Ó 2015 Eur J Oral Sci
Eur J Oral Sci 2015; 123: 267–275 DOI: 10.1111/eos.12192 Printed in Singapore. All rights reserved
European Journal of Oral Sciences
Inequality in oral health-related quality of life before and after a major subsidization reform Raittio E, Lahti S, Kiiskinen U, Helminen S, Aromaa A, Suominen AL. Inequality in oral health-related quality of life before and after a major subsidization reform. Eur J Oral Sci 2015; 123: 267–275. © 2015 Eur J Oral Sci In Finland, a dental subsidization reform, implemented in 2001–2002, abolished age restrictions on subsidized dental care. We investigated income-related inequality in oral health-related quality of life (OHRQoL) and its determinants among adult Finns before and after the reform. Three cross-sectional postal surveys, focusing on perceived oral health and the use of dental services among people born before 1971, were conducted in 2001 (n = 2,046), 2004 (n = 1,728), and 2007 (n = 1,560). Five measures, based on the Oral Health Impact Profile-14, were used as indicators of OHRQoL. Income-related inequality and associated factors were analysed using the concentration index and its decomposition. Prevalence, extent, and severity of oral health impacts were slightly lower in 2007 than in 2001. The oral health impacts were concentrated, at all study time points, among individuals with lower income. Most of the inequality was related to self-perceived general health, tooth loss, and income. Contributions of time since the last dental visit and satisfaction with the last treatment period to the inequality decreased from 2001 to 2007. However, the contributions of these factors were already small (10–20%) in 2001. In general, OHRQoL improved slightly; however, no clear or dramatic change in inequality in OHRQoL was seen after the reform.
Reducing social inequalities in health (i.e. health differences between different population groups, for example, between poor and financially better-off people) by actions in the health-care sector has been a general goal of governments in several western countries during the 2000s (1, 2). Moreover, the role of universal public health-care coverage in reducing health inequalities has been emphasized by, for instance, the World Health Organization (3). These aims seem valid also in the case of oral health care: limited access to dental services seems to contribute to inequality in oral health (4–7); and universal coverage of dental care seems to be associated with somewhat smaller inequalities in perceived oral health (8). In contrast, GUARNIZO-HERRENO et al. (9) showed that Scandinavian countries, with their universal coverage of dental care, did not have lower socio-economic inequalities in oral health impacts compared with other European countries categorized according to their welfare regime type. However, (oral) health is better in Nordic welfare states, with their universal and generous welfare benefits, than it is elsewhere (10, 11). In the late 1990s, adults born in 1955 or earlier were not entitled to subsidized dental care in Finland. They did not have access to Public Dental Services (PDS) and were not entitled to receive reimbursement for private dental costs from the National Health
Eero Raittio1, Satu Lahti2, Urpo Kiiskinen3, Sari Helminen4, Arpo Aromaa5, Anna L. Suominen1,5,6 1
Institute of Dentistry, University of Eastern Finland, Kuopio; 2Institute of Dentistry, University of Turku, Turku; 3Eli Lilly Finland Ab, Helsinki; 4Social Insurance Institution, Helsinki; 5Institute for Health and Welfare (THL), Helsinki; 6Department of Oral and Maxillofacial Surgery, Kuopio University Hospital, Kuopio, Finland
Anna Liisa Suominen, Institute of Dentistry, University of Eastern Finland, PO Box 1627, 70211 Kuopio, Finland E-mail: [email protected] Key words: access to care; income; inequality; oral health-care services; socioeconomics Accepted for publication April 2015
Insurance (NHI). They were thus required to pay the full costs of their dental care. However, it was estimated that one-third of the adult population lived in municipalities that were able, temporarily and voluntarily, to provide PDS for their inhabitants born in 1955 or earlier. In contrast, many municipalities were not able to supply services even to those entitled to receive them (12). All age restrictions were gradually abolished following introduction of the major Oral Health Care Reform (OHCR) between 2001 and 2002. In the first phase of the OHCR, in spring 2001, entitlements to use PDS and to receive reimbursements from the NHI were extended to cover those born between 1946 and 1955. In the second phase, at the end of 2002, all age restrictions were abolished. Since then, the entire Finnish population has been entitled to use PDS and to receive reimbursements from the NHI for their private dental costs. In Finland, subsidized dental-care services are delivered via two parallel systems. Public Dental Services are provided by municipalities (452 in 2000 and 342 in 2010), either by themselves or as cooperative efforts between several municipalities. Public Dental Services are funded partly by municipal and state taxes (two-thirds) and partly by client fees (one-third). In the private sector, client fees for dental care are partly reimbursed (effectively by 30–40%) through the
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tax-funded NHI maintained by the Social Insurance Institution of Finland (SII). Client fees in the private sector are set independently but the reimbursement from the NHI is fixed according to the treatment. Overall, out-of-pocket payments in the private sector are approximately twice as high as those in the PDS, despite the reimbursements obtained from the NHI. In contrast to the PDS, private dental services are mainly located in the large municipalities of Finland, rather than in every municipality. Most adult Finns used private dental services before the reform, and no clear change in the use of private dental services was seen after the OHCR (13). Instead, the use of and demand for PDS increased among the adult population after the reform, particularly in those areas where access to PDS was restricted before the reform (14). In addition, the use of PDS seemed to become more need-based after the OHCR (13). This benefited those less well-off (15). However, it seemed that narrowing of income-related inequity in the use of dental services after the reform was a rather temporary phenomenon (15). Taken together, an increase in the use of dental services and some improvements in access to dental care were seen after the OHCR. Through improving the equity in use of and access to dental care, we hypothesized that the OHCR may have narrowed socio-economic inequality in the oral health-related quality of life (OHRQoL) among adult Finns detected before the reform (8). No studies concerning the issue have been conducted in Finland after the reform. Therefore, the objective of this study was to investigate and describe possible changes in incomerelated inequality in OHRQoL from before to after the reform using the concentration index. We also explored how factors associated with income-related inequality in OHRQoL have changed after the reform. In particular, we looked at to what extent the change in inequality was related to changes in the use of and access to dental care induced by the OHCR.
Material and methods The data for this study were gathered by identical, nationally representative, cross-sectional postal surveys conducted by The National Institute for Health and Welfare (formerly the National Public Health Institute) and SII in Finland, before the OHCR in February 2001 and after the OHCR in February 2004 and in February 2007. The stratified cluster sampling framework of the Health 2000 Survey (16) was used. The study population was restricted to individuals born in 1970 or earlier. The response rates were 70% (n = 2,837) in 2001, 65% (n = 2,451) in 2004, and 61% (n = 2,296) in 2007. In the analyses, we used only those respondents who had answered to all questions that were used in this study (n = 2,046 in 2001, n = 1,728 in 2004, and n = 1,560 in 2007). Ethical approval was not needed for this type of postal survey. However, for the survey conducted in 2007, ethical approval was conferred by the Ethical Committees of the National Public Health Institute and SII.
OHRQoL (dependent variables) Oral health-related quality of life was measured using a short form of the Oral Health Impact Profile (OHIP-14) (17) using a 1-month reference period. The OHIP-14 includes 14 questions concerning the frequency of oral adverse impacts in the following seven dimensions: functional limitation, physical pain, psychological discomfort, physical disability, psychological disability, social disability, and handicap. The response format was as follows: ‘very often’ (score = 4), ‘fairly often’ (score = 3), ‘occasionally’ (score = 2), ‘hardly ever’ (score = 1), ‘never’ (score = 0), and ‘I don’t know’ (18). If the respondent had one or two missing or ‘I don’t know’ answers, these answers were replaced with the sample mean, whereas respondents who had more than two missing or ‘I don’t know’ answers were excluded from the analyses (18). In this study, we used five measures based on the OHIP-14. They consisted of a severity measure and two prevalence and two extent measures of oral health impacts on quality of life (17, 18). Severity was calculated by summing the values of the answers, giving a range in severity of 0 (the most healthy) to 56 (the poorest oral health). In the case of the prevalence and extent measures, two different threshold levels were used: ‘occasionally’ or ‘fairly often’ or ‘very often’ (OFOVO) and ‘fairly often’ or ‘very often’ (FOVO). The prevalence measure was given a value of 1 when the respondent had reported one or more impacts occurring on a specified threshold (OFOVO or FOVO) and a value of 0 otherwise. The extent measure was calculated by summing the number of items for which the respondent had reported one or more impacts occurring on a specified threshold (OFOVO or FOVO); therefore, the value for the extent measure ranges from 0 (the most healthy) to 14 (the poorest oral health) (17, 18). Ranking variable for the concentration index Household income per Organisation for Economic Cooperation and Development (OECD) consumption unit (19) was used as the socio-economic ranking variable for concentration indices. Monthly household income, including income transfers and excluding taxes, was elicited using a question with 13 response options, which were identical in all the study years. The first 12 options grouped household income from EUR 0 to EUR 8,400, whereas those who stated that they earned more than EUR 8,400 (option 13), were assumed to earn EUR 9,000 monthly, on average. The change in the value of money was taken into account by using change coefficients based on the consumer price index (20). Household income per OECD consumption unit was calculated by dividing the monthly household income by the weighted sum of household members, in which the first adult was given a weight of 1.0, other adults a weight of 0.7, and those under 18 yr of age a weight of 0.5 (19). Subsequently, household income per OECD consumption unit will be referred to as ‘income’. Explanatory variables for OHRQoL We divided the explanatory variables into five groups: oral health-care factors, demographic factors, health factors, socio-economic factors, and psychological factors. The division was not theory-driven and one could categorize them differently. The primary aim of the categorization was to simplify the interpretation and the presentation of the results.
Income-related inequality in OHRQoL Oral health-care factors were: time since last visit to dental care [during the past 12 months (reference), 1–2 yr ago, 3–5 yr ago, >5 yr ago, or never]; and satisfaction with the last dental-treatment period. The degree of satisfaction was established by the responses given to the statement: ‘I am satisfied with the last dental treatment period’. Answer options were ‘agree’ (reference), ‘agree to some extent’, ‘I don’t know’, ‘disagree to some extent’, and ‘disagree’. We assumed that these factors reflect, at least: access to (21), and cost of, dental care (22, 23); patient-centred care (23, 24); preventive approach (23, 24) and recall systems (25); and convenience and facilities of dental care (23). We believe that these oral health-care factors mirror the contribution of recently provided dental care to inequality and also the effects of OHCR on oral health care. Demographic factors relate to the general structure of the study population. The following variables were included: year of birth [1956–1970 (reference), 1946–1955, or 10 but not all], general health [good (reference), fairly good, average, quite poor, and poor], denture wearing [complete or partial dentures, no dentures (reference)], and toothbrushing frequency [daily (reference), weekly or more seldom than weekly or never]. Socio-economic factors were as follows: educational level (26) [basic (reference), intermediate, or higher], natural logarithm of income and main type of activity [full-time work or part-time work or retired or student or conscript (reference), unemployed or temporarily laid-off)]. These reflect social position, economic situation, and educational attainment. Socio-economic factors will capture the ‘pure effect’ of socio-economic factors on the incomerelated inequality in OHRQoL (27). The rather robust categorization of the main type of activity was made to alleviate multicollinearity in the regression models. The psychological factor was dental anxiety, which was measured using the statement: ‘I’m scared to visit the dentist.’ The options were ‘agree’, ‘agree to some extent’, ‘not sure’, ‘disagree to some extent’, and ‘disagree’ (reference). Dental anxiety is a potential confounder between oral health-care factors and OHRQoL. Concentration index and its decomposition The concentration index is a rather widely used inequality measure in health economics (27–29). It is based on a concentration curve that is formed by taking a cumulative sum curve of the variable of interest (for example, health, or use of services) in the population ranked by a variable describing potential source of inequality (i.e. income, in this study). If the variable of interest is distributed evenly by the ranking variable, the concentration curve will be a 45° – this line is also known as the ‘line of equality’. The concentration index is twice the area between the line of equality and the concentration curve. Therefore, the values of concentration index range from 1 to 1; a positive value indicates that the event of interest is more prevalent in those with a higher income than in those with a lower
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income. Conversely, negative values indicate that there is a disproportionately high concentration of the event of interest in subjects with a low income. The higher or lower the value of the concentration index, the more unequal is the distribution according to income, whereas a value of 0 represents equal distribution of event according to income. As our income measure was based on a categorical variable, we employed the so-called ‘extended Kakwani, Wagstaff, van Doorslaer’ (KWD) approach to estimate the concentration index and its variance (29, 30). For binary dependent variables (i.e. prevalence – OFOVO and FOVO), we corrected the concentration index using the method introduced by ERREYGERS (31). Its interpretation is similar to the concentration index (27–29). Concentration indices for the dependent variables were decomposed into their components (contributors) (27). In the decomposition procedure, coefficients (bk) for explanatory variables (k) were obtained from a linear regression model using OHIP-14 measures as dependent variables. Moreover, concentration indices for explanatory variables (Ck) and means of explanatory variables ( xk ) were calculated in order to use the decomposition equation: Xbk xk GCe X GCe C¼ Ck þ ¼ ; gk Ck þ l l l k k
where C is the concentration index for the dependent variable and l is the mean of the dependent variable. As seen, decomposition of the concentration index is the product of the income-related inequalities in the explanatory variables (Ck) and the associations of explanatory variables with the dependent variable (bk xk =l). Elasticity (gk ¼ bk xk =l), which is a unit-free measure, indicates the percentage change in the probability of reporting oral health impacts when the value of explanatory variables increases by 1%. The last term (GCe/l) is part of the concentration index that is not explained by the explanatory variables (i.e. the residual term) (27). Similarly, the corrected concentration index for the binary variables was decomposed into its contributors using its own decomposition equation (31). Moreover, in the case of binary dependent variables, marginal effects for the explanatory variables were obtained from probit regression models, instead of coefficients from linear regression models (27, 32). All statistical analyses were performed using R (version 3.01, R Development Core Team). Stratified cluster sampling and the effect of non-response were taken into account by using sample weights based on gender, age, region, and language. Multicollinearities in the regression models were checked and were found to be acceptable (variance inflation factors below five). ANOVA and the chisquare test (Rao–Scott), which took account of the weights and the sampling method, were used to evaluate statistical differences in prevalences and means across the study years. The t-test was used to calculate statistical significance of changes in concentration indices (33). In this study, P < 0.05 was considered as statistically significant.
Results The percentage of respondents reporting at least one oral health impact on the specified thresholds (i.e.
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FOVO and OFOVO) decreased between 2001 and 2007. Small decreases were observed, from 2001 to 2007, in the mean values of the oral health impacts severity and extent (Table 1). In all five measures, reports of oral health impacts were concentrated among individuals with lower income, and therefore the concentration index values were negative in all study years (Table 1). Inequality in oral health impact severity and oral health impact extent widened slightly from 2001 to 2007. Direction of change of inequality in prevalence was dependent on the specified threshold; on the FOVO threshold the inequality in prevalence narrowed and on the OFOVO threshold the inequality in prevalence widened. Overall, changes in concentration indices were small and not statistically significant. Means of and inequalities in explanatory variables and associations with OHRQoL
The percentages of older respondents, unemployed respondents, and respondents with a high number of missing teeth or dentures decreased from 2001 to 2007 (Table 2). The percentage of respondents who reported not to brush their teeth daily decreased. No statistically significant change in satisfaction with the last dental treatment period was reported. The average time since the last dental visit decreased, and the percentage of those who had visited dental care during the past 12 months increased, from 60% to 67% (P < 0.05, data not shown). Average income increased statistically significantly between 2001 and 2007. According to concentration indexes, pro-rich inequality in satisfaction with the last dental-treatment period showed a somewhat slight decrease, whereas the pro-rich inequality in general health increased. According to regression analysis, number of missing teeth, perceived general health, dental anxiety, and satisfaction with the last dental-treatment period showed the strongest associations with the dependent variables throughout the study years (Table S1).
Decomposition results
Decomposition of OHRQoL inequalities shows the contributions of each explanatory variable and residual to the concentration indexes for the prevalence, extent, and severity of oral health impacts on quality of life (Tables 3–5). Income, general health, and number of missing teeth were the factors that explained most (85– 100%) of the observed income-related inequality in the oral health impacts reported (this was indicated by a relatively large negative contribution in all measures). In all five measures, oral health-care factors (i.e. the time since the last dental visit and satisfaction with the last dental-treatment period) showed negative aggregate contributions to the inequalities in 2001 (i.e. favoured the financially better-off and disfavoured the less welloff; Tables 3–5). Decreases (changes towards zero) in these contributions from 2001 to 2007 were a uniform finding. Most of these changes were attributable to a weakened positive association between dissatisfaction with the last treatment period and reporting the oral health impacts (Table S1), and decreased pro-rich inequality in satisfaction with the last dental-treatment period (changes in concentration indices for satisfaction; Table 2). In terms of the prevalence and extent measures based on the OFOVO threshold and the severity measure, the negative aggregate contributions of socio-economic factors to the inequalities increased from 2001 to 2007 (Tables 3–5). Although the negative aggregate contributions of the health factors to the inequalities in the prevalence of oral health impacts increased, the corresponding contributions to the inequalities in the extent and severity of oral health impacts decreased. Neither clear nor uniform changes in the contributions of other factors to the inequalities were seen.
Discussion Oral health-related quality of life improved statistically significantly in the study population, from 2001 to
Table 1 Prevalence, severity, and extent of oral health-related quality of life (OHRQoL) among adult Finns in 2001, 2004, and 2007 Mean value or percentage (SE) Variable Prevalence FOVO OFOVO Severity Extent FOVO OFOVO
Concentration index* (SE)
2001
2004
2007
P
18.0% (0.008) 52.2% (0.012) 7.31 (0.210)
15.0% (0.009) 48.5% (0.014) 6.28 (0.195)
14.9% (0.011) 48.9% (0.016) 6.47 (0.274)
0.61 (0.042) 2.07 (0.074)
0.45 (0.034) 1.75 (0.073)
0.50 (0.049) 1.84 (0.101)
†
2001
2004
2007
0.02 0.08 0.00
0.116 (0.020) 0.116 (0.026) 0.125 (0.017)
0.113 (0.020) 0.167 (0.029) 0.148 (0.018)
0.095 (0.022) 0.143 (0.031) 0.140 (0.018)
0.07 0.03
0.251 (0.041) 0.136 (0.021)
0.293 (0.043) 0.188 (0.022)
0.279 (0.040) 0.167 (0.023)
FOVO, fairly often, very often; OFOVO, occasionally, fairly often, or very often; SE, standard error. *All indices were statistically significantly different from 0, but not different from each other at P < 0.05. † P-values were based on Rao–Scott chi-square tests and ANOVA across the study years.
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Income-related inequality in OHRQoL Table 2 Explanatory variables among adult Finns in 2001, 2004, and 2007 Concentration index†
Mean values* Variable
2001
Year of birth 1946–1955 0.270 Before 1946 0.319 Sex Female 0.517 Living in the one of the 15 biggest municipalities Yes 0.396 Marital status Cohabitation 0.117 Divorced or estranged 0.104 Widowed 0.066 Single 0.104 Number of missing teeth 6–10 0.122 > 10, but not all 0.129 All 0.076 Denture wearing Yes 0.260 Toothbrushing frequency Not daily 0.078 General health Fairly good 0.323 Average 0.273 Quite poor 0.075 Poor 0.017 Educational level Basic 0.321 Higher 0.342 Income Natural logarithm 7.249 Main type of activity Unemployed or temporarily laid-off 0.075 Time since last dental visit 1–2 years 0.161 3–5 years 0.142 >5 years or never had a dental visit 0.099 Satisfaction with last treatment period‡ Agree to some extent 0.293 I do not know 0.077 Disagree to some extent 0.034 Disagree 0.025 Dental anxiety§ Agree 0.103 Agree to some extent 0.201 I do not know 0.063 Disagree to some extent 0.277
2004
2007
2001
2004
2007
0.280 0.297
0.291 0.267
0.115 0.094
0.076 0.112
0.152 0.199
0.513
0.511
0.036
0.049
0.040
0.397
0.413
0.130
0.136
0.124
0.109 0.095 0.072 0.106
0.127 0.104 0.065 0.105
0.036 0.058 0.249 0.067
0.061 0.142 0.214 0.028
0.165 0.205 0.210 0.150
0.135 0.098 0.067
0.156 0.090 0.058
0.005 0.156 0.349
0.126 0.155 0.385
0.041 0.174 0.382
0.243
0.205
0.158
0.177
0.183
0.060
0.042
0.303
0.289
0.070
0.335 0.233 0.072 0.018
0.335 0.278 0.059 0.016
0.015 0.149 0.241 0.156
0.021 0.156 0.299 0.383
0.067 0.182 0.356 0.561
0.297 0.371
0.287 0.375
0.286 0.313
0.276 0.259
0.316 0.264
7.301
7.393
0.048
0.048
0.047
0.067
0.044
0.449
0.446
0.509
0.141 0.124 0.087
0.143 0.115 0.077
0.013 0.176 0.222
0.030 0.041 0.279
0.044 0.160 0.257
0.262 0.071 0.041 0.025
0.283 0.068 0.043 0.025
0.025 0.174 0.085 0.162
0.026 0.129 0.185 0.155
0.045 0.196 0.103 0.040
0.098 0.186 0.067 0.278
0.103 0.192 0.066 0.281
0.109 0.002 0.115 0.044
0.183 0.006 0.159 0.032
0.094 0.010 0.059 0.038
*Bold indicates statistically significant difference at P < 0.05 across the study years, based on the Rao–Scott chi-square test or † Bold indicates that the concentration index is statistically significantly different from 0 at P < 0.05. ‡ Answer to the statement: ‘I am satisfied with the last dental-treatment period’. § Answer to the statement: ‘I’m scared to visit the dentist’.
2007. Simultaneously, income-related inequality in OHRQoL widened (11–25%) slightly in terms of the oral health impact severity, extent (FOVO and OFOVO), and prevalence (OFOVO). Only income-related inequality in prevalence on the FOVO threshold narrowed (18%). However, these changes in inequalities were not statistically significant. Small increases in the contributions of socio-economic factors (i.e. income, education, and main type of activity) to OHRQoL
ANOVA.
inequalities were seen. Meanwhile, small decreases in the contributions of oral health-care factors (i.e. the time since the last dental visit and satisfaction with the last treatment period) to the inequality in OHRQoL. In contrast to the findings highlighting the role of access to dental care in oral health inequalities (4, 5), our findings suggest that the contributions of oral health-care factors to the inequality in OHRQoL were rather small (10–20%) before the OHCR in 2001. The
272
Raittio et al. Table 3
Decomposition of concentration index for oral health impact prevalence on fairly often, very often (FOVO) and occasionally, fairly often, very often (OFOVO) thresholds among adult Finns in 2001, 2004, and 2007 FOVO threshold
Demographics Year of birth Sex Living in the one of the 15 biggest municipalities Marital status Subtotal Health factors Number of missing teeth Denture wearing Toothbrushing frequency General health Subtotal Socio-economic factors Educational level Natural logarithm of income Main type of activity Subtotal Oral health-care factors Time since last dental visit Satisfaction with last treatment period Subtotal Psychological factor Dental anxiety Residual Concentration index
OFOVO threshold
2001
2004
2007
Change
2001
2004
2007
Change
0.001 0.003 0.004 0.001 0.004
0.008 0.004 0.006 0.002 0.008
0.003 0.006 0.006 0.013 0.009
0.002 0.003 0.002 0.014 0.013
0.007 0.001 0.003 0.004 0.012
0.007 0.003 0.000 0.006 0.003
0.002 0.001 0.008 0.010 0.001
0.005 0.001 0.005 0.015 0.013
0.028 0.003 0.004 0.038 0.072
0.026 0.000 0.005 0.034 0.066
0.001 0.014 0.001 0.041 0.058
0.026 0.012 0.003 0.003 0.015
0.043 0.016 0.002 0.057 0.118
0.053 0.011 0.002 0.067 0.133
0.032 0.032 0.000 0.041 0.105
0.011 0.016 0.002 0.016 0.013
0.029 0.049 0.003 0.024
0.011 0.038 0.002 0.025
0.017 0.029 0.005 0.006
0.011 0.021 0.008 0.017
0.021 0.022 0.008 0.009
0.046 0.068 0.012 0.033
0.054 0.092 0.013 0.051
0.034 0.070 0.005 0.042
0.001 0.015 0.016
0.007 0.015 0.009
0.006 0.004 0.010
0.006 0.012 0.006
0.009 0.019 0.011
0.008 0.024 0.015
0.000 0.002 0.003
0.009 0.017 0.008
0.005 0.003 0.116
0.009 0.013 0.113
0.002 0.009 0.095
0.002 0.006 0.022
0.006 0.015 0.116
0.015 0.033 0.167
0.012 0.029 0.143
0.006 0.013 0.027
contributions diminished by 2007. These differing findings may stem from different study methods, context, and variables used, including the dependent variables. Moreover, despite the large variation in the availability of the dental services between municipalities in Finland before and after the reform, the factor of ‘living in one of the 15 biggest municipalities’ showed only a small contribution (2–5%) to the inequality in OHRQoL. Taken together, based on our findings, it seems that the inequality in OHRQoL that was related to recently provided dental care narrowed after the major legislative changes, namely OHCR. Nevertheless, it seems that these measures had only a modest significance on the current inequality in OHRQoL. Therefore, further actions to reduce the inequality in OHRQoL should be undertaken in the field of broader social structures at state/municipality level (3). In addition to the broader social determinants of health (inequalities), it is possible to suggest some factors behind the persisting income-related inequality in OHRQoL in the older adult population in Finland. First, OHRQoL inequality among the study population may stem partly from the fact that dental care is still not affordable for everyone, mainly because fees still need to be paid for treatment obtained from PDS (34, 35). For instance, findings from Sweden showed that, despite the reform which aimed to reduce financial barriers to dental care-seeking, refraining from dental care for financial reasons had very large contribution to the (unequal) distribution of perceived poor oral health (6). Second, because tooth loss is an important factor
behind impaired OHRQoL (36), it may be that the change to the universal subsidized dental care is less ‘effective’ in tackling the oral health inequalities in populations in which a major proportion of individuals have a long history of receiving only emergency dental care, in which tooth extraction was the principal treatment given, during their adulthood. In other words, it is no surprise that the modern-day universal subsidized dental care does not redress the decades of inequity in access to subsidized dental care among the adults studied. Moreover, the limited narrowing of inequalities after implementation of the OHCR may be a result of the fact that, in particular, interventions relying on voluntary behaviour change in improving health and tackling inequalities tend to result in an increase of socio-economic inequalities in health as a result of variations in response to interventions according to socio-economic position (37). Signs of this have also been seen in the case of OHCR, as, 4-5 yr after the reform, some of the disadvantaged were not aware of their entitlement to subsidized visits to the PDS (35). It is also likely that increased income inequality in Finland is, to some extent, behind the persisting incomerelated inequality in OHRQoL (38). In addition, during the last decades, attitudes in Finnish social and welfare policy have transferred from governmental support towards emphasizing individual’s own responsibility (39). Finally, it must be noted that the reform did not affect everyone included in the analysis because some municipalities already offered PDS to all their citizens (approximately one-third of the Finnish population)
Income-related inequality in OHRQoL Table 4 Decomposition of concentration index for oral health impact severity among adult Finns in 2001, 2004, and 2007 2001 Demographics Year of birth Sex Living in the one of the 15 biggest municipalities Marital status Subtotal Health factors Number of missing teeth Denture wearing Toothbrushing frequency General health Subtotal Socio-economic factors Educational level Natural logarithm of income Main type of activity Subtotal Oral health-care factors Time since last dental visit Satisfaction with last treatment period Subtotal Psychological factor Dental anxiety Residual Concentration index
2004
0.005 0.006 0.000 0.002 0.002 0.004 0.001 0.006 0.033 0.004 0.003 0.032 0.073
2007
Change
0.014 0.000 0.004
0.009 0.000 0.002
0.000 0.006 0.005 0.007 0.011 0.005 0.037 0.011 0.005 0.041 0.094
0.024 0.009 0.019 0.015 0.001 0.002 0.036 0.003 0.081 0.007
0.020 0.015 0.032 0.012 0.056 0.050 0.093 0.037 0.005 0.002 0.000 0.005 0.042 0.033 0.061 0.019 0.001 0.003 0.001 0.016 0.019 0.003
0.000 0.012
0.014 0.016 0.002
0.012
0.006 0.013 0.008 0.002 0.004 0.000 0.000 0.004 0.125 0.148 0.140 0.015
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before the reform (12). This probably further weakened the effects of the OHCR. Nonetheless, improvement in OHRQoL after implementation of the major legislative changes advancing equitable access to dental care must be acknowledged. This is line with evidence showing an association of social democratic (Nordic) welfare policies (states) with (oral) health (10, 11). Our findings concerning the prevalence and severity of oral health impact are different from the results of another national Finnish survey, which showed clearly lower rates of reporting the impacts (36). In comparison with other countries, our figures suggest that OHRQoL is somewhat poorer in Finland than in the other Nordic countries (40, 41), the UK (8), and Germany (8), but similar to that in Australia (18). We are aware of only one study that has used the concentration index and OHIP-14 to analyse socio-economic inequality in OHRQoL (42). It suggested that there was no incomerelated inequality in OHRQoL in the UK. This is contrary to the findings of SANDERS et al. (8), who showed that inequalities were at similar levels in the UK and Finland. Based on the decomposition of income-related inequality in OHRQoL, it seems essential to improve OHRQoL in individuals with poor general health, a high number of missing teeth, and a low level of income in order to tackle the inequality in OHRQoL. This also implies that the inequality could somewhat narrow as a result of a continuously increasing number
Table 5 Decomposition of concentration index for oral health impact extent on fairly often, very often (FOVO) and occasionally, fairly often, very often (OFOVO) thresholds among adult Finns in 2001, 2004, and 2007 FOVO threshold
Demographics Year of birth Sex Living in the one of the 15 biggest municipalities Marital status Subtotal Health factors Number of missing teeth Denture wearing Toothbrushing frequency General health Subtotal Socio-economic factors Educational level Natural logarithm of income Main type of activity Subtotal Oral health-care factors Time since last dental visit Satisfaction with last treatment period Subtotal Psychological factor Dental anxiety Residual Concentration index
OFOVO threshold
2001
2004
2007
Change
2001
2004
2007
Change
0.006 0.002 0.016 0.007 0.014
0.015 0.010 0.015 0.003 0.017
0.015 0.004 0.005 0.025 0.008
0.009 0.002 0.010 0.019 0.022
0.006 0.001 0.005 0.001 0.009
0.006 0.003 0.005 0.001 0.008
0.016 0.000 0.006 0.013 0.009
0.010 0.001 0.001 0.013 0.000
0.070 0.012 0.005 0.063 0.126
0.069 0.009 0.021 0.065 0.164
0.038 0.015 0.003 0.081 0.137
0.032 0.027 0.002 0.018 0.011
0.043 0.003 0.003 0.037 0.086
0.047 0.009 0.004 0.049 0.109
0.021 0.025 0.002 0.048 0.096
0.022 0.022 0.001 0.011 0.010
0.058 0.164 0.004 0.110
0.028 0.117 0.020 0.069
0.036 0.147 0.013 0.097
0.022 0.017 0.017 0.013
0.027 0.060 0.007 0.040
0.028 0.081 0.001 0.052
0.045 0.116 0.001 0.069
0.019 0.056 0.008 0.029
0.005 0.030 0.035
0.002 0.043 0.045
0.007 0.016 0.009
0.011 0.015 0.026
0.001 0.018 0.017
0.006 0.024 0.018
0.003 0.005 0.002
0.002 0.013 0.015
0.012 0.019 0.251
0.030 0.002 0.293
0.015 0.012 0.279
0.002 0.031 0.028
0.005 0.005 0.136
0.015 0.002 0.188
0.010 0.002 0.167
0.004 0.003 0.031
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of dentate individuals (43). On the other hand, the rather large contribution of number of missing teeth (20–30%) represents the significance of disease experience and the history of dental care provided in the current OHRQoL inequality seen in Finland. In addition to the high number of missing teeth, issues of low income and poor general health should be taken into account in the realm of dental care more vigorously (for example, recalls for the poor and sick and lower charges for dental treatment). However, improving oral health in certain population groups is not the only way to achieve equality in OHRQoL: measures aiming to decrease income inequality and socio-economic inequality in general health can be considered at least as equally important (see the decomposition equation). Overall, we would like to see the socio-economic inequality in OHRQoL tackled and prevented, primarily as a goal of society and its politics, by taking account of the rather proximal standpoint of dental care on OHRQoL. In other words, this is a call for socalled upstream actions and policies (44). One of the strengths of the study was that we were able to study inequality in OHRQoL in an interesting study design, namely before and after major reform. Response rates were also rather good, despite the downward trend from 2001 (70%) to 2007 (61%). The methods used in the study were also established and referenced. Our regression models had rather high coefficients of determination (R2) in comparison with the other studies that used OHIP-14 measures (36, 42) (Table S1). However, there were also limitations to the study. First, we were not able to detect causalities and therefore the actual effect of OHCR could not be directly measured. Our follow-up time was also rather short, and we were unable to distinguish the effects of reform from longer-term trends in OHRQoL and its socio-economic inequality. It is also clear that the postal surveys did not reach the most socially excluded individuals. In addition, our income measure was based on a categorical variable and so not all the differences in income were detected. The decreasing response rate and attrition over the study period (75% of which was a result of failure to answer income and OHIP questions) may have led to underestimates to some extent of poor OHRQoL and inequality in it. In addition, measuring OHRQoL and comparing it between different time points and among individuals of different socio-economic status raises questions, such as: do individuals of different socio-economic status report oral health impacts differently; or has the basis of reporting oral health impacts changed from 2001 to 2007? For instance, TSAKOS et al. (45) and SLADE (46) have discussed the problems of comparing OHIP scores over time; one problem is the dynamic nature of OHRQoL (47). It is also unclear why the findings were somewhat dependent on the OHIP-14 measure and threshold (OFOVO/FOVO) used; however, it should be noted that the changes detected in this study were, overall, small. Despite the limitations, we see our results being representative and comparable across the
study years. Further studies on OHRQoL among Finnish adults are needed, for instance to identify the actual oral health impacts plaguing the disadvantaged. In general, OHRQoL improved slightly, but no clear or dramatic change in income-related inequality in OHRQoL was seen among Finnish adults after the change to the universal subsidized dental care. These findings imply that the contribution of recently provided dental care to income-related inequality in OHRQoL was already relatively small before the reform, and that the contribution diminished further after the reform. Most of the observed inequality in OHRQoL was related to general health, number of missing teeth, and income. Therefore, it is essential to take account of these factors in future measures aiming to tackle the persisting income-related inequality in OHRQoL in Finland. Acknowledgements – This study was supported by a personal grant from Finnish Dental Society Apollonia to ER. Conflicts of interest – The authors report no conflicts of interest.
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Supporting Information Additional Supporting Information may be found in the online version of this article: Table S1. Associations between explanatory variables and oral health-related quality of life.
Eur J Oral Sci 2015; 123: 267–275 DOI: 10.1111/eos.12192 Printed in Singapore. All rights reserved
European Journal of Oral Sciences
Inequality in oral health-related quality of life before and after a major subsidization reform Raittio E, Lahti S, Kiiskinen U, Helminen S, Aromaa A, Suominen AL. Inequality in oral health-related quality of life before and after a major subsidization reform. Eur J Oral Sci 2015; 123: 267–275. © 2015 Eur J Oral Sci In Finland, a dental subsidization reform, implemented in 2001–2002, abolished age restrictions on subsidized dental care. We investigated income-related inequality in oral health-related quality of life (OHRQoL) and its determinants among adult Finns before and after the reform. Three cross-sectional postal surveys, focusing on perceived oral health and the use of dental services among people born before 1971, were conducted in 2001 (n = 2,046), 2004 (n = 1,728), and 2007 (n = 1,560). Five measures, based on the Oral Health Impact Profile-14, were used as indicators of OHRQoL. Income-related inequality and associated factors were analysed using the concentration index and its decomposition. Prevalence, extent, and severity of oral health impacts were slightly lower in 2007 than in 2001. The oral health impacts were concentrated, at all study time points, among individuals with lower income. Most of the inequality was related to self-perceived general health, tooth loss, and income. Contributions of time since the last dental visit and satisfaction with the last treatment period to the inequality decreased from 2001 to 2007. However, the contributions of these factors were already small (10–20%) in 2001. In general, OHRQoL improved slightly; however, no clear or dramatic change in inequality in OHRQoL was seen after the reform.
Reducing social inequalities in health (i.e. health differences between different population groups, for example, between poor and financially better-off people) by actions in the health-care sector has been a general goal of governments in several western countries during the 2000s (1, 2). Moreover, the role of universal public health-care coverage in reducing health inequalities has been emphasized by, for instance, the World Health Organization (3). These aims seem valid also in the case of oral health care: limited access to dental services seems to contribute to inequality in oral health (4–7); and universal coverage of dental care seems to be associated with somewhat smaller inequalities in perceived oral health (8). In contrast, GUARNIZO-HERRENO et al. (9) showed that Scandinavian countries, with their universal coverage of dental care, did not have lower socio-economic inequalities in oral health impacts compared with other European countries categorized according to their welfare regime type. However, (oral) health is better in Nordic welfare states, with their universal and generous welfare benefits, than it is elsewhere (10, 11). In the late 1990s, adults born in 1955 or earlier were not entitled to subsidized dental care in Finland. They did not have access to Public Dental Services (PDS) and were not entitled to receive reimbursement for private dental costs from the National Health
Eero Raittio1, Satu Lahti2, Urpo Kiiskinen3, Sari Helminen4, Arpo Aromaa5, Anna L. Suominen1,5,6 1
Institute of Dentistry, University of Eastern Finland, Kuopio; 2Institute of Dentistry, University of Turku, Turku; 3Eli Lilly Finland Ab, Helsinki; 4Social Insurance Institution, Helsinki; 5Institute for Health and Welfare (THL), Helsinki; 6Department of Oral and Maxillofacial Surgery, Kuopio University Hospital, Kuopio, Finland
Anna Liisa Suominen, Institute of Dentistry, University of Eastern Finland, PO Box 1627, 70211 Kuopio, Finland E-mail: [email protected] Key words: access to care; income; inequality; oral health-care services; socioeconomics Accepted for publication April 2015
Insurance (NHI). They were thus required to pay the full costs of their dental care. However, it was estimated that one-third of the adult population lived in municipalities that were able, temporarily and voluntarily, to provide PDS for their inhabitants born in 1955 or earlier. In contrast, many municipalities were not able to supply services even to those entitled to receive them (12). All age restrictions were gradually abolished following introduction of the major Oral Health Care Reform (OHCR) between 2001 and 2002. In the first phase of the OHCR, in spring 2001, entitlements to use PDS and to receive reimbursements from the NHI were extended to cover those born between 1946 and 1955. In the second phase, at the end of 2002, all age restrictions were abolished. Since then, the entire Finnish population has been entitled to use PDS and to receive reimbursements from the NHI for their private dental costs. In Finland, subsidized dental-care services are delivered via two parallel systems. Public Dental Services are provided by municipalities (452 in 2000 and 342 in 2010), either by themselves or as cooperative efforts between several municipalities. Public Dental Services are funded partly by municipal and state taxes (two-thirds) and partly by client fees (one-third). In the private sector, client fees for dental care are partly reimbursed (effectively by 30–40%) through the
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tax-funded NHI maintained by the Social Insurance Institution of Finland (SII). Client fees in the private sector are set independently but the reimbursement from the NHI is fixed according to the treatment. Overall, out-of-pocket payments in the private sector are approximately twice as high as those in the PDS, despite the reimbursements obtained from the NHI. In contrast to the PDS, private dental services are mainly located in the large municipalities of Finland, rather than in every municipality. Most adult Finns used private dental services before the reform, and no clear change in the use of private dental services was seen after the OHCR (13). Instead, the use of and demand for PDS increased among the adult population after the reform, particularly in those areas where access to PDS was restricted before the reform (14). In addition, the use of PDS seemed to become more need-based after the OHCR (13). This benefited those less well-off (15). However, it seemed that narrowing of income-related inequity in the use of dental services after the reform was a rather temporary phenomenon (15). Taken together, an increase in the use of dental services and some improvements in access to dental care were seen after the OHCR. Through improving the equity in use of and access to dental care, we hypothesized that the OHCR may have narrowed socio-economic inequality in the oral health-related quality of life (OHRQoL) among adult Finns detected before the reform (8). No studies concerning the issue have been conducted in Finland after the reform. Therefore, the objective of this study was to investigate and describe possible changes in incomerelated inequality in OHRQoL from before to after the reform using the concentration index. We also explored how factors associated with income-related inequality in OHRQoL have changed after the reform. In particular, we looked at to what extent the change in inequality was related to changes in the use of and access to dental care induced by the OHCR.
Material and methods The data for this study were gathered by identical, nationally representative, cross-sectional postal surveys conducted by The National Institute for Health and Welfare (formerly the National Public Health Institute) and SII in Finland, before the OHCR in February 2001 and after the OHCR in February 2004 and in February 2007. The stratified cluster sampling framework of the Health 2000 Survey (16) was used. The study population was restricted to individuals born in 1970 or earlier. The response rates were 70% (n = 2,837) in 2001, 65% (n = 2,451) in 2004, and 61% (n = 2,296) in 2007. In the analyses, we used only those respondents who had answered to all questions that were used in this study (n = 2,046 in 2001, n = 1,728 in 2004, and n = 1,560 in 2007). Ethical approval was not needed for this type of postal survey. However, for the survey conducted in 2007, ethical approval was conferred by the Ethical Committees of the National Public Health Institute and SII.
OHRQoL (dependent variables) Oral health-related quality of life was measured using a short form of the Oral Health Impact Profile (OHIP-14) (17) using a 1-month reference period. The OHIP-14 includes 14 questions concerning the frequency of oral adverse impacts in the following seven dimensions: functional limitation, physical pain, psychological discomfort, physical disability, psychological disability, social disability, and handicap. The response format was as follows: ‘very often’ (score = 4), ‘fairly often’ (score = 3), ‘occasionally’ (score = 2), ‘hardly ever’ (score = 1), ‘never’ (score = 0), and ‘I don’t know’ (18). If the respondent had one or two missing or ‘I don’t know’ answers, these answers were replaced with the sample mean, whereas respondents who had more than two missing or ‘I don’t know’ answers were excluded from the analyses (18). In this study, we used five measures based on the OHIP-14. They consisted of a severity measure and two prevalence and two extent measures of oral health impacts on quality of life (17, 18). Severity was calculated by summing the values of the answers, giving a range in severity of 0 (the most healthy) to 56 (the poorest oral health). In the case of the prevalence and extent measures, two different threshold levels were used: ‘occasionally’ or ‘fairly often’ or ‘very often’ (OFOVO) and ‘fairly often’ or ‘very often’ (FOVO). The prevalence measure was given a value of 1 when the respondent had reported one or more impacts occurring on a specified threshold (OFOVO or FOVO) and a value of 0 otherwise. The extent measure was calculated by summing the number of items for which the respondent had reported one or more impacts occurring on a specified threshold (OFOVO or FOVO); therefore, the value for the extent measure ranges from 0 (the most healthy) to 14 (the poorest oral health) (17, 18). Ranking variable for the concentration index Household income per Organisation for Economic Cooperation and Development (OECD) consumption unit (19) was used as the socio-economic ranking variable for concentration indices. Monthly household income, including income transfers and excluding taxes, was elicited using a question with 13 response options, which were identical in all the study years. The first 12 options grouped household income from EUR 0 to EUR 8,400, whereas those who stated that they earned more than EUR 8,400 (option 13), were assumed to earn EUR 9,000 monthly, on average. The change in the value of money was taken into account by using change coefficients based on the consumer price index (20). Household income per OECD consumption unit was calculated by dividing the monthly household income by the weighted sum of household members, in which the first adult was given a weight of 1.0, other adults a weight of 0.7, and those under 18 yr of age a weight of 0.5 (19). Subsequently, household income per OECD consumption unit will be referred to as ‘income’. Explanatory variables for OHRQoL We divided the explanatory variables into five groups: oral health-care factors, demographic factors, health factors, socio-economic factors, and psychological factors. The division was not theory-driven and one could categorize them differently. The primary aim of the categorization was to simplify the interpretation and the presentation of the results.
Income-related inequality in OHRQoL Oral health-care factors were: time since last visit to dental care [during the past 12 months (reference), 1–2 yr ago, 3–5 yr ago, >5 yr ago, or never]; and satisfaction with the last dental-treatment period. The degree of satisfaction was established by the responses given to the statement: ‘I am satisfied with the last dental treatment period’. Answer options were ‘agree’ (reference), ‘agree to some extent’, ‘I don’t know’, ‘disagree to some extent’, and ‘disagree’. We assumed that these factors reflect, at least: access to (21), and cost of, dental care (22, 23); patient-centred care (23, 24); preventive approach (23, 24) and recall systems (25); and convenience and facilities of dental care (23). We believe that these oral health-care factors mirror the contribution of recently provided dental care to inequality and also the effects of OHCR on oral health care. Demographic factors relate to the general structure of the study population. The following variables were included: year of birth [1956–1970 (reference), 1946–1955, or 10 but not all], general health [good (reference), fairly good, average, quite poor, and poor], denture wearing [complete or partial dentures, no dentures (reference)], and toothbrushing frequency [daily (reference), weekly or more seldom than weekly or never]. Socio-economic factors were as follows: educational level (26) [basic (reference), intermediate, or higher], natural logarithm of income and main type of activity [full-time work or part-time work or retired or student or conscript (reference), unemployed or temporarily laid-off)]. These reflect social position, economic situation, and educational attainment. Socio-economic factors will capture the ‘pure effect’ of socio-economic factors on the incomerelated inequality in OHRQoL (27). The rather robust categorization of the main type of activity was made to alleviate multicollinearity in the regression models. The psychological factor was dental anxiety, which was measured using the statement: ‘I’m scared to visit the dentist.’ The options were ‘agree’, ‘agree to some extent’, ‘not sure’, ‘disagree to some extent’, and ‘disagree’ (reference). Dental anxiety is a potential confounder between oral health-care factors and OHRQoL. Concentration index and its decomposition The concentration index is a rather widely used inequality measure in health economics (27–29). It is based on a concentration curve that is formed by taking a cumulative sum curve of the variable of interest (for example, health, or use of services) in the population ranked by a variable describing potential source of inequality (i.e. income, in this study). If the variable of interest is distributed evenly by the ranking variable, the concentration curve will be a 45° – this line is also known as the ‘line of equality’. The concentration index is twice the area between the line of equality and the concentration curve. Therefore, the values of concentration index range from 1 to 1; a positive value indicates that the event of interest is more prevalent in those with a higher income than in those with a lower
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income. Conversely, negative values indicate that there is a disproportionately high concentration of the event of interest in subjects with a low income. The higher or lower the value of the concentration index, the more unequal is the distribution according to income, whereas a value of 0 represents equal distribution of event according to income. As our income measure was based on a categorical variable, we employed the so-called ‘extended Kakwani, Wagstaff, van Doorslaer’ (KWD) approach to estimate the concentration index and its variance (29, 30). For binary dependent variables (i.e. prevalence – OFOVO and FOVO), we corrected the concentration index using the method introduced by ERREYGERS (31). Its interpretation is similar to the concentration index (27–29). Concentration indices for the dependent variables were decomposed into their components (contributors) (27). In the decomposition procedure, coefficients (bk) for explanatory variables (k) were obtained from a linear regression model using OHIP-14 measures as dependent variables. Moreover, concentration indices for explanatory variables (Ck) and means of explanatory variables ( xk ) were calculated in order to use the decomposition equation: Xbk xk GCe X GCe C¼ Ck þ ¼ ; gk Ck þ l l l k k
where C is the concentration index for the dependent variable and l is the mean of the dependent variable. As seen, decomposition of the concentration index is the product of the income-related inequalities in the explanatory variables (Ck) and the associations of explanatory variables with the dependent variable (bk xk =l). Elasticity (gk ¼ bk xk =l), which is a unit-free measure, indicates the percentage change in the probability of reporting oral health impacts when the value of explanatory variables increases by 1%. The last term (GCe/l) is part of the concentration index that is not explained by the explanatory variables (i.e. the residual term) (27). Similarly, the corrected concentration index for the binary variables was decomposed into its contributors using its own decomposition equation (31). Moreover, in the case of binary dependent variables, marginal effects for the explanatory variables were obtained from probit regression models, instead of coefficients from linear regression models (27, 32). All statistical analyses were performed using R (version 3.01, R Development Core Team). Stratified cluster sampling and the effect of non-response were taken into account by using sample weights based on gender, age, region, and language. Multicollinearities in the regression models were checked and were found to be acceptable (variance inflation factors below five). ANOVA and the chisquare test (Rao–Scott), which took account of the weights and the sampling method, were used to evaluate statistical differences in prevalences and means across the study years. The t-test was used to calculate statistical significance of changes in concentration indices (33). In this study, P < 0.05 was considered as statistically significant.
Results The percentage of respondents reporting at least one oral health impact on the specified thresholds (i.e.
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FOVO and OFOVO) decreased between 2001 and 2007. Small decreases were observed, from 2001 to 2007, in the mean values of the oral health impacts severity and extent (Table 1). In all five measures, reports of oral health impacts were concentrated among individuals with lower income, and therefore the concentration index values were negative in all study years (Table 1). Inequality in oral health impact severity and oral health impact extent widened slightly from 2001 to 2007. Direction of change of inequality in prevalence was dependent on the specified threshold; on the FOVO threshold the inequality in prevalence narrowed and on the OFOVO threshold the inequality in prevalence widened. Overall, changes in concentration indices were small and not statistically significant. Means of and inequalities in explanatory variables and associations with OHRQoL
The percentages of older respondents, unemployed respondents, and respondents with a high number of missing teeth or dentures decreased from 2001 to 2007 (Table 2). The percentage of respondents who reported not to brush their teeth daily decreased. No statistically significant change in satisfaction with the last dental treatment period was reported. The average time since the last dental visit decreased, and the percentage of those who had visited dental care during the past 12 months increased, from 60% to 67% (P < 0.05, data not shown). Average income increased statistically significantly between 2001 and 2007. According to concentration indexes, pro-rich inequality in satisfaction with the last dental-treatment period showed a somewhat slight decrease, whereas the pro-rich inequality in general health increased. According to regression analysis, number of missing teeth, perceived general health, dental anxiety, and satisfaction with the last dental-treatment period showed the strongest associations with the dependent variables throughout the study years (Table S1).
Decomposition results
Decomposition of OHRQoL inequalities shows the contributions of each explanatory variable and residual to the concentration indexes for the prevalence, extent, and severity of oral health impacts on quality of life (Tables 3–5). Income, general health, and number of missing teeth were the factors that explained most (85– 100%) of the observed income-related inequality in the oral health impacts reported (this was indicated by a relatively large negative contribution in all measures). In all five measures, oral health-care factors (i.e. the time since the last dental visit and satisfaction with the last dental-treatment period) showed negative aggregate contributions to the inequalities in 2001 (i.e. favoured the financially better-off and disfavoured the less welloff; Tables 3–5). Decreases (changes towards zero) in these contributions from 2001 to 2007 were a uniform finding. Most of these changes were attributable to a weakened positive association between dissatisfaction with the last treatment period and reporting the oral health impacts (Table S1), and decreased pro-rich inequality in satisfaction with the last dental-treatment period (changes in concentration indices for satisfaction; Table 2). In terms of the prevalence and extent measures based on the OFOVO threshold and the severity measure, the negative aggregate contributions of socio-economic factors to the inequalities increased from 2001 to 2007 (Tables 3–5). Although the negative aggregate contributions of the health factors to the inequalities in the prevalence of oral health impacts increased, the corresponding contributions to the inequalities in the extent and severity of oral health impacts decreased. Neither clear nor uniform changes in the contributions of other factors to the inequalities were seen.
Discussion Oral health-related quality of life improved statistically significantly in the study population, from 2001 to
Table 1 Prevalence, severity, and extent of oral health-related quality of life (OHRQoL) among adult Finns in 2001, 2004, and 2007 Mean value or percentage (SE) Variable Prevalence FOVO OFOVO Severity Extent FOVO OFOVO
Concentration index* (SE)
2001
2004
2007
P
18.0% (0.008) 52.2% (0.012) 7.31 (0.210)
15.0% (0.009) 48.5% (0.014) 6.28 (0.195)
14.9% (0.011) 48.9% (0.016) 6.47 (0.274)
0.61 (0.042) 2.07 (0.074)
0.45 (0.034) 1.75 (0.073)
0.50 (0.049) 1.84 (0.101)
†
2001
2004
2007
0.02 0.08 0.00
0.116 (0.020) 0.116 (0.026) 0.125 (0.017)
0.113 (0.020) 0.167 (0.029) 0.148 (0.018)
0.095 (0.022) 0.143 (0.031) 0.140 (0.018)
0.07 0.03
0.251 (0.041) 0.136 (0.021)
0.293 (0.043) 0.188 (0.022)
0.279 (0.040) 0.167 (0.023)
FOVO, fairly often, very often; OFOVO, occasionally, fairly often, or very often; SE, standard error. *All indices were statistically significantly different from 0, but not different from each other at P < 0.05. † P-values were based on Rao–Scott chi-square tests and ANOVA across the study years.
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Income-related inequality in OHRQoL Table 2 Explanatory variables among adult Finns in 2001, 2004, and 2007 Concentration index†
Mean values* Variable
2001
Year of birth 1946–1955 0.270 Before 1946 0.319 Sex Female 0.517 Living in the one of the 15 biggest municipalities Yes 0.396 Marital status Cohabitation 0.117 Divorced or estranged 0.104 Widowed 0.066 Single 0.104 Number of missing teeth 6–10 0.122 > 10, but not all 0.129 All 0.076 Denture wearing Yes 0.260 Toothbrushing frequency Not daily 0.078 General health Fairly good 0.323 Average 0.273 Quite poor 0.075 Poor 0.017 Educational level Basic 0.321 Higher 0.342 Income Natural logarithm 7.249 Main type of activity Unemployed or temporarily laid-off 0.075 Time since last dental visit 1–2 years 0.161 3–5 years 0.142 >5 years or never had a dental visit 0.099 Satisfaction with last treatment period‡ Agree to some extent 0.293 I do not know 0.077 Disagree to some extent 0.034 Disagree 0.025 Dental anxiety§ Agree 0.103 Agree to some extent 0.201 I do not know 0.063 Disagree to some extent 0.277
2004
2007
2001
2004
2007
0.280 0.297
0.291 0.267
0.115 0.094
0.076 0.112
0.152 0.199
0.513
0.511
0.036
0.049
0.040
0.397
0.413
0.130
0.136
0.124
0.109 0.095 0.072 0.106
0.127 0.104 0.065 0.105
0.036 0.058 0.249 0.067
0.061 0.142 0.214 0.028
0.165 0.205 0.210 0.150
0.135 0.098 0.067
0.156 0.090 0.058
0.005 0.156 0.349
0.126 0.155 0.385
0.041 0.174 0.382
0.243
0.205
0.158
0.177
0.183
0.060
0.042
0.303
0.289
0.070
0.335 0.233 0.072 0.018
0.335 0.278 0.059 0.016
0.015 0.149 0.241 0.156
0.021 0.156 0.299 0.383
0.067 0.182 0.356 0.561
0.297 0.371
0.287 0.375
0.286 0.313
0.276 0.259
0.316 0.264
7.301
7.393
0.048
0.048
0.047
0.067
0.044
0.449
0.446
0.509
0.141 0.124 0.087
0.143 0.115 0.077
0.013 0.176 0.222
0.030 0.041 0.279
0.044 0.160 0.257
0.262 0.071 0.041 0.025
0.283 0.068 0.043 0.025
0.025 0.174 0.085 0.162
0.026 0.129 0.185 0.155
0.045 0.196 0.103 0.040
0.098 0.186 0.067 0.278
0.103 0.192 0.066 0.281
0.109 0.002 0.115 0.044
0.183 0.006 0.159 0.032
0.094 0.010 0.059 0.038
*Bold indicates statistically significant difference at P < 0.05 across the study years, based on the Rao–Scott chi-square test or † Bold indicates that the concentration index is statistically significantly different from 0 at P < 0.05. ‡ Answer to the statement: ‘I am satisfied with the last dental-treatment period’. § Answer to the statement: ‘I’m scared to visit the dentist’.
2007. Simultaneously, income-related inequality in OHRQoL widened (11–25%) slightly in terms of the oral health impact severity, extent (FOVO and OFOVO), and prevalence (OFOVO). Only income-related inequality in prevalence on the FOVO threshold narrowed (18%). However, these changes in inequalities were not statistically significant. Small increases in the contributions of socio-economic factors (i.e. income, education, and main type of activity) to OHRQoL
ANOVA.
inequalities were seen. Meanwhile, small decreases in the contributions of oral health-care factors (i.e. the time since the last dental visit and satisfaction with the last treatment period) to the inequality in OHRQoL. In contrast to the findings highlighting the role of access to dental care in oral health inequalities (4, 5), our findings suggest that the contributions of oral health-care factors to the inequality in OHRQoL were rather small (10–20%) before the OHCR in 2001. The
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Raittio et al. Table 3
Decomposition of concentration index for oral health impact prevalence on fairly often, very often (FOVO) and occasionally, fairly often, very often (OFOVO) thresholds among adult Finns in 2001, 2004, and 2007 FOVO threshold
Demographics Year of birth Sex Living in the one of the 15 biggest municipalities Marital status Subtotal Health factors Number of missing teeth Denture wearing Toothbrushing frequency General health Subtotal Socio-economic factors Educational level Natural logarithm of income Main type of activity Subtotal Oral health-care factors Time since last dental visit Satisfaction with last treatment period Subtotal Psychological factor Dental anxiety Residual Concentration index
OFOVO threshold
2001
2004
2007
Change
2001
2004
2007
Change
0.001 0.003 0.004 0.001 0.004
0.008 0.004 0.006 0.002 0.008
0.003 0.006 0.006 0.013 0.009
0.002 0.003 0.002 0.014 0.013
0.007 0.001 0.003 0.004 0.012
0.007 0.003 0.000 0.006 0.003
0.002 0.001 0.008 0.010 0.001
0.005 0.001 0.005 0.015 0.013
0.028 0.003 0.004 0.038 0.072
0.026 0.000 0.005 0.034 0.066
0.001 0.014 0.001 0.041 0.058
0.026 0.012 0.003 0.003 0.015
0.043 0.016 0.002 0.057 0.118
0.053 0.011 0.002 0.067 0.133
0.032 0.032 0.000 0.041 0.105
0.011 0.016 0.002 0.016 0.013
0.029 0.049 0.003 0.024
0.011 0.038 0.002 0.025
0.017 0.029 0.005 0.006
0.011 0.021 0.008 0.017
0.021 0.022 0.008 0.009
0.046 0.068 0.012 0.033
0.054 0.092 0.013 0.051
0.034 0.070 0.005 0.042
0.001 0.015 0.016
0.007 0.015 0.009
0.006 0.004 0.010
0.006 0.012 0.006
0.009 0.019 0.011
0.008 0.024 0.015
0.000 0.002 0.003
0.009 0.017 0.008
0.005 0.003 0.116
0.009 0.013 0.113
0.002 0.009 0.095
0.002 0.006 0.022
0.006 0.015 0.116
0.015 0.033 0.167
0.012 0.029 0.143
0.006 0.013 0.027
contributions diminished by 2007. These differing findings may stem from different study methods, context, and variables used, including the dependent variables. Moreover, despite the large variation in the availability of the dental services between municipalities in Finland before and after the reform, the factor of ‘living in one of the 15 biggest municipalities’ showed only a small contribution (2–5%) to the inequality in OHRQoL. Taken together, based on our findings, it seems that the inequality in OHRQoL that was related to recently provided dental care narrowed after the major legislative changes, namely OHCR. Nevertheless, it seems that these measures had only a modest significance on the current inequality in OHRQoL. Therefore, further actions to reduce the inequality in OHRQoL should be undertaken in the field of broader social structures at state/municipality level (3). In addition to the broader social determinants of health (inequalities), it is possible to suggest some factors behind the persisting income-related inequality in OHRQoL in the older adult population in Finland. First, OHRQoL inequality among the study population may stem partly from the fact that dental care is still not affordable for everyone, mainly because fees still need to be paid for treatment obtained from PDS (34, 35). For instance, findings from Sweden showed that, despite the reform which aimed to reduce financial barriers to dental care-seeking, refraining from dental care for financial reasons had very large contribution to the (unequal) distribution of perceived poor oral health (6). Second, because tooth loss is an important factor
behind impaired OHRQoL (36), it may be that the change to the universal subsidized dental care is less ‘effective’ in tackling the oral health inequalities in populations in which a major proportion of individuals have a long history of receiving only emergency dental care, in which tooth extraction was the principal treatment given, during their adulthood. In other words, it is no surprise that the modern-day universal subsidized dental care does not redress the decades of inequity in access to subsidized dental care among the adults studied. Moreover, the limited narrowing of inequalities after implementation of the OHCR may be a result of the fact that, in particular, interventions relying on voluntary behaviour change in improving health and tackling inequalities tend to result in an increase of socio-economic inequalities in health as a result of variations in response to interventions according to socio-economic position (37). Signs of this have also been seen in the case of OHCR, as, 4-5 yr after the reform, some of the disadvantaged were not aware of their entitlement to subsidized visits to the PDS (35). It is also likely that increased income inequality in Finland is, to some extent, behind the persisting incomerelated inequality in OHRQoL (38). In addition, during the last decades, attitudes in Finnish social and welfare policy have transferred from governmental support towards emphasizing individual’s own responsibility (39). Finally, it must be noted that the reform did not affect everyone included in the analysis because some municipalities already offered PDS to all their citizens (approximately one-third of the Finnish population)
Income-related inequality in OHRQoL Table 4 Decomposition of concentration index for oral health impact severity among adult Finns in 2001, 2004, and 2007 2001 Demographics Year of birth Sex Living in the one of the 15 biggest municipalities Marital status Subtotal Health factors Number of missing teeth Denture wearing Toothbrushing frequency General health Subtotal Socio-economic factors Educational level Natural logarithm of income Main type of activity Subtotal Oral health-care factors Time since last dental visit Satisfaction with last treatment period Subtotal Psychological factor Dental anxiety Residual Concentration index
2004
0.005 0.006 0.000 0.002 0.002 0.004 0.001 0.006 0.033 0.004 0.003 0.032 0.073
2007
Change
0.014 0.000 0.004
0.009 0.000 0.002
0.000 0.006 0.005 0.007 0.011 0.005 0.037 0.011 0.005 0.041 0.094
0.024 0.009 0.019 0.015 0.001 0.002 0.036 0.003 0.081 0.007
0.020 0.015 0.032 0.012 0.056 0.050 0.093 0.037 0.005 0.002 0.000 0.005 0.042 0.033 0.061 0.019 0.001 0.003 0.001 0.016 0.019 0.003
0.000 0.012
0.014 0.016 0.002
0.012
0.006 0.013 0.008 0.002 0.004 0.000 0.000 0.004 0.125 0.148 0.140 0.015
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before the reform (12). This probably further weakened the effects of the OHCR. Nonetheless, improvement in OHRQoL after implementation of the major legislative changes advancing equitable access to dental care must be acknowledged. This is line with evidence showing an association of social democratic (Nordic) welfare policies (states) with (oral) health (10, 11). Our findings concerning the prevalence and severity of oral health impact are different from the results of another national Finnish survey, which showed clearly lower rates of reporting the impacts (36). In comparison with other countries, our figures suggest that OHRQoL is somewhat poorer in Finland than in the other Nordic countries (40, 41), the UK (8), and Germany (8), but similar to that in Australia (18). We are aware of only one study that has used the concentration index and OHIP-14 to analyse socio-economic inequality in OHRQoL (42). It suggested that there was no incomerelated inequality in OHRQoL in the UK. This is contrary to the findings of SANDERS et al. (8), who showed that inequalities were at similar levels in the UK and Finland. Based on the decomposition of income-related inequality in OHRQoL, it seems essential to improve OHRQoL in individuals with poor general health, a high number of missing teeth, and a low level of income in order to tackle the inequality in OHRQoL. This also implies that the inequality could somewhat narrow as a result of a continuously increasing number
Table 5 Decomposition of concentration index for oral health impact extent on fairly often, very often (FOVO) and occasionally, fairly often, very often (OFOVO) thresholds among adult Finns in 2001, 2004, and 2007 FOVO threshold
Demographics Year of birth Sex Living in the one of the 15 biggest municipalities Marital status Subtotal Health factors Number of missing teeth Denture wearing Toothbrushing frequency General health Subtotal Socio-economic factors Educational level Natural logarithm of income Main type of activity Subtotal Oral health-care factors Time since last dental visit Satisfaction with last treatment period Subtotal Psychological factor Dental anxiety Residual Concentration index
OFOVO threshold
2001
2004
2007
Change
2001
2004
2007
Change
0.006 0.002 0.016 0.007 0.014
0.015 0.010 0.015 0.003 0.017
0.015 0.004 0.005 0.025 0.008
0.009 0.002 0.010 0.019 0.022
0.006 0.001 0.005 0.001 0.009
0.006 0.003 0.005 0.001 0.008
0.016 0.000 0.006 0.013 0.009
0.010 0.001 0.001 0.013 0.000
0.070 0.012 0.005 0.063 0.126
0.069 0.009 0.021 0.065 0.164
0.038 0.015 0.003 0.081 0.137
0.032 0.027 0.002 0.018 0.011
0.043 0.003 0.003 0.037 0.086
0.047 0.009 0.004 0.049 0.109
0.021 0.025 0.002 0.048 0.096
0.022 0.022 0.001 0.011 0.010
0.058 0.164 0.004 0.110
0.028 0.117 0.020 0.069
0.036 0.147 0.013 0.097
0.022 0.017 0.017 0.013
0.027 0.060 0.007 0.040
0.028 0.081 0.001 0.052
0.045 0.116 0.001 0.069
0.019 0.056 0.008 0.029
0.005 0.030 0.035
0.002 0.043 0.045
0.007 0.016 0.009
0.011 0.015 0.026
0.001 0.018 0.017
0.006 0.024 0.018
0.003 0.005 0.002
0.002 0.013 0.015
0.012 0.019 0.251
0.030 0.002 0.293
0.015 0.012 0.279
0.002 0.031 0.028
0.005 0.005 0.136
0.015 0.002 0.188
0.010 0.002 0.167
0.004 0.003 0.031
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of dentate individuals (43). On the other hand, the rather large contribution of number of missing teeth (20–30%) represents the significance of disease experience and the history of dental care provided in the current OHRQoL inequality seen in Finland. In addition to the high number of missing teeth, issues of low income and poor general health should be taken into account in the realm of dental care more vigorously (for example, recalls for the poor and sick and lower charges for dental treatment). However, improving oral health in certain population groups is not the only way to achieve equality in OHRQoL: measures aiming to decrease income inequality and socio-economic inequality in general health can be considered at least as equally important (see the decomposition equation). Overall, we would like to see the socio-economic inequality in OHRQoL tackled and prevented, primarily as a goal of society and its politics, by taking account of the rather proximal standpoint of dental care on OHRQoL. In other words, this is a call for socalled upstream actions and policies (44). One of the strengths of the study was that we were able to study inequality in OHRQoL in an interesting study design, namely before and after major reform. Response rates were also rather good, despite the downward trend from 2001 (70%) to 2007 (61%). The methods used in the study were also established and referenced. Our regression models had rather high coefficients of determination (R2) in comparison with the other studies that used OHIP-14 measures (36, 42) (Table S1). However, there were also limitations to the study. First, we were not able to detect causalities and therefore the actual effect of OHCR could not be directly measured. Our follow-up time was also rather short, and we were unable to distinguish the effects of reform from longer-term trends in OHRQoL and its socio-economic inequality. It is also clear that the postal surveys did not reach the most socially excluded individuals. In addition, our income measure was based on a categorical variable and so not all the differences in income were detected. The decreasing response rate and attrition over the study period (75% of which was a result of failure to answer income and OHIP questions) may have led to underestimates to some extent of poor OHRQoL and inequality in it. In addition, measuring OHRQoL and comparing it between different time points and among individuals of different socio-economic status raises questions, such as: do individuals of different socio-economic status report oral health impacts differently; or has the basis of reporting oral health impacts changed from 2001 to 2007? For instance, TSAKOS et al. (45) and SLADE (46) have discussed the problems of comparing OHIP scores over time; one problem is the dynamic nature of OHRQoL (47). It is also unclear why the findings were somewhat dependent on the OHIP-14 measure and threshold (OFOVO/FOVO) used; however, it should be noted that the changes detected in this study were, overall, small. Despite the limitations, we see our results being representative and comparable across the
study years. Further studies on OHRQoL among Finnish adults are needed, for instance to identify the actual oral health impacts plaguing the disadvantaged. In general, OHRQoL improved slightly, but no clear or dramatic change in income-related inequality in OHRQoL was seen among Finnish adults after the change to the universal subsidized dental care. These findings imply that the contribution of recently provided dental care to income-related inequality in OHRQoL was already relatively small before the reform, and that the contribution diminished further after the reform. Most of the observed inequality in OHRQoL was related to general health, number of missing teeth, and income. Therefore, it is essential to take account of these factors in future measures aiming to tackle the persisting income-related inequality in OHRQoL in Finland. Acknowledgements – This study was supported by a personal grant from Finnish Dental Society Apollonia to ER. Conflicts of interest – The authors report no conflicts of interest.
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Supporting Information Additional Supporting Information may be found in the online version of this article: Table S1. Associations between explanatory variables and oral health-related quality of life.
