Abstract
Background
Although systemic medical conditions are associated with periodontitis and tooth loss, large-scale studies that include less prevalent systemic conditions are needed. The purpose of the study was to investigate the link between periodontal disease and tooth loss with systemic medical conditions in a large and diverse population.
Methods
Dental charts of adult patients who had attended the dental clinics seeking dental therapy of the universities contributing data to the BigMouth network and accepted the protocol of the study were included. Dental Procedure Codes and Current Procedural Terminology procedures were utilised to identify patients with and without periodontitis. Data were extracted from patients’ electronic health records including demographic characteristics, dental procedural codes, and self-reported medical conditions as well as the number of missing teeth.
Results
A total of 108,307 records were ultimately included in the analysis; 42,377 of them included a diagnosis of periodontitis. The median age of the included population was 47.0 years, and 55.2% were female. Older and male individuals were significantly more likely to be in the periodontitis group and have higher number of missing teeth. A number of systemic conditions are associated with periodontitis and a higher number of missing teeth. High blood pressure, smoking, drug use, and diabetes were all found to be significant. Other significant conditions were anaemia, lymphoma, glaucoma, dialysis, bronchitis, sinusitis hepatitis, and asthma.
Conclusions
Within the limitations of this retrospective study that utilised the BigMouth dental data repository, the association of a number of systemic conditions such as smoking, diabetes, and hypertension with periodontitis and tooth loss has been confirmed. Additional connections have been highlighted for conditions that are not commonly reported in the literature.
Key words: Epidemiology, Oral health, Oral-systemic disease, Periodontal disease, Tooth loss
Background
Periodontal disease is a chronic noncommunicable inflammatory disease that affects the integrity of the tooth-supporting tissues when an imbalance interaction occurs between the periodontal microbiome and the inflammatory response of the host.1 Periodontal disease is the sixth most prevalent condition worldwide, and at least 10% of the adult population has a severe form of the disease.2,3 Apart from its negative impact on oral health, evidence over the last 30 years has revealed the relationships between oral diseases, including periodontitis, and a variety of systemic conditions.4 Periodontitis adversely impacts systemic health through biologically plausible mechanisms, whilst its successful treatment can modify the risk of disease comorbidities.4
In 2013, experts from the European Federation of Periodontology and the American Academy of Periodontology reviewed the available evidence regarding the associations between periodontal and systemic diseases and concluded that periodontitis contributes to the systemic inflammatory response.5, 6, 7, 8 In another review that examined potential associations between periodontitis and other systemic conditions including chronic kidney disease, rheumatoid arthritis, cognitive impairment, inflammatory cancers, and obesity, modest associations were found with obesity and weak associations with rheumatoid arthritis, cognitive impairment, and oropharyngeal cancer.9 A systematic mapping of trial registers evaluated 2015 Medical Subject Headings (MesH) terms for systemic conditions and reported associations between periodontal disease and 57 systemic conditions, which covers about 2% of the diseases indexed in MeSH.10
The associations between periodontal disease and systemic medical conditions may be a result of inflammatory mechanisms or due to a disruptive host immune response.11 Susceptible hosts in patients with systemic conditions may negatively impact the homeostatic balance and initiate a state of disease. Presence of systemic conditions, obesity, smoking, stress, and ageing characterise a susceptible host that can shift the polymicrobial synergy towards dysbiosis and may influence the progression and severity of periodontal disease.12 It is imperative to understand whether there is a link between periodontal disease and associated comorbidities. According to the periodontal classification developed at the 2017 World Workshop, the presence of systemic risk associated conditions and diseases including smoking and diabetes are considered in the grading process.13 Patients with syndromes such as Papillon-Lefevre are also classified as having “periodontitis as a manifestation of systemic diseases.”14 Therefore, detecting the associations between periodontal disease and systemic medical conditions can provide a holistic approach to patient care management.
Electronic dental records are effectively used to answer focussed research questions and allow efficient public health surveillance with respect to disease prevalence amongst other factors.15 Surveillance of medical conditions amongst dental patients and mining associations between periodontal and medical conditions can be provided using electronic health and dental records. The BigMouth Dental Data Repository was developed in 2012 using partially de-identified electronic health records from 11 dental schools in the US. This dental data repository can be used to investigate relationships between oral conditions such as periodontitis and systemic conditions.16 The BigMouth Dental Data Repository is a multi-institutional dental data repository that is derived from electronic health records of dental institutions in the US aiming to improve oral health research, education, and treatment. It provides information regarding the feasibility of research studies, facilitates population-based observation studies, supports quality improvement efforts, and assists researchers in identifying clinical trial cohorts for recruitment. It is critically important to recognise the interrelationship between the oral cavity and the general systemic health status of an individual. However, further large-scale studies should be performed.
The purposes of this study are to (1) assess the prevalence of systemic medical conditions, (2) investigate the relationship between periodontal disease and systemic conditions, and (3) examine the link between medical conditions and the extent of missing teeth in a large and diverse population. Using a large database allows generalisability across multiple dental institutions, plays a key role in developing preventative care models, and may assist practitioners in providing a more accurate and enhanced treatment.
Methods
This cross-sectional, retrospective study was reviewed by the Institutional Review Board of the University of Minnesota and determined that it is not research involving human subjects as defined by the Department of Health and Human Services as well as the United States Food and Drug Administration (STUDY00016576). It was further reviewed and approved by the BigMouth Consortium for Oral Health Research and Informatics clinical review committee. This study was conducted in agreement with the Helsinki Declaration of 1975 as most recently revised in 2013.
The BigMouth Dental Data Repository was utilised to extract electronic health records from 2011 through 2021. Dental charts of adult patients who had attended the dental clinics seeking dental therapy of the universities contributing data to the BigMouth network and accepted the protocol of the study were evaluated: Harvard University; University of Texas Health; The University of California, San Francisco; University of Colorado; Loma Linda University; University of Buffalo; The University of Iowa; and The University of Minnesota. Electronic health records were entered during patients’ visits by dental students, residents, and faculty oral health care providers. Dental Procedure Codes and Current Procedural Terminology procedures were utilised. Current Dental Terminology (CDT) is a code set for dental diagnoses and treatments with descriptive terms developed and updated by the American Dental Association (ADA) for reporting dental services and procedures to dental benefits plans. Patients with at least one completed treatment code D0150 (comprehensive oral evaluation), D0120 (periodic oral evaluation provided to an established patient), or D0180 (comprehensive restorative and periodontal exam) were included.
Patients were categorised into 2 groups based on the presence of planned or completed CDT codes:
-
•
Group 1: Periodontitis group when the following CDT codes “D4210” OR “D4211” OR D4240” OR “D4241” OR “D4245” OR “D4260” OR “D4261” OR “D4263” OR “D4266” OR “D4274” OR “D4341” OR “D4342” OR “D4910” were utilised. These CDT codes are used for nonsurgical and surgical treatment of periodontal disease.
-
•
Group 2: Non-periodontitis group when patients had at least one D1110 code (dental prophylaxis in the absence of periodontal disease) and none of the CDT codes in group 1.
Relevant data were extracted from patients’ electronic health records, including demographic characteristics, dental procedural codes, and self-reported medical conditions of patients who met the inclusion criteria of the study. In addition, the number of missing teeth and the number of lost teeth after the first periodontal maintenance/recall visit were recorded. The independent variables included were as follows:
-
•
Demographic characteristics: age (at the time of CDT code completion); ethnicity; race; gender; self-reported alcohol consumption.
-
•
CDT: D4210, D4211, D4240, D4241, D4245, D4260, D4261, D4263, D4266, D4274, D4341, D4342, D4910, and D1110.
-
•
Self-reported medical conditions: Self-reported systemic diseases are based on a patient questionnaire that is completed at the initial visit and updated every 6 to 12 months.
Statistical analysis
Patients’ demographic and clinical characteristics were summarised as means and standard deviations or medians and interquartile ranges (IQRs) for continuous variables, as appropriate, and frequencies and percentages for categorical variables. Normality was assessed using density plots. Between healthy patients and those with periodontal disease, Wilcoxon rank sum, negative binomial regression, and Chi-square tests were used for comparison of continuous, count, and categorical characteristics, respectively. Univariate associations between systemic medical conditions and periodontal disease status were assessed using a logistic regression model with results presented as odds ratios (ORs) and their corresponding 95% confidence intervals (CIs). Negative binomial regression models were used to assess associations between medical conditions and tooth loss, with results presented as incident rate ratios (RRs) and their corresponding 95% CIs. Multivariable regression models were explored for the above outcomes, adjusting for the effects of age and gender. For all multivariable regression models, P values were corrected for multiple comparisons using the Holm method. All analyses were based on complete cases and were conducted at the .05 significance level using the R environment (Version 4.2.1).
Results
A total of 164,892 patients’ records were identified in the BigMouth Dental Data Repository using the inclusion and exclusion criteria of the study. Out of these initially screened records, a total of 108,307 records were ultimately included in the analysis after excluding records with missing data. The demographic characteristics of the included population are shown in Table 1. The periodontitis group included individuals who were significantly older (P < .001) and had a significantly higher proportion of males (P < .001), Hispanics (P < .001), as well as African Americans and Hispanics or Latinos (P < .001). The numbers of missing teeth were also significantly different between the periodontitis and non-periodontitis groups, and the former demonstrated a significantly higher number of missing teeth (P < .001). Alcohol consumption was more frequently reported by patients with periodontitis (P = .033) than without periodontitis. Both age (P < .001) and gender (P < .001) were significantly associated with periodontal status. Similar significant associations were identified for age (P < .001) and gender (P < .001) for the number of missing teeth.
Table 1.
Demographic characteristics of the included population.
| Characteristics | Overall (N = 108,307) | Non-periodontitis group (n = 65,930) | Periodontitis group (n = 42,377) | P value | |
|---|---|---|---|---|---|
| Age, median (IQR) | 47.00 (31.00, 62.00) | 39.00 (27.00, 58.00) | 55.00 (41.00, 65.00) | <.001 | |
| Age, mean (SD) | 47.35 (17.91) | 43.44 (18.17) | 53.44 (15.65) | ||
| Gender, No. (%) | Female | 59,756 (55.2) | 38,306 (58.1) | 21,450 (50.6) | <.001 |
| Male | 48,514 (44.8) | 27,595 (41.9) | 20,919 (49.4) | ||
| Other | 37 (0.0) | 29 (0.0) | 8 (0.0) | ||
| Ethnicity, No. (%) | Non-Hispanic | 63,724 (79.3) | 37,827 (80.4) | 25,897 (77.9) | <.001 |
| Hispanic | 12,206 (15.2) | 6312 (13.4) | 5894 (17.7) | ||
| Other | 4390 (5.5) | 2917 (6.2) | 1473 (4.4) | ||
| Race, No. (%) | White | 69,553 (64.2) | 44,254 (67.1) | 25,299 (59.7) | |
| American Indian | 300 (0.3) | 185 (0.3) | 115 (0.3) | .4821 | |
| Asian | 7771 (7.2) | 5049 (7.7) | 2722 (6.4) | .0191 | |
| African American | 11,982 (11.1) | 6033 (9.2) | 5949 (14.0) | <.0011 | |
| Hispanic or Latino | 6896 (6.4) | 3246 (4.9) | 3650 (8.6) | <.0011 | |
| Other | 6544 (6.0) | 4237 (6.4) | 2307 (5.4) | .0721 | |
| Pacific islander | 110 (0.1) | 69 (0.1) | 41 (0.1) | .8451 | |
| 2 or more races | 5151 (4.8) | 2857 (4.3) | 2294 (5.4) | <.0011 | |
| Race, No. (%) | White | 72,086 (66.6) | 45,799 (69.5) | 26,287 (62.0) | <.001 |
| Non-White | 36,221 (33.4) | 20,131 (30.5) | 16,090 (18.0) | ||
| Missing teeth, mean (SD) | 1.43 (2.71) | 1.08 (2.42) | 1.98 (3.02) | <.0012 | |
| Missing teeth, median (IQR) | 0.00 (0.00, 2.00) | 0.00 (0.00, 1.00) | 1.00 (0.00, 3.00) | ||
| Alcohol consumption, No. (%) | 34,390 (31.8) | 20,774 (31.5) | 13,616 (32.1) | .033 | |
Data obtained from 8 dental schools in the US that contribute data to the BigMouth network and accepted the protocol of the study. A total of 164,892 patients’ records were identified in the BigMouth Dental Data Repository, whilst 108,307 records were ultimately included in the analysis after excluding records with missing data.
*The level of significance was set at .05.
Based on univariable logistic regression and comparison to White reference group.
Based on univariable negative binomial regression.
IQR, interquartile range.
Prevalence of self-reported systemic conditions
The prevalence of the examined self-reported systemic medical conditions for all patients and compared between patients with and without periodontitis are presented in Table 2. Smoking was reported by 10.76% of the included population, and it was significantly more prevalent in the periodontitis group (P < .001). Amongst the most prevalent systemic medical conditions were high blood pressure (22.13%), cardiovascular problems (17.61%), arthritis (12.05%), depression (8.73%), and cancer (7.73%). Significant differences were observed between patients with and without periodontitis for a number of conditions. Amongst others, cancer, cardiovascular problems, high blood pressure, diabetes, glaucoma, kidney disease, arthriti,s and osteoporosis were significantly (P < .001) more prevalent in the periodontitis group. In contrast, anaemia, anxiety, depression, and asthma were more often observed in the non-periodontitis group (P < .001).
Table 2.
Prevalence of the examined self-reported systemic medical conditions and smoking for all patients and compared between non-periodontitis and periodontitis groups.
| Self-reported medical conditions and smoking | Overall (n = 108,307) | Non-periodntitis (n = 65,930) | Periodontitis (n = 42,377) | OR (95% CI) | P value |
|---|---|---|---|---|---|
| Smoking, No. (%) | 10.756 | 9.076 | 13.370 | 1.546 (1.488–1.607) | <.001 |
| Anaemia, No. (%) | 1.806 | 1.984 | 1.529 | 0.767 (0.698–0.844) | <.001 |
| Bleeding disorders, No. (%) | 1.761 | 1.864 | 1.600 | 0.856 (0.779–0.941) | .001 |
| Lymphoma, No. (%) | 0.137 | 0.094 | 0.203 | 2.160 (1.558–2.995) | <.001 |
| Blood haemotologic disorders, No. (%) | 1.222 | 1.045 | 1.498 | 1.440 (1.292–1.606) | <.001 |
| Leukaemia, No. (%) | 0.058 | 0.038 | 0.090 | 2.366 (1.428–3.920) | .001 |
| Multiple myeloma, No. (%) | 0.008 | 0.006 | 0.012 | 1.945 (0.522–7.243) | .321 |
| Malignant, No. (%) | 7.726 | 6.689 | 9.340 | 1.437 (1.374–1.503) | <.001 |
| Angina, No. (%) | 0.720 | 0.632 | 0.857 | 1.357 (1.179–1.563) | <.001 |
| Cardiovascular heart problem, No. (%) | 17.609 | 14.758 | 22.045 | 1.633 (1.583–1.686) | <.001 |
| Congenital heart disease, No. (%) | 0.331 | 0.196 | 0.540 | 2.771 (2.233–3.440) | <.001 |
| Coronary heart disease, No. (%) | 0.784 | 0.493 | 1.237 | 2.527 (2.199–2.904) | <.001 |
| History of endocarditis, No. (%) | 0.126 | 0.111 | 0.149 | 1.343 (0.959–1.882) | .086 |
| Heart attack, No. (%) | 1.178 | 0.869 | 1.659 | 1.924 (1.722–2.150) | <.001 |
| High blood pressure, No. (%) | 22.133 | 17.500 | 29.341 | 1.958 (1.902–2.015) | <.001 |
| Implanted defibrillator, No. (%) | 2.031 | 1.791 | 2.405 | 1.351 (1.241–1.470) | <.001 |
| Rheumatic fever, No. (%) | 0.147 | 0.100 | 0.219 | 2.195 (1.601–3.010) | <.001 |
| Cocaine use, No. (%) | 0.548 | 0.570 | 0.514 | 0.902 (0.763–1.066) | .225 |
| Heroin use, No. (%) | 0.029 | 0.020 | 0.042 | 2.155 (1.056–4.398) | .035 |
| Marijuana use, No. (%) | 2.084 | 1.788 | 2.544 | 1.434 (1.319–1.558) | <.001 |
| Methamphetamine use, No. (%) | 0.150 | 0.091 | 0.241 | 2.649 (1.925–3.645) | <.001 |
| Anorexia, No. (%) | 0.356 | 0.463 | 0.191 | 0.412 (0.322–0.527) | <.001 |
| Bulimia, No. (%) | 0.142 | 0.190 | 0.068 | 0.361 (0.241–0.540) | <.001 |
| Andrenal gland disorder, No. (%) | 0.069 | 0.059 | 0.085 | 1.436 (0.913–2.260) | .117 |
| Diabetes, No. (%) | 8.339 | 6.466 | 11.254 | 1.834 (1.757–1.915) | <.001 |
| Thyroid problems, No. (%) | 5.593 | 5.225 | 6.166 | 1.192 (1.131–1.256) | <.001 |
| Glaucoma, No. (%) | 3.365 | 2.542 | 4.644 | 1.867 (1.747–1.995) | <.001 |
| AIDS, No. (%) | 0.042 | 0.044 | 0.038 | 0.858 (0.466–1.580) | .624 |
| HIV, No. (%) | 0.421 | 0.381 | 0.484 | 1.272 (1.057–1.530) | .011 |
| STD, No. (%) | 0.733 | 0.754 | 0.701 | 0.929 (0.804–1.073) | .319 |
| Dialysis, No. (%) | 0.268 | 0.171 | 0.418 | 2.443 (1.929–3.094) | <.001 |
| Kidney, No. (%) | 5.592 | 5.016 | 6.487 | 1.314 (1.247–1.384) | <.001 |
| Renal failure or insufficiency, No. (%) | 0.892 | 0.731 | 1.142 | 1.569 (1.382–1.781) | <.001 |
| Arthritis, No. (%) | 12.051 | 10.120 | 15.055 | 1.574 (1.517–1.633) | <.001 |
| Lupus, No. (%) | 0.262 | 0.262 | 0.262 | 0.998 (0.786–1.267) | .988 |
| Osteoporosis, No. (%) | 2.945 | 2.624 | 3.445 | 1.324 (1.234–1.421) | <.001 |
| Dementia, No. (%) | 0.336 | 0.311 | 0.375 | 1.207 (0.981–1.486) | .075 |
| Anxiety, No. (%) | 4.771 | 5.407 | 3.780 | 0.687 (0.647–0.730) | <.001 |
| Depression, No. (%) | 8.728 | 9.901 | 6.902 | 0.675 (0.645–0.706) | <.001 |
| Parkinson disease, No. (%) | 0.170 | 0.140 | 0.217 | 1.557 (1.166–2.079) | .003 |
| Multiple sclerosis, No. (%) | 0.164 | 0.176 | 0.146 | 0.831 (0.611–1.132) | .241 |
| Seizure or epilepsy, No. (%) | 0.827 | 0.751 | 0.946 | 1.263 (1.106–1.441) | .001 |
| Stroke, No. (%) | 1.227 | 1.054 | 1.496 | 1.426 (1.279–1.589) | <.001 |
| Organ transplant, No. (%) | 0.329 | 0.300 | 0.373 | 1.242 (1.008–1.532) | .042 |
| Asthma, No. (%) | 6.931 | 7.590 | 5.907 | 0.764 (0.727–0.803) | <.001 |
| Bronchitis, No. (%) | 2.345 | 1.631 | 3.457 | 2.160 (1.995–2.340) | <.001 |
| Chronic bronchitis or emphysema, No. (%) | 4.889 | 5.231 | 4.356 | 0.825 (0.779–0.874) | <.001 |
| Respiratory or lung problem, No. (%) | 1.961 | 1.853 | 2.129 | 1.152 (1.056–1.256) | .001 |
| Sinusitis, No. (%) | 2.702 | 2.274 | 3.367 | 1.498 (1.392–1.612) | <.001 |
| Sleep apnoea, No. (%) | 2.729 | 2.219 | 3.523 | 1.609 (1.496–1.731) | <.001 |
| Crohn's disease, No. (%) | 0.185 | 0.180 | 0.191 | 1.059 (0.798–1.405) | .690 |
| Tuberculosis, No. (%) | 1.692 | 1.197 | 2.464 | 2.085 (1.900–2.289) | <.001 |
| Cirrhosis or chronic hepatitis, No. (%) | 1.610 | 0.884 | 2.740 | 3.157 (2.856–3.490) | <.001 |
| Gastrointestinal disorders, No. (%) | 1.927 | 1.673 | 2.322 | 1.397 (1.281–1.524) | <.001 |
| Hepatitis, No. (%) | 3.148 | 2.437 | 4.255 | 1.779 (1.661–1.905) | <.001 |
*Univariate associations between systemic medical conditions and periodontal disease status were assessed using a logistic regression model with results presented as odds ratios (ORs) and their corresponding 95% confidence intervals (CIs). The level of significance was set at .05.
Association between systemic medical conditions and tooth loss
The mean tooth loss for all patients and compared between self-reported systemic medical conditions and smoking is demonstrated in Table 3. Methamphetamine users exhibited the highest number of missing teeth (3.41 teeth), whilst individuals with gastrointestinal disorder (0.87 teeth), multiple myeloma (0.89 teeth), and respiratory or lung problems (0.84 teeth) showed the lowest. Significant differences were identified between some systematic medical conditions and the number of missing teeth. Anaemia, bleeding disorders, lymphoma, cancer, angina, cardiovascular disease, congenital heart disease, coronary heart disease, heart attack, high blood pressure, implanted defibrillator, smoking, cocaine use, marijuana use, methamphetamine use, diabetes, thyroid problems, glaucoma, HIV infection, dialysis, kidney disease, renal failure, arthritis, lupus, osteoporosis, dementia, depression, Parkinson disease, seizures or epilepsy, stroke, asthma, bronchitis, chronic bronchitis, respiratory or lung problems, sinusitis, sleep apnoea, tuberculosis, cirrhosis or chronic hepatitis, gastrointestinal disorders, and hepatitis were significantly associated with higher number of missing teeth in the periodontitis group (P < .05). The mean tooth loss by periodontitis status and systemic medical conditions is shown in the Supplementary Table.
Table 3.
Mean tooth loss for all patients and compared between self-reported systemic medical conditions and smoking.
| Self-reported medical conditions and smoking | Tooth loss | Rate ratio (95% CI) | P value |
|---|---|---|---|
| ANEMIA NO | 1.427 | 1.247 (1.148–1.355) | <.001 |
| ANEMIA YES | 1.779 | ||
| BLEEDING_DISORDERS NO | 1.420 | 1.535 (1.414–1.667) | <.001 |
| BLEEDING_DISORDERS YES | 2.180 | ||
| LYMPHOMA NO | 1.432 | 1.496 (1.115–2.007) | .007 |
| LYMPHOMA YES | 2.142 | ||
| BLOOD_HEMOTOLOGICAL_DISORDERS NO | 1.432 | 1.093 (0.987–1.209) | .087 |
| BLOOD_HEMOTOLOGICAL_DISORDERS YES | 1.564 | ||
| LEUKEMIA NO | 1.433 | 1.485 (0.946–2.330) | .086 |
| LEUKEMIA YES | 2.127 | ||
| MULTIPLE_MYELOMA NO | 1.433 | 0.620 (0.168–2.285) | .473 |
| MULTIPLE_MYELOMA YES | 0.889 | ||
| MALIGNANT NO | 1.398 | 1.321 (1.268–1.376) | <.001 |
| MALIGNANT YES | 1.847 | ||
| ANGINA NO | 1.429 | 1.419 (1.248–1.615) | <.001 |
| ANGINA YES | 2.028 | ||
| CARDIOVASCULAR_HEART_PROBLEM NO | 1.320 | 1.485 (1.443–1.529) | <.001 |
| CARDIOVASCULAR_HEART_PROBLEM YES | 1.961 | ||
| CONGENITAL_HEART_DISEASE NO | 1.431 | 1.511 (1.251–1.826) | <.001 |
| CONGENITAL_HEART_DISEASE YES | 2.162 | ||
| CORONARY_HEART_DISEASE NO | 1.426 | 1.644 (1.454–1.858) | <.001 |
| CORONARY_HEART_DISEASE YES | 2.344 | ||
| HISTORY_OF_ENDOCARDITIS NO | 1.433 | 0.954 (0.694–1.312) | .773 |
| HISTORY_OF_ENDOCARDITIS YES | 1.368 | ||
| HEART_ATTACK NO | 1.421 | 1.698 (1.537–1.876) | <.001 |
| HEART_ATTACK YES | 2.414 | ||
| HIGH_BLOOD_PRESSURE NO | 1.243 | 1.693 (1.650–1.738) | <.001 |
| HIGH_BLOOD_PRESSURE YES | 2.104 | ||
| IMPLANT_DEFIBRILLATOR NO | 1.415 | 1.625 (1.505–1.754) | <.001 |
| IMPLANT_DEFIBRILLATOR YES | 2.300 | ||
| RHEUMATIC_FEVER NO | 1.433 | 1.225 (0.918–1.634) | .168 |
| RHEUMATIC_FEVER YES | 1.755 | ||
| SMOKING NO | 1.348 | 1.590 (1.535–1.647) | <.001 |
| SMOKING YES | 2.143 | ||
| COCAINE_USE NO | 1.431 | 1.259 (1.084–1.461) | .002 |
| COCAINE_USE YES | 1.801 | ||
| HEROIN_USE NO | 1.433 | 1.486 (0.782–2.824) | .227 |
| HEROIN_USE YES | 2.129 | ||
| MARIJUANA_USE NO | 1.424 | 1.292 (1.197–1.396) | <.001 |
| MARIJUANA_USE YES | 1.841 | ||
| METHAMPHETAMINE_USE NO | 1.430 | 2.387 (1.816–3.138) | <.001 |
| METHAMPHETAMINE_USE YES | 3.414 | ||
| ANOREXIA NO | 1.433 | 1.049 (0.869–1.265) | .620 |
| ANOREXIA YES | 1.503 | ||
| BULIMIA NO | 1.433 | 0.974 (0.722–1.313) | .863 |
| BULIMIA YES | 1.396 | ||
| ANDRENAL_GLAND_DISORDER NO | 1.433 | 0.958 (0.624–1.471) | .845 |
| ANDRENAL_GLAND_DISORDER YES | 1.373 | ||
| DIABETES NO | 1.361 | 1.640 (1.577–1.705) | <.001 |
| DIABETES YES | 2.231 | ||
| THYROID_PROBLEMS NO | 1.426 | 1.087 (1.035–1.141) | .001 |
| THYROID_PROBLEMS YES | 1.550 | ||
| GLAUCOMA NO | 1.418 | 1.320 (1.242–1.403) | <.001 |
| GLAUCOMA YES | 1.872 | ||
| AIDS NO | 1.433 | 1.272 (0.741–2.181) | .383 |
| AIDS YES | 1.822 | ||
| HIV NO | 1.432 | 1.221 (1.029–1.447) | .022 |
| HIV YES | 1.748 | ||
| STD NO | 1.432 | 1.112 (0.976–1.267) | .111 |
| STD YES | 1.592 | ||
| DIALYSIS NO | 1.431 | 1.547 (1.254–1.908) | <.001 |
| DIALYSIS YES | 2.214 | ||
| KIDNEY NO | 1.392 | 1.532 (1.462–1.606) | <.001 |
| KIDNEY YES | 2.133 | ||
| RENAL_FAILURE_OR_INSUFFICIENCY NO | 1.426 | 1.556 (1.387–1.746) | <.001 |
| RENAL_FAILURE_OR_INSUFFICIENCY YES | 2.219 | ||
| ARTHRITIS NO | 1.365 | 1.412 (1.365–1.460) | <.001 |
| ARTHRITIS YES | 1.927 | ||
| LUPUS NO | 1.432 | 1.412 (1.141–1.747) | .002 |
| LUPUS YES | 2.021 | ||
| OSTEOPOROSIS NO | 1.424 | 1.227 (1.149–1.309) | <.001 |
| OSTEOPOROSIS YES | 1.746 | ||
| DEMENTIA NO | 1.430 | 1.590 (1.319–1.917) | <.001 |
| DEMENTIA YES | 2.275 | ||
| ANXIETY NO | 1.433 | 0.999 (0.948–1.054) | .983 |
| ANXIETY YES | 1.432 | ||
| DEPRESSION NO | 1.392 | 1.341 (1.289–1.394) | <.001 |
| DEPRESSION YES | 1.866 | ||
| PARKINSON_DISEASE NO | 1.432 | 1.381 (1.059–1.801) | .017 |
| PARKINSON_DISEASE YES | 1.978 | ||
| MULTIPLE_SCLEROSIS NO | 1.433 | 1.255 (0.956–1.647) | .101 |
| MULTIPLE_SCLEROSIS YES | 1.798 | ||
| SEIZURE_OR_EPILEPSY NO | 1.432 | 1.137 (1.006–1.285) | .040 |
| SEIZURE_OR_EPILEPSY YES | 1.627 | ||
| STROKE NO | 1.421 | 1.722 (1.562–1.899) | <.001 |
| STROKE YES | 2.446 | ||
| ORGAN_TRANSPLANT NO | 1.433 | 1.116 (0.919–1.355) | .269 |
| ORGAN_TRANSPLANT YES | 1.598 | ||
| ASTHMA NO | 1.398 | 1.365 (1.308–1.425) | <.001 |
| ASTHMA YES | 1.908 | ||
| BRONCHITIS NO | 1.423 | 1.295 (1.204–1.392) | <.001 |
| BRONCHITIS YES | 1.843 | ||
| CHRONIC_BRONCHITIS_OR_EMPHYSEMA NO | 1.395 | 1.553 (1.476–1.633) | <.001 |
| CHRONIC_BRONCHITIS_OR_EMPHYSEMA YES | 2.167 | ||
| RESPIRATORY_OR_LUNG_PROBLEM NO | 1.445 | 0.579 (0.531–0.631) | <.001 |
| RESPIRATORY_OR_LUNG_PROBLEM YES | 0.837 | ||
| SINUSITIS NO | 1.425 | 1.203 (1.123–1.288) | <.001 |
| SINUSITIS YES | 1.714 | ||
| SLEEP_APNEA NO | 1.419 | 1.353 (1.266–1.448) | <.001 |
| SLEEP_APNEA YES | 1.921 | ||
| CHRONS_DISEASE NO | 1.433 | 1.110 (0.856–1.438) | .431 |
| CHRONS_DISEASE YES | 1.590 | ||
| TUBERCULOSIS NO | 1.424 | 1.369 (1.257–1.490) | <.001 |
| TUBERCULOSIS YES | 1.949 | ||
| CIRRHOSIS_OR_CHRONIC_HEPATITIS NO | 1.425 | 1.372 (1.258–1.497) | <.001 |
| CIRRHOSIS_OR_CHRONIC_HEPATITIS YES | 1.955 | ||
| GASTRO_INTESTINAL_DISORDERS NO | 1.444 | 0.600 (0.550–0.654) | <.001 |
| GASTRO_INTESTINAL_DISORDERS YES | 0.866 | ||
| HEPATITIS NO | 1.418 | 1.343 (1.261–1.430) | <.001 |
| HEPATITIS YES | 1.904 |
*Negative binomial regression models were used to assess associations between medical conditions and tooth loss with results presented as incident rate ratios (RRs) and their corresponding 95% confidence intervals. The level of significance was set at .05.
The multivariable negative binomial regression analysis for the association between systemic medical conditions and number of teeth lost adjusted for age and gender is shown in Table 4. Individuals self-reporting anaemia, bleeding disorders, cardiovascular diseases, heart attack, high blood pressure, implanted defibrillator, smoking, cocaine use, marijuana use, methamphetamine use, diabetes, kidney disease, renal failure, arthritis, lupus, depression, stroke, asthma, and chronic bronchitis exhibited a significantly higher incident rate of tooth loss (P < .05). In contrast, patients with gastrointestinal disorders and respiratory or lung problems displayed a significantly lower incident rate of tooth loss (P < .001).
Table 4.
Multivariable negative binomial regression analysis for the association between systemic medical conditions and number of tooth loss adjusted for age and gender.
| Self-reported systemic medical conditions and smoking | RR | 95% CI | P value* |
|---|---|---|---|
| ANEMIA | 1.280 | (1.180–1.388) | <.001 |
| BLEEDING_DISORDERS | 1.469 | (1.356–1.592) | <.001 |
| LYMPHOMA | 1.390 | (1.044–1.850) | .700 |
| BLOOD_HEMOTOLOGICAL_ DISORDERS | 1.025 | (0.929–1.132) | >.99 |
| LEUKEMIA | 1.328 | (0.860–2.051) | >.99 |
| MULTIPLE_MYELOMA | 0.512 | (0.145–1.805) | >.99 |
| MALIGNANT | 1.003 | (0.962–1.046) | >.99 |
| ANGINA | 1.155 | (1.018–1.309) | .700 |
| CARDIOVASCULAR_HEART_ PROBLEM | 1.191 | (1.156–1.227) | <.001 |
| CONGENITAL_HEART_DISEASE | 1.105 | (0.919–1.329) | >.99 |
| CORONARY_HEART_DISEASE | 1.125 | (0.998–1.267) | >.99 |
| HISTORY_OF_ENDOCARDITIS | 0.753 | (0.552–1.026) | >.99 |
| HEART_ATTACK | 1.189 | (1.078–1.311) | .018 |
| HIGH_BLOOD_PRESSURE | 1.327 | (1.290–1.365) | <.001 |
| IMPLANT_DEFIBRILLATOR | 1.350 | (1.252–1.454) | <.001 |
| RHEUMATIC_FEVER | 0.977 | (0.738–1.293) | >.99 |
| SMOKING | 1.501 | (1.450–1.553) | <.001 |
| COCAINE_USE | 1.309 | (1.132–1.514) | .010 |
| HEROIN_USE | 1.584 | (0.850–2.953) | >.99 |
| MARIJUANA_USE | 1.364 | (1.265–1.471) | <.001 |
| METHAMPHETAMINE_USE | 2.501 | (1.919–3.259) | <.001 |
| ANOREXIA | 1.242 | (1.033–1.493) | .635 |
| BULIMIA | 1.283 | (0.957–1.720) | >.99 |
| ANDRENAL_GLAND_DISORDER | 0.875 | (0.575–1.332) | >.99 |
| DIABETES | 1.355 | (1.303–1.408) | <.001 |
| THYROID_PROBLEMS | 0.959 | (0.914–1.007) | >.99 |
| GLAUCOMA | 1.017 | (0.958–1.080) | >.99 |
| AIDS | 1.160 | (0.687–1.960) | >.99 |
| HIV | 1.099 | (0.931–1.297) | >.99 |
| STD | 1.155 | (1.017–1.312) | .718 |
| DIALYSIS | 1.292 | (1.053–1.585) | .437 |
| KIDNEY | 1.267 | (1.209–1.328) | <.001 |
| RENAL_FAILURE_OR_ INSUFFICIENCY | 1.315 | (1.176–1.471) | <.001 |
| ARTHRITIS | 1.139 | (1.101–1.179) | <.001 |
| LUPUS | 1.482 | (1.205–1.823) | .007 |
| OSTEOPOROSIS | 1.010 | (0.947–1.078) | >.99 |
| DEMENTIA | 1.047 | (0.873–1.257) | >.99 |
| ANXIETY | 1.046 | (0.993–1.101) | >.99 |
| DEPRESSION | 1.414 | (1.362–1.469) | <.001 |
| PARKINSON_DISEASE | 0.993 | (0.768–1.285) | >.99 |
| MULTIPLE_SCLEROSIS | 1.238 | (0.951–1.613) | >.99 |
| SEIZURE_OR_EPILEPSY | 1.188 | (1.054–1.338) | .150 |
| STROKE | 1.397 | (1.270–1.536) | <.001 |
| ORGAN_TRANSPLANT | 0.949 | (0.785–1.148) | >.99 |
| ASTHMA | 1.307 | (1.253–1.363) | <.001 |
| BRONCHITIS | 1.064 | (0.991–1.143) | >.99 |
| CHRONIC_BRONCHITIS_OR_ EMPHYSEMA | 1.460 | (1.390–1.533) | <.001 |
| RESPIRATORY_OR_LUNG_PROBLEM | 0.529 | (0.485–0.576) | <.001 |
| SINUSITIS | 1.061 | (0.992–1.134) | >.99 |
| SLEEP_APNEA | 1.111 | (1.040–1.186) | .059 |
| CHRONS_DISEASE | 1.138 | (0.883–1.467) | >.99 |
| TUBERCULOSIS | 1.016 | (0.935–1.104) | >.99 |
| CIRRHOSIS_OR_CHRONIC_ HEPATITIS | 1.061 | (0.974–1.155) | >.99 |
| GASTRO_INTESTINAL_DISORDERS | 0.541 | (0.496–0.590) | <.001 |
| HEPATITIS | 1.123 | (1.056–1.195) | .008 |
Multivariable regression models were explored adjusting for the effects of age and gender. Holm method is used to adjust P values for multiple comparison.
Association between systemic medical conditions and periodontal status
The multivariable logistic regression analysis for the association between systemic medical conditions and periodontal status adjusted for age and gender is shown in Table 5. Individuals reporting lymphoma, blood haematologic disorders, congenital heart disease, high blood pressure, smoking, marijuana use, methamphetamine use, diabetes, glaucoma, dialysis, seizure or epilepsy, bronchitis, sinusitis, tuberculosis, cirrhosis or chronic hepatitis, gastrointestinal disorders, and hepatitis exhibited significantly higher odds of having periodontitis (P < .05). Anaemia, bleeding disorders, cancer, anorexia, thyroid problems, kidney disease, osteoporosis, dementia, anxiety, depression, asthma, and chronic bronchitis or emphysema were significantly less likely to be associated with periodontitis (P < .05). Methamphetamine users displayed the highest odds of having periodontitis (OR, 2.891; 95% CI, 2.09–4.01) amongst all significant conditions.
Table 5.
Multivariable logistic regression analysis for the association between systemic medical conditions and periodontal status adjusted for age and gender.
| Self-reported systemic medical conditions and smoking | OR | 95% CI | P value* |
|---|---|---|---|
| ANEMIA | 0.750 | (0.679–0.828) | <.001 |
| BLEEDING_DISORDERS | 0.706 | (0.640–0.779) | <.001 |
| LYMPHOMA | 1.868 | (1.331–2.621) | .009 |
| BLOOD_HEMOTOLOGICAL_ DISORDERS | 1.241 | (1.108–1.390) | .006 |
| LEUKEMIA | 1.571 | (0.926–2.666) | >.99 |
| MULTIPLE_MYELOMA | 1.183 | (0.313–4.466) | >.99 |
| MALIGNANT | 0.835 | (0.796–0.876) | <.001 |
| ANGINA | 0.899 | (0.777–1.041) | >.99 |
| CARDIOVASCULAR_HEART_ PROBLEM | 1.033 | (0.998–1.069) | >.99 |
| CONGENITAL_HEART_DISEASE | 1.656 | (1.325–2.071) | <.001 |
| CORONARY_HEART_DISEASE | 1.253 | (1.087–1.444) | .050 |
| HISTORY_OF_ENDOCARDITIS | 0.808 | (0.571–1.144) | >.99 |
| HEART_ATTACK | 0.974 | (0.869–1.091) | >.99 |
| HIGH_BLOOD_PRESSURE | 1.166 | (1.129–1.204) | <.001 |
| IMPLANT_DEFIBRILLATOR | 0.905 | (0.829–0.988) | .550 |
| RHEUMATIC_FEVER | 1.478 | (1.069–2.045) | .399 |
| SMOKING | 1.359 | (1.305–1.414) | <.001 |
| COCAINE_USE | 0.939 | (0.790–1.116) | >.99 |
| HEROIN_USE | 2.255 | (1.081–4.706) | .605 |
| MARIJUANA_USE | 1.655 | (1.517–1.805) | <.001 |
| METHAMPHETAMINE_USE | 2.891 | (2.089–4.001) | <.001 |
| ANOREXIA | 0.541 | (0.420–0.696) | <.001 |
| BULIMIA | 0.571 | (0.379–0.862) | .192 |
| ANDRENAL_GLAND_DISORDER | 1.245 | (0.781–1.984) | >.99 |
| DIABETES | 1.211 | (1.157–1.267) | <.001 |
| THYROID_PROBLEMS | 0.894 | (0.846–0.944) | .002 |
| GLAUCOMA | 1.145 | (1.068–1.227) | .004 |
| AIDS | 0.701 | (0.377–1.304) | >.99 |
| HIV | 1.040 | (0.861–1.257) | >.99 |
| STD | 0.969 | (0.835–1.125) | >.99 |
| DIALYSIS | 1.926 | (1.510–2.458) | <.001 |
| KIDNEY | 0.863 | (0.817–0.912) | <.001 |
| RENAL_FAILURE_OR_ INSUFFICIENCY | 1.085 | (0.952–1.238) | >.99 |
| ARTHRITIS | 0.973 | (0.935–1.012) | >.99 |
| LUPUS | 0.969 | (0.759–1.237) | >.99 |
| OSTEOPOROSIS | 0.822 | (0.763–0.885) | <.001 |
| DEMENTIA | 0.562 | (0.454–0.696) | <.001 |
| ANXIETY | 0.713 | (0.670–0.758) | <.001 |
| DEPRESSION | 0.673 | (0.642–0.706) | <.001 |
| PARKINSON_DISEASE | 0.809 | (0.603–1.086) | >.99 |
| MULTIPLE_SCLEROSIS | 0.761 | (0.555–1.042) | >.99 |
| SEIZURE_OR_EPILEPSY | 1.259 | (1.098–1.444) | .028 |
| STROKE | 0.871 | (0.779–0.974) | .357 |
| ORGAN_TRANSPLANT | 0.956 | (0.770–1.188) | >.99 |
| ASTHMA | 0.668 | (0.634–0.703) | <.001 |
| BRONCHITIS | 1.548 | (1.425–1.682) | <.001 |
| CHRONIC_BRONCHITIS_OR_ EMPHYSEMA | 0.660 | (0.621–0.701) | <.001 |
| RESPIRATORY_OR_LUNG_ PROBLEM | 1.119 | (1.022–1.225) | .357 |
| SINUSITIS | 1.144 | (1.059–1.235) | .017 |
| SLEEP_APNEA | 1.123 | (1.041–1.211) | .073 |
| CHRONS_DISEASE | 1.128 | (0.842–1.512) | >.99 |
| TUBERCULOSIS | 1.224 | (1.111–1.348) | .001 |
| CIRRHOSIS_OR_CHRONIC_ HEPATITIS | 1.969 | (1.776–2.182) | <.001 |
| GASTRO_INTESTINAL_ DISORDERS | 1.297 | (1.185–1.419) | <.001 |
| HEPATITIS | 1.258 | (1.171–1.350) | <.001 |
Multivariable regression models were explored adjusting for the effects of age and gender. Holm method is used to adjust P values for multiple comparison.
Discussion
The importance of the oral-systemic connection has been highlighted in recent years. Especially during the COVID-19 pandemic, it has been demonstrated that oral health is of paramount importance for the maintenance of systemic health.17 The results of the present investigation indicated that patients with anaemia, bleeding disorders, cardiovascular diseases, heart attack, high blood pressure, implanted defibrillator, smoking, cocaine use, marijuana use, methamphetamine use, diabetes, kidney disease, renal failure, arthritis, lupus, depression, stroke, asthma, and chronic bronchitis exhibited a significantly higher number of missing teeth. In regards to periodontitis, individuals reported lymphoma, blood haematologic disorders, congenital heart disease, high blood pressure, smoking, marijuana use, methamphetamine use, diabetes, glaucoma, dialysis, seizure or epilepsy, bronchitis, sinusitis, tuberculosis, gastrointestinal disorders, and hepatitis exhibited significantly higher odds of having periodontitis (P < .05).
The relationship between periodontitis and other pathologic systemic conditions has been suggested in the literature, but the biological connection between periodontal disease and systemic conditions is still unknown. A number of theories have been proposed to explain these associations including bacteraemia, low-grade systemic inflammation, and increased myelopoietic activity. As periodontitis is characterised by the presence of periodontal pathogens in the oral cavity, bacteria or activated lymphocytes may disseminate to different tissues and may lead to inflammatory and functional complications that initiate comorbidities.4 Periodontitis is also associated with bacteraemia and systemic inflammation, and it may induce acute response as well as metabolic and inflammatory alterations in the liver and bone marrow, which can connect different chronic inflammatory diseases.4 Expression of virulence factors produced by periodontopathogens and the presence of pathogens in non-oral tissues may support the biological relationship between chronic oral diseases such as periodontal disease and systemic diseases.18 Moreover, individuals with severe periodontitis demonstrate elevated levels of pro-inflammatory mediators as well as increased neutrophil counts in the blood.4 Therefore, the plausible connection between systemic health and periodontal health is evident.
In this investigation, environmental factors including smoking, marijuana use, and methamphetamine use were associated with periodontitis as well as a higher number of missing teeth. Smoking affects all components of the inflammatory response, both the innate and immune host response, and neutrophils in smokers have shown decreased chemotaxis, phagocytosis, and adherence.19 A higher prevalence of severe periodontal disease and increased tooth loss have been associated with tobacco use.20,21 Periodontal disease and tooth loss are also more prevalent amongst people who use drugs due to a number of reasons including poor nutrition, oral hygiene, and limited access to dental care facilities.22 This study adds to the limited current knowledge regarding the effect of drugs on periodontal status and tooth loss.
Diabetes was also significantly associated with periodontitis and the number of missing teeth in the present investigation. This is in agreement with previous studies that have shown the positive bidirectional association between periodontal disease and diabetes mellitus.23,24 Both conditions are driven by inflammatory processes, which may explain their association.25 Diagnoses of moderate-severe and severe periodontitis have been associated with hypertension, whilst periodontal treatment leads to improvement in hypertensive and prehypertensive individuals.26,27 In addition, a systematic review of the literature showed that individuals with tooth loss exhibit a higher risk for hypertension and that hypertensive individuals have a higher risk of tooth loss.28 This suggests a bidirectional association between tooth loss and hypertension. In the present study, older individuals and males were more likely to have periodontitis, which is in agreement with the updated prevalence of periodontitis in adults in the US that reported an 8.9% prevalence of severe periodontal disease and a positive significant correlation between age and male gender.29
It is of paramount importance to exercise caution in interpreting the data and analysis due to the limitations of the study. This is a retrospective study that has evaluated electronic health records, and its design may inherently lead to flaws. Prospective longitudinal studies are required to establish cause-and-effect relationships amongst periodontitis, tooth loss, and systemic conditions. In the present investigation, patient self-reported data were utilised, rather than medical records, which may exhibit limitations due to bias in patient recall, untruthful responses as a result of social desirability, and a patient's lack of knowledge.30 However, it has been documented that self-reported measures are accurate for chronic conditions and routine screening exams and may also provide valuable information for broad measures of population prevalence.31
A strength of this investigation was the use of data from a large record database (BigMouth) that has in-depth information of patients’ dental and medical histories and are derived from a variety of institutions and providers. Pooling datasets from different sources provides a greater picture of types of patients. It may facilitate the investigation of conditions that are not very prevalent and can lead to a better understanding of their effect on oral diseases including periodontitis and tooth loss. Many systemic diseases that are not often reported in the periodontal literature such as tuberculosis, gastrointestinal disorders, bronchitis, multiple sclerosis, sexually transmitted diseases, drug use, and lymphoma are analysed in this study.32 A number of studies have demonstrated an association between systemic diseases and periodontitis.33 The present investigation has added new candidates in the oral-systemic connections that need to be further explored in prospective longitudinal studies. In addition, the present study investigates the association of systemic conditions with periodontal diseases and tooth loss separately, and many of the results are confirmed with the 2 methodologies. With the inclusion of more than 100,000 dental records, this is one of the largest cohorts analysed in the history of dental research and may guide new research towards mapping connections between periodontitis and systemic conditions.
Conclusions
Within the limitations of this retrospective study, the association of a number of systemic conditions with periodontitis and tooth loss was identified. Patients with anaemia, bleeding disorders, cardiovascular diseases, heart attack, high blood pressure, implanted defibrillator, smoking, cocaine use, marijuana use, methamphetamine use, diabetes, kidney disease, renal failure, arthritis, lupus, depression, stroke, asthma, and chronic bronchitis exhibited a significantly higher number of missing teeth. Individuals reporting lymphoma, blood haematologic disorders, congenital heart disease, high blood pressure, smoking, marijuana use, methamphetamine use, diabetes, glaucoma, dialysis, seizure or epilepsy, bronchitis, sinusitis, tuberculosis, gastrointestinal disorders, and hepatitis exhibited significantly higher odds of having periodontitis. Future studies should investigate further the potential causative relationships amongst these conditions, tooth loss, and periodontitis.
Conflict of Interest
None disclosed.
Acknowledgments
Acknowledgements
Data for this research were obtained from the BigMouth Dental Data Repository. The authors would like to thank the Consortium for Oral Health Research and Informatics clinical research committee. Research reported in this publication was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health Award Number UL1-TR002494. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This research was further supported by a University of Minnesota School of Dentistry, Division of Periodontology grant (L.F.W).
Author contributions
Authors' contributions: GSC and LFW conceived the study. GSC, ZJ, NM, and LFW designed the study. GSC completed the data collection. ZJ and NM analysed the data. GSC wrote the paper. GSC, ZJ, NM, and LFW reviewed and edited the manuscript. All authors read and approved the final manuscript.
Funding
Research reported in this publication was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health Award Number UL1-TR002494.
Footnotes
Supplementary material associated with this article can be found in the online version at doi:10.1016/j.identj.2023.08.002.
Appendix. Supplementary materials
REFERENCES
- 1.Lamont RJ, Koo H, Hajishengallis G. The oral microbiota: dynamic communities and host interactions. Nat Rev Microbiol. 2018;16(12):745–759. doi: 10.1038/s41579-018-0089-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.NCD Countdown 2030 Collaborators NCD Countdown 2030: worldwide trends in non-communicable disease mortality and progress towards Sustainable Development Goal target 3.4. Lancet. 2018;392(10152):1072–1088. doi: 10.1016/S0140-6736(18)31992-5. [DOI] [PubMed] [Google Scholar]
- 3.Kassebaum NJ, Bernabé E, Dahiya M, Bhandari B, Murray CJ, Marcenes W. Global burden of severe periodontitis in 1990-2010: a systematic review and meta-regression. J Dent Res. 2014;93(11):1045–1053. doi: 10.1177/0022034514552491. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Hajishengallis G, Chavakis T. Local and systemic mechanisms linking periodontal disease and inflammatory comorbidities. Nat Rev Immunol. 2021;21(7):426–440. doi: 10.1038/s41577-020-00488-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Tonetti MS, Van Dyke TE, Working group 1 of the joint EFP/AAP workshop Periodontitis and atherosclerotic cardiovascular disease: consensus report of the Joint EFP/AAP Workshop on Periodontitis and Systemic Diseases. J Periodontol. 2013;84(4 Suppl):S24–S29. doi: 10.1902/jop.2013.1340019. [DOI] [PubMed] [Google Scholar]
- 6.Chapple ILC, Genco R, Working group 2 of the joint EFP/AAP workshop Diabetes and periodontal diseases: consensus report of the Joint EFP/AAP Workshop on Periodontitis and Systemic Diseases. J Periodontol. 2013;84(4 Suppl):S106–S112. doi: 10.1902/jop.2013.1340011. [DOI] [PubMed] [Google Scholar]
- 7.Sanz M, Kornman K, Working Group 3 of the Joint EFP/AAP Workshop Periodontitis and adverse pregnancy outcomes: consensus report of the Joint EFP/AAP Workshop on Periodontitis and Systemic Diseases. J Clin Periodontol. 2013;40(Suppl 14):S164–S169. doi: 10.1111/jcpe.12083. [DOI] [PubMed] [Google Scholar]
- 8.Linden GJ, Herzberg MC, Working group 4 of the Joint EFP/AAP Workshop Periodontitis and systemic diseases: a record of discussions of working group 4 of the Joint EFP/AAP Workshop on Periodontitis and Systemic Diseases. J Clin Periodontol. 2013;40(Suppl 14):S20–S23. doi: 10.1111/jcpe.12091. [DOI] [PubMed] [Google Scholar]
- 9.Linden GJ, Lyons A, Scannapieco FA. Periodontal systemic associations: review of the evidence. J Periodontol. 2013;84(4 Suppl):S8–S19. doi: 10.1902/jop.2013.1340010. [DOI] [PubMed] [Google Scholar]
- 10.Monsarrat P, Blaizot A, Kémoun P, et al. Clinical research activity in periodontal medicine: a systematic mapping of trial registers. J Clin Periodontol. 2016;43(5):390–400. doi: 10.1111/jcpe.12534. [DOI] [PubMed] [Google Scholar]
- 11.Loos BG. Periodontal medicine: work in progress. J Clin Periodontol. 2016;43:470–471. doi: 10.1111/jcpe.12550. [DOI] [PubMed] [Google Scholar]
- 12.Hajishengallis G. Immunomicrobial pathogenesis of periodontitis: keystones, pathobionts, and host response. Trends Immunol. 2014;35(1):3–11. doi: 10.1016/j.it.2013.09.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Papapanou PN, Sanz M, Buduneli N, et al. Periodontitis: Consensus report of workgroup 2 of the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions. J Periodontol. 2018;89(Suppl 1)):S173–S182. doi: 10.1002/JPER.17-0721. [DOI] [PubMed] [Google Scholar]
- 14.Albandar JM, Susin C, Hughes FJ. Manifestations of systemic diseases and conditions that affect the periodontal attachment apparatus: case definitions and diagnostic considerations. J Clin Periodontol. 2018;45(Suppl 20)):S171–S189. doi: 10.1111/jcpe.12947. [DOI] [PubMed] [Google Scholar]
- 15.Birkhead GS, Klompas M, Shah NR. Uses of electronic health records for public health surveillance to advance public health. Annu Rev Publ Health. 2015;36:345e59. doi: 10.1146/annurev-publhealth-031914-122747. [DOI] [PubMed] [Google Scholar]
- 16.Walji MF, Kalenderian E, Stark PC, et al. BigMouth: a multi-institutional dental data repository. J Am Med Inform Assoc. 2014;21(6):1136–1140. doi: 10.1136/amiajnl-2013-002230. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Qi X, Northridge ME, Hu M, Wu B. Oral health conditions and COVID-19: a systematic review and meta-analysis of the current evidence. Aging Health Res. 2022;2(1) doi: 10.1016/j.ahr.2022.100064. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Van Dyke TE, van Winkelhoff AJ. Infection and inflammatory mechanisms. J Periodontol. 2013;84(4 Suppl):S1–S7. doi: 10.1902/jop.2013.1340018. [DOI] [PubMed] [Google Scholar]
- 19.Strzelak A, Ratajczak A, Adamiec A, Feleszko W. Tobacco smoke induces and alters immune responses in the lung triggering inflammation, allergy, asthma and other lung diseases: a mechanistic review. Int J Environ Res Public Health. 2018;15(5):1033. doi: 10.3390/ijerph15051033. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Souto MLS, Rovai ES, Villar CC, Braga MM, Pannuti CM. Effect of smoking cessation on tooth loss: a systematic review with meta-analysis. BMC Oral Health. 2019;19(1):245. doi: 10.1186/s12903-019-0930-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Leite FRM, Nascimento GG, Scheutz F, López R. Effect of smoking on periodontitis: a systematic review and meta-regression. Am J Prev Med. 2018;54(6):831–841. doi: 10.1016/j.amepre.2018.02.014. [DOI] [PubMed] [Google Scholar]
- 22.Yazdanian M, Armoon B, Noroozi A, et al. Dental caries and periodontal disease among people who use drugs: a systematic review and meta-analysis. BMC Oral Health. 2020;20(1):44. doi: 10.1186/s12903-020-1010-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Stöhr J, Barbaresko J, Neuenschwander M, Schlesinger S. Bidirectional association between periodontal disease and diabetes mellitus: a systematic review and meta-analysis of cohort studies. Sci Rep. 2021;11(1):13686. doi: 10.1038/s41598-021-93062-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Ahmadinia AR, Rahebi D, Mohammadi M, et al. Association between type 2 diabetes (T2D) and tooth loss: a systematic review and meta-analysis. BMC Endocr Disord. 2022;22(1):100. doi: 10.1186/s12902-022-01012-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Engebretson SP, Hey-Hadavi J, Ehrhardt FJ, et al. Gingival crevicular fluid levels of interleukin-1beta and glycemic control in patients with chronic periodontitis and type 2 diabetes. J Periodontol. 2004 Sep;75(9):1203–1208. doi: 10.1902/jop.2004.75.9.1203. [DOI] [PubMed] [Google Scholar]
- 26.Muñoz Aguilera E, Suvan J, Buti J, et al. Periodontitis is associated with hypertension: a systematic review and meta-analysis. Cardiovasc Res. 2020;116(1):28–39. doi: 10.1093/cvr/cvz201. [DOI] [PubMed] [Google Scholar]
- 27.Sharma S, Sridhar S, McIntosh A, et al. Periodontal therapy and treatment of hypertension-alternative to the pharmacological approach. A systematic review and meta-analysis. Pharmacol Res. 2021;166 doi: 10.1016/j.phrs.2021.105511. [DOI] [PubMed] [Google Scholar]
- 28.Xu K, Yu W, Li Y, et al. Association between tooth loss and hypertension: a systematic review and meta-analysis. J Dent. 2022;123 doi: 10.1016/j.jdent.2022.104178. [DOI] [PubMed] [Google Scholar]
- 29.Eke PI, Dye BA, Wei L, et al. Update on prevalence of periodontitis in adults in the United States: NHANES 2009 to 2012. J Periodontol. 2015;86(5):611–622. doi: 10.1902/jop.2015.140520. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Newell SA, Girgis A, Sanson-Fisher RW, Savolainen NJ. The accuracy of self-reported health behaviors and risk factors relating to cancer and cardiovascular disease in the general population: a critical review. Am J Prev Med. 1999;17(3):211–229. doi: 10.1016/s0749-3797(99)00069-0. [DOI] [PubMed] [Google Scholar]
- 31.Martin LM, Leff M, Calonge N, Garrett C, Nelson DE. Validation of self-reported chronic conditions and health services in a managed care population. Am J Prev Med. 2000;18(3):215–218. doi: 10.1016/s0749-3797(99)00158-0. [DOI] [PubMed] [Google Scholar]
- 32.Walji MF, Spallek H, Kookal KK, et al. BigMouth: development and maintenance of a successful dental data repository. J Am Med Inform Assoc. 2022;29(4):701–706. doi: 10.1093/jamia/ocac001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Winning L, Linden GJ. Periodontitis and systemic disease: association or causality? Curr Oral Health Rep. 2017;4(1):1–7. doi: 10.1007/s40496-017-0121-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.