IADR Abstract Archives
SES and dental outcomes in young children using population data
Objectives: Socio-economic status (SES) is a pervasive but obtuse concept in understanding social determinants and oral health. Armfield 2007 has highlighted the association SES measures and child oral health and Thomson et al. (2004, 2006) the interplay of area and household SES measures. We have previously adjusted for Socio-Economic Index for Area (SEIFA) for level of disadvantage in analysis but not investigated in groups. Objective was to investigate the association of SES with oral health outcomes (particularly hospital admissions) in young children using population linkable data.
Methods: Linkable data regarding children born live 1980-1995 followed for five years in WA (midwives, hospital admissions, births, deaths) were used, linked to population databases for birth defects and intellectual disability (ID). Data was extensively cleaned. It is used here to investigate the relationship between dental hospital admissions and area based measures of socioeconomic status. The measure used was odds of admission by SEIFA quartile using population level SEIFA. Data were stratified to investigate SES trends using SEIFA with univariate and multivariable analysis, stratifying data. Most analyses used urban data. Risk from multiple comparisons considered.
Results: Generally the odds of an admission increased the lower the SES group but this varies in different population groups. Trends varied with factors such as rurality, mothers’ ethnicity and ID. For example remote children (1.25, 1.18, 0.85; with increasing advantage): non-Indigenous children (1.05, 0.93, 0.83); children without ID (1.01, 0.92, 0.82).
Conclusions: There are limitations in interpretation of hospital admissions and SEIFA. However, area measures such as SEIFA provide some value in investigating SES impacts on dental outcomes in young children but we need to better understand influences on oral health. Acknowledge Drs Anne Read and Lyn Colvin for advice.
Methods: Linkable data regarding children born live 1980-1995 followed for five years in WA (midwives, hospital admissions, births, deaths) were used, linked to population databases for birth defects and intellectual disability (ID). Data was extensively cleaned. It is used here to investigate the relationship between dental hospital admissions and area based measures of socioeconomic status. The measure used was odds of admission by SEIFA quartile using population level SEIFA. Data were stratified to investigate SES trends using SEIFA with univariate and multivariable analysis, stratifying data. Most analyses used urban data. Risk from multiple comparisons considered.
Results: Generally the odds of an admission increased the lower the SES group but this varies in different population groups. Trends varied with factors such as rurality, mothers’ ethnicity and ID. For example remote children (1.25, 1.18, 0.85; with increasing advantage): non-Indigenous children (1.05, 0.93, 0.83); children without ID (1.01, 0.92, 0.82).
Conclusions: There are limitations in interpretation of hospital admissions and SEIFA. However, area measures such as SEIFA provide some value in investigating SES impacts on dental outcomes in young children but we need to better understand influences on oral health. Acknowledge Drs Anne Read and Lyn Colvin for advice.