Presentation on theme: "Social Class and Oral Health. A comparison between the 1988 and 1998 Adult Oral Health Surveys Juan Gonzalez, Jimmy Steele, Nairn Wilson, Nora Donaldson."— Presentation transcript:
Social Class and Oral Health. A comparison between the 1988 and 1998 Adult Oral Health Surveys Juan Gonzalez, Jimmy Steele, Nairn Wilson, Nora Donaldson
Fewer teeth is associated with… Poor dental attendance. (Sanders et al, 2006) Low socio-economic group (Sakki et al, 1994) Increasing age (Todd & Lader, 1991) BACKGROUND
Regular Dental Attendance may be a factor contributing to the socio-economic gradient in oral health: Regular dental attendance is more prevalent in high socio- economic groups and is associated with better oral health outcomes, after adjustment for socio-economic status (SES). Barriers (i.e. attitudes and perceptions) Attitudes and perceptions include: anxiety, cost concerns, value placed on restored teeth, and beliefs regarding the importance of regular dental attendance Positive attitudes and perceptions (Barriers) about dental attendance are associated with better oral health and tend to be held by high-socio-economic groups.
How these factors inter-relate ? Establishing the pathways between the various factors would improve the understanding of how… - demographic factors, - socio-economic status and - barriers to dental attendance impact on Regular Dental Attendance and on the number of sound teeth (NST).
In the 1998 UK Adult Dental Health Survey (n=3800) Using Structural Equation Modeling: (Donaldson et al, JDR, Jan 2008) Found that the association between social class and the number of sound teeth (NST) SOCIAL CLASS NST Is partially explained by pathway: Barriers REGULAR ATTENDANCE
1998 UK Adult Oral Health Survey
Aim of present study In this study we examine the data on N=2210 participants from the 1988 UK Adult Oral Health Surveys to compare the effect of socio-economic status (SES) on oral health, between the two periods (1988 and 1998). Particular attention given to differences in the model structures (pathways) of that relationship.
Distribution of the number of sound teeth by decade of study. NST ordinal with 3 categories 1998: Continuous Mean: % c.i to NST N (%) fewer than (17%)473 (7%) between 10 and (37%)474 (17%) more than 201,031 (46%)2208 (77%)
Distribution of the number of sound teeth by decade of study
Sex Male Female 1080 (49%) 1128 (51%) 1745 (46%) 2072 (54%) Social class Poor Medium High 440 (20%) 1157 (54%) 557 (26%) 473 (18%) 1133 (42%) 1089 (40%) Age under (68%) 709 (32%) 2185 (76%) 690 (24%) Distribution of Factors for both surveys
Anxiety feel like that to some extent don't feel like that 737 (34%) 491 (23%) 936 (43%) 865 (23%) 936 (25%) 1949 (52%) Fancy feel like that to some extent don't feel like that 622 (29%) 471 (22%) 1,043 (49%) 878 (27%) 865 (27%) 1507 (46%) Cost feel like that to some extent don't feel like that 360 (17%) 406 (19%) 1,340 (64%) 1092 (35%) 923 (30%) 1090 (35%)
Multiple Ordinal Regression for NST (1988) OR95% CIP –value LowerUpper Social Class Medium: Poor High: Poor Sex Female: Male Age 55 over: Under Regular Occasional: Regular Seldom: Regular Anxiety Not anxious: anxious
Structural Equation Modelling (SEM) Pathways between the various predictors are explored. Variables are analysed simultaneously in the sequence of their operating order, allowing the predictors to have both direct and indirect influences on the outcome. SEM allows latent variables to be modelled, which reduces the likelihood of regression dilution (Der, 2001; Garson, 2004).
Structural equation model (1988)
Common Features 1988/1998 There is a significant direct pathway from Social Class to NST. There is a significant direct pathway from Regularity to NST. No direct pathway from Barriers to Social Class: Barriers mediates the effect of Social Class on NST.