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Educational interventions for preventing lead poisoning in workers

2020· article· en· W2886687706 on OpenAlexaff
Sara Allaouat, Viraj K. Reddy, Kimmo Räsänen, Sohaib Khan, Mieke E. G. L. Lumens

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy Metal Exposure and Toxicity
Canadian institutionsUniversity of ManitobaGeorge & Fay Yee Centre for Healthcare Innovation
Fundersnot available
KeywordsMedicineLead poisoningPsychological interventionRandomized controlled trialZinc protoporphyrinIntensive care medicineInternal medicinePsychiatry

Abstract

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BACKGROUND: Occupational lead exposure can lead to serious health effects that range from general symptoms (depression, generalised ache, and digestive signs, such as loss of appetite, stomach ache, nausea, diarrhoea, and constipation) to chronic conditions (cerebrovascular and cardiovascular diseases, cognitive impairment, kidney disease, cancers, and infertility). Educational interventions may contribute to the prevention of lead uptake in workers exposed to lead, and it is important to assess their effectiveness. OBJECTIVES: To assess the effect of educational interventions for preventing lead uptake in workers exposed to lead. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, CINAHL, and OSH UPDATE to 5 June 2020, with no language restrictions. SELECTION CRITERIA: We sought randomised controlled trials (RCT), cluster-RCTs (cRCT), interrupted time series (ITS), controlled before-after studies (CBA) and uncontrolled before-after studies that examined the effects of an educational intervention aimed at preventing lead exposure and poisoning in workers who worked with lead, for which effectiveness was measured by lead levels in blood and urine, blood zinc protoporphyrin levels and urine aminolevulinic acid levels. DATA COLLECTION AND ANALYSIS: Two review authors independently screened the search results, assessed studies for eligibility, and extracted data using standard Cochrane methods. We used the ROBINS-I tool to assess the risk of bias, and GRADE methodology to assess the certainty of the evidence. MAIN RESULTS: We did not find any RCT, cRCT, ITS or CBA studies that met our criteria. We included four uncontrolled before-after studies studies, conducted between 1982 and 2004. Blood lead levels Educational interventions may reduce blood lead levels, but the evidence is very uncertain. In the short-term after the educational intervention, blood lead levels may decrease (mean difference (MD) 9.17 µg/dL, 95% confidence interval (CI) 4.14 to 14.20; one study with high baseline blood lead level, 18 participants; very low-certainty evidence). In the medium-term, blood lead levels may decrease (MD 3.80 µg/dL, 95% CI 1.48 to 6.12; one study with high baseline blood lead level, 34 participants; very low-certainty evidence). In the long-term, blood lead levels may decrease when the baseline blood lead levels are high (MD 8.08 µg/dL; 95% CI 3.67 to 12.49; two studies, 69 participants; very low-certainty evidence), but not when the baseline blood lead levels are low (MD 1.10 µg/dL, 95% CI -0.11 to 2.31; one study, 52 participants, very low-certainty evidence). Urine lead levels In the long-term, urinary lead levels may decrease after the educational intervention, but the evidence is very uncertain (MD 42.43 µg/L, 95% CI 29.73 to 55.13; one study, 35 participants; very low-certainty evidence). Behaviour change The evidence is very uncertain about the effect of educational intervention on behaviour change. At medium-term follow-up after the educational intervention, very low-certainty evidence from one study (89 participants) found inconclusive results for washing before eating (risk ratio (RR) 1.71, 95% CI 0.42 to 6.91), washing before drinking (RR 1.37, 95% CI 0.61 to 3.06), and not smoking in the work area (RR 1.04, 95% CI 0.74 to 1.46). Very low-certainty evidence from one study (21 participants) suggested that employers may improve the provision of fit testing for all respirator users (RR 1.87, 95% CI 1.16 to 3.01), and prohibit eating, drinking, smoking, and other tobacco use in the work area (RR 4.25, 95% CI 1.72 to 10.51), however, the results were inconclusive for the adequate provision of protective clothing (RR 1.40, 95% CI 0.82 to 2.40). At long-term follow-up, very low-certainty evidence from one study (89 participants) suggested that workers may improve washing before drinking (RR 3.24, 95% CI 1.09 to 9.61), but results were inconclusive for washing before eating (RR 11.71, 95% CI 0.66 to 208.33), and for not smoking in the work area (RR 1.56, 95% CI 0.98 to 2.50). Very low-certainty evidence from one study (21 participants) suggested that employers may improve the provision of fit testing for all respirator users (RR 1.70, 95% CI 1.09 to 2.63), may provide adequate protective clothing (RR 2.80, 95% CI 1.23 to 6.37), and may prohibit eating, drinking, smoking, and other tobacco use in the work area (RR 2.13, 95% CI 1.19 to 3.81). Improved knowledge or awareness of the adverse health effects of lead The evidence is very uncertain about the effect of educational intervention on workers' knowledge. At medium-term follow-up, questionnaires found that workers' knowledge may improve (MD 5.20, 95% CI 3.29 to 7.11; one study, 34 participants; very low-certainty evidence). At long-term follow-up, there may be an improvement in workers' knowledge (MD 5.80, 95% CI 3.89 to 7.71; one study, 34 participants; very low-certainty evidence), but results were inconclusive for employers' knowledge (RR 1.67, 95% CI 0.74 to 3.75; one study, 21 participants; very low-certainty evidence). None of the studies measured the other outcomes of interest: blood zinc protoporphyrin levels, urine aminolevulinic acid levels, air lead levels, and harms. One study provided the costs of each component of the intervention. AUTHORS' CONCLUSIONS: Educational interventions may prevent lead poisoning in workers with high baseline blood lead levels and urine lead levels but this is uncertain. Educational interventions may not prevent lead poisoning in workers with low baseline blood lead levels but this is uncertain.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score0.704

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.134
GPT teacher head0.378
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations6
Published2020
Admission routes1
Has abstractyes

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