Explaining variation in elevated blood lead levels among children in Minnesota using neighborhood socioeconomic variables

Individual and Neighborhood Level Predictors of Children's Exposure to Residential Greenspace

Inequities in urban greenspace have been identified, though patterns by race and socioeconomic status vary across US settings. We estimated the magnitude of the relationship between a broad mixture of neighborhood-level factors and residential greenspace using weighted quantile sum (WQS) regression, and compared predictive models of greenspace using only neighborhood-level, only individual-level, or multi-level predictors. Greenspace measures included the Normalized Difference Vegetation Index (NDVI), tree canopy, and proximity of the nearest park, for residential locations in Shelby County, Tennessee of children in the CANDLE cohort. Neighborhood measures include socioeconomic and education resources, as well as racial composition and racial residential segregation. In this sample of 1012 mother-child dyads, neighborhood factors were associated with higher NDVI and tree canopy (0.021 unit higher NDVI [95% CI: 0.014, 0.028] per quintile increase in WQS index); homeownership rate, proximity of and enrollment at early childhood education centers, and racial composition, were highly weighted in the WQS index. In models constrained in the opposite direction (0.028 unit lower NDVI [95% CI: - 0.036, - 0.020]), high school graduation rate and teacher experience were highly weighted. In prediction models, adding individual-level predictors to the suite of neighborhood characteristics did not meaningfully improve prediction accuracy for greenspace measures. Our findings highlight disparities in greenspace for families by neighborhood socioeconomic and early education factors, and by race, suggesting several neighborhood indicators for consideration both as potential confounders in studies of greenspace and pediatric health as well as in the development of policies and programs to improve equity in greenspace access.

Childhood poverty and school readiness: Differences by poverty type and immigration background

Objectives

Poverty exposes children to adverse conditions that negatively impact development. However, there is limited understanding on how different types of poverty may affect children of various immigration backgrounds differently in outcomes such as school readiness. This study examined these relationships between household and/or neighbourhood poverty, poverty timing, and immigration background with school readiness outcomes at kindergarten.

Methods

This study utilized a retrospective, population-based cohort of administrative records linked with surveys completed by kindergarten teachers for 15 369 children born in British Columbia, Canada. The exposures investigated were neighbourhood poverty (residing in a neighbourhood in the lowest income-quintile) and/or household poverty (receiving a health insurance subsidy due to low household income). Experiencing both neighbourhood and household poverty simultaneously was defined as "combined" household and neighbourhood poverty. The outcome of vulnerability on school readiness domains was assessed at kindergarten (47.8% female; mean age = 6.01 years) using teacher ratings on the Early Development Instrument (EDI).

Results

Children exposed to combined poverty between age 0 and 2 had greater odds of being vulnerable in two or more domains of school readiness than children not exposed to any poverty during this period (adjusted odds ratio (aOR) = 2.07, 95% CI: [1.74; 2.47], p < 0.001). The effect of combined poverty was larger than household poverty only (aOR = 1.54, 95% CI: [1.31; 1.82], p < 0.001) or neighbourhood poverty only (aOR = 1.49, 95% CI: [1.30; 1.70], p < 0.001). Combined poverty was associated with negative outcomes regardless of timing. Both non-immigrants (aOR = 2.40, 95% CI: [1.92; 3.00], p < 0.001) and second-generation immigrants (aOR = 1.63, 95% CI: [1.22; 2.17], p < 0.001) experiencing combined poverty scored lower on school readiness.

Conclusions

Children who experienced combined poverty had lower levels of school readiness at kindergarten, regardless of timing and immigration background.

Methods in Public Health Environmental Justice Research: a Scoping Review from 2018 to 2021

PURPOSE OF REVIEW

The volume of public health environmental justice (EJ) research produced by academic institutions increased through 2022. However, the methods used for evaluating EJ in exposure science and epidemiologic studies have not been catalogued. Here, we completed a scoping review of EJ studies published in 19 environmental science and epidemiologic journals from 2018 to 2021 to summarize research types, frameworks, and methods.

RECENT FINDINGS

We identified 402 articles that included populations with health disparities as a part of EJ research question and met other inclusion criteria. Most studies (60%) evaluated EJ questions related to socioeconomic status (SES) or race/ethnicity. EJ studies took place in 69 countries, led by the US (n = 246 [61%]). Only 50% of studies explicitly described a theoretical EJ framework in the background, methods, or discussion and just 10% explicitly stated a framework in all three sections. Among exposure studies, the most common area-level exposure was air pollution (40%), whereas chemicals predominated personal exposure studies (35%). Overall, the most common method used for exposure-only EJ analyses was main effect regression modeling (50%); for epidemiologic studies the most common method was effect modification (58%), where an analysis evaluated a health disparity variable as an effect modifier. Based on the results of this scoping review, current methods in public health EJ studies could be bolstered by integrating expertise from other fields (e.g., sociology), conducting community-based participatory research and intervention studies, and using more rigorous, theory-based, and solution-oriented statistical research methods.

Modeling historic neighborhood deprivation and non-Hodgkin lymphoma risk

Many studies have identified associations between neighborhood deprivation and disease, emphasizing the importance of social determinants of health. However, when studying diseases with long latency periods such as cancers, considering the timing of exposures for deprivation becomes more important. In this study, we estimated the associations between neighborhood deprivation indices at several time points and risk of non-Hodgkin lymphoma (NHL) in a population-based case-control study at four study centers - Detroit, Iowa, Los Angeles County, and Seattle (1998-2000). We used the Bayesian index regression model and residential histories to estimate neighborhood deprivation index effects in crude models and adjusted for four chemical mixtures measured in house dust and individual-level covariates. We found that neighborhood deprivation in 1980, approximately twenty years before study entry, provided better model fit than did neighborhood deprivation at 1990 and 2000. We identified several statistically significant associations between neighborhood deprivation in 1980 and NHL risk in Iowa and among long-term (20+ years) residents of Detroit. The most important variables in these indices were median gross rent as a percentage of household income in Iowa and percent of single-parent households with at least one child and median household income in Detroit. Associations remained statistically significant after adjustment for individual-level covariates and chemical mixtures, providing evidence for historic neighborhood deprivation as a risk factor for NHL and motivating future research to uncover the specific carcinogens driving these associations in deprived areas.

The impact of neighborhood disadvantage on colorectal cancer screening among African Americans in Chicago

Historically, colorectal cancer (CRC) screening rates have been lower among African Americans. Previous studies that have examined the relationship between community characteristics and adherence to CRC screening have generally focused on a single community parameter, making it challenging to evaluate the overall impact of the social and built environment. In this study, we will estimate the overall effect of social and built environment and identify the most important community factors relevant to CRC screening. Data are from the Multiethnic Prevention and Surveillance Study (COMPASS), a longitudinal study among adults in Chicago, collected between May 2013 to March 2020. A total 2,836 African Americans completed the survey. Participants' addresses were geocoded and linked to seven community characteristics (i.e., community safety, community crime, household poverty, community unemployment, housing cost burden, housing vacancies, low food access). A structured questionnaire measured adherence to CRC screening. Weighted quantile sum (WQS) regression was used to evaluate the impact of community disadvantages on CRC screening. When analyzing all community characteristics as a mixture, overall community disadvantage was associated with less adherence to CRC screening even after controlling for individual-level factors. In the adjusted WQS model, unemployment was the most important community characteristic (37.6%), followed by community insecurity (26.1%) and severe housing cost burden (16.3%). Results from this study indicate that successful efforts to improve adherence to CRC screening rates should prioritize individuals living in communities with high rates of insecurity and low socioeconomic status.

Neighborhood Deprivation, Indoor Chemical Concentrations, and Spatial Risk for Childhood Leukemia

Leukemia is the most common childhood cancer in industrialized countries, and the increasing incidence trends in the US suggest that environmental exposures play a role in its etiology. Neighborhood socioeconomic status (SES) has been found to be associated with many health outcomes, including childhood leukemia. In this paper, we used a Bayesian index model approach to estimate a neighborhood deprivation index (NDI) in the analysis of childhood leukemia in a population-based case-control study (diagnosed 1999 to 2006) in northern and central California, with direct indoor measurements of many chemicals for 277 cases and 306 controls <8 years of age. We considered spatial random effects in the Bayesian index model approach to identify any areas of significantly elevated risk not explained by neighborhood deprivation or individual covariates, and assessed if groups of indoor chemicals would explain any elevated spatial risk areas. Due to not all eligible cases and controls participating in the study, we conducted a simulation study to add non-participants to evaluate the impact of potential selection bias when estimating NDI effects and spatial risk. The results in the crude model showed an odds ratio (OR) of 1.06 and 95% credible interval (CI) of (0.98, 1.15) for a one unit increase in the NDI, but the association became slightly inverse when adjusting for individual level covariates in the observed data (OR = 0.97 and 95% CI: 0.87, 1.07), as well as when using simulated data (average OR = 0.98 and 95% CI: 0.91, 1.05). We found a significant spatial risk of childhood leukemia after adjusting for NDI and individual-level covariates in two counties, but the area of elevated risk was partly explained by selection bias in simulation studies that included more participating controls in areas of lower SES. The area of elevated risk was explained when including chemicals measured inside the home, and insecticides and herbicides had greater effects for the risk area than the overall study. In summary, the consideration of exposures and variables at different levels from multiple sources, as well as potential selection bias, are important for explaining the observed spatial areas of elevated risk and effect estimates.

Tobacco Retail Outlets, Neighborhood Deprivation and the Risk of Prenatal Smoke Exposure

INTRODUCTION

Smoking and smoke exposure among pregnant women remain persistent public health issues. Recent estimates suggest that approximately one out of four nonsmokers have measurable levels of cotinine, a marker indicating regular exposure to secondhand smoke. Epidemiological research has attempted to pinpoint individual-level and neighborhood-level factors for smoking during pregnancy. However, most of these studies have relied upon self-reported measures of smoking.

AIMS AND METHODS

To more accurately assess smoke exposure resulting from both smoking and secondhand exposure in mothers during pregnancy, we used Bayesian regression models to estimate the association of cotinine levels with tobacco retail outlet (TRO) exposure and a neighborhood deprivation index (NDI) in six counties in North Carolina centered on Durham County.

RESULTS

Results showed a significant positive association between TRO exposure (β = 0.008, 95% credible interval (CI) = [0.003, 0.013]) and log cotinine after adjusting for individual covariates (eg, age, race/ethnicity, education, marital status). TRO exposure was not significant after including the NDI, which was significantly associated with log cotinine (β = 0.143, 95% CI = [0.030, 0.267]). However, in a low cotinine stratum (indicating secondhand smoke exposure), TRO exposure was significantly associated with log cotinine (β = 0.005, 95% CI = [0.001, 0.009]), while in a high cotinine stratum (indicating active smoking), the NDI was significantly associated with log cotinine (β = 0.176, 95% CI = [0.005, 0.372]).

CONCLUSIONS

In summary, our findings add to the evidence that contextual factors are important for active smoking during pregnancy.

IMPLICATIONS

In this study, we found several significant associations that suggest a more nuanced understanding of the potential influence of environmental- and individual-level factors for levels of prenatal smoke exposure. Results suggested a significant positive association between TRO exposure and cotinine levels, after adjusting for the individual factors such as race, education, and marital status. Individually, NDI was similarly positively associated with cotinine levels as well. However, when combining TRO exposure alongside NDI in the same model, TROs were no longer significantly associated with overall cotinine levels.

Lead Data Mapping to Prioritize US Locations for Whole-of-Government Exposure Prevention Efforts: State of the Science, Federal Collaborations, and Remaining Challenges

For this state-of-science overview of geospatial approaches for identifying US communities with high lead-exposure risk, we compiled and summarized public data and national maps of lead indices and models, environmental lead indicators, and children's blood lead surveillance data. Currently available indices and models are primarily constructed from housing-age and sociodemographic data; differing methods, variables, data, weighting schemes, and geographic scales yield maps with different exposure risk profiles. Environmental lead indicators are available (e.g., air, drinking water, dust, soil) at different spatial scales, but key gaps remain. Blood lead level data have limitations as testing, reporting, and completeness vary across states. Mapping tools and approaches developed by federal agencies and other groups for different purposes present an opportunity for greater collaboration. Maps, data visualization tools, and analyses that synthesize available geospatial efforts can be evaluated and improved with local knowledge and blood lead data to refine identification of high-risk locations for prioritizing prevention efforts and targeting risk-reduction strategies. Remaining challenges are discussed along with a work-in-progress systematic approach for cross-agency data integration, toward advancing "whole-of-government" public health protection from lead exposures. (Am J Public Health. 2022;112(S7):S658-S669. https://doi.org/10.2105/AJPH.2022.307051).

A Generalizable Evaluated Approach, Applying Advanced Geospatial Statistical Methods, to Identify High Lead Exposure Locations at Census Tract Scale: Michigan Case Study

BACKGROUND

Despite great progress in reducing environmental lead (Pb) levels, many children in the United States are still being exposed.

OBJECTIVE

Our aim was to develop a generalizable approach for systematically identifying, verifying, and analyzing locations with high prevalence of children's elevated blood Pb levels (EBLLs) and to assess available Pb models/indices as surrogates, using a Michigan case study.

METHODS

We obtained ∼1.9 million BLL test results of children <6 years of age in Michigan from 2006-2016; we then evaluated them for data representativeness by comparing two percentage EBLL (%EBLL) rates (number of children tested with EBLL divided by both number of children tested and total population). We analyzed %EBLLs across census tracts over three time periods and between two EBLL reference values (≥5 vs. ≥10μg/dL) to evaluate consistency. Locations with high %EBLLs were identified by a top 20 percentile method and a Getis-Ord Gi* geospatial cluster "hotspot" analysis. For the locations identified, we analyzed convergences with three available Pb exposure models/indices based on old housing and sociodemographics.

RESULTS

Analyses of 2014-2016 %EBLL data identified 11 Michigan locations via cluster analysis and 80 additional locations via the top 20 percentile method and their associated census tracts. Data representativeness and consistency were supported by a 0.93 correlation coefficient between the two EBLL rates over 11 y, and a Kappa score of ∼0.8 of %EBLL hotspots across the time periods (2014-2016) and reference values. Many EBLL hotspot locations converge with current Pb exposure models/indices; others diverge, suggesting additional Pb sources for targeted interventions.

DISCUSSION

This analysis confirmed known Pb hotspot locations and revealed new ones at a finer geographic resolution than previously available, using advanced geospatial statistical methods and mapping/visualization. It also assessed the utility of surrogates in the absence of blood Pb data. This approach could be applied to other states to inform Pb mitigation and prevention efforts. https://doi.org/10.1289/EHP9705.

The Intersection of Neighborhood Environment and Adverse Childhood Experiences: Methods for Creation of a Neighborhood ACEs Index

This study evaluated methods for creating a neighborhood adverse childhood experiences (ACEs) index, a composite measure that captures the association between neighborhood environment characteristics (e.g., crime, healthcare access) and individual-level ACEs exposure, for a particular population. A neighborhood ACEs index can help understand and address neighborhood-level influences on health among individuals affected by ACEs. Methods entailed cross-sectional secondary analysis connecting individual-level ACEs data from the Philadelphia ACE Survey (n = 1677) with 25 spatial datasets capturing neighborhood characteristics. Four methods were tested for index creation (three methods of principal components analysis, Bayesian index regression). Resulting indexes were compared using Akaike Information Criteria for accuracy in explaining ACEs exposure. Exploratory linear regression analyses were conducted to examine associations between ACEs, the neighborhood ACEs index, and a health outcome—in this case body mass index (BMI). Results demonstrated that Bayesian index regression was the best method for index creation. The neighborhood ACEs index was associated with higher BMI, both independently and after controlling for ACEs exposure. The neighborhood ACEs index attenuated the association between BMI and ACEs. Future research can employ a neighborhood ACEs index to inform upstream, place-based interventions and policies to promote health among individuals affected by ACEs.

Systematic review of neighborhood socioeconomic indices studied across the cancer control continuum

BACKGROUND

There is extensive interest in understanding how neighborhood socioeconomic status (nSES) may affect cancer incidence or survival. However, variability regarding items included and approaches used to form a composite nSES index presents challenges in summarizing overall associations with cancer. Given recent calls for standardized measures of neighborhood sociodemographic effects in cancer disparity research, the objective of this systematic review was to identify and compare existing nSES indices studied across the cancer continuum (incidence, screening, diagnosis, treatment, survival/mortality) and summarize associations by race/ethnicity and cancer site to inform future cancer disparity studies.

METHODS

Using PRISMA guidelines, peer-reviewed articles published between 2010 and 2019 containing keywords related to nSES and cancer were identified in PubMed.

RESULTS

Twenty-four nSES indices were identified from 75 studies. In general, findings indicated a significant association between nSES and cancer outcomes (n = 64/75 studies; 85.33%), with 42/64 (65.63%) adjusting for highly-correlated individual SES factors (e.g., education). However, the direction of association differed by cancer site, race/ethnicity, and nSES index.

CONCLUSIONS

This review highlights several methodologic and conceptual issues surrounding nSES measurement and potential associations with cancer disparities. Recommendations pertaining to the selection of nSES measures are provided, which may help inform disparity-related disease processes and improve the identification of vulnerable populations in need of intervention.

Spatially Varying Associations of Neighborhood Disadvantage with Alcohol and Tobacco Retail Outlet Rates

More than 30% of cancer related deaths are related to tobacco or alcohol use. Controlling and restricting access to these cancer-causing products, especially in communities where there is a high prevalence of other cancer risk factors, has the potential to improve population health and reduce the risk of specific cancers associated with these substances in more vulnerable population subgroups. One policy-driven method of reducing access to these cancer-causing substances is to regulate where these products are sold through the placement and density of businesses selling tobacco and alcohol. Previous work has found significant positive associations between tobacco, alcohol, and tobacco and alcohol retail outlets (TRO, ARO, TARO) and a neighborhood disadvantage index (NDI) using Bayesian shared component index modeling, where NDI associations differed across outlet types and relative risks varied by population density (e.g., rural, suburban, urban). In this paper, we used a novel Bayesian index model with spatially varying effects to explore spatial nonstationarity in NDI effects for TROs, AROs, and TAROs across census tracts in North Carolina. The results revealed substantial variation in NDI effects that varied by outlet type. However, all outlet types had strong positive effects in one coastal area. The most important variables in the NDI were percent renters, Black racial segregation, and the percentage of homes built before 1940. Overall, more disadvantaged areas experienced a greater neighborhood burden of outlets selling one or both of alcohol and tobacco.

Neighborhood Deprivation is Associated with Increased Risk of Prenatal Smoke Exposure

Despite years of advisories against the behavior, smoking among pregnant women remains a persistent public health issue in the USA. Recent estimates suggest that 9.4% of women smoke before pregnancy and 7.1% during pregnancy in the USA. Epidemiological research has attempted to pinpoint individual-level and neighborhood-level factors for smoking during pregnancy, including educational attainment, employment status, housing conditions, poverty, and racial demographics. However, most of these studies have relied upon self-reported measures of smoking, which are subject to reporting bias. To more accurately and objectively assess smoke exposure in mothers during pregnancy, we used Bayesian index models to estimate a neighborhood deprivation index (NDI) for block groups in Durham County, North Carolina, and its association with cotinine, a marker of smoke exposure, in pregnant mothers (n = 887 enrolled 2005-2011). Results showed a significant positive association between NDI and log cotinine (beta = 0.20, 95% credible interval = [0.11, 0.29]) after adjusting for individual covariates (e.g., race/ethnicity and education). The two most important variables in the NDI according to the estimated index weights were percent females without a high school degree and percent Black population. At the individual level, Hispanic and other race/ethnicity were associated with lowered cotinine compared with non-Hispanic Whites. Higher education levels were also associated with lowered cotinine. In summary, our findings provide stronger evidence that the socio-geographic variables of educational attainment and neighborhood racial composition are important factors for smoking and secondhand smoke exposure during pregnancy and can be used to target intervention efforts.

Modeling annual elevated blood lead levels among children in Maryland in relation to neighborhood deprivation

Estimating environmental lead exposure using ecologic risk models is an inexpensive strategy to inform public health departments and to develop location-based intervention strategies such as targeted screening and mitigation. Importantly, studies in this area have not assessed temporal and spatio-temporal lead exposure risk trends. Due to lead abatement efforts and targeted screening efforts, it is anticipated that lead exposure risk has decreased over time. However, it is unknown if decreases have occurred, and if the decreases are evenly distributed across neighborhoods. Thus, the purpose of this study was to examine the association between neighborhood deprivation and risk of elevated blood lead levels (EBLLs) in both temporal and spatio-temporal contexts within the US state of Maryland in 2005-2015. To consider the temporal dimension of lead risk, we used a novel extension of Bayesian index models to estimate time-varying neighborhood deprivation indices along with time-varying index effects. The results showed that overall EBLL proportion decreased over time, from a high of 0.11 in 2006 to a low of 0.02 in 2015. The association between neighborhood deprivation and EBLL risk was positive and significant annually, but generally diminished over time. The most important variables in the neighborhood deprivation index were percent of houses built before 1940 and median household income. In summary, using Bayesian index models that can account for both temporal and spatio-temporal contexts is a promising approach to inform public health efforts to remediate lead and focus testing efforts and may be useful in studies in other geographic areas and times.

Associations of Alcohol and Tobacco Retail Outlet Rates with Neighborhood Disadvantage

Tobacco causes 29% of cancer-related deaths while alcohol causes 5.5% of cancer-related deaths. Reducing the consumption of these cancer-causing products is a special priority area for the National Cancer Institute. While many factors are linked to tobacco and alcohol use, the placement and density of retail outlets within neighborhoods may be one community-level risk factor contributing to greater use of these products. To elucidate associations between tobacco, alcohol, and tobacco and alcohol retail outlets (TRO, ARO, and TARO) and neighborhood disadvantage over a large geographic area, we employed a novel Bayesian index modeling approach to estimate a neighborhood disadvantage index (NDI) and its associations with rates of the three types of retailers across block groups in the state of North Carolina. We used a novel extension of the Bayesian index model to include a shared component for the spatial pattern common to all three types of outlets and NDI effects that varied by outlet type. The shared component identifies areas that are elevated in risk for all outlets. The results showed significant positive associations between neighborhood disadvantage and TROs (relative risk (RR) = 1.12, 95% credible interval (CI = 1.09, 1.14)) and AROs (RR = 1.15, 95% CI = 1.11, 1.17), but the association was greatest for TAROs (RR = 1.21, 95% CI = 1.18, 1.24). The most important variables in the NDI were percent renters (i.e., low home ownership), percent of homes built before 1940 (i.e., old housing stock), and percent without a high school diploma (i.e., low education).

Adolescent Brain Cognitive Development (ABCD) study Linked External Data (LED): Protocol and practices for geocoding and assignment of environmental data

Our brain is constantly shaped by our immediate environments, and while some effects are transient, some have long-term consequences. Therefore, it is critical to identify which environmental risks have evident and long-term impact on brain development. To expand our understanding of the environmental context of each child, the Adolescent Brain Cognitive Development (ABCD) Study® incorporates the use of geospatial location data to capture a range of individual, neighborhood, and state level data based on the child's residential location in order to elucidate the physical environmental contexts in which today's youth are growing up. We review the major considerations and types of geocoded information incorporated by the Linked External Data Environmental (LED) workgroup to expand on the built and natural environmental constructs in the existing and future ABCD Study data releases. Understanding the environmental context of each youth furthers the consortium's mission to understand factors that may influence individual differences in brain development, providing the opportunity to inform public policy and health organization guidelines for child and adolescent health.

Selected Metal Concentration in Maternal and Cord Blood

Essential and non-essential elements deficiencies may lead to various birth complications. The aim of this paper was to determine calcium (Ca), copper (Cu), iron (Fe), potassium (K), magnesium (Mg), sodium (Na), phosphorus (P), lead (Pb), strontium (Sr), and zinc (Zn) concentrations in maternal blood and cord blood. Whole blood and cord blood samples collected from pregnant women (n = 136) were analyzed for the concentration of the elements by spectrophotometric atomic absorption in inductively coupled argon plasma (ICP-OES). The results showed that Ca, Pb, and Sr concentrations were similar in maternal and cord blood, while Fe and K levels were higher in cord blood than in maternal blood. The cord blood Cu, Na, and Zn concentrations were lower than those in maternal blood, suggesting transplacental transfer of these elements were limited. Moreover, checking the influence of studied elements on the anthropometric parameters of the newborns, we found that the highest number of associations was between Cu in cord blood. Due to the fact that the pregnant women were healthy, and the newborns were without any disorders, we suggest that the values obtained in our study are normal values of studied elements in whole blood and cord blood in patients from Poland.

Risk of lead exposure, subcortical brain structure, and cognition in a large cohort of 9- to 10-year-old children

BACKGROUND

Lead, a toxic metal, affects cognitive development at the lowest measurable concentrations found in children, but little is known about its direct impact on brain development. Recently, we reported widespread decreases in cortical surface area and volume with increased risks of lead exposure, primarily in children of low-income families.

METHODS AND FINDINGS

We examined associations of neighborhood-level risk of lead exposure with cognitive test performance and subcortical brain volumes. We also examined whether subcortical structure mediated associations between lead risk and cognitive performance. Our analyses employed a cross-sectional analysis of baseline data from the observational Adolescent Brain Cognitive Development (ABCD) Study. The multi-center ABCD Study used school-based enrollment to recruit a demographically diverse cohort of almost 11,900 9- and 10-year-old children from an initial 22 study sites. The analyzed sample included data from 8,524 typically developing child participants and their parents or caregivers. The primary outcomes and measures were subcortical brain structure, cognitive performance using the National Institutes of Health Toolbox, and geocoded risk of lead exposure. Children who lived in neighborhoods with greater risks of environmental lead exposure exhibited smaller volumes of the mid-anterior (partial correlation coefficient [rp] = -0.040), central (rp = -0.038), and mid-posterior corpus callosum (rp = -0.035). Smaller volumes of these three callosal regions were associated with poorer performance on cognitive tests measuring language and processing speed. The association of lead exposure risk with cognitive performance was partially mediated through callosal volume, particularly the mid-posterior corpus callosum. In contrast, neighborhood-level indicators of disadvantage were not associated with smaller volumes of these brain structures.

CONCLUSIONS

Environmental factors related to the risk of lead exposure may be associated with certain aspects of cognitive functioning via diminished subcortical brain structure, including the anterior splenium (i.e., mid-posterior corpus callosum).

Secondary School Socioeconomic Status and Athletic Training Practice Characteristics

CONTEXT

Socioeconomic status (SES) is a significant predictor of morbidity and mortality across health outcomes. Limited information exists on how school SES impacts athletic training practice when a certified athletic trainer (AT) is present at secondary schools.

OBJECTIVE

To describe contact frequencies and service rates provided by ATs for injuries among secondary school student athletes and how these differ by school SES.

DESIGN

Cross-sectional study Setting: Athletic training room (ATR) visit days and AT services were collected from 77 secondary schools. Schools were separated into three school SES groups: affluent (n=31), average (n=29), and disadvantaged (n=17).

PATIENTS OR OTHER PARTICIPANTS

Secondary school student-athletes participating in 12 boys' and 11 girls' sports who visited the ATR during the 2014-2015 through 2018-2019 academic years and received athletic or non-athletic injury care.

MAIN OUTCOME MEASURES

Contact frequencies expressed as ATR visit days per injury, AT services per injury, and AT services per ATR visit day. Rates for service type utilized were expressed as the total count over reported athlete-exposures.

RESULTS

ATs documented 1,191 services. Affluent and average SES school communities provided greater contact frequencies for injury related care compared to disadvantaged school communities, particularly by AT services/injury (7.10±13.08 versus average: 9.30±11.60 and affluent: 9.40±12.20; p=0.020). Affluent school communities provided greater rates of services in five of the eleven service groups reported. No significant differences were observed among school SES groups in therapeutic exercises.

CONCLUSIONS

Our findings reflect that AT practice characteristics may differ by school SES, but these differences do not appear to result in less medical care. Given the complexity and widespread effects of SES, future investigations should utilize a complex method to determine SES as well as aim to identify how SES may impact secondary school student athletes outside of AT practice characteristics.

Estimated IQ points and lifetime earnings lost to early childhood blood lead levels in the United States

There is no safe detectable level of lead (Pb) in the blood of children. Blood lead levels (BLLs) at ages 6-24 months ≥2 μg/dL result in lost grade school intelligence quotient (IQ) points at ages 5-10 years. Black children continue to have the highest BLLs in the United States. Therefore, we examined currently undetermined racial/ethnic disparities in anticipated IQ points and associated lifetime earnings lost to early childhood blood lead. We conducted secondary analysis of infants with blood lead (in μg/dL) measured at ages 12-24 months by the cross-sectional National Health and Nutrition Examination Survey (NHANES) during 1999 to 2010. Nationally-representative estimates were produced using weighted simulation model. A total of 1241 infants were included from the NHANES sample (52% male; mean [SD] age, 18.5 [3.5] months; 25% Black [non-Hispanic], 42% Hispanic [any race], 5% Other/Multiracial, and 29% White [non-Hispanic]) after excluding 811 without BLL determinations. For national outcomes, Black infants experienced approximately 46-55% greater average estimated loss of grade school IQ points from blood lead than Hispanic or White infants (-1.78 IQ points vs. -1.15 and -1.21 respectively) with similar disparities in costs to expected lifetime earnings (-$47,116 USD vs. -$30,393 and -$32,356 respectively). Our estimated nationwide costs of IQ points lost to BLLs during this 12-year period totaled $554 billion ($46.2 billion/year), in which blood lead <5 μg/dL accounted for 74% of this total burden. We report two aspects of the substantial national costs attributable to lead exposure in just the second year of life alone, which disproportionately impact predominately African-American Black infants from continuing legacies of environmental racism in lead exposure. Our findings underscore the remarkably high costs from recognized hazards of blood lead even at the lowest levels and the importance of primary prevention regarding childhood lead exposure.

Modeling elevated blood lead level risk across the United States

Lead exposure adversely affects child health and continues to be a major public health concern in the United States (US). Lead exposure risk has been linked with older housing and households in poverty, but more studies of neighborhood socioeconomic status (SES) and lead exposure risk over large and diverse geographic areas are needed. In this paper, we combined lead test result data over many states for a majority of the US ZIP Codes in order to estimate its association with many SES variables and predict lead exposure risk in all populated ZIP Codes in the US. The methods used for estimation and prediction of lead risk included the Vox lead exposure risk score, random forest, weighted quantile sum (WQS) regression, and a Bayesian SES index model. The results showed that the Bayesian index model had the best overall performance for modeling elevated blood lead level (EBLL) risk and therefore was used to create a lead exposure risk score for US ZIP Codes. There was a statistically significant association between EBLL risk and the SES index and the most important SES variables for explaining EBLL risk were percentage of houses built before 1940 and median home value. When mapping the lead exposure risk scores, there was a clear pattern of elevated risk in the Northeast and Midwest, but areas in the South and Southwest regions of the US also had high risk. In summary, the Bayesian index model was an effective method for modeling EBLL risk associated with neighborhood deprivation while accounting for additional heterogeneity in risk using lead test result data covering a majority of the US. The resulting lead exposure risk score can be used for targeting public health intervention efforts.

Blood lead concentration and its associated factors in preschool children in eastern Iran: a cross-sectional study

Background

Lead is a toxic metal that affects almost every organ in the body. Children are more susceptible to lead toxicity because they ingest non-food items (pica), have oral exploratory habits, absorb more substantial amounts of ingested lead compared to adults, and have a developing central nervous system. This study describes venous blood lead concentrations (BLC) in young children living in Birjand, Iran.

Methods

A cross-sectional study was performed in 2016 on children 1–7 years of age who were referred to healthcare centers in Birjand City. Demographic information was obtained, and their BLC was tested using atomic absorption spectrometry (AAS).

Results

Four hundred children were tested. Their mean age was 52.37 ± 23.77 months; their mean BLC was 2.49 ± 2.64 μg/dL (median 1.85 μg/dL). Thirty-two (8%) children had a BLC > 5 μg/dL. A logistic regression model revealed that per one unit of increase in age, the chance of an elevated BLC decreased by 3% (OR (95%CI): 0.97 (0.96–0.99), p < 0.01). The risks of an elevated BLC was 61% lower in girls compared to boys (OR (95%CI): 0.39 (0.17–0.92), p = 0.03). Further, per one rate of increase in the BMI, the chance of an elevated BLC was higher (OR (95%CI): 1.13 (1.02–1.24), p = 0.01). Children whose fathers were laborers had higher BLC than those with employee fathers (p = 0.01).

Conclusion

Of 400 children aged 1–7 years old living in Birjand, Iran, 8% had elevated BLC. BLC correlated with the child ‘s age, gender, body mass index, and father’s occupation.

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.

Disparity in Risk Factor Severity for Early Childhood Blood Lead among Predominantly African-American Black Children: The 1999 to 2010 US NHANES

There is no safe detectable level of lead (Pb) in the blood of young children. In the United States, predominantly African-American Black children are exposed to more Pb and present with the highest mean blood lead levels (BLLs). However, racial disparity has not been fully examined within risk factors for early childhood Pb exposure. Therefore, we conducted secondary analysis of blood Pb determinations for 2841 US children at ages 1–5 years with citizenship examined by the cross-sectional 1999 to 2010 National Health and Nutrition Examination Survey (NHANES). The primary measures were racial disparities for continuous BLLs or an elevated BLL (EBLL) ≥5 µg/dL in selected risk factors between non-Hispanic Black children (n = 608) and both non-Hispanic White (n = 1208) or Hispanic (n = 1025) children. Selected risk factors included indoor household smoking, low income or poverty, older housing built before 1978 or 1950, low primary guardian education <12th grade/general education diploma (GED), or younger age between 1 and 3 years. Data were analyzed using a regression model corrected for risk factors and other confounding variables. Overall, Black children had an adjusted +0.83 µg/dL blood Pb (95% CI 0.65 to 1.00, p < 0.001) and a 2.8 times higher odds of having an EBLL ≥5 µg/dL (95% CI 1.9 to 3.9, p < 0.001). When stratified by risk factor group, Black children had an adjusted 0.73 to 1.41 µg/dL more blood Pb (p < 0.001 respectively) and a 1.8 to 5.6 times higher odds of having an EBLL ≥5 µg/dL (p ≤ 0.05 respectively) for every selected risk factor that was tested. For Black children nationwide, one in four residing in pre-1950 housing and one in six living in poverty presented with an EBLL ≥5 µg/dL. In conclusion, significant nationwide racial disparity in blood Pb outcomes persist for predominantly African-American Black children even after correcting for risk factors and other variables. This racial disparity further persists within housing, socio-economic, and age-related risk factors of blood Pb outcomes that are much more severe for Black children.

Association of lead-exposure risk and family income with childhood brain outcomes

Socioeconomic factors influence brain development and structure, but most studies have overlooked neurotoxic insults that impair development, such as lead exposure. Childhood lead exposure affects cognitive development at the lowest measurable concentrations, but little is known about its impact on brain development during childhood. We examined cross-sectional associations among brain structure, cognition, geocoded measures of the risk of lead exposure and sociodemographic characteristics in 9,712 9- and 10-year-old children. Here we show stronger negative associations of living in high-lead-risk census tracts in children from lower- versus higher-income families. With increasing risk of exposure, children from lower-income families exhibited lower cognitive test scores, smaller cortical volume and smaller cortical surface area. Reducing environmental insults associated with lead-exposure risk might confer greater benefit to children experiencing more environmental adversity, and further understanding of the factors associated with high lead-exposure risk will be critical for improving such outcomes in children.

Bayesian deprivation index models for explaining variation in elevated blood lead levels among children in Maryland

Lead exposure adversely affects children's health. Exposure in the United States is highest among socioeconomically disadvantaged individuals who disproportionately live in substandard housing. We used Bayesian binomial regression models to estimate a neighborhood deprivation index and its association with elevated blood lead level (EBLL) risk using blood lead level testing data in Maryland census tracts. Our results show the probability of EBLL was spatially structured with high values in Baltimore city and low values in the District of Columbia suburbs and Baltimore suburbs. The association between the neighborhood deprivation index and EBLL risk was statistically significant after accounting for spatial dependence in probability of EBLL. The percent of houses built before 1940, African Americans, and renter occupied housing were the most important variables in the index. Bayesian models provide a flexible one-step approach to modeling risk associated with neighborhood deprivation while accounting for spatially structured and unstructured heterogeneity in risk.