Household interventions for preventing domestic lead exposure in children
Bibliographic record
Abstract
BACKGROUND: Lead poisoning is associated with physical, cognitive and neurobehavioural impairment in children and trials have tested many household interventions to prevent lead exposure. This is an update of the original review by the same authors first published in 2008. OBJECTIVES: To determine the effectiveness of household interventions in preventing or reducing lead exposure in children as measured by reductions in blood lead levels and/or improvements in cognitive development. SEARCH METHODS: We identified trials through electronic searches of CENTRAL (2012, Issue 1), MEDLINE (1948 to January Week 1 2012), EMBASE (1980 to Week 2 2012), CINAHL (1937 to January 2012), PsycINFO (1887 to January Week 2 2012), ERIC (1966 to January 2012), Sociological Abstracts (1952 to January 2012), Science Citation Index (1970 to 20 January 2012), ZETOC (20 January 2012), LILACS (20 January 2012), Dissertation Abstracts (late 1960s to January 2012), ClinicalTrials.gov (19 January 2012), Current Controlled Trials (19 January 2012), Australian New Zealand Clinical Trials Registry (19 January 2012) and the National Research Register Archive. We also contacted experts to find unpublished studies. SELECTION CRITERIA: Randomised and quasi-randomised controlled trials of household educational or environmental interventions to prevent lead exposure in children where at least one standardised outcome measure was reported. DATA COLLECTION AND ANALYSIS: Two authors independently reviewed all eligible studies for inclusion, assessed risk of bias and extracted data. We contacted trialists to obtain missing information. MAIN RESULTS: We included 14 studies (involving 2656 children). All studies reported blood lead level outcomes and none reported on cognitive or neurobehavioural outcomes. We put studies into subgroups according to their intervention type. We performed meta-analysis of both continuous and dichotomous data for subgroups where appropriate. Educational interventions were not effective in reducing blood lead levels (continuous: mean difference (MD) 0.02, 95% confidence interval (CI) -0.09 to 0.12, I(2) = 0 (log transformed); dichotomous ≥ 10µg/dL (≥ 0.48 µmol/L): relative risk (RR) 1.02, 95% CI 0.79 to 1.30, I(2)=0; dichotomous ≥ 15µg/dL (≥ 0.72 µmol/L): RR 0.60, 95% CI 0.33 to 1.09, I(2) = 0). Meta-analysis for the dust control subgroup also found no evidence of effectiveness (continuous: MD -0.15, 95% CI -0.42 to 0.11, I(2) = 0.9 (log transformed); dichotomous ≥ 10µg/dL (≥ 0.48 µmol/L): RR 0.93, 95% CI 0.73 to 1.18, I(2) =0; dichotomous ≥ 15µg/dL (≥ 0.72 µmol/L): RR 0.86, 95% CI 0.35 to 2.07, I(2) = 0.56). When meta-analysis for the dust control subgroup was adjusted for clustering, no statistical significant benefit was incurred. The studies using soil abatement (removal and replacement) and combination intervention groups were not able to be meta-analysed due to substantial differences between studies. AUTHORS' CONCLUSIONS: Based on current knowledge, household educational or dust control interventions are ineffective in reducing blood lead levels in children as a population health measure. There is currently insufficient evidence to draw conclusions about the effectiveness of soil abatement or combination interventions.Further trials are required to establish the most effective intervention for prevention of lead exposure. Key elements of these trials should include strategies to reduce multiple sources of lead exposure simultaneously using empirical dust clearance levels. It is also necessary for trials to be carried out in developing countries and in differing socioeconomic groups in developed countries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".