Background There is very little information about the relationship between welfare regimes and oral health inequalities. We compared socioeconomic inequalities in adults’ oral health in five European welfare-state regimes: Scandinavian, Anglo-Saxon, Bismarckian, Southern and Eastern.
Methods Using data from the oral health module of the Eurobarometer 72.3 survey, we assessed inequalities in two self-reported oral health measures: no functional dentition (less than 20 natural teeth) and edentulousness (no natural teeth). Occupational social class, education and subjective social status (SSS) were included as socioeconomic position indicators. We estimated age-standardised prevalence rates, ORs, the Relative Index of Inequality (RII) and the Slope Index of Inequality (SII).
Results The Scandinavian regime showed the lowest prevalence rates of the two oral health measures while the Eastern showed the highest. In all welfare regimes there was a general pattern of social gradients by occupational social class and education. Relative educational inequalities in no functional dentition were largest in the Scandinavian welfare regime (RII=3.81; 95% CI 2.68 to 5.42). The Scandinavian and Southern regimes showed the largest relative inequalities in edentulousness by occupation and education, respectively. There were larger absolute inequalities in no functional dentition in the Eastern regime by occupation (SII=42.16; 95% CI 31.42 to 52.89) and in the Southern by SSS (SII=27.92; 95% CI 17.36 to 38.47).
Conclusions Oral health inequalities in adults exist in all welfare-state regimes, but contrary to what may be expected from theory, they are not smaller in the Scandinavian regime. Future work should examine the potential mechanisms linking welfare provision and oral health inequalities.
- Health inequalities
- Oral health
- Social epidemiology
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Tackling health inequalities is a global public health challenge that requires major political and social changes.1–6 During the last decades, there have been improvements in certain indicators of population health, but health inequalities have not decreased consistently.7–10 Socially disadvantaged groups still bear a higher disease and mortality burden and there is evidence of persisting social gradients in numerous health outcomes.7 ,11–15 Health inequalities are even likely to rise since social inequalities have increased following recent processes of economic crisis and dismantling of social welfare policies.16–18 Therefore, measuring and understanding health inequalities remains as a research and policy priority.
In the study of health inequalities, the role of political factors and more specifically the influence of welfare-state regimes have received increasing attention.19–22 In terms of welfare states, differences in coverage and generosity of the welfare provisions, and diverse mechanisms to allocate resources have been considered to cluster countries in distinctive types or regimes.23 Based on theory, welfare regimes with more generous, universal and redistributive policies (such as the Scandinavian) are expected to exhibit lower socioeconomic inequalities in health. However, although population health is reported to be consistently better in Scandinavian countries, the evidence on health inequalities is inconclusive.19 ,21 ,22 ,24
In oral health, there is a growing focus on understanding how social determinants influence population oral health,12 ,25–28 but very little is known about the effect of political factors, and particularly of welfare regimes on oral health inequalities. To our knowledge, only one study has addressed the relationship between welfare state regimes and the magnitude of oral health inequalities. Sanders et al29 used the Korpi and Palme30 welfare typology, based on the generosity and coverage of pensions and sickness cash benefits, to compare the Oral Health Related Quality of Life (OHRQoL) between four countries representing different welfare types (Finland, the UK, Germany and Australia). They found lower income-related inequalities in OHRQoL in Germany and larger inequalities in Australia. We are not aware of any cross-national analysis of socioeconomic inequalities in oral health in adults using both different socioeconomic measures and oral health outcomes in a wide range of countries. The purpose of this study was therefore to compare socioeconomic inequalities in the oral health of adults in European countries grouped into five welfare state types: Scandinavian, Anglo-Saxon, Bismarckian, Southern and Eastern.
Data source and study sample
This study is based on cross-sectional data from the Eurobarometer wave 72.3, a survey carried out in 2009 in 31 countries (the 27 European Union Member States, three candidate countries—Croatia, Turkey, the former Yugoslav Republic of Macedonia– and the Turkish Cypriot Community). The survey used a multistage, random sampling design to provide representative samples of individuals aged 15 years and over in each country. The sampling points of the national surveys were selected from the administrative regional units with probability proportional to population size and density. In each selected sampling point, households were randomly selected and one respondent was then randomly selected from each identified household. We included in the analyses 12 516 individuals aged 45 years and older from the 21 countries, which are classified in one of the Ferrera's welfare state types31 or the additional Eastern type. Ten countries were excluded from the analyses since they have not been previously classified into the welfare regimes used in this study.
Oral health outcomes
The outcomes are two clinical self-reported measures: (1) no functional dentition (fewer than 20 natural teeth) and (2) edentulousness (no natural teeth). Both measures were derived from a question on number of natural teeth with a five-item response: all; 20 or more, but not all; 10–19; 1–9; no natural teeth. Key functions related to oral health, that is, eating comfortably and socialising without embarrassment, have been related to the number and distribution of natural teeth.32 ,33 Studies have shown that having fewer than 20 teeth is related to inadequate dental function and impaired masticatory ability.32 ,34 ,35 In contrast, having a ‘functional dentition’ (more than 20 natural teeth) has associations with chewing ability,36 and consumption of fruits and vegetables.37 There is also evidence of an association between tooth loss and OHRQoL, both among adults in general and also among older adults.38 ,39 We created two dichotomous indicators, one for not having a functional dentition, and another for edentulousness. As there was a very low prevalence of these outcomes among young adults, we included in analyses individuals aged 45 years and over. Only dentate persons were considered for the outcome of no functional dentition as it is based on number of natural teeth.
Socioeconomic position measures and other covariates
We used three measures of socioeconomic position (SEP): education, occupation-based social class and subjective social status (SSS). Education referred to age at which the participant completed full-time education. This was categorised into three education-level groups: before 16; 16–19; 20 years and older. The current or most recent occupation was assessed using a question with 18 possible responses. These were fitted into the UK three-category National Statistics SocioEconomic Classification scheme: managerial and professional; intermediate and routine-manual. Retired participants were classified according to their last job. For SSS, respondents were asked to place themselves on a scale of 1–10 representing the social hierarchy. We categorised SSS into lowest social rank (steps 1–3), second lowest social rank (steps 4 and 5), second highest social rank (steps 6 and 7) and the highest social rank (steps 8–10). Age and sex were included as covariates given the relationship of these demographic characteristics with oral health.
Welfare state regimes
Countries were clustered into five welfare regimes based on Ferrera's typology,31 and the additional Eastern type. Ferrera's typology accounts for theoretical and methodological weaknesses identified in other classifications, and it has been used in previous research to explain cross-national differences in health inequalities.40–43 This typology considers how welfare benefits are granted and organised, and clusters countries according to coverage of benefits, eligibility, financing regulations and administrative arrangements of the social security schemes.40 ,44 It results in four welfare state regimes: Scandinavian, Anglo-Saxon, Bismarckian and Southern. The Scandinavian regime (represented by Sweden, Finland and Denmark in this analysis) is characterised by universal, generous welfare provisions with a redistributive social security system; in the Anglo-Saxon (the UK and Ireland), the market has a relevant role in the welfare provision, and only the healthcare has universal coverage; the Bismarckian (Austria, Belgium, France, Germany, Luxemburg and Netherlands) is distinguished by certain earnings-related welfare benefits provided by the state, and a key role of the family in the welfare provision; finally, the Southern regime (Greece, Italy, Portugal and Spain) is characterised by generosity in certain provisions and weakness in others, and by marked public–private mix in benefits and services. In addition, we included the Eastern European regime (Czech Republic, Estonia, Hungary, Poland, Slovakia and Slovenia) containing former communist countries which have experienced intensive changes in social policies since the 1990s.41 ,43 ,45
First, we estimated prevalence rates of the two oral health outcomes by SEP in each welfare state regime. The prevalence rates were age-standardised by the direct method, using the whole sample as standard population. Second, multivariate logistic regression models were fitted to show the association between SEP measures and the two outcomes in each welfare regime. All models were adjusted for age and sex. Third, to further measure absolute and relative socioeconomic inequalities, we estimated the Relative Index of Inequality (RII) and the Slope Index of Inequality (SII) for all three SEP measures. The RII and SII are regression-based indices which take into account the distribution of the population across all socioeconomic groups, thereby removing differences in the size of socioeconomic groups as source of variation in the magnitude of health inequalities.46 ,47 The RII can be interpreted as the prevalence ratio of the oral health outcome between people at the bottom and those at the top of the SEP hierarchy, with values greater than 1 indicating inequality. Similarly, the SII corresponds to the absolute difference in prevalence rates of the outcome between the two extremes of the SEP spectrum, and positive values indicate the existence of inequality. In general, higher scores on these indices indicate larger inequalities across the socioeconomic hierarchy. In the present study, the RII was estimated by fitting log-binomial regression models, adjusting for age and sex. Ideally the SII would also be calculated by fitting such models. However, due to non-convergence issues we employed weighted linear regression models instead. Considering the requirements of the RII and SII, each SEP measure was introduced as a quantitative variable with values between 0 and 1 according to the distribution in the population of each welfare regime. To assess the potential association between different welfare regimes and socioeconomic inequalities in oral health, we calculated interaction effects between welfare regime and each SEP measure. All models were weighted by a poststratification sample weighting (which accounts for non-response) and a population size weighting to obtain population-based estimates. All analyses were conducted in Stata V.12.
Baseline characteristics of the analytic sample are presented in table 1. There were differences in SEP distribution by welfare state regimes, particularly for education and SSS. Age-standardised prevalence rates for the two outcomes by SEP showed that the lowest and highest prevalence rates were observed for the Scandinavian and the Eastern welfare regimes, respectively (figures 1 and 2). For no functional dentition, there were social gradients in all welfare state types; namely, higher proportions of participants with less than 20 teeth at successively lower SEP levels (figure 1). For edentulousness, there were statistically significant social gradients for education and occupational social class in all welfare state regimes, but the respective associations with SSS showed a gradient in the Scandinavian and followed either a J-shaped or a U-shaped pattern in the other four welfare regimes (figure 2).
After adjusting for age and sex, ORs confirmed the existence of social gradients in no functional dentition by all SEP measures and welfare state regimes (table 2). The only exception to this pattern was the marginal lack of a statistically significant gradient for SSS in the Anglo-Saxon welfare type. In general, while gradients were clear for education and occupation, such gradients were less consistent for SSS, particularly for edentulousness.
RII and SII indicated that there were absolute and relative inequalities by education and occupation in all welfare regimes, but not equally so by SSS (tables 3 and 4). Again, RII and SII were non-significant for the two outcomes by SSS in the Anglo-Saxon regime and for edentulousness in the Eastern regime. Relative inequalities in no functional dentition according to education were higher in the Scandinavian welfare type. Tests for the interaction between welfare regime clusters and SEP indicators were significant for education but not for occupation and SSS (table 3). There was variability in RIIs for edentulousness between SEP measures and welfare state regimes. Since edentulousness was very uncommon in certain socioeconomic groups in some countries (eg, managers and professionals in Scandinavian countries), this resulted in very large CIs. The Scandinavian and Southern regimes showed the largest RIIs in edentulousness by occupation and education, respectively, whereas the Eastern type had the smaller. The interactions between welfare regimes and SEP were significant for education and occupation but non-significant for SSS (table 4). Regarding absolute inequalities for no functional dentition, there were significant differences between welfare types by occupation and SSS. The largest SIIs were observed in the Eastern and Southern regimes for occupation and SSS, respectively. Absolute inequalities in edentulousness were significantly different by welfare type only for SSS with larger SII in the Southern welfare regime.
We found inequalities in the form of social gradients in oral health outcomes in all welfare state regimes analysed. Age-adjusted prevalence rates showed generally higher levels of edentulousness and no functional dentition at successively lower educational and occupational levels. The Scandinavian welfare regime had higher relative inequalities in no functional dentition by education and in edentulousness by occupation. The Eastern regime exhibited larger absolute inequalities by occupation and the Southern by SSS. It is important to acknowledge that the small relative inequalities found in the Eastern regime partially result from a numerical artefact. In this regime, there were large prevalence rates of the two outcomes even in the highest SEP categories. Then, when estimating the relative inequalities, these tend to be smaller because the starting point of comparison is very high.
The study results agreed with recent literature reviews showing that (1) contrary to what is expected, socioeconomic inequalities in health are not systematically smaller in Scandinavian (social democratic) countries when compared with other welfare state types and (2) there is no consistent pattern of health inequalities across welfare regimes.19 ,21 ,22 In particular, our findings for no functional dentition are in line with reports of larger relative educational inequalities in self-reported morbidity in Sweden, Norway and Denmark.48 Another study showed that among 11 European countries, Sweden and Norway had larger RIIs for perceived general health by education level.49 In addition, Eikemo et al,40 reported that Scandinavian countries registered higher levels of relative educational inequalities in self-assessed general health than the Anglo-Saxon and Eastern welfare types. These authors also found the largest relative educational inequalities in the Southern welfare regime, in line with our finding for edentulousness but not for no functional dentition. On the other hand, our results disagree with those of Borrell et al50 who found smaller relative educational inequalities in men's self-rated health in social democratic countries.
Suggested explanations for why Scandinavian countries do not consistently show the smallest health inequalities can help to understand our results. One argument is that Scandinavian states generate high expectations of upward social mobility among less privileged people and these expectations are often not met. Then, poor self-perceived health could reflect the stress of being relatively deprived.51 However, such an explanation seems less likely for this study, as self-reported number of natural teeth is less prone to be influenced by perceptions than self-rated oral health. A second suggested mechanism is that health inequalities in Scandinavian countries are partially explained by the large socioeconomic differences in health-related behaviours, especially smoking.47 ,52 This is a potentially valid argument and further research should establish if inequalities in other oral health-related behaviours are also larger in Scandinavian countries. A third explanation relates to the increasing immigration to Scandinavian countries, since immigrants are often excluded from the full benefits of welfare policies, are more likely to experience unemployment, social exclusion, poor acculturation, discrimination and have higher levels of poor self-perceived health.40 Additional analyses considering specific subgroups or including variables about immigration status could shed light on this point for oral health. Finally, it has been argued that poor health is more concentrated in people at lower educational levels in Scandinavian countries than in other countries, increasing the educational health inequalities.50 Our findings of larger relative educational inequalities in no functional dentition in Scandinavian countries seem to support that point.
In addition to these suggested mechanisms, results from the present study may indicate that other factors need to also be considered. First, the large relative inequalities in Scandinavian countries could partly be a reflection of a measurement issue. Relative inequalities tend to be larger when the prevalence rate is low53 and these countries had low prevalence of both edentulousness and no functional dentition. Absolute inequalities are less sensitive to the prevalence rates and, in line with this argument, we did not observe consistently lower absolute inequalities in the Scandinavian welfare regime. Second, both oral health measures used in this analysis are based on the number of natural teeth, a cumulative indicator of oral health that is also heavily influenced by dental care provision. In this context, considerations related to the oral healthcare system and approaches in the delivery of dental care are important in their own right, not just as a part of the broader welfare regime, and could have partly accounted for our results. In addition, people included in the analyses are aged 45 years and over, and may have experienced different changes in oral health policies and more general welfare policies over their life-course. This may particularly be the case among the Eastern European, former communist, countries that experienced a fast and abrupt transition to capitalism. Furthermore, there was a slight variation in the age profiles between the different welfare regimes and as tooth loss is an age-related process, this age variation may have influenced our results. However, most diseases are age related and we could not find any concrete empirical evidence in the literature to suggest that regimes with older age profiles would have larger inequalities. Finally, psychosocial factors crucial for oral health such as stress, self-esteem and sense of coherence54–56 might be higher in lower SEP groups in Scandinavian countries. Further research with comparable data about psychosocial factors is needed.
In the only earlier oral health study, Sanders et al,29 found the smallest income-related inequalities in OHRQoL in Germany when compared with Finland, the UK and Australia. A direct comparison with our findings and theirs is not straightforward since the studies used different oral health outcomes, welfare state typology and SEP measures. Nevertheless, the findings agree that the magnitude of certain oral health inequalities varies between different welfare regimes, with Scandinavian countries not having the smallest inequalities, but there is also disagreement since we did not find smaller relative inequalities in Bismarckian countries. Clearly, different SEP measures capture different dimensions of the social position, thereby affecting the magnitude of health inequalities. More importantly, it is unclear to what degree tooth loss could be less sensitive to welfare state conditions than OHRQoL.
To our knowledge, this is the first study analysing the potential relationship between welfare state regimes and oral health inequalities in a wide range of European countries. This study has strengths in terms of precision and comparability since the same data source was used for all countries. In addition, we employed different socioeconomic measures and estimated absolute and relative inequalities. We also included in analysis the less studied Eastern welfare regime, which could provide important insights about the impact of the extensive social and political changes experienced in Eastern Europe.
Our study is also subject to limitations. First, countries with different populations have similar sample sizes. However, in the analyses we used a weighting factor correcting for population size. Second, the oral health measures used have certain limitations. Both oral health outcomes were self reported and they may partly reflect variations in cultural backgrounds. However, self-reported health outcomes are considered suitable for cross-national comparisons,57 ,58 self-assessed measures are valid indicators of oral health56 ,59–61 and number of natural teeth is less sensitive to cultural differences than other subjective measures. In addition, the survey did not include data on causes of tooth loss, which would have been a relevant variable considering the outcomes used. Nevertheless, as the main causes of tooth loss are related to caries and periodontal disease, it is plausible to consider the oral health outcomes used in this study as measures of cumulative disease. Third, we did not use log-binomial regression to calculate the SII due to non-convergence issues. However, in cases where convergence of the log-binomial model was achieved, the two methods (log-binomial and linear regression) gave very similar SII results. Fourth, the SEP measures used might have limitations for international comparisons of health inequalities. Although age, when completing full-time education, is a marker for years of schooling, comparisons may not be completely accurate since countries have different policies regarding age of starting and leaving compulsory education. Cross-national comparisons based on occupation are complicated because the same occupational level may be linked to dissimilar access to material and immaterial resources in different countries. However, the three occupational categories used here represent broad and well-differentiated employment relations and conditions of occupations in modern societies.62 And while SSS seems to be susceptible to cultural differences, it is a good predictor of health and in older adults is considered a proxy of life-time SEP.63 Finally, there is no agreement in the social policy literature about an ‘ideal’ welfare regime typology. Ferrera's typology was chosen because it has been recognised as one of the most accurate classifications, it considers the quantity of welfare provided and also how welfare benefits are delivered, and has been widely used in cross-national analyses of population health and health inequalities.40–43 ,57 ,64 ,65
In summary, our results suggest that oral health inequalities in adults exist in all welfare state regimes but, contrary to expectations, are not smaller in those with more generous and universal welfare provisions. While Scandinavian countries exhibited the lowest prevalence rates for both oral health outcomes, they also showed intermediate absolute inequalities and larger relative inequalities. Further research is needed to explain these findings and fully understand the potential mechanisms linking welfare provision and socioeconomic inequalities in oral health.
What is already known on this subject?
Oral health inequalities and social gradients in oral health have been observed in different countries, using various measures of socioeconomic position and oral health outcomes.
Different mechanisms have been suggested to explain socioeconomic inequalities in oral health, primarily behavioural, material and psychosocial.
To date, very few studies have analysed the effect of political factors on oral health inequalities and only one study has compared the magnitude of oral health inequalities across welfare state regimes.
What this study adds?
This study compared socioeconomic inequalities in the oral health of adults in 21 European countries grouped into different welfare state regimes.
The lowest prevalence of the two oral health outcomes was observed for the Scandinavian regime and the highest prevalence for the Eastern regime.
Oral health inequalities were found in all welfare state regimes, but contrary to what is expected from theory inequalities were not smaller in the Scandinavian welfare regime.
Contributors CCG-H, RGW and GT codesigned the study. CCG-H, GT and HP performed the statistical analysis. CCG-H wrote the first draft. AS, RGW, GT and HP read the draft and provided comments. All coauthors read and approved the final draft.
Competing interests None.
Provenance and peer review Not commissioned; externally peer reviewed.
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