Long-term hot spring bathing on improving sleep quality with the decrease of TNF-α and increase of 5-HT

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In this study, we undertook comprehensive investigation on the long-term health effects of hot spring bathing among the residents of Hot Spring Village and collected their blood samples for biochemical tests, including inflammatory cytokines (TNF-α) and neurotransmitters (5-HT and BDNF) analysis as well. We found that hot spring bathing ( OR =0.18, 95% CI : 0.05-0.68), with the length of more than 30 minutes ( OR =0.10, 95% CI : 0.02-0.53), and the frequency of more than 3 times per week ( OR =0.07, 95% CI : 0.01-0.32) were protective factors for sleep quality ( P <0.05). Interestingly, we observed at the first time that the blood TNF-α significantly decreased ( P <0.05), with an increasing trend of 5-HT and BDNF in the bathing group. Besides, participants with good sleep quality exhibited significantly lower levels of TNF-α compared to those of poor ones, and among good sleepers aged 65 and older, higher levels of 5-HT were observed. Further logistic analysis revealed that a decrease of TNF-α ( OR =1.03, 95% CI : 1.01-1.06) and an increase of 5-HT ( OR =0.98, 95% CI : 0.97-0.99) were associated with good sleep quality. Additionally, the trends of decreasing TNF-α and increasing 5-HT were also observed in the hot spring bathing group with good sleep quality for the first time. These findings suggested that hot spring bathing might improve sleep quality with the alteration of TNF-α and 5-HT, which could serve as potential indicators for future studies on health benefits of bathing. Hot spring bathing Sleep quality TNF-α 5-HT Health effect Figures Figure 1 Introduction Studies on the beneficial effects of hot spring bathing such as hypertension (Yamasaki et al. 2022), obesity (Firszt-Adamczyk et al. 2016), arthritis (Karagülle et al. 2016), muscular pain (Özkuk et al. 2018), skin lesions (Inaka et al. 2021), as well as sleep improvement has been reported. For example, a seven-day sleep-promoting program involving 31 individuals with sleep disorders, led to improvements in insomnia (Long et al. 2022). A two-week balneotherapy (hot spring bathing) has been found to significantly enhance sleep quality among the elderly participants (Latorre-Román et al. 2015). However, most of these study primarily focused on the short-term effects depending on questionnaire investigation without blood collection for biochemical analysis. In this study, we conducted comprehensive surveys on the long-term health effects of hot spring bathing among the residents of Hot Spring Village with natural hot spring resources located in Xunsi Town, Junlian County, Yibin City, Sichuan Province, China. People lived in this village have the privilege of unrestricted access to hot spring, and some individuals enjoying hot spring bathing almost everyday in their lifetime. This provided us the opportunity to explore the long-term health effects of hot spring bathing. So we conducted a face-to-face interviews to collect basic demographic data, including gender, age, marital status, income, educational, BMI, smoking, and drinking, as well as the hot spring bathing behavior, including the length and frequency of bathing and their self-reported improvements in fatigue alleviation, mood enhancement, and sleep quality etc. Besides, we also collected their blood samples to study the long-term health effects of hot spring bathing with the relationship of biochemical factor changes. The tests we conducted in this research not only basic biochemical indicators, but also inflammatory biomarkers and neurotransmitters such as TNF-α, 5-HT and BDNF. TNF-α is an inflammatory cytokine that plays a pivotal role in the immune system by stimulating inflammatory responses, improving intercellular communication and participating in immune regulation; however, its excessive activation leads to inflammation and the development of various diseases such as sleep disorder. It has been reported that the higher the TNF-α and the worse the quality of sleep (Yang et al. 2023), and a randomized controlled trial also demonstrated that TNF-α levels significantly decreased in patients with chronic heart failure after two weeks of hot spring bathing (Oyama et al. 2013). Nevertheless, the changes in blood TNF-α among long-term hot spring bathing individuals have not been reported. So, it was investigated in this study. 5-HT, also known as serotonin, is a neurotransmitter that regulate s neural activity and a wide range of neuropsychological processes including modulation of mood, perception, aggression, memory, and attention etc with numerous animal research supporting (Berger et al. 2009; Pourhamzeh et al. 2022). However, there is still limited community-based study focus on the 5-HT changes. Although, liu et al. (2021) demonstrated that acupuncture could increase tryptophan content in the peripheral system and elevate 5-HT levels in the blood, no study has been reported related the changes of 5-HT levels in the hot spring bathers. Therefore, in this study we detected blood 5-HT to evaluate the relationship of long-term hot spring bathing on improving sleep quality with the alteration of this neurotransmitter. In addition to 5-HT, we also detected BDNF, a protein that acts on neurons in the central and peripheral nervous systems, promoting the growth of new neurons, modulating neuronal plasticity, and alleviating anxiety and depression (Maniam et al. 2010; Giese et al. 2014; Kojima et al. 2018). In summary, we conducted comprehensive investigation on the long-term health effects of hot spring bathing among the residents of Hot Spring Village with blood sample collection for biochemical indicator tests, including TNF-α, 5-HT and BDNF levels determination to study the health effect of hot spring bathing. Materials and methods Study design A cross-sectional study design was used to investigate the long-term health effects of hot spring bathing. It was conducted according to the Declaration of Helsinki and approved by the Ethics Committee of Sichuan University (IRB Gwll2022102). All participants were informed about the study and signed an informed consent form. Participants From February to April 2023, 153 residents were recruited from Hot Spring Village, Xunsi Town, Junlian County, Yibin City, Sichuan Province, China. A face-to-face interviews were conducted to collect basic demographic data (gender, age, marital status, income, educational, BMI, smoking, and drinking), as well as the hot spring bathing behavior, including the length and frequency of bathing and their self-reported improvements in fatigue alleviation, mood enhancement, and sleep quality etc. Eligibility for the study was followed several criteria: participants were to be within the age of 30 to 70 years and have a history of hot spring bathing exceeding a decade. Exclusionary factors encompassed severe conditions affecting the heart, liver, spleen, lungs, and kidneys, as well as immune and infectious disorders. In the end, a total of 153 questionnaires were collected, with 13 incomplete samples excluded, resulting in 140 participants. The methods of sleep quality assessment The sleep quality assessment by the Pittsburgh Sleep Quality Index (PSQI) (Chinese version), consists of 19 items evaluating sleep conditions over the past month from various perspectives. Each item in the seven factors is rated on a 4-level Likert scale, ranging from 0 to 3. The factors include sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbances, use of sleep medication, and daytime dysfunction. Good sleep quality is defined as a PSQI total score below 5, while a score above 5 indicates poor sleep quality. Biochemical indicators test We also collected blood samples to study the long-term health effects of hot spring bathing with the relationship of biochemical factor changes. A total of 6 mL of venous blood sample was collected from each participant after an 8-hour fasting period. The fully automated biochemical analyzer was used to measure the levels of triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), fasting plasma glucose (FPG), white blood cell (WBC), red blood cell (RBC), hemoglobin (HGB), platelet (PLT), alanine transaminase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), and urea in peripheral venous blood samples. The tests we conducted in this research not only basic biochemical indicators, but also inflammatory biomarker (TNF-α) and neurotransmitters (5-HT and BDNF) by ELISA assay. Physicochemical properties of the hot spring water The water samples were analyzed using ion chromatography for Cl, SO 4 , NO 3 , and F, inductively coupled plasma mass spectrometry for Fe, Li, V, Cr, Mn, Co, Ni, Cu, Zn, Sb, Mo, Ag, Cd, Ba, Pb, and Al, and inductively coupled plasma-atomic emission spectrometry for K, Na, Ca, Mg, and Sr. Silicic acid (H 2 SiO 3 ), NaNO 2 , iodide (I − ), cyanide, bromide (Br − ), borate (B − ), and carbon dioxide (CO 2 ) levels, as well as oxygen consumption (O 2 ), total acidity, total hardness, and total alkalinity, were determined using spectrophotometry and titrimetry methods, respectively. Total dissolved solids (TDS) were analyzed by weight method, and pH was evaluated using a glass electrode. The analyses were conducted at the laboratory of the Chengdu Comprehensive Rock and Mine Testing Center of Sichuan province. The hot spring water has a source temperature of 50 ~ 53℃ with total dissolved solids of 5088.000 mg/L. Therefore, it is classified in the “thermomineral waters” group according to the Geological Exploration Standard for Geothermal Resources of China (GB-T-11615-2010). Furthermore, this hot spring water is rich in cations of K + , Na + , Ca 2+ , Mg 2+ and Fe 2+ +Fe 3+ with the amount reach to 1866.667 mg/L and relatively high level of TDS, Li and HCO 3 − (Table 1 ). Table 1 Physicochemical properties of the hot spring water Characteristic (mg/L) Morning (7:00) Noon (15:00) Night (23:00) Mean Temperature a 50℃ 53℃ 52℃ 51.670℃ Temperature b 44.5℃ 44.9℃ 44.9℃ 44.777℃ PH value 7.690 7.200 7.160 7.350 Total acidity (by CaCO 3 ) 5.200 13.000 15.500 11.233 Total alkalinity (by CaCO 3 ) 148.000 148.000 144.000 146.667 Hardness 780.000 742.000 704.000 742.000 Cations Potassium (K + ) 20.400 19.500 18.000 19.300 Sodium (Na + ) 1662.000 1544.000 1494.000 1566.667 Calcium (Ca 2+ ) 255.000 241.000 226.000 240.667 Magnesium (Mg 2+ ) 42.500 39.500 37.600 39.867 Iron (Fe 2+ +Fe 3+ ) 0.356 0.122 0.032 0.170 Subtotal 1980.000 1844.000 1776.000 1866.667 Anions Bicarbonate (HCO 3 − ) 180.000 180.000 175.000 178.333 Carbonate (CO 3 2− ) < 3.0 < 3.0 < 3.0 < 3.0 Chloride (Cl − ) 2252.000 2224.000 2238.000 2238.000 Sulfate (SO 4 2− ) 741.000 725.000 743.000 736.333 Nitrate (NO 3 − ) 1.800 1.700 1.700 1.733 Fluoride (F − ) 2.540 2.430 2.490 2.487 Subtotal 3177.000 3133.000 3160.000 3156.667 Lithium (Li) 0.236 0.229 0.232 0.232 Strontium (Sr) 7.790 7.360 6.960 7.370 Metasilicic acid 44.500 42.700 42.700 43.300 Nitrite 0.003 0.003 0.003 0.003 Carbon dioxide 4.600 11.400 13.700 9.900 Iodide 0.011 0.012 0.012 0.012 Cyanides < 0.002 < 0.002 < 0.002 < 0.002 Volatile phenols < 0.002 < 0.002 < 0.002 < 0.002 Bromide (Br − ) 3.000 3.300 3.150 3.150 Oxygen consumption 1.580 1.900 1.920 1.800 Sulfide < 0.003 < 0.003 < 0.003 < 0.003 Metaboric acid (B) 0.380 0.370 0.380 0.377 Total dissolved solids (TDS) 5190.000 5050.000 5024.000 5088.000 Note: a the temperature of the hot spring source; b the temperature of the bathing pool. Statistical analysis We conducted statistical analysis using R 4.2.2 software. Measurement data were expressed as mean ± SD and analyzed with t test. Non-normally distributed data were described using median and interquartile range with Mann-Whitney U test. Categorical variables were described using frequencies and percentages with chi-square test. Logistic regression was to analyze the relationship between hot spring bathing and sleep quality. Statistical significance was defined as P < 0.05. Results Basic demographic characteristics and biochemical test results for the participants A total of 140 residents who lived in the Hot Spring Village more than ten years (48 males and 92 females) were included, and 44.29% (62/140) of them took hot spring bath regularly. Among them, 88 were under the age of 65, while 52 were 65 or older. No significant differences of age, gender, marital status, smoking, drinking, length of residence, educational, BMI, Waist, DBP were observed between the hot spring bathing and non bathing groups ( P > 0.05). Interestingly, we found at the first time that the TNF-α, a kind of inflammatory biomarkers, significantly decreased ( P < 0.05), with an increasing trend of neurotransmitters 5-HT and BDNF in the hot spring bathing group (Table 2 ). These results suggested a potential health-improving effect of hot spring bathing for further analysis. Table 2 Basic demographic characteristics and biochemical test results for the participants Variable Overall Hot spring bathing P No [n (%)] Yes [n (%)] Total 140 78 (55.71) 62 (44.29) Age 0.295 < 65 years old 88 (62.9) 52 (66.7) 36 (58.1) ≥ 65 years old 52 (37.1) 26 (33.3) 26 (41.9) Gender 0.326 Male 48 (34.29) 24 (30.77) 24 (38.71) Female 92 (65.71) 54 (69.23) 38 (61.29) Marital status 0.077 Others 8 (5.71) 7 (8.97) 1 (1.61) Married 132 (94.29) 71 (91.03) 61 (98.39) Smoking 0.556 No 105 (75.00) 60 (76.92) 45 (72.58) Yes 35 (25.00) 18 (23.08) 17 (27.42) Drinking 0.291 No 118 (84.29) 68 (87.18) 50 (80.65) Yes 22 (15.71) 10 (12.82) 12 (19.35) Educational (Junior high school or above) 0.144 No 43 (30.71) 20 (25.64) 23 (37.10) Yes 97 (69.29) 58 (74.36) 39 (62.90) BMI 26.09 ± 3.54 26.56 ± 3.56 25.50 ± 3.46 0.089 Waist 83.31 ± 8.53 83.12 ± 9.23 83.54 ± 7.62 0.634 SBD 148.86 ± 21.04 151.88 ± 19.39 145.06 ± 22.53 0.043 DBP 83.96 ± 21.87 86.10 ± 19.82 81.26 ± 24.10 0.116 TC 5.50 ± 1.05 5.39 ± 0.99 5.60 ± 1.09 0.227 TG 3.25 ± 1.58 3.04 ± 1.62 3.42 ± 1.54 0.176 LDL-C 2.67 ± 0.90 2.55 ± 0.93 2.76 ± 0.87 0.111 HDL-C 1.38 ± 0.33 1.40 ± 0.34 1.37 ± 0.33 0.549 FPG 6.31 ± 1.87 6.29 ± 2.19 6.32 ± 1.57 0.237 WBC 6.05 ± 1.97 6.25 ± 2.36 5.89 ± 1.60 0.441 RBC 4.96 ± 0.52 5.01 ± 0.55 4.91 ± 0.50 0.224 HGB 144.55 ± 14.05 147.12 ± 14.50 142.51 ± 13.43 0.100 PLT 225.09 ± 62.98 217.78 ± 70.60 230.90 ± 55.99 0.094 ALT 16.63 ± 8.42 16.61 ± 7.82 16.65 ± 8.91 0.603 AST 26.51 ± 7.17 25.56 ± 6.64 27.27 ± 7.52 0.162 TBIL 11.26 ± 3.66 11.10 ± 4.02 11.39 ± 3.36 0.351 UREA 5.25 ± 1.51 5.13 ± 1.45 5.35 ± 1.56 0.392 TNF-α 49.73 (18.94, 89.31) 67.19 (36.81, 104.18) 25.75 (15.20, 67.18) 0.0001 5-HT 54.40 (40.76, 79.80) 49.68 (39.25, 67.89) 58.48 (45.86, 88.87) 0.051 BDNF 0.99 (0.28, 1.84) 1.05 (0.34, 1.73) 1.98 (0.16, 2.16) 0.633 The relationship between hot spring bathing and sleep quality by age with basic demographic characteristics As shown in Table 2 , the inflammatory biomarkers and neurotransmitters were altered suggesting potential sleep-improving effects. Therefore, we analyzed the relationship between hot spring bathing and sleep quality by age with basic demographic characteristics. In the hot spring bathing group, 51.61% of them reported a length of hot spring bathing more than 30 minutes, and 48.39% reported a frequency of hot spring bathing at least 3 times per week, which were significant association with sleep quality in the group of 65 and older ( P < 0.05) (Table 3 ). Table 3 Distribution of sleep quality by age with basic demographic characteristics Variable Overall Under 65 years old P Above 65 years old P Good [n (%)] Poor [n (%)] Good [n (%)] Poor [n (%)] Total 140 23 (16.43) 65 (46.43) 17 (12.14) 35 (25.00) Hot spring bathing 0.840 0.008 Yes 62 (44.29) 9 (25.00) 27 (75.00) 13 (50.00) 13 (50.00) No 78 (55.71) 14 (26.92) 38 (73.08) 4 (15.38) 22 (84.62) Length of hot spring bathing each time (min) 0.889 0.012 No 78 (55.71) 14 (26.92) 38 (73.08) 4 (15.38) 22 (84.62) < 30 30 (21.43) 3 (20.00) 12 (80.00) 6 (40.00) 9 (60.00) ≥ 30 32 (22.86) 6 (28.57) 15 (71.43) 7 (63.64) 4 (36.36) Frequency of hot spring bathing per week 0.590 < 0.001 No 78 (55.71) 14 (26.92) 38 (73.08) 4 (15.38) 22 (84.62) < 3 32 (22.86) 4 (19.05) 17 (80.95) 2 (18.18) 9 (81.82) ≥ 3 30 (21.43) 5 (33.33) 10 (66.67) 11 (73.33) 4 (26.67) Gender 0.488 0.202 Male 48 (34.29) 5 (20.83) 19 (79.17) 10 (41.67) 14 (58.33) Female 92 (65.71) 18 (28.13) 46 (71.88) 7 (25.00) 21 (75.00) Marital status > 0.999 0.404 Others 8 (5.71) 0 (0.00) 1 (100.00) 1 (14.29) 6 (85.71) Married 132 (94.29) 23 (26.44) 64 (73.56) 16 (35.56) 29 (64.44) Smoking > 0.999 0.124 No 105 (75) 18 (25.71) 52 (74.29) 9 (25.71) 26 (74.29) Yes 35 (25) 5 (27.78) 13 (72.22) 8 (47.06) 9 (52.94) Drinking > 0.999 0.496 No 118 (84.29) 21 (26.92) 57 (73.08) 12 (30.00) 28 (70.00) Yes 22 (15.71) 2 (20.00) 8 (80.00) 5 (41.67) 7 (58.33) Educational (Junior high school or above) 0.269 0.735 No 43 (30.71) 10 (33.33) 20 (66.67) 5 (38.46) 8 (61.54) Yes 97 (69.29) 13 (22.41) 45 (77.59) 12 (30.77) 27 (69.23) BMI 26.09 ± 3.54 26.35 ± 4.18 26.81 ± 3.65 0.528 24.00 ± 2.32 25.60 ± 2.99 0.097 Waist 83.31 ± 8.53 81.65 ± 9.43 84.13 ± 9.13 0.262 83.27 ± 6.73 82.87 ± 7.62 0.703 SBD 148.86 ± 21.04 147.96 ± 17.41 146.42 ± 22.89 0.512 147.04 ± 27.04 154.88 ± 15.24 0.175 DBP 83.96 ± 21.87 88.11 ± 7.85 80.75 ± 28.03 0.666 84.00 ± 13.96 87.18 ± 17.41 0.245 TC 5.50 ± 1.05 5.48 ± 0.71 5.50 ± 1.24 0.857 5.43 ± 1.15 5.56 ± 0.80 0.384 TG 3.25 ± 1.58 3.32 ± 0.97 3.59 ± 1.44 0.992 2.39 ± 0.79 2.98 ± 2.18 0.640 LDL-C 2.67 ± 0.90 2.67 ± 0.68 2.78 ± 0.96 0.417 2.36 ± 0.91 2.59 ± 0.90 0.507 HDL-C 1.38 ± 0.33 1.36 ± 0.24 1.36 ± 0.38 0.722 1.49 ± 0.26 1.39 ± 0.34 0.407 FPG 6.31 ± 1.87 5.81 ± 0.96 6.61 ± 2.23 0.115 6.13 ± 1.26 6.16 ± 1.78 0.930 WBC 6.05 ± 1.97 6.56 ± 1.22 5.87 ± 1.58 0.020 6.66 ± 4.07 5.74 ± 1.39 0.762 RBC 4.96 ± 0.52 4.96 ± 0.66 5.00 ± 0.45 0.347 5.05 ± 0.68 4.84 ± 0.46 0.215 HGB 144.55 ± 14.05 143.22 ± 12.32 144.74 ± 14.75 > 0.999 144.59 ± 16.22 145.06 ± 13.20 0.868 PLT 225.09 ± 62.98 245.52 ± 87.83 231.45 ± 59.94 0.943 191.48 ± 46.72 216.18 ± 49.29 0.069 ALT 16.63 ± 8.42 13.35 ± 5.49 18.80 ± 10.31 0.030 15.18 ± 4.89 15.47 ± 6.32 0.800 AST 26.51 ± 7.17 24.29 ± 4.87 27.86 ± 8.88 0.096 26.08 ± 4.29 25.68 ± 5.49 0.822 TBIL 11.26 ± 3.66 10.73 ± 2.86 11.88 ± 4.00 0.217 10.28 ± 3.97 10.93 ± 3.19 0.558 UREA 5.25 ± 1.51 5.42 ± 1.56 4.82 ± 1.25 0.085 6.08 ± 1.82 5.53 ± 1.56 0.339 TNF-α 49.73 (18.94, 89.31) 19.46 (9.42, 67.32) 51.14 (20.76, 87.45) 0.041 21.56 (16.27, 43.44) 72.79 (40.83, 101.41) 0.001 5-HT 54.40 (40.76, 79.80) 48.93 (35.24, 66.18) 52.14 (45.07, 79.44) 0.369 86.71 (49.24, 123.44) 48.40 (38.39, 79.64) 0.046 BDNF 0.99 (0.28, 1.84) 0.87 (0.43, 1.69) 0.83 (0.22, 1.75) 0.660 2.11 (0.17, 2.98) 1.15 (0.21, 1.70) 0.407 Further logistic regression analysis demonstrated that hot spring bathing ( OR = 0.18, 95% CI : 0.05–0.68). with the length of bathing time more than 30 minutes ( OR = 0.10, 95% CI : 0.02–0.53), and the frequency of more than 3 times per week ( OR = 0.07, 95% CI : 0.01–0.32) were protective factors for sleep quality ( P < 0.05). When taking hot spring bath as a reference, logistic regression analyses found that the risk of poor sleep quality in the hot spring bathing group was 5.5 times lower than that in the non-bathing group ( OR = 5.50, 95% CI : 1.48–20.46) (Table 4 ). Table 4 Logistic regression analysis the association of hot spring bathing and inflammatory biomarkers with sleep quality Variable (Reference) β S.E. Wald χ2 OR (95% CI ) P value Hot spring bath (No) -1.71 0.67 6.47 0.18 (0.05–0.68) 0.011 Hot spring bath (Yes) 1.705 0.67 6.47 5.50 (1.48–20.46) 0.011 Length of hot spring bathing each time (No) bathing time (No) - - - - ≤ 30 min -1.30 0.76 2.95 0.27 (0.06–1.20) 0.086 > 30 min -2.26 0.83 7.45 0.10 (0.02–0.53) 0.006 Frequency of hot spring bathing per week (No) - - - - - ≤ 3 times/week -0.20 0.95 0.04 0.82 (0.13–5.29) 0.833 > 3 times/week -2.72 0.80 11.59 0.07 (0.01–0.32) 0.001 TNF-α 0.03 0.01 8.78 1.03 (1.01–1.06) 0.003 5-HT -0.02 0.01 4.66 0.98 (0.97–0.99) 0.031 Hot spring bathing improved sleep quality with the alteration of TNF-α and 5-HT levels As shown in Table 2 , the levels of TNF-α in participants with good sleep quality were significant lower than those of poor sleepers ( P < 0.05). Moreover, The levels of 5-HT in aged above 65 with good sleep quality were significant higher than poor sleepers ( P < 0.05) (Table 3 ). Further logistic analysis revealed that a decrease of TNF-α ( OR = 1.03, 95% CI : 1.01–1.06) and an increase of 5-HT ( OR = 0.98, 95% CI :0.97–0.99) were associated with good sleep quality (Table 4 ), a decreased of TNF-α and an increased of 5-HT levels in the hot spring bathing group with good sleep quality were also observed (Fig. 1 ), suggesting that hot spring bathing might improve sleep quality by regulating 5-HT and TNF-α. Discussion In this study, we undertook a comprehensive investigation that integrating questionnaire survey and analyses of both blood and hot spring water samples. Our aim was to examine the long-term health effects of hot spring bathing among the residents of Hot Spring Village, who enjoy complimentary access to these natural resources. We found that hot spring bathing was beneficial for improving sleep quality, and the risk of poor sleep quality in the hot spring bathing group was 5.5 times lower than that in the non-bathing group ( OR = 5.50, 95% CI : 1.48–20.46) when taking hot spring bath as a reference. This result is consistent with Yang’s findings (Yang et al. 2018 ). Besides, our results also demonstrated that in order to have a significant improvement in sleep quality, taking bathing three times per week ( R = 0.10, 95% CI : 0.02–0.53) with a minimum of 30 minutes each time ( OR = 0.07, 95% CI : 0.01–0.32) were recommended. Furthermore, the novel findings of this present study are that long-term hot spring bathing improved sleep quality with the alteration of TNF-α and 5-HT. TNF-α is the most common inflammatory factor and considered as a sleep-improving cytokine. It was reported that sleep disturbance, as well poor sleep quality could cause an increase of TNF-α (Irwin et al. 2016 ; Poluektov MG. 2021 ; D'Antono et al. 2019), whereas dietary supplement with melatonin improving sleep quality with a decrease of TNF-α (Zarezadeh et al. 2020 ). Very interestingly, our research for the first time revealed a significant reduction in TNF-α levels among individuals who engaged in hot spring bathing and exhibited good sleep quality. We speculated that the thermal stimulation from hot spring bathing might help supporting immune regulation and anti-inflammatory responses, leading to a reduction in TNF-α levels. In fact, there has been some studies demonstrated that the thermotherapy effects of either hot water bathing or hot spring bathing on the alternation of TNF-α. For instance, Muthita et al (2019) reported a significant decrease in the expression of TNF-α protein levels in rats subjected to heat treatment with a core body temperature maintained within the range of 40.5–41.5°C for a duration of 30 minutes daily over a period of seven days, while a randomized controlled trial demonstrated the decrease of TNF-α levels in patients with chronic heart failure after two weeks of hot spring bathing (Oyama et al. 2013 ). Collectively, the results suggested that hot spring bathing could confer anti-inflammatory effects, potentially enhancing sleep quality through the modulation of TNF-α levels. Although it has been reported that hot spring bathing helps regulate emotions, promote relaxation, and achieve a pleasurable state, reducing anxiety and tension and improving psychological well-being. We found for the first time that an increasing trend in 5-HT levels in hot spring bathing participants was associated with good sleep quality ( OR = 0.98, 95% CI :0.97–0.99). 5-HT, also called serotonin, known as "happiness neurotransmitter", not only an important factor for mood regulation but also involved in the sleep-wake mechanism with a crucial role in maintaining slow-wave sleep (Monti et al. 2011). Besides, research has also shown that physiotherapy increased the tryptophan content in the peripheral system, increase the level of 5-HT in the blood, and accelerate tryptophan transport, thereby promoting the synthesis of 5-HT in the brain and ultimately improving the sleep of patients (Liu et al. 2021 ). The mechanisms of hot spring bathing on improving sleep quality may be similar to the effects of the physiotherapy. Furthermore, in this research, participants self-reported feelings of happiness and relaxation after hot spring bathing which might be related to the increased level of blood 5-HT. Additionally, in this study, we also tested the composition of the water samples and found this hot spring water was characterized by high sodium, carbon dioxide, bicarbonate and lithium contents, which might be associated with regulating mood and improving sleep. Tamaoki et al ( 2023 ) conducted a randomized controlled trial and found that sodium bicarbonate bathing for a period of seven days had positive effects on improving sleep quality of adults. Yamazaki et al ( 2021 ) also demonstrated that bathing in neutral bicarbonate ionized water resulting in percutaneously absorbed carbon dioxide enhanced blood flow with a improvement in sleep quality. These studies suggested that a bath rich in bicarbonate ions (HCO 3 − ), as well as carbon dioxide, might enable ions to penetrate the skin, promoting neurohumoral regulation, accelerating metabolism, and facilitating the excretion of lactic acid which effectively relieve fatigue and improve sleep efficiency. Notably, the lithium ion content in this hot spring water was 0.236 mg/L, ten times higher than that reported by Long et al (2023). Lithium, a kind of trace element, has a modulating effect on the central nervous system and is a potent mood stabilizer. Clinically, lithium has been widely used to treat bipolar disorder mania. It was reported that lithium treatment selectively reversed the hyperexcitability of young neurons in patients with bipolar disorder in those who responded well to lithium (Mertens et al. 2015 ). Besides, the increasing serum levels of lithium following balneotherapy with Dead Sea bath salt may imply the possibility of transcutaneous absorption of lithium from the salt (Halevy et al. 2001 ). In addition, we also noticed that the amount of total dissolved solids content of this hot spring was as high as 5,088 mg/L and rich in cations of K + , Na + , Ca 2+ , Mg 2+ and Fe 2+ +Fe 3+ with the amount up to 1,866.667 mg/L, which was relatively higher than Özkuk’s (2018) report. It has been considered that high amount of total dissolved solids and cations resulting in buoyancy and hydrostatic pressure might promote muscle relaxation, emotional stability, and lower adrenal cortex hormone levels in turn enhanced the sleep improvement (Su et al. 1999). It has been reported that the increased buoyancy experienced during immersion in hot spring water induces various physiological changes. These include strengthen circulation, relaxation of tense muscles, and relief from spasms, etc. Overall, the psychological benefits of hot spring bathing could be partly attributed to the chemical properties of the hot spring water (Morer et al. 2017 ). In the other hand, in this study, the villagers usually took hot spring bating at the temperature of 44.5 ~ 45℃. Harding et al ( 2019 ) proposed that pre-sleep hot spring bathing might postpone the occurrence of the body's temperature trough, which could consequently facilitate deeper sleep stages. Passive body heating by immersing in hot (40 ~ 40.5℃) bath 1.5 ~ 2 hours before bedtime for older female insomniacs could increase core body temperature with the increasing of slow-wave sleep in the early part of the sleep period resulting in sleep continuity improvement (Dorsey et al. 1999 ). So, we inferred long-term hot spring bathing on improving sleep quality might also related to the thermotherapy effects. Limitations The major limitation of this study was that the data we collected regarding the years of hot spring bathing were categorized as less than 10 years or 10 years or more, without obtaining continuous data on the specific years of hot spring bathing. Therefore, "long-term" in this study refers to periods of 10 years or longer. Additionally, the data for this study were derived from a cross-sectional survey. Further research should consider establishing a prospective cohort specific to hot spring bathers and conducting continuously follow-up investigation to observe a wider range of health effects associated with long-term hot spring bathing. Conclusion This study suggested that long-term hot spring bathing may improve sleep quality by regulating TNF-α and 5-HT levels, potentially serving as biomarkers for future investigations into the health-promoting effects of bathing. These findings further provide valuable evidence for the health benefits of hot spring bathing. Declarations Acknowledgments We would like to thank the staff members at the Junlian County Xunsi Central Health Centre and all the volunteers for their collaborative efforts. And we also gratefully acknowledge the supports of Provincial Public Health Experiment Teaching Demonstration Center at Sichuan University. Author contributions Fen Yang: Investigation, experimental analysis and writing-original draft. Yue Zou: Experimental analysis. Ying-ying Zhang: Data collection and experimental analysis. Hong-xia Li: Data collection. Yi-hang Xu: Data collection. Bao-chao Zhang: Data collection and experimental analysis. Lin-xuan Liao: Data collection. Meng-xi Cao: Data analysis. Rui-xue Wang: Data analysis and experimental analysis. Yuan Yuan: Data collection. Yun Zhou: Formal analysis. Da-yong Zeng: Data collection. Xiao-fang Pei: Conceptualization, funding acquisition, writing-review & editing. Funding This work was supported by the Yibin Science and Technology Planning Program (Grant numbers: 2021ZYSF006). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Data availability The data involved in this study are not publicly available due to privacy but are available from the authors on reasonable request. Conflict of interest The authors have no conflict of interest. References Berger M, Gray JA, Roth BL et al (2009) The expanded biology of serotonin. Annu Rev Med 60:355-366. https://doi.org/10.1146/annurev.med.60.042307.110802 D'Antono B, Bouchard V (2019) Impaired sleep quality is associated with concurrent elevations in inflammatory markers: are post-menopausal women at greater risk? Biol Sex Differ 10(1):34. https://doi.org/10.1186/s13293-019-0250-x Dorsey CM, Teicher MH, Cohen-Zion M et al (1999) Core body temperature and sleep of older female insomniacs before and after passive body heating. Sleep 22(7):891-898. https://doi.org/10.1093/sleep/22.7.891 Firszt-Adamczyk A, Ruszkowska-Ciastek B, Adamczyk P (2016) Effect of a 3-week low-calorie diet and balneological treatment on selected coagulation parameters in morbidly obese patients. Adv Clin Exp Med 25(4):755-761. https://doi.org/10.17219/acem/42414 Giese M, Unternahrer E, Huttig H et al (2014) BDNF: an indicator of insomnia? Mol Psychiatry 19:151-152. https://doi.org/10.1038/mp.2013.10 Halevy S, Giryes H, Friger M et al (2001) The role of trace elements in psoriatic patients undergoing balneotherapy with Dead Sea bath salt. The Israel Medical Association journal : IMAJ 3(11):828-832. Harding EC, Franks NP, Wisden W (2019) The Temperature Dependence of Sleep. Front Neurosci 13:336. https://doi.org/10.3389/fnins.2019.00336 Inaka K, & Kimura T (2021) Comfortable and dermatological effects of hot spring bathing provide demonstrative insight into improvement in the rough skin of Capybaras. Sci Rep 11(1):23675. https://doi.org/10.1038/s41598-021-03102-4 Irwin MR, Olmstead R, Carroll JE (2016) Sleep Disturbance, Sleep Duration, and Inflammation: A Systematic Review and Meta-Analysis of Cohort Studies and Experimental Sleep Deprivation. Biol Psychiatry 80(1):40-52. https://doi.org/10.1016/j.biopsych.2015.05.014 Karagülle M, Kardeş S, Dişçi R et al (2016) Spa therapy for elderly: a retrospective study of 239 older patients with osteoarthritis. Int J Biometeorol 60:1481-1491. https://doi.org/10.1007/s00484-016-1138-7 Kojima D, Nakamura T, Banno M et al (2018) Head-out immersion in hot water increases serum BDNF in healthy males. Int J Hyperthermia 34(6):834-839. https://doi.org/10.1080/02656736.2017.1394502 Latorre-Román PÁ, Rentero-Blanco M, Laredo-Aguilera JA et al (2015) Effect of a 12-day balneotherapy programme on pain, mood, sleep, and depression in healthy elderly people. Psychogeriatrics 15(1):14-19. https://doi.org/10.1111/psyg.12068 Liu C, Zhao Y, Qin S et al (2021) Randomized controlled trial of acupuncture for anxiety and depression in patients with chronic insomnia. Ann Transl Med 9(18):1426. https://doi.org/10.21037/atm-21-3845 Long J, Qin Q, Huang Y et al (2022) Study on nondrug intervention of 7 days of balneotherapy combined with various sleep-promoting measures on people with sleep disorders: preliminary and pilot study. Int J Biometeorol 67(3):457-464. https://doi.org/10.1007/s00484-023-02425-3 Maniam J, Morris MJ (2010) Voluntary exercise and palatable high-fat diet both improve behavioural profile and stress responses in male rats exposed to early life stress: role of hippocampus. Psychoneuroendocrinology 35(10):1553-1564. https://doi.org/10.1016/j.psyneuen.2010.05.012 Mertens J, Wang QW, Kim Y et al (2015) Differential responses to lithium in hyperexcitable neurons from patients with bipolar disorder. Nature 527(7576):95-99. https://doi.org/10.1038/nature15526 Monti JM (2011) Serotonin control of sleep-wake behavior. Sleep Med Rev 15(4):269-281. https://doi.org/10.1016/j.smrv.2010.11.003 Morer C, Roques CF, Françon A et al (2017) The role of mineral elements and other chemical compounds used in balneology: data from double-blind randomized clinical trials. Int J Biometeorol. 61(12):2159-2173. https://doi.org/10.1007/s00484-017-1421-2. Muthita H, Ratchakrit S (2019) Whole Body Hyperthermia Ameliorates Inflammation via Regulating Pro-inflammatory but not Anti-inflammatory Macrophages in Tenotomized Rat Skeletal Muscle[J] Physiology (A abstract is from the Experimental Biology 2019 Meeting). https://doi.org/10.1096/fasebj.2019.33.1_supplement.868.4 Oyama J, Kudo Y, Maeda T et al (2013) Hyperthermia by bathing in a hot spring improves cardiovascular functions and reduces the production of inflammatory cytokines in patients with chronic heart failure. Heart Vessel 28(2):173-178. https://doi.org/10.1007/s00380-011-0220-7 Özkuk K, Uysal B, Ateş Z, et al (2018) The effects of inpatient versus outpatient spa therapy on pain, anxiety, and quality of life in elderly patients with generalized osteoarthritis: a pilot study. Int J Biometeorol 62(10):1823-1832. https://doi.org/10.1007/s00484-018-1584-5 Poluektov MG (2021) Sleep and immunity. Neurosci Behav Physiol 51(5):609-615. https://doi.org/10.1007/s11055-021-01113-2 Pourhamzeh M, Moravej FG, Arabi M, et al (2022) The Roles of Serotonin in Neuropsychiatric Disorders. Cell Mol Neurobio 42(6):1671-1692. https://doi.org/10.1007/s10571-021-01064-9 Su Y, Hu PC (1999) The origin and current research status of floatation therapy. Chinese Journal of Clinical Psychology. 1999(04): 248-252 (Chinese) Tamaoki S, Matsumoto S, Sasa N, et al (2023) Effects of sodium bicarbonate bath on the quality of sleep: An assessor-blinded, randomized, controlled, pilot clinical trial.Complement Ther Clin Pract 50:101714. https://doi.org/10.1016/j.ctcp.2022.101714 Yamasaki S, Tokunou T, Maeda T, et al (2022) Hot spring bathing is associated with a lower prevalence of hypertension among Japanese older adults: a cross-sectional study in Beppu. Sci Rep 12(1):19462. https://doi.org/10.1038/s41598-022-24062-3 Yamazaki T, Ushikoshi-Nakayama R, Shakya S et al (2021) The effects of bathing in neutral bicarbonate ion water. Sci Rep 11(1):21789. https://doi.org/10.1038/s41598-021-01285-4 Yang B, Qin QZ, Han LL et al (2018) Spa therapy (balneotherapy) relieves mental stress, sleep disorder, and general health problems in sub-healthy people. Int J Biometeorol 62(2):261-272. https://doi.org/10.1007/s00484-017-1447-5 Yang Y, Gu K, Meng C, et al (2023) Relationship between sleep and serum inflammatory factors in patients with major depressive disorder. Psychiatry Res 329:115528. https://doi.org/10.1016/j.psychres.2023.115528 Zarezadeh M, Khorshidi M, Emami M et al (2020) Melatonin supplementation and pro-inflammatory mediators: a systematic review and meta-analysis of clinical trials. Eur J Nutr 59(5):1803-1813. https://doi.org/10.1007/s00394-019-02123-0 Cite Share Download PDF Status: Published Journal Publication published 27 Jan, 2025 Read the published version in International Journal of Biometeorology → Version 1 posted Reviewers agreed at journal 09 Jul, 2024 Reviewers invited by journal 08 Jul, 2024 Editor assigned by journal 08 Jul, 2024 First submitted to journal 06 Jul, 2024 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-4685238","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":324386464,"identity":"965c0c9c-2220-4211-95ac-49b9da9cfb78","order_by":0,"name":"Fen 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09:04:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4685238/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4685238/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00484-025-02855-1","type":"published","date":"2025-01-27T15:57:59+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62152769,"identity":"3a772550-b891-4da8-bf61-854ce99a236d","added_by":"auto","created_at":"2024-08-09 20:52:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":35942,"visible":true,"origin":"","legend":"\u003cp\u003eThe sleep-improving effects of hot spring bathing with the alteration of TNF-α and 5-HT levels\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4685238/v1/c1fe3c581595b38f2fa789e4.png"},{"id":75351492,"identity":"2fecc011-3389-4adb-ae52-b50538260b62","added_by":"auto","created_at":"2025-02-03 16:12:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1392312,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4685238/v1/d360d438-34c0-45fc-b04f-0d8abd975a40.pdf"}],"financialInterests":"","formattedTitle":"Long-term hot spring bathing on improving sleep quality with the decrease of TNF-α and increase of 5-HT","fulltext":[{"header":"Introduction","content":"\u003cp\u003eStudies on the beneficial effects of hot spring bathing such as hypertension (Yamasaki et al. 2022), obesity (Firszt-Adamczyk et al. 2016), arthritis (Karagülle et al. 2016), muscular pain (Özkuk et al. 2018), skin lesions (Inaka et al. 2021), as well as sleep improvement has been reported.\u0026nbsp;For example, a seven-day sleep-promoting program involving 31 individuals with sleep disorders, led to improvements in insomnia\u0026nbsp;(Long et al. 2022). A two-week balneotherapy (hot spring bathing) has been found to significantly enhance sleep quality among the elderly participants (Latorre-Román et al. 2015). However,\u0026nbsp;most of these study primarily focused on the short-term effects depending on questionnaire investigation without blood collection for biochemical analysis.\u003c/p\u003e\n\u003cp\u003eIn this study, we conducted comprehensive surveys on the long-term health effects of hot spring bathing among the residents of Hot Spring Village with natural hot spring resources located in Xunsi Town, Junlian County, Yibin City, Sichuan Province, China. People lived in this village have the privilege of unrestricted access to hot spring, and some individuals enjoying hot spring bathing almost everyday in their lifetime. This provided us the opportunity to explore the long-term health effects of hot spring bathing. So we conducted a face-to-face interviews to collect basic demographic data, including gender, age, marital status, income, educational, BMI, smoking, and drinking, as well as the hot spring bathing behavior, including the length and frequency of bathing and their self-reported improvements in fatigue alleviation, mood enhancement, and sleep quality etc. Besides, we also collected their blood samples to study the long-term health effects of hot spring bathing with the relationship of biochemical factor changes. The tests we conducted in this research not only basic biochemical indicators, but also inflammatory biomarkers and neurotransmitters such as TNF-α, 5-HT and BDNF.\u003c/p\u003e\n\u003cp\u003eTNF-α is an inflammatory cytokine that plays a pivotal role in the immune system by stimulating inflammatory responses, improving intercellular communication and participating in immune regulation; however, its excessive activation leads to inflammation and the development of various diseases such as sleep disorder. It has been reported that the higher the TNF-α and the worse the quality of sleep (Yang et al. 2023), and a randomized controlled trial also demonstrated that TNF-α levels significantly decreased in patients with chronic heart failure after two weeks of hot spring bathing (Oyama et al. 2013).\u0026nbsp;Nevertheless,\u0026nbsp;the changes in blood TNF-α among long-term hot spring bathing individuals have not been reported. So, it was investigated in this study.\u003c/p\u003e\n\u003cp\u003e5-HT, also known as serotonin, is a neurotransmitter that\u0026nbsp;\u003ca href=\"https://www.collinsdictionary.com/zh/dictionary/english-thesaurus/regulate\" title=\"regulate 的同义词\"\u003eregulate\u003c/a\u003es neural activity and a wide range of neuropsychological processes including\u0026nbsp;modulation of\u0026nbsp;mood, perception, aggression, memory, and attention\u0026nbsp;etc with numerous animal research supporting (Berger et al. 2009; Pourhamzeh et al. 2022).\u0026nbsp;However, there is still limited community-based study focus on the 5-HT changes. Although,\u0026nbsp;liu et al. (2021) demonstrated that acupuncture could increase tryptophan content in the peripheral system and elevate 5-HT levels in the blood, no study has been reported related the changes of 5-HT levels in the hot spring bathers. Therefore, in this study we detected blood 5-HT to evaluate the relationship of long-term hot spring bathing on improving sleep quality with the alteration of this neurotransmitter. In addition to 5-HT, we also detected BDNF, a protein that acts on neurons in the central and peripheral nervous systems, promoting the growth of new neurons, modulating neuronal plasticity, and alleviating anxiety and depression (Maniam et al. 2010; Giese et al. 2014;\u0026nbsp;Kojima et al. 2018).\u003c/p\u003e\n\u003cp\u003eIn summary, we conducted comprehensive investigation on the long-term health effects of hot spring bathing among the residents of Hot Spring Village with blood sample collection for biochemical indicator tests, including TNF-α, 5-HT and BDNF levels determination to study the health effect of hot spring bathing.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eA cross-sectional study design was used to investigate the long-term health effects of hot spring bathing. It was conducted according to the Declaration of Helsinki and approved by the Ethics Committee of Sichuan University (IRB Gwll2022102). All participants were informed about the study and signed an informed consent form.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eFrom February to April 2023, 153 residents were recruited from Hot Spring Village, Xunsi Town, Junlian County, Yibin City, Sichuan Province, China. A face-to-face interviews were conducted to collect basic demographic data (gender, age, marital status, income, educational, BMI, smoking, and drinking), as well as the hot spring bathing behavior, including the length and frequency of bathing and their self-reported improvements in fatigue alleviation, mood enhancement, and sleep quality etc. Eligibility for the study was followed several criteria: participants were to be within the age of 30 to 70 years and have a history of hot spring bathing exceeding a decade. Exclusionary factors encompassed severe conditions affecting the heart, liver, spleen, lungs, and kidneys, as well as immune and infectious disorders. In the end, a total of 153 questionnaires were collected, with 13 incomplete samples excluded, resulting in 140 participants.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eThe methods of sleep quality assessment\u003c/h2\u003e \u003cp\u003eThe sleep quality assessment by the Pittsburgh Sleep Quality Index (PSQI) (Chinese version), consists of 19 items evaluating sleep conditions over the past month from various perspectives. Each item in the seven factors is rated on a 4-level Likert scale, ranging from 0 to 3. The factors include sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbances, use of sleep medication, and daytime dysfunction. Good sleep quality is defined as a PSQI total score below 5, while a score above 5 indicates poor sleep quality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eBiochemical indicators test\u003c/h2\u003e \u003cp\u003eWe also collected blood samples to study the long-term health effects of hot spring bathing with the relationship of biochemical factor changes. A total of 6 mL of venous blood sample was collected from each participant after an 8-hour fasting period. The fully automated biochemical analyzer was used to measure the levels of triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), fasting plasma glucose (FPG), white blood cell (WBC), red blood cell (RBC), hemoglobin (HGB), platelet (PLT), alanine transaminase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), and urea in peripheral venous blood samples. The tests we conducted in this research not only basic biochemical indicators, but also inflammatory biomarker (TNF-α) and neurotransmitters (5-HT and BDNF) by ELISA assay.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePhysicochemical properties of the hot spring water\u003c/h2\u003e \u003cp\u003eThe water samples were analyzed using ion chromatography for Cl, SO\u003csub\u003e4\u003c/sub\u003e, NO\u003csub\u003e3\u003c/sub\u003e, and F, inductively coupled plasma mass spectrometry for Fe, Li, V, Cr, Mn, Co, Ni, Cu, Zn, Sb, Mo, Ag, Cd, Ba, Pb, and Al, and inductively coupled plasma-atomic emission spectrometry for K, Na, Ca, Mg, and Sr. Silicic acid (H\u003csub\u003e2\u003c/sub\u003eSiO\u003csub\u003e3\u003c/sub\u003e), NaNO\u003csub\u003e2\u003c/sub\u003e, iodide (I\u003csup\u003e\u0026minus;\u003c/sup\u003e), cyanide, bromide (Br\u003csup\u003e\u0026minus;\u003c/sup\u003e), borate (B\u003csup\u003e\u0026minus;\u003c/sup\u003e), and carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e) levels, as well as oxygen consumption (O\u003csub\u003e2\u003c/sub\u003e), total acidity, total hardness, and total alkalinity, were determined using spectrophotometry and titrimetry methods, respectively. Total dissolved solids (TDS) were analyzed by weight method, and pH was evaluated using a glass electrode. The analyses were conducted at the laboratory of the Chengdu Comprehensive Rock and Mine Testing Center of Sichuan province. The hot spring water has a source temperature of 50\u0026thinsp;~\u0026thinsp;53℃ with total dissolved solids of 5088.000 mg/L. Therefore, it is classified in the \u0026ldquo;thermomineral waters\u0026rdquo; group according to the Geological Exploration Standard for Geothermal Resources of China (GB-T-11615-2010). Furthermore, this hot spring water is rich in cations of K\u003csup\u003e+\u003c/sup\u003e, Na\u003csup\u003e+\u003c/sup\u003e, Ca\u003csup\u003e2+\u003c/sup\u003e, Mg\u003csup\u003e2+\u003c/sup\u003e and Fe\u003csup\u003e2+\u003c/sup\u003e+Fe\u003csup\u003e3+\u003c/sup\u003e with the amount reach to 1866.667 mg/L and relatively high level of TDS, Li and HCO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhysicochemical properties of the hot spring water\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic (mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMorning (7:00)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNoon (15:00)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNight (23:00)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperature \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50℃\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53℃\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52℃\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e51.670℃\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperature \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.5℃\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.9℃\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.9℃\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e44.777℃\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePH value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.350\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal acidity (by CaCO\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.233\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal alkalinity (by CaCO\u003csub\u003e3\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e148.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e144.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e146.667\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHardness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e780.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e742.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e704.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e742.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotassium (K\u003csup\u003e+\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19.300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSodium (Na\u003csup\u003e+\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1662.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1544.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1494.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1566.667\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalcium (Ca\u003csup\u003e2+\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e255.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e241.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e226.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e240.667\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMagnesium (Mg\u003csup\u003e2+\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39.867\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIron (Fe\u003csup\u003e2+\u003c/sup\u003e+Fe\u003csup\u003e3+\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.170\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubtotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1980.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1844.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1776.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1866.667\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBicarbonate (HCO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e180.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e175.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e178.333\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbonate (CO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChloride (Cl\u003csup\u003e\u0026minus;\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2252.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2224.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2238.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2238.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSulfate (SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e741.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e725.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e743.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e736.333\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNitrate (NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.733\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFluoride (F\u003csup\u003e\u0026minus;\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.487\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubtotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3177.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3133.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3160.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3156.667\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLithium (Li)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.232\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrontium (Sr)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.790\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.370\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetasilicic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43.300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNitrite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbon dioxide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.900\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIodide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCyanides\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVolatile phenols\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBromide (Br\u003csup\u003e\u0026minus;\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.150\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOxygen consumption\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.800\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSulfide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetaboric acid (B)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.377\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal dissolved solids (TDS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5190.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5050.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5024.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5088.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: \u003csup\u003ea\u003c/sup\u003e the temperature of the hot spring source; \u003csup\u003eb\u003c/sup\u003e the temperature of the bathing pool.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eWe conducted statistical analysis using R 4.2.2 software. Measurement data were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD and analyzed with \u003cem\u003et\u003c/em\u003e test. Non-normally distributed data were described using median and interquartile range with Mann-Whitney \u003cem\u003eU\u003c/em\u003e test. Categorical variables were described using frequencies and percentages with chi-square test. Logistic regression was to analyze the relationship between hot spring bathing and sleep quality. Statistical significance was defined as \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eBasic demographic characteristics and biochemical test results for the participants\u003c/h2\u003e \u003cp\u003eA total of 140 residents who lived in the Hot Spring Village more than ten years (48 males and 92 females) were included, and 44.29% (62/140) of them took hot spring bath regularly. Among them, 88 were under the age of 65, while 52 were 65 or older. No significant differences of age, gender, marital status, smoking, drinking, length of residence, educational, BMI, Waist, DBP were observed between the hot spring bathing and non bathing groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Interestingly, we found at the first time that the TNF-α, a kind of inflammatory biomarkers, significantly decreased (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with an increasing trend of neurotransmitters 5-HT and BDNF in the hot spring bathing group (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These results suggested a potential health-improving effect of hot spring bathing for further analysis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic demographic characteristics and biochemical test results for the participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eHot spring bathing\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo [n (%)]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes [n (%)]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78 (55.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62 (44.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;65 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88 (62.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (58.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;65 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52 (37.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (41.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.326\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (34.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24 (30.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 (38.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92 (65.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54 (69.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38 (61.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (5.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (8.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (1.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132 (94.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71 (91.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61 (98.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.556\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105 (75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60 (76.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45 (72.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18 (23.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (27.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrinking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.291\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118 (84.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68 (87.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50 (80.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (15.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (12.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (19.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eEducational (Junior high school or above)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.144\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (30.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20 (25.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23 (37.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97 (69.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58 (74.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (62.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.09\u0026thinsp;\u0026plusmn;\u0026thinsp;3.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.56\u0026thinsp;\u0026plusmn;\u0026thinsp;3.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.50\u0026thinsp;\u0026plusmn;\u0026thinsp;3.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83.31\u0026thinsp;\u0026plusmn;\u0026thinsp;8.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e83.12\u0026thinsp;\u0026plusmn;\u0026thinsp;9.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83.54\u0026thinsp;\u0026plusmn;\u0026thinsp;7.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.634\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148.86\u0026thinsp;\u0026plusmn;\u0026thinsp;21.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e151.88\u0026thinsp;\u0026plusmn;\u0026thinsp;19.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e145.06\u0026thinsp;\u0026plusmn;\u0026thinsp;22.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83.96\u0026thinsp;\u0026plusmn;\u0026thinsp;21.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86.10\u0026thinsp;\u0026plusmn;\u0026thinsp;19.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81.26\u0026thinsp;\u0026plusmn;\u0026thinsp;24.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.116\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.60\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.227\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.04\u0026thinsp;\u0026plusmn;\u0026thinsp;1.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.176\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.549\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFPG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.29\u0026thinsp;\u0026plusmn;\u0026thinsp;2.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.237\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.05\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.25\u0026thinsp;\u0026plusmn;\u0026thinsp;2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.89\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.441\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHGB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e144.55\u0026thinsp;\u0026plusmn;\u0026thinsp;14.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e147.12\u0026thinsp;\u0026plusmn;\u0026thinsp;14.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e142.51\u0026thinsp;\u0026plusmn;\u0026thinsp;13.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e225.09\u0026thinsp;\u0026plusmn;\u0026thinsp;62.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e217.78\u0026thinsp;\u0026plusmn;\u0026thinsp;70.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e230.90\u0026thinsp;\u0026plusmn;\u0026thinsp;55.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.63\u0026thinsp;\u0026plusmn;\u0026thinsp;8.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.61\u0026thinsp;\u0026plusmn;\u0026thinsp;7.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.65\u0026thinsp;\u0026plusmn;\u0026thinsp;8.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.603\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.51\u0026thinsp;\u0026plusmn;\u0026thinsp;7.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.56\u0026thinsp;\u0026plusmn;\u0026thinsp;6.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.27\u0026thinsp;\u0026plusmn;\u0026thinsp;7.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTBIL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.26\u0026thinsp;\u0026plusmn;\u0026thinsp;3.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.10\u0026thinsp;\u0026plusmn;\u0026thinsp;4.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.39\u0026thinsp;\u0026plusmn;\u0026thinsp;3.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.351\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUREA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.35\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.392\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF-α\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.73 (18.94, 89.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.19 (36.81, 104.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.75 (15.20, 67.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-HT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.40 (40.76, 79.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49.68 (39.25, 67.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58.48 (45.86, 88.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBDNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.99 (0.28, 1.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.05 (0.34, 1.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.98 (0.16, 2.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.633\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eThe relationship between hot spring bathing and sleep quality by age with basic demographic characteristics\u003c/h2\u003e \u003cp\u003eAs shown in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the inflammatory biomarkers and neurotransmitters were altered suggesting potential sleep-improving effects. Therefore, we analyzed the relationship between hot spring bathing and sleep quality by age with basic demographic characteristics. In the hot spring bathing group, 51.61% of them reported a length of hot spring bathing more than 30 minutes, and 48.39% reported a frequency of hot spring bathing at least 3 times per week, which were significant association with sleep quality in the group of 65 and older (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of sleep quality by age with basic demographic characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eUnder 65 years old\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eAbove 65 years old\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGood [n (%)]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor [n (%)]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGood [n (%)]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePoor [n (%)]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23 (16.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65 (46.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17 (12.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35 (25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHot spring bathing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (44.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27 (75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13 (50.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13 (50.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78 (55.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14 (26.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38 (73.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (15.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22 (84.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eLength of hot spring bathing each time (min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78 (55.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14 (26.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38 (73.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (15.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22 (84.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (21.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (20.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12 (80.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6 (40.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9 (60.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (22.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (28.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15 (71.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (63.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (36.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eFrequency of hot spring bathing per week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78 (55.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14 (26.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38 (73.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (15.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22 (84.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (22.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (19.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17 (80.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (18.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9 (81.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (21.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (33.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10 (66.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11 (73.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (26.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.202\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (34.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (20.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19 (79.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 (41.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14 (58.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92 (65.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18 (28.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46 (71.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21 (75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.404\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (5.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (14.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6 (85.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132 (94.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23 (26.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64 (73.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16 (35.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29 (64.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105 (75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18 (25.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52 (74.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9 (25.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26 (74.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (27.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13 (72.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8 (47.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9 (52.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrinking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.496\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118 (84.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21 (26.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57 (73.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (30.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28 (70.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (15.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (20.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8 (80.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (41.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7 (58.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eEducational (Junior high school or above)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.735\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (30.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (33.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20 (66.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (38.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (61.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97 (69.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13 (22.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45 (77.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12 (30.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27 (69.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.09\u0026thinsp;\u0026plusmn;\u0026thinsp;3.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.35\u0026thinsp;\u0026plusmn;\u0026thinsp;4.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.81\u0026thinsp;\u0026plusmn;\u0026thinsp;3.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.60\u0026thinsp;\u0026plusmn;\u0026thinsp;2.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83.31\u0026thinsp;\u0026plusmn;\u0026thinsp;8.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81.65\u0026thinsp;\u0026plusmn;\u0026thinsp;9.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e84.13\u0026thinsp;\u0026plusmn;\u0026thinsp;9.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83.27\u0026thinsp;\u0026plusmn;\u0026thinsp;6.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82.87\u0026thinsp;\u0026plusmn;\u0026thinsp;7.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.703\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148.86\u0026thinsp;\u0026plusmn;\u0026thinsp;21.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e147.96\u0026thinsp;\u0026plusmn;\u0026thinsp;17.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e146.42\u0026thinsp;\u0026plusmn;\u0026thinsp;22.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e147.04\u0026thinsp;\u0026plusmn;\u0026thinsp;27.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e154.88\u0026thinsp;\u0026plusmn;\u0026thinsp;15.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83.96\u0026thinsp;\u0026plusmn;\u0026thinsp;21.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e88.11\u0026thinsp;\u0026plusmn;\u0026thinsp;7.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80.75\u0026thinsp;\u0026plusmn;\u0026thinsp;28.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e84.00\u0026thinsp;\u0026plusmn;\u0026thinsp;13.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e87.18\u0026thinsp;\u0026plusmn;\u0026thinsp;17.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.384\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.59\u0026thinsp;\u0026plusmn;\u0026thinsp;1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.98\u0026thinsp;\u0026plusmn;\u0026thinsp;2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.640\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.507\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.722\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.407\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFPG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.61\u0026thinsp;\u0026plusmn;\u0026thinsp;2.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.16\u0026thinsp;\u0026plusmn;\u0026thinsp;1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.930\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.05\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.56\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.87\u0026thinsp;\u0026plusmn;\u0026thinsp;1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.66\u0026thinsp;\u0026plusmn;\u0026thinsp;4.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.74\u0026thinsp;\u0026plusmn;\u0026thinsp;1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.762\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRBC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.215\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHGB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e144.55\u0026thinsp;\u0026plusmn;\u0026thinsp;14.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e143.22\u0026thinsp;\u0026plusmn;\u0026thinsp;12.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e144.74\u0026thinsp;\u0026plusmn;\u0026thinsp;14.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e144.59\u0026thinsp;\u0026plusmn;\u0026thinsp;16.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e145.06\u0026thinsp;\u0026plusmn;\u0026thinsp;13.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.868\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e225.09\u0026thinsp;\u0026plusmn;\u0026thinsp;62.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e245.52\u0026thinsp;\u0026plusmn;\u0026thinsp;87.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e231.45\u0026thinsp;\u0026plusmn;\u0026thinsp;59.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e191.48\u0026thinsp;\u0026plusmn;\u0026thinsp;46.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e216.18\u0026thinsp;\u0026plusmn;\u0026thinsp;49.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.63\u0026thinsp;\u0026plusmn;\u0026thinsp;8.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.35\u0026thinsp;\u0026plusmn;\u0026thinsp;5.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.80\u0026thinsp;\u0026plusmn;\u0026thinsp;10.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.18\u0026thinsp;\u0026plusmn;\u0026thinsp;4.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15.47\u0026thinsp;\u0026plusmn;\u0026thinsp;6.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.800\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.51\u0026thinsp;\u0026plusmn;\u0026thinsp;7.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.29\u0026thinsp;\u0026plusmn;\u0026thinsp;4.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.86\u0026thinsp;\u0026plusmn;\u0026thinsp;8.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.08\u0026thinsp;\u0026plusmn;\u0026thinsp;4.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.68\u0026thinsp;\u0026plusmn;\u0026thinsp;5.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.822\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTBIL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.26\u0026thinsp;\u0026plusmn;\u0026thinsp;3.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.73\u0026thinsp;\u0026plusmn;\u0026thinsp;2.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.88\u0026thinsp;\u0026plusmn;\u0026thinsp;4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.28\u0026thinsp;\u0026plusmn;\u0026thinsp;3.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.93\u0026thinsp;\u0026plusmn;\u0026thinsp;3.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.558\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUREA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.82\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.08\u0026thinsp;\u0026plusmn;\u0026thinsp;1.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.339\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF-α\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.73 (18.94, 89.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.46 (9.42, 67.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.14 (20.76, 87.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.56 (16.27, 43.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e72.79 (40.83, 101.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-HT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.40 (40.76, 79.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.93 (35.24, 66.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.14 (45.07, 79.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e86.71 (49.24, 123.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e48.40 (38.39, 79.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBDNF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.99 (0.28, 1.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.87 (0.43, 1.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.83 (0.22, 1.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.11 (0.17, 2.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.15 (0.21, 1.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.407\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFurther logistic regression analysis demonstrated that hot spring bathing (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.18, 95%\u003cem\u003eCI\u003c/em\u003e: 0.05\u0026ndash;0.68). with the length of bathing time more than 30 minutes (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.10, 95%\u003cem\u003eCI\u003c/em\u003e: 0.02\u0026ndash;0.53), and the frequency of more than 3 times per week (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.07, 95%\u003cem\u003eCI\u003c/em\u003e: 0.01\u0026ndash;0.32) were protective factors for sleep quality (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). When taking hot spring bath as a reference, logistic regression analyses found that the risk of poor sleep quality in the hot spring bathing group was 5.5 times lower than that in the non-bathing group (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.50, 95% \u003cem\u003eCI\u003c/em\u003e: 1.48\u0026ndash;20.46) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression analysis the association of hot spring bathing and inflammatory biomarkers with sleep quality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable (Reference)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eS.E.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWald\u003csub\u003eχ2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eOR\u003c/em\u003e (95%\u003cem\u003eCI\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHot spring bath (No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.18 (0.05\u0026ndash;0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHot spring bath (Yes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.50 (1.48\u0026ndash;20.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eLength of hot spring bathing each time (No)\u003c/p\u003e \u003cp\u003ebathing time (No)\u003c/p\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;30 min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.27 (0.06\u0026ndash;1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;30 min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.10 (0.02\u0026ndash;0.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eFrequency of hot spring bathing per week (No)\u003c/p\u003e \u003cp\u003e-\u003c/p\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;3 times/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.82 (0.13\u0026ndash;5.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.833\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;3 times/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07 (0.01\u0026ndash;0.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF-α\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.03 (1.01\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5-HT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.98 (0.97\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eHot spring bathing improved sleep quality with the alteration of TNF-α and 5-HT levels\u003c/h2\u003e \u003cp\u003eAs shown in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the levels of TNF-α in participants with good sleep quality were significant lower than those of poor sleepers (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Moreover, The levels of 5-HT in aged above 65 with good sleep quality were significant higher than poor sleepers (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Further logistic analysis revealed that a decrease of TNF-α (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.03, 95% \u003cem\u003eCI\u003c/em\u003e: 1.01\u0026ndash;1.06) and an increase of 5-HT (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.98, 95% \u003cem\u003eCI\u003c/em\u003e:0.97\u0026ndash;0.99) were associated with good sleep quality (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), a decreased of TNF-α and an increased of 5-HT levels in the hot spring bathing group with good sleep quality were also observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e), suggesting that hot spring bathing might improve sleep quality by regulating 5-HT and TNF-α.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we undertook a comprehensive investigation that integrating questionnaire survey and analyses of both blood and hot spring water samples. Our aim was to examine the long-term health effects of hot spring bathing among the residents of Hot Spring Village, who enjoy complimentary access to these natural resources. We found that hot spring bathing was beneficial for improving sleep quality, and the risk of poor sleep quality in the hot spring bathing group was 5.5 times lower than that in the non-bathing group (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.50, 95% \u003cem\u003eCI\u003c/em\u003e: 1.48\u0026ndash;20.46) when taking hot spring bath as a reference. This result is consistent with Yang\u0026rsquo;s findings (Yang et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Besides, our results also demonstrated that in order to have a significant improvement in sleep quality, taking bathing three times per week (\u003cem\u003eR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.10, 95%\u003cem\u003eCI\u003c/em\u003e: 0.02\u0026ndash;0.53) with a minimum of 30 minutes each time (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.07, 95%\u003cem\u003eCI\u003c/em\u003e: 0.01\u0026ndash;0.32) were recommended. Furthermore, the novel findings of this present study are that long-term hot spring bathing improved sleep quality with the alteration of TNF-α and 5-HT.\u003c/p\u003e \u003cp\u003eTNF-α is the most common inflammatory factor and considered as a sleep-improving cytokine. It was reported that sleep disturbance, as well poor sleep quality could cause an increase of TNF-α (Irwin et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Poluektov MG. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; D'Antono et al. 2019), whereas dietary supplement with melatonin improving sleep quality with a decrease of TNF-α (Zarezadeh et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Very interestingly, our research for the first time revealed a significant reduction in TNF-α levels among individuals who engaged in hot spring bathing and exhibited good sleep quality. We speculated that the thermal stimulation from hot spring bathing might help supporting immune regulation and anti-inflammatory responses, leading to a reduction in TNF-α levels. In fact, there has been some studies demonstrated that the thermotherapy effects of either hot water bathing or hot spring bathing on the alternation of TNF-α. For instance, Muthita et al (2019) reported a significant decrease in the expression of TNF-α protein levels in rats subjected to heat treatment with a core body temperature maintained within the range of 40.5\u0026ndash;41.5\u0026deg;C for a duration of 30 minutes daily over a period of seven days, while a randomized controlled trial demonstrated the decrease of TNF-α levels in patients with chronic heart failure after two weeks of hot spring bathing (Oyama et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Collectively, the results suggested that hot spring bathing could confer anti-inflammatory effects, potentially enhancing sleep quality through the modulation of TNF-α levels.\u003c/p\u003e \u003cp\u003eAlthough it has been reported that hot spring bathing helps regulate emotions, promote relaxation, and achieve a pleasurable state, reducing anxiety and tension and improving psychological well-being. We found for the first time that an increasing trend in 5-HT levels in hot spring bathing participants was associated with good sleep quality (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.98, 95% \u003cem\u003eCI\u003c/em\u003e:0.97\u0026ndash;0.99). 5-HT, also called serotonin, known as \"happiness neurotransmitter\", not only an important factor for mood regulation but also involved in the sleep-wake mechanism with a crucial role in maintaining slow-wave sleep (Monti et al. 2011). Besides, research has also shown that physiotherapy increased the tryptophan content in the peripheral system, increase the level of 5-HT in the blood, and accelerate tryptophan transport, thereby promoting the synthesis of 5-HT in the brain and ultimately improving the sleep of patients (Liu et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The mechanisms of hot spring bathing on improving sleep quality may be similar to the effects of the physiotherapy. Furthermore, in this research, participants self-reported feelings of happiness and relaxation after hot spring bathing which might be related to the increased level of blood 5-HT.\u003c/p\u003e \u003cp\u003eAdditionally, in this study, we also tested the composition of the water samples and found this hot spring water was characterized by high sodium, carbon dioxide, bicarbonate and lithium contents, which might be associated with regulating mood and improving sleep. Tamaoki et al (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) conducted a randomized controlled trial and found that sodium bicarbonate bathing for a period of seven days had positive effects on improving sleep quality of adults. Yamazaki et al (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) also demonstrated that bathing in neutral bicarbonate ionized water resulting in percutaneously absorbed carbon dioxide enhanced blood flow with a improvement in sleep quality. These studies suggested that a bath rich in bicarbonate ions (HCO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e), as well as carbon dioxide, might enable ions to penetrate the skin, promoting neurohumoral regulation, accelerating metabolism, and facilitating the excretion of lactic acid which effectively relieve fatigue and improve sleep efficiency. Notably, the lithium ion content in this hot spring water was 0.236 mg/L, ten times higher than that reported by Long et al (2023). Lithium, a kind of trace element, has a modulating effect on the central nervous system and is a potent mood stabilizer. Clinically, lithium has been widely used to treat bipolar disorder mania. It was reported that lithium treatment selectively reversed the hyperexcitability of young neurons in patients with bipolar disorder in those who responded well to lithium (Mertens et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Besides, the increasing serum levels of lithium following balneotherapy with Dead Sea bath salt may imply the possibility of transcutaneous absorption of lithium from the salt (Halevy et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). In addition, we also noticed that the amount of total dissolved solids content of this hot spring was as high as 5,088 mg/L and rich in cations of K\u003csup\u003e+\u003c/sup\u003e, Na\u003csup\u003e+\u003c/sup\u003e, Ca\u003csup\u003e2+\u003c/sup\u003e, Mg\u003csup\u003e2+\u003c/sup\u003e and Fe\u003csup\u003e2+\u003c/sup\u003e+Fe\u003csup\u003e3+\u003c/sup\u003e with the amount up to 1,866.667 mg/L, which was relatively higher than \u0026Ouml;zkuk\u0026rsquo;s (2018) report. It has been considered that high amount of total dissolved solids and cations resulting in buoyancy and hydrostatic pressure might promote muscle relaxation, emotional stability, and lower adrenal cortex hormone levels in turn enhanced the sleep improvement (Su et al. 1999). It has been reported that the increased buoyancy experienced during immersion in hot spring water induces various physiological changes. These include strengthen circulation, relaxation of tense muscles, and relief from spasms, etc. Overall, the psychological benefits of hot spring bathing could be partly attributed to the chemical properties of the hot spring water (Morer et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the other hand, in this study, the villagers usually took hot spring bating at the temperature of 44.5\u0026thinsp;~\u0026thinsp;45℃. Harding et al (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) proposed that pre-sleep hot spring bathing might postpone the occurrence of the body's temperature trough, which could consequently facilitate deeper sleep stages. Passive body heating by immersing in hot (40\u0026thinsp;~\u0026thinsp;40.5℃) bath 1.5\u0026thinsp;~\u0026thinsp;2 hours before bedtime for older female insomniacs could increase core body temperature with the increasing of slow-wave sleep in the early part of the sleep period resulting in sleep continuity improvement (Dorsey et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). So, we inferred long-term hot spring bathing on improving sleep quality might also related to the thermotherapy effects.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThe major limitation of this study was that the data we collected regarding the years of hot spring bathing were categorized as less than 10 years or 10 years or more, without obtaining continuous data on the specific years of hot spring bathing. Therefore, \"long-term\" in this study refers to periods of 10 years or longer. Additionally, the data for this study were derived from a cross-sectional survey. Further research should consider establishing a prospective cohort specific to hot spring bathers and conducting continuously follow-up investigation to observe a wider range of health effects associated with long-term hot spring bathing.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study suggested that long-term hot spring bathing may improve sleep quality by regulating TNF-α and 5-HT levels, potentially serving as biomarkers for future investigations into the health-promoting effects of bathing. These findings further provide valuable evidence for the health benefits of hot spring bathing.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e We would like to thank the staff members at the Junlian County Xunsi Central Health Centre and all the volunteers for their collaborative efforts. And we also gratefully acknowledge the supports of Provincial Public Health Experiment Teaching Demonstration Center at Sichuan University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e Fen Yang: Investigation, experimental analysis and writing-original draft. Yue Zou: Experimental analysis. Ying-ying Zhang: Data collection and experimental analysis. Hong-xia Li: Data collection. Yi-hang Xu: Data collection. Bao-chao Zhang: Data collection and experimental analysis. Lin-xuan Liao: Data collection. Meng-xi Cao: Data analysis. Rui-xue Wang: Data analysis and experimental analysis. Yuan Yuan: Data collection. Yun Zhou: Formal analysis. Da-yong Zeng: Data collection. Xiao-fang Pei: Conceptualization, funding acquisition, writing-review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThis work was supported by the Yibin Science and Technology Planning Program (Grant numbers: 2021ZYSF006). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e The data involved in this study are not publicly available due to privacy but are available from the authors on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003eThe authors have no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBerger M, Gray JA, Roth BL et al (2009) The expanded biology of serotonin. Annu Rev Med 60:355-366. https://doi.org/10.1146/annurev.med.60.042307.110802\u003c/li\u003e\n\u003cli\u003eD\u0026apos;Antono B, Bouchard V (2019) Impaired sleep quality is associated with concurrent elevations in inflammatory markers: are post-menopausal women at greater risk? 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Eur J Nutr 59(5):1803-1813. https://doi.org/10.1007/s00394-019-02123-0\u003c/li\u003e\n\u003c/ol\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":"international-journal-of-biometeorology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijbm","sideBox":"Learn more about [International Journal of Biometeorology](http://link.springer.com/journal/484)","snPcode":"484","submissionUrl":"https://www.editorialmanager.com/ijbm/default2.aspx","title":"International Journal of Biometeorology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Hot spring bathing, Sleep quality, TNF-α, 5-HT, Health effect","lastPublishedDoi":"10.21203/rs.3.rs-4685238/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4685238/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePrevious studies investigating the influence of hot spring bathing on sleep quality have predominantly focused on the short-term effects basically depending on questionnaire without blood collection for biochemical tests. In this study, we undertook comprehensive investigation on the long-term health effects of hot spring bathing among the residents of Hot Spring Village and collected their blood samples for biochemical tests, including inflammatory cytokines (TNF-α) and neurotransmitters (5-HT and BDNF) analysis as well. We found that hot spring bathing (\u003cem\u003eOR\u003c/em\u003e=0.18, 95%\u003cem\u003eCI\u003c/em\u003e: 0.05-0.68), with the length of more than 30 minutes (\u003cem\u003eOR\u003c/em\u003e=0.10, 95%\u003cem\u003eCI\u003c/em\u003e: 0.02-0.53), and the frequency of more than 3 times per week (\u003cem\u003eOR\u003c/em\u003e=0.07, 95%\u003cem\u003eCI\u003c/em\u003e: 0.01-0.32) were protective factors for sleep quality (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05). Interestingly, we observed at the first time that the blood TNF-α significantly decreased (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05), with an increasing trend of 5-HT and BDNF in the bathing group. Besides, participants with good sleep quality exhibited significantly lower levels of TNF-α compared to those of poor ones, and among good sleepers aged 65 and older, higher levels of 5-HT were observed. Further logistic analysis revealed that a decrease of TNF-α (\u003cem\u003eOR\u003c/em\u003e=1.03, 95% \u003cem\u003eCI\u003c/em\u003e: 1.01-1.06) and an increase of 5-HT (\u003cem\u003eOR\u003c/em\u003e=0.98, 95% \u003cem\u003eCI\u003c/em\u003e: 0.97-0.99) were associated with good sleep quality. Additionally, the trends of decreasing TNF-α and increasing 5-HT were also\u003c/p\u003e\n\u003cp\u003eobserved in the hot spring bathing group with good sleep quality for the first time. These findings suggested that hot spring bathing might improve sleep quality with the alteration of TNF-α and 5-HT, which could serve as potential indicators for future studies on health benefits of bathing.\u003c/p\u003e","manuscriptTitle":"Long-term hot spring bathing on improving sleep quality with the decrease of TNF-α and increase of 5-HT","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-09 20:51:54","doi":"10.21203/rs.3.rs-4685238/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-07-09T07:28:13+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-08T21:38:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-08T19:46:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Journal of Biometeorology","date":"2024-07-06T12:01:21+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-biometeorology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijbm","sideBox":"Learn more about [International Journal of Biometeorology](http://link.springer.com/journal/484)","snPcode":"484","submissionUrl":"https://www.editorialmanager.com/ijbm/default2.aspx","title":"International Journal of Biometeorology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"5f40eb8e-5aa5-417e-a906-068e212a1327","owner":[],"postedDate":"August 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-02-03T16:06:29+00:00","versionOfRecord":{"articleIdentity":"rs-4685238","link":"https://doi.org/10.1007/s00484-025-02855-1","journal":{"identity":"international-journal-of-biometeorology","isVorOnly":false,"title":"International Journal of Biometeorology"},"publishedOn":"2025-01-27 15:57:59","publishedOnDateReadable":"January 27th, 2025"},"versionCreatedAt":"2024-08-09 20:51:54","video":"","vorDoi":"10.1007/s00484-025-02855-1","vorDoiUrl":"https://doi.org/10.1007/s00484-025-02855-1","workflowStages":[]},"version":"v1","identity":"rs-4685238","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4685238","identity":"rs-4685238","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}