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Keywords:

  • accessability;
  • dental care;
  • socio-economic factors;
  • adults

Abstract

  1. Top of page
  2. Abstract
  3. Methods
  4. Analysis
  5. Results
  6. Discussion
  7. Implications
  8. Conclusion
  9. Acknowledgements
  10. References

Objectives:The aim of this study was to assess social inequality in use of dental services by examination of visiting for relief of pain and receipt of extractions.

Methods: Data were collected in the period of 2004-06, from a stratified clustered sample of Australians aged 15+ years, using a computer-aided telephone interview. Analysis was restricted to n=10,099 dentate adults.

Results: Visiting for relief of pain varied by age, country of birth, education and income with lower odds (Odds ratio, 95%CI) among 55-74 (0.43, 0.35-0.54) and 75+ year-olds (0.22, 0.15-0.33) compared to the 15-34 year-olds, lower odds among Australian-born persons (0.82,0.69-0.98) compared to those born overseas, higher odds for those with no post-secondary education (1.31, 1.07-1.61) and with TAFE, trade or other qualifications (1.34, 1.09-1.66) compared to university qualified, and for those in the <$20,000 income group (1.61, 1.23-2.12), the $20,000-<$40,000 (1.53, 1.20-1.96) and the $40,000-<$60,000 group (1.33, 1.02-1.72) compared to <$80,000+. Receipt of extractions varied by age, sex, qualifications and income, with lower odds of extraction among persons of 75+ years (0.61,0.40-0.93) compared to the youngest age group, higher odds among males (1.34, 1.13-1.59) compared to females, those with no post-secondary education (1.59, 1.27-1.99) and with TAFE, trade or other qualifications (1.49, 1.21-1.84) compared to university qualified, and for the income groups <$20,000 (3.06, 2.27-4.12), $20,000-<40,000 (2.37, 1.80-3.12) and $40,000-<60,000 (1.94 1.47-2.55) compared to the $80,000+ income group.

Conclusions: The results indicate social inequality in provision of dental services and suggest an urgent need for the dental profession and governments to address this inequality.

The philosophy underlying Australia's health system is that health is a right and that access to health care should not be related to ability to pay. This philosophy is in line with Priester1 who argues that fair access should be the pre-eminent value within any health care system. Fair access does not apply to oral health care in Australia as funding for dental services is predominantly an out-of-pocket expense for individuals.2

Access to regular dental care for check-ups and maintenance is associated with better oral health and quality of life. However, pain and other problems are strongly associated with use of dental services.3 Adults who make a dental visit when they are experiencing pain are likely to have more advanced disease and thus more limited treatment options.4 Brennan et al.5 found that extraction rates were higher at emergency visits than at visits for general care.

The decision to extract a tooth reflects a complex interaction between patient and provider. There are a number of possible explanations for extraction rates, some of which relate to characteristics of the patients (e.g. late presentation of the problem, ability to pay, value placed on retention of teeth, and ability to discuss treatment options). Other factors which could be important include factors relating to the dental provider (e.g. assumptions about the values and therefore the wishes of the patient, or ease of treatment).6 Whatever the explanation, the loss of teeth is regarded as a negative health outcome and it is of concern when extraction is significantly associated with socio-demographic factors as it indicates likely inequalities in oral health outcomes between different groups in the population.

Social inequality in health may be reflected in access to care issues related to irregular, symptomatic visiting and receipt of care resulting in tooth loss. The aims of this study were to assess social inequality in use of dental services in terms of whether the reason for visit was for relief of pain and if extraction services were received.

Methods

  1. Top of page
  2. Abstract
  3. Methods
  4. Analysis
  5. Results
  6. Discussion
  7. Implications
  8. Conclusion
  9. Acknowledgements
  10. References

Sampling and data collection

The 2004-06 National Survey of Adult Oral Health (NSAOH) involved a three-stage, stratified clustered sampling design to select a sample of Australians aged 15+ years from households with telephone numbers from a electronic white pages database.7 From this sampling frame, 15 strata were selected with population proportional to size selection. The strata comprised metropolitan and non-metropolitan areas of seven States/Territories and the single stratum of the ACT. Postcode comprised the primary sampling unit, with household being the secondary sampling unit. The sample was approached to participate in a computer-assisted telephone interview (CATI), followed by an oral epidemiological examination and a mailed questionnaire.

Variables measured

In the first stage of data collection respondents supplied information during a CATI on variables such as self-reported health status, use of dental services, demographics and socio-economic status.

Measurement of dental services

The percentage of persons who reported making a dental visit for relief of pain within the past two years, and the percentage of persons who reported receiving a dental extraction in the past year comprised the dependent variables. These different time periods alter the number of people in each analysis.

Measurement of socio-economic position

The explanatory variables consisted of age, sex, country of birth, highest level of educational qualifications, occupation, and income. Age was coded into four categories (15-34, 35-54, 55-74 and 75+ years) to simulate differing dental generations e.g. 15-34 years the fluoride generation. Qualifications were coded as university/college and other (comprising trade, technical or TAFE, and other) which gave a 55%, 45% split of the data, country of birth was coded as Australia and overseas, occupation was classified using ASCO codes8 and recoded into manager/professional/para-professional, clerical/sales and services/other and blue collar/tradespersons groupings, while income was coded into five categories (<$20,000, $20,000-<$40,000, $40,000-<$60,000, $60,000-<$80,000 and $80,000+). The research was approved by the Human Research Ethics Committee of the University of Adelaide.

Analysis

  1. Top of page
  2. Abstract
  3. Methods
  4. Analysis
  5. Results
  6. Discussion
  7. Implications
  8. Conclusion
  9. Acknowledgements
  10. References

The analysis was restricted to dentate persons aged 15 years or older, who had made a dental visit within the past two years. Data were weighted by state/territory, metropolitan/non-metropolitan location, age and sex. To account for design effects associated with the complex sample design, data were analysed using survey procedures that adjusted for strata and primary sampling units.9 Initially, age-specific distributions of the explanatory variables of sex, country of birth, qualifications, occupation, and income were tabulated. Unadjusted bivariate associations of this set of explanatory variables were then tabulated for the percentage of persons making a dental visit for relief of pain within the past two years, and for the percentage of persons receiving a dental extraction in the past year. Adjusted odds were then determined from multivariate logistic regression models of persons making a dental visit for relief of pain within the past two years and for persons receiving a dental extraction in the past year, with the dependent variables coded as one with the reference category coded as zero. Occupation was omitted from the multivariate analyses as it was not a significant predictor when it is added to both logistic regression models, in fact it did not improve the Pseudo R-squared value.

Results

  1. Top of page
  2. Abstract
  3. Methods
  4. Analysis
  5. Results
  6. Discussion
  7. Implications
  8. Conclusion
  9. Acknowledgements
  10. References

Response and distributions

In the NSAOH a total of n=14,123 adults responded to the CATI, a 49% response rate. This analysis was restricted to dentate adults aged 15+ years who had made a dental visit in the previous two years (n=10,099). The number of people who visited for relief of pain was 2,358, and 1,143 reported an extraction in the past year. Distributions of explanatory variables are presented in Table 1. There were only a small proportion of persons in the oldest age group (5.2%), reflecting the scope of the study. There were similar proportions of males (47.6%) and females (52.4%), of university (34.9%) and trade/TAFE/other qualifications (29.2%) as well as more with no education beyond schooling (35.9%). There were similar proportions of managers/professional (46.8%) and clerical/sales and other (28.4%) with somewhat fewer blue collar/tradespersons (24.9%). The majority of persons were Australian-born (76.6%). The largest proportion by income was observed in the $80,000+ income category (30.8%). Age-specific variation in distributions was observed for country of birth with highest proportion of Australian-born persons observed in the 15-34 years age group (82.5%), highest qualification where a greater proportion of those with no education beyond schooling were in the 15-34 and 75+ year age groups and income where higher proportions of older adults tended to be in the lower income groups with 48.4% of 75+ year-olds in the <$20,000 income group.

Table 1.  Distribution of explanatory variables (all persons).
 AGE CATEGORY (col%)
 15-34 years35-54 years55-74 years75+ yearsAll ages
 na%bSEcna%bSEcna%bSEcna%bSEcna%bSEc
  1. Notes:

  2. (a) unweighted

  3. (b) weighted

  4. (c) standard errors corrected for complex sample design

Sex(ns, p=0.100)
  Male88447.81.4153947.31.0116149.21.224941.72.1383347.60.7
  Female150252.21.4265052.71.0172150.81.239358.32.1626652.40.7
Country of birth(p≤0.0001)
  Australia200782.51.1321074.81.0203269.91.249377.41.8774276.60.7
  Overseas37617.51.197525.21.084930.11.214722.61.8234723.40.7
Highest Qual(p≤0.0001)
  University/College68431.31.3173140.01.197833.11.216925.12.1356234.90.8
  Trac/AFE/Other52327.11.4125630.71.083730.21.116225.42.0277829.20.7
  No education beyond schooling80841.61.4119829.30.9106336.61.130949.52.3337835.90.7
Occupation(p≤0.0001
  Manager/Professional/Para-professional63936.91.6183852.21.159053.21.9658.912.2307346.80.9
  Clerical/sales & Service/Other58936.51.691824.50.828721.11.416.86.9179528.40.7
  Blue collar/Tradesperson34226.61.668423.31.025025.71.7434.311.8128024.90.8
Income(p≤0.0001
  <$20K1366.30.63276.30.572223.81.031248.42.7149712.40.5
  $20,000-<40,00036817.51.166315.60.782629.91.017733.92.4203420.30.6
  $40,000-<60,00044221.01.285220.80.844917.10.85410.81.7179719.50.6
  $60,000-<80,00038620.41.277319.70.824210.00.7214.11.1142216.90.5
  $80,000+64134.81.4137837.61.140919.21.2142.91.1244230.80.8
ALL (row%)2,38635.00.74,18938.40.72,88221.30.66425.20.310,099100.00.0

Unadjusted associations

A higher proportion of persons made dental visits for relief of pain among the two younger age groups of adults (57.9% and 56.2%) compared to the two older age groups (43.1% and 29.2%), for those in groups without university qualifications (55.8% and 54.4%) compared to university qualified persons (47.2%) and for those in the blue collar/tradesperson group (60.5%) compared to the other occupation groupings (51.2% and 53.8%) (see Table 2). Significant age-specific differences in relief of pain visiting were noted in some strata for country of birth, qualifications, occupation and income, for example, of the n=43 aged 15-34 years who earned <$20,000, 65% visited for relief of pain and by default 35% did not visit for relief of pain.

Table 2.  Bivariate associations for relief of pain visits (within the past two years).
 AGE CATEGORY (col%)
 15-34 years35-54 years55-74 years75+ yearsAll ages
 na%bSEcna%bSEcna%bSEcna%bSEcna%bSEc
  1. Notes:

  2. (a) unweighted

  3. (d) p<0.05

  4. (b) weighted

  5. (e) p<0.01

  6. (c) Standard errors corrected for complex sample design

Sex               
  Male18059.03.346257.72.227144.22.34434.35.495753.41.4
  Female33557.02.668254.71.734441.92.04025.34.3140150.71.2
Country of birth       e       
  Australia42957.02.387955.21.740040.81.86228.93.7177051.21.2
  Overseas8662.95.026459.42.721548.12.82230.56.358755.01.8
Highest Qualification d  e     d  e 
  University/College12351.34.235649.92.418142.93.11315.65.367347.21.7
  Trade/TAFE/Other16866.13.5377756.82.521545.22.82841.17.078855.81.7
  No education beyond schooling19563.63.641161.82.521841.42.34228.94.386654.41.7
Occupation    d        e 
  Manager/Professional/Para-professional12555.84.142053.42.29638.23.70064151.21.8
  Clerical/sales & Service/Other12458.84.124252.53.06544.55.00043153.82.1
  Blue colla/Tradesperson10564.04.625262.93.17547.04.40043260.52.4
Income    d  d       
  <$20,0004365.17.513760.64.119648.42.84934.34.942551.22.2
  $20,000-<40,00011163.44.725464.02.916943.43.42229.26.055654.82.0
  $40,000-<60,00010259.14.924057.92.910646.53.6420.510.345255.12.3
  $60,000-<80,0008662.75.220154.33.34535.75.028.96.833453.72.7
  $80,000+11751.74.227250.92.85633.94.115.66.544648.02.2
ALL(p<0.0001)51557.92.1114456.21.461543.11.68429.23.3235852.11.0

A higher proportion of persons received extractions for males (16.2%) compared to females (12.8%), for those born overseas (16.4%) compared to Australian-born (13.8%), for persons with no education beyond schooling (17.4%) and those with trade/TAFE or other qualifications (16.7%) compared to university qualified persons (10.7%), for blue collar/trades occupations (21.4%) compared to clerical/sales and service (13.4%) and manager/professionals (10.7%). A gradient was also noted by income with a higher proportion of persons receiving extractions in lower (e.g. 22.9% in the <$20,000 group) compared to higher income groups (e.g. 9.3% in the $80,000+ group) (Table 3).

Table 3.  Bivariate associations – percentage receiving extractions within the past year.
 AGE CATEGORY (col%)
 15-34 years35-54 years55-74 years75+ yearsAll ages
 na%bSEcna%bSEcna%bSEcna%bSEcna%bSEc
  1. Notes:

  2. (a) unweighted

  3. (d) p<0.05

  4. (b) weighted

  5. (e) p<0.01

  6. (c) Standard errors corrected for complex sample design

Sex    e        e 
  Male9615.81.819316.81.216716.41.43015.03.148616.20.9
  Female16512.61.124912.20.920313.71.04014.72.665712.80.6
Country of birth       e     d 
  Australia21413.51.134914.40.822713.11.05114.82.184113.80.6
  Overseas4616.72.79314.41.614319.41.71914.83.830116.41.1
Highest Qualification    e  d     e 
  University/College5813.52.211.38.41.011112.11.41511.33.329710.70.8
  Trade/TAFE/Other7518.22.414616.11.511416.41.52416.03.435916.71.0
  No education beyond schooling10114.41.718321.31.614516.71.63116.23.046017.41.0
Occupation    e        e 
  Manager/Professional/Para-professional5311.52.11389.91.06311.81.7118.116.925510.70.9
  Clerical/sales & Service/Other6413.71.99613.11.52813.12.70018813.41.1
  Blue collar/Tradesperson4719.03.010724.62.43817.82.90019221.41.7
Income e  e  e  d  e 
  <$20,0002928.35.67428.93.513223.92.12711.42.226222.91.5
  $20,000-<40,0005217.82.710724.32.310314.51.62623.04.528819.11.1
  $40,000-<60,0004915.52.59918.01.95617.22.356.73.420916.61.3
  $60,000-<80,0003110.02.25912.01.92310.72.30011310.91.2
  $80,000+6312.52.0867.00.9359.11.7337.221.81879.30.9
ALL (ns)26114.11.144214.40.737015.00.97014.81.9114314.50.5

Multivariate models

Multivariate analysis (see Table 4) showed that relief of pain visiting varied by age, educational qualifications, country of birth and income with lower odds (Odds ratio, 95%CI) among 55-74 (0.43, 0.35-0.54) and 75+ year-olds (0.22, 0.15-0.33) compared to the reference of 15-34 year-olds, lower odds for persons born in Australia (0.82, 0.69-0.98) compared to those born overseas, higher odds for those with no education beyond schooling (1.31, 1.07-1.61) and for those with TAFE, trade and other qualifications (1.34, 1.09-1.66) compared to university qualified, and for those in the <$20,000 income group (1.61, 1.23-2.12) the $20,000-<$40,000 group (1.53,1.20-1.96) and the $40,000-<$60,000 group (1.33, 1.02-1.72) compared to <$80,000+. Receipt of extractions varied by age group, sex, qualifications and income, with lower odds of extraction among people in the 75+ year age group (0.61, 0.40-0.93) compared to the 15-34 year age group, higher odds of extraction among males (1.34, 1.13-1.59) compared to females, higher odds among those who had no education beyond schooling (1.59, 1.27-1.99) and with trade/TAFE/other qualifications (1.49, 1.21-1.84) compared to university qualifications, and for those in the income groups <$20,000 (3.06, 2.27-4.12), $20,000-<40,000 (2.37,1.80-3.12)and $40,000-<60,000(1.94,1.47-2.55) compared to those in the $80,000+ income group.

Table 4.  Multivariate model – Logistic regressions of relief of pain visits and extractions.
  Relief of pain visitsExtractions 
VariableCategoryOR(95% CI)OR(95% CI)Reference
  1. Note: (a) p<0.05

Age35-54 years0.86(0.70,1.06)0.98(0.77,1.25)15-34 years
 55-74 yearsa0.43(0.35,0.54)0.80(0.62,1.03) 
 75+ yearsa0.22(0.15,0.33)a0.61(0.40,0.93) 
SexMale1.13(0.98,1.31)a1.34(1.13,1.59)Female
Country of birthAustraliaa0.82(0.69,0.98)0.88(0.73,1.05)Overseas
Highest QualificationTrade/TAFE/Othera1.34(1.09,1.66)a1.49(1.21,1.84)University/college
 No education beyond schoolinga1.31(1.07,1.61)a1.59(1.27,1.99) 
Income<$20,000a1.61(1.23,2.12)a3.06(2.27,4.12)$80,000+
 $20-<40,000a1.53(1.20,1.96)a2.37(1.80,3.12) 
 $40-<60,000a1.33(1.02,1.72)a1.94(1.47,2.55) 
 $60-<80,0001.16(0.89,1.52)1.14(0.82,1.59) 
Pseudo R Squared: 0.0591 0.0533  

Discussion

  1. Top of page
  2. Abstract
  3. Methods
  4. Analysis
  5. Results
  6. Discussion
  7. Implications
  8. Conclusion
  9. Acknowledgements
  10. References

Main findings

Analysis of response patterns and comparisons with 2001 Census data revealed that participants differed from non-participants in some characteristics that influence oral health.7 There was over-representation of people who were Australian born, English speakers or employed relative to the Census. The survey may have also had over-representation of people who had completed year 12 schooling where there were higher percentages of ‘not stated’ in the Census. Thus, this study probably underestimates the differences in access to timely and appropriate dental care by socio-economic position.

The limitations of this study are the cross sectional design and the self-reported nature of the reason for dental visiting and the experience of receiving an extraction. The strengths of the study lie in the population wide sample.

Visits for relief of pain were strongly related to age with older adults having lower odds of making a dental visit in the past two years because of pain. Older adults report experiencing less dental pain and therefore may be less likely to make a pain-related visit.10,11 Alternatively, they may have more tolerance to pain and be able to wait to have their dental treatment at a scheduled visit. However, young adults may experience more barriers to routine dental care associated with factors such as changes in accommodation, relationships and economic responsibility related to this life stage and thus have less timely and appropriate interventions resulting in an increased likelihood of more severe disease leading to dental pain and a pain-related dental visit. The oldest age group also had lower odds of having an extraction, possibly because most vulnerable teeth had been extracted previously.

Males had higher odds of having an extraction, this finding is similar to previous work.4 Males may delay seeking restorative treatment or prefer an extraction rather than more complex treatment. Lower odds of making a dental visit for relief of pain by Australian-born adults may indicate less access to dental services and poorer quality care related to language barriers among migrants.

Level of education was associated with both pain-related dental visiting and to receipt of extractions independently of income. Education level reflects knowledge, attitudes and value placed on dental health. Education is an important determinant of the use of dental services,12 with those of less education receiving less preventive and timely maintenance care. Mechanic13 suggests that education has two roles in relation to health. First, it empowers people improving future income and access to information and health care; second, it is ‘a strong predictor of many intervening variables more directly associated with good health outcomes’ such as self-efficacy, control and coping. Adler and Newman14 raise the possibility that increasing expenditure on education may be counteracted by decreasing health costs.

Income was almost linearly related to receipt of an extraction, the lower the income the higher the odds of an extraction. The lower income groups also had higher odds of making a dental visit because of pain. Income reflects the ability of an individual to purchase dental services with higher income groups more able to afford regular dental care and dental insurance to mitigate the costs of dental care. A number of authors have found that low income is associated with irregular use of dental services.12,15,16 In Australia, people with very low incomes (those eligible for public dental care) may have to wait long periods for treatment or delay attending a private dentist until they have a problem. In either case the result may be extensive disease resulting in an extraction or an extraction because alternative treatments are too expensive or unwanted.17,18 Practice factors and practitioner factors may also play a role.19

These results suggest that socio-economic factors are related to symptomatic seeking of dental care and receipt of extractions. Riley et al.20 also found that poorer overall oral health was associated with visits due to pain. However, another concern is that people of lower socio-economic status are more likely to have dental pain but are also less likely to receive dental care when in pain.10 Irregular dental visiting and acceptance of extraction as an option may reflect values of patients and the socio-economic factors shaping those values,4 but also may reflect significant barriers existing in the provision of dental care for disadvantaged groups in Australia.

Implications

  1. Top of page
  2. Abstract
  3. Methods
  4. Analysis
  5. Results
  6. Discussion
  7. Implications
  8. Conclusion
  9. Acknowledgements
  10. References

Australia needs to find ways to make oral health care a right similar to that for general health. This may involve innovation in dental care provision such as new practice settings and use of allied dental personnel as well as the integration of oral and primary health care.21 Improving access to health services for adults who experience barriers appears to be a particularly important pathway to improved population health.13 Inequality in health care services including dental care services, have a major role in creating health inequalities.22 There is a need for all levels of government as well as the dental profession to address these issues and improve both the oral health and the quality of life of those experiencing barriers to timely and appropriate dental care.

Conclusion

  1. Top of page
  2. Abstract
  3. Methods
  4. Analysis
  5. Results
  6. Discussion
  7. Implications
  8. Conclusion
  9. Acknowledgements
  10. References

Age, country of birth, educational attainment and income level were associated with symptomatic use of dental services and age, sex, education and income were associated with receipt of extractions indicating that knowledge and values as well as financial constraints may affect access to timely dental care. The results indicate that there is an urgent need for the dental profession and governments to address the social inequality in dental care.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Methods
  4. Analysis
  5. Results
  6. Discussion
  7. Implications
  8. Conclusion
  9. Acknowledgements
  10. References

The NSAOH was supported by NHMRC, Australian Government Department of Health and Ageing, AIHW, Colgate Oral Care, Australian Dental Association, US Centers for Disease Control and Prevention, and Australian state/territory health departments.

References

  1. Top of page
  2. Abstract
  3. Methods
  4. Analysis
  5. Results
  6. Discussion
  7. Implications
  8. Conclusion
  9. Acknowledgements
  10. References