The relationship between childhood blood lead levels below 5 µg/dL and childhood intelligence quotient (IQ): Protocol for a systematic review and meta-analysis

BACKGROUND

The causal association between childhood lead (Pb) exposure and decrements in intelligence quotient (IQ) is well-established, and no safe blood lead level (BLL) in children has been identified. An international pooled analysis of seven prospective studies published by Lanphear et al. in 2005 quantified the relationship between childhood BLL and IQ. Further studies of Pb and IQ have been published more recently with mean BLLs generally lower than in the studies analyzed by Lanphear et al. In this article, we present the protocol for a systematic review to estimate an updated Pb-IQ relationship focusing on BLLs below 5 µg per deciliter (µg/dL).

STUDY QUESTION

What is the quantitative relationship between childhood BLLs and IQ at ages 3-17 years at BLLs below 5 μg/dL?

DATA SOURCES

A comprehensive search of the scientific literature will utilize citation mapping and key word searching. In the citation mapping approach, we will identify seed references that are relevant to our study question, and will then identify more recent references that have cited at least one of the seed references. The key word search will be conducted in the PubMed, Biosis Previews, Scopus, and Web of Science databases. We will also search electronic grey literature databases for conference proceedings, dissertations, and preprints.

STUDY ELIGIBILITY CRITERIA, STUDY SCREENING AND DATA EXTRACTION

We will include studies that measured BLL in children at any age, assessed full-scale IQ of the same children (concurrent with or subsequent to BLL sample collection) at ages 3-17, and estimated a continuous quantitative relationship between BLL and IQ. We will consider only studies with a central tendency BLL < 10 µg/dL. The title and abstract of each record will be reviewed independently by two authors to determine whether the study in question satisfies the inclusion criteria. The full text of each article remaining after title-abstract screening will be reviewed independently by two authors to determine whether the study in question satisfies the inclusion criteria. Two authors will independently extract study characteristics and data from each included study.

RISK OF BIAS ASSESSMENT

Studies meeting inclusion criteria will be evaluated for risk of bias (RoB) using the Navigation Guide method applied in a previous systematic review of neurodevelopmental effects (Lam et al., 2017), with adaptation to our study question. Each study will be independently evaluated by two review authors.

DATA ANALYSIS AND SYNTHESIS

We intend to conduct a random-effects meta-analysis to summarize the effects of children's exposure to Pb on IQ scores. Additionally, we plan to perform sensitivity analyses using sub-group analyses and/or meta-regression techniques to assess the impact of study design and study population characteristics to examine potential heterogeneity of results across studies. We will assign a confidence level rating (high, moderate, low, or very low) to the effect estimate from the meta-analyses/meta-regressions.

Does short-term, airborne lead exposure during pregnancy affect birth outcomes? Quasi-experimental evidence from NASCAR's deleading policy

BACKGROUND

There is evidence of a weak placental-fetal barrier to lead, suggesting that maternal lead exposure could affect the fetus. The health consequences for newborns from in utero lead exposure are not well understood.

OBJECTIVES

We estimated the effects by trimester, of short-term (<1 week), airborne lead exposure during pregnancy on birth outcomes.

METHODS

We use quasi-experimental variation in airborne lead exposure during pregnancy, based on NASCAR's deleading of racing fuel in 2007, in a difference-in-differences model, to estimate the effect of deleading on the birth outcomes of all live births (n = 147,673) in the Charlotte-Concord-Gastonia Metropolitan Statistical Area between 2004 and 2009.

RESULTS

After deleading, children born to mothers residing <4000 m of Charlotte Motor Speedway (relative to those residing >10,000 m) experienced an average increase in birthweight (BW) of 102.50 g [P < 0.001]. The probability of low birthweight (LBW) declined by 0.045 [P = 0.001], preterm (PRE) births by 0.03 [P = 0.04], and small for gestational age (SGA) by 0.04 [P = 0.002]. We find that benefits accrue primarily in preterm LBW and SGA babies, and from decreased lead exposure in the first trimester.

CONCLUSIONS

Short-term exposure to airborne lead during pregnancy adversely affects birth outcomes. Reducing even very brief exposure to airborne lead during pregnancy may improve birth outcomes.

Superfund Cleanups and Children's Lead Exposure

This study evaluates the effect of EPA's Superfund cleanup program on children's lead exposure. We linked two decades of blood lead level (BLL) measurements from children in six states with data on Superfund sites and other lead risk factors. We used quasi-experimental methods to identify the causal effect of proximity to Superfund cleanups on rates of elevated BLL. We estimated a difference-in-difference model comparing the change in elevated BLL of children closer to versus farther from lead-contaminated sites before, during, and after cleanup. We also estimated a triple difference model including children near hazardous sites with minimal to no lead contamination as a comparison group. We used spatial fixed effects and matching to minimize potential bias from unobserved differences between the treatment and comparison groups. Results indicate that Superfund cleanups lowered the risk of elevated BLL for children living within 2 kilometers of lead-contaminated sites 13 to 26 percent.

Early childhood lead exposure and the persistence of educational consequences into adolescence

BACKGROUND

There is consensus that early childhood lead exposure causes adverse cognitive and behavioral effects, even at blood lead levels (BLL) below 5 μg/dL. What has not been established is to what extent the effects of childhood lead exposure persist across grades.

OBJECTIVE

To measure the effects of early childhood lead exposure (BLL 1-10 μg/dL) on educational performance from grades 3-8; to determine if effects in lower grades persist as a child progresses through school; and if so, to characterize the pattern of persistence.

METHODS

We examine data from 560,624 children living in North Carolina between 2000 and 2012 with a BLL ≤10 μg/dL measured between age 0-5 years. Children are matched to their standardized math and reading scores for grades 3-8, creating an unbalanced panel of 2,344,358 student-year observations. We use socio-economic, demographic, and school information along with matching techniques to control for confounding effects.

RESULTS

We find that early childhood exposure to low lead levels caused persistent deficits in educational performance across grades. In each grade (3-8), children with higher blood lead levels had, on average, lower percentile scores in both math and reading than children with lower blood lead levels. In our primary model, we find that children with BLL = 5 μg/dL in early childhood ranked 0.90-1.20 (1.35-1.55) percentiles lower than children with BLL ≤ 1 μg/dL on math (reading) tests during grades 3-8. As children progressed through school, the average percentile deficit in their test scores remained stable.

CONCLUSIONS

Our study shows that the adverse effects of early childhood exposure to low lead levels persist through early adolescence, and that the magnitude of the test-score percentile deficit remains steady between grades 3-8.

How Do Data Centers Make Energy-Efficiency Investment Decisions? Qualitative Evidence from Focus Groups and Interviews 1

The data center industry is one of the fastest growing energy users in the US. While the industry has improved its energy efficiency over the past decade, engineering analyses suggest that ample opportunities remain to reduce energy use that would save firms money. This study explores whether and why data centers might limit investment in energy efficiency. Given the scarcity of empirical data in this context, we conducted focus groups and interviews with data center managers to elicit information about factors affecting their investments and used content analysis to qualitatively evaluate the results. Split incentives between departments within companies and between colocation data centers and their tenants, imperfect information about the performance of new technologies, and tradeoffs with data center reliability were the most pervasive factors discussed by participants. While we find some evidence that market failure explanations such as split incentives and imperfect information had a limited role in slowing adoption for participants, rival explanations such as the cost of acquiring context-specific information, and opportunity costs associated with alternate uses of funds or highly valued attributes played a larger role in slowing investment in energy efficiency.

Adaptation, Sea Level Rise, and Property Prices in the Chesapeake Bay Watershed

Coastal communities are facing the dual threat of increasing sea level rise (SLR) and swelling populations, causing challenging policy problems. To help inform policy makers, this paper explores the property price impact of structures that help protect against SLR using a novel and spatially explicit dataset of coastal features. Results indicate that adaptation structures can have a significant positive impact on waterfront home prices, with the most vulnerable homes seeing the largest impacts. The Chesapeake Bay is facing increasing pressure from SLR, and this is one of the first papers to report that local property markets are incorporating that threat.

Improving Water Quality in an Iconic Estuary: An Internal Meta-analysis of Property Value Impacts around the Chesapeake Bay

This study conducts a meta-analysis and benefit transfer of the value of water clarity in the Chesapeake Bay estuary to estimate the property value impacts of pollution reduction policies. Estimates of the value of water clarity are derived from separate hedonic property value analyses of 14 counties bordering the Bay. The meta-analysis allows us to: 1) estimate the average effect of water clarity in the Chesapeake Bay, 2) investigate heterogeneity of effects across counties based on socioeconomic and ecological factors, 3) evaluate different measures of water clarity used in the original hedonic equations, and 4) transfer the values to Bayfront counties in nearby jurisdictions to estimate the property value impacts of the Total Maximum Daily Load (TMDL), a policy to reduce nutrient and sediment pollution entering the Bay that is expected to improve water clarity and ecological health. We also investigate the in-sample and out-of-sample predictive power of different transfer strategies and find that a simpler unit value transfer can outperform more complex function transfers. We estimate that aggregate near-waterfront property values could increase by roughly $400 million to $700 million in response to water clarity improvements from the TMDL.