Confounding and causation in the epidemiology of lead.
The National Health and Medical Research Council recently reported that there were not enough high-quality studies to conclude that associations between health effects and blood lead levels <10 μg/dL were caused by lead. It identified uncontrolled confounding, measurement error and other potential c...
| Publicado en: | International Journal of Environmental Health Research Vol. 26; no. 5/6; pp. 467 - 483 |
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| Autores principales: | , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Oct-Dec2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=118353293&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 118353293 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09603123 57L jtl: International Journal of Environmental Health Research issn: 09603123 maglogo: Y pubinfo: dt: Oct-Dec2016 vid: 26 iid: 5/6 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 118353293 118353293 118353293 10.1080/09603123.2016.1161179 118353293 ppf: 467 ppct: 16 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Confounding and causation in the epidemiology of lead. aug: au: Wilson, Ian Harold Wilson, Simon Barton affil: Sustainable Resource Sciences, Chapel Hill, Australia sug: subj: Lead Blood Confounding Variable Epidemiology Bias (Research) Human Measurement Error Loglinear Models Linear Regression Public Health ab: The National Health and Medical Research Council recently reported that there were not enough high-quality studies to conclude that associations between health effects and blood lead levels <10 μg/dL were caused by lead. It identified uncontrolled confounding, measurement error and other potential causal factors as common weaknesses. This paper supports those findings with evidence of uncontrolled confounding by parental education, intelligence or household management from several papers. It suggests that inappropriate statistical tests and aggregation of data representing different exposure routes partly explain why confounding has been overlooked. Inadequate correction of confounding has contributed to incorrect conclusions regarding causality at low levels of lead. Linear or log-linear regression models have tended to mask any threshold. While the effects of higher levels of lead exposure are not disputed, overestimation of health effects at low lead exposures has significant implications for policy-makers endeavouring to protect public health through cost-effective regulations. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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