Annals of Occupational and Environmental Medicine

  • Volume 35
  • /
  • Pages.23.1-23.14
  • /
  • 2023
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  • 1225-3618(pISSN)
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  • 2052-4374(eISSN)
The Korean Society of Occupational & Environmental Medicine (대한직업환경의학회)
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Association of heavy metal complex exposure and neurobehavioral function of children

  • Minkeun Kim (Department of Occupational and Environmental Medicine, Yeungnam University Medical Center) ;
  • Chulyong Park (Department of Occupational and Environmental Medicine, Yeungnam University Medical Center) ;
  • Joon Sakong (Department of Occupational and Environmental Medicine, Yeungnam University Medical Center) ;
  • Shinhee Ye (Occupational Safety and Health Research Institute, Korea Occupational Safety and Health Agency) ;
  • So young Son (Department of Occupational and Environmental Medicine, Yeungnam University Medical Center) ;
  • Kiook Baek (Department of Occupational and Environmental Medicine, Yeungnam University Medical Center)
  • Received : 2022.12.21
  • Accepted : 2023.05.20
  • Published : 2023.12.31
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Abstract

Background: Exposure to heavy metals is a public health concern worldwide. Previous studies on the association between heavy metal exposure and neurobehavioral functions in children have focused on single exposures and clinical manifestations. However, the present study evaluated the effects of heavy metal complex exposure on subclinical neurobehavioral function using a Korean Computerized Neurobehavior Test (KCNT). Methods: Urinary mercury, lead, cadmium analyses as well as symbol digit substitution (SDS) and choice reaction time (CRT) tests of the KCNT were conducted in children aged between 10 and 12 years. Reaction time and urinary heavy metal levels were analyzed using partial correlation, linear regression, Bayesian kernel machine regression (BKMR), the weighted quantile sum (WQS) regression and quantile G-computation analysis. Results: Participants of 203 SDS tests and 198 CRT tests were analyzed, excluding poor cooperation and inappropriate urine sample. Partial correlation analysis revealed no association between neurobehavioral function and exposure to individual heavy metals. The result of multiple linear regression shows significant positive association between urinary lead, mercury, and CRT. BMKR, WQS regression and quantile G-computation analysis showed a statistically significant positive association between complex urinary heavy metal concentrations, especially lead and mercury, and reaction time. Conclusions: Assuming complex exposures, urinary heavy metal concentrations showed a statistically significant positive association with CRT. These results suggest that heavy metal complex exposure during childhood should be evaluated and managed strictly.

Keywords

Acknowledgement

This research was supported by the Inha University Hospital's Environmental Health Center for Training Environmental Medicine Professionals funded by the Ministry of Environment, Republic of Korea (2022).

References

  1. Centers for Disease Control and Prevention. Fourth national report on human exposure to environmental chemicals updated tables. Updated 2017. Accessed March 28, 2023. http://www.cdc.gov/exposurereport. 
  2. Korea Centers for Disease Control and Prevention. Korea National Health and Nutrition Examination Survey, 7th ed (2016-2018). Updated 2018. Accessed March 28, 2023 https://knhanes.kdca.go.kr/knhanes/sub03/sub03_02_05.do. 
  3. Goyer RA. Results of lead research: prenatal exposure and neurological consequences. Environ Health Perspect 1996;104(10):1050-4.
  4. Lozano M, Murcia M, Soler-Blasco R, Gonzalez L, Iriarte G, Rebagliato M, et al. Exposure to mercury among 9-year-old children and neurobehavioural function. Environ Int 2021;146:106173.
  5. Gorini F, Muratori F, Morales MA. The role of heavy metal pollution in neurobehavioral disorders: a focus on autism. Rev J Autism Dev Disord 2014;1(4):354-72.
  6. Farina M, Aschner M, Rocha JB. Oxidative stress in MeHg-induced neurotoxicity. Toxicol Appl Pharmacol 2011;256(3):405-17.
  7. Ramirez Ortega D, Gonzalez Esquivel DF, Blanco Ayala T, Pineda B, Gomez Manzo S, Marcial Quino J, et al. Cognitive impairment induced by lead exposure during lifespan: mechanisms of lead neurotoxicity. Toxics 2021;9(2):23.
  8. Aguinis H, Gottfredson RK, Joo H. Best-practice recommendations for defining, identifying, and handling outliers. Organ Res Methods 2013;16(2):270-301.
  9. Occupational Safety and Health Research Institute (KR). A Research on Utilization of Korean Computerized Neurobehavioral Test in Workers' Health Check. (2020-Occupational Safety and Health Research Institute-680). Incheon, Korea: Occupational Safety and Health Research Institute; 2020. 
  10. Chung JH, Kim CY, Sakong J. A computer-administered neurobehavioral evaluation of workers exposed to organic solvents. Korean J Occup Environ Med 1994;6(2):219-41.
  11. Chaumont A, Nickmilder M, Dumont X, Lundh T, Skerfving S, Bernard A. Associations between proteins and heavy metals in urine at low environmental exposures: evidence of reverse causality. Toxicol Lett 2012;210(3):345-52.
  12. Barr DB, Wilder LC, Caudill SP, Gonzalez AJ, Needham LL, Pirkle JL. Urinary creatinine concentrations in the U.S. population: implications for urinary biologic monitoring measurements. Environ Health Perspect 2005;113(2):192-200.
  13. Chen L, Sun Q, Peng S, Tan T, Mei G, Chen H, et al. Associations of blood and urinary heavy metals with rheumatoid arthritis risk among adults in NHANES, 1999-2018. Chemosphere 2022;289:133147.
  14. Tennant PW, Murray EJ, Arnold KF, Berrie L, Fox MP, Gadd SC, et al. Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations. Int J Epidemiol 2021;50(2):620-32.
  15. Bobb JF, Claus Henn B, Valeri L, Coull BA. Statistical software for analyzing the health effects of multiple concurrent exposures via Bayesian kernel machine regression. Environ Health 2018;17(1):67.
  16. Carrico C, Gennings C, Wheeler DC, Factor-Litvak P. Characterization of weighted quantile sum regression for highly correlated data in a risk analysis setting. J Agric Biol Environ Stat 2015;20(1):100-20.
  17. Keil AP, Buckley JP, O'Brien KM, Ferguson KK, Zhao S, White AJ. A quantile-based g-computation approach to addressing the effects of exposure mixtures. Environ Health Perspect 2020;128(4):47004.
  18. Feng C, Wang H, Lu N, Chen T, He H, Lu Y, et al. Log-transformation and its implications for data analysis. Shanghai Arch Psychiatry 2014;26(2):105-9.
  19. Mendez-Armenta M, Rios C. Cadmium neurotoxicity. Environ Toxicol Pharmacol 2007;23(3):350-8.
  20. Ouyang L, Li Q, Rao S, Su R, Zhu Y, Du G, et al. Cognitive outcomes caused by low-level lead, cadmium, and mercury mixture exposure at distinct phases of brain development. Food Chem Toxicol 2023;175:113707. 
  21. Chang Z, Qiu J, Wang K, Liu X, Fan L, Liu X, et al. The relationship between co-exposure to multiple heavy metals and liver damage. J Trace Elem Med Biol 2023;77:127128.
  22. Tian X, Shan X, Ma L, Zhang C, Wang M, Zheng J, et al. Mixed heavy metals exposure affects the renal function mediated by 8-OHG: a cross-sectional study in rural residents of China. Environ Pollut 2023;317:120727.
  23. Capelo R, Rohlman DS, Jara R, Garcia T, Vinas J, Lorca JA, et al. Residence in an area with environmental exposure to heavy metals and neurobehavioral performance in children 9-11 years old: an explorative study. Int J Environ Res Public Health 2022;19(8):4732.
  24. Bellinger DC, Trachtenberg F, Barregard L, Tavares M, Cernichiari E, Daniel D, et al. Neuropsychological and renal effects of dental amalgam in children: a randomized clinical trial. JAMA 2006;295(15):1775-83.
  25. Wu L, Cui F, Zhang S, Ding X, Gao W, Chen L, et al. Associations between multiple heavy metals exposure and neural damage biomarkers in welders: a cross-sectional study. Sci Total Environ 2023;869:161812.
  26. Bellavia A. Statistical methods for environmental mixtures. Updated 2021. Accessed December 13, 2022. https://bookdown.org/andreabellavia/mixtures. 
  27. Liu SH, Bobb JF, Lee KH, Gennings C, Claus Henn B, Bellinger D, et al. Lagged kernel machine regression for identifying time windows of susceptibility to exposures of complex mixtures. Biostatistics 2018;19(3):325-41.
  28. Clarkson TW, Magos L. The toxicology of mercury and its chemical compounds. Crit Rev Toxicol 2006;36(8):609-62.
  29. Iregren A, Gamberale F, Kjellberg A. SPES: a psychological test system to diagnose environmental hazards. Swedish Performance Evaluation System. Neurotoxicol Teratol 1996;18(4):485-91.
  30. Kim YC, Jeon MJ, Hong YC, Lee CG, Ha MN, Kwon HJ, et al. Association between blood lead concentration and computerized neurobehavioral performance in Korean elementary school students. Korean J Occup Environ Med 2011;23(2):183-91.
  31. Park KS, Park JY, Sakong J. Relationship between blood lead concentration and neurobehavioral function of children. Korean J Occup Environ Med 2009;21(2):131-42.
  32. Sakong J, Jeon MJ, Yun SH, Hong YC, Lee CG, Kim Y, et al. Association of blood mercury level and neurobehavioral performance in Korean elementary school students. Ann Occup Environ Med 2010;22(4):324-30. 
  33. Ministry of Environment. Korean National Environmental Health Survey. Updated 2020. Accessed March 28, 2023. https://knhanes.kdca.go.kr/knhanes/sub03/sub03_02_05.do. 
  34. Kim HR, Lee YA, Kim JH, Seo S, Gong BJ, Park JM, et al. Characteristics of heavy metal concentration and emission location estimation in fine dust in around pohang industrial complex. J Korean Soc Urban Environ 2020;20(4):343-57. 
  35. Kim GB, Song SH, Cho YS, Kang TS, Jo HJ, Cheon SH, et al. Study on the Exposure Assessment of Residents Near Smelter Industry. Incheon, Korea: National Institute of Environmental Research; 2012. 
  36. Kim DM, Kim KH. The changes in obesity prevalence and dietary habits in Korean adults by residential area during the last 10 years-Based on the 4 th (2007-2009) and the 7 th (2016-2018) Korea national health and nutrition examination survey data. Korean J Community Nutr 2021;26(1):37-47.