The results of this study reinforce the association between socioeconomic inequalities and the concentration of oral diseases. In addition, it highlights the need to examine access to public oral health services. The distribution of oral diseases occurs heterogeneously in different social groups. Oral disease is considered a health inequality, given that it is preventable, and the fact that it persists is unjust [28].
A greater presence of components of ODB (dental caries, tooth loss, the need for dental prostheses, and periodontal conditions) was identified in nonwhite individuals, those with a low family income, those with few years of study, and those who indicated that their oral health had an impact on their daily activities. This supports the findings of the study, who argue that strong socioeconomic inequalities in oral health mean that poor and vulnerable groups in society are particularly affected [14].
It is relevant to investigate whether the majority population group in Brazil (the brown and black population) is receiving adequate care to reduce the burden of oral diseases [29]. This group is more vulnerable because it has lower levels of education and income [30], poorer overall health outcomes [31] and poorer oral health [32]. However, although they are at higher risk, they are less likely to use the dental health services available [33] and to visit the dentist for preventative care [29].
The association of higher ODB with socioeconomic factors reinforces the need to overcome the exclusiveness of oral health care approaches and to combine broader policy initiatives to combat oral health inequalities at the structural level, with a focus on social issues, determinants of health and shared risk factors between oral diseases and other chronic noncommunicable diseases [34].
The few studies of this higher disease burden demonstrate the need for inclusive educational policies. Cities with better educational policies showed a lower prevalence of untreated dental caries and tooth loss than cities with worse educational policies [35]. Education can also act indirectly on income: the higher an individual’s education level is, the greater his or her possibility of finding a better paid job, which would increase his or her ability to pay for private dental care, among other needs [29]. In addition, the positive impact can manifest as increased knowledge and the adoption of healthy habits [36].
The lower income group had higher percentages of untreated dental caries in all municipalities, regardless of the availability of public policies (sanitation, dental care and education) and the fluoridation of public water supply. The income indicator establishes a nexus with health levels to the extent that it enables individuals to acquire goods and services that promote or rehabilitate health [36].
The adjusted multivariate binary logistic regression model showed that elderly individuals have a two times greater chance than adolescents of having a component of ODB. This demonstrates that socioeconomic status cumulatively affects oral health throughout life and highlights the importance of this status as an indirect factor in oral health later in life [37].
In this study, we considered different age groups because it is necessary to expand oral health studies beyond children and adolescents to include adults and elderly individuals due to changes in the aging of the population, the increase in life expectancy, and the displacement of the disease burden in the direction of chronic diseases. For this reason, studies on inequalities in the distribution of dental caries among these groups are necessary [3].
The OIDP results were associated with a higher ODB. The analysis of this indicator is relevant because it enables the assessment of oral health-related quality of life (HRQOL). Oral HRQOL is a multidimensional indicator that assesses the extent to which oral diseases affect the daily functioning and the social, emotional and psychological well-being of individuals [38]. The findings corroborate those of other studies that associate the worst individual social conditions with oral health problems and low HRQOL [39–41].
Considering the high concentration of goods and wealth in Brazil and the existence of a health system that includes equity as one of its principles, it is very important for health research and planning to have a systematic understanding of studies that have investigated social inequalities in the prevalence of dental caries [3].
The use of zone and population information in the planning and programming of health services is a major challenge given the initial limitation of professional training and the efforts required by the health surveillance-based model of care, which is based on the premise that information on determinants, risk and protective factors, and damage to health can be monitored to identify vulnerable groups and populations or those with potential for a healthy life [42].
There are compelling reasons to be concerned with resolving health inequalities. The persistence of differences in health based on race/ethnicity or other social factors (such as education) raises moral concerns and upsets the basic notion of justice and human rights.
The current study has some limitations and strengths. In general, this population-based study from the state of São Paulo provides some evidence of the social and economic factors associated with a greater ODB. Although it is not possible to replicate the results for the entire country of Brazil, it is noteworthy that São Paulo is the most populous state in the country, comprising approximately 22% of the Brazilian population [43].
It should be noted that the multiple correspondence analysis should be interpreted as complementary to the logistic regression model because it illustrates the relationships of each category of independent variable with the binary categories of the dependent variable.
Due to the cross-sectional nature of the study, temporal relationships cannot be elucidated. However, the inverse cause may be unlikely given that the components of ODB have low latency in the population, presumably because the contextual characteristics that were evaluated, such as race/color and years of study, were present before the ODB emerged.
The findings of this study may help researchers, oral health professionals and managers in planning and programming oral health services in the SUS. Other studies that analyze the association between oral health diseases and socioeconomic factors, the work of oral health teams, and the organization of the Oral Health Network are necessary to construct an inclusive and effective practice; therefore, it is necessary to approach the people who need oral health services and try to understand their living conditions.