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Journal of Undergraduate Research

Keywords

predict preadolescent children, indoor PM10 exposures

College

Life Sciences

Department

Health Science

Abstract

Asthma is the most common chronic disease among children worldwide, and the third-ranking cause of hospitalization for children under 15 years of age.(1-2) While the exact causes are unknown, studies show that having a genetic predisposition coupled with early-life allergen exposures increases the likelihood of developing asthma.(3) For inhalation exposure to occur, allergens must be airborne and must have an aerodynamic particle diameter of 10μm or less (PM10). Particles 10μm or less can penetrate to the bronchial region of the lungs. In sensitized individuals, inhaled allergens that reach the bronchi can initiate a hyper-responsive immune reaction, resulting in airway constriction, wheezing, and shortness of breath. House dust has been implicated as a major source of exposure to allergens. While low levels of allergens can be found floating in the air inside the home, we hypothesize that childhood allergen exposures occur primarily through the re-suspension of settled dust found in reservoirs such as carpets, bedding, and upholstered furniture. Furthermore, this dust re-suspension occurs in the immediate vicinity of the child while playing on the dust reservoir and is dependent on the type of play and level of activity. However, few studies have considered how children’s activity levels influence their PM10 dust exposures. Most studies measure allergen levels in settled house dust, and use this measure as a surrogate of exposure. Price et al. (1990), however, found that reservoir carpet sampling is not a good indicator of inhaled antigen load.(4) Personal breathing zone samples collected within 6 – 9 inches of the nose and mouth are preferred when conducting exposure assessments because contaminants are collected from air representative of that entrained into the lungs during inhalation; however, this method is expensive and difficult to use in large studies. Development of a mathematical exposure model will help identify how reservoir dust load, ambient PM10, and physical activity contribute to a child’s breathing zone PM10 exposure. We hypothesize that by adding ambient PM10, and the child’s activity level, we can improve the prediction of breathing zone allergen exposures. If the model is more predictive than reservoir sampling alone, future studies could refine their exposure estimates without having to collect personal breathing zone samples.

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