Maternal stress and hair cortisol among pregnant women following hurricane Florence.

Natural disasters represent major stressors, resulting in psychological distress and physiological responses such as increased cortisol. During pregnancy, this impacts not only maternal well-being, but also fetal development. In 2018, Hurricane Florence caused extensive damage across the eastern United States. Studies indicated that compared to married pregnant women, unmarried pregnant women had higher risk of distress. Here we assess hair cortisol among a subsample of participants, and variations based on marital status. METHODS: We analyzed multiple stress measures among 37 participants who were pregnant during Hurricane Florence. We used questionnaires modeled on previous studies to assess hardship associated with the hurricane, psychological distress, sociodemographic characteristics, social support, and food security. We analyzed cortisol concentrations in proximal and distal hair sections, representing stress around the time of the disaster (distal) and 3-4 months following the disaster (proximal). We used linear regression to test relationships between hair cortisol and self-report stress measures, and variations based on marital status. RESULTS: Self-report measures of distress and hardship were similar among married and unmarried participants. Mean cortisol levels in distal and proximal sections were higher among unmarried participants. Controlling for confounding variables, hardship was not associated with hair cortisol. Distress predicted cortisol in distal sections (ß = .482, p = .018), with a trend for proximal sections (ß = .368, p = .055). Marital status was a significant predictor of distal (ß = .388, p = .027) and proximal (ß = .333, p = .047) hair cortisol, explaining 8.6%-11.7% of unique variance. CONCLUSIONS: Preexisting and intersecting risk factors likely place unmarried pregnant individuals at risk of stress during and following a disaster.

A framework for widespread replication of a highly spatially resolved childhood lead exposure risk model.

BACKGROUND: Preventive approaches to childhood lead poisoning are critical for addressing this longstanding environmental health concern. Moreover, increasing evidence of cognitive effects of blood lead levels < 10 microg/dL highlights the need for improved exposure prevention interventions. OBJECTIVES: Geographic information system-based childhood lead exposure risk models, especially if executed at highly resolved spatial scales, can help identify children most at risk of lead exposure, as well as prioritize and direct housing and health-protective intervention programs. However, developing highly resolved spatial data requires labor-and time-intensive geocoding and analytical processes. In this study we evaluated the benefit of increased effort spent geocoding in terms of improved performance of lead exposure risk models. METHODS: We constructed three childhood lead exposure risk models based on established methods but using different levels of geocoded data from blood lead surveillance, county tax assessors, and the 2000 U.S. Census for 18 counties in North Carolina. We used the results to predict lead exposure risk levels mapped at the individual tax parcel unit. RESULTS: The models performed well enough to identify high-risk areas for targeted intervention, even with a relatively low level of effort on geocoding. CONCLUSIONS: This study demonstrates the feasibility of widespread replication of highly spatially resolved childhood lead exposure risk models. The models guide resource-constrained local health and housing departments and community-based organizations on how best to expend their efforts in preventing and mitigating lead exposure risk in their communities.

The relationship between early childhood blood lead levels and performance on end-of-grade tests.

BACKGROUND: Childhood lead poisoning remains a critical environmental health concern. Low-level lead exposure has been linked to decreased performance on standardized IQ tests for school-aged children. OBJECTIVE: In this study we sought to determine whether blood lead levels in early childhood are related to educational achievement in early elementary school as measured by performance on end-of-grade (EOG) testing. METHODS: Educational testing data for 4th-grade students from the 2000-2004 North Carolina Education Research Data Center were linked to blood lead surveillance data for seven counties in North Carolina and then analyzed using exploratory and multivariate statistical methods. RESULTS: The discernible impact of blood lead levels on EOG testing is demonstrated for early childhood blood lead levels as low as 2 microg/dL. A blood lead level of 5 microg/dL is associated with a decline in EOG reading (and mathematics) scores that is roughly equal to 15% (14%) of the interquartile range, and this impact is very significant in comparison with the effects of covariates typically considered profoundly influential on educational outcomes. Early childhood lead exposures appear to have more impact on performance on the reading than on the mathematics portions of the tests. CONCLUSIONS: Our emphasis on population-level analyses of children who are roughly the same age linked to previous (rather than contemporaneous) blood lead levels using achievement (rather than aptitude) outcome complements the important work in this area by previous researchers. Our results suggest that the relationship between blood lead levels and cognitive outcomes are robust across outcome measures and at low levels of lead exposure.

Changes in blood lead levels associated with use of chloramines in water treatment systems.

BACKGROUND: More municipal water treatment plants are using chloramines as a disinfectant in order to reduce carcinogenic by-products. In some instances, this has coincided with an increase in lead levels in drinking water in those systems. Lead in drinking water can be a significant health risk. OBJECTIVES: We sought to test the potential effect of switching to chloramines for disinfection in water treatment systems on childhood blood lead levels using data from Wayne County, located in the central Coastal Plain of North Carolina. METHODS: We constructed a unified geographic information system (GIS) that links blood lead screening data with age of housing, drinking water source, and census data for 7,270 records. The data were analyzed using both exploratory methods and more formal multivariate techniques. RESULTS: The analysis indicates that the change to chloramine disinfection may lead to an increase in blood lead levels, the impact of which is progressively mitigated in newer housing. CONCLUSIONS: Introducing chloramines to reduce carcinogenic by-products may increase exposure to lead in drinking water. Our research provides guidance on adjustments in the local childhood lead poisoning prevention program that should accompany changes in water treatment. As similar research is conducted in other areas, and the underlying environmental chemistry is clarified, water treatment strategies can be optimized across the multiple objectives that municipalities face in providing high quality drinking water to local residents.