The seasonal influence on TMD prevalence in South Korea which has four seasons

The seasonal influence on TMD prevalence in South Korea which has four seasons | 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 Article The seasonal influence on TMD prevalence in South Korea which has four seasons Yeon-Hee Lee, Jin-Woo Chung This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3821655/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Aim This study aimed to explore seasonal variations in temporomandibular disorder (TMD) prevalence in South Korea, utilizing nationwide population-based big data. Method Data from the Korean Meteorological Administration combined with big data from the Health Insurance Review and Assessment Service (HIRA) (2010–2022), identified as TMD (K07.6) through a 4-digit disease code search, were used. TMD patient data for the past 13 years were statistically processed every month, and prevalence by season was analyzed. Results In 2022, 484,241 individuals sought treatment for TMD in hospitals with an increase of 97.89% from 244,708 cases in 2010. The onset of TMD showed no sex differences in those under 10 years of age. However, a distinct female predominance emerged after 10 years of age, with an average female-to-male ratio of 1.84:1. The peak prevalence was observed in the 20–24 age group. TMD patient numbers across seasons showed no significant increase in winter compared with spring or summer. However, there was a significant correlation between the maximum and minimum temperatures and the number of patients with TMD. A higher temperature difference correlated with a higher TMD patient count. The strongest correlation between TMD patient numbers and temperature differences was observed in winter (r = 0.480, p < 0.01), followed by summer (r = 0.443, p < 0.05), and spring (r = 0.366, p < 0.01). The highest number of patients with TMD were distributed in Seoul and Gyeonggi-do, with metropolitan areas accounting for 50% of the total patient count. Conclusions Diurnal temperature fluctuations showed a significantly stronger correlation with the increase in the number of TMD patients than absolute climate temperatures. This aspect should be a key consideration when examining trends in patients with TMD across distinct seasons in South Korea. Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Health sciences/Risk factors seasonal winter temporomandibular disorder climate temperature prevalence Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction South Korea is renowned for its pronounced seasonal diversity encompassing spring, summer, fall, and winter. Spring, observed from March to mid-May, sees temperatures ranging between 10°C and 20°C, coinciding with the blossoming of flora and the emergence of leaves. Although it typically is warm and agreeable, intermittent cold snaps may be accompanied by brisk winds. Summer, spanning from June to mid-August, experiences temperatures surging between 25°C and 35°C accompanied by escalated humidity, often resulting in sultry and occasionally rainy conditions during the monsoon season [ 1 ]. This season may encounter strong winds and heavy rainfall due to the influence of typhoons. Fall, extending from September to mid-November, boasts mild temperatures ranging from 10°C to 20°C, characterized by clear and pleasant weather. Finally, winter extends from December to February with witnessed temperatures plunging below freezing temperatures, particularly in inland and mountainous areas, with numerous regions experiencing subzero temperatures. Frequent snowfall is common and is compounded by varying humidity levels that contribute to a further reduction in perceived temperatures [ 2 ]. Notably, South Korea's climate presents a unique contrast, with a difference in temperature of over 35°C between winter and summer. Temporomandibular disorders (TMD) include various conditions affecting the temporomandibular joint (TMJ) and the associated masticatory muscles, bones, and tissues [ 3 ]. The etiology of TMD is multifaceted, potentially involving muscle or cartilage damage around the TMJ, TMJ instability, muscle tension due to psychological stress, malocclusion, macrotrauma, microtrauma, and systemic disorders, such as rheumatism or growth issues during childhood or adolescence [ 4 , 5 ]. While prevalence rates may vary based on sex, age, and geographical location, reports indicate that most individuals experience TMD-related symptoms at least once in their lifetimes [ 6 ]. TMD is highly prevalent worldwide, with an overall prevalence of approximately 31% in adults and 11% in children/adolescents [ 7 ]. Notably, it tends to be a 2–4 times higher prevalence among women compared to men, particularly in their 20s and 40s [ 8 , 9 ]. The signs and symptoms of TMD are diverse and contribute to its diagnosis. Key symptoms include pain or discomfort in the TMJ area; TMJ noises such as clicking, popping, and crepitus; sensation of jaw locking or restricted mandibular movement; deformities or swelling around the TMJ; muscle stiffness; ear pain; tinnitus; neck pain; and headaches [ 10 ]. These symptoms significantly affect daily life and restrict activities such as eating, speaking, and facial expressions. Accurate diagnosis and appropriate treatment planning are crucial for effective management of TMD. Additionally, persistent TMD symptoms may be accompanied by sleep disturbances or psychological issues [ 11 , 12 ]. Hence, understanding the nature of TMD and addressing its diagnosis, treatment, management, and prevention is imperative. Historically, TMD has been classified with various systems, such as the Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) and the Diagnostic Criteria for Temporomandibular Disorders (DC/TMD), which play significant roles in defining and categorizing TMD. The RDC/TMD, developed in the 1990s, was among the initial comprehensive systems used for diagnosing TMD [ 13 ]. It is categorized based on clinical and imaging criteria and divided into groups such as myofascial pain, internal derangement, and arthralgia. Subsequently, the DC/TMD introduced by the International RDC/TMD Consortium Network in 2014 refined and updated the classification system [ 10 ]. It expanded the diagnostic categories, incorporated more specific assessment methods, and integrated both physical and psychosocial factors, emphasizing a more comprehensive approach to diagnosing and managing TMD. In South Korea, TMD specialists and general dentists diagnose patients based on the international TMD diagnostic criteria. National data in South Korea are categorized under the overarching term temporomandibular disorder (K07.6) and its subcategories (K07.60-K07.69). However, research on TMD using South Korea's healthcare big data and national population-based data is limited. To date, associations between various factors such as region, race, and sex and TMD occurrence have been reported [ 8 , 14 , 15 ]. During winter, the human body adapts to cold weather and attempts to regulate the internal temperature, increase muscle contraction, and decrease oxygen supply to the muscles, resulting in increased muscle pain or stiffness [ 16 – 18 ]. Arthritic pain can also increase during cold winters and at low temperatures as opposed to during summer and warm temperatures. A recent systematic review of osteoarthritis pain reported a negative correlation between temperature and pain severity [ 19 ]. However, the association between TMD pain and weather conditions remains unclear. Therefore, this study aimed to investigate seasonal fluctuations in TMD prevalence in South Korea using nationwide population-based data from the Health Insurance Review and Assessment Service (HIRA), also called the National Health Insurance data. Moreover, this study sought to examine the hypothesis that TMD prevalence increases during winter. Methods Study population HIRA serves as a nationally representative healthcare big data repository that collects billing data throughout the reimbursement process for healthcare service providers. The universal coverage system contains extensive and comprehensive information regarding medical services encompassing treatments, medications, procedures, and diagnoses for around 50 million beneficiaries covered under Korea's universal healthcare system. The HIRA dataset, which constitutes a substantial repository within the healthcare sector, has a significant potential for creating value across various domains. This aids in enhancing the efficiency of healthcare delivery systems while maintaining high-quality care, offering support for specific interventions, and furnishing crucial information to prevent or monitor side effects. Leveraging HIRA data for research is imperative to unlock its potential in understanding symptoms and managing, treating, and addressing activities related to patients with TMD. In this study, we analyzed prevalence trends under relevant circumstances among all cases classified under “temporomandibular joint disorders (K07.6)” in the HIRA dataset spanning 13 years from 2010 to 2022. Data acquisition All the data used in this study were obtained from officially accredited sources in the public domain. Korean patients' health statuses, medical providers, medical expenses, utilization rates, and summary statistics related to medical services were made public through the Healthcare Big Data Open System ( http://opendata.hira.or.kr ). Monthly temperature data for the past 13 years were obtained from the National Climate Data Center of the Korea Meteorological Administration ( https://data.kma.go.kr ). Statistical analysis Data were analyzed using the Statistical Package for Social Sciences (SPSS) for Windows (version 26.0; IBM Corp. Armonk, NY, USA). Descriptive statistics were reported as mean ± standard deviation or numbers with percentages, as appropriate. To analyze the distribution of discontinuous data, we used the χ 2 and Bonferroni tests for equality of proportions. The t-test was used to compare the means between the two groups. Analysis of variance and Tukey’s post-hoc tests were used to compare the parameter values for the four seasons (spring, summer, fall, and winter) and for the 12 months from January to December. Spearman's correlation analysis was conducted to explore the correlation between two parameters. The closer the absolute value of the correlation coefficient (r) is to 1, the stronger the correlation, whereas values closer to 0 indicate a weaker correlation. Statistical significance was set at a two-tailed p-value < 0.05. Results Prevalence and the number of patients with TMD By analyzing health data from January 2010 to March 2022 published by the HIRA we investigated the number of patients (prevalence) who visited hospitals due to TMD in Korea. In 2022, the total population of Korea was 51.74 million, and the number of patients who visited hospitals and clinics due to TMD was 484,241; accounting for 0.94% of the total Korean population. The period with the largest increase in the number of patients over the 13 years studied was 2010–2011, with an increase of 12.86%. The second period with the largest increase was 2020–2021, with an increase of 8.42% (Fig. 1 ). Further investigation is needed to determine whether the increase in the number of patients with TMD between 2020 and 2021 is correlated with the COVID-19 pandemic. From 2010 to 2022, the number of patients increased by 97.89%, from 244,708 to 484,241. In Korea, the number of patients with TMD has increased steadily over the past 13 years. The number of women with TMD increased from 148,110 in 2010 to 289,525 in 2022, marking a surge of 95.48%. Among males, the increase was 101.57%, from 96,598 in 2010 to 194,716 in 2022. Consequently, the growth rate of TMD patients in males was 6.09% higher than that in females (Fig. 1 ). Peak prevalence of TMD in the 20s age group Patients who visited the hospital in 2022 were divided in five-year intervals, the largest age group was 20–24 years old, followed by 25–29 years old, 15–19 years old, 30–34 years old, and 50–54 years old, 45–49 years old, 40–44 years old, 60–64 years old, 35–39 years old, 55–59 years old, 10–14 years old, 70–74 years old, 75 − 59 years old, 80 + years old, 5–9 years old, < 5 years old; the frequency trends according to age group among all TMD patients were similar in both males and females. Interestingly mid-to-late teens (15–19 years old) had the 3rd highest number of TMD patients out of a total of 17 age groups, while early teens (10–14 years old) ranked 12th. Additionally, TMD occurred even in children under the age of 10 years, and in very elderly people aged over 80 years; TMD occurred in 21,909 people (Fig. 2a). The female-to-male ratio among TMD patients across age groups The female-to-male ratio of all patients admitted to the hospital in 2022 is 1.84:1. The female-to-male ratio of patients who visited the hospital in 2022 was calculated according to 17 age groups (Fig. 2b). When examining the ratio of females to males in the 17 age groups (5-year age range), the ratio of males to females was higher in the < 5 (0.98:1) and 5–9 (0.97:1) age groups. Excluding these two groups, in all 15 age groups, TMD was more prevalent in women than in men (ranges: 2.23–1.37:1). The highest ratio was 2.23 in the 50–54 age group. The lowest ratio was in the 15–19 age group, with a value of 1.37:1. There was no gender difference in the number of TMD patients in the past 13 years from 2010 to 2022 in those under 10 years of age; there was a statistically significant difference in the number of TMD patients between males and females in the age range of under 5 years (171.71 ± 47.35 vs 181.07 ± 39.27, p = 0574) and 5–9 years (1246.21 ± 151.04 vs 1179 ± 153.91, p = 0.254). In the other 15 5-year age groups, the number of patients with TMD was higher in women than in men (p 65 years and super-aged patients aged > 80 years (Table 1 ). Distribution of TMD patients by type of healthcare institution in 2022 In Korea, the treatment of patients with TMD was conducted on an outpatient basis, and outpatients (99.9%) overwhelmingly outnumbered inpatients (0.1%) (Fig. 3 a). Considering each type of healthcare institution, in the distribution of total medical expenses by type of healthcare institution, clinic-level care accounted for an overwhelmingly higher proportion (75.8%) than other types (Fig. 3 b). Medical expenses for hospital-level care accounted for 19%, while general hospitals accounted for 2.6%, and tertiary general hospitals accounted for 2.5% of the total. The medical expenses of patients with TMD at public health institutions were 0.0%. Statistics on treatment days also showed a similar pattern to that of medical expenses, with clinic-level care accounting for an overwhelmingly large proportion (70.7%; Fig. 3 c). This was followed by hospital care (23.4%), tertiary general hospitals (3.5%), general hospitals (2.4%), and public health institutions (0.0%). The distribution of the number of TMD patients by region At the city level, the distribution of patient numbers was as follows: Seoul (121,886, 26.92%), Pusan (32,632, 7.21%), Daegu (26,869, 5.94%), Incheon (23,271, 5.14%), Daejeon (15,859, 3.50%), Gwangju (14,625, 3.23%), Ulsan (8,943, 1.98%), Jeju (4,450, 0.98%), and Sejong (2,659, 0.59%). At the provincial level, it was Gyeonggi (101,484, 22.42%), Gyeongsangnam-do (25,465, 5.63%), Chungcheongnam-do (16,137, 3.57%), Jeollabuk-do (14,219, 3.14%), Gyeongsangbuk-do (12,433, 2.75%), Chungcheongbuk-do (11,442, 2.53%), Gangwon-do (10,028, 2.22%), and Jeollanam-do (10,246, 2.26%). The incidence in the capital region, including Seoul and Gyeonggi, accounted for approximately 49.35% of the total, nearly half of the total occurrence (Fig. 4 a). Similar results were found when examining the regional distribution of the number of patients as the average of the data over the past five years (2018–2022). At the city level, Seoul (12886 patients), and at the provincial level, Gyeonggi-do (101484 patients) had the highest number of TMD patients (Fig. 4 b). Distribution of TMD patient numbers across 12 months in a year Interestingly, when the number of patients was divided into 12 months, there was no significant difference between the months (Table 2 ). Figure 5 shows the monthly change trend in patients with TMD over the past 13 years (2010–2022). The number of patients on Korea's summer vacation, summer vacation, and winter vacation during July-August (the average number of patients: 48854–49292) and December-January (the average number of patients: 47164–48718) was higher at a statistically insignificant level than in other months. Unusually, the number of patients was higher in November (48370) than in March, April, May, June, September, and October, although this was not a vacation period, and the number was not statistically significant (Table 2 ). This may mean that cold weather or large daily temperature differences contribute to an increase in the number of patients with TMD, even if it is not a vacation or a vacation period when there is relatively ample time. The number of TMD patients in December (48718) increased by 7.01% compared to the number of TMD patients in September (45528). However, when the 12 months were divided into four seasons (March-June: spring; July–August: summer; September-November: fall; and December–February: winter), completely different results were obtained. There were significantly more TMD patients in the summer season (49073 ± 309) than in spring (46379 ± 390) and fall (46161 ± 894) (p < 0.05) (Fig. 5 a). There was no significant difference in the number of TMD patients in winter (47941 ± 1099) compared to summer. The number of patients with TMD in winter was higher than that in spring and fall, and the number of patients with TMD in winter increased by 3.86% compared to spring and by 3.59% compared to fall; however, the difference was not significant (Table 3 ). Distribution of climate temperature across 12 months in a year The average temperature in January was the lowest; however, there was no significant difference between the average temperatures in December and February (Fig. 5 b). These three months had significantly lower averages than the other nine months. The average temperature in the months corresponding to spring was higher than that in winter and lower than that in summer. The monthly climate temperatures were ranked as follows: August > July > June > September > May > October > April > November > March > February > December > January. However, there was no significant difference in the mean climate temperature between January (-2.325 ± 2.156 ℃), February (0.367 ± 1.603 ℃), and December (-0.6177 ± 1.747 ℃), and between July (26.017 ± 1.159 ℃) and August (26.742 ± 1.047 ℃) (all p > 0.05). The monthly averages of the highest and lowest temperatures exhibited the same pattern (Fig. 5 c). The order of the largest temperature difference between the highest and lowest temperatures was May (10.325 ± 1.057 ℃) > April (10.033 ± 0.817 ℃) > October (9.908 ± 0.632 ℃) > March (9.700 ± 1.111 ℃) > June (9.200 ± 0.743 ℃) > February (8.933 ± 0.618 ℃) > November (8.617 ± 0.878 ℃) > September (8.517 ± 0.958 ℃) > January (8.083 ± 0.769 ℃) > December (7.933 ± 0.641℃) > August (6.975 ± 0.966 ℃) > July (6.767 ± 0.885 ℃) (Table 2 ). Since the average temperature difference per year was 8.76 ℃, the distribution was investigated by dividing it into cases of ≤ 8.76 ℃ and > 8.76 ℃ for each of the four seasons: spring, summer, fall, and winter (Table 4 ). The seasons with the highest proportion of temperature differences > 8.76°C were spring (83.7%), followed by fall (63.9%), winter (33.3%), and summer (0.0%). The ratio of temperature difference > 8.76 ℃ is spring > autumn > winter > summer (p < 0.001). Changes in climate temperature and number of TMD patients over the past 13 years Table 2 shows the cumulative changes in climate temperature and the number of patients with TMD over the past 13 years. Considering the climate temperature, Korea's temperature distribution was very clear according to spring, summer, fall, and winter, and by month from January to December (Table 3 and Fig. 5 a). Over the past 13 years, Korea's average temperature (temperature distribution of -8 ℃ − 29 ℃), minimum temperature, and maximum temperature range have been constant (Fig. 5 b). Seasonal changes in the number of patients with TMD were less obvious than seasonal changes in climate temperature, and an increasing pattern was observed during summer vacation, vacation periods, and winter vacation and increased in fall and winter rather than in spring (Fig. 5 c). Over the past 13 years, the number of patients with TMD has steadily increased with seasonal increases and decreases. The correlation between the number of TMD patients and climate temperature It is worth reporting that in all four seasons, the number of patients with TMD was not significantly correlated with the mean temperature (Table 5 ). In spring, summer, and winter, excluding fall, the number of patients with TMD had a significant positive correlation with the temperature difference, which is the difference between the highest and lowest temperatures. The strongest correlation was observed between the number of patients with TMD and the temperature difference in winter (r = 0.480, p < 0.01), followed by summer (r = 0.443, p < 0.05), and spring (r = 0.366, p < 0.01). In other words, the temperature difference during the day contributed more significantly to the increase in the number of patients with TMD than the average climate temperature (Fig. 6 ). Table 1. Sex distribution of the number of TMD patients according to age group (2010-2022) Age group (5y interval) Male Female p-value <5y 171.71 ± 47.35 181.07 ± 39.27 0.574 5-9y 1246.21 ± 151.04 1179.02 ± 153.91 0.254 10-14y 11146.21 ± 1490.52 21157.64 ± 3545.45 <0.001*** 15-19y 45566.29 ± 3891.54 65025.29 ± 5876.48 <0.001*** 20-24y 46684.64 ± 11977.03 77232 ± 16494.17 <0.001*** 25-29y 34369.01 ± 10749.41 64302.79 ± 17174.05 <0.001*** 30-34y 23131.86 ± 6579.92 45678.79 ± 9435.59 <0.001*** 35-39y 18489.64 ± 4784.67 39617.29 ± 8203.37 <0.001*** 40-44y 16804.71 ± 3831.16 37213.29 ± 8868.23 <0.001*** 45-49y 16796.79 ± 4471.14 36942.57 ± 10879.90 <0.001*** 50-54y 16550.07 ± 4340.92 37843.14 ± 10177.88 <0.001*** 55-59y 16014.21 ± 5089.23 35160.29 ± 11471.41 <0.001*** 60-64y 14332.29 ± 5736.15 27940.43 ± 11989.86 0.0007*** 65-69y 12494.21 ± 4312.46 21931.36 ± 7679.37 <0.001*** 70-74y 10401.71 ± 3117.94 17284.29 ± 4272.25 <0.001*** 75-79y 7040.856 ± 2649.31 12675.93 ± 3967.15 <0.001*** ≥ 80y 4198.21 ± 2007.73 8224.57 ± 3238.27 0.0005*** The results were analyzed using t-tests. Statistical significance was set at p<0.05, *** p<0.001. Table 2. Distribution of TMD patient numbers and temperature across 12 months in a year (2010-2022) Month Number of TMD patients p-value Mean temperature (℃) p-value Lowest temperature (℃) p-value Highest temperature (℃) p-value Temperature difference (℃) p-value January 47164 ± 10510 0.974 -2.325 ± 2.156 <0.001*** -6.067 ± 2.037 <0.001*** 2.017 ± 2.385 <0.001*** 8.083 ± 0.769 <0.001*** February 45125 ± 9599 0.367 ± 1.603 -3.733 ± 1.630 5.200 ± 1.688 8.933 ± 0.618 March 46631± 10996 6.554 ± 1.619 2.138 ± 1.374 11.838 ± 2.058 9.700 ± 1.111 April 45930 ± 11392 12.350 ± 1.677 7.75 ± 1.418 17.783 ± 2.074 10.033 ± 0.817 May 46577 ± 11644 18.550 ± 0.914 13.767 ± 0.668 24.092 ± 1.400 10.325 ± 1.0567 June 43590 ± 10368 23.317 ± 0.678 19.233 ± 0.709 28.433 ± 0.899 9.200 ± 0.743 July 50266 ± 12519 26.017 ± 1.159 23.05 ± 1.007 29.817 ± 1.408 6.767 ± 0.885 August 49292 ± 10801 26.742 ± 1.047 23.65 ± 0.950 30.625 ± 1.352 6.975 ± 0.966 September 45528 ± 11205 22.017 ± 0.591 18.108 ± 0.643 26.625 ± 0.946 8.517 ± 0.958 October 46793 ± 11659 15.233 ± 1.008 10.683 ± 0.996 20.592 ± 1.187 9.908 ± 0.632 November 48370 ± 11421 7.567 ± 1.538 3.601 ± 1.736 12.217 ± 1.511 8.617 ± 0.878 December 48718 ± 11668 -0.6177 ± 1.747 -4.358 ± 1.643 3.575 ± 1.907 7.933 ± 0.641 The results were analyzed using ANOVA. Statistical significance was set at p<0.05, *** p<0.001. Table 3. The difference in TMD patient numbers across four seasons Season Number of TMD patients (Mean ± SD) p-value post-hoc Spring 46379 ± 390 0.021* Spring < Summer, Fall < Summer Summer 49073 ± 309 Fall 46161 ± 894 Winter 47941 ± 1099 The results were analyzed using ANOVA and post hoc analysis. Statistical significance was set at p<0.05, * p<0.05. Table 4. The proportion where the difference between the minimum and maximum temperatures within a day exceeds 8.76 ℃ Temperature difference Spring Summer Fall Winter p-value ≤ 8.76 ℃ Frequency 8 24 13 24 8.76℃ Frequency 41 0 23 12 % 83.7% 0.0% 63.9% 33.3% Results were obtained using χ 2 test and repeated χ 2 test between two age groups. Statistical significance was set at p<0.05, *** p<0.001. Discussion This study aimed to ascertain whether the hypothesis that TMD occurs more frequently during colder winter months than warmer summer months in correlation with climate temperature is true. Therefore, we examined the number of patients with TMD based on the temperature and season. However, the analysis of the HIRA open big data revealed that the difference in TMD patient numbers between summer and winter was not significant. Surprisingly, the average number of patients with TMD during summer was the highest among the four seasons. Based on the analysis, the number of patients with TMD exhibited two peaks throughout the year, in August and December. This seems to correlate with summer and winter vacations in school and holidays for working individuals and students. Despite not being a period for vacations or holidays, November showed an increase in the number of patients with TMD compared to October. In other words, the number of patients can be affected to some extent by increases and decreases in the daily temperature range. However, the availability of time for patients to visit the hospital themselves or with their guardians during school or work vacations is interpreted as a major factor in the increase in the number of patients with TMD. By combining data from the Korean Meteorological Administration with HIRA big data, we first established a positive correlation between the temperature difference between the maximum and minimum climate temperatures and the number of TMD patients. TMD is regarded as a heterogeneous group of conditions primarily characterized by a multifactorial pathogenesis [ 20 ]. The prevailing opinion is that TMD involves both physical and psychological factors; is understood to have a multifactorial etiology encompassing parafunctional habits, bruxism, maladaptive body posture, occlusal characteristics, developmental irregularities, macro or microtrauma, excessive loading, and stress [ 21 ]. Painful TMD has been demonstrated to be biopsychosocial and multifactorial [ 6 ]. One factor that may influence the occurrence of TMD symptoms is cold or low temperatures. There have been consistent reports about the association between lower temperatures and increased muscle pain [ 22 , 23 ]. As the temperature decreases, individuals with chronic pain often experience an exacerbation of symptoms. This leads to increased joint discomfort, heightened muscle tension, and intense sharp pains [ 24 ]. However, despite speculation regarding the correlation between climatic temperature and TMD prevalence, only weak direct evidence supports this relationship. According to the DC/TMD, common TMD can be classified into arthrogenous and myogenous TMD, and headaches can be attributed to TMD. Some factors can contribute to increased joint or muscle pain in cold weather. When temperatures drop, air pressure tends to decrease, which can directly impact joint sensitivity [ 25 ]. This might result in the expansion of soft tissues such as tendons and muscles, exerting more pressure on inflammatory arthritic joints and causing discomfort during movement [ 26 ]. Moreover, colder weather often leads to reduced physical activity and prolonged indoor stay. Extended periods of inactivity can lead to muscle weakening and decreased joint flexibility, contributing to muscle stiffness and an increased risk of painful cramps [ 27 ]. Seasonal affective disorder, which is prevalent during colder months, may influence pain perception owing to its impact on mood [ 28 ]. Reduced daylight exposure and brightness during winter may exacerbate psychological aspects [ 29 ]. Additionally, individuals with heightened nerve sensitivity may experience amplified muscle and joint pain in response to cold temperatures, as cold weather tends to negatively affect nerve conduction, intensifying existing nerve-related issues [ 30 ]. In a study conducted in Taiwan, patients with migraines were asked to keep a headache diary for one year, and 51.5% were affected by weather changes, but 48.5% were not [ 31 ]. However, the effects of the weather on headaches attributed to TMD have not yet been investigated. Approximately 67% of patients with joint pain, including osteoarthritis and rheumatoid arthritis, believe that weather factors worsen their symptoms; however, external weather conditions do not significantly affect the daily symptoms of arthritis [ 32 ]. According to Tsai et al., an abrupt temperature change is a triggering factor that increases arthralgia [ 33 ]. This can serve as evidence to support the results of this study, showing an increase in temperature change and the number of patients with TMD. In the most recently reported meta-analysis, levels of musculoskeletal pain were higher in cold countries and lower in countries with warm climates; however, heterogeneity in patient composition and a lack of studies hindered the valid synthesis or analysis of risk scales [ 34 ]. In a recent study conducted in Morocco, symptom severity in patients with rheumatoid arthritis was not significantly affected by seasonal changes in temperature [ 35 ]. However, Morocco is a country with a rainy season and a dry season, and the climate alternates between warm and humid (average 15 ℃) in the rainy season and hot and dry (average 28 ℃) in the dry season. Therefore, the situation differs from that in Korea, where the spring, summer, fall, and winter are distinct. Few studies have investigated changes in TMD prevalence or symptom severity according to seasonal or temperature changes. TMD is a major musculoskeletal disorder affecting the orofacial region and is one of the most common conditions causing severe facial pain [ 5 , 6 ]. Additional research is needed to determine the myth or reality of changes in TMD symptoms depending on weather or season. An essential aspect of this study was the utilization of robust national data spanning a 13-year period to conduct statistical analyses of patients seeking treatment for TMD at hospitals. Notably, our findings align with prior research on TMD prevalence, indicating a peak occurrence among individuals in their 20s [ 36 , 37 ]. However, according to a prospective cohort study in the United States, the incidence of TMD tends to increase with age, with the highest incidence in the 35–44 years age group [ 38 ]. In this study, a noteworthy departure was observed in the mid-to-late teenage demographics, exhibiting substantial prevalence, unlike the patterns observed in other studies. Contrary to prevailing trends, this age group (mid-to-late teenage) demonstrated a heightened prevalence, potentially linked to the social and psychological stress experienced by Korean middle and high school students [ 39 ]. Academic pressure, interpersonal relationships, and developmental challenges during this phase may have contributed to the atypical prevalence. Additionally, a notable observation was the significant occurrence of TMD among the elderly, particularly those aged over 65 years and notably over 80 years. One limitation of this study is the lack of a detailed examination of TMD diagnosis, symptom severity, duration, and treatment specifics among patients with TMD. While acknowledging the significant influence of psychological factors on the physical factors of signs and symptoms of TMD, this study did not incorporate these psychological aspects. During the transition from fall to winter, colder temperatures and reduced sunlight durations may trigger mood alterations or depression in certain individuals [ 40 ]. TMD is defined as chronic pain, and weather and temperature factors that affect mood and psychology have been considered in chronic pain [ 41 , 42 ]. Additional comprehensive investigations and analyses of these elements are required. For the first time, we investigated the fluctuations in TMD patient numbers concerning seasons and temperature variations in Korea, utilizing HIRA healthcare big data in conjunction with data from the Korea Meteorological Administration. Consequently, we were able to elucidate the trends in the number of patients with TMD associated with distinct seasonal variations in Korea. Although the decrease in absolute temperature influenced the increase in the number of patients with TMD, the difference between the highest and lowest temperatures was a more decisive factor in Korea. Declarations Acknowledgments: The authors thank Sung-Woo Lee of the Department of Oral Medicine and Oral Diagnosis at the Seoul National University School of Dentistry. Conflict of interest statement The author declares no competing interests. Funding: This work was supported by the Korea Medical Device Development Fund grant funded by the Korean government (Ministry of Science and ICT; Ministry of Trade, Industry, and Energy; Ministry of Health & Welfare, Republic of Korea; Ministry of Food and Drug Safety) (Project Number: KMDF_PR_20200901_0023, 9991006696). Author contributions Conceptualization: Y.-H.L., Investigation: Y.-H.L., Visualization: Y.-H.L., Writing: Y.-H.L. and J.-W.C., Review and editing: Y.-H.L. and J.-W.C. Data availability statement: The datasets used and/or analyzed in the current study are available from the corresponding author upon reasonable request. Korean patients' health statuses, medical providers, medical expenses, utilization rates, and summary statistics related to medical services were made public through the Healthcare Big Data Open System (http://opendata.hira.or.kr). Monthly temperature data for the past 13 years were obtained from the National Climate Data Center of the Korea Meteorological Administration (https://data.kma.go.kr). Competing interests : The author declares no competing interests. Ethics declaration The protocol for this study was exempt from review by the Institutional Review Board of Kyung Hee University Dental Hospital. Consent to participate: N/A Consent to publish The author has read and agreed to the published version of the manuscript. References Choi B, Choi HM, Choi Y, Kim I, Hwang S: High Temperature and Its Association With Work-Related Injuries by Employment Status in South Korea, 2017-2018 . J Occup Environ Med 2022, 64 (11):e690-e694. Choi G, Lee DE: Changing human-sensible temperature in Korea under a warmer monsoon climate over the last 100 years . Int J Biometeorol 2020, 64 (5):729-738. Lee Y-H, Lee KM, Kim T, Hong J-P: Psychological Factors that Influence Decision-Making Regarding Trauma-Related Pain in Adolescents with Temporomandibular Disorder . Scientific Reports 2019, 9 (1):18728. Sharma S, Gupta DS, Pal US, Jurel SK: Etiological factors of temporomandibular joint disorders . Natl J Maxillofac Surg 2011, 2 (2):116-119. Lee YH, Lee KM, Auh QS: MRI-Based Assessment of Masticatory Muscle Changes in TMD Patients after Whiplash Injury . J Clin Med 2021, 10 (7). Kapos FP, Exposto FG, Oyarzo JF, Durham J: Temporomandibular disorders: a review of current concepts in aetiology, diagnosis and management . Oral Surg 2020, 13 (4):321-334. Al-Moraissi EA, Christidis N, Ho Y-S: Publication performance and trends in temporomandibular disorders research: A bibliometric analysis . Journal of Stomatology, Oral and Maxillofacial Surgery 2023, 124 (1):101273. Bueno CH, Pereira DD, Pattussi MP, Grossi PK, Grossi ML: Gender differences in temporomandibular disorders in adult populational studies: A systematic review and meta-analysis . J Oral Rehabil 2018, 45 (9):720-729. LeResche L: Epidemiology of temporomandibular disorders: implications for the investigation of etiologic factors . Crit Rev Oral Biol Med 1997, 8 (3):291-305. Schiffman E, Ohrbach R, Truelove E, Look J, Anderson G, Goulet JP, List T, Svensson P, Gonzalez Y, Lobbezoo F et al : Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) for Clinical and Research Applications: recommendations of the International RDC/TMD Consortium Network* and Orofacial Pain Special Interest Group† . J Oral Facial Pain Headache 2014, 28 (1):6-27. Lee Y-H, Auh QS, An J-S, Kim T: Poorer sleep quality in patients with chronic temporomandibular disorders compared to healthy controls . BMC Musculoskeletal Disorders 2022, 23 (1):246. Lee Y-H, Auh QS: Comparison of sleep quality deterioration by subgroup of painful temporomandibular disorder based on diagnostic criteria for temporomandibular disorders . Scientific Reports 2022, 12 (1):9026. John MT, Dworkin SF, Mancl LA: Reliability of clinical temporomandibular disorder diagnoses . Pain 2005, 118 (1):61-69. Raphael KG, Janal MN, Sirois DA, Dubrovsky B, Klausner JJ, Krieger AC, Lavigne GJ: Validity of self-reported sleep bruxism among myofascial temporomandibular disorder patients and controls . J Oral Rehabil 2015, 42 (10):751-758. Slade GD, Sanders AE, Bair E, Brownstein N, Dampier D, Knott C, Fillingim R, Maixner WO, Smith S, Greenspan J et al : Preclinical episodes of orofacial pain symptoms and their association with health care behaviors in the OPPERA prospective cohort study . Pain 2013, 154 (5):750-760. Racinais S, Cocking S, Périard JD: Sports and environmental temperature: From warming-up to heating-up . Temperature (Austin) 2017, 4 (3):227-257. Gatterer H, Dünnwald T, Turner R, Csapo R, Schobersberger W, Burtscher M, Faulhaber M, Kennedy MD: Practicing Sport in Cold Environments: Practical Recommendations to Improve Sport Performance and Reduce Negative Health Outcomes . Int J Environ Res Public Health 2021, 18 (18). Cheshire WP: Thermoregulatory disorders and illness related to heat and cold stress . Autonomic Neuroscience 2016, 196 :91-104. Wang L, Xu Q, Chen Y, Zhu Z, Cao Y: Associations between weather conditions and osteoarthritis pain: a systematic review and meta-analysis . Ann Med 2023, 55 (1):2196439. Lee Y-H, Auh QS: Clinical factors affecting depression in patients with painful temporomandibular disorders during the COVID-19 pandemic . Scientific Reports 2022, 12 (1):14667. Furquim BD, Flamengui LM, Conti PC: TMD and chronic pain: a current view . Dental Press J Orthod 2015, 20 (1):127-133. Berglund B, Harju EL, Kosek E, Lindblom U: Quantitative and qualitative perceptual analysis of cold dysesthesia and hyperalgesia in fibromyalgia . Pain 2002, 96 (1-2):177-187. Tuveson B, Lindblom U, Fruhstorfer H: Experimental muscle pain provokes long-lasting alterations of thermal sensitivity in the referred pain area . Eur J Pain 2003, 7 (1):73-79. Jahan F, Nanji K, Qidwai W, Qasim R: Fibromyalgia syndrome: an overview of pathophysiology, diagnosis and management . Oman Med J 2012, 27 (3):192-195. Terao C, Hashimoto M, Furu M, Nakabo S, Ohmura K, Nakashima R, Imura Y, Yukawa N, Yoshifuji H, Matsuda F et al : Inverse association between air pressure and rheumatoid arthritis synovitis . PLoS One 2014, 9 (1):e85376. Gracey E, Burssens A, Cambré I, Schett G, Lories R, McInnes IB, Asahara H, Elewaut D: Tendon and ligament mechanical loading in the pathogenesis of inflammatory arthritis . Nat Rev Rheumatol 2020, 16 (4):193-207. Lurati AR: Health Issues and Injury Risks Associated With Prolonged Sitting and Sedentary Lifestyles . Workplace Health Saf 2018, 66 (6):285-290. Kuppili PP, Selvakumar N, Menon V: Sickness Behavior and Seasonal Affective Disorder: An Immunological Perspective of Depression . Indian J Psychol Med 2018, 40 (3):266-268. Walker WH, 2nd, Walton JC, DeVries AC, Nelson RJ: Circadian rhythm disruption and mental health . Transl Psychiatry 2020, 10 (1):28. Vale TA, Symmonds M, Polydefkis M, Byrnes K, Rice ASC, Themistocleous AC, Bennett DLH: Chronic non-freezing cold injury results in neuropathic pain due to a sensory neuropathy . Brain 2017, 140 (10):2557-2569. Yang AC, Fuh JL, Huang NE, Shia BC, Wang SJ: Patients with migraine are right about their perception of temperature as a trigger: time series analysis of headache diary data . J Headache Pain 2015, 16 :533. Sibley JT: Weather and arthritis symptoms . J Rheumatol 1985, 12 (4):707-710. Tsai WS, Yang YH, Wang LC, Chiang BL: Abrupt temperature change triggers arthralgia in patients with juvenile rheumatoid arthritis . J Microbiol Immunol Infect 2006, 39 (6):465-470. Farbu EH, Höper AC, Reierth E, Nilsson T, Skandfer M: Cold exposure and musculoskeletal conditions; A scoping review . Front Physiol 2022, 13 :934163. Azzouzi H, Ichchou L: Seasonal and Weather Effects on Rheumatoid Arthritis: Myth or Reality? Pain Res Manag 2020, 2020 :5763080. Gauer RL, Semidey MJ: Diagnosis and treatment of temporomandibular disorders . Am Fam Physician 2015, 91 (6):378-386. Omezli MM, Torul D, Varer Akpinar C: Temporomandibular disorder severity and its association with psychosocial and sociodemographic factors in Turkish adults . BMC Oral Health 2023, 23 (1):34. Slade GD, Fillingim RB, Sanders AE, Bair E, Greenspan JD, Ohrbach R, Dubner R, Diatchenko L, Smith SB, Knott C et al : Summary of findings from the OPPERA prospective cohort study of incidence of first-onset temporomandibular disorder: implications and future directions . J Pain 2013, 14 (12 Suppl):T116-124. Hong CH: Current health issues in Korean adolescents . Korean J Pediatr 2011, 54 (10):395-400. Melrose S: Seasonal Affective Disorder: An Overview of Assessment and Treatment Approaches . Depress Res Treat 2015, 2015 :178564. Dworkin SF, Massoth DL: Temporomandibular disorders and chronic pain: disease or illness? J Prosthet Dent 1994, 72 (1):29-38. Jamison RN, Anderson KO, Slater MA: Weather changes and pain: perceived influence of local climate on pain complaint in chronic pain patients . Pain 1995, 61 (2):309-315. Table 5 Table 5 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table5.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 04 Mar, 2024 Reviews received at journal 04 Mar, 2024 Reviewers agreed at journal 28 Feb, 2024 Reviews received at journal 02 Feb, 2024 Reviewers agreed at journal 27 Jan, 2024 Reviewers agreed at journal 24 Jan, 2024 Reviewers invited by journal 22 Jan, 2024 Editor assigned by journal 22 Jan, 2024 Editor invited by journal 31 Dec, 2023 Submission checks completed at journal 31 Dec, 2023 First submitted to journal 29 Dec, 2023 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-3821655","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":264865289,"identity":"3b415098-541b-4651-8271-bc6260aab44e","order_by":0,"name":"Yeon-Hee Lee","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYJACiYQKCTl+ECuhgFgtH87YGEs2gLQYEKlFcmZbWuKGAyAmMVr4xQ4fvM3Ddjhx8/nViR8eGDDI84sdIGDD7LRkax6ew8bbbrzdLAF0mOHM2Qn4tRjczjGT5pE4LLvtxtkNIC0JBreJ0mJwmHHzjLObfxCtRXJGQpriBv7ebcTZAvKLxYcDNsYSN3i3WSQYSBD2C7908sEbif+AUdl/dvPNHxU28vzSBLQggARYpQSxysH2HSBF9SgYBaNgFIwkAABmBkY6UviVWwAAAABJRU5ErkJggg==","orcid":"","institution":"Kyung Hee University, Kyung Hee University","correspondingAuthor":true,"prefix":"","firstName":"Yeon-Hee","middleName":"","lastName":"Lee","suffix":""},{"id":264865290,"identity":"8c3f2799-afd2-44c6-bb7f-70d5da1b6335","order_by":1,"name":"Jin-Woo Chung","email":"","orcid":"","institution":"Seoul National University School of Dentistry","correspondingAuthor":false,"prefix":"","firstName":"Jin-Woo","middleName":"","lastName":"Chung","suffix":""}],"badges":[],"createdAt":"2023-12-29 14:59:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3821655/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3821655/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49129156,"identity":"ad7a26cb-ad8b-4732-bd83-f673fafe9c37","added_by":"auto","created_at":"2024-01-03 15:13:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":78135,"visible":true,"origin":"","legend":"\u003cp\u003eIncreased incidence of TMD over the past 13 years\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3821655/v1/c35536d7b3a6fc643c21a015.png"},{"id":49129154,"identity":"977fac7f-5246-456f-8e31-c3f760e5abd3","added_by":"auto","created_at":"2024-01-03 15:13:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":138773,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of TMD patients by age and gender in 2022\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3821655/v1/5f7fbfce6f671fa5aba215c6.png"},{"id":49129155,"identity":"ace95c33-6d8f-4f6e-a9a6-88b1bc94b060","added_by":"auto","created_at":"2024-01-03 15:13:21","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":76278,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of TMD patients by type of healthcare institution in 2022\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3821655/v1/317dee324a4126cbe59eb050.png"},{"id":49129924,"identity":"85059a4f-836c-45a2-b3d6-c72a0359d7af","added_by":"auto","created_at":"2024-01-03 15:21:21","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":160359,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of the number of patients by region in South Korea\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3821655/v1/8aa322f7a813f1165c97e410.png"},{"id":49130168,"identity":"4b86fc80-7fc0-45d3-927b-e694621c815d","added_by":"auto","created_at":"2024-01-03 15:29:21","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":354847,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of TMD patients according to seasons\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-3821655/v1/0fcac1ed3dbacccc8446ac02.png"},{"id":49129159,"identity":"0a06424a-d127-4f4f-ab12-b7a87364932e","added_by":"auto","created_at":"2024-01-03 15:13:21","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":126775,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between temperature difference among the lowest and highest temperatures and the number of TMD patients. (A) Spring, (B) summer, (C) fall, and (D) winter. X-axis: temperature difference, y-axis: the number of TMD patients.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-3821655/v1/d124800868756f1987a0e569.png"},{"id":49130926,"identity":"21d800ac-d608-4296-99af-a6f878777c94","added_by":"auto","created_at":"2024-01-03 15:37:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2264447,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3821655/v1/a049dc74-aad2-49a5-9383-7d9faead2036.pdf"},{"id":49129153,"identity":"ffcf3ba5-f728-4269-9fe8-e7bd0ca14500","added_by":"auto","created_at":"2024-01-03 15:13:21","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15522,"visible":true,"origin":"","legend":"","description":"","filename":"Table5.docx","url":"https://assets-eu.researchsquare.com/files/rs-3821655/v1/2e8f0e0e258715701a906b44.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The seasonal influence on TMD prevalence in South Korea which has four seasons","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSouth Korea is renowned for its pronounced seasonal diversity encompassing spring, summer, fall, and winter. Spring, observed from March to mid-May, sees temperatures ranging between 10\u0026deg;C and 20\u0026deg;C, coinciding with the blossoming of flora and the emergence of leaves. Although it typically is warm and agreeable, intermittent cold snaps may be accompanied by brisk winds. Summer, spanning from June to mid-August, experiences temperatures surging between 25\u0026deg;C and 35\u0026deg;C accompanied by escalated humidity, often resulting in sultry and occasionally rainy conditions during the monsoon season [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This season may encounter strong winds and heavy rainfall due to the influence of typhoons. Fall, extending from September to mid-November, boasts mild temperatures ranging from 10\u0026deg;C to 20\u0026deg;C, characterized by clear and pleasant weather. Finally, winter extends from December to February with witnessed temperatures plunging below freezing temperatures, particularly in inland and mountainous areas, with numerous regions experiencing subzero temperatures. Frequent snowfall is common and is compounded by varying humidity levels that contribute to a further reduction in perceived temperatures [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Notably, South Korea's climate presents a unique contrast, with a difference in temperature of over 35\u0026deg;C between winter and summer.\u003c/p\u003e \u003cp\u003eTemporomandibular disorders (TMD) include various conditions affecting the temporomandibular joint (TMJ) and the associated masticatory muscles, bones, and tissues [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The etiology of TMD is multifaceted, potentially involving muscle or cartilage damage around the TMJ, TMJ instability, muscle tension due to psychological stress, malocclusion, macrotrauma, microtrauma, and systemic disorders, such as rheumatism or growth issues during childhood or adolescence [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. While prevalence rates may vary based on sex, age, and geographical location, reports indicate that most individuals experience TMD-related symptoms at least once in their lifetimes [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. TMD is highly prevalent worldwide, with an overall prevalence of approximately 31% in adults and 11% in children/adolescents [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Notably, it tends to be a 2\u0026ndash;4 times higher prevalence among women compared to men, particularly in their 20s and 40s [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe signs and symptoms of TMD are diverse and contribute to its diagnosis. Key symptoms include pain or discomfort in the TMJ area; TMJ noises such as clicking, popping, and crepitus; sensation of jaw locking or restricted mandibular movement; deformities or swelling around the TMJ; muscle stiffness; ear pain; tinnitus; neck pain; and headaches [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. These symptoms significantly affect daily life and restrict activities such as eating, speaking, and facial expressions. Accurate diagnosis and appropriate treatment planning are crucial for effective management of TMD. Additionally, persistent TMD symptoms may be accompanied by sleep disturbances or psychological issues [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Hence, understanding the nature of TMD and addressing its diagnosis, treatment, management, and prevention is imperative.\u003c/p\u003e \u003cp\u003eHistorically, TMD has been classified with various systems, such as the Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) and the Diagnostic Criteria for Temporomandibular Disorders (DC/TMD), which play significant roles in defining and categorizing TMD. The RDC/TMD, developed in the 1990s, was among the initial comprehensive systems used for diagnosing TMD [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. It is categorized based on clinical and imaging criteria and divided into groups such as myofascial pain, internal derangement, and arthralgia. Subsequently, the DC/TMD introduced by the International RDC/TMD Consortium Network in 2014 refined and updated the classification system [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. It expanded the diagnostic categories, incorporated more specific assessment methods, and integrated both physical and psychosocial factors, emphasizing a more comprehensive approach to diagnosing and managing TMD. In South Korea, TMD specialists and general dentists diagnose patients based on the international TMD diagnostic criteria. National data in South Korea are categorized under the overarching term temporomandibular disorder (K07.6) and its subcategories (K07.60-K07.69).\u003c/p\u003e \u003cp\u003eHowever, research on TMD using South Korea's healthcare big data and national population-based data is limited. To date, associations between various factors such as region, race, and sex and TMD occurrence have been reported [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. During winter, the human body adapts to cold weather and attempts to regulate the internal temperature, increase muscle contraction, and decrease oxygen supply to the muscles, resulting in increased muscle pain or stiffness [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Arthritic pain can also increase during cold winters and at low temperatures as opposed to during summer and warm temperatures. A recent systematic review of osteoarthritis pain reported a negative correlation between temperature and pain severity [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, the association between TMD pain and weather conditions remains unclear. Therefore, this study aimed to investigate seasonal fluctuations in TMD prevalence in South Korea using nationwide population-based data from the Health Insurance Review and Assessment Service (HIRA), also called the National Health Insurance data. Moreover, this study sought to examine the hypothesis that TMD prevalence increases during winter.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eHIRA serves as a nationally representative healthcare big data repository that collects billing data throughout the reimbursement process for healthcare service providers. The universal coverage system contains extensive and comprehensive information regarding medical services encompassing treatments, medications, procedures, and diagnoses for around 50\u0026nbsp;million beneficiaries covered under Korea's universal healthcare system. The HIRA dataset, which constitutes a substantial repository within the healthcare sector, has a significant potential for creating value across various domains. This aids in enhancing the efficiency of healthcare delivery systems while maintaining high-quality care, offering support for specific interventions, and furnishing crucial information to prevent or monitor side effects. Leveraging HIRA data for research is imperative to unlock its potential in understanding symptoms and managing, treating, and addressing activities related to patients with TMD. In this study, we analyzed prevalence trends under relevant circumstances among all cases classified under \u0026ldquo;temporomandibular joint disorders (K07.6)\u0026rdquo; in the HIRA dataset spanning 13 years from 2010 to 2022.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData acquisition\u003c/h2\u003e \u003cp\u003eAll the data used in this study were obtained from officially accredited sources in the public domain. Korean patients' health statuses, medical providers, medical expenses, utilization rates, and summary statistics related to medical services were made public through the Healthcare Big Data Open System (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://opendata.hira.or.kr\u003c/span\u003e\u003cspan address=\"http://opendata.hira.or.kr\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Monthly temperature data for the past 13 years were obtained from the National Climate Data Center of the Korea Meteorological Administration (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://data.kma.go.kr\u003c/span\u003e\u003cspan address=\"https://data.kma.go.kr\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData were analyzed using the Statistical Package for Social Sciences (SPSS) for Windows (version 26.0; IBM Corp. Armonk, NY, USA). Descriptive statistics were reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or numbers with percentages, as appropriate. To analyze the distribution of discontinuous data, we used the χ\u003csup\u003e2\u003c/sup\u003e and Bonferroni tests for equality of proportions. The t-test was used to compare the means between the two groups. Analysis of variance and Tukey\u0026rsquo;s post-hoc tests were used to compare the parameter values for the four seasons (spring, summer, fall, and winter) and for the 12 months from January to December. Spearman's correlation analysis was conducted to explore the correlation between two parameters. The closer the absolute value of the correlation coefficient (r) is to 1, the stronger the correlation, whereas values closer to 0 indicate a weaker correlation. Statistical significance was set at a two-tailed p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence and the number of patients with TMD\u003c/h2\u003e \u003cp\u003eBy analyzing health data from January 2010 to March 2022 published by the HIRA we investigated the number of patients (prevalence) who visited hospitals due to TMD in Korea. In 2022, the total population of Korea was 51.74\u0026nbsp;million, and the number of patients who visited hospitals and clinics due to TMD was 484,241; accounting for 0.94% of the total Korean population. The period with the largest increase in the number of patients over the 13 years studied was 2010\u0026ndash;2011, with an increase of 12.86%. The second period with the largest increase was 2020\u0026ndash;2021, with an increase of 8.42% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFurther investigation is needed to determine whether the increase in the number of patients with TMD between 2020 and 2021 is correlated with the COVID-19 pandemic. From 2010 to 2022, the number of patients increased by 97.89%, from 244,708 to 484,241. In Korea, the number of patients with TMD has increased steadily over the past 13 years.\u003c/p\u003e \u003cp\u003eThe number of women with TMD increased from 148,110 in 2010 to 289,525 in 2022, marking a surge of 95.48%. Among males, the increase was 101.57%, from 96,598 in 2010 to 194,716 in 2022. Consequently, the growth rate of TMD patients in males was 6.09% higher than that in females (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePeak prevalence of TMD in the 20s age group\u003c/h2\u003e \u003cp\u003ePatients who visited the hospital in 2022 were divided in five-year intervals, the largest age group was 20\u0026ndash;24 years old, followed by 25\u0026ndash;29 years old, 15\u0026ndash;19 years old, 30\u0026ndash;34 years old, and 50\u0026ndash;54 years old, 45\u0026ndash;49 years old, 40\u0026ndash;44 years old, 60\u0026ndash;64 years old, 35\u0026ndash;39 years old, 55\u0026ndash;59 years old, 10\u0026ndash;14 years old, 70\u0026ndash;74 years old, 75\u0026thinsp;\u0026minus;\u0026thinsp;59 years old, 80\u0026thinsp;+\u0026thinsp;years old, 5\u0026ndash;9 years old, \u0026lt;\u0026thinsp;5 years old; the frequency trends according to age group among all TMD patients were similar in both males and females.\u003c/p\u003e \u003cp\u003eInterestingly mid-to-late teens (15\u0026ndash;19 years old) had the 3rd highest number of TMD patients out of a total of 17 age groups, while early teens (10\u0026ndash;14 years old) ranked 12th. Additionally, TMD occurred even in children under the age of 10 years, and in very elderly people aged over 80 years; TMD occurred in 21,909 people (Fig.\u0026nbsp;2a).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eThe female-to-male ratio among TMD patients across age groups\u003c/h2\u003e \u003cp\u003eThe female-to-male ratio of all patients admitted to the hospital in 2022 is 1.84:1. The female-to-male ratio of patients who visited the hospital in 2022 was calculated according to 17 age groups (Fig.\u0026nbsp;2b). When examining the ratio of females to males in the 17 age groups (5-year age range), the ratio of males to females was higher in the \u0026lt;\u0026thinsp;5 (0.98:1) and 5\u0026ndash;9 (0.97:1) age groups. Excluding these two groups, in all 15 age groups, TMD was more prevalent in women than in men (ranges: 2.23\u0026ndash;1.37:1). The highest ratio was 2.23 in the 50\u0026ndash;54 age group. The lowest ratio was in the 15\u0026ndash;19 age group, with a value of 1.37:1.\u003c/p\u003e \u003cp\u003eThere was no gender difference in the number of TMD patients in the past 13 years from 2010 to 2022 in those under 10 years of age; there was a statistically significant difference in the number of TMD patients between males and females in the age range of under 5 years (171.71\u0026thinsp;\u0026plusmn;\u0026thinsp;47.35 vs 181.07\u0026thinsp;\u0026plusmn;\u0026thinsp;39.27, p\u0026thinsp;=\u0026thinsp;0574) and 5\u0026ndash;9 years (1246.21\u0026thinsp;\u0026plusmn;\u0026thinsp;151.04 vs 1179\u0026thinsp;\u0026plusmn;\u0026thinsp;153.91, p\u0026thinsp;=\u0026thinsp;0.254). In the other 15 5-year age groups, the number of patients with TMD was higher in women than in men (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The female predominance trend was the same among elderly people aged\u0026thinsp;\u0026gt;\u0026thinsp;65 years and super-aged patients aged\u0026thinsp;\u0026gt;\u0026thinsp;80 years (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eDistribution of TMD patients by type of healthcare institution in 2022\u003c/h2\u003e \u003cp\u003eIn Korea, the treatment of patients with TMD was conducted on an outpatient basis, and outpatients (99.9%) overwhelmingly outnumbered inpatients (0.1%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Considering each type of healthcare institution, in the distribution of total medical expenses by type of healthcare institution, clinic-level care accounted for an overwhelmingly higher proportion (75.8%) than other types (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). Medical expenses for hospital-level care accounted for 19%, while general hospitals accounted for 2.6%, and tertiary general hospitals accounted for 2.5% of the total. The medical expenses of patients with TMD at public health institutions were 0.0%. Statistics on treatment days also showed a similar pattern to that of medical expenses, with clinic-level care accounting for an overwhelmingly large proportion (70.7%; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). This was followed by hospital care (23.4%), tertiary general hospitals (3.5%), general hospitals (2.4%), and public health institutions (0.0%).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eThe distribution of the number of TMD patients by region\u003c/h2\u003e \u003cp\u003eAt the city level, the distribution of patient numbers was as follows: Seoul (121,886, 26.92%), Pusan (32,632, 7.21%), Daegu (26,869, 5.94%), Incheon (23,271, 5.14%), Daejeon (15,859, 3.50%), Gwangju (14,625, 3.23%), Ulsan (8,943, 1.98%), Jeju (4,450, 0.98%), and Sejong (2,659, 0.59%). At the provincial level, it was Gyeonggi (101,484, 22.42%), Gyeongsangnam-do (25,465, 5.63%), Chungcheongnam-do (16,137, 3.57%), Jeollabuk-do (14,219, 3.14%), Gyeongsangbuk-do (12,433, 2.75%), Chungcheongbuk-do (11,442, 2.53%), Gangwon-do (10,028, 2.22%), and Jeollanam-do (10,246, 2.26%). The incidence in the capital region, including Seoul and Gyeonggi, accounted for approximately 49.35% of the total, nearly half of the total occurrence (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). Similar results were found when examining the regional distribution of the number of patients as the average of the data over the past five years (2018\u0026ndash;2022). At the city level, Seoul (12886 patients), and at the provincial level, Gyeonggi-do (101484 patients) had the highest number of TMD patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eb).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDistribution of TMD patient numbers across 12 months in a year\u003c/h2\u003e \u003cp\u003eInterestingly, when the number of patients was divided into 12 months, there was no significant difference between the months (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the monthly change trend in patients with TMD over the past 13 years (2010\u0026ndash;2022). The number of patients on Korea's summer vacation, summer vacation, and winter vacation during July-August (the average number of patients: 48854\u0026ndash;49292) and December-January (the average number of patients: 47164\u0026ndash;48718) was higher at a statistically insignificant level than in other months. Unusually, the number of patients was higher in November (48370) than in March, April, May, June, September, and October, although this was not a vacation period, and the number was not statistically significant (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This may mean that cold weather or large daily temperature differences contribute to an increase in the number of patients with TMD, even if it is not a vacation or a vacation period when there is relatively ample time. The number of TMD patients in December (48718) increased by 7.01% compared to the number of TMD patients in September (45528).\u003c/p\u003e \u003cp\u003eHowever, when the 12 months were divided into four seasons (March-June: spring; July\u0026ndash;August: summer; September-November: fall; and December\u0026ndash;February: winter), completely different results were obtained. There were significantly more TMD patients in the summer season (49073\u0026thinsp;\u0026plusmn;\u0026thinsp;309) than in spring (46379\u0026thinsp;\u0026plusmn;\u0026thinsp;390) and fall (46161\u0026thinsp;\u0026plusmn;\u0026thinsp;894) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). There was no significant difference in the number of TMD patients in winter (47941\u0026thinsp;\u0026plusmn;\u0026thinsp;1099) compared to summer. The number of patients with TMD in winter was higher than that in spring and fall, and the number of patients with TMD in winter increased by 3.86% compared to spring and by 3.59% compared to fall; however, the difference was not significant (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDistribution of climate temperature across 12 months in a year\u003c/h2\u003e \u003cp\u003eThe average temperature in January was the lowest; however, there was no significant difference between the average temperatures in December and February (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). These three months had significantly lower averages than the other nine months. The average temperature in the months corresponding to spring was higher than that in winter and lower than that in summer. The monthly climate temperatures were ranked as follows: August\u0026thinsp;\u0026gt;\u0026thinsp;July\u0026thinsp;\u0026gt;\u0026thinsp;June\u0026thinsp;\u0026gt;\u0026thinsp;September\u0026thinsp;\u0026gt;\u0026thinsp;May\u0026thinsp;\u0026gt;\u0026thinsp;October\u0026thinsp;\u0026gt;\u0026thinsp;April\u0026thinsp;\u0026gt;\u0026thinsp;November\u0026thinsp;\u0026gt;\u0026thinsp;March\u0026thinsp;\u0026gt;\u0026thinsp;February\u0026thinsp;\u0026gt;\u0026thinsp;December\u0026thinsp;\u0026gt;\u0026thinsp;January. However, there was no significant difference in the mean climate temperature between January (-2.325\u0026thinsp;\u0026plusmn;\u0026thinsp;2.156 ℃), February (0.367\u0026thinsp;\u0026plusmn;\u0026thinsp;1.603 ℃), and December (-0.6177\u0026thinsp;\u0026plusmn;\u0026thinsp;1.747 ℃), and between July (26.017\u0026thinsp;\u0026plusmn;\u0026thinsp;1.159 ℃) and August (26.742\u0026thinsp;\u0026plusmn;\u0026thinsp;1.047 ℃) (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The monthly averages of the highest and lowest temperatures exhibited the same pattern (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). The order of the largest temperature difference between the highest and lowest temperatures was May (10.325\u0026thinsp;\u0026plusmn;\u0026thinsp;1.057 ℃)\u0026thinsp;\u0026gt;\u0026thinsp;April (10.033\u0026thinsp;\u0026plusmn;\u0026thinsp;0.817 ℃)\u0026thinsp;\u0026gt;\u0026thinsp;October (9.908\u0026thinsp;\u0026plusmn;\u0026thinsp;0.632 ℃)\u0026thinsp;\u0026gt;\u0026thinsp;March (9.700\u0026thinsp;\u0026plusmn;\u0026thinsp;1.111 ℃)\u0026thinsp;\u0026gt;\u0026thinsp;June (9.200\u0026thinsp;\u0026plusmn;\u0026thinsp;0.743 ℃)\u0026thinsp;\u0026gt;\u0026thinsp;February (8.933\u0026thinsp;\u0026plusmn;\u0026thinsp;0.618 ℃)\u0026thinsp;\u0026gt;\u0026thinsp;November (8.617\u0026thinsp;\u0026plusmn;\u0026thinsp;0.878 ℃)\u0026thinsp;\u0026gt;\u0026thinsp;September (8.517\u0026thinsp;\u0026plusmn;\u0026thinsp;0.958 ℃)\u0026thinsp;\u0026gt;\u0026thinsp;January (8.083\u0026thinsp;\u0026plusmn;\u0026thinsp;0.769 ℃)\u0026thinsp;\u0026gt;\u0026thinsp;December (7.933\u0026thinsp;\u0026plusmn;\u0026thinsp;0.641℃)\u0026thinsp;\u0026gt;\u0026thinsp;August (6.975\u0026thinsp;\u0026plusmn;\u0026thinsp;0.966 ℃)\u0026thinsp;\u0026gt;\u0026thinsp;July (6.767\u0026thinsp;\u0026plusmn;\u0026thinsp;0.885 ℃) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Since the average temperature difference per year was 8.76 ℃, the distribution was investigated by dividing it into cases of \u0026le;\u0026thinsp;8.76 ℃ and \u0026gt;\u0026thinsp;8.76 ℃ for each of the four seasons: spring, summer, fall, and winter (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The seasons with the highest proportion of temperature differences\u0026thinsp;\u0026gt;\u0026thinsp;8.76\u0026deg;C were spring (83.7%), followed by fall (63.9%), winter (33.3%), and summer (0.0%). The ratio of temperature difference\u0026thinsp;\u0026gt;\u0026thinsp;8.76 ℃ is spring\u0026thinsp;\u0026gt;\u0026thinsp;autumn\u0026thinsp;\u0026gt;\u0026thinsp;winter\u0026thinsp;\u0026gt;\u0026thinsp;summer (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eChanges in climate temperature and number of TMD patients over the past 13 years\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the cumulative changes in climate temperature and the number of patients with TMD over the past 13 years. Considering the climate temperature, Korea's temperature distribution was very clear according to spring, summer, fall, and winter, and by month from January to December (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Over the past 13 years, Korea's average temperature (temperature distribution of -8 ℃ \u0026minus;\u0026thinsp;29 ℃), minimum temperature, and maximum temperature range have been constant (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). Seasonal changes in the number of patients with TMD were less obvious than seasonal changes in climate temperature, and an increasing pattern was observed during summer vacation, vacation periods, and winter vacation and increased in fall and winter rather than in spring (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). Over the past 13 years, the number of patients with TMD has steadily increased with seasonal increases and decreases.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eThe correlation between the number of TMD patients and climate temperature\u003c/h2\u003e \u003cp\u003eIt is worth reporting that in all four seasons, the number of patients with TMD was not significantly correlated with the mean temperature (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). In spring, summer, and winter, excluding fall, the number of patients with TMD had a significant positive correlation with the temperature difference, which is the difference between the highest and lowest temperatures. The strongest correlation was observed between the number of patients with TMD and the temperature difference in winter (r\u0026thinsp;=\u0026thinsp;0.480, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), followed by summer (r\u0026thinsp;=\u0026thinsp;0.443, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and spring (r\u0026thinsp;=\u0026thinsp;0.366, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). In other words, the temperature difference during the day contributed more significantly to the increase in the number of patients with TMD than the average climate temperature (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eSex distribution of the number of TMD patients according to age group (2010-2022)\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.48076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge group\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(5y interval)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.28205128205128%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.21153846153846%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.025641025641026%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.48076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;5y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.28205128205128%\"\u003e\n \u003cp\u003e171.71 \u0026plusmn; 47.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.21153846153846%\"\u003e\n \u003cp\u003e181.07 \u0026plusmn; 39.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.025641025641026%\"\u003e\n \u003cp\u003e0.574\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.48076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003e5-9y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.28205128205128%\"\u003e\n \u003cp\u003e1246.21 \u0026plusmn; 151.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.21153846153846%\"\u003e\n \u003cp\u003e1179.02 \u0026plusmn; 153.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.025641025641026%\"\u003e\n \u003cp\u003e0.254\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.48076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003e10-14y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.28205128205128%\"\u003e\n \u003cp\u003e11146.21 \u0026plusmn; 1490.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.21153846153846%\"\u003e\n \u003cp\u003e21157.64 \u0026plusmn; 3545.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.025641025641026%\"\u003e\n \u003cp\u003e\u0026lt;0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.48076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003e15-19y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.28205128205128%\"\u003e\n \u003cp\u003e45566.29 \u0026plusmn; 3891.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.21153846153846%\"\u003e\n \u003cp\u003e65025.29 \u0026plusmn; 5876.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.025641025641026%\"\u003e\n \u003cp\u003e\u0026lt;0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.48076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003e20-24y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.28205128205128%\"\u003e\n \u003cp\u003e46684.64 \u0026plusmn; 11977.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.21153846153846%\"\u003e\n \u003cp\u003e77232 \u0026plusmn; 16494.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.025641025641026%\"\u003e\n \u003cp\u003e\u0026lt;0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.48076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003e25-29y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.28205128205128%\"\u003e\n \u003cp\u003e34369.01 \u0026plusmn; 10749.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.21153846153846%\"\u003e\n \u003cp\u003e64302.79 \u0026plusmn; 17174.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.025641025641026%\"\u003e\n \u003cp\u003e\u0026lt;0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.48076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003e30-34y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.28205128205128%\"\u003e\n \u003cp\u003e23131.86 \u0026plusmn; 6579.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.21153846153846%\"\u003e\n \u003cp\u003e45678.79 \u0026plusmn; 9435.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.025641025641026%\"\u003e\n \u003cp\u003e\u0026lt;0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.48076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003e35-39y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.28205128205128%\"\u003e\n \u003cp\u003e18489.64 \u0026plusmn; 4784.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.21153846153846%\"\u003e\n \u003cp\u003e39617.29 \u0026plusmn; 8203.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.025641025641026%\"\u003e\n \u003cp\u003e\u0026lt;0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.48076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003e40-44y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.28205128205128%\"\u003e\n \u003cp\u003e16804.71 \u0026plusmn; 3831.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.21153846153846%\"\u003e\n \u003cp\u003e37213.29 \u0026plusmn; 8868.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.025641025641026%\"\u003e\n \u003cp\u003e\u0026lt;0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.48076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003e45-49y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.28205128205128%\"\u003e\n \u003cp\u003e16796.79 \u0026plusmn; 4471.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.21153846153846%\"\u003e\n \u003cp\u003e36942.57 \u0026plusmn; 10879.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.025641025641026%\"\u003e\n \u003cp\u003e\u0026lt;0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.48076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003e50-54y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.28205128205128%\"\u003e\n \u003cp\u003e16550.07 \u0026plusmn; 4340.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.21153846153846%\"\u003e\n \u003cp\u003e37843.14 \u0026plusmn; 10177.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.025641025641026%\"\u003e\n \u003cp\u003e\u0026lt;0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.48076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003e55-59y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.28205128205128%\"\u003e\n \u003cp\u003e16014.21 \u0026plusmn; 5089.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.21153846153846%\"\u003e\n \u003cp\u003e35160.29 \u0026plusmn; 11471.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.025641025641026%\"\u003e\n \u003cp\u003e\u0026lt;0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.48076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003e60-64y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.28205128205128%\"\u003e\n \u003cp\u003e14332.29 \u0026plusmn; 5736.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.21153846153846%\"\u003e\n \u003cp\u003e27940.43 \u0026plusmn; 11989.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.025641025641026%\"\u003e\n \u003cp\u003e0.0007***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.48076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003e65-69y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.28205128205128%\"\u003e\n \u003cp\u003e12494.21 \u0026plusmn; 4312.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.21153846153846%\"\u003e\n \u003cp\u003e21931.36 \u0026plusmn; 7679.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.025641025641026%\"\u003e\n \u003cp\u003e\u0026lt;0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.48076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003e70-74y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.28205128205128%\"\u003e\n \u003cp\u003e10401.71 \u0026plusmn; 3117.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.21153846153846%\"\u003e\n \u003cp\u003e17284.29 \u0026plusmn; 4272.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.025641025641026%\"\u003e\n \u003cp\u003e\u0026lt;0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.48076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003e75-79y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.28205128205128%\"\u003e\n \u003cp\u003e7040.856 \u0026plusmn; 2649.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.21153846153846%\"\u003e\n \u003cp\u003e12675.93 \u0026plusmn; 3967.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.025641025641026%\"\u003e\n \u003cp\u003e\u0026lt;0.001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.48076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;\u003c/strong\u003e\u003cstrong\u003e80y\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.28205128205128%\"\u003e\n \u003cp\u003e4198.21 \u0026plusmn; 2007.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.21153846153846%\"\u003e\n \u003cp\u003e8224.57 \u0026plusmn; 3238.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.025641025641026%\"\u003e\n \u003cp\u003e0.0005***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe results were analyzed using t-tests. Statistical significance was set at p\u0026lt;0.05, *** p\u0026lt;0.001. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eDistribution of TMD patient numbers and temperature across 12 months in a year (2010-2022)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"647\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.166409861325116%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.785824345146379%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of TMD patients\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.855161787365177%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.015408320493066%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean temperature\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(℃)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.395993836671803%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.864406779661017%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLowest temperature\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(℃)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.395993836671803%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.864406779661017%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHighest temperature\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(℃)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.395993836671803%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.864406779661017%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTemperature difference\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(℃)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.395993836671803%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.166409861325116%\"\u003e\n \u003cp\u003e\u003cstrong\u003eJanuary\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.785824345146379%\"\u003e\n \u003cp\u003e\u003cstrong\u003e47164 \u0026plusmn; 10510\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.855161787365177%\" rowspan=\"12\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.974\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.015408320493066%\"\u003e\n \u003cp\u003e\u003cstrong\u003e-2.325 \u0026plusmn; 2.156\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.395993836671803%\" rowspan=\"12\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.864406779661017%\"\u003e\n \u003cp\u003e\u003cstrong\u003e-6.067 \u0026plusmn; 2.037\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.395993836671803%\" rowspan=\"12\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.864406779661017%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.017 \u0026plusmn; 2.385\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.395993836671803%\" rowspan=\"12\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.864406779661017%\"\u003e\n \u003cp\u003e\u003cstrong\u003e8.083 \u0026plusmn; 0.769\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.395993836671803%\" rowspan=\"12\"\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 width=\"12.649164677804295%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFebruary\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.706443914081145%\"\u003e\n \u003cp\u003e\u003cstrong\u003e45125 \u0026plusmn; 9599\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.513126491646778%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.367 \u0026plusmn; 1.603\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e-3.733 \u0026plusmn; 1.630\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.200 \u0026plusmn; 1.688\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e8.933 \u0026plusmn; 0.618\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.649164677804295%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarch\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.706443914081145%\"\u003e\n \u003cp\u003e\u003cstrong\u003e46631\u0026plusmn; 10996\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.513126491646778%\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.554 \u0026plusmn; 1.619\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.138 \u0026plusmn; 1.374\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e11.838 \u0026plusmn; 2.058\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e9.700 \u0026plusmn; 1.111\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.649164677804295%\"\u003e\n \u003cp\u003e\u003cstrong\u003eApril\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.706443914081145%\"\u003e\n \u003cp\u003e\u003cstrong\u003e45930 \u0026plusmn; 11392\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.513126491646778%\"\u003e\n \u003cp\u003e\u003cstrong\u003e12.350 \u0026plusmn; 1.677\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.75 \u0026plusmn; 1.418\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e17.783 \u0026plusmn; 2.074\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e10.033 \u0026plusmn; 0.817\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.649164677804295%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMay\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.706443914081145%\"\u003e\n \u003cp\u003e\u003cstrong\u003e46577 \u0026plusmn; 11644\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.513126491646778%\"\u003e\n \u003cp\u003e\u003cstrong\u003e18.550 \u0026plusmn; 0.914\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e13.767 \u0026plusmn; 0.668\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e24.092 \u0026plusmn; 1.400\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e10.325 \u0026plusmn; 1.0567\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.649164677804295%\"\u003e\n \u003cp\u003e\u003cstrong\u003eJune\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.706443914081145%\"\u003e\n \u003cp\u003e\u003cstrong\u003e43590 \u0026plusmn; 10368\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.513126491646778%\"\u003e\n \u003cp\u003e\u003cstrong\u003e23.317 \u0026plusmn; 0.678\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e19.233 \u0026plusmn; 0.709\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e28.433 \u0026plusmn; 0.899\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e9.200 \u0026plusmn; 0.743\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.649164677804295%\"\u003e\n \u003cp\u003e\u003cstrong\u003eJuly\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.706443914081145%\"\u003e\n \u003cp\u003e\u003cstrong\u003e50266 \u0026plusmn; 12519\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.513126491646778%\"\u003e\n \u003cp\u003e\u003cstrong\u003e26.017 \u0026plusmn; 1.159\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e23.05 \u0026plusmn; 1.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e29.817 \u0026plusmn; 1.408\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.767 \u0026plusmn; 0.885\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.649164677804295%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAugust\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.706443914081145%\"\u003e\n \u003cp\u003e\u003cstrong\u003e49292 \u0026plusmn; 10801\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.513126491646778%\"\u003e\n \u003cp\u003e\u003cstrong\u003e26.742 \u0026plusmn; 1.047\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e23.65 \u0026plusmn; 0.950\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e30.625 \u0026plusmn; 1.352\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.975 \u0026plusmn; 0.966\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.649164677804295%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSeptember\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.706443914081145%\"\u003e\n \u003cp\u003e\u003cstrong\u003e45528 \u0026plusmn; 11205\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.513126491646778%\"\u003e\n \u003cp\u003e\u003cstrong\u003e22.017 \u0026plusmn; 0.591\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e18.108 \u0026plusmn; 0.643\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e26.625 \u0026plusmn; 0.946\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e8.517 \u0026plusmn; 0.958\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.649164677804295%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOctober\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.706443914081145%\"\u003e\n \u003cp\u003e\u003cstrong\u003e46793 \u0026plusmn; 11659\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.513126491646778%\"\u003e\n \u003cp\u003e\u003cstrong\u003e15.233 \u0026plusmn; 1.008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e10.683 \u0026plusmn; 0.996\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e20.592 \u0026plusmn; 1.187\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e9.908 \u0026plusmn; 0.632\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.649164677804295%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNovember\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.706443914081145%\"\u003e\n \u003cp\u003e\u003cstrong\u003e48370 \u0026plusmn; 11421\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.513126491646778%\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.567 \u0026plusmn; 1.538\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.601 \u0026plusmn; 1.736\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e12.217 \u0026plusmn; 1.511\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e8.617 \u0026plusmn; 0.878\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.649164677804295%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDecember\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.706443914081145%\"\u003e\n \u003cp\u003e\u003cstrong\u003e48718 \u0026plusmn; 11668\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.513126491646778%\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.6177 \u0026plusmn; 1.747\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e-4.358 \u0026plusmn; 1.643\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.575 \u0026plusmn; 1.907\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.37708830548926%\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.933 \u0026plusmn; 0.641\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe results were analyzed using ANOVA. Statistical significance was set at p\u0026lt;0.05, *** p\u0026lt;0.001. \u0026nbsp;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eThe difference in TMD patient numbers across four seasons\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"538\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.769944341372913%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSeason\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.34508348794063%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of TMD patients\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Mean\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.769944341372913%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.11502782931354%\"\u003e\n \u003cp\u003e\u003cstrong\u003epost-hoc\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.769944341372913%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpring\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.34508348794063%\" valign=\"top\"\u003e\n \u003cp\u003e46379 \u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.769944341372913%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.021*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.11502782931354%\" rowspan=\"4\"\u003e\n \u003cp\u003eSpring \u0026lt; Summer, Fall \u0026lt; Summer\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.44493392070485%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSummer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"62.55506607929515%\" valign=\"top\"\u003e\n \u003cp\u003e49073 \u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e309\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.44493392070485%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"62.55506607929515%\" valign=\"top\"\u003e\n \u003cp\u003e46161 \u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e894\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.44493392070485%\"\u003e\n \u003cp\u003e\u003cstrong\u003eWinter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"62.55506607929515%\" valign=\"top\"\u003e\n \u003cp\u003e47941 \u003cstrong\u003e\u0026plusmn;\u003c/strong\u003e 1099\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe results were analyzed using ANOVA and post hoc analysis. Statistical significance was set at p\u0026lt;0.05, * p\u0026lt;0.05. \u0026nbsp;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003eThe proportion where the difference between the minimum and maximum temperatures within a day exceeds 8.76 ℃\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"614\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.781758957654723%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e Temperature difference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.517915309446254%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpring\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.169381107491857%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSummer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.749185667752442%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.37785016286645%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWinter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.798045602605864%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026le;\u003c/strong\u003e\u003cstrong\u003e8.76\u003c/strong\u003e\u003cstrong\u003e℃\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.98371335504886%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.517915309446254%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.169381107491857%\" valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.749185667752442%\" valign=\"top\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.37785016286645%\" valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.403908794788272%\" rowspan=\"4\" valign=\"top\"\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 width=\"22.77227722772277%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.544554455445546%\" valign=\"top\"\u003e\n \u003cp\u003e16.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.534653465346533%\" valign=\"top\"\u003e\n \u003cp\u003e100.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.336633663366335%\" valign=\"top\"\u003e\n \u003cp\u003e36.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e66.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.36127744510978%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;8.76℃\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.36327345309381%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.56686626746507%\" valign=\"top\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.365269461077844%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.173652694610778%\" valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.169660678642714%\" valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.77227722772277%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.544554455445546%\" valign=\"top\"\u003e\n \u003cp\u003e83.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.534653465346533%\" valign=\"top\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.336633663366335%\" valign=\"top\"\u003e\n \u003cp\u003e63.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.81188118811881%\" valign=\"top\"\u003e\n \u003cp\u003e33.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eResults were obtained using \u0026chi;\u003csup\u003e2\u003c/sup\u003e test and repeated \u0026chi;\u003csup\u003e2\u003c/sup\u003e test between two age groups. Statistical significance was set at p\u0026lt;0.05, *** p\u0026lt;0.001.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study aimed to ascertain whether the hypothesis that TMD occurs more frequently during colder winter months than warmer summer months in correlation with climate temperature is true. Therefore, we examined the number of patients with TMD based on the temperature and season. However, the analysis of the HIRA open big data revealed that the difference in TMD patient numbers between summer and winter was not significant. Surprisingly, the average number of patients with TMD during summer was the highest among the four seasons. Based on the analysis, the number of patients with TMD exhibited two peaks throughout the year, in August and December. This seems to correlate with summer and winter vacations in school and holidays for working individuals and students. Despite not being a period for vacations or holidays, November showed an increase in the number of patients with TMD compared to October. In other words, the number of patients can be affected to some extent by increases and decreases in the daily temperature range. However, the availability of time for patients to visit the hospital themselves or with their guardians during school or work vacations is interpreted as a major factor in the increase in the number of patients with TMD. By combining data from the Korean Meteorological Administration with HIRA big data, we first established a positive correlation between the temperature difference between the maximum and minimum climate temperatures and the number of TMD patients.\u003c/p\u003e \u003cp\u003eTMD is regarded as a heterogeneous group of conditions primarily characterized by a multifactorial pathogenesis [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The prevailing opinion is that TMD involves both physical and psychological factors; is understood to have a multifactorial etiology encompassing parafunctional habits, bruxism, maladaptive body posture, occlusal characteristics, developmental irregularities, macro or microtrauma, excessive loading, and stress [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Painful TMD has been demonstrated to be biopsychosocial and multifactorial [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. One factor that may influence the occurrence of TMD symptoms is cold or low temperatures. There have been consistent reports about the association between lower temperatures and increased muscle pain [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. As the temperature decreases, individuals with chronic pain often experience an exacerbation of symptoms. This leads to increased joint discomfort, heightened muscle tension, and intense sharp pains [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. However, despite speculation regarding the correlation between climatic temperature and TMD prevalence, only weak direct evidence supports this relationship.\u003c/p\u003e \u003cp\u003eAccording to the DC/TMD, common TMD can be classified into arthrogenous and myogenous TMD, and headaches can be attributed to TMD. Some factors can contribute to increased joint or muscle pain in cold weather. When temperatures drop, air pressure tends to decrease, which can directly impact joint sensitivity [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This might result in the expansion of soft tissues such as tendons and muscles, exerting more pressure on inflammatory arthritic joints and causing discomfort during movement [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Moreover, colder weather often leads to reduced physical activity and prolonged indoor stay. Extended periods of inactivity can lead to muscle weakening and decreased joint flexibility, contributing to muscle stiffness and an increased risk of painful cramps [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Seasonal affective disorder, which is prevalent during colder months, may influence pain perception owing to its impact on mood [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Reduced daylight exposure and brightness during winter may exacerbate psychological aspects [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Additionally, individuals with heightened nerve sensitivity may experience amplified muscle and joint pain in response to cold temperatures, as cold weather tends to negatively affect nerve conduction, intensifying existing nerve-related issues [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In a study conducted in Taiwan, patients with migraines were asked to keep a headache diary for one year, and 51.5% were affected by weather changes, but 48.5% were not [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, the effects of the weather on headaches attributed to TMD have not yet been investigated.\u003c/p\u003e \u003cp\u003eApproximately 67% of patients with joint pain, including osteoarthritis and rheumatoid arthritis, believe that weather factors worsen their symptoms; however, external weather conditions do not significantly affect the daily symptoms of arthritis [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. According to Tsai et al., an abrupt temperature change is a triggering factor that increases arthralgia [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. This can serve as evidence to support the results of this study, showing an increase in temperature change and the number of patients with TMD. In the most recently reported meta-analysis, levels of musculoskeletal pain were higher in cold countries and lower in countries with warm climates; however, heterogeneity in patient composition and a lack of studies hindered the valid synthesis or analysis of risk scales [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In a recent study conducted in Morocco, symptom severity in patients with rheumatoid arthritis was not significantly affected by seasonal changes in temperature [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. However, Morocco is a country with a rainy season and a dry season, and the climate alternates between warm and humid (average 15 ℃) in the rainy season and hot and dry (average 28 ℃) in the dry season. Therefore, the situation differs from that in Korea, where the spring, summer, fall, and winter are distinct. Few studies have investigated changes in TMD prevalence or symptom severity according to seasonal or temperature changes. TMD is a major musculoskeletal disorder affecting the orofacial region and is one of the most common conditions causing severe facial pain [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Additional research is needed to determine the myth or reality of changes in TMD symptoms depending on weather or season.\u003c/p\u003e \u003cp\u003eAn essential aspect of this study was the utilization of robust national data spanning a 13-year period to conduct statistical analyses of patients seeking treatment for TMD at hospitals. Notably, our findings align with prior research on TMD prevalence, indicating a peak occurrence among individuals in their 20s [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. However, according to a prospective cohort study in the United States, the incidence of TMD tends to increase with age, with the highest incidence in the 35\u0026ndash;44 years age group [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In this study, a noteworthy departure was observed in the mid-to-late teenage demographics, exhibiting substantial prevalence, unlike the patterns observed in other studies. Contrary to prevailing trends, this age group (mid-to-late teenage) demonstrated a heightened prevalence, potentially linked to the social and psychological stress experienced by Korean middle and high school students [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Academic pressure, interpersonal relationships, and developmental challenges during this phase may have contributed to the atypical prevalence. Additionally, a notable observation was the significant occurrence of TMD among the elderly, particularly those aged over 65 years and notably over 80 years.\u003c/p\u003e \u003cp\u003eOne limitation of this study is the lack of a detailed examination of TMD diagnosis, symptom severity, duration, and treatment specifics among patients with TMD. While acknowledging the significant influence of psychological factors on the physical factors of signs and symptoms of TMD, this study did not incorporate these psychological aspects. During the transition from fall to winter, colder temperatures and reduced sunlight durations may trigger mood alterations or depression in certain individuals [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. TMD is defined as chronic pain, and weather and temperature factors that affect mood and psychology have been considered in chronic pain [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Additional comprehensive investigations and analyses of these elements are required.\u003c/p\u003e \u003cp\u003eFor the first time, we investigated the fluctuations in TMD patient numbers concerning seasons and temperature variations in Korea, utilizing HIRA healthcare big data in conjunction with data from the Korea Meteorological Administration. Consequently, we were able to elucidate the trends in the number of patients with TMD associated with distinct seasonal variations in Korea. Although the decrease in absolute temperature influenced the increase in the number of patients with TMD, the difference between the highest and lowest temperatures was a more decisive factor in Korea.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003eThe authors thank Sung-Woo Lee of the Department of Oral Medicine and Oral Diagnosis at the Seoul National University School of Dentistry.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declares no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Korea Medical Device Development Fund grant funded by the Korean government (Ministry of Science and ICT; Ministry of Trade, Industry, and Energy; Ministry of Health \u0026amp; Welfare, Republic of Korea; Ministry of Food and Drug Safety) (Project Number: KMDF_PR_20200901_0023, 9991006696).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: Y.-H.L., Investigation: Y.-H.L., Visualization: Y.-H.L., Writing: Y.-H.L. and J.-W.C., Review and editing: Y.-H.L. and J.-W.C.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed in the current study are available from the corresponding author upon reasonable request. Korean patients\u0026apos; health statuses, medical providers, medical expenses, utilization rates, and summary statistics related to medical services were made public through the Healthcare Big Data Open System (http://opendata.hira.or.kr). Monthly temperature data for the past 13 years were obtained from the National Climate Data Center of the Korea Meteorological Administration (https://data.kma.go.kr).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe author declares no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe protocol for this study was exempt from review by the Institutional Review Board of Kyung Hee University Dental Hospital.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eN/A\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author has read and agreed to the published version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChoi B, Choi HM, Choi Y, Kim I, Hwang S: \u003cstrong\u003eHigh Temperature and Its Association With Work-Related Injuries by Employment Status in South Korea, 2017-2018\u003c/strong\u003e. \u003cem\u003eJ Occup Environ Med \u003c/em\u003e2022, \u003cstrong\u003e64\u003c/strong\u003e(11):e690-e694.\u003c/li\u003e\n\u003cli\u003eChoi G, Lee DE: \u003cstrong\u003eChanging human-sensible temperature in Korea under a warmer monsoon climate over the last 100 years\u003c/strong\u003e. \u003cem\u003eInt J Biometeorol \u003c/em\u003e2020, \u003cstrong\u003e64\u003c/strong\u003e(5):729-738.\u003c/li\u003e\n\u003cli\u003eLee Y-H, Lee KM, Kim T, Hong J-P: \u003cstrong\u003ePsychological Factors that Influence Decision-Making Regarding Trauma-Related Pain in Adolescents with Temporomandibular Disorder\u003c/strong\u003e. \u003cem\u003eScientific Reports \u003c/em\u003e2019, \u003cstrong\u003e9\u003c/strong\u003e(1):18728.\u003c/li\u003e\n\u003cli\u003eSharma S, Gupta DS, Pal US, Jurel SK: \u003cstrong\u003eEtiological factors of temporomandibular joint disorders\u003c/strong\u003e. \u003cem\u003eNatl J Maxillofac Surg \u003c/em\u003e2011, \u003cstrong\u003e2\u003c/strong\u003e(2):116-119.\u003c/li\u003e\n\u003cli\u003eLee YH, Lee KM, Auh QS: \u003cstrong\u003eMRI-Based Assessment of Masticatory Muscle Changes in TMD Patients after Whiplash Injury\u003c/strong\u003e. \u003cem\u003eJ Clin Med \u003c/em\u003e2021, \u003cstrong\u003e10\u003c/strong\u003e(7).\u003c/li\u003e\n\u003cli\u003eKapos FP, Exposto FG, Oyarzo JF, Durham J: \u003cstrong\u003eTemporomandibular disorders: a review of current concepts in aetiology, diagnosis and management\u003c/strong\u003e. \u003cem\u003eOral Surg \u003c/em\u003e2020, \u003cstrong\u003e13\u003c/strong\u003e(4):321-334.\u003c/li\u003e\n\u003cli\u003eAl-Moraissi EA, Christidis N, Ho Y-S: \u003cstrong\u003ePublication performance and trends in temporomandibular disorders research: A bibliometric analysis\u003c/strong\u003e. \u003cem\u003eJournal of Stomatology, Oral and Maxillofacial Surgery \u003c/em\u003e2023, \u003cstrong\u003e124\u003c/strong\u003e(1):101273.\u003c/li\u003e\n\u003cli\u003eBueno CH, Pereira DD, Pattussi MP, Grossi PK, Grossi ML: \u003cstrong\u003eGender differences in temporomandibular disorders in adult populational studies: A systematic review and meta-analysis\u003c/strong\u003e. \u003cem\u003eJ Oral Rehabil \u003c/em\u003e2018, \u003cstrong\u003e45\u003c/strong\u003e(9):720-729.\u003c/li\u003e\n\u003cli\u003eLeResche L: \u003cstrong\u003eEpidemiology of temporomandibular disorders: implications for the investigation of etiologic factors\u003c/strong\u003e. \u003cem\u003eCrit Rev Oral Biol Med \u003c/em\u003e1997, \u003cstrong\u003e8\u003c/strong\u003e(3):291-305.\u003c/li\u003e\n\u003cli\u003eSchiffman E, Ohrbach R, Truelove E, Look J, Anderson G, Goulet JP, List T, Svensson P, Gonzalez Y, Lobbezoo F\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eDiagnostic Criteria for Temporomandibular Disorders (DC/TMD) for Clinical and Research Applications: recommendations of the International RDC/TMD Consortium Network* and Orofacial Pain Special Interest Group\u0026dagger;\u003c/strong\u003e. \u003cem\u003eJ Oral Facial Pain Headache \u003c/em\u003e2014, \u003cstrong\u003e28\u003c/strong\u003e(1):6-27.\u003c/li\u003e\n\u003cli\u003eLee Y-H, Auh QS, An J-S, Kim T: \u003cstrong\u003ePoorer sleep quality in patients with chronic temporomandibular disorders compared to healthy controls\u003c/strong\u003e. \u003cem\u003eBMC Musculoskeletal Disorders \u003c/em\u003e2022, \u003cstrong\u003e23\u003c/strong\u003e(1):246.\u003c/li\u003e\n\u003cli\u003eLee Y-H, Auh QS: \u003cstrong\u003eComparison of sleep quality deterioration by subgroup of painful temporomandibular disorder based on diagnostic criteria for temporomandibular disorders\u003c/strong\u003e. \u003cem\u003eScientific Reports \u003c/em\u003e2022, \u003cstrong\u003e12\u003c/strong\u003e(1):9026.\u003c/li\u003e\n\u003cli\u003eJohn MT, Dworkin SF, Mancl LA: \u003cstrong\u003eReliability of clinical temporomandibular disorder diagnoses\u003c/strong\u003e. \u003cem\u003ePain \u003c/em\u003e2005, \u003cstrong\u003e118\u003c/strong\u003e(1):61-69.\u003c/li\u003e\n\u003cli\u003eRaphael KG, Janal MN, Sirois DA, Dubrovsky B, Klausner JJ, Krieger AC, Lavigne GJ: \u003cstrong\u003eValidity of self-reported sleep bruxism among myofascial temporomandibular disorder patients and controls\u003c/strong\u003e. \u003cem\u003eJ Oral Rehabil \u003c/em\u003e2015, \u003cstrong\u003e42\u003c/strong\u003e(10):751-758.\u003c/li\u003e\n\u003cli\u003eSlade GD, Sanders AE, Bair E, Brownstein N, Dampier D, Knott C, Fillingim R, Maixner WO, Smith S, Greenspan J\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003ePreclinical episodes of orofacial pain symptoms and their association with health care behaviors in the OPPERA prospective cohort study\u003c/strong\u003e. \u003cem\u003ePain \u003c/em\u003e2013, \u003cstrong\u003e154\u003c/strong\u003e(5):750-760.\u003c/li\u003e\n\u003cli\u003eRacinais S, Cocking S, P\u0026eacute;riard JD: Sports\u003cstrong\u003e and environmental temperature: From warming-up to heating-up\u003c/strong\u003e. \u003cem\u003eTemperature (Austin) \u003c/em\u003e2017, \u003cstrong\u003e4\u003c/strong\u003e(3):227-257.\u003c/li\u003e\n\u003cli\u003eGatterer H, D\u0026uuml;nnwald T, Turner R, Csapo R, Schobersberger W, Burtscher M, Faulhaber M, Kennedy MD: \u003cstrong\u003ePracticing Sport in Cold Environments: Practical Recommendations to Improve Sport Performance and Reduce Negative Health Outcomes\u003c/strong\u003e. \u003cem\u003eInt J Environ Res Public Health \u003c/em\u003e2021, \u003cstrong\u003e18\u003c/strong\u003e(18).\u003c/li\u003e\n\u003cli\u003eCheshire WP: \u003cstrong\u003eThermoregulatory disorders and illness related to heat and cold stress\u003c/strong\u003e. \u003cem\u003eAutonomic Neuroscience \u003c/em\u003e2016, \u003cstrong\u003e196\u003c/strong\u003e:91-104.\u003c/li\u003e\n\u003cli\u003eWang L, Xu Q, Chen Y, Zhu Z, Cao Y: \u003cstrong\u003eAssociations between weather conditions and osteoarthritis pain: a systematic review and meta-analysis\u003c/strong\u003e. \u003cem\u003eAnn Med \u003c/em\u003e2023, \u003cstrong\u003e55\u003c/strong\u003e(1):2196439.\u003c/li\u003e\n\u003cli\u003eLee Y-H, Auh QS: \u003cstrong\u003eClinical factors affecting depression in patients with painful temporomandibular disorders during the COVID-19 pandemic\u003c/strong\u003e. \u003cem\u003eScientific Reports \u003c/em\u003e2022, \u003cstrong\u003e12\u003c/strong\u003e(1):14667.\u003c/li\u003e\n\u003cli\u003eFurquim BD, Flamengui LM, Conti PC: \u003cstrong\u003eTMD and chronic pain: a current view\u003c/strong\u003e. \u003cem\u003eDental Press J Orthod \u003c/em\u003e2015, \u003cstrong\u003e20\u003c/strong\u003e(1):127-133.\u003c/li\u003e\n\u003cli\u003eBerglund B, Harju EL, Kosek E, Lindblom U: \u003cstrong\u003eQuantitative and qualitative perceptual analysis of cold dysesthesia and hyperalgesia in fibromyalgia\u003c/strong\u003e. \u003cem\u003ePain \u003c/em\u003e2002, \u003cstrong\u003e96\u003c/strong\u003e(1-2):177-187.\u003c/li\u003e\n\u003cli\u003eTuveson B, Lindblom U, Fruhstorfer H: \u003cstrong\u003eExperimental muscle pain provokes long-lasting alterations of thermal sensitivity in the referred pain area\u003c/strong\u003e. \u003cem\u003eEur J Pain \u003c/em\u003e2003, \u003cstrong\u003e7\u003c/strong\u003e(1):73-79.\u003c/li\u003e\n\u003cli\u003eJahan F, Nanji K, Qidwai W, Qasim R: \u003cstrong\u003eFibromyalgia syndrome: an overview of pathophysiology, diagnosis and management\u003c/strong\u003e. \u003cem\u003eOman Med J \u003c/em\u003e2012, \u003cstrong\u003e27\u003c/strong\u003e(3):192-195.\u003c/li\u003e\n\u003cli\u003eTerao C, Hashimoto M, Furu M, Nakabo S, Ohmura K, Nakashima R, Imura Y, Yukawa N, Yoshifuji H, Matsuda F\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eInverse association between air pressure and rheumatoid arthritis synovitis\u003c/strong\u003e. \u003cem\u003ePLoS One \u003c/em\u003e2014, \u003cstrong\u003e9\u003c/strong\u003e(1):e85376.\u003c/li\u003e\n\u003cli\u003eGracey E, Burssens A, Cambr\u0026eacute; I, Schett G, Lories R, McInnes IB, Asahara H, Elewaut D: \u003cstrong\u003eTendon and ligament mechanical loading in the pathogenesis of inflammatory arthritis\u003c/strong\u003e. \u003cem\u003eNat Rev Rheumatol \u003c/em\u003e2020, \u003cstrong\u003e16\u003c/strong\u003e(4):193-207.\u003c/li\u003e\n\u003cli\u003eLurati AR: \u003cstrong\u003eHealth Issues and Injury Risks Associated With Prolonged Sitting and Sedentary Lifestyles\u003c/strong\u003e. \u003cem\u003eWorkplace Health Saf \u003c/em\u003e2018, \u003cstrong\u003e66\u003c/strong\u003e(6):285-290.\u003c/li\u003e\n\u003cli\u003eKuppili PP, Selvakumar N, Menon V: \u003cstrong\u003eSickness Behavior and Seasonal Affective Disorder: An Immunological Perspective of Depression\u003c/strong\u003e. \u003cem\u003eIndian J Psychol Med \u003c/em\u003e2018, \u003cstrong\u003e40\u003c/strong\u003e(3):266-268.\u003c/li\u003e\n\u003cli\u003eWalker WH, 2nd, Walton JC, DeVries AC, Nelson RJ: \u003cstrong\u003eCircadian rhythm disruption and mental health\u003c/strong\u003e. \u003cem\u003eTransl Psychiatry \u003c/em\u003e2020, \u003cstrong\u003e10\u003c/strong\u003e(1):28.\u003c/li\u003e\n\u003cli\u003eVale TA, Symmonds M, Polydefkis M, Byrnes K, Rice ASC, Themistocleous AC, Bennett DLH: \u003cstrong\u003eChronic non-freezing cold injury results in neuropathic pain due to a sensory neuropathy\u003c/strong\u003e. \u003cem\u003eBrain \u003c/em\u003e2017, \u003cstrong\u003e140\u003c/strong\u003e(10):2557-2569.\u003c/li\u003e\n\u003cli\u003eYang AC, Fuh JL, Huang NE, Shia BC, Wang SJ: \u003cstrong\u003ePatients with migraine are right about their perception of temperature as a trigger: time series analysis of headache diary data\u003c/strong\u003e. \u003cem\u003eJ Headache Pain \u003c/em\u003e2015, \u003cstrong\u003e16\u003c/strong\u003e:533.\u003c/li\u003e\n\u003cli\u003eSibley JT: \u003cstrong\u003eWeather and arthritis symptoms\u003c/strong\u003e. \u003cem\u003eJ Rheumatol \u003c/em\u003e1985, \u003cstrong\u003e12\u003c/strong\u003e(4):707-710.\u003c/li\u003e\n\u003cli\u003eTsai WS, Yang YH, Wang LC, Chiang BL: \u003cstrong\u003eAbrupt temperature change triggers arthralgia in patients with juvenile rheumatoid arthritis\u003c/strong\u003e. \u003cem\u003eJ Microbiol Immunol Infect \u003c/em\u003e2006, \u003cstrong\u003e39\u003c/strong\u003e(6):465-470.\u003c/li\u003e\n\u003cli\u003eFarbu EH, H\u0026ouml;per AC, Reierth E, Nilsson T, Skandfer M: \u003cstrong\u003eCold exposure and musculoskeletal conditions; A scoping review\u003c/strong\u003e. \u003cem\u003eFront Physiol \u003c/em\u003e2022, \u003cstrong\u003e13\u003c/strong\u003e:934163.\u003c/li\u003e\n\u003cli\u003eAzzouzi H, Ichchou L: \u003cstrong\u003eSeasonal and Weather Effects on Rheumatoid Arthritis: Myth or Reality?\u003c/strong\u003e \u003cem\u003ePain Res Manag \u003c/em\u003e2020, \u003cstrong\u003e2020\u003c/strong\u003e:5763080.\u003c/li\u003e\n\u003cli\u003eGauer RL, Semidey MJ: \u003cstrong\u003eDiagnosis and treatment of temporomandibular disorders\u003c/strong\u003e. \u003cem\u003eAm Fam Physician \u003c/em\u003e2015, \u003cstrong\u003e91\u003c/strong\u003e(6):378-386.\u003c/li\u003e\n\u003cli\u003eOmezli MM, Torul D, Varer Akpinar C: \u003cstrong\u003eTemporomandibular disorder severity and its association with psychosocial and sociodemographic factors in Turkish adults\u003c/strong\u003e. \u003cem\u003eBMC Oral Health \u003c/em\u003e2023, \u003cstrong\u003e23\u003c/strong\u003e(1):34.\u003c/li\u003e\n\u003cli\u003eSlade GD, Fillingim RB, Sanders AE, Bair E, Greenspan JD, Ohrbach R, Dubner R, Diatchenko L, Smith SB, Knott C\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eSummary of findings from the OPPERA prospective cohort study of incidence of first-onset temporomandibular disorder: implications and future directions\u003c/strong\u003e. \u003cem\u003eJ Pain \u003c/em\u003e2013, \u003cstrong\u003e14\u003c/strong\u003e(12 Suppl):T116-124.\u003c/li\u003e\n\u003cli\u003eHong CH: \u003cstrong\u003eCurrent health issues in Korean adolescents\u003c/strong\u003e. \u003cem\u003eKorean J Pediatr \u003c/em\u003e2011, \u003cstrong\u003e54\u003c/strong\u003e(10):395-400.\u003c/li\u003e\n\u003cli\u003eMelrose S: \u003cstrong\u003eSeasonal Affective Disorder: An Overview of Assessment and Treatment Approaches\u003c/strong\u003e. \u003cem\u003eDepress Res Treat \u003c/em\u003e2015, \u003cstrong\u003e2015\u003c/strong\u003e:178564.\u003c/li\u003e\n\u003cli\u003eDworkin SF, Massoth DL: \u003cstrong\u003eTemporomandibular disorders and chronic pain: disease or illness?\u003c/strong\u003e \u003cem\u003eJ Prosthet Dent \u003c/em\u003e1994, \u003cstrong\u003e72\u003c/strong\u003e(1):29-38.\u003c/li\u003e\n\u003cli\u003eJamison RN, Anderson KO, Slater MA: \u003cstrong\u003eWeather changes and pain: perceived influence of local climate on pain complaint in chronic pain patients\u003c/strong\u003e. \u003cem\u003ePain \u003c/em\u003e1995, \u003cstrong\u003e61\u003c/strong\u003e(2):309-315.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 5","content":"\u003cp\u003eTable 5 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"seasonal, winter, temporomandibular disorder, climate, temperature, prevalence","lastPublishedDoi":"10.21203/rs.3.rs-3821655/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3821655/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eAim\u003c/h2\u003e \u003cp\u003eThis study aimed to explore seasonal variations in temporomandibular disorder (TMD) prevalence in South Korea, utilizing nationwide population-based big data.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eData from the Korean Meteorological Administration combined with big data from the Health Insurance Review and Assessment Service (HIRA) (2010\u0026ndash;2022), identified as TMD (K07.6) through a 4-digit disease code search, were used. TMD patient data for the past 13 years were statistically processed every month, and prevalence by season was analyzed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn 2022, 484,241 individuals sought treatment for TMD in hospitals with an increase of 97.89% from 244,708 cases in 2010. The onset of TMD showed no sex differences in those under 10 years of age. However, a distinct female predominance emerged after 10 years of age, with an average female-to-male ratio of 1.84:1. The peak prevalence was observed in the 20\u0026ndash;24 age group. TMD patient numbers across seasons showed no significant increase in winter compared with spring or summer. However, there was a significant correlation between the maximum and minimum temperatures and the number of patients with TMD. A higher temperature difference correlated with a higher TMD patient count. The strongest correlation between TMD patient numbers and temperature differences was observed in winter (r\u0026thinsp;=\u0026thinsp;0.480, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), followed by summer (r\u0026thinsp;=\u0026thinsp;0.443, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and spring (r\u0026thinsp;=\u0026thinsp;0.366, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The highest number of patients with TMD were distributed in Seoul and Gyeonggi-do, with metropolitan areas accounting for 50% of the total patient count.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eDiurnal temperature fluctuations showed a significantly stronger correlation with the increase in the number of TMD patients than absolute climate temperatures. This aspect should be a key consideration when examining trends in patients with TMD across distinct seasons in South Korea.\u003c/p\u003e","manuscriptTitle":"The seasonal influence on TMD prevalence in South Korea which has four seasons","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-03 15:13:17","doi":"10.21203/rs.3.rs-3821655/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-03-05T03:46:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-03-04T05:18:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"c5deebce-ab66-46c8-93ce-2cec1e86a9b4","date":"2024-02-28T05:06:43+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-02-02T22:10:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6e121394-d8f5-4169-9880-81c7882229a4","date":"2024-01-27T13:34:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"da08fdb6-47b0-4e99-9a4a-351d3b719ba7","date":"2024-01-24T13:14:15+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-22T13:10:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-22T13:09:27+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2023-12-31T12:10:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-12-31T12:05:42+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2023-12-29T14:43:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b9b59dd0-46b0-4042-a86e-696567f6a997","owner":[],"postedDate":"January 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":27912479,"name":"Health sciences/Diseases"},{"id":27912480,"name":"Health sciences/Health care"},{"id":27912481,"name":"Health sciences/Medical research"},{"id":27912482,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2024-05-10T01:56:09+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-03 15:13:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3821655","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3821655","identity":"rs-3821655","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}