Burden of Systemic Diseases and Associated Factors Among Dental Outpatients in a Routine Care Setting: A Cross-Sectional Study

Burden of Systemic Diseases and Associated Factors Among Dental Outpatients in a Routine Care Setting: A Cross-Sectional Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Burden of Systemic Diseases and Associated Factors Among Dental Outpatients in a Routine Care Setting: A Cross-Sectional Study Ali Altındağ, Sultan Uzun, Hilal Yalın Özdemir, İrem Meriç, Ömer Altındağ This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9084367/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : Systemic diseases are common among dental patients and may directly affect treatment planning, patient safety, and clinical outcomes. Dental outpatient settings may also provide an accessible opportunity to identify the burden of chronic conditions in routine care. This study aimed to assess the prevalence and distribution of systemic diseases among dental outpatients and to identify demographic and clinical factors associated with systemic disease status. Methods : This cross-sectional study included 15,002 patients aged 15 years and older who attended a university-based dental outpatient clinic between January and December 2022. Demographic characteristics, medical anamnesis records, and medication histories were obtained from the digital patient management system. Associations were examined using chi-square tests, and independent predictors were evaluated using multivariable binary logistic regression. A sensitivity analysis was also performed using a revised outcome that excluded psychiatric disorders from the composite systemic disease variable. Results: At least one systemic disease was recorded in 25.1% of patients. Hypertension (8.5%), diabetes mellitus (6.8%), and cardiovascular diseases (5.8%) were the most common conditions. The prevalence of systemic disease increased markedly with age, reaching 67.6% among patients aged 60 years and older. In multivariable analysis, older age, female sex, and psychiatric disorder status were independently associated with systemic disease, whereas smoking did not show an independent association. In the sensitivity analysis excluding psychiatric disorders from the outcome, older age remained the strongest predictor of systemic disease, female sex remained significantly associated, and psychiatric disorder status continued to show an independent association, although with a substantially attenuated effect size. Conclusions: A considerable proportion of dental outpatients had at least one systemic disease, with the burden concentrated in older adults and other clinically vulnerable groups. These findings highlight the value of routine medical anamnesis in dental settings and support the role of oral healthcare services in identifying medically at-risk patients and contributing to more integrated care. anamnesis dentistry medical condition prevalence public health systemic diseases Introduction Anamnesis is the systematic collection of information on a patient’s medical conditions, medication use, and reason for seeking care, and it remains essential for accurate diagnosis and safe dental decision-making [1]. A thorough medical history allows dentists to identify risks that may influence treatment planning, prescribing, local anesthesia, surgical procedures, and infection control [1, 2]. This is particularly important because some patients may underestimate the relevance of their systemic conditions, be unaware of drug-related oral effects, or fail to adhere to prescribed therapies [3, 4]. Beyond its clinical importance, oral health is increasingly recognized as part of general health. The World Health Organization (WHO) identifies oral health as a key indicator of overall health, well-being, and quality of life, and emphasizes that oral conditions should be addressed within broader health systems and universal health coverage frameworks [5, 6]. In parallel with population ageing, multimorbidity—commonly defined as the coexistence of two or more chronic conditions—has become a major public health challenge because it increases care complexity, healthcare utilization, and the need for integrated management [7, 8]. Dental settings are therefore not only sites of oral care, but also important points of contact where the broader burden of systemic disease may be recognized in routine practice. The prevalence of systemic diseases among dental patients varies across settings, yet consistently rises with age and mirrors the epidemiology of noncommunicable diseases in the wider community [1, 5]. Identifying this burden in real-world dental outpatient populations may support chairside risk assessment, more appropriate referral pathways, and better integration between dental care and general health services, particularly in middle-income settings where chronic disease burdens are increasing [3, 9]. This issue is further reinforced by the growing retention of natural dentition and the increasing number of patients receiving long-term pharmacotherapy for chronic medical conditions [1, 10]. As a result, dentists are encountering more medically compromised individuals in daily practice, making competence in systemic disease recognition and medication-related risk assessment increasingly important [10]. Within this context, psychiatric disorders also deserve attention, as both the disorders themselves and their pharmacological treatment may contribute to xerostomia, caries susceptibility, bruxism, and periodontal vulnerability, thereby complicating dental management [4, 11]. Despite growing recognition of dental clinics as valuable settings for systemic health assessment, contemporary large-scale data on the prevalence and determinants of systemic diseases among dental outpatients remain limited in many regions. Therefore, this study aimed to quantify the burden and distribution of systemic diseases among patients attending a dental clinic and to identify demographic and clinical factors associated with systemic disease status in a real-world outpatient population. Materials and Methods Study Design and Ethical Approval This study was designed as a retrospective cross-sectional analysis. The study protocol was conducted in accordance with the principles of the Declaration of Helsinki and received approval from the Local Pharmaceutical and Non-Device Research Ethics Committee (Approval No: 2022/173). Access to the study data was restricted to the research team, and all patient information was evaluated in anonymized form. Study Population and Data Collection The study population consisted of patients aged 15 years and older who attended the Initial Examination Clinic of the Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, X University, between January 2022 and December 2022. Patients were eligible for inclusion if their anamnesis information was fully recorded in the digital patient management system. No additional clinical examinations, laboratory tests, or imaging procedures were requested for the purposes of this study; all analyses were based solely on archived anamnesis records. For each patient, demographic variables including age and sex were recorded. Medical history data were systematically reviewed to identify the presence of systemic conditions, including cardiovascular, endocrine, gastrointestinal, respiratory, hematological, oncological, and other chronic diseases, as well as current medication use. Age was categorized into four predefined groups: <30 years, 30–44 years, 45–59 years, and ≥60 years. Definition of Systemic Condition and Comorbidity Burden Systemic condition status was defined as the presence of at least one documented chronic systemic disease in the medical history records. In addition, comorbidity burden was categorized based on the total number of systemic conditions reported for each patient and classified into four groups: no systemic condition (0), one condition (1), two conditions (2), and three or more conditions (≥3). Psychiatric disorder status was identified based on medication history, with the use of antidepressants and/or higher-intensity psychotropic medications considered indicative of a clinically relevant psychiatric disorder. Statistical Analysis Descriptive statistics were calculated to summarize demographic characteristics and the prevalence of systemic conditions. Continuous variables were presented as mean ± standard deviation (SD), median, and range, while categorical variables were expressed as frequencies and percentages. Associations between systemic condition status (yes/no) and categorical variables such as age group, sex, smoking status, and psychiatric disorder status were assessed using the Pearson chi-square test. Fisher’s exact test was applied where appropriate. Effect sizes for significant associations were quantified using Cramer’s V and interpreted according to conventional thresholds. The distribution of comorbidity burden across demographic and clinical subgroups was evaluated using chi-square analysis, with Cramer’s V reported as a measure of association strength. To identify independent factors associated with the presence of a systemic condition, a multivariable binary logistic regression analysis was performed. Variables included in the model were age (continuous), sex, smoking status, and psychiatric disorder status. Results were reported as odds ratios (ORs) with corresponding 95% confidence intervals (CIs). Sensitivity analysis: To assess whether the strong association observed for psychiatric disorder status was driven by overlap with the composite outcome definition, a sensitivity analysis was performed using a revised outcome that excluded psychiatric disorders from the systemic disease variable. Multivariable logistic regression was then repeated with non-psychiatric systemic disease as the dependent variable. All statistical analyses were performed using IBM SPSS Statistics for Windows, version 22.0 (IBM Corp., Armonk, NY, USA). A two-sided p-value <0.05 was considered statistically significant. Results The study included 15,002 patients with a mean age of 39.06 ± 15.09 years (median: 37.0 years). Baseline demographic and clinical characteristics of the study population are presented in Table 1. Approximately two-thirds of the study population were younger than 45 years. Overall, 25.1% of patients were classified as having at least one systemic condition. Psychiatric disorders were identified in 2.4% of the patients. Most patients reported no history of drug or food allergy (98.2%). Hypertension was the most frequently reported systemic condition in the overall study population (8.5%), followed by diabetes mellitus (6.8%) and cardiovascular disease (5.8%). Hypertension, respiratory disease, and thyroid disease were more prevalent among female patients, whereas diabetes mellitus, cardiovascular disease, and liver disease were more frequently reported among male patients (Table 2). A strong and statistically significant association was observed between age group and the presence of a systemic condition (χ² = 2926.9, p < 0.001), with a large effect size (Cramer’s V = 0.44). The prevalence of systemic conditions increased markedly with advancing age, reaching 67.6% among patients aged 60 years and older (Table 3). Sex was also significantly associated with systemic condition status (χ² = 24.8, p < 0.001); however, the effect size was small (Cramer’s V = 0.04), indicating limited clinical relevance. No statistically significant association was found between smoking status and the presence of a systemic condition (p = 0.138). Comorbidity burden increased markedly with advancing age (p < 0.001), with a large effect size (Cramer’s V = 0.49). While more than 90% of patients younger than 30 years had no comorbid conditions, only 32.4% of patients aged 60 years and older were free of comorbidity, and 13.3% presented with three or more conditions (Table 4). Sex was significantly associated with comorbidity burden (p < 0.001), although the effect size was small (Cramer’s V = 0.06). Smoking status was not significantly associated with comorbidity burden (p = 0.19). In contrast, psychiatric disorders showed a strong association with comorbidity burden (p < 0.001; Cramer’s V = 0.38). Nearly 40% of patients with psychiatric disorders had two or more comorbid conditions, compared with only 8.1% among those without psychiatric disorders. Increasing age was independently associated with the presence of a systemic condition, with an 8% increase in odds per additional year of age (OR = 1.08, 95% CI: 1.08–1.09; p < 0.001) (Table 5). Female sex was associated with a significantly higher likelihood of having a systemic condition compared with male sex (OR = 1.72, 95% CI: 1.57–1.89; p < 0.001). Smoking was not independently associated with systemic condition status in the multivariable model (OR = 1.23, 95% CI: 0.96–1.58; p = 0.098). Because psychiatric disorders were included in the composite systemic condition variable, an additional sensitivity analysis was performed using a revised outcome that excluded psychiatric disorders from the definition of systemic disease. In this analysis, increasing age remained the strongest independent predictor (OR = 1.08, 95% CI: 1.08–1.09; p < 0.001), and female sex also remained significantly associated (OR = 1.65, 95% CI: 1.50–1.80; p < 0.001). Psychiatric disorder status continued to show an independent association with non-psychiatric systemic disease, although the effect size was substantially attenuated (OR = 1.56, 95% CI: 1.22–1.99; p < 0.001). In contrast, smoking was no longer statistically significant in the sensitivity model (OR = 1.18, 95% CI: 0.93–1.50; p = 0.177) (Table 6). Accordingly, the very large odds ratio observed for psychiatric disorders in the primary model should be interpreted cautiously, as it was at least partly driven by structural overlap with the composite outcome definition. Discussion Dentists routinely encounter patients with systemic diseases in daily practice, and accurate medical anamnesis is essential for safe treatment planning and complication prevention [2, 10]. From a public health perspective, dental outpatient clinics may also function as accessible points for identifying chronic disease burden in individuals who may have limited contact with other healthcare services. In the present study, at least one systemic disease was identified in 25.1% of dental patients. This prevalence falls within the broad range reported in previous studies, where rates among dental populations vary from approximately 10% to nearly 70% depending on population structure, clinical setting, and case definitions [10, 12, 13]. Lower prevalence rates have been reported by Dhanuthai et al.[14] (12.2%), and Şener et al. [15] (24%), while higher rates have been observed in hospital-based or faculty settings, particularly in studies including older populations. Large-scale contemporary data further support this variability; for example, Aranda Romo et al. [16] reported a prevalence of 39.1% among more than 82,000 dental patients in a university clinic setting in Mexico, highlighting the influence of setting and population structure on observed prevalence estimates. Studies conducted in Turkey also demonstrate substantial heterogeneity. Hatipoğlu et al.[12] and Aydıntuğ et al.[17] reported prevalence rates exceeding 35%, whereas Şener et al.[15] (24%), Altan et al.[10] (24.1%), and Ciğerim [18](26%) reported figures closely aligned with the present findings. Differences across studies may be attributed to variations in age and sex distribution, socioeconomic background, referral patterns, and the operational definitions of systemic disease. Importantly, faculty-based clinics often serve medically vulnerable or referred patients, which may inflate prevalence estimates compared with general outpatient dental clinics. Regarding disease patterns, hypertension, diabetes mellitus, and cardiovascular diseases were the most common systemic conditions in the present cohort. This distribution is consistent with the broader epidemiology of noncommunicable diseases and supports the view that cardiometabolic conditions constitute a major component of medical burden in dental populations. Jain et al.[19] reported that cardiovascular risk factors frequently cluster in socially vulnerable communities, potentially leading to a high disease burden outside traditionally defined high-risk age groups. Similarly, Takeuchi et al. [20] showed that multimorbidity is highly prevalent in patients with heart failure and is strongly associated with adverse outcomes. Although our cohort was drawn from a dental setting rather than a medical one, these findings similarly suggest that dental services may encounter a meaningful burden of chronic cardiometabolic disease in routine care. In the present study, hypertension was the most frequently reported individual systemic condition, followed by diabetes mellitus and cardiovascular disease. This pattern is broadly consistent with the global burden of noncommunicable diseases, in which cardiovascular and metabolic disorders remain major contributors to morbidity and mortality [5]. Given their implications for invasive procedures, medical emergencies, and treatment planning, these conditions are particularly relevant in routine dental care. Previous studies have reported the prevalence of cardiovascular diseases among dental patients as 14.8% by Ciğerim [18] and 13.40% by Oktay et al. [21]. In our study, cardiovascular disease was recorded in 5.8% of patients, while hypertension, which may be considered part of the broader cardiometabolic burden encountered in dental practice, was present in 8.5%. Previous studies have reported hypertension prevalence rates of 7.5% [22], 9.95% [23], and 12.6% [7]. Given the high frequency of hypertension both in the general population and in dental settings, appropriate precautions during dental treatment remain particularly important. Diabetes mellitus represented the second most common systemic disease group in the present study, with a prevalence of 6.8%. This finding is consistent with the results reported by Shakir et al.[24] and Al-Bayaty et al.[7], as well as with previous studies conducted in the Turkish population [18, 22]. Because acute stress may predispose individuals with diabetes to metabolic complications, dentists should take appropriate precautions during dental treatment to reduce the risk of hyperglycemic or hypoglycemic coma. In addition, the potential for diabetes-related complications, including microvascular ischemia as well as macrovascular outcomes such as atherosclerosis and myocardial infarction, should be carefully considered in the dental management of diabetic patients [17]. Age was the strongest determinant of systemic disease burden in the present study. Although individuals aged 60 years and older represented a relatively small proportion of the study population, more than two-thirds of them had at least one systemic condition. This finding is in line with previous dental and epidemiologic studies showing that chronic disease burden increases markedly with age [7, 20, 25]. From a service planning perspective, this pattern suggests that aging dental populations may require increasingly integrated models of care, particularly in university and referral-based outpatient settings. Sex was statistically associated with systemic disease status, and female patients showed higher odds of having a systemic condition in both the primary and sensitivity models. However, the univariate effect size was small, suggesting that the contribution of sex should be interpreted cautiously at the population level. This pattern may reflect differences in healthcare-seeking behavior, medication use, or age distribution rather than a uniform biological effect across all disease categories [21, 23]. Although crude prevalence differed by sex, the adjusted findings indicate that sex-related differences in systemic disease burden are likely to be context-dependent and influenced by the composition of the study population. Smoking was not independently associated with systemic disease in the primary model, and this lack of significance was maintained in the sensitivity analysis. Although smoking remains a well-established risk factor for cardiometabolic and respiratory morbidity [19], the present findings suggest that its effect may be less pronounced in this dental outpatient population when considered alongside age, sex, and psychiatric disorder status. Psychiatric disorder status was also associated with systemic disease burden, particularly with greater comorbidity burden. Nearly 40% of patients with psychiatric disorders had two or more comorbid conditions, compared with 8.1% among those without psychiatric disorders. However, the very large odds ratio observed in the primary regression model should be interpreted cautiously, because psychiatric disorders were included within the composite systemic disease outcome. When a sensitivity analysis was performed using a revised outcome that excluded psychiatric disorders, the association remained statistically significant but was substantially attenuated. This indicates that the primary estimate was influenced, at least in part, by structural overlap in variable definition rather than by an isolated epidemiologic effect. Even so, the persistence of the association in the sensitivity model is consistent with previous literature showing that mental health conditions often coexist with greater medical complexity and treatment burden [26, 27]. For dental services, this is relevant not only clinically, but also from a public health standpoint, as patients with psychiatric disorders may require more coordinated and person-centered models of care. Overall, the present findings suggest that routine dental care settings can provide useful opportunities to recognize medically vulnerable patients, particularly older adults and individuals with complex comorbidity profiles. In this sense, dental clinics should not be viewed solely as treatment sites for oral conditions, but also as part of a broader health system in which medical history taking can support safer care, timely referral, and better integration between oral and general health services [20, 23, 27-30]. Future studies should use multicenter and longitudinal designs, and where possible incorporate more robust diagnostic definitions and social determinants of health, in order to better clarify the pathways linking systemic disease burden, mental health, and dental service utilization. Limitations This study has several limitations. First, its retrospective cross-sectional design precludes causal inference regarding the relationship between systemic diseases and associated factors. Second, all medical information was derived from anamnesis records, which may be subject to reporting bias or underreporting, particularly for conditions that patients perceive as unimportant or are unaware of. Third, psychiatric disorder status was operationalized using medication history rather than standardized psychiatric diagnoses, which may have introduced misclassification. In addition, because psychiatric disorders were part of the original composite systemic disease outcome, the association observed in the primary regression model was partly affected by structural overlap; although this was addressed through sensitivity analysis, the finding should still be interpreted cautiously. Finally, the study was conducted in a single university-based dental clinic, which may limit generalizability to other settings with different referral patterns, case mix, and healthcare access characteristics. The absence of detailed socioeconomic and healthcare utilization variables is another limitation, as these factors may influence both systemic disease burden and patterns of dental attendance. Despite these limitations, the large sample size and use of real-world clinical data provide useful insight into the burden of systemic disease among dental outpatients. Conclusions Systemic diseases were common among dental outpatients, with one in four patients presenting with at least one chronic condition. Cardiometabolic diseases accounted for a substantial share of this burden, and age was the strongest determinant of systemic disease status. Psychiatric disorder status was also associated with greater comorbidity burden, although this relationship was attenuated in sensitivity analysis, while smoking did not show an independent association. These findings support the value of routine medical anamnesis in dental settings and highlight the potential role of oral healthcare services in identifying medically vulnerable patients and supporting more integrated care. Declarations Ethics Committee Approval The study received ethical approval from the Research Ethics Committee of the Faculty of Dentistry at Necmettin Erbakan University, and the study was conducted in accordance with the Declaration of Helsinki (Approval Date: 28.07.2022; Approval Number: 2022/173). Informed consents were obtained from all participants, and all data were processed anonymously. Author Contributions Study Design: AA Data Collection: AA, SU, HY, İM Statistical Analysis: AA, ÖA Data Interpretation: AA, SU, HY, İM Manuscript Preparation: AA, SU, HY, İM, ÖA Literature Search: AA, SU, HY, İM, ÖA Critical Review: AA Acknowledgements - Conflict of Interest There is no conflict of interest. Financial Disclosure None. The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Data availability Data are available from the corresponding author upon reasonable request. References Taş A, Yardimci S. 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Demographic and clinical characteristics of patients attending the dental clinic (n = 15,002) Variable Total (n = 15,002) Age, years Mean ± SD 39.06 ± 15.09 Median (IQR) 37.0 (26.0–49.0) Range 16–96 Age group, n (%) <30 years 4,916 (32.8%) 30–44 years 5,025 (33.5%) 45–59 years 3,374 (22.5%) ≥60 years 1,687 (11.2%) Sex, n (%) Male 6,039 (40.3%) Female 8,963 (59.7%) Smoking status, n (%) Non-smoker 14,471 (96.5%) Smoker* 531 (3.5%) Systemic diseases, n (%) No 11,243 (74.9%) Yes 3,759 (25.1%) Psychiatric disorder, n (%) No 14,642 (97.6%) Yes 360 (2.4%) Allergy status, n (%) None 14,735 (98.2%) Drug allergy 104 (0.7%) Food allergy 5 (<0.1%) Drug + food allergy 3 (<0.1%) Seasonal allergy 82 (0.5%) Other 73 (0.5%) Table 2. Distribution of systemic diseases by sex in the study population Systemic diseases Total, n (%) Male, n (%) Female, n (%) Hypertension 1,271 (8.5%) 457 (7.6%) 814 (9.1%) Diabetes mellitus 1,021 (6.8%) 430 (7.1%) 591 (6.6%) Cardiovascular disease 870 (5.8%) 422 (7.0%) 448 (5.0%) Thyroid disease 519 (3.5%) 61 (1%) 458 (5.1%) Respiratory disease 420 (2.8%) 101 (1.7%) 319 (3.6%) Renal disease 13 (0.1%) 7 (0.1%) 6 (0.1%) Liver disease 165 (1.1%) 99 (1.6%) 66 (0.7%) Table 3. Association between systemic disease and age group, sex, and smoking status (n = 15,002) Variable Systemic Disease: No n (%) Systemic Disease: Yes n (%) p-value Cramer’s V Age group <0.001 0.442 <30 years 4,486 (91.2) 430 (8.7) 30–44 years 4,193 (83.5) 832 (16.5) 45–59 years 2,017 (59.8) 1,357 (40.2) ≥60 years 547 (32.4) 1,140 (67.6) Sex <0.001 0.041 Male 4,656 (77.1) 1,383 (22.9) Female 6,587 (73.5) 2,376 (26.5) Smoking status 0.138 0.012 Non-smoker 10,830 (74.9) 3,641 (25.1) Smoker* 413 (77.8) 118 (22.2) Table 4. Distribution of comorbidity burden (0 / 1 / 2 / ≥3 conditions) across demographic and clinical subgroups (n = 15,002) Age group 0 1 2 ≥3 p-value Cramer’s V <30 years 4,486 (91.2%) 385 (7.8%) 39 (0.8%) 6 (0.1%) <0.001 0.49 30–44 years 4,193 (83.5%) 677 (13.5%) 128 (2.5%) 27 (0.5%) 45–59 years 2,017 (59.8%) 848 (25.1%) 381 (11.3%) 128 (3.8%) ≥60 years 547 (32.4%) 520 (30.8%) 396 (23.5%) 224 (13.3%) Sex Male 4,656 (77.1%) 900 (14.9%) 353 (5.8%) 130 (2.2%) <0.001 0.06 Female 6,587 (73.5%) 1,530 (17.1%) 591 (6.6%) 255 (2.8%) Smoking status Non-smoker 10,830 (74.9%) 2,346 (16.2%) 944 (6.5%) 351 (2.4%) 0.19 0.01 Smoker 413 (77.8%) 84 (15.8%) 0 (0.0%) 34 (6.4%) Psychiatric disorder No 11,113 (75.9%) 2,343 (16.0%) 872 (6.0%) 314 (2.1%) <0.001 0.38 Yes 130 (36.1%) 87 (24.2%) 72 (20.0%) 71 (19.7%) Table 5. Multivariable binary logistic regression analysis for factors associated with systemic condition status (n = 15,002) Variable OR 95% CI p-value Age (per 1-year increase) 1.08 1.08–1.09 <0.001 Sex (Female vs Male) 1.72 1.57–1.89 <0.001 Smoking (Smoker vs Non-smoker) 1.23 0.96–1.58 0.098 Psychiatric disorder (Yes vs No) 294.10 132.67–651.94 <0.001 OR, odds ratio; CI, confidence interval. The dependent variable in the primary model was the presence of at least one systemic condition, including psychiatric disorders. Because psychiatric disorder status was part of the composite outcome definition, the corresponding odds ratio should be interpreted with caution due to potential structural overlap Table 6. Sensitivity analysis: multivariable binary logistic regression for factors associated with non-psychiatric systemic disease status (n = 15,002) Variable OR 95% CI p-value Age (per 1-year increase) 1.08 1.08–1.09 <0.001 Sex (Female vs Male) 1.65 1.50–1.80 <0.001 Smoking (Smoker vs Non-smoker) 1.18 0.93–1.50 0.177 Psychiatric disorder (Yes vs No) 1.56 1.22–1.99 <0.001 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9084367","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":604457944,"identity":"f2fc9456-4ed6-43ea-a14c-2b36a612d7e2","order_by":0,"name":"Ali Altındağ","email":"data:image/png;base64,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","orcid":"","institution":"Necmettin Erbakan University","correspondingAuthor":true,"prefix":"","firstName":"Ali","middleName":"","lastName":"Altındağ","suffix":""},{"id":604457945,"identity":"1f8f4294-5264-4951-9092-2e80829342c1","order_by":1,"name":"Sultan Uzun","email":"","orcid":"","institution":"Bilecik University","correspondingAuthor":false,"prefix":"","firstName":"Sultan","middleName":"","lastName":"Uzun","suffix":""},{"id":604457946,"identity":"d9786e4f-e91c-41a2-9700-40a4112ca4dc","order_by":2,"name":"Hilal Yalın Özdemir","email":"","orcid":"","institution":"Necmettin Erbakan University","correspondingAuthor":false,"prefix":"","firstName":"Hilal","middleName":"Yalın","lastName":"Özdemir","suffix":""},{"id":604457947,"identity":"4e11f016-2d6e-47ad-93ec-b5d128243fd4","order_by":3,"name":"İrem Meriç","email":"","orcid":"","institution":"Kırıkkale University","correspondingAuthor":false,"prefix":"","firstName":"İrem","middleName":"","lastName":"Meriç","suffix":""},{"id":604457948,"identity":"1a60f429-a96b-4cb9-a0ae-af97bae216c0","order_by":4,"name":"Ömer Altındağ","email":"","orcid":"","institution":"Bilecik University","correspondingAuthor":false,"prefix":"","firstName":"Ömer","middleName":"","lastName":"Altındağ","suffix":""}],"badges":[],"createdAt":"2026-03-10 13:08:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9084367/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9084367/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104964541,"identity":"46d5b71f-9aaa-4856-90eb-75a800d26299","added_by":"auto","created_at":"2026-03-19 09:33:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":867859,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9084367/v1/66e60eae-16c5-4ff7-9d24-9795e011bb2f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Burden of Systemic Diseases and Associated Factors Among Dental Outpatients in a Routine Care Setting: A Cross-Sectional Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAnamnesis is the systematic collection of information on a patient’s medical conditions, medication use, and reason for seeking care, and it remains essential for accurate diagnosis and safe dental decision-making [1]. A thorough medical history allows dentists to identify risks that may influence treatment planning, prescribing, local anesthesia, surgical procedures, and infection control [1, 2]. This is particularly important because some patients may underestimate the relevance of their systemic conditions, be unaware of drug-related oral effects, or fail to adhere to prescribed therapies [3, 4].\u003c/p\u003e\n\u003cp\u003eBeyond its clinical importance, oral health is increasingly recognized as part of general health. The World Health Organization (WHO) identifies oral health as a key indicator of overall health, well-being, and quality of life, and emphasizes that oral conditions should be addressed within broader health systems and universal health coverage frameworks [5, 6]. In parallel with population ageing, multimorbidity—commonly defined as the coexistence of two or more chronic conditions—has become a major public health challenge because it increases care complexity, healthcare utilization, and the need for integrated management [7, 8].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDental settings are therefore not only sites of oral care, but also important points of contact where the broader burden of systemic disease may be recognized in routine practice. The prevalence of systemic diseases among dental patients varies across settings, yet consistently rises with age and mirrors the epidemiology of noncommunicable diseases in the wider community [1, 5]. Identifying this burden in real-world dental outpatient populations may support chairside risk assessment, more appropriate referral pathways, and better integration between dental care and general health services, particularly in middle-income settings where chronic disease burdens are increasing [3, 9].\u003c/p\u003e\n\u003cp\u003eThis issue is further reinforced by the growing retention of natural dentition and the increasing number of patients receiving long-term pharmacotherapy for chronic medical conditions [1, 10]. As a result, dentists are encountering more medically compromised individuals in daily practice, making competence in systemic disease recognition and medication-related risk assessment increasingly important [10]. Within this context, psychiatric disorders also deserve attention, as both the disorders themselves and their pharmacological treatment may contribute to xerostomia, caries susceptibility, bruxism, and periodontal vulnerability, thereby complicating dental management [4, 11].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDespite growing recognition of dental clinics as valuable settings for systemic health assessment, contemporary large-scale data on the prevalence and determinants of systemic diseases among dental outpatients remain limited in many regions. Therefore, this study aimed to quantify the burden and distribution of systemic diseases among patients attending a dental clinic and to identify demographic and clinical factors associated with systemic disease status in a real-world outpatient population.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy Design and Ethical Approval\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was designed as a retrospective cross-sectional analysis. The study protocol was conducted in accordance with the principles of the Declaration of Helsinki and received approval from the Local Pharmaceutical and Non-Device Research Ethics Committee (Approval No: 2022/173). Access to the study data was restricted to the research team, and all patient information was evaluated in anonymized form.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy Population and Data Collection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study population consisted of patients aged 15 years and older who attended the Initial Examination Clinic of the Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, X University, between January 2022 and December 2022. Patients were eligible for inclusion if their anamnesis information was fully recorded in the digital patient management system. No additional clinical examinations, laboratory tests, or imaging procedures were requested for the purposes of this study; all analyses were based solely on archived anamnesis records.\u003c/p\u003e\n\u003cp\u003eFor each patient, demographic variables including age and sex were recorded. Medical history data were systematically reviewed to identify the presence of systemic conditions, including cardiovascular, endocrine, gastrointestinal, respiratory, hematological, oncological, and other chronic diseases, as well as current medication use. Age was categorized into four predefined groups: \u0026lt;30 years, 30–44 years, 45–59 years, and ≥60 years.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eDefinition of Systemic Condition and Comorbidity Burden\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSystemic condition status was defined as the presence of at least one documented chronic systemic disease in the medical history records. In addition, comorbidity burden was categorized based on the total number of systemic conditions reported for each patient and classified into four groups: no systemic condition (0), one condition (1), two conditions (2), and three or more conditions (≥3).\u003c/p\u003e\n\u003cp\u003ePsychiatric disorder status was identified based on medication history, with the use of antidepressants and/or higher-intensity psychotropic medications considered indicative of a clinically relevant psychiatric disorder.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDescriptive statistics were calculated to summarize demographic characteristics and the prevalence of systemic conditions. Continuous variables were presented as mean ± standard deviation (SD), median, and range, while categorical variables were expressed as frequencies and percentages.\u003c/p\u003e\n\u003cp\u003eAssociations between systemic condition status (yes/no) and categorical variables such as age group, sex, smoking status, and psychiatric disorder status were assessed using the Pearson chi-square test. Fisher’s exact test was applied where appropriate. Effect sizes for significant associations were quantified using Cramer’s V and interpreted according to conventional thresholds.\u003c/p\u003e\n\u003cp\u003eThe distribution of comorbidity burden across demographic and clinical subgroups was evaluated using chi-square analysis, with Cramer’s V reported as a measure of association strength.\u003c/p\u003e\n\u003cp\u003eTo identify independent factors associated with the presence of a systemic condition, a multivariable binary logistic regression analysis was performed. Variables included in the model were age (continuous), sex, smoking status, and psychiatric disorder status. Results were reported as odds ratios (ORs) with corresponding 95% confidence intervals (CIs).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSensitivity analysis:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo assess whether the strong association observed for psychiatric disorder status was driven by overlap with the composite outcome definition, a sensitivity analysis was performed using a revised outcome that excluded psychiatric disorders from the systemic disease variable. Multivariable logistic regression was then repeated with non-psychiatric systemic disease as the dependent variable.\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were performed using IBM SPSS Statistics for Windows, version 22.0 (IBM Corp., Armonk, NY, USA). A two-sided p-value \u0026lt;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe study included 15,002 patients with a mean age of 39.06 ± 15.09 years (median: 37.0 years). Baseline demographic and clinical characteristics of the study population are presented in Table 1. Approximately two-thirds of the study population were younger than 45 years. Overall, 25.1% of patients were classified as having at least one systemic condition. Psychiatric disorders were identified in 2.4% of the patients. Most patients reported no history of drug or food allergy (98.2%).\u003c/p\u003e\n\u003cp\u003eHypertension was the most frequently reported systemic condition in the overall study population (8.5%), followed by diabetes mellitus (6.8%) and cardiovascular disease (5.8%). Hypertension, respiratory disease, and thyroid disease were more prevalent among female patients, whereas diabetes mellitus, cardiovascular disease, and liver disease were more frequently reported among male patients (Table 2).\u003c/p\u003e\n\u003cp\u003eA strong and statistically significant association was observed between age group and the presence of a systemic condition (χ² = 2926.9, p \u0026lt; 0.001), with a large effect size (Cramer’s V = 0.44). The prevalence of systemic conditions increased markedly with advancing age, reaching 67.6% among patients aged 60 years and older (Table 3).\u003c/p\u003e\n\u003cp\u003eSex was also significantly associated with systemic condition status (χ² = 24.8, p \u0026lt; 0.001); however, the effect size was small (Cramer’s V = 0.04), indicating limited clinical relevance.\u003c/p\u003e\n\u003cp\u003eNo statistically significant association was found between smoking status and the presence of a systemic condition (p = 0.138).\u003c/p\u003e\n\u003cp\u003eComorbidity burden increased markedly with advancing age (p \u0026lt; 0.001), with a large effect size (Cramer’s V = 0.49). While more than 90% of patients younger than 30 years had no comorbid conditions, only 32.4% of patients aged 60 years and older were free of comorbidity, and 13.3% presented with three or more conditions (Table 4).\u003c/p\u003e\n\u003cp\u003eSex was significantly associated with comorbidity burden (p \u0026lt; 0.001), although the effect size was small (Cramer’s V = 0.06). Smoking status was not significantly associated with comorbidity burden (p = 0.19).\u003c/p\u003e\n\u003cp\u003eIn contrast, psychiatric disorders showed a strong association with comorbidity burden (p \u0026lt; 0.001; Cramer’s V = 0.38). Nearly 40% of patients with psychiatric disorders had two or more comorbid conditions, compared with only 8.1% among those without psychiatric disorders.\u003c/p\u003e\n\u003cp\u003eIncreasing age was independently associated with the presence of a systemic condition, with an 8% increase in odds per additional year of age (OR = 1.08, 95% CI: 1.08–1.09; p \u0026lt; 0.001) (Table 5).\u003c/p\u003e\n\u003cp\u003eFemale sex was associated with a significantly higher likelihood of having a systemic condition compared with male sex (OR = 1.72, 95% CI: 1.57–1.89; p \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003eSmoking was not independently associated with systemic condition status in the multivariable model (OR = 1.23, 95% CI: 0.96–1.58; p = 0.098).\u003c/p\u003e\n\u003cp\u003eBecause psychiatric disorders were included in the composite systemic condition variable, an additional sensitivity analysis was performed using a revised outcome that excluded psychiatric disorders from the definition of systemic disease. In this analysis, increasing age remained the strongest independent predictor (OR = 1.08, 95% CI: 1.08–1.09; p \u0026lt; 0.001), and female sex also remained significantly associated (OR = 1.65, 95% CI: 1.50–1.80; p \u0026lt; 0.001). Psychiatric disorder status continued to show an independent association with non-psychiatric systemic disease, although the effect size was substantially attenuated (OR = 1.56, 95% CI: 1.22–1.99; p \u0026lt; 0.001). In contrast, smoking was no longer statistically significant in the sensitivity model (OR = 1.18, 95% CI: 0.93–1.50; p = 0.177) (Table 6).\u003c/p\u003e\n\u003cp\u003eAccordingly, the very large odds ratio observed for psychiatric disorders in the primary model should be interpreted cautiously, as it was at least partly driven by structural overlap with the composite outcome definition.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eDentists routinely encounter patients with systemic diseases in daily practice, and accurate medical anamnesis is essential for safe treatment planning and complication prevention [2, 10]. From a public health perspective, dental outpatient clinics may also function as accessible points for identifying chronic disease burden in individuals who may have limited contact with other healthcare services.\u003c/p\u003e\n\u003cp\u003eIn the present study, at least one systemic disease was identified in 25.1% of dental patients. This prevalence falls within the broad range reported in previous studies, where rates among dental populations vary from approximately 10% to nearly 70% depending on population structure, clinical setting, and case definitions [10, 12, 13]. Lower prevalence rates have been reported by Dhanuthai et al.[14] (12.2%), and Şener et al. [15] (24%), while higher rates have been observed in hospital-based or faculty settings, particularly in studies including older populations. Large-scale contemporary data further support this variability; for example, Aranda Romo et al. [16] reported a prevalence of 39.1% among more than 82,000 dental patients in a university clinic setting in Mexico, highlighting the influence of setting and population structure on observed prevalence estimates. Studies conducted in Turkey also demonstrate substantial heterogeneity. Hatipoğlu et al.[12] and Aydıntuğ et al.[17] reported prevalence rates exceeding 35%, whereas Şener et al.[15] (24%), Altan et al.[10] (24.1%), and Ciğerim [18](26%) reported figures closely aligned with the present findings. Differences across studies may be attributed to variations in age and sex distribution, socioeconomic background, referral patterns, and the operational definitions of systemic disease. Importantly, faculty-based clinics often serve medically vulnerable or referred patients, which may inflate prevalence estimates compared with general outpatient dental clinics.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRegarding disease patterns, hypertension, diabetes mellitus, and cardiovascular diseases were the most common systemic conditions in the present cohort. This distribution is consistent with the broader epidemiology of noncommunicable diseases and supports the view that cardiometabolic conditions constitute a major component of medical burden in dental populations. Jain et al.[19] reported that cardiovascular risk factors frequently cluster in socially vulnerable communities, potentially leading to a high disease burden outside traditionally defined high-risk age groups. Similarly, Takeuchi et al. [20] showed that multimorbidity is highly prevalent in patients with heart failure and is strongly associated with adverse outcomes. Although our cohort was drawn from a dental setting rather than a medical one, these findings similarly suggest that dental services may encounter a meaningful burden of chronic cardiometabolic disease in routine care.\u003c/p\u003e\n\u003cp\u003eIn the present study, hypertension was the most frequently reported individual systemic condition, followed by diabetes mellitus and cardiovascular disease. This pattern is broadly consistent with the global burden of noncommunicable diseases, in which cardiovascular and metabolic disorders remain major contributors to morbidity and mortality [5]. Given their implications for invasive procedures, medical emergencies, and treatment planning, these conditions are particularly relevant in routine dental care. Previous studies have reported the prevalence of cardiovascular diseases among dental patients as 14.8% by Ciğerim [18] and 13.40% by Oktay et al. [21]. In our study, cardiovascular disease was recorded in 5.8% of patients, while hypertension, which may be considered part of the broader cardiometabolic burden encountered in dental practice, was present in 8.5%. Previous studies have reported hypertension prevalence rates of 7.5% [22], 9.95% [23], and 12.6% [7]. Given the high frequency of hypertension both in the general population and in dental settings, appropriate precautions during dental treatment remain particularly important.\u003c/p\u003e\n\u003cp\u003eDiabetes mellitus represented the second most common systemic disease group in the present study, with a prevalence of 6.8%. This finding is consistent with the results reported by Shakir et al.[24] and Al-Bayaty et al.[7], as well as with previous studies conducted in the Turkish population [18, 22]. Because acute stress may predispose individuals with diabetes to metabolic complications, dentists should take appropriate precautions during dental treatment to reduce the risk of hyperglycemic or hypoglycemic coma. In addition, the potential for diabetes-related complications, including microvascular ischemia as well as macrovascular outcomes such as atherosclerosis and myocardial infarction, should be carefully considered in the dental management of diabetic patients [17].\u003c/p\u003e\n\u003cp\u003eAge was the strongest determinant of systemic disease burden in the present study. Although individuals aged 60 years and older represented a relatively small proportion of the study population, more than two-thirds of them had at least one systemic condition. This finding is in line with previous dental and epidemiologic studies showing that chronic disease burden increases markedly with age [7, 20, 25]. \u0026nbsp;From a service planning perspective, this pattern suggests that aging dental populations may require increasingly integrated models of care, particularly in university and referral-based outpatient settings.\u003c/p\u003e\n\u003cp\u003eSex was statistically associated with systemic disease status, and female patients showed higher odds of having a systemic condition in both the primary and sensitivity models. However, the univariate effect size was small, suggesting that the contribution of sex should be interpreted cautiously at the population level. This pattern may reflect differences in healthcare-seeking behavior, medication use, or age distribution rather than a uniform biological effect across all disease categories [21, 23]. Although crude prevalence differed by sex, the adjusted findings indicate that sex-related differences in systemic disease burden are likely to be context-dependent and influenced by the composition of the study population.\u003c/p\u003e\n\u003cp\u003eSmoking was not independently associated with systemic disease in the primary model, and this lack of significance was maintained in the sensitivity analysis. Although smoking remains a well-established risk factor for cardiometabolic and respiratory morbidity [19], the present findings suggest that its effect may be less pronounced in this dental outpatient population when considered alongside age, sex, and psychiatric disorder status.\u003c/p\u003e\n\u003cp\u003ePsychiatric disorder status was also associated with systemic disease burden, particularly with greater comorbidity burden. Nearly 40% of patients with psychiatric disorders had two or more comorbid conditions, compared with 8.1% among those without psychiatric disorders. However, the very large odds ratio observed in the primary regression model should be interpreted cautiously, because psychiatric disorders were included within the composite systemic disease outcome. When a sensitivity analysis was performed using a revised outcome that excluded psychiatric disorders, the association remained statistically significant but was substantially attenuated. This indicates that the primary estimate was influenced, at least in part, by structural overlap in variable definition rather than by an isolated epidemiologic effect.\u003c/p\u003e\n\u003cp\u003eEven so, the persistence of the association in the sensitivity model is consistent with previous literature showing that mental health conditions often coexist with greater medical complexity and treatment burden [26, 27]. For dental services, this is relevant not only clinically, but also from a public health standpoint, as patients with psychiatric disorders may require more coordinated and person-centered models of care.\u003c/p\u003e\n\u003cp\u003eOverall, the present findings suggest that routine dental care settings can provide useful opportunities to recognize medically vulnerable patients, particularly older adults and individuals with complex comorbidity profiles. In this sense, dental clinics should not be viewed solely as treatment sites for oral conditions, but also as part of a broader health system in which medical history taking can support safer care, timely referral, and better integration between oral and general health services [20, 23, 27-30].\u003c/p\u003e\n\u003cp\u003eFuture studies should use multicenter and longitudinal designs, and where possible incorporate more robust diagnostic definitions and social determinants of health, in order to better clarify the pathways linking systemic disease burden, mental health, and dental service utilization.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLimitations\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study has several limitations. First, its retrospective cross-sectional design precludes causal inference regarding the relationship between systemic diseases and associated factors. Second, all medical information was derived from anamnesis records, which may be subject to reporting bias or underreporting, particularly for conditions that patients perceive as unimportant or are unaware of. Third, psychiatric disorder status was operationalized using medication history rather than standardized psychiatric diagnoses, which may have introduced misclassification. In addition, because psychiatric disorders were part of the original composite systemic disease outcome, the association observed in the primary regression model was partly affected by structural overlap; although this was addressed through sensitivity analysis, the finding should still be interpreted cautiously. Finally, the study was conducted in a single university-based dental clinic, which may limit generalizability to other settings with different referral patterns, case mix, and healthcare access characteristics. The absence of detailed socioeconomic and healthcare utilization variables is another limitation, as these factors may influence both systemic disease burden and patterns of dental attendance. Despite these limitations, the large sample size and use of real-world clinical data provide useful insight into the burden of systemic disease among dental outpatients.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eSystemic diseases were common among dental outpatients, with one in four patients presenting with at least one chronic condition. Cardiometabolic diseases accounted for a substantial share of this burden, and age was the strongest determinant of systemic disease status. Psychiatric disorder status was also associated with greater comorbidity burden, although this relationship was attenuated in sensitivity analysis, while smoking did not show an independent association. These findings support the value of routine medical anamnesis in dental settings and highlight the potential role of oral healthcare services in identifying medically vulnerable patients and supporting more integrated care.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Committee Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study received ethical approval from the Research Ethics Committee of the Faculty of Dentistry at Necmettin Erbakan University, and the study was conducted in accordance with the Declaration of Helsinki (Approval Date: 28.07.2022; Approval Number: 2022/173). Informed consents were obtained from all participants, and all data were processed anonymously.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy Design: AA\u003c/p\u003e\n\u003cp\u003eData Collection: AA, SU, HY, İM\u003c/p\u003e\n\u003cp\u003eStatistical Analysis: AA, ÖA\u003c/p\u003e\n\u003cp\u003eData Interpretation: AA, SU, HY, İM\u003c/p\u003e\n\u003cp\u003eManuscript Preparation: AA, SU, HY, İM, ÖA\u003c/p\u003e\n\u003cp\u003eLiterature Search: AA, SU, HY, İM, ÖA\u003c/p\u003e\n\u003cp\u003eCritical Review: AA\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinancial Disclosure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u0026nbsp;The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eTaş A, Yardimci S. 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Ann Afr Med. 2020;19(1):40-46. https://doi.org/10.4103/aam.aam_22_19\u003c/li\u003e\n\u003cli\u003eHatipoğlu MG, Hatipoğlu H, Pekkan G. Evaluation of medical records of a dental patient population which admitted to a university hospital dental clinic. Balıkesir Health Sci J. 2012;1(2):54-58.\u003c/li\u003e\n\u003cli\u003eSmeets EC, de Jong KJ, Abraham-Inpijn L. Detecting the medically compromised patient in dentistry by means of the medical risk-related history: a survey of 29,424 dental patients in the Netherlands. Prev Med. 1998;27(4):530-535. https://doi.org/10.1006/pmed.1998.0285\u003c/li\u003e\n\u003cli\u003eDhanuthai K, Sappayatosok K, Bijaphala P, Kulvitit S, Sereerat T. Prevalence of medically compromised conditions in dental patients. Med Oral Patol Oral Cir Bucal. 2009;14(6):E287-E291.\u003c/li\u003e\n\u003cli\u003eŞener E, G\u0026uuml;rhan C, Coşgun E, Mert A. Evaluation of the impact of systemic diseases on dental treatment need and quality of life. 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JAMA Netw Open. 2023;6(1):e2251214. https://doi.org/10.1001/jamanetworkopen.2022.51214\u003c/li\u003e\n\u003cli\u003eCampos-Alberto E, Hirose T, Napatalung L, Ohyama M. Prevalence, comorbidities, and treatment patterns of Japanese patients with alopecia areata: a descriptive study using Japan medical data center claims database. J Dermatol. 2023;50(1):37-45. https://doi.org/10.1111/1346-8138.16615\u003c/li\u003e\n\u003cli\u003eYing J, Xiang W, Qiu Y, Zeng X. Risk of metabolic syndrome in patients with lichen planus: a systematic review and meta-analysis. PLoS One. 2020;15(8):e0238005. https://doi.org/10.1371/journal.pone.0238005\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Demographic and clinical characteristics of patients attending the dental clinic (n = 15,002)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTotal (n = 15,002)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39.06 \u0026plusmn; 15.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37.0 (26.0\u0026ndash;49.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16\u0026ndash;96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAge group, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;30 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4,916 (32.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e30\u0026ndash;44 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5,025 (33.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e45\u0026ndash;59 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3,374 (22.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ge;60 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1,687 (11.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSex, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6,039 (40.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8,963 (59.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNon-smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14,471 (96.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSmoker*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e531 (3.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSystemic diseases, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11,243 (74.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3,759 (25.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePsychiatric disorder, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14,642 (97.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e360 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAllergy status, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14,735 (98.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDrug allergy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e104 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFood allergy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5 (\u0026lt;0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDrug + food allergy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3 (\u0026lt;0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSeasonal allergy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e82 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e73 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Distribution of systemic diseases by sex in the study population\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSystemic diseases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTotal, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMale, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFemale, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1,271 (8.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e457 (7.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e814 (9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDiabetes mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1,021 (6.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e430 (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e591 (6.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCardiovascular disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e870 (5.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e422 (7.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e448 (5.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eThyroid disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e519 (3.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e61 (1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e458 (5.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRespiratory disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e420 (2.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e101 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e319 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRenal disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLiver disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e165 (1.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e99 (1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e66 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Association between systemic disease and age group, sex, and smoking status (n = 15,002)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSystemic Disease: No n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSystemic Disease: Yes n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCramer\u0026rsquo;s V\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAge group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e0.442\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;30 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4,486 (91.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e430 (8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e30\u0026ndash;44 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4,193 (83.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e832 (16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e45\u0026ndash;59 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2,017 (59.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1,357 (40.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ge;60 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e547 (32.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1,140 (67.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e0.041\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4,656 (77.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1,383 (22.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6,587 (73.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2,376 (26.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNon-smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10,830 (74.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3,641 (25.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSmoker*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e413 (77.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e118 (22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003e Distribution of comorbidity burden (0 / 1 / 2 / \u0026ge;3 conditions) across demographic and clinical subgroups (n = 15,002)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAge group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCramer\u0026rsquo;s V\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;30 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4,486 (91.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e385 (7.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e0.49\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e30\u0026ndash;44 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4,193 (83.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e677 (13.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e128 (2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27 (0.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e45\u0026ndash;59 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2,017 (59.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e848 (25.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e381 (11.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e128 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ge;60 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e547 (32.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e520 (30.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e396 (23.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e224 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4,656 (77.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e900 (14.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e353 (5.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e130 (2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6,587 (73.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1,530 (17.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e591 (6.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e255 (2.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNon-smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10,830 (74.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2,346 (16.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e944 (6.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e351 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSmoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e413 (77.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e84 (15.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34 (6.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePsychiatric disorder\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11,113 (75.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2,343 (16.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e872 (6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e314 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e0.38\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e130 (36.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e87 (24.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e72 (20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e71 (19.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u0026nbsp;\u003c/strong\u003eMultivariable binary logistic regression analysis for factors associated with systemic condition status (n = 15,002)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge (per 1-year increase)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.08\u0026ndash;1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSex (Female vs Male)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.57\u0026ndash;1.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSmoking (Smoker vs Non-smoker)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.96\u0026ndash;1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e0.098\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePsychiatric disorder (Yes vs No)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e294.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e132.67\u0026ndash;651.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eOR, odds ratio; CI, confidence interval. The dependent variable in the primary model was the presence of at least one systemic condition, including psychiatric disorders. Because psychiatric disorder status was part of the composite outcome definition, the corresponding odds ratio should be interpreted with caution due to potential structural overlap\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6.\u003c/strong\u003e Sensitivity analysis: multivariable binary logistic regression for factors associated with non-psychiatric systemic disease status (n = 15,002)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge (per 1-year increase)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.08\u0026ndash;1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSex (Female vs Male)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e1.65\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e1.50\u0026ndash;1.80\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSmoking (Smoker vs Non-smoker)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.93\u0026ndash;1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePsychiatric disorder (Yes vs No)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.22\u0026ndash;1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"anamnesis, dentistry, medical condition, prevalence, public health, systemic diseases","lastPublishedDoi":"10.21203/rs.3.rs-9084367/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9084367/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Systemic diseases are common among dental patients and may directly affect treatment planning, patient safety, and clinical outcomes. Dental outpatient settings may also provide an accessible opportunity to identify the burden of chronic conditions in routine care. This study aimed to assess the prevalence and distribution of systemic diseases among dental outpatients and to identify demographic and clinical factors associated with systemic disease status.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: This cross-sectional study included 15,002 patients aged 15 years and older who attended a university-based dental outpatient clinic between January and December 2022. Demographic characteristics, medical anamnesis records, and medication histories were obtained from the digital patient management system. Associations were examined using chi-square tests, and independent predictors were evaluated using multivariable binary logistic regression. A sensitivity analysis was also performed using a revised outcome that excluded psychiatric disorders from the composite systemic disease variable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e At least one systemic disease was recorded in 25.1% of patients. Hypertension (8.5%), diabetes mellitus (6.8%), and cardiovascular diseases (5.8%) were the most common conditions. The prevalence of systemic disease increased markedly with age, reaching 67.6% among patients aged 60 years and older. In multivariable analysis, older age, female sex, and psychiatric disorder status were independently associated with systemic disease, whereas smoking did not show an independent association. In the sensitivity analysis excluding psychiatric disorders from the outcome, older age remained the strongest predictor of systemic disease, female sex remained significantly associated, and psychiatric disorder status continued to show an independent association, although with a substantially attenuated effect size.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e A considerable proportion of dental outpatients had at least one systemic disease, with the burden concentrated in older adults and other clinically vulnerable groups. These findings highlight the value of routine medical anamnesis in dental settings and support the role of oral healthcare services in identifying medically at-risk patients and contributing to more integrated care.\u003c/p\u003e","manuscriptTitle":"Burden of Systemic Diseases and Associated Factors Among Dental Outpatients in a Routine Care Setting: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-19 09:33:24","doi":"10.21203/rs.3.rs-9084367/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a5f7caaf-2ecb-4345-a517-2f3fc09b96f6","owner":[],"postedDate":"March 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-19T09:33:24+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-19 09:33:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9084367","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9084367","identity":"rs-9084367","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}