Socioeconomic inequalities in child oral health: a comparison of discrete and composite area-based measures.
OBJECTIVE
This study aims to examine the relationship between child caries prevalence and six discrete area-based measures of socioeconomic status (SES). Comparisons were also made of the discrete SES measures and the Socio-Economic Index for Areas (SEIFA) composite index in explaining child caries experience.


METHODS
Oral health data were electronically captured for 58,463 4- to 16-year-old children enrolled in the School Dental Service of South Australia in 2001. Socioeconomic measures for the same year were extracted from Basic Community Profiles for postcodes available from the Australian Bureau of Statistics.


RESULTS
There were generally consistent linear relationships between caries prevalence and SES with children having poorer oral health residing in areas of greater socioeconomic disadvantage. This was evident across all SES measures, although some variations were shown for some measures. Children from more socioeconomically disadvantaged areas had higher odds of having either one or more decayed, missing, or filled teeth or four or more decayed, missing, or filled teeth. Most discrete SES measures explained a significant amount of the variance in oral disease beyond that accounted for by the composite SEIFA index.


CONCLUSIONS
Pervasive social inequality in child oral health exists in Australia. Specific area-based measures of SES are valuable in documenting these inequalities and may be more meaningful than composite area-based indices of SES.
Armfield
Jason M
JM
Send correspondence and reprint requests to Jason AIHW Dental Statistics and Research Unit, Australian Research Centre for Population Oral Health, The University of Adelaide, South Australia 5005, Australia. jason.armfield@adelaide.edu.au
D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D004245:DMF Index; D003731:Dental Caries / Q000191:economics / Q000453:epidemiology*; D005260:Female; D006297:Health Services Accessibility / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D011204:Poverty Areas; D015995:Prevalence; D012044:Regression Analysis; D017062:Small-Area Analysis; D012923:Social Class; D013021:South Australia / Q000453:epidemiology; D035862:Vulnerable Populations