.1001/jamaneurol.2019.4501.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Gilsanz P, Mayeda ER, Glymour MM, Quesenberry CP, Mungas D, DeCarli CS, et al. Birth in high infant mortality states and dementia risk in a cohort of elderly African American and white health care members. Alzheimer Dis Assoc Disord. 2019;33(1):1–6. https://doi.org/10.1097/WAD.0000000000000270.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Nishizawa T, Morita A, Fujiwara T, Kondo K. Association between childhood socioeconomic status and subjective memory complaints among older adults: results from the Japan Gerontological Evaluation Study 2010. Int Psychogeriatr. 2019;31(12):1699–707. https://doi.org/10.1017/S1041610219000814.

    Article  PubMed  Google Scholar 

  55. Murayama H, Sugiyama M, Inagaki H, Ura C, Miyamae F, Edahiro A, et al. The differential effects of age on the association between childhood socioeconomic disadvantage and subjective symptoms of dementia among older Japanese people. J Epidemiol. 2019;29(7):241–6. https://doi.org/10.2188/jea.JE20180002.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Samuel LJ, Szanton SL, Wolff JL, Ornstein KA, Parker LJ, Gitlin LN. Socioeconomic disparities in six-year incident dementia in a nationally representative cohort of U.S. older adults: an examination of financial resources. BMC Geriatr. 2020;20:156. https://doi.org/10.1186/s12877-020-01553-4.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Chen L, Cao Q. Poverty increases the risk of incident cognitive impairment among older adults: a longitudinal study in China. Aging Ment Health. 2020;24(11):1822–7. https://doi.org/10.1080/13607863.2019.1663491.

    Article  PubMed  Google Scholar 

  58. Cadar D, Lassale C, Davies H, Llewellyn DJ, Batty GD, Steptoe A. Individual and area-based socioeconomic factors associated with dementia incidence in England: evidence from a 12-year follow-up in the English longitudinal study of ageing. JAMA Psychiatry. 2018;75(7):723–32. https://doi.org/10.1001/jamapsychiatry.2018.1012Large-scale population analysis demonstrating that risk of dementia correlates with socioeconomic status. This study examined data from the English Longitudinal Study of Ageing, a prospective cohort study representative of the English population. Researchers demonstrated that the hazard of developing dementia was significantly higher for individuals in the lowest socioeconomic quintiles when compared to the highest quintile when controlling for other variables.

  59. McCann A, McNulty H, Rigby J, Hughes CF, Hoey L, Molloy AM, et al. Effect of area-level socioeconomic deprivation on risk of cognitive dysfunction in older adults. J Am Geriatr Soc. 2018;66(7):1269–75. https://doi.org/10.1111/jgs.15258.

    Article  PubMed  Google Scholar 

  60. Hurstak E, Johnson JK, Tieu L, Guzman D, Ponath C, Lee CT, et al. Factors associated with cognitive impairment in a cohort of older homeless adults: results from the HOPE HOME study. Drug Alcohol Depend. 2017;178:562–70. https://doi.org/10.1016/j.drugalcdep.2017.06.002.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Gicas KM, Jones AA, Thornton AE, Petersson A, Livingston E, Waclawik K, et al. Cognitive decline and mortality in a community-based sample of homeless and precariously housed adults: 9-year prospective study. BJPsych Open. 2020;6(2):e21. https://doi.org/10.1192/bjo.2020.3.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Depp CA, Vella L, Orff HJ, Twamley EW. A quantitative review of cognitive functioning in homeless adults. J Nerv Ment Dis. 2015;203(2):126–31. https://doi.org/10.1097/NMD.0000000000000248.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Kleindorfer D, Lindsell C, Alwell KA, Moomaw CJ, Woo D, Flaherty ML, et al. Patients living in impoverished areas have more severe ischemic strokes. Stroke. 2012;43(8):2055–9. https://doi.org/10.1161/STROKEAHA.111.649608.

    Article  PubMed  PubMed Central  Google Scholar 

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  1. University of Notre Dame, Chicago, IL, USA

    Monica Maalouf, Maureen Fearon, Mary Clare Lipa, Hannah Chow- Johnson, Linda Tayeh & Daniel Lipa

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Maalouf, M., Fearon, M., Lipa, M.C. et al. Neurologic Complications of Poverty: the Associations Between Poverty as a Social Determinant of Health and Adverse Neurologic Outcomes. Curr Neurol Neurosci Rep 21, 29 (2021). https://doi.org/10.1007/s11910-021-01116-z

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