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Aust N Z J Public Health ; 26(3): 203-7, 2002.
Article in English | MEDLINE | ID: mdl-12141613

ABSTRACT

OBJECTIVE: To determine the potential hazard posed by indoor lead dust to young children in Broken Hill, a silver-lead-zinc mining town in outback Australia, and the degree to which lead flux is influenced by factors such as geographical location, house construction type and condition. METHODS: 116 homes were selected and 93 (80%) studied from 10 localities in Broken Hill during the spring of 1995. Lead flux was measured using 85 mm diameter polystyrene petri dishes. Dishes were placed in four rooms of each house to collect dust over a six-to-eight-week period. Data on the location, condition and construction type of each house were recorded. Multiple linear regression was used to determine predictors of lead flux. Flux data were log transformed for the analysis. RESULTS: Average household lead flux varied nearly seven-fold across districts from a low of 166 (distant from the mines), to a high of 1,104 microg/m2/30-day period (adjacent to the mines). Houses that were 'adequately sealed' had 2.9 times the lead flux, and 'poorly sealed' houses 4.3 times the flux, of 'very well sealed' houses. Construction material did not significantly affect these flux levels, and no statistically significant interactions were found between house condition and location or house type. CONCLUSIONS: Many Broken Hill homes have high levels of lead flux that pose a potential risk to young children. Quantification of this hazard provides useful information for the community that can help focus efforts on actions required to minimise lead dust in the home. IMPLICATIONS: Household dust is a potential source of lead for young children in at-risk communities. Information on lead flux in homes can assist these communities and public health agencies to better understand and deal more effectively with the problem.


Subject(s)
Air Pollution, Indoor , Lead Poisoning/epidemiology , Lead , Child, Preschool , Dust , Housing , Humans , Lead/blood , Linear Models , Mining , New South Wales/epidemiology , Risk Factors , Rural Health
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