Heavy Metal Index
Ask the IndexAboutIndex Pro

Association between heavy metals exposure (cadmium, lead, arsenic, mercury) and child autistic disorder: a systematic review and meta-analysis

Cite this pageVersion history

Overview

This Frontiers in Pediatrics meta-analysis pooled 53 case-control studies (5,054 participants; 2,533 ASD cases and 2,521 healthy controls, all aged <18) to test whether children with Autistic Disorder carry higher body burdens of cadmium, lead, arsenic, and mercury than healthy controls. Hair, blood, urine, fingernail, and tooth measurements were extracted from primary studies indexed in PubMed, Web of Science, Embase, and the Cochrane Library from inception through October 2022. The pooled standardized mean differences show ASD children carry significantly higher Pb, As, and Hg body burdens (P<0.001 for each) than healthy controls; Cd did not separate the two groups overall (P>0.05) but did differ by region. Effect direction varied strongly by geographic region: ASD-control differences were largest in Asian and European studies and reversed in North American studies for Cd, As, and Hg.

Key numbers

Pooled sample (Table 1; PRISMA flow on Figure 6):

  • 1,374 records identified (PubMed 372, Embase 341, Web of Science 645, Cochrane 16); 574 duplicates removed; 800 screened; 89 sought for retrieval; 53 included.
  • 53 included case-control studies; 5,054 total participants (2,533 ASD, 2,521 controls).
  • Geographic distribution of included studies: 12 North America, 19 Asia, 20 Europe, 1 Australia, 1 Africa.
  • All included studies scored ≥6 on the Newcastle-Ottawa Scale; mean NOS score 7.1.

Cadmium (22 studies, random-effects model, I²=92.1%, P_heterogeneity<0.001):

  • Overall: SMD = 0.17, 95% CI (−0.18, 0.51), P>0.05 (not significant).
  • By detection source (Table 2): hair 13 studies, SMD 0.22 (−0.33, 0.77), P=0.429; blood 7 studies, SMD 0.21 (−0.36, 0.77), P=0.476; urine 5 studies, SMD −0.05 (−0.69, 0.59), P=0.879.
  • By region (Table 2): North America 5 studies, SMD −0.52 (−1.04, −0.01), P=0.048; Asia 9 studies, SMD 0.61 (−0.18, 1.40), P=0.128; Europe 9 studies, SMD 0.12 (−0.18, 0.42), P=0.430.

Lead (41 studies, random-effects model, I²=96.7%, P_heterogeneity<0.001):

  • Overall: SMD = 1.16, 95% CI (0.76, 1.55), P<0.001 (ASD > controls).
  • By detection source: hair 20 studies, SMD 1.56 (0.85, 2.28), P<0.001; fingernails SMD 4.49 (3.51, 5.46), P<0.05; blood 16 studies, SMD 1.23 (0.70, 1.77), P<0.001; urine 7 studies, SMD −0.28 (−1.09, 0.53), P=0.497; teeth SMD −0.03 (−0.64, 0.59), P>0.05.
  • By region (Table 2): North America 7 studies, SMD 0.27 (−0.08, 0.61), P=0.130; Asia 16 studies, SMD 1.77 (0.85, 2.69), P<0.001; Europe 17 studies, SMD 1.08 (0.53, 1.63), P<0.001.
  • Significant publication bias (Begg’s P=0.002, Egger’s P<0.001); Trim-and-Fill did not change conclusions.

Arsenic (16 studies, random-effects model, I²=97.3%, P_heterogeneity<0.001):

  • Overall: SMD = 1.40, 95% CI (0.75, 2.05), P<0.001 (ASD > controls).
  • By detection source: hair 9 studies, SMD 1.41 (0.45, 2.37), P<0.05; urine 3 studies, SMD 0.34 (0.00, 0.68), P=0.051; blood 6 studies, SMD 1.98 (0.59, 3.37), P<0.05.
  • By region (Table 2): North America 2 studies, SMD −0.09 (−0.33, 0.15), P=0.464; Asia 7 studies, SMD 2.49 (1.07, 3.90), P=0.001; Europe 6 studies, SMD 1.19 (0.40, 1.99), P=0.003.

Mercury (34 studies, random-effects model, I²=94.6%, P_heterogeneity<0.001):

  • Overall: SMD = 0.74, 95% CI (0.44, 1.03), P<0.001 (ASD > controls).
  • By detection source (Table 2): hair 20 studies, SMD 0.91 (0.35, 1.48), P=0.001; blood 13 studies, SMD 0.77 (0.35, 1.19), P<0.001; urine 20 studies, SMD 0.29 (0.11, 0.47), P=0.002; fingernails SMD 1.22 (0.60, 1.83), P<0.05; teeth SMD 0.40 (−0.42, 1.21), P>0.05.
  • By region (Table 2): North America 8 studies, SMD −0.02 (−0.62, 0.59), P=0.951; Asia 13 studies, SMD 1.55 (0.82, 2.29), P<0.001; Europe 12 studies, SMD 0.55 (0.24, 0.86), P<0.001.
  • Significant publication bias (Begg’s P=0.002, Egger’s P=0.008); Trim-and-Fill did not change conclusions.

Sensitivity analysis (leave-one-out, Figure 3) did not reverse the pooled direction for any of the four metals.

Methods (brief)

PRISMA-aligned systematic review and meta-analysis. Search: PubMed, Embase, Web of Science, and Cochrane Library from inception through October 2022 with terms combining “Autistic Disorder” OR “Autism” AND “Cadmium” OR “Lead” OR “arsenic” OR “mercury” (full strategy in Supplementary File S1). Inclusion required ASD patients <18, case-control design with healthy-control comparison, at least one of the four target metals measured. Animal studies, in-vitro work, non-English papers, and studies without extractable full-text data were excluded. Two reviewers independently scored study quality with the Newcastle-Ottawa Scale (NOS); disagreements were resolved by discussion. Effect sizes were standardized mean differences (SMD) with 95% confidence intervals, computed in Stata 15.0 (StataCorp). Heterogeneity was assessed by Cochran’s Q and I²; random-effects modeling was used when I² > 50% (this applied to every metal). Subgroup analyses were prespecified for geographic region and biological matrix (hair, blood, urine, fingernails, teeth). Publication bias was tested with Begg’s and Egger’s; Trim-and-Fill was applied when bias was detected. The included primary studies used a mix of analytical methods at the underlying level: Atomic Absorption Spectrometry (AAS), Inductively Coupled Plasma Mass Spectrometry (ICP-MS), Flame Atomic Absorption Spectrometry (FAAS), Automatic Biochemical Analysis (ABA), and Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES). The authors’ subgroup analysis indicates the choice of analytical method did not drive the ASD-vs-control direction. Speciation: included primary studies overwhelmingly reported total arsenic and total mercury rather than inorganic-arsenic or methylmercury-specific measurements, so the pooled estimates reflect tAs and tHg.

Implications

  • Certification (HMTc): Exposure-side evidence rather than food-contamination evidence. Contributes pooled biomarker-elevation data linking ASD case status to higher body burdens of Pb (SMD 1.16), As (SMD 1.40), and Hg (SMD 0.74) versus healthy controls; the Cd null result overall, with reversed direction in North America, is part of the same evidence base. This is the population-health context that threshold-setting workflows draw on; the paper does not propose threshold values and neither does this page.
  • Courses: Useful as a teachable example of high-heterogeneity meta-analysis where geographic subgroup analysis materially changes the conclusion. The North America vs Asia/Europe split (with North American studies showing lower or null ASD-control differences for Cd, As, and Hg) is a useful case study for regulatory-affairs audiences working across jurisdictions.
  • App: Does not contribute to ingredient contamination_profile values. This is biomarker/exposure data, not food-occurrence data.
  • Microbiome: The discussion (section 4.4) notes that altered gut flora in ASD children (related to antibiotic use and to glutathione/GSH levels) may compromise Hg excretion via reduced demethylation of methylmercury, contributing to higher body burdens. This is a literature-citation framing within the discussion, not an original measurement; relevant context for the metals-microbiome-neurodevelopment axis but secondary to the meta-analytic findings.

Update history

No substantive edit history is available in this build. The full commit record is available in git.

Referenced by