Social determinants of health linked with oral health in a representative sample of U.S. adults

Abstract

Background

Oral diseases remain a significant public health problem worldwide, with growing gaps in oral health status among various socioeconomic groups. The objective of the current study is to analyze the impact of different social determinants of health (SDOH) on oral health outcomes (frequency of dental visits, self-reported oral health status, embarrassment because of oral health status, and tooth loss) among a representative sample of United States (U.S.) adults.

Methods

Cross-sectional data for this observational study came from adults aged 18 and above (N = 5,320) participating in the nationally representative 2021 State of Oral Health Equity in America survey. Bivariate and multivariable analyses were conducted to examine the associations between oral health outcomes (dependent variables) and SDOH independent variables: structural (race/ethnicity, income, education); and intermediary (lack of transportation, food insecurity, racial discrimination, and housing instability), controlling for the confounding variables of age, gender, employment status, dental insurance, self-rated mental/emotional health, self-rated physical health, presence of one or more chronic conditions, and having had a routine physical examination in the past year.

Results

When controlling for confounding variables, Black adults were less likely than White adults to have had a dental visit in the last year (odds ratio (OR) = 0.72 (95% confidence interval (CI) = 0.57–0.92, p < 0.05), more likely to report feeling self-conscious or embarrassed due to their oral health (OR = 1.67 (95% CI = 1.31–2.12, p < 0.05), and more likely to have at least one permanent tooth removed (OR = 1.67 (95% CI = 1.31–2.13, p < 0.05). Higher income and more education were significantly associated with greater odds of rating one’s oral health positively and having had a dental visit in the past year and lesser odds of feeling self-conscious or having at least one tooth removed (p’s < 0.05). All four intermediary determinants were associated with significant (p < 0.05) and negative odds of having a dental visit in the past year and reporting positive oral health, and with positive odds of having at least one permanent tooth removed. The odds of feeling self-conscious or embarrassed due to their oral health were significantly and positive associated with all intermediary determinants except for racial discrimination (OR = 1.21, 95% CI = 1.00–1.46).

Conclusions

Significant inequities still exist in the U.S. regarding SDOH and their relationship to oral health. Improving oral health will involve addressing SDOH. Successful policy and public health interventions must address not only structural factors but also intermediary SDOH.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12903-024-05257-8.

Background

Social determinants of health (SDOH) are associated with access to care, dental care utilization [1], and several oral health conditions [2–5] across the life span [6–8]. Key determinants of pediatric oral health, for example, include lack of access to healthy food and transportation, as well as social factors such as neighborhood and family social capital [9–12]. Based on the conceptual framework by the World Health Organization (WHO) Commission on Social Determinants of Health (CSDH), structural determinants such as economic, social, and welfare policies can create societal structures and influence individuals' socioeconomic position (SEP) within communities [13]. These structural determinants in turn shape specific intermediary determinants of health such as housing and working conditions, social capital, social support, psychosocial factors, and behavior and biology [13]. This framework acknowledges the interaction of structural and intermediary determinants in shaping health outcomes.

Structural determinants of oral health

In the United States (U.S.), racial and ethnic disparities exist for several oral health indicators, including tooth loss [14]. In a study of tooth retention and poverty level among adults aged 25–64, 35% of non-Hispanic White adults had a full set of permanent teeth compared to only 19% of Hispanic adults and 11% of Black adults [7]. Nazer and colleagues found ethnic inequalities in tooth loss among American adults aged < 40 years exist even after adjusting for SEP [15].

Because of environmental conditions and SDOH [4, 5, 16, 17], populations from low SEP backgrounds, including those with lower education and income, are at a higher risk for various adverse oral health conditions [6, 7, 15, 18–21]. They are also commonly located in areas where access to health care is limited [22]. Individuals with poor oral health often feel embarrassed in social settings and when visiting a dentist [23, 24]. Individuals receiving public assistance have reported the gradual deterioration of their oral health over the course of their lives and discussed the negative effects this deterioration has on their social interactions, employability, and self-esteem [23].

Intermediary determinants of oral health

Lack of or limited access to public transportation, eligibility of transportation for certain populations, travel cost, and depending on relatives and friends for transportation are among several barriers to accessing health care [14, 25, 26]. In a scoping review to investigate the relationship between socio-demographic and psychosocial barriers to access to oral health care among adults, lack of transportation to dental services was reported as a critical barrier across studies [14].

Food insecure adults are more likely to have poor self-reported oral health and unmet dental care [21]. Food insecurity and housing instability contribute significantly to dental care use and access, adding information not captured by standard socioeconomic determinants [20, 27].

Racial discrimination is a significant contributor to various adverse health outcomes for racial and ethnic minorities, in part by depriving impacted groups of access to health care [28]. The key effects of racism (discriminatory employment policies, immigration policies, limited oral health resources, and limited oral health care access) perpetuate inequities and lead to poor oral health outcomes [29]. Individuals who experience the emotional impact of discrimination are less likely to have a dental visit than those who do not [30].

Wallace and colleagues found a relationship between poor self-reported oral health status and housing instability [31]. A meta-regression of data from four nationally representative surveys found worsening housing instability and economic standing were associated with poorer access to healthcare [32].

The current literature examines the association of social determinants of oral health mostly in terms of SEP, biology and behavior [15, 17, 33], with limited research on intermediary determinants such as material circumstances or how social determinants are modified by intermediary determinants. The current literature does not hypothesize that the intermediary determinants explain, or mediate, the relationship between structural determinants and oral health outcomes, so we do not explore that in this paper. To date, the literature regarding social determinants of health related to oral health has primarily focused on direct relationships between individual social determinants and oral health, rather than the complex interactions between structural and intermediary determinants and how those interactions relate to oral health [34, 35]. To our knowledge, no studies have investigated multiple SDOH with multiple oral health-related outcomes and assessed the interaction effects between structural and intermediary determinants, which help identify if the intermediary determinants modify the impact of structure determinants on our outcomes of interest. Given this, the aim of the present study was to analyze the impact of the interactions of different structural and intermediary determinants of health outlined within the CSDH framework on the oral health outcomes of dental visits, oral health status, embarrassment because of teeth and tooth loss among a sample of U.S. adults.

Methods

Study population

Data for this study came from the nationally representative 2021 State of Oral Health Equity in America survey [36]. This survey contains ~ 150 items related to consumer experiences, behaviors, and attitudes toward oral health and related factors. The survey was developed by CareQuest Institute for Oral Health and was administered in January–February 2021 through the non-partisan research organization National Opinion Research Center (NORC) at the University of Chicago, using the AmeriSpeak® panel. Respondents were aged 18 and above and recruited from randomly selected households sampled using area probability and address-based sampling. When contacted by an AmeriSpeak® staff member and before taking part in the survey, adults invited to participate in the survey were provided with information about the survey and asked to provide their informed consent to participate, either online (for those completing the survey online) or verbally (for those completing the survey by telephone). A sampling unit of 17,603 was used, with a final sample size of 5,682 and a final weighted cumulative response rate of 4.0%. All data presented account for appropriate sample weights provided by NORC at the University of Chicago and account for design effects accounting for their probability of selection into the panel, patterns of nonresponse among key demographic groups, and post-stratification population weighting to align with known population benchmarks. The margin of error for the survey was 1.75%. It was reviewed and determined to be exempt by the Western Institutional Review Board (WIRB). Data are available from the corresponding author upon request.

Structural and intermediary determinants (independent variables)

Using the CSDH conceptual framework, three SDOH variables were included in the analyses as structural determinants: race/ethnicity (White; Black; Asian; Hispanic; or other), education (less than high school; high school equivalent; or some college or more), and household income (less than $30,000; $30,000 to under $60,000; $60,000 to under $100,000; or $100,000 or more). Four SDOH variables were included in the analyses as intermediary determinants: lack of transportation, food insecurity, racial discrimination, and housing instability. Respondents replied yes or no to the following question to indicate lack of transportation: “Within the last year, have you ever delayed care, missed an appointment or been unable to obtain needed health care because of problems with your transportation?” Respondents were categorized as experiencing food insecurity if they responded “often” or “sometimes true” to one or both of the following questions: “My household was worried whether our food would run out before we got money to buy more / The food we bought just didn’t last, and we didn’t have money to get more” [37]. Respondents were asked, “Have you experienced racial discrimination as a result of any of the following in your lifetime?” (yes/no). Housing instability was categorized as yes if, in the last year, respondents missed a rent or mortgage payment, were threatened with foreclosure or eviction, or had to move.

Dependent variables

This study examined four dependent variables outcomes (DVs) as described in Appendix A. Respondents who said they had a dental visit less than 6 months ago or between 6–12 months ago were identified as having a dental visit within the past year (“yes”) as a proxy for access to dental care. They were also asked to describe their self-reported oral health status, and responses were dichotomized as excellent/very good/good vs. fair/poor. Respondents indicated how often (hardly ever/never or occasionally/fairly/very often) they had been self-conscious or embarrassed because of their teeth, mouth, or dentures. Finally, they indicated whether they had any permanent teeth removed because of tooth decay or gum disease (none or more than one).

Confounding variables

Confounding variables included age (18–29; 30–44; 45–59; and 60 and above), gender (male/female), employment status (yes/no), dental insurance (yes/no), status of mental/emotional health and physical health (excellent/very good/good vs. fair/poor), presence of one or more chronic health conditions (yes/no) and having had routine annual physical examination in the last two years (yes/no).

Statistical analysis

Descriptive statistics were used to calculate frequencies and weighted percentages of the SDOH structural and intermediary determinants and confounding variables. All estimates were stratified by the SDOH variables, and chi-square tests were used to determine statistical significance of differences (p < 0.05) between variables. Separate multivariable logistic regression models were conducted to examine associations between primary independent SDOH variables and dichotomous DVs. Because the SDOHs are highly correlated with each other and we want to understand the separate effects of the SDOH variables on our outcomes, we developed a separate logistic regression model for each SDOH to avoid issues of multicollinearity (correlation between SDOH variables).

Two sets of models were built for each SDOH: 1) a main effects model isolated the effects of each SDOH on oral health outcomes while adjusting for covariates, and 2) a model testing for interactions between structural determinants (race/ethnicity, education, household income) and intermediary determinants (lack of transportation, food insecurity, racial discrimination, housing instability) in order to assess the moderating effects of the structural determinants on those intermediary effects (i.e., whether levels of intermediary determinants changed by different levels of structural determinants). The main effects models adjusted for confounding factors including age, gender, mental health status, physical health status, other chronic health conditions, routine medical visit, and employment status. The interaction models were adjusted for the same confounding variables and tested the effects on oral health outcomes of each primary SDOH variable at different levels of three structural determinants of race/ethnicity, education, and income. This helped determine if the impact of the SDOH variable on dental utilization or outcomes is moderated by socio-demographic conditions. All analyses were performed using R Version 4.2.0 (Foundation for Statistical Computing, Vienna, Austria) using the Survey package. The survey package was used to provide appropriate weights to obtain national-level estimates.

Results

Descriptive and bivariate statistics

Table 1 shows descriptive statistics for the sample (N = 5,320). Table 2 shows the results of descriptive statistics for the primary SDOH independent variables stratified by the DVs (main effects of structural and intermediary determinants are shown in Supplementary Table 1). Having had a dental visit in the past year was significantly associated with all SDOH except for racial discrimination (p = 0.233). Self-reported oral health status was significantly associated with all independent variables except racial discrimination (p = 0.063). All SDOH were significantly associated with feeling self-conscious or embarrassed due to their oral health (p’s < 0.05). Having had at least one permanent tooth removed was significantly associated with food insecurity, lack of transportation, and dental insurance (all p’s < 0.05), but not with housing instability (p = 0.699) or racial discrimination (p = 0.954; Table 2).

Table 1.

Demographic variables of the study sample

	Overall
Total N = 5,320	Frequency	Weighted %
Race/ethnicity
White	3,255	63.4
Black	769	11.8
Asian	112	4.6
Hispanic	952	16.3
Other	232	3.8
Education
< High school	261	9.6
HS graduate	1,023	27.6
College or more	4,036	62.8
Household income
< $30 k	1,451	27.2
$30 K-$60 k	1,506	25.9
$60 K-$100 K	1,335	24.3
$100 K +	1,028	22.5
Age
18–29	795	20.0
30–44	1,509	25.3
45–59	1,124	24.4
60 +	1,892	30.3
Gender
Male	2,722	48.2
Female	2,598	51.8
Dental Insurance
Yes	3,687	70.3
No	1,615	29.7
Employment Status
Employed	3,075	57.5
Unemployed	2,245	42.5
Mental health status
Fair/poor	917	17.9
Excellent/very good/good	4,379	82.1
Physical health status
Fair/poor	963	17.2
Excellent/very good/good	4,351	82.8
Other chronic conditions
No	3,323	64.7
Yes	1,963	35.3
Routine medical visit
No	1,215	23.8
Yes	4,092	76.2

Table 2.

Descriptive statistics for dental visit within the past year, self-reported oral health status, being self-conscious or embarrassed due to oral health, and having at least one permanent tooth removed because of tooth decay or gum disease by intermediary determinants (independent variables)

	Overall		Dental visit in the past year Weighted (Wtd) %)			Self-reported oral health status (Wtd%)
Total N = 5,320	Freq.	Wtd %	No (N=2,021)	Yes (N=3,295)	p-value	Excellent/ very good/ good (N=3,868)	Fair/Poor (N=1,437)	p-value
			37.3	62.7		73.8	26.2
Lack of Transportation
No	4,729	89.1	84.4	91.7	<0.001	92.2	79.8	<0.001
Yes	556	10.9	15.6	8.3		7.8	20.2
Housing Instability
No	4,588	85.8	80.2	89.4	<0.001	88.1	79.1	<0.001
Yes	732	14.2	19.8	10.6		11.9	20.9
Racial Discrimination
No	4,055	77.7	76.2	78.5	0.233	78.4	75.6	0.063
Yes	1,265	22.3	23.8	21.5		21.6	24.4
Food Insecurity
No	3,950	74.5	65.8	78.9	<0.001	79.0	61.4	<0.001
Yes	1,318	25.5	34.2	21.2		21.0	38.6
	Overall		Self-conscious or embarrassed due to oral health (Wtd%)			At least one permanent tooth removed (Wtd%)
Total N = 5,320	Freq.	Wtd %	Hardly ever/ Never (N=3,499)	Occasionally/ fairly/ very often (N=1,768)	p-value	None (N=2,696)	At least one (N=2,608)	p-value
			66.4%	33.6%		54.3%	45.7%
Lack of Transportation
No	4,729	89.1	93.3	80.7	<0.001	91.9	85.4	<0.001
Yes	556	10.9	6.7	19.3		8.1	14.6
Housing Instability
No	4,588	85.8	89.7	78.0	<0.001	85.5	86.1	0.699
Yes	732	14.2	10.3	22.0		14.5	13.9
Racial Discrimination
No	4,055	77.7%	78.9%	75.4%	0.025	77.6%	77.7%	0.954
Yes	1,265	22.3%	21.1%	24.6%		22.4%	22.3%
Food Insecurity
No	3,950	74.5%	83.1%	57.5%	<0.001	78.5%	69.3%	<0.001
Yes	1,318	25.5%	16.9%	42.5%		21.5%	30.7%

Logistic regression models

Structural determinants

Figure 1 and Supplementary Table 1 show the results of multivariate logistic regression models used to examine associations between structural determinants and oral health outcomes. Overall, when adjusting for confounders, Black adults were less likely than White adults to have had a dental visit in the last year (odds ratio (OR) = 0.72 (95% confidence interval (CI) = 0.57–0.92, p < 0.05) and more likely to report feeling self-conscious or embarrassed due to their oral health (OR = 1.67 (95% CI = 1.31–2.12, p < 0.05) or have at least one permanent tooth removed (OR = 1.67 (95% CI = 1.31–2.13, p < 0.05). Adults with some college or more and adults whose household income was $60,000 or more annually were more likely to have had a dental visit in the last year (ORs range = 1.57–1.71) and describe having positive oral health (ORs range = 1.56–2.40) and less likely to feel embarrassed due to their oral health (ORs range = 0.53–0.61) or have at least one tooth removed (ORs range = 0.27–0.53) than individuals with less than high school and those whose household income was less than $30,000 annually.

Fig. 1.

Results of multivariable logistic regression models to examine associations between structural determinants (independent variables) and outcomes (dependent variables). Models are adjusted for age, gender, dental insurance, self-reported mental and physical health status, other chronic conditions, routine medical visit, and employment status. Reference categories: Race/ethnicity = white; education = less than high school; income = less than $30,000

Intermediary determinants

Table 2 and Fig. 2 show descriptive statistics and results of multivariable logistic regression models to examine associations between intermediary determinants and outcomes. All four intermediary determinants were associated with significant (p < 0.05) and negative odds of having a dental visit in the past year and reporting positive oral health and were associated with significant and positive odds of having at least one permanent tooth removed. The odds of feeling self-conscious or embarrassed due to their oral health were significantly and positively associated with all intermediary determinants except for racial discrimination (OR = 1.21, 95% CI = 1.00–1.46).

Fig. 2.

Results of multivariable logistic regression models to examine associations between intermediary determinants (independent variables) and outcomes (dependent variables). Models are adjusted for age, gender, dental insurance, self-reported mental and physical health status, other chronic conditions, routine medical visit, and employment status

Interaction effects

Table 3 shows the significant (p < 0.05) marginal interaction effects between the structural and intermediary determinants. In general, the interaction effects demonstrate differences in the degree of association of the structural determinants with the outcome variables within particular intermediary determinants. In other words, these effects show how, within the context of a particular intermediary determinant, the relationship between a structural determinant and a dependent variable is moderated by the level of the structural determinant. As an example, for adults experiencing a lack of transportation (intermediary), the odds of having one or more teeth removed (dependent) were less for Hispanic adults than White adults (OR = 0.26, 95% CI = 0.13–0.48; structural). Among adults experiencing food insecurity, the odds of reporting positive oral health were 1.68 times higher for Hispanic adults than White adults (OR = 1.68, 95% CI = 1.04–2.58). For adults experiencing racial discrimination, the odds of reporting positive oral health were lower for Black adults than White adults (OR = 0.56, 95% CI = 0.34–0.91). Finally, for individuals experiencing housing instability, Black (OR = 1.87, 95% CI = 1.02–3.46) and Hispanic (OR = 2.32, 95% CI = 1.20–4.51) adults were more likely to describe their oral health as positive compared to White adults, while adults reporting their race as “other” were less likely than White adults to rate their oral health in this way (OR = 0.29, 95% CI = 0.11–0.81).

Table 3.

Significant marginal interaction effects on outcomes (dependent variables) by structural and intermediary determinants (independent variables)

	Lack of Transportation		Housing Instability		Racial Discrimination		Food Insecurity
	Yes	No	Yes	No	Yes	No	Yes	No
	OR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)	OR (95% CI)
Dental Visit in Last Year
Race/Ethnicity: Black	ns	ns	ns	0.72 (0.55–0.95)	ns	ns	ns	0.68 (0.51–0.91)
Race/Ethnicity: Hispanic	ns	0.78 (0.62–0.99)	ns	0.76 (0.60–0.97)	ns	ns	ns	0.75 (0.58–0.98)
Race/Ethnicity: Asian	ns	0.53 (0.30–0.91)	ns	0.37 (0.21–0.66)	ns	0.36 (0.16–0.78)	ns	0.34 (0.19–0.60)
Positive Self-Reported Oral Health
Race/Ethnicity: Black	ns	ns	1.87 (1.02–3.46)	ns	0.56 (0.34–0.91)	1.80 (1.11–2.90)	ns	0.69 (0.49–0.99)
Race/Ethnicity: Hispanic	ns	ns	2.32 (1.20–4.51)	ns	ns	ns	1.68 (1.04–2.58)	ns
Race/Ethnicity: Asian	ns	ns	ns	ns	ns	ns	ns	0.50 (0.25–0.99)
Race/Ethnicity: Other	ns	ns	0.29 (0.11–0.81)	ns	ns	ns	ns	ns
Education: High school	ns	ns	2.82 (1.10–7.25)	ns	ns	ns	ns	ns
Education: Some college or more	ns	ns	ns	ns	0.35 (0.13–0.97)	ns	ns	ns
Feeling Self-Conscious due to Oral Health
Race/Ethnicity: Black	ns	1.46 (1.11–1.92)	ns	1.51 (1.15–1.99)	ns	ns	ns	1.40 (1.05–1.88)
At Least One Permanent Tooth Removed
Race/Ethnicity: Black	ns	1.62 (1.25–2.11)	ns	1.44 (1.10–1.90)	1.61 (1.04–2.48)	ns	ns	1.56 (1.17–2.08)
Race/Ethnicity: Hispanic	0.26 (0.13–0.48)	ns	ns	ns	ns	ns	ns	ns

Only effects significant at p < 0.05 shown (ns = not significant); Reference categories: Race/ethnicity = white; education = less than high school

Discussion

This study is one of the first to investigate the associations between multiple SDOHs and various oral health outcomes in one study, as well as one of the first studies to examine how intermediary determinants modify the relationship between structural determinants and oral health outcomes, which provides a novel contribution to the existing literature that examines the relationships between SDOH and oral health. Adults who reported experiencing any SDOH were generally more likely to have poor oral health outcomes, including being significantly less likely to have had a dental visit within the previous year. Consistent with earlier findings, participants who reported racial discrimination were 20% less likely to have visited a dentist in the last year compared to those who had not [30]. This aligns with the results of Singhal & Jackson, who found that those who experienced racial discrimination in healthcare settings were 15% less likely to visit a dentist [28]. This study highlights how perceived discrimination can deter individuals from seeking necessary dental care, leading to disparities among racial and ethnic groups [28]. It is important to mention that in the current study, participants were asked about racial discrimination experienced during their lifetime, and not specifically within healthcare settings. The context of perceived discrimination may vary, and it is essential to investigate the timing, patterns, and severity of these experiences to fully understand their impact on oral health outcomes.

The association between racial discrimination and poor oral health outcomes points to the need for policies that address systemic racism within healthcare systems. In recent years, dental schools across the U.S. have incorporated mandatory cultural competency and implicit bias training to reduce racial disparities in oral healthcare. For instance, a study aimed to evaluate the effectiveness of the cultural competency curriculum at Boston University Henry M. Goldman School of Dental Medicine (GSDM) concluded that implementation of a cultural competency curriculum significantly improved dental students' awareness, knowledge, and skills related to providing care to diverse populations including minorities [38]. Additionally, programs like the National Health Service Corps aim to diversify the dental workforce by offering loan repayment incentives for minority dentists working in underserved communities, improving the representation of minority groups in oral healthcare settings [39]. These policies help reduce discriminatory practices and improve access to dental care for underrepresented populations.

Our finding that transportation is a significant barrier to dental care is also consistent with other research on older adults by Marchini and colleagues [25]. However, those authors found an association between two predictor variables—needing assistance with housekeeping and transportation— which could indicate that older adults' lack of social support and their difficulty accessing public transportation could be partially due to age-related factors. In the current study, we included adults aged 18 and above, so stratifying by age group would be important to assess whether transportation remains a barrier across all age groups. Meanwhile, McKernan and colleagues found that the median distance to the nearest dentist was not significantly associated with having had a dental visit among Medicaid-insured adults [26]. However, transportation barriers in particular, using public transportation and cost, were associated with lower odds of having dental visits [26]. Transportation barriers are multifaceted and need further investigation from a public health standpoint to effectively intervene and allocate resources. We found lower odds of dental visits for respondents who reported housing instability, which is consistent with the results of Maxwell and colleagues who found that public housing residents (as a proxy for housing instability) had significantly lower odds of having been to the dentist in the past year for any reason and also lower odds of having had their teeth cleaned in the past year [27]. However, in the adjusted analyses, this association became nonsignificant, suggesting that other factors may mediate the association between housing instability and dental visits [27].

Our finding that transportation barriers and housing instability are associated with reduced dental visits highlights the importance of integrating oral health into public health strategies. For instance, public health initiatives could focus on expanding mobile dental clinics or providing transportation vouchers to reduce barriers to dental care, particularly for vulnerable populations such as the elderly, rural populations, or those experiencing housing instability [40]. For example, the Delta Dental Mobile Program provides dental services to rural children throughout South Dakota [41, 42]. Similarly, housing programs that integrate healthcare services, such as the Boston REACH: Partners in Health and Housing, have demonstrated how incorporating oral health services into public housing programs can improve outcomes for residents by addressing both healthcare and housing-related barriers [43, 44].

Our analysis showed no significant interaction effects between adults reporting intermediary determinants and structural determinants for having a dental visit within the last year, which is inconsistent with the results of Singhal & Jackson who found that racial discrimination partially mediates the racial-ethnic disparities for dental visits among particular groups such as Hispanics [28].

Adults who experienced any of the SDOHs, except for race/ethnicity, were significantly less likely to report positive oral health. Food insecurity was associated with a 30% lower likelihood of reporting positive oral health. This finding is consistent with research that identifies food insecurity as the most robust correlate of poor self-reported oral health in a non-gender-stratified model [19]. However, Chi and colleagues recruited older adults who received government food stamps, which could mediate the association between food insecurity and self-reported oral health [19]. From a sociological perspective, food insecurity may impact self-reported oral health through social inequality and stigma [45]. Affected individuals may face disadvantages like limited access to nutritious food and increased stress, which contribute to poor oral health [45]. The stigma surrounding food insecurity can also lead to social exclusion and reduced use of dental services due to embarrassment or perceived discrimination. For instance, the University of Florida HealthStreet launched initiatives addressing food insecurity and oral health, including the HOPE Food Pantry and the Saving Smiles Program [46]. These programs provide nutritious food and free dental care, helping to reduce stigma and improve oral health [46]. This highlights the need for interventions that address not only the material aspects of food insecurity but also the social and psychological barriers that prevent individuals from seeking care.

Housing instability was similarly linked to poor oral health, with adults experiencing housing issues being 29% less likely to report positive oral health. Our findings are in line with those of Wallace and colleagues, who found that individuals experiencing homelessness or living in publicly supported housing were more likely to report poor oral health [31]. Our results also showed that Black adults who reported racial discrimination were 44% less likely than White adults to report positive oral health. We also found interaction effects between structural determinants, such as race/ethnicity, and intermediary determinants for self-reported oral health. Black individuals and adults who reported lack of transportation, food insecurity, and housing instability were more likely to report being self-conscious or embarrassed due to their oral health. These results are consistent with previous findings [23, 24, 47]. Black adults, and adults with some college education or higher, were less likely to report being embarrassed due to their oral health, consistent with the results of the study by Bedos and colleagues [23]. According to the findings of this qualitative study, people on social assistance have poor oral health and are self-aware of the progressive decline of their dental appearance. Our analysis showed no significant interaction effects between intermediary determinants and structural determinants for feeling self-conscious or embarrassed due to oral health.

Finally, adults who experienced any SDOHs were significantly more likely to have had at least one tooth removed. Black adults were 67% more likely than White adults to experience tooth loss, a finding confirmed by Nazer and colleagues [15]. Adults with some college or more and annual household incomes of $60,000 or more were less likely to have tooth loss than individuals with less than high school and those with an annual household income of less than $30,000. This finding is similar to the results of Gilbert and colleagues, who found that race and socioeconomic status are strong determinants of tooth loss [48]. There were interaction effects between intermediary and structural determinants for tooth loss. We found that among individuals experiencing racial discrimination, the odds of having one or more teeth removed were higher for Black adults than White adults which is consistent with the results of Singhal & Jackson [28]. Their study found that among participants who experienced racial discrimination, non-Hispanic Black adults were 36% more likely to have tooth loss relative to non-Hispanic White adults with similar risk factors [28]. Perceived discrimination appears to partially mediate the racial-ethnic disparities in dental utilization. However, Black adults were more likely to have tooth loss regardless of having reported any of the intermediary determinants. Interestingly, among adults reporting a lack of transportation, the odds of having one or more teeth removed were less for Hispanic adults than White adults.

The observed disparities highlight the need for targeted policies to address the structural determinants of oral health inequality. Expanding access to affordable dental care, improving transportation, and addressing food insecurity and housing instability are essential for racial/ethnic minorities and those facing socioeconomic challenges. For instance, expanding programs like Medicaid to low-income adults has been shown to increase access to dental care and improve oral health among low income and minority populations [41, 49]. Additionally, policies should aim to reduce systemic racism in healthcare and integrate oral health into broader social welfare programs to mitigate the impact of these disadvantages and reduce self-consciousness about dental appearance.

Our findings align with previous comparative research on the association of oral health and different social determinants of oral health. Generally, adults who reported experiencing any SDOH were more likely to have poor oral health outcomes. Our effects modification analysis does not find that the intermediary determinants mediate the structural determinants nor, with few exceptions, do we find a strong compounding effect of the intermediary determinants on the structural determinants. Instead, we found differences in degree, where intermediary determinants do not modify the direction, but rather the magnitude, of the structural determinants.

This study had some limitations. First, this cross-sectional study allowed us to examine associations but not causation, and temporal associations could not be determined. Second, data collected in this survey was self-reported with its inherent biases (recall, reporting, and social desirability). Third, this study does not assess the combined effects of SDOH on oral health outcomes, nor does it address for the mediating effects between structural and intermediary determinants. Despite these limitations, this study highlights associations between different oral health outcomes and SDOH at the population level using nationally representative data, allowing us to perform robust analyses.

To our knowledge, this is the first study to measure the association of different oral health-related outcomes with different SDOH. Our findings could help policymakers focus efforts or target populations affected by these SDOHs. Our findings highlight the complex relationship between SDOH and oral health outcomes. Future research should explore these intersections further, identifying key SDOH impacting vulnerable populations, and developing targeted strategies and policies to address these issues effectively. Additionally, conducting longitudinal studies will help clarify the causal relationships between SDOH and oral health outcomes, providing valuable insights for developing targeted interventions.

Authors' contributions

RO contributed to the conceptualization of the study and contributed to drafting the manuscript. LH contributed to drafting the manuscript. ET contributed to the conceptualization of the study and the acquisition and interpretation of data. JO contributed to the analysis and interpretation of data. PT contributed to the conceptualization of the study and contributed to drafting the manuscript. All authors reviewed the manuscript.

Authors' information

Not applicable.

Funding

Not applicable.

Data availability

The dataset used and analyzed during this study is available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

This study protocol was reviewed and determined to be exempt by the Western Institutional Review Board (WIRB). When contacted by an AmeriSpeak® staff member and before taking part in the survey, adults invited to participate in the survey were provided with information about the survey and asked to provide their informed consent to participate, either online (for those completing the survey online) or verbally (for those completing the survey by telephone).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.