Evidence map›Paper›PMID 41965589›Full record

ArticleBMC pediatrics2026

Heavy metal exposure and dental caries in children and adolescents: a NHANES-based analysis integrating machine learning approaches.

Haibo Shen, Yan Zhou, Jie Lu, Yao Chu, Xiangyin Liu, Jing Jin

Abstract read
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Article in BMC pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Haibo Shen *Nantong Dental Hospital, No.36, South Yue Long Road, Chongchuan District, Nantong, 226001, China.
Yan Zhou *Nantong Dental Hospital, No.36, South Yue Long Road, Chongchuan District, Nantong, 226001, China.
Jie LuNantong Dental Hospital, No.36, South Yue Long Road, Chongchuan District, Nantong, 226001, China.
Yao ChuNantong Dental Hospital, No.36, South Yue Long Road, Chongchuan District, Nantong, 226001, China.
Xiangyin Liu *Nantong Dental Hospital, No.36, South Yue Long Road, Chongchuan District, Nantong, 226001, China. 404058429@qq.com.
Jing Jin *Nantong Hospital of Integranted Traditional Chinese and Western Medicine, No. 50, Renmin Middle Road, Chongchuan District, Nantong City, Jiangsu Province, 226001, China. 335608711@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDental caries remains a major public health concern among children and adolescents. While established risk factors such as diet and oral hygiene are well recognized, the association between environmental heavy metal exposure and pediatric dental caries is not fully understood. This study examined the relationship between blood heavy metal concentrations and dental caries in a nationally representative pediatric population.

methodsData from 15,194 participants aged 5-19 years were obtained from the National Health and Nutrition Examination Survey (NHANES). Dental caries was assessed using the DMFT/S index. Blood lead, cadmium, and mercury concentrations were measured by inductively coupled plasma mass spectrometry. Multivariable logistic regression models were used to evaluate associations after adjustment for sociodemographic, nutritional, and hematological covariates. Multiple machine learning models were constructed to assess predictive performance, and SHAP values were applied to interpret feature importance.

resultsHigher blood concentrations of lead, cadmium, and mercury were independently associated with increased odds of dental caries (lead: OR = 1.10, 95% CI: 1.02-1.18; cadmium: OR = 1.18, 95% CI: 1.10-1.27; mercury: OR = 1.14, 95% CI: 1.06-1.22). Subgroup analyses demonstrated heterogeneity by age and socioeconomic status, with stronger associations for cadmium observed among adolescents and higher-income groups. Among the machine learning models, XGBoost showed the best predictive performance (AUC = 0.75), with cadmium ranking as the most influential feature.

conclusionBlood heavy metal concentrations were significantly associated with dental caries in children and adolescents, suggesting that environmental exposure may be an important correlate of pediatric caries risk.

Indexed as

Dental CariesEnvironmental ExposureMachine LearningMetals, HeavyAdolescentBoosting Machine Learning AlgorithmsCadmiumChildChild, PreschoolFemaleHumansLeadLogistic ModelsMaleMercuryNutrition SurveysCadmiumLeadMercuryMetals, HeavyChildrenDental cariesHeavy metalsMachine learningNHANES

Identifiers

PMID41965589
PMCPMC13195908

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.