BackgroundLimited research has been undertaken in Australia to assess the dental status of pre-school Aboriginal children. This cross-sectional study records the number of decayed, missing and filled teeth (dmft) and surfaces (dmfs) of pre-school Aboriginal children living in different locations in New South Wales (NSW), Australia.MethodsA convenience sample of young children from seven Aboriginal communities in rural, remote and metropolitan areas of NSW, was recruited. One calibrated examiner recorded the dmft/s of children with written parental consent.Results196 children were invited to participate and 173 children aged two to five years were examined, a response rate of 88.3 %. Forty percent (n = 69) of the children were diagnosed with dental caries with a mean of 2.1 (SD = 3.6). The dmft scores were significantly higher in remote locations when compared to rural (p = <0.0001) and metropolitan areas (p = 0.0155). Children 4–5 years old living in remote NSW had a mean dmft of 3.5 and mean dmfs of 8.0 compared with children living in rural areas who had a dmft and dmfs of 1.5 and 4.2 respectively. Untreated dental caries was the primary contributor to the scores, and children who had previously received dental treatment still had active carious lesions.ConclusionThere was a high prevalence of untreated dental caries among the Aboriginal children, particularly for those in remote locations.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-015-2673-6) contains supplementary material, which is available to authorized users.
In response to pandemic-related shortages in medical supplies, the authors use an institutional review board-supervised research protocol to clinically test a 3Dprinted face shield in a hospital emergency department. This allowed a major academic medical center to incorporate locally manufactured personal protective equipment into the care of COVID-19 patients.
Background:
Mediation analysis is a powerful tool for understanding mechanisms, but conclusions about direct and indirect effects will be invalid if there is unmeasured confounding of the mediator–outcome relationship. Sensitivity analysis methods allow researchers to assess the extent of this bias but are not always used. One particularly straightforward technique that requires minimal assumptions is nonetheless difficult to interpret, and so would benefit from a more intuitive parameterization.
Methods:
We conducted an exhaustive numerical search over simulated mediation effects, calculating the proportion of scenarios in which a bound for unmeasured mediator–outcome confounding held under an alternative parameterization.
Results:
In over 99% of cases, the bound for the bias held when we described the strength of confounding directly via the confounder–mediator relationship instead of via the conditional exposure–confounder relationship.
Conclusions:
Researchers can conduct sensitivity analysis using a method that describes the strength of the confounder–outcome relationship and the approximate strength of the confounder–mediator relationship that, together, would be required to explain away a direct or indirect effect.
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