- Sultana, Daniel;
- Kauffman, Duyen;
- Castorina, Rosemary;
- Paulsen, Michael;
- Bartlett, Russell;
- Ranjbar, Kelsey;
- Gunier, Robert;
- Aguirre, Victor;
- Rowen, Marina;
- Garban, Natalia;
- DeGuzman, Josephine;
- She, Jianwen;
- Patterson, Regan;
- Simpson, Christopher;
- Bradman, Asa;
- Hoover, Sara
BACKGROUND: Diesel exhaust (DE) exposures pose concerns for serious health effects, including asthma and lung cancer, in California communities burdened by multiple stressors. OBJECTIVE: To evaluate DE exposures in disproportionately impacted communities using biomonitoring and compare results for adults and children within and between families. METHODS: We recruited 40 families in the San Francisco East Bay area. Two metabolites of 1-nitropyrene (1-NP), a marker for DE exposures, were measured in urine samples from parent-child pairs. For 25 families, we collected single-day spot urine samples during two sampling rounds separated by an average of four months. For the 15 other families, we collected daily spot urine samples over four consecutive days during the two sampling rounds. We also measured 1-NP in household dust and indoor air. Associations between urinary metabolite levels and participant demographics, season, and 1-NP levels in dust and air were evaluated. RESULTS: At least one 1-NP metabolite was present in 96.6% of the urine samples. Detection frequencies for 1-NP in dust and indoor air were 97% and 74%, respectively. Results from random effect models indicated that levels of the 1-NP metabolite 6-hydroxy-1-nitropyrene (6-OHNP) were significantly higher in parents compared with their children (p-value = 0.005). Urinary 1-NP metabolite levels were generally higher during the fall and winter months. Within-subject variability was higher than between-subject variability (~60% of total variance versus ~40%, respectively), indicating high short-term temporal variability. IMPACT: Biomonitoring, coupled with air monitoring, improves understanding of hyperlocal air pollution impacts. Results from these studies will inform the design of effective exposure mitigation strategies in disproportionately affected communities.