Detecting New Sources of Childhood Environmental Lead Exposure Using a Statistical Surveillance System, 2015-2019.

Objectives. To design and implement a statistical surveillance system to prospectively identify potential clusters of elevated blood lead levels (EBLLs) in children younger than 6 years in the Denver, Colorado, metro area. Methods. We evaluated the ability of 2 independent statistical surveillance methods to detect synthetic clusters of EBLLs in Denver between 2015 and 2019. Results. Together, the statistical surveillance methods took an average of 9 months to detect the synthetic clusters. This is faster than similar real-world clusters that have been reported in the past. The system was relatively unaffected by changes in the testing rate and to the blood lead reference value. Conclusions. The adequate design of a statistical surveillance system can help increase the rate at which clusters of EBLLs are detected in Denver, but doing so requires an accurate model of the spatial distribution of EBLLs. Earlier detection of clusters can help guide more effective public health interventions at the local level. (Am J Public Health. 2022;112(S7):S715-S722. https://doi.org/10.2105/AJPH.2022.307009).

A data-driven approach to identifying PFAS water sampling priorities in Colorado, United States.

BACKGROUND: Per and polyfluoroalkyl substances (PFAS), a class of environmentally and biologically persistent chemicals, have been used across many industries since the middle of the 20th century. Some PFAS have been linked to adverse health effects. OBJECTIVE: Our objective was to incorporate known and potential PFAS sources, physical characteristics of the environment, and existing PFAS water sampling results into a PFAS risk prediction map that may be used to develop a PFAS water sampling prioritization plan for the Colorado Department of Public Health and Environment (CDPHE). METHODS: We used random forest classification to develop a predictive surface of potential groundwater contamination from two PFAS, perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA). The model predicted PFAS risk at locations without sampling data into one of three risk categories after being "trained" with existing PFAS water sampling data. We used prediction results, variable importance ranking, and population characteristics to develop recommendations for sampling prioritization. RESULTS: Sensitivity and precision ranged from 58% to 90% in the final models, depending on the risk category. The model and prioritization approach identified private wells in specific census blocks, as well as schools, mobile home parks, and public water systems that rely on groundwater as priority sampling locations. We also identified data gaps including areas of the state with limited sampling and potential source types that need further investigation. IMPACT STATEMENT: This work uses random forest classification to predict the risk of groundwater contamination from two per- and polyfluoroalkyl substances (PFAS) across the state of Colorado, United States. We developed the prediction model using data on known and potential PFAS sources and physical characteristics of the environment, and "trained" the model using existing PFAS water sampling results. This data-driven approach identifies opportunities for PFAS water sampling prioritization as well as information gaps that, if filled, could improve model predictions. This work provides decision-makers information to effectively use limited resources towards protection of populations most susceptible to the impacts of PFAS exposure.

Effects of isocaloric carbohydrate vs. carbohydrate-protein supplements on cycling time to exhaustion.

The purpose of this study was to investigate the effects of isocaloric carbohydrate (CHO) and carbohydrate-protein (CHO-Pro) supplements on time to exhaustion. Eleven moderately aerobically fit adults (V[Combining Dot Above]O2max= 48.3 ± 6.5 ml·kg·min) performed a maximal cycle ergometer test for the determination of V[Combining Dot Above]O2max. At least 72 hours later, the participants performed a time-to-exhaustion test at a power output equivalent to the power output when subjects were at 75% of their V[Combining Dot Above]O2max. Either the CHO or the CHO-Pro supplement was administered at 0, 30, 60, 90, and 120 minutes after this test. After 3 hours of recovery and supplement ingestion, a second time-to-exhaustion test was performed. This testing protocol was repeated for the third visit, but the supplement not given during the second visit was administered. The results indicated that there was no significant difference in time to exhaustion after isocaloric CHO (pretest 22.4 ± 2.84 minutes, posttest 25.4 ± 4.45 minutes) and CHO-Pro (pretest 22.3 ± 3.46 minutes, posttest 24.0 ± 5.08 minutes) supplementation. Carbohydrate and CHO-Pro ingestion after exercise appear to have similar effects on short-term recovery.

Long-term air pollution and other risk factors associated with COVID-19 at the census tract level in Colorado.

Previous nationwide studies have reported links between long-term concentrations of fine particulate matter (PM2.5) and COVID-19 infection and mortality rates. In order to translate these results to the state level, we use Bayesian hierarchical models to explore potential links between long-term PM2.5 concentrations and census tract-level rates of COVID-19 outcomes (infections, hospitalizations, and deaths) in Colorado. We explicitly consider how the uncertainty in PM2.5 estimates affects our results by comparing four different PM2.5 surfaces from academic and governmental organizations. After controlling for 20 census tract-level covariates, we find that our results depend heavily on the choice of PM2.5 surface. Using PM2.5 estimates from the United States EPA, we find that a 1 µg/m3 increase in long-term PM2.5 concentrations is associated with a statistically significant 26% increase in the relative risk of hospitalizations and a 34% increase in mortality. Results for all other surfaces and outcomes were not statistically significant. At the same time, we find a clear association between communities of color and COVID-19 outcomes at the Colorado census tract level that is minimally affected by the choice of PM2.5 surface. A per-interquartile range (IQR) increase in the percent of non-African American people of color was associated with a 31%, 43%, and 56% increase in the relative risk of infection, hospitalization, and mortality respectively, while a per-IQR increase in the proportion of non-Hispanic African Americans was associated with a 4% and 7% increase in the relative risk of infections and hospitalizations. The current disagreement among the different PM2.5 estimates is a key factor limiting our ability to link environmental exposures and health outcomes at the census tract level. These results have strong implications for the implementation of an equitable public health response during the crisis and suggest targeted areas for additional air monitoring in Colorado.

A Systematic Review of the Epidemiologic Literature Assessing Health Outcomes in Populations Living near Oil and Natural Gas Operations: Study Quality and Future Recommendations.

A systematic method was used to review the existing epidemiologic literature and determine the state of the scientific evidence for potential adverse health outcomes in populations living near oil and natural gas (ONG) operations in the United States. The review utilized adapted systematic review frameworks from the medical and environmental health fields, such as Grading of Recommendations, Assessment, Development and Evaluations (GRADE), the Navigation Guide, and guidance from the National Toxicology Program's Office of Health Assessment and Translation (OHAT). The review included 20 epidemiologic studies, with 32 different health outcomes. Studies of populations living near ONG operations provide limited evidence (modest scientific findings that support the outcome, but with significant limitations) of harmful health effects including asthma exacerbations and various self-reported symptoms. Study quality has improved over time and the highest rated studies within this assessment have primarily focused on birth outcomes. Additional high-quality studies are needed to confirm or dispute these correlations.

Identifying seminal papers in the Australasian Journal on Ageing 1982-2011: a Delphi consensus approach.

AIMS: The aim of this study was to identify seminal Australasian Journal on Ageing papers published over 30 years through a Delphi consensus process. METHOD: The main data collection was a three-round Delphi consensus study with 38 past and current members of the Australasian Journal on Ageing Editorial Board, Editorial Team and Management Committee. RESULTS: Three papers were agreed as top-ranking. One of the top-ranking articles was also highly cited. One article was published in the 1990 s, two in 2001. CONCLUSIONS: While it is difficult to judge how well the top-ranking papers represent seminal papers arising over 30 years, these papers do represent three different research strengths in Australasia, they do span three different disciplines, and they do reflect some of the diversity that characterises ageing research in Australasia over 30 years.