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110  |  Community Dent Oral Epidemiol. 2021;49:110–118.wileyonlinelibrary.com/journal/cdoe

Received: 21 May 2020  |  Revised: 28 August 2020  |  Accepted: 23 September 2020

DOI: 10.1111/cdoe.12582

O R I G I N A L A R T I C L E

Changes in income-related inequalities in oral health status in Ontario, Canada

Cheng Fang1  | Musfer Aldossri1 | Julie Farmer1 | Noha Gomaa2 | Carlos Quiñonez1 | Vahid Ravaghi3

© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd

1Dental Public Health, Faculty of Dentistry, University of Toronto, Toronto, ON, Canada 2Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada 3School of Dentistry, University of Birmingham, Birmingham, UK

Correspondence Cheng Fang, Dental Public Health, Faculty of Dentistry, University of Toronto, Toronto, ON, Canada. Email: [email protected]

Funding information Institute of Musculoskeletal Health and Arthritis, Grant/Award Number: 157758

Abstract Objectives: Oral health inequalities impose a substantial burden on society and the healthcare system across Canadian provinces. Monitoring these inequalities is crucial for informing public health policy and action towards reducing inequalities; however, trends within Canada have not been explored. The objectives of this study are as follows: (a) to assess trends in income-related inequalities in oral health in Ontario, Canada's most populous province, from 2003 to 2014, and (b) to determine whether the magnitude of such inequalities differ by age and sex. Methods: Data representative of the Ontario population aged 12 years and older were sourced from the Canadian Community Health Survey (CCHS) cycles 2003 (n = 36,182), 2007/08 (n = 36,430) and 2013/14 (n = 41,258). Income-related in- equalities in poor self-reported oral health (SROH) were measured using the Slope Index of Inequality (SII) and Relative Index of Inequality (RII) and compared across surveys. All analyses were sample-weighted and performed with STATA 15. Results: The prevalence of poor SROH was stable across the CCHS cycles, rang- ing from 14.1% (2003 cycle) to 14.8% (2013/14 cycle). SII estimates did not change (18.7-19.0), while variation in RII estimates was observed over time (2003 = 3.85; 2007/08 = 4.47; 2013/14 = 4.02); differences were not statistically significant. SII and RII were lowest among 12- to 19-year-olds and gradually higher among 20- to 64-year-olds. RII was slightly higher among females in all survey years. Conclusion: Absolute and relative income-related inequalities in SROH have persisted in Ontario over time and are more severe among middle-aged adults. Therefore, oral health inequalities in Ontario require attention from key stakeholders, including gov- ernments, regulators and health professionals.

K E Y W O R D S

income, inequalities, Ontario, oral health, public health

     |  111FANG et Al.

1  | INTRODUC TION

Socioeconomic inequalities in oral health and dental care are well-recognized globally, in which individuals of lower socioeco- nomic position have poorer oral health and more limited access to dental care than individuals of higher socioeconomic position.1,2 Compared with other developed nations, Canada, in particular, ex- periences similar inequalities in oral health, but more inequalities in dental care use.3-6

The Canadian healthcare system excludes oral health care from its national system of universal health insurance. Unlike physician and hospital care, oral health care is almost entirely pri- vately financed and delivered. Only about 5.5% of the Canadian population, predominately low-income groups, is covered by public dental insurance offered through programmes funded by federal, provincial and territorial governments.7,8 Compared with other developed nations, in 2009, Canada ranked second last in the percentage of dental care paid for by government.8 The major- ity of Canadians pay for dental care through private insurance or out-of-pocket spending, constituting 94% of all dental expenditure in the country.7,8 This also applies to children and youth in Canada as the majority of publicly funded dental programmes for chil- dren only cover basic dental care for children less than 18 years old from low-income families.9 Consequently, the probability and rate of visiting the dentist are heavily influenced by income and insurance, with affluent and privately insured groups visiting more often.10

As individuals of lower socioeconomic status experience greater difficulty accessing dental care, they arguably become more vul- nerable to oral diseases and conditions, thereby exacerbating in- equalities in oral health. A 2014 report by the Canadian Academy of Health Sciences explains that ‘those with the highest levels of oral health problems are also those with the greatest difficulty access- ing oral health care’.10 Studies using data from the Canadian Health Measures Survey 2007-2009 demonstrate that Canadians from lower-income households experience significantly worse oral health outcomes than those from higher-income households, such as the number of decayed and missing teeth, periodontal disease and oral pain.8,10,11 Further, the concentration of oral disease in lower-income groups is much greater than the concentration of general health con- ditions, such as obesity and high blood pressure.10

In 2012, Canada expressed a commitment towards reducing health inequalities by endorsing the Rio Political Declaration on Social Determinants of Health.12 Progress in this area is uncertain though, as little monitoring of health inequalities appears to occur. Yet, the 2008 World Health Organization Commission of Social Determinants of Health recommended ‘that routine monitoring systems for health equity and the social determinants of health (be) in place, locally, and internationally’.13 These ideas have been rein- forced by Canadian governing bodies and public health agencies,10,14 given that the monitoring of inequalities can help identify priority areas for action and the effectiveness of publicly funded dental pro- grammes in reducing inequalities.15,16

Despite this, there is currently little research quantifying the magnitude of oral health–related inequalities in Canada over time. Most studies in the Canadian and international literature have mea- sured inequalities in dental care, such as number of dental visits rather than oral health status. As a result, this study assesses in- come-related oral health inequalities over time in Ontario, Canada's most diverse and populous province. Specifically, it measures the magnitude of income-related inequality in self-reported oral health status between 2003 and 2014 using the Slope Index of Inequality (SII) and Relative Index of Inequality (RII), and evaluates differences by age and sex.

2  | METHODS

2.1 | Data source

Three public-use data sets of the Canadian Community Health Survey (CCHS) accessed through the University of Toronto were used in this study: (a) CCHS cycle 2.1, 2003; (b) CCHS 2007-2008; and (c) CCHS 2013-2014. The CCHS is a nationally representative cross-sectional survey initiated in 2001 by Statistics Canada, collect- ing self-reported information related to the health status, healthcare utilization and health determinants of the Canadian population aged 12 years or older who are living in private dwellings. The CCHS sta- tistically represents 98% of the Canadian population aged 12 years or older from all ten provinces and three territories, excluding in- dividuals living on Indian Reserves and Crown Lands, institutional residents, children aged 12 to 17 living in foster care, full-time mem- bers of the Canadian Forces and residents of certain remote regions. The methodology and sampling used in the CCHS are described elsewhere.17

The CCHS comprises a series of questions asked to all respon- dents (core content) and questions only asked to respondents within select regions varying from year to year (optional content). The ‘oral health 1’ module in which self-reported oral health status was collected was only included in the CCHS for certain years and provinces/territories, thereby only permitting analysis to the three aforementioned survey cycles.

2.2 | Outcome variable

Self-reported oral health (SROH) was used as the outcome variable from the CCHS. Participants provided SROH status by answering the question: ‘In general, would you say the health of your teeth and mouth is’ according to a 5-point scale (1 = excellent, 2 = very good, 3 = good, 4 = fair, and 5 = poor). For the purpose of this study, we dichotomized respondents who reported ‘excellent’, ‘very good’ or ‘good’ SROH into ‘good’ SROH, and respondents who reported ‘fair’ or ‘poor’ into poor SROH. For large epidemiological surveys, SROH serves as a cost-effective, valid and reliable measure of oral health status in individuals and populations.18,19 Clinical oral health

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measures are much more expensive and difficult to conduct in large populations and thus are often unfeasible. Nonetheless, SROH has been reported to be associated with various extents with numerous clinical indicators of oral health such as number of decayed teeth, missing teeth, future tooth loss and periodontal health status.18-22

2.3 | Exposure variable

Total annual household income was used as the socioeconomic variable. Alternative indicators of socioeconomic status such as educational attainment and occupational status tend to be stable or provide little variation among adults, potentially masking substantial socioeconomic variation in health outcomes.11 Income also appears to be the strongest contributor towards dental care inequalities among OECD countries.5 The CCHS adjusted total household in- come for household size in all three data sets used in this study and additionally adjusted for community size in the CCHS 2007-2008 and CCHS 2013-2014. In the CCHS 2007-2008 and CCHS 2013- 2014, total household income was categorized into income deciles based on the provincial income distribution. In the CCHS 2003, total household income was instead categorized into a 5-point income adequacy variable with ‘1’ being the lowest income group and ‘5’ being the highest income group. For consistency purposes, we col- lapsed total household income in CCHS 2007-2008 and CCHS 2013- 2014 into income quintiles. Since 2011, missing values for the total household income variable due to either respondent refusal or re- spondent's lack of knowledge of household income were imputed by Statistics Canada using a nearest neighbour imputation method.17,23

2.4 | Data analysis

All analyses were sample-weighted using values provided in the CCHS data sets to derive estimates for the Ontario population. Respondents with missing income data were excluded from analysis. There was no significant difference in reporting self-reported oral health status between respondents with reported and unreported income. Final percentages of included cases were n = 36,182 (84.6%) in the CCHS 2003, n = 36,430 (82.9%) in the CCHS 2007-2008 and n = 41,258 (97.0%) in the CCHS 2013-2014. Age-standardized proportions and odds ratios of poor SROH by income, age and sex were calculated. The data sets were age-standardized to the 2011 Canadian Census, Ontario subcomponent. Income-related inequality in SROH was measured using two complex, regression-based meas- ures of inequality, the Slope Index of Inequality (SII) and Relative Index of Inequality (RII).

Methods used to quantify the magnitude of health inequalities are termed ‘summary measures of health inequality’, which, at the most basic level, can be categorized into simple and complex mea- sures.16 Simple measures make pairwise comparisons in a health outcome between two subgroups, such as the most and least wealthy. Simple measures are typically easier to understand and

have historically been the dominant measurement used in inequality monitoring. However, simple measures only make comparisons be- tween two subgroups at once, and overlook other subgroups of the population, thus may be inadequate in capturing the whole picture of inequality.16 Recently, there has been growing interest in complex measures. Complex measures such as the SII and RII produce a sin- gle weighted value that describes the absolute and relative amount of inequality among all subgroups in a population, while account- ing for the proportion of the population each subgroup reflects.15,16 As the sociodemographic distribution of a population may change over time, it is important that summary measures are sensitive to these changes. Thus, the SII and RII are summary measures recom- mended when making comparisons over time or across different populations.15,16

In this study, the SII estimates the absolute difference in the prevalence of reporting poor SROH between those with the highest and lowest level of income, while taking into consideration the dis- tribution of poor SROH in all income groups.15,16 Positive SII values indicate that poor SROH is more prevalent in lower-income groups. We multiplied the coefficients of SII and corresponding confidence intervals by 100 for interpretation of SII as a difference in percent- age points. For example, an SII value of 25 in this study indicates a 25-percentage point increase in the prevalence of poor SROH from the very top of the income distribution to the very bottom. Negative SII values indicate a larger prevalence of poor SROH in higher-in- come groups and an SII value of 0 indicates virtually no inequality. The RII is an analogous measure except it estimates the relative dif- ference in inequality.15,16 It is calculated in the same manner as the SII, except the predicted values of the health outcome at the highest and lowest income group in the regression model are divided rather than subtracted. Therefore, an RII value greater than 1 indicates higher prevalence of poor SROH in the lowest income group.

Obtaining the SII and RII involves calculating the prevalence of poor SROH status in each income group and then transforming ranked income levels in each survey into weighted ridit scores scaled from zero (highest income level) to one (lowest income level).15,16 The ridit score is the midpoint of the income group's range in cumu- lative proportion of the total population. For instance, if the highest income group comprises 30% of the total population, the range of individuals in this group is assigned a ridit score of 0.15 (0.3/2), and if the second highest income group comprises 20% of the population, this group is assigned a value of 0.4 (0.3 + [0.2/2]), and so forth. The ridit scores are then incorporated as the exposure variable into the regression models of poor SROH status to calculate the SII and RII. In accordance with the literature, generalized linear models (log-bino- mial regression) were used with an identity link function to calculate the SII and with a logarithmic link function to calculate the RII.24

Sex- and age-stratified analyses were also performed to assess differences in inequalities between males and females and across age groups. Age categories were collapsed into 5 age groups: 12 to 19 years, 20 to 34 years, 35 to 49 years, 50 to 64 years, and 65 years and older. All data analyses were performed using STATA/ IC version 15.1. Findings were considered significantly different if

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two parameter estimates did not overlap in their 95% confidence intervals.

3  | RESULTS

3.1 | Sample characteristics

The sample comprised an equal proportion of males and females, with similar distribution of age and sex across the three CCHS sur- veys (Table 1). As previously mentioned, the distribution of income in the CCHS 2003 was different from the CCHS 2007-2008 and CCHS 2013-14 due to changes in reporting and classifying income. The prevalence of reporting poor SROH in Ontario was stable over

time at 14.5% in the CCHS 2003, 13.9% in the CCHS 2007-2008 and 14.8% in the CCHS 2013-2014. These values were similar to the age- standardized proportions presented in Table 2.

3.2 | Age-standardized proportions and odds ratios

Each survey demonstrated a higher prevalence of poor SROH with lower income (Table 2). For instance, in the CCHS 2007-2008, in- dividuals in the lowest income category were at 3.90 times greater odds of experiencing poor SROH than those in the highest income category. Even individuals of the middle-income category had al- most twice the odds of experiencing poor SROH than individuals in the highest income category. The proportion of individuals with poor SROH was generally higher with age and was also significantly higher in males than females across all three surveys. There were no significant changes in proportions and odds ratios by age group and sex across the three surveys.

3.3 | Slope and relative indices of inequality

The SII and RII were statistically significant in all surveys, indicating a persistent presence of absolute and relative inequalities where poor SROH was disproportionately present among individuals of lower income (Table 3). Since the CCHS 2003, there was very little change in the SII, ranging from 18.7 to 19.0 indicating approximately a 19 percentage point difference in poor SROH between the top and bot- tom of the income distribution. In terms of relative inequality, the RII increased from 3.85 in the CCHS 2003 to 4.47 in the CCHS 2007- 2008 and then decreased to 4.02 in the CCHS 2013-2014. These differences were not statistically significant.

Table 3 also presents the inequality analysis stratified by age and sex. These findings are also graphically represented in Figure 1 and Figure 2. In each CCHS survey, the SII and RII values were sta- tistically significant across all age groups and in both males and females. All the SII and RII values were positive and larger than 1, respectively, indicating a higher prevalence of poor SROH in low- er-income groups, regardless of age or sex. In each CCHS survey, the SII increased with each subsequent age group up to the 50- to 64-year age group and then decreased with the 65-year and older age group. Additionally, SII values in the 12- to 19-year age group (2003 = 10.2; 2007/08 = 2.8; 2013/14 = 4.2) were significantly lower than in older age groups across all CCHS cycles. Similarly, RII findings were lowest in the age group of 12- to 19-year-olds (2003 = 4.44; 2007/08 = 1.51; 2013/14 = 1.67) and highest in the middle age groups. From the CCHS 2003, the SII and RII decreased among adolescents and young adults but increased among older in- dividuals over time. These differences were not statistically signif- icant. The SII values were fairly similar between males and females in each survey and did not change significantly over time. The RII was slightly greater among females in each survey and increased from the CCHS 2003 to CCHS 2007-2008 and then decreased in

TA B L E 1   Sample population characteristics; frequency counts; and nonstandardized proportions (%)

CCHS 2003 CCHS 2007-2008

CCHS 2013-2014

n = 36 182 n = 36 430 n = 41 258

n (%) n (%) n (%)

Age (y)

12-14 1805 (4.4) 1496 (4.5) 1554 (3.6)

15-19 2484 (6.7) 2290 (6.8) 2825 (7.4)

20-24 1722 (8.1) 1745 (7.5) 2258 (8.2)

25-29 2419 (7.8) 2204 (8.2) 2226 (8.0)

30-34 3005 (8.6) 2660 (8.0) 2128 (7.5)

35-39 3292 (10.6) 2998 (9.2) 2402 (7.6)

40-44 3061 (11.6) 3115 (10.8) 2506 (8.5)

45-49 2743 (9.3) 2723 (9.5) 2135 (8.4)

50-54 2933 (8.4) 3051 (8.5) 3073 (9.3)

55-59 2904 (7.0) 3295 (8.2) 3809 (8.3)

60-64 2441 (5.1) 2938 (5.7) 3976 (6.9)

65-69 2220 (4.1) 2384 (4.5) 3973 (5.8)

70-74 1989 (3.4) 2015 (3.4) 2995 (4.2)

75-79 1670 (2.8) 1685 (2.6) 2403 (3.1)

80 and up 1494 (2.2) 1831 (2.5) 2995 (3.2)

Sex

Male 16 833 (49.9) 16 832 (49.8) 18 255 (48.8)

Female 19 349 (50.1) 19 598 (50.2) 23 003 (51.2)

Income

Richest 12 930 (43.1) 7629 (20.1) 8561 (20.2)

2nd 12 629 (32.9) 7050 (20.2) 8498 (20.2)

3rd 7070 (16.8) 7476 (20.1) 8519 (19.4)

4th 2492 (4.9) 6791 (19.8) 8538 (19.9)

Poorest 1061 (2.4) 7304 (19.8) 7142 (19.8)

SROH

Good 30 844 (85.6) 31 320 (86.1) 35 191 (85.2)

Poor 5338 (14.5) 5110 (13.9) 6067 (14.8)

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114  |     FANG et Al.

the CCHS 2013-2014 but differences were again not statistically significant.

4  | DISCUSSION

This study quantified and compared the magnitude of inequalities in reporting poor SROH in Ontario by using the complex measures of inequality (SII and RII). While it is important to monitor inequalities in dental care utilization, it is also vital to assess how socioeconomic inequalities may translate to actual differences in oral health out- comes. This study revealed a persistent presence of income-related inequalities in poor SROH in Ontario, Canada's most diverse and populous province. Since 2003, individuals in lower-income groups have experienced a noticeably higher prevalence of reporting poor SROH. Our findings also suggested that the severity of this inequal- ity has not improved over the course of ten years. Additionally,

income-related inequalities in SROH exist across all ages, and amongst both males and females. Findings also suggested that age groups from 20- to 64-year-olds experience a greater magnitude of inequality in SROH than 12- to 19-year-olds.

Explanations for oral health inequalities in Ontario and Canada have been discussed in the literature. Studies propose variation in oral health behaviours, dental service utilization and psychosocial factors as possible pathways leading to inequalities in oral health status between income groups.25-27 Due to the lack of available data on these factors, there is no way to assess the role of each in the inequalities in this study. Yet, as previously mentioned, dental care in Canada is almost wholly privately fi- nanced via employer-provided insurance plans or out-of-pocket payments. Similar to other high-income countries, higher-income groups and those with private insurance coverage visit the dentist significantly more often in Canada, especially for preventive den- tal services, thereby such populations generally have better oral

TA B L E 2   Age-standardized proportions (%) and odds ratios for poor self-reported oral health by income level, age and sex

CCHS 2003 CCHS 2007-2008 CCHS 2013-2014

Prop. (95% CI) Odds Ratio (95% CI) Prop. (95% CI)

Odds Ratio (95% CI) Prop. (95% CI)

Odds Ratio (95% CI)

Income a 

Richest 9.7 (8.9, 10.6) 1 7.8 (6.8, 8.8) 1 8.2 (7.1, 9.4) 1

2 15.0 (14.0, 16.0) 1.71 (1.52, 1.92) 9.7 (8.7, 10.8) 1.35 (1.13, 1.61) 9.9 (8.9, 11.1) 1.29 (1.07, 1.56)

3 21.7 (19.9, 23.5) 2.62 (2.30, 2.99) 12.2 (11.1, 13.4) 1.73 (1.47, 2.04) 14.1 (12.7, 15.7) 1.90 (1.58, 2.28)

4 28.9 (25.6, 32.4) 3.77 (3.14, 4.53) 17.5 (15.9, 19.2) 2.67 (2.26, 3.15) 17.9 (16.2, 19.8) 2.48 (2.07, 2.97)

Poorest 23.3 (19.8, 27.3) 2.89 (2.19, 3.81) 24.8 (22.9, 26.8) 3.90 (3.32, 4.59) 25.7 (23.7, 27.9) 3.65 (3.06, 4.36)

Age (y)

12-14 7.6 (5.8, 09.9) 1 7.3 (5.7, 9.4) 1 8.8 (6.8, 11.2) 1

15-19 7.8 (6.4, 09.6) 1.04 (0.72, 1.50) 6.3 (5.1, 7.8) 0.85 (0.60, 1.21) 7.8 (6.2, 9.8) 0.89 (0.61, 1.29)

20-24 10.8 (8.7, 13.4) 1.48 (1.01, 2.17) 11.3 (9.3, 13.7) 1.61 (1.14, 2.29) 13.9 (11.6, 16.4) 1.68 (1.19, 2.36)

25-29 11.8 (10.0, 13.9) 1.63 (1.16, 2.31) 11.7 (9.9, 13.9) 1.68 (1.20, 2.34) 14.5 (12.4, 17.0) 1.77 (1.28, 2.47)

30-34 13.5 (11.8, 15.4) 1.91 (1.37, 2.66) 10.8 (9.3, 12.5) 1.53 (1.11, 2.11) 11.8 (9.6, 14.3) 1.39 (0.97, 1.98)

35-39 13.6 (12.0, 15.5) 1.93 (1.39, 2.68) 12.1 (10.4, 13.9) 1.73 (1.26, 2.39) 12.6 (10.3, 15.2) 1.50 (1.05, 2.14)

40-44 14.8 (13.0, 16.8) 2.12 (1.53, 2.95) 14.5 (12.5, 16.8) 2.14 (1.55, 2.96) 14.7 (12.2, 17.7) 1.80 (1.26, 2.56)

45-49 16.1 (14.1, 18.5) 2.35 (1.68, 3.28) 15.8 (13.6, 18.4) 2.37 (1.71, 3.30) 13.6 (11.0, 16.6) 1.64 (1.14, 2.36)

50-54 19.6 (17.4, 22.0) 2.97 (2.14, 4.12) 16.8 (14.7, 19.2) 2.56 (1.86, 3.51) 19.5 (16.3, 23.2) 2.53 (1.78, 3.59)

55-59 16.9 (14.9, 19.2) 2.49 (1.79, 3.47) 16.6 (13.4, 20.5) 2.51 (1.73, 3.66) 18.5 (16.1, 21.1) 2.36 (1.71, 3.26)

60-64 17.8 (15.7, 20.1) 2.65 (1.91, 3.68) 18.6 (16.3, 21.1) 2.88 (2.09, 3.95) 16.1 (14.2, 18.2) 2.00 (1.46, 2.73)

65-69 17.8 (15.6, 20.2) 2.64 (1.90, 3.68) 17.8 (15.3, 20.6) 2.73 (1.97, 3.80) 18.4 (16.1, 21.0) 2.35 (1.71, 3.24)

70-74 16.4 (14.3, 18.8) 2.40 (1.72, 3.35) 19.3 (16.7, 22.3) 3.03 (2.18, 4.20) 17.3 (14.5, 20.5) 2.18 (1.55, 3.08)

75-79 20.2 (17.2, 23.6) 3.09 (2.17, 4.40) 18.6 (15.5, 22.2) 2.88 (2.03, 4.10) 17.8 (15.1, 20.9) 2.26 (1.61, 3.17)

80 or more 17.3 (14.7, 20.3) 2.56 (1.80, 3.64) 18.9 (16.1, 22.0) 2.94 (2.11, 4.12) 19.3 (16.8, 22.1) 2.50 (1.81, 3.45)

Sex

Male 16.1 (15.3, 17.0) 1 15.7 (14.7, 16.7) 1 16.4 (15.4, 17.5) 1

Female 13.2 (12.4, 13.9) 0.80 (0.73, 0.88) 12.5 (11.7, 13.2) 0.76 (0.68, 0.84) 13.1 (12.3, 14.0) 0.78 (0.70, 0.87)

Overall 14.6 (14.1, 15.2) – 14.1 (13.5, 14.7) – 14.8 (14.1, 15.5) –

aIn CCHS 2003, income was categorized by the CCHS into five income adequacy groups. In CCHS 2007-2008 and 2013-2014, income was categorized by provincial income distribution.

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health, which may play a role in explaining the inequalities this study has observed.28

A previous study assessing the Canadian Health Measure Survey reported greater magnitude of income-related inequalities in terms of decayed and missing teeth among women.11 Contrarily, this study

did not find significant differences in absolute or relative inequality between males and females for reporting poor SROH. A study by Wamala et al on the Swedish population also did not find sex dif- ferences when evaluating inequalities in self-reported oral health between men and women.26 Research on other aspects of health

F I G U R E 1   Change in SII and RII for poor SROH over CCHS survey cycles [Colour figure can be viewed at wileyonlinelibrary.com]

F I G U R E 2   Change in absolute and relativeinequalities in poor SROH by age and sex

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     |  117FANG et Al.

however generally suggests that inequality is greater among men.29-

31 Potential mechanisms explaining differences in health inequalities between sexes such as differences in lifestyle, employment status and access to oral healthcare services have been proposed; however, the mechanisms remain unclear.3 Further investigation in the contri- bution of sex to the magnitude of oral health inequality is merited.

The magnitude of income-related inequalities in this study also increased with age with the exception of the RII in the CCHS 2003. It could be that, for children and adolescents, parents and guardians without private dental insurance are more willing to spend out-of- pocket for their child's dental care needs rather than their own even when their income and available expenditure is lower. Additionally, prior to 2016, Ontario had six provincially funded dental programmes for children and youth from low-income families, constituting a sig- nificant portion of all public dental expenditure in the province.32 In 2016, Ontario amalgamated these programmes into one programme for children and youth 0 to 17 years old from low-income families.33 Consequently, publicly funded programmes might help reduce the magnitude of oral health inequality in the youth/adolescent pop- ulation. For individuals over 17 years of age, Ontario operates the Ontario Works and the Ontario Disability Support Program, but these programmes only cover individuals on social assistance and disability assistance, and constitute a relatively minor share of all dental expenditure in Ontario. Beyond the publicly funded dental programme available to children, there is very limited public cover- age for adults in Ontario.

Differences in the magnitude of income-related inequalities in oral health by age group may also partially be explained by the in- verse relationship between the retention of teeth and increasing age and diminishing income.3,34 As older adult populations retire, the cost of dental care also becomes a larger barrier to care due to loss of employment-based insurance and reduction in income.35-38 Our findings reinforce the need for age-specific analyses of oral health inequalities to better understand what might influence the increas- ing magnitude of oral health inequalities.

This study should also be interpreted within its limits. The con- fidence intervals were relatively broad and overlapping; therefore, potential differences in inequalities might not have been captured. Further, as SROH data are not included in each cycle of the CCHS nor for every province, there was a less than optimal number of data points to assess changes in inequality in Ontario or Canada over time. Additionally, self-reported measures are heavily subjective to personal beliefs, education, and societal and cultural factors to varying degrees between individuals.39,40 Patients may also be less likely to adequately assess the presence of caries and periodontal disease than they are the number of teeth and restorations.19,41-43 As more data regarding oral health outcomes and status are collected in Canada, a more comprehensive analysis of changes in inequality will be permitted.

Ultimately, this study demonstrates a lack of improvement in oral health–related inequality in a Canadian population over time. Using the SII and RII along with other measurement tools of inequality can allow for the identification of the most inequitable areas of health

and populations experiencing the greatest severity of inequality. This can help inform policymakers in regard to decision-making around the allocation of resources to areas and populations in great- est need.

ACKNOWLEDG EMENTS Support for this study was generously provided by the Canadian Institute of Health Research (CIHR) Undergraduate Studentship Award—Institute Community Support (Award No. 157758). The funders had no role in study design, data collection, analysis or inter- pretation, nor the writing of the manuscript.

CONFLIC T OF INTERE S T The authors declare that they have no conflicts of interest.

AUTHOR CONTRIBUTIONS Fang, Aldossri, Farmer, Gomaa, Quiñonez and Ravaghi conceived or designed the work, critically revised the article and approved the final version for publication. Fang and Aldossri collected data. Fang, Aldossri, Farmer and Gomaa analysed and interpreted data. Fang drafted the article.

DATA AVAIL ABILIT Y S TATEMENT The Public Use Microdata Files (PUMFs) that support the findings of this study are available from Statistics Canada. Restrictions apply to the availability of these data, which were used under licence for this study. The PUMFs are available at https://www150.statc an.gc. ca/n1/en/catal ogue/82M0013X with the permission of Statistics Canada.

ORCID Cheng Fang https://orcid.org/0000-0002-7192-7415 Vahid Ravaghi https://orcid.org/0000-0003-3056-3704

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How to cite this article: Fang C, Aldossri M, Farmer J, Gomaa N, Quiñonez C, Ravaghi V. Changes in income-related inequalities in oral health status in Ontario, Canada. Community Dent Oral Epidemiol. 2021;49:110–118. https://doi. org/10.1111/cdoe.12582

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onditions (https://onlinelibrary.w iley.com

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ibrary for rules of use; O A

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