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Original Research

Building a stronger child dental health system in Australia: statistical sampling masks the burden of dental disease distribution in Australian children

Submitted: 19 April 2013
Revised: 12 December 2013
Accepted: 23 March 2014
Published: 15 September 2014

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Author(s) : Tennant M, Kruger E.

Marc TennantEstie Kruger

Citation: Tennant M, Kruger E.  Building a stronger child dental health system in Australia: statistical sampling masks the burden of dental disease distribution in Australian children. Rural and Remote Health (Internet) 2014; 14: 2636. Available: http://www.rrh.org.au/articles/subviewnew.asp?ArticleID=2636 (Accessed 17 October 2017)

ABSTRACT

Introduction:  In Australia, over the past 30 years, the prevalence of dental decay in children has reduced significantly, where today 60–70% of all 12-year-olds are caries free, and only 10% of children have more than two decayed teeth. However, many studies continue to report a small but significant subset of children suffering severe levels of decay.
Methods:  The present study applies Monte Carlo simulation to examine, at the national level, 12-year-old decayed, missing or filled teeth and shed light on both the statistical limitation of Australia’s reporting to date as well as the problem of targeting high-risk children.
Results:  A simulation for 273 000 Australian 12-year-old children found that moving from different levels of geographic clustering produced different statistical influences that drive different conclusions. At the high scale (ie state level) the gross averaging of the non-normally distributed disease burden masks the small subset of disease bearing children. At the much higher acuity of analysis (ie local government area) the risk of low numbers in the sample becomes a significant issue.
Conclusions:  The results clearly highlight the importance of care when examining the existing data, and, second, opportunities for far greater levels of targeting of services to children in need. The sustainability (and fairness) of universal coverage systems needs to be examined to ensure they remain highly targeted at disease burden, and not just focused on the children that are easy to reach (and suffer the least disease).

Key words: childhood, computational mathematics, dental decay, dental public health, Monte Carlo.

This abstract has been viewed 2623 times since 15-Sep-2014.

   
 

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