Abstract
Background
Social factors affect oral health status, and poor oral health has been associated with worse health outcomes. Using the Oral Health Risk Assessment Value Index (OHRAVI), a bedside tool for non-dentists to assess oral health, we investigated the interplay of oral health with social drivers of health and social vulnerability, as measured by the Social Vulnerability Index (SVI), in severely injured patients.
Methods
Our retrospective study included dentulous critically ill trauma patients who were previously assigned an OHRAVI score (range 0–3; unhealthy score >1). Patient demographics, comorbidities, and self-reported social drivers were obtained from health records. SVI was calculated using census-tract data. Bayesian regression analyses were performed to calculate posterior probabilities of an association between risk factors and poor oral health (PP OR >1).
Results
Among 170 patients, 91 (54%) patients had unhealthy OHRAVI scores. Median index OHRAVI score was 1.13 (IQR 0.86–1.43); median SVI was 0.7 (0.5–0.9). Median OHRAVI scores were higher in the high SVI group (SVI >0.7; OHRAVI 1.19) than in the low SVI group (SVI <0.7; OHRAVI 1.06, p=0.026). Social factors associated with poor oral health from Bayesian analysis (PP OR>1) included lack of social support (99%), housing instability (99%), divorced marital status (87%), and non-English primary language (86%). Social vulnerability was also associated with poor oral health (98%).
Conclusions
Poor oral health in critically ill injured patients was associated with lack of social support, housing insecurity, divorced marital status, non-English primary language, and increased social vulnerability. OHRAVI may provide quick, objective bedside assessment to help identify socially vulnerable patients and serve as a marker for the presence of social risk factors that may portend poor outcomes. Oral health may be a modifiable risk factor, and early identification of patients may allow them to benefit from oral hygiene regimens, including treatment with antimicrobial agents.
Level of evidence
Level II/III, prospective/retrospective cohort study with only one negative criterion.
Keywords: health disparities
WHAT IS ALREADY KNOWN ON THIS TOPIC
Oral health is an indicator of general health, with poor oral health linked to chronic diseases and worse outcomes in certain surgical subspecialties. However, the relationship between social determinants of health and poor oral health in a critically injured population has been understudied, and few studies have used a validated oral health screening tool.
WHAT THIS STUDY ADDS
Our study found that poor oral health is associated with social vulnerability, lack of social support, housing instability, divorce, and non-English language.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
Future studies should assess if oral health is a modifiable risk factor that can improve patient outcomes.
Background
Oral disease is a significant condition that affects individuals during their entire lifetimes. It is estimated that 3.5 billion people worldwide are affected by oral diseases, with untreated dental caries being the most common condition.1 2 Oral health is also often a marker of general health; poor oral health and lack of oral care have been associated with chronic conditions such as cardiovascular disease, chronic obstructive pulmonary disease, cirrhosis, and diabetes mellitus.3 4 Furthermore, poor oral health may lead to complications after surgery. Previous studies have demonstrated an association between poor oral health in specific surgical subspecialties (cardiovascular, thoracic, minimally invasive, and colorectal) and worse surgical outcomes.5,13 Perioperative oral care has been reported to reduce the risk of complications such as surgical site infections (SSIs), indicating oral health may be a modifiable risk factor.7 9 10
Oral disease imposes a major burden on the healthcare system. Treatment for oral health conditions is expensive and not covered by traditional medical insurance plans in the USA. Having medical insurance is a strong predictor of access to dental care, and patients from underserved areas are more likely to have their oral disease untreated due to lack of health insurance. Socioeconomic status, including income, occupation, and education level, constitutes additional barriers to dental care, strongly correlating with both the prevalence and severity of oral disease.1
Social drivers of health are non-medical factors that influence health outcomes and are defined by five major domains: economic stability, education access and quality, healthcare access and quality, neighborhood and built environment, and social and community resources and infrastructure.5 As well, social vulnerability, defined as the susceptibility of communities to the impacts of hazards, disasters, or adverse events to various socioeconomic, cultural and political factors, is intertwined with social factors affecting health outcomes.14 Consequently, the Centers for Disease Control and Prevention (CDC) created the Social Vulnerability Index (SVI) tool to assess social vulnerability based on census-tract data.14 15
In trauma patients, previous studies have shown a connection between poor SVI and adverse long-term outcomes and increased mortality in trauma patients.15 16 However, associations between (1) poor oral health and social drivers of health and (2) poor oral health and social vulnerability within the critically ill trauma population are not well-defined. Although prior work has assessed the relationship between oral health and complications (eg, hospital-acquired pneumonia/ventilator-associated pneumonia (VAP)) after traumatic injury, these studies have not used a standardized oral health assessment tool, leading to variability in patient reporting. The Oral Health Risk Assessment Value Index (OHRAVI) is a standardized oral assessment designed to allow non-dental professionals to define the status of a patient’s oral health by providing a numerical comprehensive oral health score.17 18 The OHRAVI has demonstrated good inter-rater reliability when used in a critically ill injured patient population.17 18
In our study, we used the OHRAVI to analyze associations between (1) oral health status and social drivers of health and (2) oral health status and social vulnerability. Our primary hypothesis was that poor oral health, as assessed by the OHRAVI, is associated with social drivers of health and poor social vulnerability, as measured by SVI, in a severely injured population.
Methods
Study design
This single-center retrospective cohort analysis was performed using prospectively collected data from a busy, urban level 1 trauma center from May 25, 2022 to December 9, 2022 at The University of Texas Health Science Center at Houston (UTHealth Houston) and Memorial Hermann—Texas Medical Center. Results were reported according to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist.
Patients
Dentulous adult trauma patients ≥16 years old requiring an intensive care unit (ICU) admission were included. Patients with severe orofacial trauma (eg, orofacial trauma requiring surgical intervention), concurrent pneumonia at admission, comfort care status, or expected survival time of less than 2 days were excluded.
Data collection
Oral health data and patient baseline characteristics and demographics were collected from our institutional trauma registry and patient medical records. Medical comorbidities, including atherosclerotic disease, diabetes, chronic obstructive pulmonary disease, asthma, chronic kidney disease, and end-stage renal disease, were noted. Patients with any of these conditions were classified as having a medical comorbidity for the purposes of this study. Patient toothbrushing practices and information about recent dental visits were abstracted from medical records. Social drivers of health were collected from case management intake assessment forms in the patient medical records; collected drivers of interest included preferred language, health literacy, perceived social support, food insecurity, and stable housing. All social factors of health were self-reported.
SVI calculation
The SVI ranks each census tract based on 16 social factors grouped into four social themes: socioeconomic status, household characteristics, racial and ethnic minority status, and housing type/transportation.14 We calculated SVIs using the CDC’s database with census tract information based on patients’ self-reported home addresses. The overall vulnerability score was based on a composite score of the four social theme categories, and the higher the SVI value, the more vulnerable the community.14 For example, if a community has an SVI of 0.9, it is more vulnerable than 90% of communities and less vulnerable than 10% of communities.19 20
OHRAVI score
The OHRAVI score consists of eight categories: missing/restored/carious teeth, salivary secretion, visible caries, periodontal condition, oral lesions, pain, bite/occlusion, and oral hygiene. A trained rater scores each of the individual categories from 0 to 3 (range 0 best to 3 worst) and combines them to calculate a total score, which is then averaged to create the index score. Category scores of 1–2 indicate moderate oral disease, whereas scores greater than 2 are indicative of poor oral health, with these patients often requiring additional procedures and specialized care. For the assessment of periodontal disease (PD), grade 1 indicates gingival inflammation, whereas grade 2 indicates mild to moderate periodontitis with minimal bone loss; grade 3 signifies severe periodontitis with obvious bone loss.
OHRAVI scores were retrospectively collected. Patients received an OHRAVI score within 72 hours of admission by trained raters. If a patient was scored by more than one rater, the scores were adjudicated to analyze the patient’s final score. An unhealthy score was defined as an index score greater than 1.
Outcomes
Our primary outcome was unhealthy oral health status, which was defined by an OHRAVI score greater than 1. Secondary outcomes assessed included death, complications (including hospital-acquired infections), venous thromboembolism/pulmonary embolism, postoperative complications, and any SSI; a composite outcome comprised of either death or complications during hospital admission was also evaluated. Complications were defined by the Trauma Quality Improvement Project Data Dictionary.21
Statistical analysis
Statistical analysis was conducted using R (V.4.1.2).22 Univariate analyses were performed based on oral health score (healthy or unhealthy) and SVI (high or low) based on the median of the cohort. Specific components of oral health examined included the index score and PD. Index score and PD were examined as a binary variable, with 0 indicating a healthy score (index score 0–1) or no PD, and 1 indicating an unhealthy score (index score >1) or positive PD (gingivitis or moderate to severe disease). Demographics, injury characteristics, social factors, and oral health scores were compared between the two groups. Categorical variables were compared using χ² or Fisher’s exact tests. Continuous variables were compared using the Wilcoxon rank-sum test. Categorical and continuous variables were presented as the median (IQR) and as counts (percent).
To maximize the knowledge gained from this study, multivariable Bayesian analysis was used. A Bayesian analytical approach offers advantages in studies with small sample sizes and in estimating subtle treatment effects, compared with frequentist methods that often require larger samples to achieve sufficient power. Bayesian inference uses a prior, or an estimated effect based on previous evidence, and likelihood, which summarizes the data from the study. The prior and likelihood are combined to produce a posterior, or estimated treatment effect, with a credible interval that conveys the magnitude and precision of the treatment effect. A posterior may be used to analyze the posterior probability (PP) of a specific effect, such as harm or benefit of the treatment under study.23 PP provides a direct estimate of treatment benefit, which is often easier to interpret and more informative for clinical decision-making under uncertainty.23 Using the rstanarm package in R, logistic regression analyses under a Bayesian framework were performed. The relationship between social factors and unhealthy oral health scores was assessed, adjusting for age and presence of comorbid conditions. Each social factor believed to impact oral health was independently assessed. Due to minimal prior available knowledge, a neutral prior probability centered at an OR of 1 and a 95% credible interval (CrI) of 0.33–3.0 was applied. Continuous variables were standardized to have a mean of zero and a unit SD. ORs were estimated for outcomes with 95% CrI as well as the PP of any OR greater than 1 (PP OR >1). This PP is referred to as the likelihood of higher odds of infection or harm. Similar multivariable analyses assessing the relationship between SVI and secondary outcomes of interest were performed.
Results
Patient population
170 patients were included. The median patient age was 42 years (IQR 28–57), with 130 males (76.5%), and the group as a whole was severely injured with a median Injury Severity Score of 26 (IQR 18–35; table 1). 80 patients were missing oral health practices data (47%), mostly due to inability to respond due to injuries.
Table 1. OHRAVI Index Score and Social Vulnerability Index association with patient characteristics.
| Healthy index OHRAVI score*(N=79) | Unhealthy index OHRAVI score(N=91) | All(N=170) | P value | Low SVI <0.7(N=78) | High SVI >0.7(N=78) | All(N=156) | P value | |
|---|---|---|---|---|---|---|---|---|
| Age, years | <0.001 | 0.658 | ||||||
| Median (IQR) | 33 (22–44) | 51 (35–61) | 42 (28–57) | 42 (27–59) | 44 (30–56) | 42 (29–57) | ||
| Race and ethnicity† | 0.688 | 0.021 | ||||||
| White | 28 (35.4) | 34 (37.4) | 62 (36.5) | 33 (42.3) | 26 (33.3) | 59 (37.8) | ||
| Black | 28 (35.4) | 24 (26.4) | 52 (30.6) | 30 (38.5) | 18 (23.1) | 48 (30.8) | ||
| Asian | 8 (10.1) | 14 (15.4) | 22 (12.9) | 5 (6.4) | 14 (17.9) | 19 (12.2) | ||
| Hispanic | 12 (15.2) | 16 (17.6) | 28 (16.5) | 9 (11.5) | 17 (21.8) | 26 (16.7) | ||
| Other | 3 (3.8) | 3 (3.3) | 6 (3.5) | 1 (1.3) | 3 (3.8) | 4 (2.6) | ||
| Sex | 0.382 | 0.263 | ||||||
| Male | 58 (73.4) | 72 (79.1) | 130 (76.5) | 56 (71.8) | 62 (79.5) | 118 (75.6) | ||
| Female | 21 (26.6) | 19 (20.9) | 40 (23.5) | 21 (26.6) | 19 (20.9) | 40 (23.5) | ||
| Injury Severity Score | 0.501 | 0.315 | ||||||
| Median (IQR) | 27 (19–36) | 24 (18–35) | 26 (18–35) | 27 (18–38) | 27 (17–35) | 27 (18–36) | ||
| Any comorbidities* | 28 (35.4) | 48 (52.7) | 76 (44.7) | 0.024 | 40 (51.3) | 30 (38.5) | 70 (44.9) | 0.107 |
| Any comorbidities, smoker | 78 (98.7) | 88 (96.7) | 166 (97.6) | 0.384 | 75 (96.2) | 77 (98.7) | 152 (97.4) | 0.311 |
| BMI | 0.919 | 0.612 | ||||||
| Median (IQR) | 26 (23–31) | 26 (23–30) | 26 (23–30) | 26 (23–30) | 27 (24–30) | 26 (23–30) | ||
| Dentist visit within 1 year | 26 (55.3) | 15 (33.3) | 41 (44.6) | 0.034 | 18 (43.9) | 20 (44.4) | 38 (44.2) | 0.960 |
| Dentist visit within lifetime | 46 (97.9) | 40 (90.9) | 86 (94.5) | 0.145 | 39 (95.1) | 41 (93.2) | 80 (94.1) | 0.704 |
| Daily toothbrushing | 44 (95.7) | 32 (72.7) | 76 (84.4) | 0.003 | 34 (82.9) | 36 (83.7) | 70 (83.3) | 0.922 |
| OHRAVI Index Score | < 0.001 | 0.026 | ||||||
| Median (IQR) | 0.75 (0.63–0.94) | 1.43 (1.25–1.63) | 1.13 (0.86–1.43) | 1.06 (0.78–1.29) | 1.19 (0.88–1.48) | 1.13 (0.86–1.43) | ||
| Periodontal disease, grade | <0.001 | 0.116 | ||||||
| 0 | 0 (0.0) | 0 (0.0) | 0 (0.0) | 17 (21.8) | 13 (16.7) | 30 (19.2) | ||
| 1 | 37 (46.8) | 28 (30.8) | 65 (38.2) | 28 (35.9) | 32 (41.0) | 60 (38.5) | ||
| 2 | 13 (16.5) | 49 (53.8) | 62 (36.5) | 32 (41.0) | 26 (33.3) | 58 (37.2) | ||
| 3 | 0 (0.0) | 9 (9.9) | 9 (5.3) | 1 (1.3) | 7 (9.0) | 8 (5.1) |
Comorbidities were defined as diabetes, hypertension, coronary artery disease, atrial fibrillation, chronic kidney disease/end-stage renal disease, chronic obstructive pulmonary disease/asthma, or any other chronic systemic condition that would affect general health.
Data represented as n patients (%) except where indicated.
BMI, body mass index; OHRAVI, Oral Health Risk Assessment Value Index; SVI, Social Vulnerability Index.
OHRAVI score
The median index OHRAVI score was 1.13 (IQR 0.86–1.43); 79 patients had healthy index OHRAVI scores of <1 (46%), and the remaining 91 patients had unhealthy index OHRAVI scores of >1 (table 1). Compared with patients with a healthy index OHRAVI score, patients with an unhealthy index OHRAVI score were older (median 51 years vs 33 years, p<0.001), more frequently had medical comorbidities (p=0.024), had more severe PD (p<0.001), were less likely to have seen a dentist within the year (p=0.034), and were less likely to brush their teeth daily (p=0.003; table 1). Patients in the unhealthy OHRAVI group were also more likely to be divorced (p=0.029), without housing (p=0.012), and without social support (p=0.010; table 2). Interestingly, patients with an unhealthy OHRAVI index score were readmitted within 30 days less often than patients with a healthy OHRAVI score; however, there were more deaths in the unhealthy OHRAVI group (1 vs 11, p=0.006).
Table 2. OHRAVI Index Score and Social Vulnerability Index association with social factors of health.
| Healthy index OHRAVI score(N=79) | Unhealthy index OHRAVI score(N=91) | All(n=170) | P value | Low SVI <0.7(N=78) | High SVI >0.7(N=78) | All(N=156) | P value | |
|---|---|---|---|---|---|---|---|---|
| Health literacy status* | 0.699 | 0.238 | ||||||
| 0 (inadequate) | 2 (2.5) | 4 (4.4) | 6 (3.5) | 5 (6.4) | 1 (1.3) | 6 (3.8) | ||
| 1 (adequate) | 72 (91.1) | 83 (91.2) | 155 (91.2) | 70 (89.7) | 73 (93.6) | 143 (91.7) | ||
| 2 (declined to answer) | 5 (6.3) | 4 (4.4) | 9 (5.3) | 3 (3.8) | 4 (5.1) | 7 (4.5) | ||
| Marital status | 0.029 | 0.161 | ||||||
| Married | 49 (62.0) | 40 (44.0) | 89 (52.4) | 37 (47.4) | 44 (56.4) | 81 (51.9) | ||
| Never married | 26 (32.9) | 38 (41.8) | 64 (37.6) | 35 (44.9) | 24 (30.8) | 59 (37.8) | ||
| Divorced | 4 (5.1) | 13 (14.3) | 17 (10.0) | 6 (7.7) | 10 (12.8) | 16 (10.3) | ||
| Non-English primary language | 14 (17.7) | 23 (25.3) | 37 (21.8) | 0.234 | 8 (10.3) | 25 (32.1) | 33 (21.2) | <0.001 |
| Health illiterate | 2 (2.5) | 4 (4.4) | 6 (3.5) | 0.511 | 5 (6.4) | 1 (1.3) | 6 (3.8) | 0.096 |
| No social support | 1 (1.3) | 10 (11.0) | 11 (6.5) | 0.010 | 5 (6.4) | 5 (6.4) | 10 (6.4) | 0.010 |
| Without housing | 0 (0.0) | 7 (7.7) | 7 (4.1) | 0.012 | 2 (2.6) | 4 (5.2) | 6 (3.9) | 0.396 |
Data represented as n patients (%) except where indicated.
OHRAVI, Oral Health Risk Assessment Value Index; SVI, Social Vulnerability Index.
Social Vulnerability Index
There were 156 patients with available SVI data, and the median SVI was 0.70 (0.48–0.87). The low SVI group (SVI <0.7) had a median SVI of 0.48, and the high SVI group (SVI >0.7, that is, more socially vulnerable) had a median SVI of 0.87. The high SVI group more frequently identified as Hispanic (17 patients (22%) vs 9 patients (12%); table 1) and did not speak English as their primary language (25 patients (32%) vs 8 patients (10%); table 2). Other demographics were similar between groups.
There was a higher median index OHRAVI score (higher scores are indicative of worsening oral health status) in the high SVI group (1.19) than in the low SVI group (1.06, p=0.026; table 1). There were also more patients with grade 3 PD in the high SVI group (7 patients, 9%) than in the low SVI group (1 patient, 1%, p=0.116, table 1), but this did not reach statistical significance. Dental habits, including frequency of seeing a dentist within 1 year, seeing a dentist within a lifetime, and daily toothbrushing, were similar between groups. There were no notable differences between rates of death, readmission, or complications between the SVI groups. Patients in the high SVI group were also more likely to not speak English as their primary language (p<0.001; table 2); other social factors of health were similar between groups.
Social factors associated with unhealthy oral status
Using multivariable Bayesian analysis adjusted for age and presence of comorbidities, we found several social factors associated with unhealthy oral status (table 3). Lack of social support, housing insecurity, and SVI were all associated with increased odds of an unhealthy oral status, with PP of ORs >1 (PP OR >1 > 98%). Additionally, divorced marital status (PP OR >1 of 87%) and non-English primary language (PP OR >1 of 86%) were also correlated with worse oral health. Never married status was not associated with unhealthy oral health status (PP OR >1 of 4%). Death (PP OR >1 of 83%) and complications (PP OR >1 of 68%) separately, as well as the composite measure of death or complications (PP OR >1 of 55%), were associated with a higher SVI; however, there was significant imprecision in evaluating these associations (table 4).
Table 3. Factors associated with unhealthy oral health status in a critically ill trauma population.
| OR (95% CrI) | PP OR >1 | |
|---|---|---|
| Lack of social support | 1.66 (1.14–2.11) | 99% |
| Housing insecurity | 1.71 (1.14–2.14) | 99% |
| Social Vulnerability Index (per point) | 1.88 (1.03–3.29) | 98% |
| Divorced | 1.25 (0.83–1.70) | 87% |
| Non-English primary language | 1.20 (0.85–1.58) | 86% |
| Poor health literacy | 1.10 (0.41–1.73) | 60% |
| Never married | 0.77 (0.55–1.03) | 4% |
Bold values indicate statistical significance.
CrI, credible interval; PP OR, posterior probability OR.
Table 4. Association between SVI and complications (adjusted for age, ISS, any comorbidities*).
| OR (95% CrI) | PP OR>1 | |
|---|---|---|
| Death | 11.3 (0.29–65.4) | 83% |
| Complications | 1.48 (0.48–3.72) | 68% |
| Any SSI | 0.82 (0.22–2.33) | 25% |
| Death or complications | 1.14 (0.53–2.27) | 55% |
Bold values indicate statistical significance.
Comorbidities were defined as diabetes, hypertension, coronary artery disease, atrial fibrillation, CKD/ESRD, chronic obstructive pulmonary disease/asthma, or any other chronic systemic condition that would affect general health.
CKD, chronic kidney disease; CrI, credible interval; ESRD, end-stage renal disease; ISS, Injury Severity Score; PP OR, posterior probability OR; SSI, surgical site infection; SVI, Social Vulnerability Index.
Discussion
Our study used an objective, standardized oral health assessment tool, the OHRAVI, to investigate the association between poor oral health and self-reported social factors of health and SVI. In our single-center study, we found that poor oral health in critically ill injured patients was correlated with a lack of social support, housing insecurity, divorced marital status, non-English primary language, and increased social vulnerability. SVI assesses area-level vulnerability but is not as accurate in predicting individual-level needs. In this study, we used both SVI and self-reported social drivers of health, allowing for a more comprehensive assessment of social vulnerability in this patient population. Although the OHRAVI assessment can be easily completed at the bedside, the SVI calculation requires complete patient address information, which is then converted into census-tract information that is searchable within the CDC database. These additional steps make it challenging to calculate SVI bedside quickly. However, OHRAVI takes into account some social drivers of health that are linked with poor oral health and are included as SVI variables, such as non-English primary language and lack of social support. This may allow for poor oral health to serve as a marker for the presence of other social risk factors.
Associations between poor oral health and social drivers, including limited education, low socioeconomic status, poor health literacy, and patient’s annual income, have previously been found in outpatient survey studies.24,26 Borell et al surveyed 1168 participants and found that those with yearly incomes less than US$40,000 and those with less than 12 years of education were twice as likely to rate their oral health as fair or poor than their counterparts.24 Additionally, Zivkovic et al found that patients with dental insurance were more likely to visit a dentist (56.6% without vs 79.4% with insurance) and more likely to report good or excellent oral health.26 Our study similarly found an association between poor oral health and social factors of health with the OHRAVI, suggesting that heightened attention to social drivers should be considered in the setting of poor oral health. Although these prior studies have focused on outpatients, our study specifically explored this association in a critically ill inpatient population, indicating that consideration of social drivers may impact outcomes in various patient settings.
Social factors of health and social vulnerability have been found to be correlated with poor outcomes in the trauma surgery population.1627,29 Phelos et al, using three national social vulnerability indices surveying 3,137 US counties, noted that increased social vulnerability in trauma patients was associated with increased fatality rates overall.29 Furthermore, poor oral health, and the local inflammatory response associated with periodontitis, have been connected with the progression of chronic inflammatory diseases such as cardiovascular disease, diabetes, and respiratory disease. Poor oral health has also been linked to acute conditions such as VAP.30 Data from our institution showed that poor oral health was associated with a 79% probability of increased odds of developing VAP (OR 1.40, 95% CrI 0.64–3.17) and 96% probability of developing healthcare-associated pneumonia (OR 1.84, 95% CrI 0.93–3.70). Additionally, during the COVID-19 pandemic, poor oral health in COVID-19 patients was found to be coupled with increased rates of ICU admissions, need for mechanical ventilation, and death.31
Oral health may be a modifiable risk factor. Dental plaque rapidly accumulates in critically ill patients if there is poor oral care, resulting in changes in the oral microbiome and colonization of VAP pathogens.30 Treatment with antimicrobial agents to induce good oral hygiene may reverse some outcomes. For example, oral chlorhexidine has broad antimicrobial properties and reduces dental plaque formation, with multiple systematic reviews of well-conducted randomized controlled trials showing reductions in VAP.1230 32,34 Additionally, meta-analysis showed that chlorhexidine decreased the risk of VAP from 26% to 18% (relative risk 0.67, 95% CIs 0.47 to 0.97; p=0.03).12 Other oral health hygiene regimens such as oral povidone iodine, toothbrushing, and saline rinses have also been shown to decrease the risk of VAP.30 Strict attention to effective oral hygiene in the ICU may result in improved oral health and, thus, better and more equitable overall outcomes.
Limitations
Our study had several limitations. As a retrospective study, there is potential for unmeasured confounders and missing information. For example, many patients had missing data regarding the collection of social factors of health and potential variation among case management personnel. Second, although SVI is typically analyzed by quartile, comparing the lowest to the highest, we used the median SVI in this study due to the high number of socially vulnerable patients. Future studies should consider analyzing SVI by quartile. Consideration should be given to implementing a standardized social factors of health assessment tool such as HealthBegins or Protocol for Responding to and Assessing Patient Assets, Risks and Experiences, which have both been validated in a variety of clinical settings, including the emergency department where the bulk of these assessments are conducted.35
Conclusion
In conclusion, we found that poor oral health in critically ill injured patients was associated with a lack of social support, housing insecurity, divorced marital status, non-English primary language, and increased social vulnerability. Identification of poor oral health using OHRAVI, which can quickly be performed and provides objective data, may serve as a marker for the presence of social risk factors that may portend poor outcomes. Furthermore, poor oral health may be a modifiable risk factor that can be addressed through strict attention to effective oral hygiene in the ICU.
Footnotes
Funding: MOF and SMU are supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number T32GM008792.
Data availability free text: Data available upon reasonable request and in compliance with institutional policy.
Patient consent for publication: Not applicable.
Ethics approval: The UTHealth Houston Committee for the Protection of Human Subjects and Memorial Hermann Health System approved this study with waiver of informed consent (HSC-GEN-13-0325). IRB determined consent was waived for this study.
Provenance and peer review: Not commissioned; externally peer reviewed.
Presented at: Previously presented in part at the 19th Annual Academic Surgical Congress Conference, February 6–8, 2024, Washington DC and 2024 South Texas Chapter Annual Meeting of the American College of Surgeons, February 29–March 2, 2024, Houston, Texas, USA.
Data availability statement
Data are available upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data are available upon reasonable request.