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. Author manuscript; available in PMC: 2019 Jun 1.
Published in final edited form as: Curr Epidemiol Rep. 2018 Apr 10;5(2):79–91. doi: 10.1007/s40471-018-0140-5

Table 3.

Summary of recent studies in children that found significant associations between ambient and traffic-related exposures with metabolic dysfunction

Reference Study Design Location Sample Size Pollutants with Significant Associations* Main Findings
Alderete et. al. (2017) Longitudinal Los Angeles, CA, USA 314 NO2, PM2.5 ↓ SI, ↓ β-cell function (DI)
Ghosh et. al. (2017) Prospective /Intervention New York Area, USA 75 NO2, PM2.5 ↓ Metabolic benefits (e.g., HbA1c) of laparoscopic adjustable gastric banding
Thiering et. al. (2016) Cross-sectional Southern and Western Germany 837 PM10, NO2 ↑ HOMA-IR
Toledo-Corral & Alderete et. al. (2016) Cross-sectional Los Angeles, CA, USA 429 PM2.5, NO2, NOX ↑ Fasting glucose, ↓ Fasting insulin, ↓ SI, ↑ AIRg
Caldero n -Garciduen as et. al. (2015) Cross-sectional Mexico City Metropolitan Area (MCMA) and Polotitlán, Mexico (Control City) 54 MCMA and 26 Controls Matched case vs. control for high vs. low exposure in Mexico Compared to control children, MCMA had ↑ Fasting glucose levels
Thiering et. al. (2013) Cross-sectional Munich, South Germany, and Wesel, West Germany, 397 NO2, PM2.5, Proximity to Roadway ↑ HOMA-IR

Summarizes the main findings from studies in children between 2012 and 2017 that were included in this review. Pollutants listed are those found to be significantly associated with at least one measure of metabolic dysfunction. AIRg: acute insulin response to glucose, DI: disposition index, HbA1c: hemoglobin A1C, HOMA-IR: homeostatic model assessment of insulin resistance, NO2: nitrogen dioxide, PM: particulate matter, SI: insulin sensitivity, MCMA: Mexico City Metropolitan Area.

*

Statistically significant associations at a p-value <0.05.