Dennis Kotchmar

Challenges for environmental epidemiology research: are biomarker concentrations altered by kidney function or urine concentration adjustment?

Biomonitoring has become a standard approach for exposure assessment in occupational and environmental epidemiology. The use of biological effect markers to identify early adverse changes in target organs has also become widely adopted. However, the potential for kidney function to affect biomarker levels in the body and the optimal approach to adjustment of biomarker concentrations in spot urine samples for hydration status are two important but underappreciated challenges associated with biomarker use. Several unexpected findings, such as positive associations between urine nephrotoxicant levels and estimated glomerular filtration rate (eGFR), have been reported recently in research using biomarkers. These and other findings, discussed herein, suggest an impact of kidney glomerular filtration or tubule processing on biomarker levels. This is more commonly raised in the context of decreased kidney filtration, traditionally referred to as reverse causality; however, recent data suggest that populations with normal kidney filtration may be affected as well. Misclassification bias would result if biomarkers reflect kidney function as well as either exposures or early biological effect outcomes. Furthermore, urine biomarker associations with eGFR that differ markedly by approach used to adjust for urine concentration have been reported. Associations between urine measures commonly used for this adjustment, such as urine creatinine, and specific research outcomes could alter observed biomarker associations with outcomes. Research recommendations to address the potential impact of kidney function and hydration status adjustment on biomarkers are provided, including a range of approaches to study design, exposure and outcome assessment, and adjustment for urine concentration.

The Influence of Declining Air Lead Levels on Blood Lead–Air Lead Slope Factors in Children

Background: It is difficult to discern the proportion of blood lead (PbB) attributable to ambient air lead (PbA), given the multitude of lead (Pb) sources and pathways of exposure. The PbB–PbA relationship has previously been evaluated across populations. This relationship was a central consideration in the 2008 review of the Pb national ambient air quality standards. Objectives: The objectives of this study were to evaluate the relationship between PbB and PbA concentrations among children nationwide for recent years and to compare the relationship with those obtained from other studies in the literature. Methods: We merged participant-level data for PbB from the National Health and Nutrition Examination Survey (NHANES) III (1988–1994) and NHANES 9908 (1999–2008) with PbA data from the U.S. Environmental Protection Agency. We applied mixed-effects models, and we computed slope factor, d[PbB]/d[PbA] or the change in PbB per unit change in PbA, from the model results to assess the relationship between PbB and PbA. Results: Comparing the NHANES regression results with those from the literature shows that slope factor increased with decreasing PbA among children 0–11 years of age. Conclusion: These findings suggest that a larger relative public health benefit may be derived among children from decreases in PbA at low PbA exposures. Simultaneous declines in Pb from other sources, changes in PbA sampling uncertainties over time largely related to changes in the size distribution of Pb-bearing particulate matter, and limitations regarding sampling size and exposure error may contribute to the variability in slope factor observed across peer-reviewed studies. Citation: Richmond-Bryant J, Meng Q, Davis A, Cohen J, Lu SE, Svendsgaard D, Brown JS, Tuttle L, Hubbard H, Rice J, Kirrane E, Vinikoor-Imler LC, Kotchmar D, Hines EP, Ross M. 2014. The Influence of declining air lead levels on blood lead–air lead slope factors in children. Environ Health Perspect 122:754–760; http://dx.doi.org/10.1289/ehp.1307072

A multi-level model of blood lead as a function of air lead

National and local declines in lead (Pb) in blood (PbB) over the past several years coincide with the decline in ambient air Pb (PbA) concentrations. The objective of this work is to evaluate how the relationship between PbB levels and PbA levels has changed following the phase out of leaded gasoline and tightened controls on industrial Pb emissions over the past 30 years among a national population sample. Participant-level data from the National Health and Nutrition Examination Survey (NHANES) were employed for two time periods (1988-1994 and 1999-2008), and the model was corrected for housing, demographic, socioeconomic, and other covariates present in NHANES. NHANES data for PbB and covariates were merged with PbA data from the U.S. Environmental Protection Agency. Linear mixed effects models (LMEs) were run to assess the relationship of PbB with PbA; sample weights were omitted, given biases encountered with the use of sample weights in LMEs. The 1988-1994 age-stratified results found that ln(PbB) was statistically significantly associated with ln(PbA) for all age groups. The consistent influence of PbA on PbB across age groups for the years 1988-1994 suggests a ubiquitous exposure unrelated to age of the sample population. The comparison of effect estimates for ln(PbA) shows a statistically significant effect estimate and ANOVA results for ln(PbB) for the 6- to 11-year and 12- to 19-year age groups during 1999-2008. The more recent finding suggests that PbA has less consistent influence on PbB compared with other factors.

Contribution of Particle-Size-Fractionated Airborne Lead to Blood Lead during the National Health and Nutrition Examination Survey, 1999–2008

The objective of this work is to examine associations between blood lead (PbB) and air lead (PbA) in particulate matter measured at different size cuts by use of PbB concentrations from the National Health and Nutrition Examination Survey and PbA concentrations from the U.S. Environmental Protection Agency for 1999-2008. Three size fractions of particle-bound PbA (TSP, PM10, and PM2.5) data with different averaging times (current and past 90-day average) were utilized. A multilevel linear mixed effect model was used to characterize the PbB-PbA relationship. At 0.15 μg/m(3), a unit decrease in PbA in PM10 was significantly associated with a decrease in PbB of 0.3-2.2 μg/dL across age groups and averaging times. For PbA in PM2.5 and TSP, slopes were generally positive but not significant. PbB levels were more sensitive to the change in PbA concentrations for children (1-5 and 6-11 years) and older adults (≥ 60 years) than teenagers (12-19 years) and adults (20-59 years). For the years following the phase-out of Pb in gasoline and a resulting upward shift in the PbA particle size distribution, PbA in PM10 was a statistically significant predictor of PbB. The results also suggest that age could affect the PbB-PbA association, with children having higher sensitivity than adults.

The Estimation of Personal Exposures to Air Pollutants for a Community-Based Study of Health Effects in Asthmatics—Exposure Model

Estimates of individual personal exposure to ozone, nitrogen dioxide, pollen, temperature, and relative humidity for a group of asthmatics participating in a health effects study were obtained by means of a modelling approach utilizing fixed site monitoring data, regression relationships between fixed site and indoor and outdoor microenvironment concentrations, study subject activity patterns and study household characteristics. A considerable improvement in the accuracy of exposure assessment using the exposure model instead of fixed site measurements alone was demonstrated for ozone. This large refinement of zone exposure estimates was achieved using a simplified approach which emphasized the large differences between indoor and outdoor microenvironmental concentrations, and assumed relatively little heterogeneity in exposure within either of these two broad microenvironmental categories. Major sources of error in the exposure model for ozone include: failure to include indoor microenvironments with no air conditioning in the development of the model, inability to accurately apportion within-hour time spent in different microenvironments, and misclassification of hour-specific personal location by study subjects.

Exposure estimates for the Houston Area Asthma Study

Procedures for determining exposure extimates for the Houston Area Asthma Study are discussed. Two residential clusters of asthmatics in the Houston area have been studied as part of an overall attempt to assess the health effects of air pollution in the Texas Gulf Coast area. Air pollutant exposure data have been produced according to a three-tier monitoring scheme, i.e. (1) continuous data from centrally-located fixed stations, (2) residential indoor/outdoor measurements, and (3) personal monitoring. This air monitoring network should yield estimates of individual exposures for use in health effect correlations.The fixed sites and mobile continuously monitor ambient levels of ozone, nitrogen oxides, sulfur dioxide, carbon monoxide, and meteorological parameters (wind speed, wind direction, temperature, dew point, solar irradiation, and precipitation). Continuous sequential integrated sampling is preformed for total suspended particulates (TSP) and, inhalable particulates (IP) (total of < 2.5μm and 2.5–15.0 μm) by dichotomous samplers for 24 hr samplers), aldehydes (bubblers), and aeroallergens (intermittent rotorod samplers). In addition to gravimetric determinations, particulate filters are routinely analyzed for sulfate, nitrate, and (every third day) trace elements. Personal monitoring includes ozone, respirable particles, nitrogen dioxide and formaldehyde. A quality assurance/control program that meets specifications established in the EPA Quality Assurance Handbook for air pollution measurement systems was implemented. Examples of results consisting of unvalidated preliminary data from the monitoring for ozone for three participants is presented and approaches to determining exposure estimates are discussed for both an integrated exposure estimate and short time period exposure estimate.

Effect measure modification of blood lead–air lead slope factors

There is abundant literature finding that susceptibility factors, including race and ethnicity, age, and housing, directly influence blood lead levels. No study has explored how susceptibility factors influence the blood lead–air lead relationship nationally. The objective is to evaluate whether susceptibility factors act as effect measure modifiers on the blood lead–air lead relationship. Participant level blood lead data from the 1999 to 2008 National Health and Nutrition Examination Survey were merged with air lead data from the US Environmental Protection Agency. Linear mixed effects models were run with and without an air lead interaction term for age group, sex, housing age, or race/ethnicity to determine whether these factors are effect measure modifiers for all ages combined and for five age brackets. Age group and race/ethnicity were determined to be effect measure modifiers in the all-age model and for some age groups. Being a child (1–5, 6–11, and 12–19 years) or of Mexican-American ethnicity increased the effect estimate. Living in older housing (built before 1950) decreased the effect estimate for all models except for the 1–5-year group, where older housing was an effect measure modifier. These results are consistent with the peer-reviewed literature of time-activity patterns, ventilation, and toxicokinetics.