Depression Symptoms Linked to Multiple Oral Health Outcomes in US Adults

Abstract

Background:

Individuals with mental illness have poor oral health compared to those without mental health conditions. However, the literature is still lacking regarding the specifics of this relationship.

Objective:

This study aims at examining the relationship between depression and oral health problems such as oral conditions, access to dental care, and oral hygiene measures.

Methods:

A cross-sectional study using a secondary data analysis of 9,693 participants from the 2017 to March 2020 prepandemic National Health and Nutrition Examination Survey (NHANES). The independent variable was severity of depressive symptoms as measured by the Patient Health Questionnaire–9 (PHQ-9). Proportional odds and binary logistic regression were used to calculate crude and adjusted odds ratios (AORs) between depression and 8 oral health outcomes and oral hygiene–related behaviors.

Results:

After adjusting for sociodemographics, health conditions, and behaviors, individuals with depression were significantly more likely to have dental aches in the past year (AOR = 1.70; 95% confidence interval [CI], 1.13–2.56), difficulty getting dental care when needed (AOR = 1.93; 95% CI, 1.45–2.58), and difficulty at their jobs due to a problem in their mouth (AOR = 1.63; 95% CI, 1.07–2.49) compared to individuals without depression.

Conclusion:

Individuals with depressive symptoms often neglect oral hygiene and self-care practices and are less likely to seek medical care for oral health problems, making them at increased risk of poor oral health outcomes. These findings can be applied by dentists, psychologists, and therapists to increase awareness of links between depression and oral health and to encourage patients with depression to seek oral hygiene preventative care.

Knowledge Transfer Statement:

Health care professionals can be on the frontline in creating awareness in the general public about the links between depression and oral health and hygiene. Applying the findings from this study can help communicate about the relationship between depression and poor oral health and relieve some burden on the American health care sector, which often struggles to provide medical care to patients with depression and oral health issues.

Introduction

People with mental illnesses are at a higher risk of worse oral health compared to those without mental health conditions (Scrine et al. 2018). Recent studies have found a link between depression and oral diseases such as gum disease, periodontal disease, and dental caries, but there are limited data available (Kisely et al. 2011; Cademartori et al. 2018; Aldosari et al. 2020). Depression has been suggested to be associated with periodontitis (Dumitrescu 2016), an inflammatory condition caused by bacteria (Tonetti et al. 2018), which results in the deterioration of the supportive anatomical structures for the teeth, including bone loss (Barbato et al. 2015) and, ultimately, the loss of teeth. People with depression often experience reduced motivation and energy, which may make them neglect crucial oral hygiene procedures (Mohammadi et al. 2019). Furthermore, people exhibiting depressive symptoms may avoid necessary dental care, which also leads to an increased risk of dental problems (Mohammadi et al. 2019). Many studies show that people who struggle with mental health issues such as depression often turn to overeating or binge eating to relieve depressive symptoms (Mills et al. 2020; Fulton et al. 2022), often turning to foods containing large amounts of sugar, which are associated with the development of tooth decay (Skośkiewicz-Malinowska et al. 2018; Laniado et al. 2020). Additionally, individuals who experience mood disorders such as depression are more likely to smoke or use alcohol, further compromising oral health (Boschloo et al. 2013). These conditions, if left untreated, can result in tooth loss (Okoro et al. 2012) and cost the United States more than $45 billion in lost productivity yearly (Righolt et al. 2018).

Multiple studies have yielded consistent results concerning the relationship between depression, oral health behaviors, and the treatment of dental conditions like periodontal disease. Some prior studies modeled depression as an outcome (O’Neil et al. 2014; Takiguchi et al. 2016), raising a question about the direction of the causal relationship. There is a substantial literature suggesting that depression does, indeed, affect oral health. The presence of depressive symptoms like anhedonia, reduced motivation, feelings of worthlessness, and fatigue can have a detrimental impact on the oral hygiene maintenance behaviors of adults (Anttila et al. 2006; Rosania et al. 2009; Okoro et al. 2012). Some hypothesize that the link between depression and oral illness may be caused by diminished salivary response due to depression symptoms and depression drugs, both of which reduce salivary flow, increasing the risk of developing tooth decay and periodontal disease (Gholami et al. 2017). Common signs of depression include increased fatigue, isolation, reduced interest in activities an individual initially engaged in, reduced concentration and focus, disrupted sleep patterns, and poor diet and lifestyle, among others (World Health Organization 2022). With increased mood changes, patients with depressive symptoms often neglect self-care activities, including those related to oral health, such as brushing teeth, using dental floss, and seeking dentist services (Mohammadi et al. 2019; Almohaimeed et al. 2022). To cope with depression, an individual can turn to poor healthy lifestyles such as smoking, drinking, poor diet, and poor physical health and hygiene, among others, leading to poor health conditions. Having a poor diet can damage teeth, causing oral problems such as tooth decay and cavities, eventually resulting in tooth loss (Laniado et al. 2020). Alternatively, suffering from dental pain can have a negative impact on one’s quality of life and mental well-being. An increased risk of dental decay and tooth loss can result in more frequent experiences of pain, social isolation, and diminished self-esteem, which can lead to a lower quality of life, which may be associated with worse mental and overall health (Gift and Atchison 1995). Finding relief from this pain plays a vital role in improving overall quality of life (Yang et al. 2016). These research findings emphasize the broader public health significance of the connection between mental health and oral health outcomes, illustrating a potential cycle where oral health influences mental health and vice versa (Tiwari et al. 2022).

While many studies have focused on the relationship between depression and oral diseases, few studies have been conducted on depression in relation to other oral health outcomes, such as general oral condition, dental hygiene, and dental visits. This presents a gap in research and demonstrates a need to assess how depression affects other crucial oral health outcomes. This study will investigate the relationship between depression and 8 oral health outcomes.

Methods

The data used for this cross-sectional analysis come from the 2017 to March 2020 prepandemic National Health and Nutrition Examination Survey (NHANES). NHANES is a nationally representative, stratified multistage probability sample of the civilian noninstitutionalized population in the United States (Chen et al. 2020). NHANES field activities paused in March 2020 due to COVID-19, leaving an incomplete 2019–2020 cycle. Data gathered from 2019 to March 2020 were joined with data from the NHANES 2017–2018 cycle to generate a nationally representative sample of NHANES 2017 to March 2020 prepandemic data. Weighting and an adjustment factor for incomplete data collection were applied to participant base weights to balance the contribution of each stratum to the entire survey sample. The 2017 to March 2020 prepandemic NHANES survey included 15,560 respondents. More details about the survey methodology are available elsewhere (Chen et al. 2020).

While there is strong theoretical and empirical evidence for bidirectional effects between depression and oral health, there is substantially more evidence supporting the effect of depression on oral health (Anttila et al. 2006; Rosania et al. 2009; Okoro et al. 2012; Dumitrescu 2016; Mohammadi et al. 2019; Mills et al. 2020; Tiwari et al. 2022). Thus, we model these relationships using oral health as the outcome and depression as the primary independent variable. Given the cross-sectional design of NHANES, care should be taken to interpret these relationships as associational and indicative of higher risks rather than purely causal effects of depression on oral health. The causal diagram provided in Appendix Figure 1 guided covariate and analytical choices.

Outcome: Oral Health Outcomes

We used participants’ responses to 8 oral health outcomes and oral hygiene–related behaviors: self-report oral condition, dental ache, last dental visit timing, gum disease, dental bone loss, dental care inaccessibility, dental flossing, and difficulty with jobs. The responses for self-report oral condition, dental ache, and difficulty with jobs were on a 5-point scale; responses for last dental visit timing were on a 7-point scale; responses for dental flossing were numeric, ranging from 0 to 9; and responses for gum disease, dental bone loss, and dental care inaccessibility were binary. We categorized last dental visit timing into 3 levels and dichotomized difficulty with jobs and dental floss into binary outcomes, as shown in Table 1.

Table 1.

Description of Oral Health Outcome and Behavior Recording.

Variable	Question	NHANES Response	Recoded Response
Self-report oral condition	“Overall, how would you rate the health of your teeth and gums?”	• Excellent • Very good • Good • Fair • Poor
Dental ache	“How often last year had aching in mouth?”	• Very often • Fairly often • Occasionally • Hardly ever • Never
Last dental visit timing	“About how long has it been since you last visited a dentist? Include all types of dentists, such as orthodontists, oral surgeons, and all other dental specialists, as well as dental hygienists.”	• 6 mo or less • More than 6 mo but not more than 1 y ago • More than 1 y but not more than 2 y ago • More than 2 y but not more than 3 y ago • More than 3 y but not more than 5 y ago • More than 5 y ago • Never have been	• Less than 1 y • 1–3 y • 3+ y
Gum disease	“Do you think you might have gum disease?”	• No • Yes
Dental bone loss	“Ever been told of bone loss around teeth?”	• No • Yes
Dental care inaccessibility	“During the past 12 months, was there a time when you needed dental care but could not get it at that time?”	• No • Yes
Difficulty with jobs	“How often during the last year have you had difficulty doing your usual jobs or attending school because of problems with your teeth, mouth or dentures?”	• Very often • Fairly often • Occasionally • Hardly ever • Never	• Yes (including everyone except those who answered never) • Never
Dental floss	“Aside from brushing your teeth with a toothbrush, in the last seven days, how many days did you use dental floss or any other device to clean between your teeth?”	• Ranged from 0 to 9	• No • Yes (any number of times)

Independent Variable: Depression

Depression was assessed using the Patient Health Questionnaire–9 (PHQ-9). The PHQ-9 is a self-report questionnaire with 9 items designed for use in medical settings to evaluate the severity of depressive symptoms based on criteria from the DSM-IV guidelines (Spitzer et al. 1999; Kroenke et al. 2001). Respondents indicate the presence of each of 9 symptoms during the previous 2 wk with responses assigned a numerical value: 0 for “not at all,” 1 for “several days,” 2 for “more than half the days,” and 3 for “nearly every day.” The 9 responses sum to a total PHQ-9 score ranging from 0 to 27, with higher scores indicating more severe depression symptoms. Internal consistency of the PHQ-9 items was assessed via Cronbach’s α. We used a cutoff of ≥10 points to indicate depression because it has been shown to have a sensitivity of 88% and a specificity of 88% for severe depression (Kroenke et al. 2001).

Covariates

Several sociodemographic characteristics, health conditions, and health behaviors were included as covariates in multivariable analyses based on a review of the scientific literature (Appendix Fig. 1). Sociodemographic characteristics included age, sex, race, education level, marital status, and family monthly poverty level index. Age was a numeric variable top-coded at 80 y. Sex was a binary variable with options male and female. Race was recoded into non-Hispanic White, non-Hispanic Black, Hispanic, and other races. Education level for people of age 20 y and above was on a 5-point scale as follows: less than grade 9, grades 9 to 11 (includes grade 12 with no diploma), high school graduate/general equivalency diploma (GED) or equivalent, some college or associate’s degree, and college graduate or above, aligned with common practice in the US Census Bureau and NHANES. Marital status was recoded into 2 groups: married/living with a partner and divorced/separated/widowed/never married. Family income relative to poverty level was categorized using the ratio of monthly family income to the Department of Health and Human Services poverty guidelines specific to family size as follows: monthly poverty level index ≤ 1.30, 1.30 < monthly poverty level index ≤ 1.85, 1.85 < monthly poverty level index ≤ 3.5, and monthly poverty level index > 3.5. These categories were selected to correspond to frequently employed percentages (specifically, 130% and 185% of the guidelines) that federal programs often use to determine eligibility, and the cutoff of 3.5 was chosen to have similar frequencies in the 2 final categories (Centers for Disease Control and Prevention 2021).

Health conditions used as covariates included general health status and diabetes. General health was measured using self-reported answers to the question, “Would you say your health in general is . . . ?” with 5 response options: excellent, very good, good, fair, and poor. Diabetes was measured using self-reported answers to the following question: “Have you ever been told by a doctor or other health professional that you had diabetes or sugar diabetes?” and was categorized into yes and no (including borderline).

Health behaviors that affect oral health and were used as covariates included overall healthy diet, smoking, and alcohol use. Participants were asked, “In general, how healthy is your overall diet?” with 5 response options: excellent, very good, good, fair, and poor. We recoded responses into excellent/very good, good, and fair/poor to have similar frequencies of responses. Respondents were defined as smokers if they reported having smoked 100 cigarettes in their lifetime and currently smoking “everyday” or “some days.” For alcohol use, the participants were asked, “During the past 12 months, about how often did you drink any type of alcoholic beverage?” The 10 possible response were recorded into 6 categories: never in their life, never in the last year, 1 to 11 times in the last year, 1 to 3 times a month, 1 to 4 times a week, and daily.

Statistical Analysis

The study included all eligible adult participants aged 18 y and above, totaling 9,693 respondents. A total of 4,516 respondents were missing information on at least one of family monthly poverty level (n = 2,178), gum disease (n = 1,935), dental bone loss (n = 1,905), difficulty with jobs (n = 1,843), dental ache (n = 1,842), dental flossing (n = 1,840), depression (n = 1,398), alcohol use (n = 1,327), education level (n = 476), marital status (n = 471), dental care inaccessible (n = 183), last dental visits timing (n = 34), general health (n = 10), self-report oral condition (n = 9), diabetes (n = 5), overall healthy diet (n = 5), and smoking (n = 5), with 5,177 respondents having complete data in the variables of interest. A more detailed analysis of the missing data is available in Appendix Figure 2 and Appendix Table 1.

Descriptive statistics are reported as unweighted counts and percentages. Chi-squared tests for categorical variables and the t test for age were used to identify significant relationships between sociodemographics, health conditions, behaviors, and oral health outcomes and depression. Prior to modeling, multiple imputation with chained equations (MICE) was used to create 5 complete data sets (White et al. 2011). MICE allows imputation of multivariate missing data by iteratively imputing individual variables using predictive models (e.g., binary or multinomial logistic regression). Multiple imputation mitigates bias incurred from dropping observations with missing data and recovers some of the information lost when dropping records, while accounting for uncertainty in imputations by incorporating variation across imputations into parameter estimate precision (White et al. 2011). Within each data set, the NHANES design was considered by incorporating sampling strata, clusters, and weights.

Proportional odds regression was conducted to investigate the relationship between depression and the 3 ordinal oral health outcomes of self-report oral condition, dental ache, and last dental visit timing. Binary logistic regression models were conducted to investigate the relationship between depression and the 5 binary oral health outcomes of gum disease, dental bone loss, dental care inaccessibility, dental floss frequency, and difficulty with jobs. The unadjusted models include only depression status as predictor for each oral health outcome, while the adjusted models include the sociodemographics, health conditions, and behaviors described above. While adjusting for health behavior mediators in the regression models biases estimates of the total relationship between depression and the oral health outcomes, the depression coefficients can be interpreted as the unique relationship between depression and oral health outcomes unaccounted for by the indirect paths through health behaviors. Since the influence of diet, smoking, and alcohol use is already well known among oral health professionals and health professionals more generally, highlighting the unique contribution of depression outside of these pathways is an important contribution. Results from the imputed analyses were combined using Rubin’s rules (Little and Rubin 2019).

Results from hypothesis tests were adjusted for multiple comparisons using Bonferroni corrections. For all models, odds ratios (ORs) and 99.4% confidence intervals (CIs) are reported. Bonferroni-corrected P < 0.05 was used throughout the analysis to indicate statistical significance. All analyses were performed in R version 4.1.1, using the mice package for imputation and pooling (van Buuren and Groothuis-Oudshoorn 2011), and the survey package version 4.1-1 (Lumley 2004) to handle the NHANES complex sampling design. This study complies with Strengthening the Reporting of Observational Studies in Epidemiology statement guidelines.

Results

Cronbach’s α for the PHQ-9 items was 0.84 (95% CI, 0.836–0.846), indicating strong internal consistency in this sample. After summing the PHQ-9 items, 586 (9%) respondents had a score of 10 or above and were classified as expressing depressive symptoms.

Table 2 shows the descriptive results of sociodemographics, health conditions, behaviors, and oral health outcomes within depression categories. The sociodemographic characteristics show that sex, education level, marital status, and family income were significantly associated with depression. Females were more likely to be depressed than males. Individuals with some college or AA degree were more likely to be depressed than any other education level. Individuals who were widowed, divorced, separated, or never married were more likely to be depressed than individuals who were married or living with a partner. Individuals with family income less than 1.30 times the federal poverty level had higher prevalence of depression than individuals with higher family incomes. Both general health and diabetes were significantly associated with depression. Individuals with successively worse general health were more likely to be depressed, while individuals with diabetes were more likely to be depressed than individuals without diabetes. Individuals who reported having fair or poor overall healthy diet were more likely to be depressed than individuals who reported having better overall healthy diet. Smoking was associated with increased risk of depression, while alcohol use was associated with depression but without a clear trend. Depression was associated with worse results for all oral health outcomes and behaviors considered.

Table 2.

Distribution of Selected Sociodemographics, Health Characteristics, and Risk Behaviors among US Adults Aged 18 and Above by Depression Status, NHANES 2017 to March 2020 (n = 5,177).

Characteristic	Without Depression	With Depression	Total	P Value a
N	4,713	464	5,177
Sociodemographics
Age, mean (SD), y	55.5 (14.7)	54.9 (14.0)	55.47 (14.6)	0.344
Sex (female)	2,345 (49.8)	289 (62.3)	2,634 (50.9)	<0.001
Race				0.237
Non-Hispanic White	1,874 (39.8)	199 (42.9)	2,073 (40.0)
Non-Hispanic Black	1,209 (25.7)	108 (23.3)	1,317 (25.4)
Hispanic	906 (19.2)	97 (20.9)	1,003 (19.4)
Other races	724 (15.4)	60 (12.9)	784 (15.1)
Education				<0.001
Less than grade 9	290 (6.2)	37 (8.0)	327 (6.3)
Grades 9–11b	468 (9.9)	72 (15.5)	540 (10.4)
High school graduate/GED or equivalent	1,078 (22.9)	124 (26.7)	1,202 (23.2)
Some college or AA degree	1,557 (33.0)	168 (36.2)	1,725 (33.3)
College graduate or above	1,320 (28.0)	63 (13.6)	1,383 (26.7)
Marital status = widowed/divorced/separated/never married	1,749 (37.1)	255 (55.0)	2,004 (38.7)	<0.001
Family income relative to poverty level				<0.001
Monthly poverty level index ≤ 1.30	1,334 (28.3)	210 (45.3)	1,544 (29.8)
1.30 < Monthly poverty level index ≤ 1.85	696 (14.8)	89 (19.2)	785 (15.2)
1.85 < Monthly poverty level index ≤ 3.5	1,265 (26.8)	94 (20.3)	1,359 (26.3)
Monthly poverty level index > 3.5	1,418 (30.1)	71 (15.3)	1,489 (28.8)
Health conditions
General health				<0.001
Excellent	536 (11.4)	12 (2.6)	548 (10.6)
Very good	1,346 (28.6)	39 (8.4)	1,385 (26.8)
Good	1,797 (38.1)	143 (30.8)	1,940 (37.5)
Fair	894 (19.0)	186 (40.1)	1,080 (20.9)
Poor	140 (3.0)	84 (18.1)	224 (4.3)
Diabetes = yes	804 (17.1)	117 (25.2)	921 (17.8)	<0.001
Behaviors
Overall healthy diet				<0.001
Excellent/very good	1,435 (30.4)	74 (15.9)	1,509 (29.1)
Good	1,892 (40.1)	138 (29.7)	2,030 (39.2)
Fair/poor	1,386 (29.4)	252 (54.3)	1,638 (31.6)
Smoking = yes	800 (17.0)	137 (29.5)	937 (18.1)	<0.001
Alcohol use				<0.001
Never in their life	389 (8.3)	24 (5.2)	413 (8.0)
Never in the last year	1,015 (21.5)	133 (28.7)	1,148 (22.2)
1 to 11 times in the last year	1,119 (23.7)	134 (28.9)	1,253 (24.2)
1 to 3 times a month	863 (18.3)	68 (14.7)	931 (18.0)
1 to 4 times a week	976 (20.7)	73 (15.7)	1,049 (20.3)
Daily	351 (7.4)	32 (6.9)	383 (7.4)
Oral health outcomes
Self-report oral condition = fair/poor				<0.001
Excellent	534 (11.3)	23 (5.0)	557 (10.8)
Very good	1,115 (23.7)	48 (10.3)	1,163 (22.5)
Good	1,556 (33.0)	113 (24.4)	1,669 (32.2)
Fair	1,054 (22.4)	158 (34.1)	1,212 (23.4)
Poor	454 (9.6)	122 (26.3)	576 (11.1)
Dental ache				<0.001
Never	2,024 (42.9)	99 (21.3)	2,123 (41.0)
Hardly ever	1,517 (32.2)	141 (30.4)	1,658 (32.0)
Occasionally	846 (18.0)	119 (25.6)	965 (18.6)
Fairly often	209 (4.4)	50 (10.8)	259 (5.0)
Very often	117 (2.5)	55 (11.9)	172 (3.3)
Last dental visit over 1 y				<0.001
Less than 1 y	2,622 (55.6)	217 (46.8)	2,839 (54.8)
1–3 y	993 (21.1)	106 (22.8)	1,099 (21.2)
3+ y	1,098 (23.3)	141 (30.4)	1,239 (23.9)
Gum disease = yes	885 (18.8)	167 (36.0)	1,052 (20.3)	<0.001
Dental bone loss = yes	617 (13.1)	146 (31.5)	763 (14.7)	<0.001
Dental care inaccessibility = yes	794 (16.8)	118 (25.4)	912 (17.6)	<0.001
Difficulty with jobs = yes	3,284 (69.7)	267 (57.5)	3,551 (68.6)	<0.001
Dental floss = yes	914 (19.4)	207 (44.6)	1,121 (21.7)	<0.001

Values are presented as number (%) unless otherwise indiacted.

AA, associate of arts; GED, general equivalency diploma.

^aP value based upon t test for continuous variable (age) and χ² test for categorical variables.

^bIncludes grade 12 with no diploma.

The unadjusted models provide crude odds ratios between depression and oral health outcomes and related oral hygiene behavior (Table 3). Depression is associated with higher odds of all 7 poor outcomes and decreased odds of dental flossing.

Table 3.

Unadjusted and Adjusted Odds Ratios from Proportional Odds (Cumulative Logit) and Binary Logistic Regression for Each of the Oral Health Outcomes by Depression Status.

Oral Health Outcomes	Depression Status a
	Unadjusted OR (95% CI)	Adjusted b OR (95% CI)
Proportional odds regression
Self-report oral condition c	2.51 (1.74–3.61) d	1.32 (0.93–1.88)
Dental ache e	2.29 (1.50–3.50) d	1.70 (1.13–2.56) d
Last dentist visit timing f	1.54 (1.23–1.93) d	1.06 (0.83–1.35)
Binary Logistic regression
Gum disease g	1.83 (1.25–2.69) d	1.30 (0.88–1.93)
Dental bone loss g	1.52 (1.01–2.27) d	1.48 (0.93–2.36)
Dental care inaccessibility g	3.09 (2.25–4.22) d	1.93 (1.45–2.58) d
Difficulty with jobs g	2.40 (1.56–3.68) d	1.63 (1.07–2.49) d
Dental floss g	0.61 (0.44–0.81) d	0.83 (0.58–1.19)

CI, confidence interval; OR, odds ratio.

^aReference group is without depression.

^bAfter adjusting for sociodemographics, health conditions, and behaviors.

^cReference group is excellent.

^dBonferroni-corrected P < 0.05.

^eReference group is never.

^fReference group is less than 1 y.

^gReference group is no.

After adjusting for covariates, depression remained associated with worse oral health outcomes, although 5 of the 8 were not statistically significant after multiple comparisons adjustment (Table 3). Individuals with depression were significantly more likely to report having dental aches in the last year (AOR = 1.70), difficulty with dental care accessibility (AOR = 1.93), and difficulty at their jobs due to a problem in their mouth (AOR = 1.63) compared to individuals without depression. Nonsignificant associations included self-report oral condition (AOR = 1.32), last dentist visit timing (AOR = 1.06), gum disease (AOR = 1.30), dental bone loss (AOR = 1.48), and use of dental floss (AOR = 0.83). Full multivariable model results are available in Appendix Tables 2 to 9. Among the covariates included in this analysis, education, family income, general health status, and smoking consistently had stronger relationships with the outcomes than did depression. The strength of association between depression and the outcomes was on the order or characteristics such as race and diet.

Discussion

This study confirms and expands upon what we know about the relationship between depression and oral health outcomes. Depression was significantly associated with increased risk of dental aches, decreased access to dental care when needed, and increased risk of difficulties with their job due to their mouth condition, with respondents with depression having over 60% increased odds of reporting each of these outcomes relative to those without depression, after adjustment for covariates. Findings did not result in statistically significant associations between depression and self-report oral condition, visiting a dentist for any reason, gum disease and dental bone loss, and using dental floss for oral hygiene, although the direction of the observed associations suggested worse outcomes in these metrics as well.

Many studies document the association between depression and oral health outcomes (Hassel et al. 2011; Hugo et al. 2012; Okoro et al. 2012; O’Neil et al. 2014; Park et al. 2014; Silveira et al. 2016; Takiguchi et al. 2016; Cademartori et al. 2018; Almohaimeed et al. 2022), some internationally (Hugo et al. 2012; Park et al. 2014; Takiguchi et al. 2016) or limited to older populations (Hugo et al. 2012; Okoro et al. 2012; Takiguchi et al. 2016). Our findings are consistent with these studies. Additionally, many studies did not adjust for potential confounders such as family income, diet, general health, and alcohol use (Hassel et al. 2011; Hugo et al. 2012; Park et al. 2014). This study provides a more comprehensive picture of the subject. For example, while patients with depression may generally be keeping their dental health appointments—the association was one of the weakest found—their behaviors, daily activities, and lack of attentiveness to oral health may still be leading to poor health outcomes like gum disease. These outcomes can further affect their confidence and performance while they do their jobs or interact with other people.

This study comprised a large general population sample and up-to-date data, using a nationally representative data set. Also, a validated questionnaire (PHQ-9) was used to assess depressive symptoms. However, there are limitations. First, this study used cross-sectional data, which restricted our ability to measure the directionality between depression and oral health outcomes. Without directionality, we can only interpret results as associations and not causal effects. However, the results show the presence of depression indicates higher risk of poor oral health and poor oral health indicates higher risk of depression, both of which are useful relationships for practicing health professionals. Our study is also challenged by selection bias, undercoverage, and noncoverage; nevertheless, the weighting and complex survey methods used by NHANES aid in addressing this issue (Chen et al. 2020). In addition, NHANES records self-reported oral and general health outcomes and behaviors, sometimes over time frames as long as a year or more. This opens the possibility for recall bias, especially for the longer-term timeframes. NHANES data were also liable to item nonresponse on information of interest. Multiple imputation was performed to account for the missing data, reducing the bias occurring because of data not missing completely at random and allows all available data to be used to its fullest extent, mitigating reductions in reduced sample size and statistical power. Potential confounding variables were not used because of unavailability (e.g., neighborhood) or substantial missing data that prevented inclusion (e.g., physical activity). Most of the questions were general, like: “Aside from brushing your teeth with a toothbrush, in the last seven days, how many days did you use dental floss or any other device to clean between your teeth?” More focused data collection is needed to better understand the impact of dental care practice.

There is a growing recognition of the importance of the connection between oral health and overall health, including mental health (Kisely et al. 2011; Cademartori et al. 2018; Tiwari et al. 2022). Furthermore, there is a crucial need to prioritize preventive dentistry, as individuals with mental health issues may be at higher risk for dental issues (Kisely et al. 2011; Cademartori et al. 2018). While dentists may not conduct formal depression screenings, they can play a role in identifying potential signs of depression or referring patients to mental health professionals when appropriate. Numerous screening tools have been devised for implementation in primary care settings (Gilbody et al. 2005). Among these, the 2-question version of the PHQ (PHQ-2) stands out as one of the simplest yet effective tools that busy dentists or general practitioners can incorporate into their toolkit (Kroenke et al. 2001). The questions involve little interest or pleasure in doing things (0–3) and feeling down, depressed, or hopeless (0–3), where a total score of ≥3 exhibited a sensitivity of 83% and a specificity of 92% in diagnosing major depression (Kroenke et al. 2001). The dentist can seamlessly integrate these 2 questions into a patient interview and, in collaboration with the patient, suggest the need for further evaluation either with their primary care physician or a mental health specialist (Hexem et al. 2014). Preventive programs should be developed and customized in collaboration with multidisciplinary teams to address the specific requirements of clients with varying diagnoses, prognoses, severity levels, and stages of mental illness. Special emphasis should be placed on sustaining periodontal health through the promotion of efficient oral hygiene practices. It is important for health care professionals to communicate and coordinate care effectively when making referrals to other specialists, including dentists. Patients may benefit from a multidisciplinary team approach that addresses both their physical and mental health needs.

Conclusion

This study contributes to existing research on the relationship between depression and oral health, both significant public health issues affecting quality of life. Health care professionals, like dentists, psychologists, and therapists, can play a pivotal role in raising awareness about this link, encouraging care for depressed patients to prevent oral problems. Dentists, with awareness of a patient’s depression, can provide targeted oral health attention, potentially aiding early intervention. Future research should consider incorporating objective diagnosis of depression and oral health conditions, more precise and detailed questions about oral health problems and behaviors—such as reasons for difficulties doing jobs—and cohort studies to help illuminate the magnitude of the potential bidirectional effects between depression and poor oral health.

Author Contributions

F. Bafageeh, contributed to conception, design, data analysis and interpretation, drafted the manuscript; T. Loux, contributed to conception, design, data interpretation, critically revised the manuscript. All authors have their final approval and agree to be accountable for all aspects of work.