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BACKGROUND: Manganese (Mn) plays a significant role in both human health and global industries. Epidemiological studies of exposed populations demonstrate a dose-dependent association between Mn and neuromotor effects ranging from subclinical effects to a clinically defined syndrome. However, little is known about the relationship between early life Mn biomarkers and adolescent postural balance OBJECTIVES: This study investigated the associations between childhood and adolescent Mn biomarkers and adolescent postural balance in participants from the longitudinal Marietta Communities Actively Researching Exposures Study (CARES) cohort. METHODS: Participants were recruited into CARES when they were 7–9 y old, and reenrolled at 13–18 years of age. At both time points, participants provided samples of blood, hair, and toenails that were analyzed for blood Mn and lead (Pb), serum cotinine, hair Mn, and toenail Mn. In adolescence, participants completed a postural balance assessment. Greater sway indicates postural instability (harmful effect), whereas lesser sway indicates postural stability (beneficial effect). Multivariable linear regression models were conducted to investigate the associations between childhood and adolescent Mn biomarkers and adolescent postural balance adjusted for age, sex, height–weight ratio, parent/caregiver intelligence quotient, socioeconomic status, blood Pb, and serum cotinine. RESULTS: CARES participants who completed the adolescent postural balance assessment (푛 = 123) were 98% White and 54% female and had a mean age of 16 y (range: 13–18 y). In both childhood and adolescence, higher Mn biomarker concentrations were significantly associated with greater adolescent sway measures. Supplemental analyses revealed sex-specific associations; higher childhood Mn biomarker concentrations were significantly associated with greater sway in females compared with males DISCUSSION: This study found childhood and adolescent Mn biomarkers were associated with subclinical neuromotor effects in adolescence. This study demonstrates postural balance as a sensitive measure to assess the association between Mn biomarkers and neuromotor function. [ABSTRACT FROM AUTHOR]

BACKGROUND: Air pollution risk assessments do not generally quantify health impacts using multipollutant risk estimates, but instead use results from single-pollutant or copollutant models. Multipollutant epidemiological models account for pollutant interactions and joint effects but can be computationally complex and data intensive. Risk estimates from multipollutant studies are therefore challenging to implement in the quantification of health impacts. OBJECTIVES: Our objective was to conduct a case study using a developmental multipollutant version of the Environmental Benefits Mapping and Analysis Program—Community Edition (BenMAP-CE) to estimate the health impact associated with changes in multiple air pollutants using both a single and multipollutant approach. METHODS: BenMAP-CE was used to estimate the change in the number of pediatric asthma emergency department (ED) visits attributable to simulated changes in air pollution between 2011 and 2025 in Atlanta, Georgia, applying risk estimates from an epidemiological study that examined shortterm single-pollutant and multipollutant (with and without first-order interactions) exposures. Analyses examined individual pollutants (i.e., ozone, fine particulate matter, carbon monoxide, nitrogen dioxide (NO2), sulfur dioxide, and particulate matter components) and combinations of these pollutants meant to represent shared properties or predefined sources (i.e., oxidant gases, secondary pollutants, traffic, power plant, and criteria pollutants). Comparisons were made between multipollutant health impact functions (HIF) and the sum of single-pollutant HIFs for the individual pollutants that constitute the respective pollutant groups. RESULTS: Photochemical modeling predicted large decreases in most of the examined pollutant concentrations between 2011 and 2025 based on sector specific (i.e., source-based) estimates of growth and anticipated controls. Estimated number of avoided asthma ED visits attributable to any given multipollutant group were generally higher when using results from models that included interaction terms in comparison with those that did not. We estimated the greatest number of avoided pediatric asthma ED visits for pollutant groups that include NO2 (i. e., criteria pollutants, oxidants, and traffic pollutants). In models that accounted for interaction, year-round estimates for pollutant groups that included NO2 ranged from 27.1 [95% confidence interval (CI): 1.6, 52.7; traffic pollutants] to 55.4 (95% CI: 41.8, 69.0; oxidants) avoided pediatric asthma ED visits. Year-round results using multipollutant risk estimates with interaction were comparable to the sum of the single-pollutant results corresponding to most multipollutant groups [e.g., 52.9 (95% CI: 43.6, 62.2) for oxidants] but were notably lower than the sum of the single-pollutant results for some pollutant groups [e.g., 77.5 (95% CI: 66.0, 89.0) for traffic pollutants]. DISCUSSION: Performing a multipollutant health impact assessment is technically feasible but computationally complex. It requires time, resources, and detailed input parameters not commonly reported in air pollution epidemiological studies. Results estimated using the sum of single-pollutant models are comparable to those quantified using a multipollutant model. Although limited to a single study and location, assessing the trade-offs between a multipollutant and single-pollutant approach is warranted. [ABSTRACT FROM AUTHOR]