Physical Activity Combined with Tea Consumption could further Reduce All-cause Mortality: Results from the US National Health and Nutrition Examination Survey, 2009-2018

Physical Activity Combined with Tea Consumption could further Reduce All-cause Mortality: Results from the US National Health and Nutrition Examination Survey, 2009-2018 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Physical Activity Combined with Tea Consumption could further Reduce All-cause Mortality: Results from the US National Health and Nutrition Examination Survey, 2009-2018 Yiqun Hu, Luning Yang, Jinshen He This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4552199/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Oct, 2024 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract The study aimed to comprehensively assess the separate and combined effects of physical activity (PA) and tea consumption on all-cause mortality among 21,350 participants from The National Health and Nutrition Examination Survey (NHANES) between 2009 and 2018. PA and tea consumption were evaluated through self-reported questionnaires and dietary recall interviews at baseline, with mortality data obtained from the National Death Index. Cox regression analyses yielded hazard ratios (HR) and 95% confidence intervals (CI). Results indicated that both tea consumption and PA independently reduced all-cause mortality. In the physically active group, tea consumption further decreased mortality risk, while this effect was not significant in the inactive group. Jointly, the highest tea consumers who exercised the most exhibited the lowest mortality risk compared to non-tea drinkers who exercised the least. These findings underscore the potential benefits of regular tea consumption and PA in promoting longevity and reducing premature death risks. Health sciences/Health care Health sciences/Diseases/Cancer NHANES Tea consumption Nutrition Exercise Mortality Joint effects model Longevity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Nowadays, tea is widely consumed and has become the second most popular beverage after water ( 1 ). The global average consumption of tea is about 0.5 kg per capita, though amounts (in kg per capita) are greater where tea drinking is common such as India (0.73), China (0.95), Japan (0.96), Ireland (1.90), United Kingdom (1.97), Turkey (2.04), and Libya (1.90) ( 1 ). The relationship between tea and health has become an increasingly important topic. It is widely believed that tea may protect against death from all causes ( 2 ). Available evidence shows that tea can interrupt lipid emulsification, reduce adipocyte differentiation, increase thermogenesis, and reduce food intake, thus tea improves systemic metabolism and decreases fat mass ( 3 – 5 ). PA has long been widely recognized for its health benefits. People who perform physical activity above the recommended level according to the current public health guidelines were associated with lower morbidity and mortality ( 6 ). Physical activity can potentially increase telomere length, enhance anti-oxidative and anti-thrombotic enzymes ( 7 ), and improve cardiovascular health by reducing risk factors like in individuals with obesity ( 8 ). At the same time, research has observed that PA may lead to an increase in the production of free radicals, potentially causing oxidative damage ( 9 – 14 ). Dietary antioxidants may help protect cells from oxidative damage ( 15 – 17 ), so tea, as a recognized antioxidant beverage, may further enhance the health benefits of PA ( 11 ). However, although there is a lot of evidence for the health benefits of PA and tea consumption, there is a lack of direct evidence on whether PA and tea consumption can further have better effects on our health when they are carried out together. In this study, we used logistic regression to analyze the effect of tea consumption on all-cause mortality in different PA subgroups. We also constructed a joint model of PA and tea consumption to explore the combined effects of them on health status. It was hypothesized that tea consumption combined with PA could more effectively reduce all-cause mortality and cancer-specific mortality, which might provide meaningful guidance for conducting more scientifically sound exercise studies. Method Study Population The National Health and Nutrition Examination Survey (NHANES) is a population-based cross-sectional study conducted by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention to assess the health and nutrition status of adults and children in the United States. Participation in the survey is voluntary and will undergo standardized personal interviews and examinations. The NHANES interview includes demographic, socioeconomic, dietary, and health-related questions. The examination component consists of medical, dental, and physiological measurements, as well as laboratory tests administered by highly trained medical personnel. More details of the sampling method and data collection have been published on the web ( http://www.cdc.gov/nchs/nhanes/index.htm ). NCHS has linked data from various surveys with death certificate records from the National Death Index (NDI). Linkage of the NCHS survey participant data with the NDI mortality data provides the opportunity to conduct a vast array of outcome studies designed to investigate the association of a wide variety of health factors with mortality. In this analysis, we included 49,693 participants from the 2009–2018 NHANES datasets. Further, we excluded 19,451 participants who were not eligible for linking NDI mortality data to NCHS data. Additionally, we excluded 8,656 participants who had missing covariate-related data and 236 participants who were pregnant at the time of the interview. Ultimately, we included 21,350 participants for data analysis. (Fig. 1 ) Outcome ascertainment For our research, we obtained the public-use linked mortality files (LMF) spanning the years 2009 to 2018 from NCHS. Vital status was determined using the "MORTSTAT" variable within the public-use LMF dataset. Additionally, we calculated the follow-up time by measuring person-months from the date of the initial interview to the date of death or the conclusion of the mortality tracking period (PERMTH_INT). For more comprehensive information regarding the NDI mortality files, please consult the following website: https://www.cdc.gov/nchs/data-linkage/mortality.htm Assessment of physical activity In NHANES, PA information was collected by using physical activity questionnaire, which is based on the Global Physical Activity Questionnaire (GPAQ). We use the following questions: 1). How much time do you spend doing vigorous-intensity activities at work on a typical day? 2). How much time do you spend doing moderate-intensity activities at work on a typical day? 3). How much time do you spend walking or bicycling for travel on a typical day? 4). How much time do you spend doing vigorous-intensity sports, fitness or recreational activities on a typical day? 5). How much time do you spend doing moderate-intensity sports, fitness or recreational activities on a typical day? For each type of activity, a suggested metabolic equivalent (MET) score of 8.0, 4.0, 4.0, 8.0, and 4.0 was assigned according to the appendix. We multiplied the suggested MET value of each type of question by the minutes spent on it in a typical week to obtain the MET min per week of each activity and then summed the scores to obtain the weekly total MET score. Additional details are available at https://www.cdc.gov/nchs/nhanes/ . According to the World Health Organization, adults should engage in physical activity for at least 75 minutes at a vigorous intensity, 150 minutes at a moderate intensity, or an equivalent combination of moderate and vigorous-intensity activity, achieving at least 600 METs per minute in a typical week ( 6 ). For our study, we defined those with MET scores less than 600 as the inactive group and those with MET scores greater than 600 as the active group. Assessment of tea consumption In NHANES, all participants are eligible for two 24-hour dietary recall interviews to provide diet-related data. The first interview is conducted in person in the Mobile Examination Center, while the second is conducted by telephone 3 to 10 days later. Each food or beverage item that can be reported in What We Eat in America (WWEIA), NHANES is placed in one of several mutually exclusive food categories that group similar items together based on usage and nutrient content ( https://www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-human-nutrition-research-center/food-surveys-research-group/ ). Based on the food category, we calculated tea consumption by averaging the two days' consumption of beverages belonging to the tea category (using only one day's data if data was missing on the other day). In the classification model, data are segmented based on approximate tertiles of tea consumption, which is categorized into three distinct groups: none, low, and high. 'None' corresponds to a tea consumption of 0g, 'low' is defined as any consumption greater than 0g but less than 300g, and 'high' encompasses consumption exceeding 300g. Covariate Assessment The following variables were included in this analysis: age, sex, race/ethnicity, education, income-to-poverty ratio (IPR), body mass index (BMI), alcohol, smoke, diabetes, hypertension, high cholesterol, and cancer. These confounders were evaluated using prior knowledge and descriptive statistics from our cohort through the use of directed acyclic graphs (Supplement Fig. 1 ). IPR is a ratio of family income to poverty guidelines, calculated by dividing family income by the poverty guidelines specific to family size, as well as the appropriate year and state ( 18 ). We divided IPR into three categories: low ( 4). BMI was calculated as a person's weight in kilograms divided by the square of height in meters. According to WHO’s classification, participants were classified as normal weight (18.5–24.9 kg/m 2 ), overweight (25.0–29.9 kg/m 2 ) or obese (≥ 30.0 kg/m 2 ) ( 18 ). Smoking status was based on following questions: 1). ‘{Have you/Has SP} smoked at least 100 cigarettes in {your/his/her} entire life?’. 2). ‘{Do you/Does SP} now smoke cigarettes?’. We defined the those who answered ‘no’ in question 1) as ‘nonsmokers’, those who answer ‘yes’ in question 1) and ‘no’ in question 2) as ‘former smokers’, those who answer ‘yes’ in both question 1) and question 2) as ‘current smokers’. According to two 24-hour dietary recall interviews, alcohol use was defined as those who reported alcohol consumption in either interview. Diabetes was defined as self-reported diabetes, or glycol hemoglobin ≥ 6.5% or measuring fasting glucose ≥ 126 mg/dL ( 19 ). Hypertension was defined as self-reported hypertension. High cholesterol was defined as the ratio of total cholesterol to HDL of > 5.9 ( 20 ). Cancer was defined as to self-reported cancers. Statistical analysis Descriptive analysis was used to explore the baseline characteristics of the included participants. We stratified them according to active and inactive activity. Means and standard deviations were used for exploring continuous variable (Tea). We first performed the Levene’s test on it to confirm homogeneity of variance and then we performed t-test to appraise significance difference between groups. Categorical variables were described as numbers and percentages. Significance difference between groups was appraised by the chi-square test. In our study, we used the Reverse Kaplan-Meier method to calculate the follow-up time to account for the occurrence of outcome events that precluded further follow-up. Before proportional hazards regression was performed, the proportional hazards assumption was tested for the variables included in the analysis, and none of the variables were violated. After that, we used Cox proportional hazard regression models to estimate the hazard ratios (HR) and 95% confidence intervals (CI) of all-cause mortality risks associated with PA and tea consumption independently with the following covariates: age, sex and race/ethnicity in model 1; model 1 plus BMI, IPR, education, smoke, alcohol, high cholesterol, diabetes, hypertension, cancer in model 2, and we confirmed reductions in all-cause mortality with both PA and tea consumption independently. To investigate the effects of tea consumption in people with different exercise profiles, we divided the population into two subgroups based on whether they were physically active or not. We used cox regression separately to estimate the hazard ratios (HR) and 95% confidence intervals (CI) of all-cause mortality risks associated with tea consumption in different subgroups. Cumulative hazard curve was fitted according to the adjusted cox regression results in model 2 to intuitively show the effect of tea consumption in different subgroups. We further stratified the analysis according to age, sex, race/ethnicity, BMI, IPR, education, smoking, alcohol, high cholesterol, diabetes, hypertension, and cancer. To assess the joint effects of physical activity (PA) and tea consumption, we constructed a combined model. Both tea consumption and exercise levels were categorized into three groups each, resulting in nine combinations when paired. Using the non-tea consumption and non-exercise group as reference, we examined the HR and 95% CIs for all-cause mortality in the remaining eight groups of patients. Finally, we conducted a binary classification of tea consumption based on whether tea was consumed to analyze its impact on cancer-specific mortality. Initially, we employed Cox regression analysis to investigate whether tea consumption alone could reduce cancer-specific mortality rates. Subsequently, we conducted a stratified analysis based on physical activity levels and plotted Kaplan-Meier survival curves for both groups. Finally, we conducted Cox regression analysis to examine the influence of tea consumption on cancer-specific mortality rates in two groups distinguished by their level of physical activity. All statistical analyses were performed using Empower Stats software version 4.1 ( 21 ). Two-sided P values < 0.05 were considered statistically significant in our study. Result Population Characteristics Of the 21,350 eligible adults in the current analysis, 1,575 deaths were observed over an average follow-up period of 74.9 months. Among the participants, 61.2% were physically active, and the average tea consumption was 173.03g and 166.69g for the active and inactive groups, respectively. There was no significant difference in tea consumption between the two groups ( P = 0.241). Significant differences were observed between the two groups in terms of age, sex, race, BMI, IPR, education, smoking, alcohol use, diabetes, hypertension, and cancer, but not in high cholesterol ( P = 0.931). Table 1 presents the full demographic characteristics by physical activity. Table 1 Sociodemographic, habit and health condition of the study participants, according to physical activity. Physical activity Inactive Active P -value Number of participants 8287 13063 Tea, g 166.69 ± 367.96 173.03 ± 394.84 0.241 All-cause mortality Survivors 7318 (88.31%) 12457 (95.36%) < 0.001 Deaths 969 (11.69%) 606 (4.64%) Cancer-specific death Survivors 8085 (97.56%) 12886 (98.65%) < 0.001 Deaths 202 (2.44%) 177 (1.35%) Age (years), % < 0.001 20<=, < 40 1875 (22.63%) 5256 (40.24%) 40<=, < 60 2734 (32.99%) 4462 (34.16%) 60<= 3678 (44.38%) 3345 (25.61%) Sex, % < 0.001 Male 3336 (40.26%) 7134 (54.61%) Female 4951 (59.74%) 5929 (45.39%) Race/ethnicity, % < 0.001 Hispanic 2111 (25.47%) 3033 (23.22%) Non-Hispanic White 3392 (40.93%) 5716 (43.76%) Non-Hispanic African American 1766 (21.31%) 2598 (19.89%) Other Race - Including Multi-Racial 1018 (12.28%) 1716 (13.14%) BMI, % < 0.001 Normal 2017 (24.34%) 3990 (30.54%) Overweight 2615 (31.56%) 4297 (32.89%) Obesity 3655 (44.11%) 4776 (36.56%) IPR, % < 0.001 Low 1956 (23.60%) 2671 (20.45%) Medium 4517 (54.51%) 6781 (51.91%) High 1814 (21.89%) 3611 (27.64%) Education, % < 0.001 High school 4098 (49.45%) 7806 (59.76%) Smoke, % < 0.001 Nonsmokers 4568 (55.12%) 7347 (56.24%) Former smokers 2162 (26.09%) 3030 (23.20%) Current smokers 1557 (18.79%) 2686 (20.56%) Alcohol, % < 0.001 No 6455 (77.89%) 8772 (67.15%) Yes 1832 (22.11%) 4291 (32.85%) High cholesterol, % 0.931 No 7594 (91.64%) 11975 (91.67%) Yes 693 (8.36%) 1088 (8.33%) Diabetes, % < 0.001 No 6410 (77.35%) 11440 (87.58%) Yes 1877 (22.65%) 1623 (12.42%) Hypertension, % < 0.001 No 4526 (54.62%) 9019 (69.04%) Yes 3761 (45.38%) 4044 (30.96%) Cancer, % < 0.001 No 7314 (88.26%) 11977 (91.69%) Yes 973 (11.74%) 1086 (8.31%) Notes: BMI body mass index; IPR income-to-poverty ratio; continuous variables are expressed as mean ± standard deviation; categorical variables are expressed as case numbers (proportions) Association of tea consumption (per 100g), physical activity and all-cause mortality We used proportional hazards models to investigate the associations between tea consumption, PA, and all-cause mortality, Table 2 . After adjusting for age, sex, race, BMI, IPR, education, smoking, alcohol use, high cholesterol, diabetes, hypertension, and cancer, we found that both tea consumption and physical activity were independently associated with reduced all-cause mortality, with HR of 0.980 (95% CI: 0.966, 0.994) and 0.595 (95% CI: 0.535, 0.661). Additionally, Fig. 2 illustrates the log (HR) fitting curve alongside the predicted curve for median time survival probability at 71 months, also adjusted for the aforementioned factors. To investigate the effect of tea consumption on people with different physical activity levels, we stratified the analysis by physical activity status and found that the effect was not significant in the inactive group ( P = 0.2047) but significant in the active group ( P = 0.0107). To investigate the effects of tea consumption and PA in different populations, we performed stratified analyses (Fig. 3 ). In the inactive group, tea consumption (per 100g) significantly reduced all-cause mortality only among those with hypertension, with HR of 0.975 (95% CI: 0.952, 0.999). However, in the active group, it significantly reduced all-cause mortality among a larger number of people. Specifically, in the physically active group, tea consumption significantly reduced all-cause mortality in people who were older than 60 (HR: 0.916, 95% CI: 0.858, 0.980), male (HR: 0.938, 95% CI: 0.885, 0.995), non-Hispanic white (HR: 0.939, 95% CI: 0.888, 0.994), and other racial groups (HR: 0.686, 95% CI: 0.497, 0.967). Additionally, we found that in the physically active group, tea consumption tended to have significant implications for people with healthier lifestyles, including those with normal BMI (HR: 0.882, 95% CI: 0.793, 0.983), non-smokers (HR: 0.917, 95% CI: 0.853, 0.999) or former smokers (HR: 0.895, 95% CI: 0.808, 0.986), and non-drinkers (HR: 0.938, 95% CI: 0.888, 0.991). In terms of disease, we found that tea consumption in the active group was significant for people who did not have high cholesterol (HR: 0.932, 95% CI: 0.883, 0.985), diabetes (HR: 0.940, 95% CI: 0.887, 0.994), or cancer (HR: 0.942, 95% CI: 0.893, 0.996). However, for those with hypertension, tea consumption was associated with a significant reduction in all-cause mortality in both groups. Furthermore, it is noteworthy that tea consumption increased all-cause mortality in people aged 20 to 40 years, regardless of whether they were physically active (HR: 1.009, 95% CI: 1.006, 1.088) or not (HR: 1.032, 95% CI: 1.006, 1.153). Table 2 Hazard ratios (95% CI) of all-cause mortality according to tea consumption (per 100g) and physical activity. Exposure Non-adjusted Model I Model II Tea, 100g 0.986 (0.972, 1.000) 0.0517 0.975 (0.960, 0.990) 0.0012 0.980 (0.966, 0.994) 0.0052 Physical activity a Inactive 1.0 1.0 1.0 Active 0.386 (0.349, 0.427) < 0.0001 0.522 (0.470, 0.579) < 0.0001 0.595 (0.535, 0.661) < 0.0001 Physical activity b Inactive 0.990 (0.972, 1.009) 0.3097 0.980 (0.961, 0.999) 0.0413 0.988 (0.970, 1.007) 0.2047 Active 0.980 (0.957, 1.004) 0.1009 0.969 (0.945, 0.993) 0.0125 0.969 (0.947, 0.993) 0.0107 Notes: Model 1: adjusted for age, sex, race. Model 2: adjusted for age, sex, race, BMI, IPR, education, smoke, alcohol, high cholesterol, diabetes, hypertension, and cancer. Values shown as coefficients and 95% CI. a The independent effect of exercise on all-cause mortality rate. b The effect of tea consumption (per 100g) on all-cause mortality, stratified by PA. Association of tea consumption (categorical variable), physical activity and all-cause mortality We categorized tea consumption into three groups: none (0g), low ( = 300g). We first investigated the effect of tea consumption on all-cause mortality separately and found that in the low group, tea consumption did not significantly reduce all-cause mortality, while in the high group, tea consumption did, with HR of 0.80 (95% CI: 0.70, 0.92), Table 3 . When stratified by physical activity and adjusting for potential confounding factors, tea consumption showed no significant effect on all-cause mortality in the inactive group (P = 0.0572), while in the active group, high tea consumption was associated with a significant reduction in all-cause mortality, with HR of 0.75 (95% CI: 0.60, 0.94), Table 3 . We plotted the cumulative hazard curves for stratified analyses in Fig. 4 . Table 3 Hazard ratios (95% CI) of all-cause mortality according to tea consumption (categorical variable) and physical activity. Exposure Non-adjusted Model I Model II Tea None 1.0 1.0 1.0 Low 1.00 (0.87, 1.14) 0.9638 0.90 (0.78, 1.03) 0.1179 0.95 (0.83, 1.09) 0.4992 High 0.83 (0.72, 0.95) 0.0057 0.75 (0.65, 0.85) < 0.0001 0.80 (0.70, 0.92) 0.0020 Inactive a None 1.0 1.0 1.0 Low 0.91 (0.76, 1.09) 0.2963 0.85 (0.71, 1.02) 0.0728 0.89 (0.75, 1.07) 0.2165 High 0.85 (0.71, 1.01) 0.0613 0.77 (0.64, 0.91) 0.0026 0.84 (0.71, 1.01) 0.0572 Active a None 1.0 1.0 1.0 Low 1.11 (0.90, 1.38) 0.3154 1.01 (0.81, 1.25) 0.9469 1.06 (0.86, 1.32) 0.5879 High 0.80 (0.64, 1.00) 0.0536 0.73 (0.58, 0.91) 0.0049 0.75 (0.60, 0.94) 0.0119 Notes: Model 1: adjusted for age, sex, race. Model 2: adjusted for age, sex, race, BMI, IPR, education, smoke, alcohol, high cholesterol, diabetes, hypertension, and cancer. Values shown as coefficients and 95% confidence intervals (95% CI). a The effect of tea consumption on all-cause mortality, stratified by PA. We further divided physical activity into three groups based on MET scores: low (MET scores < 600), medium (600 < = MET scores < 3000), and high (3000 < = MET scores), Supplementary table 1 . After adjusting for age, sex, race, BMI, IPR, education, smoking, alcohol, high cholesterol, diabetes, hypertension, and cancer, and using no tea consumption and low MET scores as the reference group, we found that tea consumption had no significant effect on all-cause mortality in the low MET group. In the medium MET group, the high tea group had the lowest risk (HR = 0.45), while in the high MET group, the risk decreased with increasing tea consumption (HR = 0.48, HR = 0.45, HR = 0.43). Figure 5 shows the relationship between all-cause mortality and different groups in the form of a heat map. Association of tea consumption (tea or non-tea), physical activity and cancer-specific mortality According to the results in Table 4 , the consumption of tea alone does not have a significant impact on reducing cancer-specific mortality (P = 0.11). However, after stratifying the analysis based on physical activity levels, we found that in the active group, tea consumption can significantly reduce cancer-specific mortality (HR = 0.640, 95% CI: 0.421–0.973). In contrast, the difference in mortality rates between tea consumers and non-consumers in the inactive group is minimal. Figure 6 illustrates the survival curves for these two groups. Table 4 Hazard ratios (95% CI) of cancer-specific mortality according to tea consumption and physical activity. NHANES, 2009–2018. Non-adjusted Adjust I Adjust II Total Non-Tea Drinkers 1 1 1 Tea Drinkers 0.859 (0.657, 1.124) 0.2681 0.782 (0.597, 1.024) 0.0738 0.801 (0.610, 1.051) 0.1086 Inactive Non-Tea Drinkers 1 1 1 Tea Drinkers 0.999 (0.702, 1.422) 0.9949 0.904 (0.634, 1.289) 0.5768 0.948 (0.663, 1.358) 0.7723 Active Non-Tea Drinkers 1 1 1 Tea Drinkers 0.711 (0.469, 1.078) 0.1079 0.652 (0.429, 0.990) 0.0445 0.640 (0.421, 0.973) 0.0370 Notes: Model 1: adjusted for age, sex, race. Model 2: adjusted for age, sex, race, BMI, IPR, education, smoke, alcohol, high cholesterol, diabetes and hypertension. Values shown as coefficients and 95% confidence intervals (95%CI). Discussion We used data from the NHANES and NDI databases from 2009 through 2018 and combined them to examine the relationship between tea consumption, PA, and all-cause mortality. We identified tea drinks based on the food/beverage category given by WWEIA and calculated each person's weekly met score based on the recommended met score given by NHANES. According to our study, in addition to the health benefits of PA and tea consumption, adding adequate tea consumption to PA has further health benefits. We first examined the effects of PA and tea consumption on all-cause mortality. Consistent with previous studies, both PA and tea consumption reduced all-cause mortality, which may be related to their cardiovascular, cancer, diabetes, and respiratory benefits ( 22 – 27 ). On this basis, we examined the effects of tea consumption separately in people with different PA status and found that after adjustment, tea consumption did not appear to have a significant effect on all-cause mortality in the inactive group, while it did in the active group. This seems to suggest that PA plays an important role in the health benefits of green tea. Although most studies have focused on the role of tea drinking in ameliorating oxidative stress caused by PA and there is a lack of research on the effect of PA on tea, in the study of Arabzadeh et al., it was found that markers (HIF-1α, BNIP3, and IGFBP3) of cardiomyocyte apoptosis in aging rats were lower in the group using green tea extract combined with PA compared with the use of green tea extract alone( 28 ). Afterward, we conducted stratified analysis and found that the health benefits of tea consumption were more significant in the physically active group. Tea consumption showed a significant effect in 12 subgroups out of 10 strata analyzed in the physically active group, while in the physically inactive group, it only significantly reduced all-cause mortality in the subgroup with hypertension, which is in keeping with the previous analysis. However, it is worth noting that among those aged 20 to 40, tea consumption actually increased all-cause mortality. In the study by Wu et al., it was found that bubble tea consumption was associated with an increased risk of experiencing symptoms of depression and anxiety in Chinese young adults, which reminds us to pay attention to the effects of tea beverages on the mental health of young people ( 29 ). Siener et al. conducted experiments on ten men between the ages of 20 and 31 and found that the consumption of 1.5 L/day of black tea resulted in a significant increase in urinary citrate excretion by 21% over the 24-h urine collection period, which is an important inhibitor of calcium stone formation ( 30 ). Whereas in the study by Rodak et al., the substances contained in caffeinated coffee decrease the level of prolactin, which is an important hormone for women with more than 300 described functions, including regulation of reproductive function, the immune system, osmotic balance, and angiogenesis ( 31 ). This also suggests us that we should do more research on the caffeine contained in tea. Fortunately, PA still showed health benefits, with lower all-cause mortality in the physically active group than in the inactive group between ages 20 and 40. In the joint effect model, compared with the inactive and non-tea drinking group, the high tea group had the lowest HR in all three PA groups. Although the result was not statistically significant in the low met group, consistent with previous analyses, it still reflected the trend of tea consumption in reducing all-cause mortality. Although high tea consumption was associated with the lowest HR in the medium met group, low tea consumption was associated with increased HR compared with no tea consumption. However, HR tended to decrease with increasing tea consumption in the high tea group, which further suggests that adequate PA may play an integral role in the beneficial effects of tea consumption. Annabella Braschi et al. had similar findings in their study of tea catechin (TC), a beneficial substance found in tea ( 32 ), exercise, and sarcopenia. leg muscle mass and usual walking speed were not improved or even decreased in the TC intake group, but were significantly improved in the exercise group and further improved in the exercise plus TC group ( 33 ). Further health benefits of tea consumption may be explained by oxidative stress (Supplement Fig. 2 ). Muscular contraction has been shown to generate several reactive radicals, such as superoxide, hydrogen peroxide, nitric oxide, and hydroxyl radicals, while unscavenged oxidants can modify macromolecules in the cell including nucleic acids, proteins, and lipids ( 14 ). This oxidation of cellular components (oxidative stress) can occur when an imbalance exists between oxidants and antioxidants ( 14 ). In general, the body can neutralize exercise-induced oxidative stress through antioxidant defense, and long-term exercise can also enhance this ability ( 14 ), but this defense may be overwhelmed by exercise-induced ROS production ( 11 ). Green tea has obvious antioxidant activity, especially green tea catechins can fight oxidative stress through direct or indirect pathways in the body, thereby protecting the body from oxidative damage( 11 ), which may reduce the possible negative effects of exercise to a certain extent, so as to further improve health. This study has several shortcomings. First, tea consumption was determined by only two dietary questionnaires, which is uncertain for determining whether a person is a habitual tea drink. Secondly, there is a lack of mechanistic studies on the interaction between tea drinking and PA, which is worthy of further investigation in our present study. Therefore, further randomized controlled trials are needed to determine the associations between tea consumption, PA and all-cause mortality as well as cancer-specific mortality, and further animal studies are needed to determine the interaction between tea consumption and PA. Conclusion In this study, we investigated the associations between tea consumption, PA, and all-cause mortality. Our findings showed that both tea consumption and PA were independently associated with a reduced risk of all-cause mortality. Moreover, we found that tea consumption further reduced all-cause mortality in the physically active group. These results highlight the potential benefits of regular tea consumption and PA in promoting longevity and reducing the risk of premature death Abbreviations PA: physical activity NHANES: The National Health and Nutrition Examination Survey HR: hazard ratios CI 95%: confidence intervals IPR: income-to-poverty ratio BMI: body mass index Declarations Ethics approval and consent to participate Our analysis used publicly available NHANES data. No new data were collected, and no new ethical approval was required. Consent for publication Not applicable Availability of data and material Publicly available datasets are available at https://www.cdc.gov/nchs/nhanes/ Competing interests The authors declare that they have no competing interests. Funding the Third Xiangya Hospital of Central South University's Wisdom Accumulation and Talent Cultivation Project (YX202209). Authors' contributions Y.H., L.Y. and J.H. wrote the main manuscript text and Y.H. prepared all figures. All authors reviewed the manuscript. Acknowledgements We appreciate the DAGitty (http://www.dagitty.net/) providing the tools to draw the Supplement Fig.1. References B. Blumberg J, W. Bolling B, Chen CYO, Xiao H. Review and Perspective on the Composition and Safety of Green Tea Extracts. European Journal of Nutrition & Food Safety. 2014;5(1):1–31. Mak JC. Potential role of green tea catechins in various disease therapies: Progress and promise. 2012;39(3):265–73. Dinh TC, Thi Phuong TN, Minh LB, Minh Thuc VT, Bac ND, Van Tien N, et al. The effects of green tea on lipid metabolism and its potential applications for obesity and related metabolic disorders - An existing update. Diabetes & Metabolic Syndrome: Clinical Research & Reviews. 2019;13(2):1667-73. Crespy V, Williamson G. A Review of the Health Effects of Green Tea Catechins in In Vivo Animal Models. The Journal of Nutrition. 2004;134(12):S3431-S40. Pervin M, Unno K, Takagaki A, Isemura M, Nakamura Y. Function of Green Tea Catechins in the Brain: Epigallocatechin Gallate and its Metabolites. 2019;20(15):3630. Xiao X, Tang C, Zhai X, Li S, Ma W, Liu K, et al. Early-Adulthood Weight Change and Later Physical Activity in Relation to Cardiovascular and All-Cause Mortality: NHANES 1999–2014. Nutrients. 2022;14(23). Pojednic R, D'Arpino E, Halliday I, Bantham A. The Benefits of Physical Activity for People with Obesity, Independent of Weight Loss: A Systematic Review. Int J Environ Res Public Health. 2022;19(9). Weiss EP, Albert SG, Reeds DN, Kress KS, McDaniel JL, Klein S, et al. Effects of matched weight loss from calorie restriction, exercise, or both on cardiovascular disease risk factors: a randomized intervention trial. The American journal of clinical nutrition. 2016;104(3):576–86. Powers SK, Jackson MJ. Exercise-induced oxidative stress: cellular mechanisms and impact on muscle force production. Physiological reviews. 2008;88(4):1243–76. Powers SK, Deminice R, Ozdemir M, Yoshihara T, Bomkamp MP, Hyatt H. Exercise-induced oxidative stress: Friend or foe? Journal of sport and health science. 2020;9(5):415–25. Nobari H, Saedmocheshi S, Chung LH, Suzuki K, Maynar-Mariño M, Pérez-Gómez J. An Overview on How Exercise with Green Tea Consumption Can Prevent the Production of Reactive Oxygen Species and Improve Sports Performance. Int J Environ Res Public Health. 2021;19(1). Knez WL, Coombes JS, Jenkins DG. Ultra-endurance exercise and oxidative damage: implications for cardiovascular health. Sports medicine (Auckland, NZ). 2006;36(5):429–41. König D, Wagner KH, Elmadfa I, Berg A. Exercise and oxidative stress: significance of antioxidants with reference to inflammatory, muscular, and systemic stress. Exercise immunology review. 2001;7:108–33. POWERS SK, JI LL, LEEUWENBURGH C. Exercise training-induced alterations in skeletal muscle antioxidant capacity: a brief review. 1999;31(7):987–97. Orlando P, Silvestri S, Galeazzi R, Antonicelli R, Marcheggiani F, Cirilli I, et al. Effect of ubiquinol supplementation on biochemical and oxidative stress indexes after intense exercise in young athletes. Redox report: communications in free radical research. 2018;23(1):136–45. Jacob RA, Burri BJ. Oxidative damage and defense. The American journal of clinical nutrition. 1996;63(6):985s-90s. Sureda A, Tejada S, Bibiloni Mdel M, Tur JA, Pons A. Polyphenols: well beyond the antioxidant capacity: polyphenol supplementation and exercise-induced oxidative stress and inflammation. Current pharmaceutical biotechnology. 2014;15(4):373–9. Gay IC, Tran DT, Paquette DW. Alcohol intake and periodontitis in adults aged >/=30 years: NHANES 2009–2012. J Periodontol. 2018;89(6):625–34. He S, Ryan KA, Streeten EA, McArdle PF, Daue M, Trubiano D, et al. Prevalence, control, and treatment of diabetes, hypertension, and high cholesterol in the Amish. BMJ Open Diabetes Res Care. 2020;8(1). Cai XY, Zhang NH, Cheng YC, Ge SW, Xu G. Sugar-sweetened beverage consumption and mortality of chronic kidney disease: results from the US National Health and Nutrition Examination Survey, 1999–2014. Clin Kidney J. 2022;15(4):718–26. Lin L, Chen CZ, Yu XD. [The analysis of threshold effect using Empower Stats software]. Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi. 2013;34(11):1139–41. Byberg L, Melhus H, Gedeborg R, Sundström J, Ahlbom A, Zethelius B, et al. Total mortality after changes in leisure time physical activity in 50 year old men: 35 year follow-up of population based cohort. BMJ (Clinical research ed). 2009;338:b688. Schnohr P, O'Keefe JH, Lange P, Jensen GB, Marott JL. Impact of persistence and non-persistence in leisure time physical activity on coronary heart disease and all-cause mortality: The Copenhagen City Heart Study. European journal of preventive cardiology. 2017;24(15):1615–23. Blond K, Brinkløv CF, Ried-Larsen M, Crippa A, Grøntved A. Association of high amounts of physical activity with mortality risk: a systematic review and meta-analysis. British journal of sports medicine. 2020;54(20):1195–201. Chen Y, Zhang Y, Zhang M, Yang H, Wang Y. Consumption of coffee and tea with all-cause and cause-specific mortality: a prospective cohort study. BMC medicine. 2022;20(1):449. Nie J, Chen L, Yu CQ, Guo Y, Pei P, Chen JS, et al. [Association between tea consumption and all-cause mortality in Chinese adults]. Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi. 2022;43(2):145–53. Saito E, Inoue M, Sawada N, Shimazu T, Yamaji T, Iwasaki M, et al. Association of green tea consumption with mortality due to all causes and major causes of death in a Japanese population: the Japan Public Health Center-based Prospective Study (JPHC Study). Annals of epidemiology. 2015;25(7):512-8.e3. Arabzadeh E, Norouzi Kamareh M, Ramirez-Campillo R, Mirnejad R, Masti Y, Shirvani H. Twelve weeks of treadmill exercise training with green tea extract reduces myocardial oxidative stress and alleviates cardiomyocyte apoptosis in aging rat: The emerging role of BNIP3 and HIF-1α/IGFBP3 pathway. Journal of food biochemistry. 2022;46(12):e14397. Wu Y, Lu Y, Xie G. Bubble tea consumption and its association with mental health symptoms: An observational cross-sectional study on Chinese young adults. Journal of affective disorders. 2022;299:620–7. Siener R, Hesse A. Effect of Black Tea Consumption on Urinary Risk Factors for Kidney Stone Formation. Nutrients. 2021;13(12). Rodak K, Kokot I, Kryla A, Kratz EM. The Examination of the Influence of Caffeinated Coffee Consumption on the Concentrations of Serum Prolactin and Selected Parameters of the Oxidative-Antioxidant Balance in Young Adults: A Preliminary Report. Oxidative medicine and cellular longevity. 2022;2022:1735204. Tokuda Y, Mori H. Essential Amino Acid and Tea Catechin Supplementation after Resistance Exercise Improves Skeletal Muscle Mass in Older Adults with Sarcopenia: An Open-Label, Pilot, Randomized Controlled Trial. Journal of the American Nutrition Association. 2023;42(3):255–62. Kim H, Suzuki T, Saito K, Yoshida H, Kojima N, Kim M, et al. Effects of exercise and tea catechins on muscle mass, strength and walking ability in community-dwelling elderly Japanese sarcopenic women: a randomized controlled trial. Geriatrics & gerontology international. 2013;13(2):458–65. Additional Declarations No competing interests reported. Supplementary Files SupplementFig.1.Directedacyclicgraphs.tif SupplementFig.2.Furtherhealthbenefitsofteaconsumption.tif SupplementFig.docx Supplementarytable1.docx Cite Share Download PDF Status: Published Journal Publication published 09 Oct, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 16 Jul, 2024 Reviews received at journal 04 Jul, 2024 Reviewers agreed at journal 26 Jun, 2024 Reviews received at journal 22 Jun, 2024 Reviewers agreed at journal 21 Jun, 2024 Reviewers agreed at journal 12 Jun, 2024 Reviewers invited by journal 12 Jun, 2024 Editor assigned by journal 12 Jun, 2024 Editor invited by journal 12 Jun, 2024 Submission checks completed at journal 10 Jun, 2024 First submitted to journal 08 Jun, 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4552199","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":317985973,"identity":"25ec40e0-b35f-4f5d-ad0c-e046fa49d031","order_by":0,"name":"Yiqun Hu","email":"","orcid":"","institution":"the Third Xiangya Hospital of Central South University","correspondingAuthor":false,"prefix":"","firstName":"Yiqun","middleName":"","lastName":"Hu","suffix":""},{"id":317985974,"identity":"60761f00-f90b-4cc2-bdc9-4d12f5b54242","order_by":1,"name":"Luning Yang","email":"","orcid":"","institution":"the Third Xiangya Hospital of Central South University","correspondingAuthor":false,"prefix":"","firstName":"Luning","middleName":"","lastName":"Yang","suffix":""},{"id":317985975,"identity":"fc0285b3-4d51-46ff-b308-5ef644c122cb","order_by":2,"name":"Jinshen He","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIiWNgGAWjYBACxmYGBmYQw4CB+RhYhI2deC1saQwMCUAtzETYBNXCYwbWwkBIC3M77+HPBRV3GMzZe749+PhjmzwfMwPjh485+BzGlyY948wzBsues9sNZyTcNmxjZmCWnLkNnxYeM2betsMMBjdyt0nzJNxmBGphY+bFr8X4M+8/oJb7b56BtNgTo8VAmrcBZAsPG0hLIjFazKR5jh3mMTiTZiY5I+12chszYzNevxj2nzH+zFNzWM7g+OFnEh9sbtvOb28++OEjPi0NEJoH2eYG3OqBQB6v7CgYBaNgFIwCEAAAxTxIohOMUFIAAAAASUVORK5CYII=","orcid":"","institution":"the Third Xiangya Hospital of Central South University","correspondingAuthor":true,"prefix":"","firstName":"Jinshen","middleName":"","lastName":"He","suffix":""}],"badges":[],"createdAt":"2024-06-09 02:23:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4552199/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4552199/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-73962-z","type":"published","date":"2024-10-09T15:57:02+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":59523895,"identity":"bcb2f4db-fd74-4520-8ed2-50648857dcc5","added_by":"auto","created_at":"2024-07-02 20:42:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":208049,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the sample selection from NHANES 2009-2018\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-4552199/v1/09cfe942d2bae9cba6550898.png"},{"id":59523897,"identity":"7878188f-f691-44ad-a8fe-1889876f6f18","added_by":"auto","created_at":"2024-07-02 20:42:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":74175,"visible":true,"origin":"","legend":"\u003cp\u003eThe log (HR) fitting curve and the predicted curve for median time (71 month) survival probability. Adjusted for age, sex, race, BMI, IPR, education, smoke, alcohol, high cholesterol, diabetes, hypertension.\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-4552199/v1/dc3c2055b0a5ddfef9347690.png"},{"id":59525100,"identity":"bd859840-ec52-47f4-9279-798984c26630","added_by":"auto","created_at":"2024-07-02 20:50:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":912789,"visible":true,"origin":"","legend":"\u003cp\u003eAssociations between tea consumption (per 100g) and all-cause mortality in different PA groups, stratified by age, sex, race, BMI, smoke, alcohol, high cholesterol, diabetes, hypertension and cancer. HR were adjusted for age (not adjusted in subgroup analysis by age), sex (not adjusted in subgroup analysis by sex), race (not adjusted in subgroup analysis by race), BMI (not adjusted in subgroup analysis by BMI), IPR, education, smoke (not adjusted in subgroup analysis by smoke), alcohol (not adjusted in subgroup analysis by alcohol), high cholesterol (not adjusted in subgroup analysis by high cholesterol), diabetes (not adjusted in subgroup analysis by diabetes), hypertension (not adjusted in subgroup analysis by hypertension), and cancer (not adjusted in subgroup analysis by cancer).\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-4552199/v1/85846b6d5e39d97d2f3fa5eb.png"},{"id":59525099,"identity":"6de25b0f-f6d3-4d92-850f-8ec61326be8b","added_by":"auto","created_at":"2024-07-02 20:50:35","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":116599,"visible":true,"origin":"","legend":"\u003cp\u003eCumulative risk curves for different tea consumption, stratified according to active physical activity\u003c/p\u003e","description":"","filename":"Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-4552199/v1/4ddb27a5146599e892cb248d.png"},{"id":59523900,"identity":"cde52fc6-a28a-41d2-b4f0-7762536de34c","added_by":"auto","created_at":"2024-07-02 20:42:35","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":67460,"visible":true,"origin":"","legend":"\u003cp\u003eHeat map based on HR values in Supplementary table 1.\u003c/p\u003e","description":"","filename":"Fig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-4552199/v1/2f973b6cf944f6ce49ba2010.png"},{"id":59523901,"identity":"9f795886-93c7-4d47-b03c-aa9dddda0e69","added_by":"auto","created_at":"2024-07-02 20:42:35","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":56058,"visible":true,"origin":"","legend":"\u003cp\u003eCancer-specific survival curves for different levels of tea consumption, stratified by physical activity level.\u003c/p\u003e","description":"","filename":"Fig.6.png","url":"https://assets-eu.researchsquare.com/files/rs-4552199/v1/1c9be48b5e32caa5f41a1504.png"},{"id":66597047,"identity":"95afe0f3-15b4-48a0-b934-7b6719cbdf19","added_by":"auto","created_at":"2024-10-14 16:05:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2401907,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4552199/v1/d0dc3a97-fe2c-42b6-81ea-43d7571ca1a8.pdf"},{"id":59523905,"identity":"8ede74d7-c023-41db-91eb-9f4b6bada28e","added_by":"auto","created_at":"2024-07-02 20:42:36","extension":"tif","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":51535228,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementFig.1.Directedacyclicgraphs.tif","url":"https://assets-eu.researchsquare.com/files/rs-4552199/v1/00b5054ccd6518cf2cceb9b1.tif"},{"id":59523904,"identity":"0acd2751-d6f1-4c9c-bbec-5c8ddb237f2f","added_by":"auto","created_at":"2024-07-02 20:42:36","extension":"tif","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":13616808,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementFig.2.Furtherhealthbenefitsofteaconsumption.tif","url":"https://assets-eu.researchsquare.com/files/rs-4552199/v1/ad40dc084bcfbaa3ec4bdbf1.tif"},{"id":59523902,"identity":"ecba2671-8271-41af-af0d-8e152abadb8a","added_by":"auto","created_at":"2024-07-02 20:42:35","extension":"docx","order_by":14,"title":"","display":"","copyAsset":false,"role":"supplement","size":441403,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementFig.docx","url":"https://assets-eu.researchsquare.com/files/rs-4552199/v1/c7c3014bc1e0993ca9934aeb.docx"},{"id":59523903,"identity":"a77a832a-42d4-4168-bf02-57f52d64869d","added_by":"auto","created_at":"2024-07-02 20:42:35","extension":"docx","order_by":15,"title":"","display":"","copyAsset":false,"role":"supplement","size":11315,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4552199/v1/f85f262a03f449334d11f1c3.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Physical Activity Combined with Tea Consumption could further Reduce All-cause Mortality: Results from the US National Health and Nutrition Examination Survey, 2009-2018","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNowadays, tea is widely consumed and has become the second most popular beverage after water (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The global average consumption of tea is about 0.5 kg per capita, though amounts (in kg per capita) are greater where tea drinking is common such as India (0.73), China (0.95), Japan (0.96), Ireland (1.90), United Kingdom (1.97), Turkey (2.04), and Libya (1.90) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The relationship between tea and health has become an increasingly important topic. It is widely believed that tea may protect against death from all causes (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Available evidence shows that tea can interrupt lipid emulsification, reduce adipocyte differentiation, increase thermogenesis, and reduce food intake, thus tea improves systemic metabolism and decreases fat mass (\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePA has long been widely recognized for its health benefits. People who perform physical activity above the recommended level according to the current public health guidelines were associated with lower morbidity and mortality (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Physical activity can potentially increase telomere length, enhance anti-oxidative and anti-thrombotic enzymes (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), and improve cardiovascular health by reducing risk factors like in individuals with obesity (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). At the same time, research has observed that PA may lead to an increase in the production of free radicals, potentially causing oxidative damage (\u003cspan additionalcitationids=\"CR10 CR11 CR12 CR13\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Dietary antioxidants may help protect cells from oxidative damage (\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), so tea, as a recognized antioxidant beverage, may further enhance the health benefits of PA (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, although there is a lot of evidence for the health benefits of PA and tea consumption, there is a lack of direct evidence on whether PA and tea consumption can further have better effects on our health when they are carried out together. In this study, we used logistic regression to analyze the effect of tea consumption on all-cause mortality in different PA subgroups. We also constructed a joint model of PA and tea consumption to explore the combined effects of them on health status. It was hypothesized that tea consumption combined with PA could more effectively reduce all-cause mortality and cancer-specific mortality, which might provide meaningful guidance for conducting more scientifically sound exercise studies.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Population\u003c/h2\u003e \u003cp\u003eThe National Health and Nutrition Examination Survey (NHANES) is a population-based cross-sectional study conducted by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention to assess the health and nutrition status of adults and children in the United States. Participation in the survey is voluntary and will undergo standardized personal interviews and examinations. The NHANES interview includes demographic, socioeconomic, dietary, and health-related questions. The examination component consists of medical, dental, and physiological measurements, as well as laboratory tests administered by highly trained medical personnel. More details of the sampling method and data collection have been published on the web (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.cdc.gov/nchs/nhanes/index.htm\u003c/span\u003e\u003cspan address=\"http://www.cdc.gov/nchs/nhanes/index.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNCHS has linked data from various surveys with death certificate records from the National Death Index (NDI). Linkage of the NCHS survey participant data with the NDI mortality data provides the opportunity to conduct a vast array of outcome studies designed to investigate the association of a wide variety of health factors with mortality.\u003c/p\u003e \u003cp\u003eIn this analysis, we included 49,693 participants from the 2009\u0026ndash;2018 NHANES datasets. Further, we excluded 19,451 participants who were not eligible for linking NDI mortality data to NCHS data. Additionally, we excluded 8,656 participants who had missing covariate-related data and 236 participants who were pregnant at the time of the interview. Ultimately, we included 21,350 participants for data analysis. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eOutcome ascertainment\u003c/h2\u003e \u003cp\u003eFor our research, we obtained the public-use linked mortality files (LMF) spanning the years 2009 to 2018 from NCHS. Vital status was determined using the \"MORTSTAT\" variable within the public-use LMF dataset. Additionally, we calculated the follow-up time by measuring person-months from the date of the initial interview to the date of death or the conclusion of the mortality tracking period (PERMTH_INT). For more comprehensive information regarding the NDI mortality files, please consult the following website: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/nchs/data-linkage/mortality.htm\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/nchs/data-linkage/mortality.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of physical activity\u003c/h2\u003e \u003cp\u003eIn NHANES, PA information was collected by using physical activity questionnaire, which is based on the Global Physical Activity Questionnaire (GPAQ). We use the following questions: 1). How much time do you spend doing vigorous-intensity activities at work on a typical day? 2). How much time do you spend doing moderate-intensity activities at work on a typical day? 3). How much time do you spend walking or bicycling for travel on a typical day? 4). How much time do you spend doing vigorous-intensity sports, fitness or recreational activities on a typical day? 5). How much time do you spend doing moderate-intensity sports, fitness or recreational activities on a typical day? For each type of activity, a suggested metabolic equivalent (MET) score of 8.0, 4.0, 4.0, 8.0, and 4.0 was assigned according to the appendix. We multiplied the suggested MET value of each type of question by the minutes spent on it in a typical week to obtain the MET min per week of each activity and then summed the scores to obtain the weekly total MET score. Additional details are available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/nchs/nhanes/\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/nchs/nhanes/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eAccording to the World Health Organization, adults should engage in physical activity for at least 75 minutes at a vigorous intensity, 150 minutes at a moderate intensity, or an equivalent combination of moderate and vigorous-intensity activity, achieving at least 600 METs per minute in a typical week (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). For our study, we defined those with MET scores less than 600 as the inactive group and those with MET scores greater than 600 as the active group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of tea consumption\u003c/h2\u003e \u003cp\u003eIn NHANES, all participants are eligible for two 24-hour dietary recall interviews to provide diet-related data. The first interview is conducted in person in the Mobile Examination Center, while the second is conducted by telephone 3 to 10 days later. Each food or beverage item that can be reported in What We Eat in America (WWEIA), NHANES is placed in one of several mutually exclusive food categories that group similar items together based on usage and nutrient content (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-human-nutrition-research-center/food-surveys-research-group/\u003c/span\u003e\u003cspan address=\"https://www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-human-nutrition-research-center/food-surveys-research-group/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Based on the food category, we calculated tea consumption by averaging the two days' consumption of beverages belonging to the tea category (using only one day's data if data was missing on the other day). In the classification model, data are segmented based on approximate tertiles of tea consumption, which is categorized into three distinct groups: none, low, and high. 'None' corresponds to a tea consumption of 0g, 'low' is defined as any consumption greater than 0g but less than 300g, and 'high' encompasses consumption exceeding 300g.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eCovariate Assessment\u003c/h2\u003e \u003cp\u003eThe following variables were included in this analysis: age, sex, race/ethnicity, education, income-to-poverty ratio (IPR), body mass index (BMI), alcohol, smoke, diabetes, hypertension, high cholesterol, and cancer. These confounders were evaluated using prior knowledge and descriptive statistics from our cohort through the use of directed acyclic graphs (Supplement Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIPR is a ratio of family income to poverty guidelines, calculated by dividing family income by the poverty guidelines specific to family size, as well as the appropriate year and state (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). We divided IPR into three categories: low (\u0026lt;\u0026thinsp;1), medium (\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) and high (\u0026gt;\u0026thinsp;4).\u003c/p\u003e \u003cp\u003eBMI was calculated as a person's weight in kilograms divided by the square of height in meters. According to WHO\u0026rsquo;s classification, participants were classified as normal weight (18.5\u0026ndash;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e), overweight (25.0\u0026ndash;29.9 kg/m\u003csup\u003e2\u003c/sup\u003e) or obese (\u0026ge;\u0026thinsp;30.0 kg/m\u003csup\u003e2\u003c/sup\u003e) (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSmoking status was based on following questions: 1). \u0026lsquo;{Have you/Has SP} smoked at least 100 cigarettes in {your/his/her} entire life?\u0026rsquo;. 2). \u0026lsquo;{Do you/Does SP} now smoke cigarettes?\u0026rsquo;. We defined the those who answered \u0026lsquo;no\u0026rsquo; in question 1) as \u0026lsquo;nonsmokers\u0026rsquo;, those who answer \u0026lsquo;yes\u0026rsquo; in question 1) and \u0026lsquo;no\u0026rsquo; in question 2) as \u0026lsquo;former smokers\u0026rsquo;, those who answer \u0026lsquo;yes\u0026rsquo; in both question 1) and question 2) as \u0026lsquo;current smokers\u0026rsquo;.\u003c/p\u003e \u003cp\u003eAccording to two 24-hour dietary recall interviews, alcohol use was defined as those who reported alcohol consumption in either interview. Diabetes was defined as self-reported diabetes, or glycol hemoglobin\u0026thinsp;\u0026ge;\u0026thinsp;6.5% or measuring fasting glucose\u0026thinsp;\u0026ge;\u0026thinsp;126 mg/dL (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Hypertension was defined as self-reported hypertension. High cholesterol was defined as the ratio of total cholesterol to HDL of \u0026gt;\u0026thinsp;5.9 (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Cancer was defined as to self-reported cancers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eDescriptive analysis was used to explore the baseline characteristics of the included participants. We stratified them according to active and inactive activity. Means and standard deviations were used for exploring continuous variable (Tea). We first performed the Levene\u0026rsquo;s test on it to confirm homogeneity of variance and then we performed t-test to appraise significance difference between groups. Categorical variables were described as numbers and percentages. Significance difference between groups was appraised by the chi-square test.\u003c/p\u003e \u003cp\u003eIn our study, we used the Reverse Kaplan-Meier method to calculate the follow-up time to account for the occurrence of outcome events that precluded further follow-up. Before proportional hazards regression was performed, the proportional hazards assumption was tested for the variables included in the analysis, and none of the variables were violated. After that, we used Cox proportional hazard regression models to estimate the hazard ratios (HR) and 95% confidence intervals (CI) of all-cause mortality risks associated with PA and tea consumption independently with the following covariates: age, sex and race/ethnicity in model 1; model 1 plus BMI, IPR, education, smoke, alcohol, high cholesterol, diabetes, hypertension, cancer in model 2, and we confirmed reductions in all-cause mortality with both PA and tea consumption independently.\u003c/p\u003e \u003cp\u003eTo investigate the effects of tea consumption in people with different exercise profiles, we divided the population into two subgroups based on whether they were physically active or not. We used cox regression separately to estimate the hazard ratios (HR) and 95% confidence intervals (CI) of all-cause mortality risks associated with tea consumption in different subgroups. Cumulative hazard curve was fitted according to the adjusted cox regression results in model 2 to intuitively show the effect of tea consumption in different subgroups. We further stratified the analysis according to age, sex, race/ethnicity, BMI, IPR, education, smoking, alcohol, high cholesterol, diabetes, hypertension, and cancer.\u003c/p\u003e \u003cp\u003eTo assess the joint effects of physical activity (PA) and tea consumption, we constructed a combined model. Both tea consumption and exercise levels were categorized into three groups each, resulting in nine combinations when paired. Using the non-tea consumption and non-exercise group as reference, we examined the HR and 95% CIs for all-cause mortality in the remaining eight groups of patients.\u003c/p\u003e \u003cp\u003eFinally, we conducted a binary classification of tea consumption based on whether tea was consumed to analyze its impact on cancer-specific mortality. Initially, we employed Cox regression analysis to investigate whether tea consumption alone could reduce cancer-specific mortality rates. Subsequently, we conducted a stratified analysis based on physical activity levels and plotted Kaplan-Meier survival curves for both groups.\u003c/p\u003e \u003cp\u003eFinally, we conducted Cox regression analysis to examine the influence of tea consumption on cancer-specific mortality rates in two groups distinguished by their level of physical activity.\u003c/p\u003e \u003cp\u003eAll statistical analyses were performed using Empower Stats software version 4.1 (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Two-sided \u003cem\u003eP\u003c/em\u003e values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant in our study.\u003c/p\u003e \u003c/div\u003e"},{"header":"Result","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003ePopulation Characteristics\u003c/h2\u003e \u003cp\u003eOf the 21,350 eligible adults in the current analysis, 1,575 deaths were observed over an average follow-up period of 74.9 months. Among the participants, 61.2% were physically active, and the average tea consumption was 173.03g and 166.69g for the active and inactive groups, respectively. There was no significant difference in tea consumption between the two groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.241). Significant differences were observed between the two groups in terms of age, sex, race, BMI, IPR, education, smoking, alcohol use, diabetes, hypertension, and cancer, but not in high cholesterol (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.931). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the full demographic characteristics by physical activity.\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\u003eSociodemographic, habit and health condition of the study participants, according to physical activity.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical activity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\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\u003eNumber of participants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTea, g\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e166.69\u0026thinsp;\u0026plusmn;\u0026thinsp;367.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e173.03\u0026thinsp;\u0026plusmn;\u0026thinsp;394.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.241\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAll-cause mortality\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurvivors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7318 (88.31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12457 (95.36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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\u003eDeaths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e969 (11.69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e606 (4.64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCancer-specific death\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurvivors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8085 (97.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12886 (98.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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\u003eDeaths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e202 (2.44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e177 (1.35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years), %\u003c/b\u003e\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=\"char\" char=\".\" colname=\"c4\"\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\u003e20\u0026lt;=, \u0026lt;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1875 (22.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5256 (40.24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026lt;=, \u0026lt;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2734 (32.99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4462 (34.16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026lt;=\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3678 (44.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3345 (25.61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex, %\u003c/b\u003e\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=\"char\" char=\".\" colname=\"c4\"\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\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3336 (40.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7134 (54.61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003e4951 (59.74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5929 (45.39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace/ethnicity, %\u003c/b\u003e\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=\"char\" char=\".\" colname=\"c4\"\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\u003eHispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2111 (25.47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3033 (23.22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic White\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3392 (40.93%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5716 (43.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic African American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1766 (21.31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2598 (19.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Race - Including Multi-Racial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1018 (12.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1716 (13.14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI, %\u003c/b\u003e\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=\"char\" char=\".\" colname=\"c4\"\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\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017 (24.34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3990 (30.54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2615 (31.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4297 (32.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3655 (44.11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4776 (36.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIPR, %\u003c/b\u003e\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=\"char\" char=\".\" colname=\"c4\"\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\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1956 (23.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2671 (20.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4517 (54.51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6781 (51.91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1814 (21.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3611 (27.64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation, %\u003c/b\u003e\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=\"char\" char=\".\" colname=\"c4\"\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\u003e\u0026lt;High school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2229 (26.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2375 (18.18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e=High school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1960 (23.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2882 (22.06%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;High school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4098 (49.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7806 (59.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoke, %\u003c/b\u003e\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=\"char\" char=\".\" colname=\"c4\"\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\u003eNonsmokers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4568 (55.12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7347 (56.24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFormer smokers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2162 (26.09%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3030 (23.20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent smokers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1557 (18.79%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2686 (20.56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlcohol, %\u003c/b\u003e\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=\"char\" char=\".\" colname=\"c4\"\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\u003e6455 (77.89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8772 (67.15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003e1832 (22.11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4291 (32.85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHigh cholesterol, %\u003c/b\u003e\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=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.931\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\u003e7594 (91.64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11975 (91.67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003e693 (8.36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1088 (8.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes, %\u003c/b\u003e\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=\"char\" char=\".\" colname=\"c4\"\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\u003e6410 (77.35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11440 (87.58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003e1877 (22.65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1623 (12.42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypertension, %\u003c/b\u003e\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=\"char\" char=\".\" colname=\"c4\"\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\u003e4526 (54.62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9019 (69.04%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003e3761 (45.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4044 (30.96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCancer, %\u003c/b\u003e\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=\"char\" char=\".\" colname=\"c4\"\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\u003e7314 (88.26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11977 (91.69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003e973 (11.74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1086 (8.31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNotes: BMI body mass index; IPR income-to-poverty ratio; continuous variables are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation; categorical variables are expressed as case numbers (proportions)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAssociation of tea consumption (per 100g), physical activity and all-cause mortality\u003c/h2\u003e \u003cp\u003eWe used proportional hazards models to investigate the associations between tea consumption, PA, and all-cause mortality, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. After adjusting for age, sex, race, BMI, IPR, education, smoking, alcohol use, high cholesterol, diabetes, hypertension, and cancer, we found that both tea consumption and physical activity were independently associated with reduced all-cause mortality, with HR of 0.980 (95% CI: 0.966, 0.994) and 0.595 (95% CI: 0.535, 0.661). Additionally, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the log (HR) fitting curve alongside the predicted curve for median time survival probability at 71 months, also adjusted for the aforementioned factors.\u003c/p\u003e \u003cp\u003eTo investigate the effect of tea consumption on people with different physical activity levels, we stratified the analysis by physical activity status and found that the effect was not significant in the inactive group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.2047) but significant in the active group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0107).\u003c/p\u003e \u003cp\u003eTo investigate the effects of tea consumption and PA in different populations, we performed stratified analyses (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In the inactive group, tea consumption (per 100g) significantly reduced all-cause mortality only among those with hypertension, with HR of 0.975 (95% CI: 0.952, 0.999). However, in the active group, it significantly reduced all-cause mortality among a larger number of people. Specifically, in the physically active group, tea consumption significantly reduced all-cause mortality in people who were older than 60 (HR: 0.916, 95% CI: 0.858, 0.980), male (HR: 0.938, 95% CI: 0.885, 0.995), non-Hispanic white (HR: 0.939, 95% CI: 0.888, 0.994), and other racial groups (HR: 0.686, 95% CI: 0.497, 0.967). Additionally, we found that in the physically active group, tea consumption tended to have significant implications for people with healthier lifestyles, including those with normal BMI (HR: 0.882, 95% CI: 0.793, 0.983), non-smokers (HR: 0.917, 95% CI: 0.853, 0.999) or former smokers (HR: 0.895, 95% CI: 0.808, 0.986), and non-drinkers (HR: 0.938, 95% CI: 0.888, 0.991). In terms of disease, we found that tea consumption in the active group was significant for people who did not have high cholesterol (HR: 0.932, 95% CI: 0.883, 0.985), diabetes (HR: 0.940, 95% CI: 0.887, 0.994), or cancer (HR: 0.942, 95% CI: 0.893, 0.996). However, for those with hypertension, tea consumption was associated with a significant reduction in all-cause mortality in both groups. Furthermore, it is noteworthy that tea consumption increased all-cause mortality in people aged 20 to 40 years, regardless of whether they were physically active (HR: 1.009, 95% CI: 1.006, 1.088) or not (HR: 1.032, 95% CI: 1.006, 1.153).\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\u003eHazard ratios (95% CI) of all-cause mortality according to tea consumption (per 100g) and physical activity.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExposure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-adjusted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel I\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel II\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTea, 100g\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.986 (0.972, 1.000) 0.0517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.975 (0.960, 0.990) 0.0012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.980 (0.966, 0.994) 0.0052\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical activity\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.386 (0.349, 0.427)\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.522 (0.470, 0.579)\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.595 (0.535, 0.661)\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical activity\u003c/b\u003e \u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.990 (0.972, 1.009) 0.3097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.980 (0.961, 0.999) 0.0413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.988 (0.970, 1.007) 0.2047\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.980 (0.957, 1.004) 0.1009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.969 (0.945, 0.993) 0.0125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.969 (0.947, 0.993) 0.0107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNotes: Model 1: adjusted for age, sex, race. Model 2: adjusted for age, sex, race, BMI, IPR, education, smoke, alcohol, high cholesterol, diabetes, hypertension, and cancer. Values shown as coefficients and 95% CI.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003e The independent effect of exercise on all-cause mortality rate.\u003c/p\u003e \u003cp\u003e \u003csup\u003eb\u003c/sup\u003e The effect of tea consumption (per 100g) on all-cause mortality, stratified by PA.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAssociation of tea consumption (categorical variable), physical activity and all-cause mortality\u003c/h2\u003e \u003cp\u003eWe categorized tea consumption into three groups: none (0g), low (\u0026lt;\u0026thinsp;300g), and high (\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;300g). We first investigated the effect of tea consumption on all-cause mortality separately and found that in the low group, tea consumption did not significantly reduce all-cause mortality, while in the high group, tea consumption did, with HR of 0.80 (95% CI: 0.70, 0.92), Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. When stratified by physical activity and adjusting for potential confounding factors, tea consumption showed no significant effect on all-cause mortality in the inactive group (P\u0026thinsp;=\u0026thinsp;0.0572), while in the active group, high tea consumption was associated with a significant reduction in all-cause mortality, with HR of 0.75 (95% CI: 0.60, 0.94), Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. We plotted the cumulative hazard curves for stratified analyses in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\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\u003eHazard ratios (95% CI) of all-cause mortality according to tea consumption (categorical variable) and physical activity.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExposure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-adjusted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModel I\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel II\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTea\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00 (0.87, 1.14) 0.9638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.90 (0.78, 1.03) 0.1179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.95 (0.83, 1.09) 0.4992\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.83 (0.72, 0.95) 0.0057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.75 (0.65, 0.85)\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.80 (0.70, 0.92) 0.0020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInactive\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.91 (0.76, 1.09) 0.2963\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.85 (0.71, 1.02) 0.0728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.89 (0.75, 1.07) 0.2165\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.85 (0.71, 1.01) 0.0613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.77 (0.64, 0.91) 0.0026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.84 (0.71, 1.01) 0.0572\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eActive\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.11 (0.90, 1.38) 0.3154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.01 (0.81, 1.25) 0.9469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.06 (0.86, 1.32) 0.5879\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.80 (0.64, 1.00) 0.0536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.73 (0.58, 0.91) 0.0049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.75 (0.60, 0.94) 0.0119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNotes: Model 1: adjusted for age, sex, race. Model 2: adjusted for age, sex, race, BMI, IPR, education, smoke, alcohol, high cholesterol, diabetes, hypertension, and cancer. Values shown as coefficients and 95% confidence intervals (95% CI).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003e The effect of tea consumption on all-cause mortality, stratified by PA.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe further divided physical activity into three groups based on MET scores: low (MET scores\u0026thinsp;\u0026lt;\u0026thinsp;600), medium (600\u0026thinsp;\u0026lt;\u0026thinsp;=\u0026thinsp;MET scores\u0026thinsp;\u0026lt;\u0026thinsp;3000), and high (3000\u0026thinsp;\u0026lt;\u0026thinsp;=\u0026thinsp;MET scores), Supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. After adjusting for age, sex, race, BMI, IPR, education, smoking, alcohol, high cholesterol, diabetes, hypertension, and cancer, and using no tea consumption and low MET scores as the reference group, we found that tea consumption had no significant effect on all-cause mortality in the low MET group. In the medium MET group, the high tea group had the lowest risk (HR\u0026thinsp;=\u0026thinsp;0.45), while in the high MET group, the risk decreased with increasing tea consumption (HR\u0026thinsp;=\u0026thinsp;0.48, HR\u0026thinsp;=\u0026thinsp;0.45, HR\u0026thinsp;=\u0026thinsp;0.43). Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the relationship between all-cause mortality and different groups in the form of a heat map.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAssociation of tea consumption (tea or non-tea), physical activity and cancer-specific mortality\u003c/h2\u003e \u003cp\u003eAccording to the results in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the consumption of tea alone does not have a significant impact on reducing cancer-specific mortality (P\u0026thinsp;=\u0026thinsp;0.11). However, after stratifying the analysis based on physical activity levels, we found that in the active group, tea consumption can significantly reduce cancer-specific mortality (HR\u0026thinsp;=\u0026thinsp;0.640, 95% CI: 0.421\u0026ndash;0.973). In contrast, the difference in mortality rates between tea consumers and non-consumers in the inactive group is minimal. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e illustrates the survival curves for these two groups.\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\u003eHazard ratios (95% CI) of cancer-specific mortality according to tea consumption and physical activity. NHANES, 2009\u0026ndash;2018.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-adjusted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdjust I\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjust II\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Tea Drinkers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTea Drinkers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.859 (0.657, 1.124) 0.2681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.782 (0.597, 1.024) 0.0738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.801 (0.610, 1.051) 0.1086\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInactive\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Tea Drinkers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTea Drinkers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.999 (0.702, 1.422) 0.9949\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.904 (0.634, 1.289) 0.5768\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.948 (0.663, 1.358) 0.7723\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eActive\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Tea Drinkers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTea Drinkers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.711 (0.469, 1.078) 0.1079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.652 (0.429, 0.990) 0.0445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.640 (0.421, 0.973) 0.0370\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNotes: Model 1: adjusted for age, sex, race. Model 2: adjusted for age, sex, race, BMI, IPR, education, smoke, alcohol, high cholesterol, diabetes and hypertension. Values shown as coefficients and 95% confidence intervals (95%CI).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe used data from the NHANES and NDI databases from 2009 through 2018 and combined them to examine the relationship between tea consumption, PA, and all-cause mortality. We identified tea drinks based on the food/beverage category given by WWEIA and calculated each person's weekly met score based on the recommended met score given by NHANES. According to our study, in addition to the health benefits of PA and tea consumption, adding adequate tea consumption to PA has further health benefits.\u003c/p\u003e \u003cp\u003eWe first examined the effects of PA and tea consumption on all-cause mortality. Consistent with previous studies, both PA and tea consumption reduced all-cause mortality, which may be related to their cardiovascular, cancer, diabetes, and respiratory benefits (\u003cspan additionalcitationids=\"CR23 CR24 CR25 CR26\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOn this basis, we examined the effects of tea consumption separately in people with different PA status and found that after adjustment, tea consumption did not appear to have a significant effect on all-cause mortality in the inactive group, while it did in the active group. This seems to suggest that PA plays an important role in the health benefits of green tea. Although most studies have focused on the role of tea drinking in ameliorating oxidative stress caused by PA and there is a lack of research on the effect of PA on tea, in the study of Arabzadeh et al., it was found that markers (HIF-1α, BNIP3, and IGFBP3) of cardiomyocyte apoptosis in aging rats were lower in the group using green tea extract combined with PA compared with the use of green tea extract alone(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAfterward, we conducted stratified analysis and found that the health benefits of tea consumption were more significant in the physically active group. Tea consumption showed a significant effect in 12 subgroups out of 10 strata analyzed in the physically active group, while in the physically inactive group, it only significantly reduced all-cause mortality in the subgroup with hypertension, which is in keeping with the previous analysis. However, it is worth noting that among those aged 20 to 40, tea consumption actually increased all-cause mortality. In the study by Wu et al., it was found that bubble tea consumption was associated with an increased risk of experiencing symptoms of depression and anxiety in Chinese young adults, which reminds us to pay attention to the effects of tea beverages on the mental health of young people (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Siener et al. conducted experiments on ten men between the ages of 20 and 31 and found that the consumption of 1.5 L/day of black tea resulted in a significant increase in urinary citrate excretion by 21% over the 24-h urine collection period, which is an important inhibitor of calcium stone formation (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Whereas in the study by Rodak et al., the substances contained in caffeinated coffee decrease the level of prolactin, which is an important hormone for women with more than 300 described functions, including regulation of reproductive function, the immune system, osmotic balance, and angiogenesis (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). This also suggests us that we should do more research on the caffeine contained in tea. Fortunately, PA still showed health benefits, with lower all-cause mortality in the physically active group than in the inactive group between ages 20 and 40.\u003c/p\u003e \u003cp\u003eIn the joint effect model, compared with the inactive and non-tea drinking group, the high tea group had the lowest HR in all three PA groups. Although the result was not statistically significant in the low met group, consistent with previous analyses, it still reflected the trend of tea consumption in reducing all-cause mortality. Although high tea consumption was associated with the lowest HR in the medium met group, low tea consumption was associated with increased HR compared with no tea consumption. However, HR tended to decrease with increasing tea consumption in the high tea group, which further suggests that adequate PA may play an integral role in the beneficial effects of tea consumption. Annabella Braschi et al. had similar findings in their study of tea catechin (TC), a beneficial substance found in tea (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), exercise, and sarcopenia. leg muscle mass and usual walking speed were not improved or even decreased in the TC intake group, but were significantly improved in the exercise group and further improved in the exercise plus TC group (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFurther health benefits of tea consumption may be explained by oxidative stress (Supplement Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Muscular contraction has been shown to generate several reactive radicals, such as superoxide, hydrogen peroxide, nitric oxide, and hydroxyl radicals, while unscavenged oxidants can modify macromolecules in the cell including nucleic acids, proteins, and lipids (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). This oxidation of cellular components (oxidative stress) can occur when an imbalance exists between oxidants and antioxidants (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). In general, the body can neutralize exercise-induced oxidative stress through antioxidant defense, and long-term exercise can also enhance this ability (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), but this defense may be overwhelmed by exercise-induced ROS production (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Green tea has obvious antioxidant activity, especially green tea catechins can fight oxidative stress through direct or indirect pathways in the body, thereby protecting the body from oxidative damage(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), which may reduce the possible negative effects of exercise to a certain extent, so as to further improve health.\u003c/p\u003e \u003cp\u003eThis study has several shortcomings. First, tea consumption was determined by only two dietary questionnaires, which is uncertain for determining whether a person is a habitual tea drink. Secondly, there is a lack of mechanistic studies on the interaction between tea drinking and PA, which is worthy of further investigation in our present study. Therefore, further randomized controlled trials are needed to determine the associations between tea consumption, PA and all-cause mortality as well as cancer-specific mortality, and further animal studies are needed to determine the interaction between tea consumption and PA.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, we investigated the associations between tea consumption, PA, and all-cause mortality. Our findings showed that both tea consumption and PA were independently associated with a reduced risk of all-cause mortality. Moreover, we found that tea consumption further reduced all-cause mortality in the physically active group. These results highlight the potential benefits of regular tea consumption and PA in promoting longevity and reducing the risk of premature death\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003col\u003e\n\u003cli\u003ePA: physical activity\u003c/li\u003e\n\u003cli\u003eNHANES: The National Health and Nutrition Examination Survey\u003c/li\u003e\n\u003cli\u003eHR: hazard ratios\u003c/li\u003e\n\u003cli\u003eCI 95%: confidence intervals\u003c/li\u003e\n\u003cli\u003eIPR: income-to-poverty ratio\u003c/li\u003e\n\u003cli\u003eBMI: body mass index\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur analysis used publicly available NHANES data. No new data were collected, and no new ethical approval was required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and material\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePublicly available datasets are available at https://www.cdc.gov/nchs/nhanes/\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ethe Third Xiangya Hospital of Central South University's Wisdom Accumulation and Talent Cultivation Project (YX202209).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors' contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY.H., L.Y. and J.H. wrote the main manuscript text and Y.H. prepared all figures. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe appreciate the DAGitty (http://www.dagitty.net/) providing the tools to draw the Supplement Fig.1.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eB. Blumberg J, W. Bolling B, Chen CYO, Xiao H. Review and Perspective on the Composition and Safety of Green Tea Extracts. European Journal of Nutrition \u0026amp; Food Safety. 2014;5(1):1\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMak JC. Potential role of green tea catechins in various disease therapies: Progress and promise. 2012;39(3):265\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDinh TC, Thi Phuong TN, Minh LB, Minh Thuc VT, Bac ND, Van Tien N, et al. The effects of green tea on lipid metabolism and its potential applications for obesity and related metabolic disorders - An existing update. Diabetes \u0026amp; Metabolic Syndrome: Clinical Research \u0026amp; Reviews. 2019;13(2):1667-73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCrespy V, Williamson G. A Review of the Health Effects of Green Tea Catechins in In Vivo Animal Models. The Journal of Nutrition. 2004;134(12):S3431-S40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePervin M, Unno K, Takagaki A, Isemura M, Nakamura Y. Function of Green Tea Catechins in the Brain: Epigallocatechin Gallate and its Metabolites. 2019;20(15):3630.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiao X, Tang C, Zhai X, Li S, Ma W, Liu K, et al. Early-Adulthood Weight Change and Later Physical Activity in Relation to Cardiovascular and All-Cause Mortality: NHANES 1999\u0026ndash;2014. Nutrients. 2022;14(23).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePojednic R, D'Arpino E, Halliday I, Bantham A. The Benefits of Physical Activity for People with Obesity, Independent of Weight Loss: A Systematic Review. Int J Environ Res Public Health. 2022;19(9).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeiss EP, Albert SG, Reeds DN, Kress KS, McDaniel JL, Klein S, et al. Effects of matched weight loss from calorie restriction, exercise, or both on cardiovascular disease risk factors: a randomized intervention trial. The American journal of clinical nutrition. 2016;104(3):576\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePowers SK, Jackson MJ. Exercise-induced oxidative stress: cellular mechanisms and impact on muscle force production. Physiological reviews. 2008;88(4):1243\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePowers SK, Deminice R, Ozdemir M, Yoshihara T, Bomkamp MP, Hyatt H. Exercise-induced oxidative stress: Friend or foe? Journal of sport and health science. 2020;9(5):415\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNobari H, Saedmocheshi S, Chung LH, Suzuki K, Maynar-Mari\u0026ntilde;o M, P\u0026eacute;rez-G\u0026oacute;mez J. An Overview on How Exercise with Green Tea Consumption Can Prevent the Production of Reactive Oxygen Species and Improve Sports Performance. Int J Environ Res Public Health. 2021;19(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKnez WL, Coombes JS, Jenkins DG. Ultra-endurance exercise and oxidative damage: implications for cardiovascular health. Sports medicine (Auckland, NZ). 2006;36(5):429\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eK\u0026ouml;nig D, Wagner KH, Elmadfa I, Berg A. Exercise and oxidative stress: significance of antioxidants with reference to inflammatory, muscular, and systemic stress. Exercise immunology review. 2001;7:108\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePOWERS SK, JI LL, LEEUWENBURGH C. Exercise training-induced alterations in skeletal muscle antioxidant capacity: a brief review. 1999;31(7):987\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOrlando P, Silvestri S, Galeazzi R, Antonicelli R, Marcheggiani F, Cirilli I, et al. Effect of ubiquinol supplementation on biochemical and oxidative stress indexes after intense exercise in young athletes. Redox report: communications in free radical research. 2018;23(1):136\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJacob RA, Burri BJ. Oxidative damage and defense. The American journal of clinical nutrition. 1996;63(6):985s-90s.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSureda A, Tejada S, Bibiloni Mdel M, Tur JA, Pons A. Polyphenols: well beyond the antioxidant capacity: polyphenol supplementation and exercise-induced oxidative stress and inflammation. Current pharmaceutical biotechnology. 2014;15(4):373\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGay IC, Tran DT, Paquette DW. Alcohol intake and periodontitis in adults aged \u0026gt;/=30 years: NHANES 2009\u0026ndash;2012. J Periodontol. 2018;89(6):625\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHe S, Ryan KA, Streeten EA, McArdle PF, Daue M, Trubiano D, et al. Prevalence, control, and treatment of diabetes, hypertension, and high cholesterol in the Amish. BMJ Open Diabetes Res Care. 2020;8(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCai XY, Zhang NH, Cheng YC, Ge SW, Xu G. Sugar-sweetened beverage consumption and mortality of chronic kidney disease: results from the US National Health and Nutrition Examination Survey, 1999\u0026ndash;2014. Clin Kidney J. 2022;15(4):718\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLin L, Chen CZ, Yu XD. [The analysis of threshold effect using Empower Stats software]. Zhonghua liu xing bing xue za zhi\u0026thinsp;=\u0026thinsp;Zhonghua liuxingbingxue zazhi. 2013;34(11):1139\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eByberg L, Melhus H, Gedeborg R, Sundstr\u0026ouml;m J, Ahlbom A, Zethelius B, et al. Total mortality after changes in leisure time physical activity in 50 year old men: 35 year follow-up of population based cohort. BMJ (Clinical research ed). 2009;338:b688.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchnohr P, O'Keefe JH, Lange P, Jensen GB, Marott JL. Impact of persistence and non-persistence in leisure time physical activity on coronary heart disease and all-cause mortality: The Copenhagen City Heart Study. European journal of preventive cardiology. 2017;24(15):1615\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlond K, Brinkl\u0026oslash;v CF, Ried-Larsen M, Crippa A, Gr\u0026oslash;ntved A. Association of high amounts of physical activity with mortality risk: a systematic review and meta-analysis. British journal of sports medicine. 2020;54(20):1195\u0026ndash;201.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Y, Zhang Y, Zhang M, Yang H, Wang Y. Consumption of coffee and tea with all-cause and cause-specific mortality: a prospective cohort study. BMC medicine. 2022;20(1):449.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNie J, Chen L, Yu CQ, Guo Y, Pei P, Chen JS, et al. [Association between tea consumption and all-cause mortality in Chinese adults]. Zhonghua liu xing bing xue za zhi\u0026thinsp;=\u0026thinsp;Zhonghua liuxingbingxue zazhi. 2022;43(2):145\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaito E, Inoue M, Sawada N, Shimazu T, Yamaji T, Iwasaki M, et al. Association of green tea consumption with mortality due to all causes and major causes of death in a Japanese population: the Japan Public Health Center-based Prospective Study (JPHC Study). Annals of epidemiology. 2015;25(7):512-8.e3.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArabzadeh E, Norouzi Kamareh M, Ramirez-Campillo R, Mirnejad R, Masti Y, Shirvani H. Twelve weeks of treadmill exercise training with green tea extract reduces myocardial oxidative stress and alleviates cardiomyocyte apoptosis in aging rat: The emerging role of BNIP3 and HIF-1α/IGFBP3 pathway. Journal of food biochemistry. 2022;46(12):e14397.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu Y, Lu Y, Xie G. Bubble tea consumption and its association with mental health symptoms: An observational cross-sectional study on Chinese young adults. Journal of affective disorders. 2022;299:620\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSiener R, Hesse A. Effect of Black Tea Consumption on Urinary Risk Factors for Kidney Stone Formation. Nutrients. 2021;13(12).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRodak K, Kokot I, Kryla A, Kratz EM. The Examination of the Influence of Caffeinated Coffee Consumption on the Concentrations of Serum Prolactin and Selected Parameters of the Oxidative-Antioxidant Balance in Young Adults: A Preliminary Report. Oxidative medicine and cellular longevity. 2022;2022:1735204.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTokuda Y, Mori H. Essential Amino Acid and Tea Catechin Supplementation after Resistance Exercise Improves Skeletal Muscle Mass in Older Adults with Sarcopenia: An Open-Label, Pilot, Randomized Controlled Trial. Journal of the American Nutrition Association. 2023;42(3):255\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim H, Suzuki T, Saito K, Yoshida H, Kojima N, Kim M, et al. Effects of exercise and tea catechins on muscle mass, strength and walking ability in community-dwelling elderly Japanese sarcopenic women: a randomized controlled trial. Geriatrics \u0026amp; gerontology international. 2013;13(2):458\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e\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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"NHANES, Tea consumption, Nutrition, Exercise, Mortality, Joint effects model, Longevity","lastPublishedDoi":"10.21203/rs.3.rs-4552199/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4552199/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe study aimed to comprehensively assess the separate and combined effects of physical activity (PA) and tea consumption on all-cause mortality among 21,350 participants from The National Health and Nutrition Examination Survey (NHANES) between 2009 and 2018. PA and tea consumption were evaluated through self-reported questionnaires and dietary recall interviews at baseline, with mortality data obtained from the National Death Index. Cox regression analyses yielded hazard ratios (HR) and 95% confidence intervals (CI). Results indicated that both tea consumption and PA independently reduced all-cause mortality. In the physically active group, tea consumption further decreased mortality risk, while this effect was not significant in the inactive group. Jointly, the highest tea consumers who exercised the most exhibited the lowest mortality risk compared to non-tea drinkers who exercised the least. These findings underscore the potential benefits of regular tea consumption and PA in promoting longevity and reducing premature death risks.\u003c/p\u003e","manuscriptTitle":"Physical Activity Combined with Tea Consumption could further Reduce All-cause Mortality: Results from the US National Health and Nutrition Examination Survey, 2009-2018","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-02 20:42:30","doi":"10.21203/rs.3.rs-4552199/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-16T06:35:21+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-04T14:33:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"309115338453101223739605425698575624005","date":"2024-06-26T14:24:49+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-23T02:37:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"162697261658753249874844122779478235488","date":"2024-06-21T16:40:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"318601748988766056739574831340650479427","date":"2024-06-13T01:27:20+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-12T12:16:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-12T12:03:34+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-06-12T10:22:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-10T12:23:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-06-09T02:13:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3f10cfe2-9cb2-4023-bb17-5d4578f38f55","owner":[],"postedDate":"July 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":33620149,"name":"Health sciences/Health care"},{"id":33620150,"name":"Health sciences/Diseases/Cancer"}],"tags":[],"updatedAt":"2024-10-14T15:59:12+00:00","versionOfRecord":{"articleIdentity":"rs-4552199","link":"https://doi.org/10.1038/s41598-024-73962-z","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-10-09 15:57:02","publishedOnDateReadable":"October 9th, 2024"},"versionCreatedAt":"2024-07-02 20:42:30","video":"","vorDoi":"10.1038/s41598-024-73962-z","vorDoiUrl":"https://doi.org/10.1038/s41598-024-73962-z","workflowStages":[]},"version":"v1","identity":"rs-4552199","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4552199","identity":"rs-4552199","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}