Conditions associated with levels of allergens and fungal aerosols in selected homes of selected primary school children in Durban.
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This indoor environment study formed part of the South Durban Health Study (SDHS) that investigated the health effects of exposure to ambient air pollution. Homes of children from seven communities corresponding schools were recruited to participate. This study was designed to determine characteristics in the homes that are associated with higher or lower levels of allergens and fungal aerosols. Homes were inspected using a field tested walkthrough checklist to collect data on home characteristics associated to adverse health effects. The characteristics include dampness, visible mould, type of flooring, type of bedding, type of heating systems, and building type and age. Dust samples for allergen analysis were collected from the bedding and the floor of the sleep area used by the children. Air samples from all rooms in the house were collected on malt extract agar, the media used for identifying and quantifying airborne fungal aerosols. More than 70% of the homes were single units standing on their own, 20% were attached houses (flats or apartments) and the rest (10%) were informal houses. Construction material of the homes comprised of bricks (93%), wood (5%) and other material (2%) such as corrugated iron of which 94% were formally constructed. Dampness signs were observed in 51% of the homes and visible mould growth 13% of them. In all them, at least one characteristic that is hypothetically associated to elevated house dust mite allergens was found. Levels of mould (Asp f 1) allergen and house dust mite (Der p 1 and Der f 1) allergen were comparable to levels found in other parts of the world. Asp f 1 allergen levels ranged between 0.32-1.379g/g and Der p 1 and Der f 1 allergen levels ranged from undetectable to 49.61 and from undetectable to 39.319g/g of dust respectively. Some home characteristics from walkthrough checklist were associated with Asp f 1, Der p1 and Der f 1 allergen levels when simple regression analysis was performed. Asp f 1 was significantly associated with single family home [OR= 0.004 (95%CI 0.004–0.35)] and polyester filled pillows [OR= 0.07 (95%CI 0.01– 0.61)] in logistic regression models. Der p 1 allergen was associated with observed extent of roof dampness [OR= 0.33 (95%CI 0.13–0.81)]. Fungal aerosol mixture consisted of Cladosporium spp. as the predominant genus together with other genera such as Aspergillus, Penicillium and Fusarium were, to a lesser extent, identified in the samples from the homes. Mean concentration of total indoor fungal aerosol of indoor and outdoor were 1108 CFU/m3 and 1298 CFU/m3 respectively. Individual genera of fungi in the childrens sleep area had mean levels of 783 CFU/ m3, 30CFU/ m3, 64CFU/ m3, 48CFU/ m3 and 43 CFU m3 for Cladosporium spp., Aspergillus spp., Penicillium, spp., Fusarium spp. and Rhizopus spp. respectively. Simple regression showed some conditions in the homes to be predictors of higher levels of total fungal aerosols. In a linear regression models, total outdoor fungal levels were a protective effect on total indoor fungal levels [C= 0.542 (95%CI 0.437–0.647)] whilst homes with hard floors had about 25 CFU/m3 [C= 5.235 (95%CI 0.557–9.913)] in the homes were significantly associated. This study showed the need to adapt observational instrument/ checklist/ questionnaire to suit the environment or the study area of interest. As other studies and findings indicated, the best way to assess exposure to biological pollutants indoors needs a combination of two or more methods, i.e. direct and indirect methods.