科研速览 · Science Skim继续刷下去 · Keep skimming →
◆ BMC medical research methodology2026-09-24

Quantifying uncertainty: a practical comparison of Bayesian and frequentist meta-analytic frameworks applied to lead exposure and children's IQ.

Paulina Sell, Margaux Sanchez, Philippe Palmont, Simon Steiger, Dietrich Plass

一句话结论 · In one sentence

Preoperative anemia was independently associated with PO30C under the China criteria, whereas WHO criteria attenuated this association through misclassification of low-risk borderline patients. Population-appropriate diagnostic criteria are important for perioperative risk estimation and may explain conflicting findings in the existing literature.

原始摘要(英文原文)· Original abstract
BACKGROUND: Uncertainty quantification is central to evidence synthesis for risk assessment and policy-making. Frequentist meta-analysis - currently predominant in epidemiology - quantifies uncertainty through confidence intervals, while Bayesian meta-analysis provides posterior distributions. We performed frequentist and Bayesian meta-analyses to compare uncertainty quantification and applicability for risk assessment using lead exposure and children's IQ as a case study. METHODS: We systematically searched PubMed and Scopus for epidemiological studies on blood lead level (BLL) and IQ score in children. After screening, risk of bias (RoB) in the identified studies was assessed and regression coefficients were harmonised to the [Formula: see text] scale. In both meta-analyses, we included the same effect estimates, assumed a multilevel structure and used random-effects models. The Bayesian meta-analysis employed a hierarchical model with weakly-informative priors. Sensitivity analyses examined robustness to RoB and prior specification. [Formula: see text] and [Formula: see text] were estimated as measures of between-study heterogeneity. RESULTS: Twelve studies were included in the meta-analysis. The frequentist model yielded a pooled estimate of -2.45 (95% confidence interval: -3.82 to -1.08) IQ points per unit increase in [Formula: see text]-transformed BLL (µg/dL) and a 95% predictive interval of -6.53 to 1.53. The Bayesian model yielded a mean pooled estimate of -2.28 (95% credible interval: -3.54 to -1.04) and a 95% predictive interval of -6.28 to 1.69. Between-study heterogeneity was substantial (frequentist: [Formula: see text] = 3.32, [Formula: see text] = 85.0%; Bayesian: posterior median [Formula: see text] = 3.26, [Formula: see text] = 84.7%). The Bayesian approach provided a full posterior distribution for heterogeneity, directly quantifying uncertainty from between-study variation. Sensitivity analyses showed both meta-analyses were robust to RoB, and Bayesian estimates were insensitive to tested priors. Depending on the specified prior configuration, the Bayesian model was less sensitive to studies reporting substantial uncertainty, resulting in a lower pooled effect compared to the frequentist model. This regularisation is particularly valuable in small meta-analyses, where frequentist heterogeneity estimates can be unstable. CONCLUSIONS: We provide updated pooled estimates for the effect of lead on children's IQ. The Bayesian framework provides posterior distributions, enabling direct probability statements, e.g. about exceeding risk thresholds, and comparative assessments between pollutants. These features are particularly valuable for risk assessment and policy-making.
读原文 · Read the paper ↗

AI 追问PRO

登录后使用 AI 追问

讨论区

登录后参与讨论

相关论文 · Related

Quantifying uncertainty: a practical comparison of Bayesian and frequentist meta-analytic frameworks applied to lead exposure and children's IQ. — 科研速览 Science Skim