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HOME > Epidemiol Health > Volume 46; 2024 > Article
Systematic Review
 Tea consumption and risk of all-cause, cardiovascular disease, and cancer mortality: a meta-analysis of thirty-eight prospective cohort data sets
Youngyo Kim1orcid, Youjin Je2orcid
Epidemiol Health 2024;46:e2024056.
DOI: https://doi.org/10.4178/epih.e2024056
Published online: June 21, 2024

1Department of Food and Nutrition/Institute of Agriculture and Life Science, Gyeongsang National University, Jinju, Korea

2Department of Food and Nutrition, Kyung Hee University, Seoul, Korea

Correspondence: Youjin Je Department of Food and Nutrition, Kyung Hee University, 26 Kyunghee-daero, Dongdaemun-gu, Seoul 02447, Korea E-mail: youjinje@khu.ac.kr
• Received: March 6, 2024   • Accepted: June 4, 2024

© 2024, Korean Society of Epidemiology

This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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  • OBJECTIVES
    Tea consumption has been considered beneficial to human health because tea contains phytochemicals such as polyphenols and theaflavins. We conducted a systematic review and meta-analysis on the association between tea consumption and mortality from all causes, cardiovascular disease (CVD), and cancer to provide a quantitative assessment of current evidence.
  • METHODS
    The PubMed, Web of Science, and Scopus databases were searched through April 2024 to identify eligible studies. Random effects models were used to combine study-specific effect estimates (ESs).
  • RESULTS
    A total of 38 prospective cohort data sets (from 27 papers) with 1,956,549 participants were included in this meta-analysis. The pooled ESs of the highest versus lowest categories of tea consumption were 0.90 (95% confidence interval [CI], 0.86 to 0.95) for all-cause mortality, 0.86 (95% CI, 0.79 to 0.94) for CVD mortality, and 0.90 (95% CI, 0.78 to 1.03) for cancer mortality. In the dose-response analysis, a non-linear association was observed. The greatest risk reductions were observed for the consumption of 2.0 cup/day for all-cause mortality (ES, 0.91; 95% CI, 0.88 to 0.94) and 1.5 cup/day for cancer mortality (ES, 0.92; 95% CI, 0.89 to 0.96), whereas additional consumption did not show a further reduction in the risk of death. A plateau was observed for CVD mortality at moderate consumption levels (1.5-3.0 cup/day), but a sustained reduction in mortality risk was observed at higher intake levels.
  • CONCLUSIONS
    Moderate tea consumption (e.g., 1.5-2.0 cup/day) was associated with lower all-cause, CVD, and cancer mortality compared to no tea consumption. Further well-designed prospective studies are needed for a definitive conclusion.
  • Keywords: Tea, Mortality, Cardiovascular diseases, Cancer, Meta-analysis
Tea is a commonly consumed beverage worldwide and has a significant public health impact. The association between tea consumption and risk of mortality from chronic disease remains inconsistent, and extensive cohort studies have been published recently. In this meta-analysis, including thirty-eight cohort studies, people who drank one and a half to two cups of tea daily had a lower risk of mortality from all causes, cardiovascular disease, and cancer than those who drank less tea.
Tea has been one of the most commonly consumed beverages worldwide for centuries [1]. Tea is a rich source of flavonoids such as catechins, theaflavins, anthocyanins, and flavonols [2]. Flavonoids are known for their potential to reduce the risk of many non-communicable diseases, including cardiovascular disease (CVD) and cancer, due to their anti-inflammatory and antioxidant properties that reduce oxidative stress [3,4]. In addition, a meta-analysis involving 386,610 participants showed that high flavonoid intake was associated with a lower risk of mortality from CVD and all causes [5].
Because tea is widely consumed globally, its effect on public health can be major even if its effect is minor on an individual level. Many observational studies have explored the associations between tea consumption and the risks of all-cause and cause-specific mortality [6-32]. Some studies found an inverse [7,17,21-24,27,28,30] or positive [9,10] association between tea consumption and the risk of mortality, whereas others did not find a significant association [6,8,11-16,18-20,25,26,29,31,32]. To date, several meta-analyses have been conducted to examine the association between tea consumption and risk of mortality, but they included studies in which all participants had a specific disease [33,34] or did not provide results for cancer mortality [34,35]. Since then, many large cohort studies have been published, analyzing data from the UK Biobank (n=498,158) and Asia Cohort Consortium (n=528,504) [27-32]. Recent large cohort studies have indicated that significant associations exist between tea consumption and mortality [27,28,30]. Given the results published to date, we speculated about the possible association between tea consumption and mortality if a meta-analysis were conducted on the general population, excluding as many studies as possible that targeted only patients.
Therefore, we performed a systematic review and meta-analysis of prospective cohort studies to provide the latest evidence on the associations between tea consumption and the risk of mortality from all causes, CVD, and cancer in the general population. Furthermore, a dose-response analysis was conducted to determine trends in mortality risk with increased tea consumption and elucidate appropriate levels of tea consumption to reduce the risk of death.
Data sources and searches
A systematic literature search was performed using the PubMed, ISI Web of Science, and Elsevier Scopus databases to identify eligible studies published in English through April 2024. We used the following keywords in the search: “(tea OR beverage OR beverages) AND (mortality OR death OR fatal).” A manual search that reviewed the included articles’ reference lists was also conducted to identify additional eligible studies. This meta-analysis was registered on PROSPERO (CRD42023400484).
Study selection
Studies were included in the current meta-analysis according to the following criteria: (1) the study had a prospective observational design; (2) the exposure of interest was tea consumption; (3) the outcome of interest was mortality from all causes, CVD, and cancer; (4) the researchers reported effect estimates (ESs; relative risks [RRs] or hazard ratios [HRs]) with the corresponding 95% confidence intervals (CIs) for each tea-intake group. If 2 different papers had been published on the same cohort data sets, the study with a more extended follow-up period or more participants was included in the meta-analysis. If 2 papers following the same cohort reported deaths from different causes, both were included in the meta-analysis [19,32]. Studies in which the participants consisted only of patients with a specific disease were excluded.

Data extraction and quality assessment

The relevant data were independently extracted by 2 authors (YK and YJ) according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [36]. The following information was collected from each paper: surname of first author, year of publication, cohort name, number of participants and cases, age, gender, geographical region or country, period of follow-up, categories of tea consumption, the ESs (RRs or HRs) and 95% CIs for each category of tea consumption, and adjusted variables.
Quality assessment of the included studies was performed using the Newcastle-Ottawa quality assessment scale [37]. We assigned a maximum score of 9 points to each study based on the following criteria: selection of participants (0-4 points), comparability of cohorts (0-2 points), and ascertainment of outcomes of interest (0-3 points). Studies with total scores of 0-3 points, 4-6 points, or 7-9 points were regarded as low, moderate, or high quality, respectively. Any discrepancies between authors in data extraction and quality assessment were resolved by reviewing and discussing the original papers.
Statistical analysis
The natural logarithm values of each study’s ESs (RRs or HRs) were combined using a DerSimonian & Laird [38] random effects model, which considers both within-study and between-study variability. If a study provided separate ESs by the presence or absence of disease history, we used the ESs for the latter [32]. The summary ESs were displayed as forest plots. The Cochran Q test [39] was used to assess heterogeneity among studies, and the I2 statistic [40] was used to quantify inconsistency. Subgroup analyses stratified by gender, geographic region, follow-up years, and sample size were conducted to investigate the variations in ESs among the studies. To assess how much a specific study may influence inferences, we performed a senstivity analysis by omitting a single study at a time and deriving pooled ESs. Publication bias was evaluated with the Begg test [41] and the Egger regression test [42], as well as funnel plot visualizations.
To estimate the study-specific slope lines, a linear dose-response meta-analysis was conducted using the methods proposed by previous studies [43-45]. The median value of tea consumption was assigned to each category based on information presented in the original paper. When the highest category was open-ended, we regarded it as of the same magnitude as the adjacent category. Referring to previous papers, we considered 150 mL of tea consumption to be 1 cup of tea [9,33]. To investigate a potential nonlinear association between tea consumption and risk of mortality, we used restricted cubic splines with 4 knots at fixed percentiles (5th, 35th, 65th, and 95th percentiles) of aggregated tea consumption. The p-value for non-linearity was computed by testing the null hypothesis that the regression coefficient of the second spline is equal to zero [46]. A 2-tailed p-value of less than 0.05 was considered to indicate statistical significance. All statistical analyses were carried out with Stata version 17.0 (StataCorp., College Station, TX, USA).
Study characteristics
A total of 38 prospective cohort data sets (27 papers) including 1,956,549 participants and 218,948 deaths from all causes, 53,234 deaths from CVD, and 56,049 deaths from cancer were eligible for this meta-analysis (Figure 1) [6-32]. Table 1 summarizes the characteristics of the included studies. Among them, 7 papers reported all estimates of mortality from all causes, CVD, and cancer [17,21-23,25,26,30], respectively. Six papers provided estimates of mortality from all causes and CVD [10,15,18,24,27,28], and 1 paper reported estimates of mortality from all causes and cancer [9]. The other papers provided mortality from either all causes [6,8,13,16,31,32], CVD [7,11,12,19,20] or cancer only [14,29]. The follow-up durations varied from 5 years to 23 years, and the mean follow-up time was 12.3 years. The studies were conducted in Asia [11,13,14,17,19,22,27,30-32], Europe [7,9,10,12,18,26,28,29], United States [6,8,15,16,20,21,23,25], and Oceania [24]. All studies were adjusted for age and smoking, and most were adjusted for alcohol consumption [7,9-11,13,15-19,21-23,25-32] and body mass index (BMI) [7-12,15-17,19-32]. The quality assessment results ranged from 7 to 9, indicating high quality (Supplementary Materrial 1).
All-cause mortality
Thirty-three prospective cohort data sets (20 papers) involving 1,825,815 participants and 218,948 deaths examined the association between tea consumption and all-cause mortality [6,7,9,10, 13,15-18,21-28,30-32]. The summary ES for all-cause mortality, comparing the highest and lowest levels of tea consumption, was 0.90 (95% CI, 0.86 to 0.95), with significant heterogeneity among studies (I2 = 81.6%, p<0.001) (Figure 2). The sensitivity analysis results, excluding 1 study at a time, showed that the pooled ESs ranged from 0.89 (95% CI, 0.85 to 0.94) to 0.92 (95% CI, 0.88 to 0.96) (Supplementary Material 2). The inverse association between tea consumption and the risk of all-cause mortality was slightly stronger in men (ES, 0.87; 95% CI, 0.77 to 0.98) than in women (ES, 0.90; 95% CI, 0.79 to 1.01), but the difference was not statistically significant (p for difference=0.97) (Table 2). By geographic region, the strongest inverse association between tea consumption and all-cause mortality was shown in Asia (ES, 0.84; 95% CI, 0.77 to 0.91), while an insignificant positive association was observed in Europe (ES, 1.12; 95% CI, 0.88 to 1.42; p for difference=0.05). We did not observe significant variation according to follow-up times (p for difference=0.17) or number of participants (p for difference=0.87). We found a non-linear association between tea consumption and all-cause mortality (p for non-linearity < 0.001) (Figure 3). A significant reduction in all-cause mortality was observed with up to 2.0 cup/day of tea consumption, and additional consumption did not show a further decrease in mortality.

CVD mortality

Thirty-one prospective cohort data sets (18 papers) involving 1,820,381 participants and 53,234 deaths examined the association between tea consumption and CVD mortality [7,10-12,15,17-28,30]. The summary ES for CVD mortality, comparing the highest and lowest levels of tea consumption, was 0.86 (95% CI, 0.79 to 0.94), showing significant heterogeneity among studies (I2= 74.6%, p<0.001) (Figure 4). When the pooled ES was estimated after omitting 1 study at a time, the ESs ranged from 0.85 (95% CI, 0.78 to 0.92) to 0.88 (95% CI, 0.82 to 0.95) (Supplementary Material 3). The inverse association between tea consumption and CVD mortality was similar in men (ES, 0.84; 95% CI, 0.71 to 0.99) and women (ES, 0.86; 95% CI, 0.75 to 0.99). By geographic region, the largest reduction in CVD mortality was found in Asia (ES, 0.75; 95% CI, 0.65 to 0.88), but the difference was not statistically significant (p for all comparisons > 0.1) (Table 2). Some evidence for a non-linear association was found between tea consumption and CVD mortality (p for non-linearity<0.001) (Figure 5). Despite the significant non-linearity showing an identical degree of risk reduction for 1.5-3.0 cup/day, the ES decreased by 27% with up to 8.0 cups of tea consumption per day.

Cancer mortality

Twenty-two prospective cohort data sets (11 papers) involving 1,439,658 participants and 56,049 deaths examined the association between tea consumption and cancer mortality [9,13,14, 17,21-23,26,29,30]. The summary ES for cancer mortality, comparing the highest and lowest levels of tea consumption, was 0.90 (95% CI, 0.78 to 1.03), with significant heterogeneity among studies (I2 =78.8%, p<0.001) (Figure 6). When we calculated the pooled ES after excluding 1 study at a time, the ESs ranged from 0.87 (95% CI, 0.75 to 1.00) to 0.94 (95% CI, 0.82 to 1.07) (Supplementary Material 4). We found no significant difference by gender (p for difference=0.93) or geographic region (p for difference>0.2 in all comparisons) (Table 2). A significant non-linear association was found between tea consumption and cancer mortality (p for nonlinearity < 0.001) (Figure 7). The most robust inverse association was shown for tea consumption of 1.5-2.0 cup/day, and a significant reduction in cancer mortality was observed with tea consumption of up to 5.5 cup/day.

Publication bias

No evidence of publication bias was found for tea consumption and all-cause mortality (Begg’s p=0.97; Egger’s p=0.75), CVD mortality (Begg’s p>0.99; Egger’s p=0.65), or cancer mortality (Begg’s p=0.88; Egger’s p=0.43).
The current systematic review and meta-analysis of 38 prospective cohort data sets (from 27 papers) with 1,956,549 total participants found inverse associations between tea consumption and all-cause and CVD mortality. People with the highest level of tea consumption had a 10% lower risk of all-cause mortality and a 14% lower risk of CVD mortality than those with the lowest consumption level. The results from the dose-response analyses showed a non-linear association between tea consumption and mortality from all causes, CVD, and cancer. The most significant reduction in all-cause mortality was observed at 2.0 cup/day of tea consumption, and further intake did not appear to further lower the risk of death. A plateau in CVD mortality was observed at moderate intake levels (1.5-3.0 cup/day of tea consumption), but a continued decline in mortality risk was observed at higher intake levels. For cancer mortality, the greatest reduction in mortality risk was observed at the level of consuming 1.5 cups of tea per day, and additional intake did not lower mortality.
Many previous observational studies have reported the association between tea drinking and the risk of chronic diseases. A recent meta-analysis of 19 prospective cohort studies, with a total of 1,076,300 participants, found that people consuming 4 or more cups of tea per day had a 17% lower risk of type 2 diabetes than people who did not drink tea [47]. For CVD risk, a meta-analysis of 7 prospective cohort studies involving 9,211 cases of coronary heart disease among 772,922 participants indicated that green tea consumers had less risk of coronary heart disease than those who did not consume green tea. The risk was 11% lower for 1 cup/day, 16% lower for 2 cup/day, 15% lower for 3 cup/day, and 12% lower for 4 cup/day [48]. Furthermore, a meta-analysis of 5 prospective cohort studies, including 11,421 stroke cases among 645,393 participants, reported that 900 mL/day of green tea consumption was associated with a 23% reduced risk of stroke [49]. Regarding risk of cancer, meta-analyses of prospective cohort studies showed that high tea consumption was inversely associated with several types of cancer, including glioma and ovarian, liver, bladder, and lymphoid cancer [50-52]. The lower risk of mortality with tea consumption observed in the current study may be due to the inverse association between tea consumption and the risks of many chronic diseases reported in previous studies.
A previous meta-analysis reported 26% lower and 24% lower risks of cardiac death and all-cause death, respectively, per 3-cup increment of tea consumption [34]. Another meta-analysis published in 2015 found that green tea consumption was inversely associated with mortality from CVD and all causes, and black tea consumption was inversely associated with mortality from cancer and all causes [33]. However, in that meta-analysis, when classifying the types of tea, the types of tea were estimated and analyzed according to the region where the study was conducted [33]. A recent meta-analysis from 2020 observed that each 1-cup increase in daily tea intake was associated with 4% and 2% lower risks of mortality from CVD and all causes, respectively [35]. Previous results and the results of our study are consistent in that tea consumption was inversely associated with the risk of CVD and all-cause mortality, and our findings indicated that consuming 1.5-2.0 cups of tea daily was associated with lower mortality rates from CVD, cancer, and all causes.
In the subgroup analysis by geographical region, the inverse association between tea consumption and risk of mortality from all causes was stronger in Asia than in Europe. These differences observed across regions may be due to regional differences in the types of tea that are widely consumed. Among the studies included in this meta-analysis, those that reported the type of tea were mostly from Asia, and it was primarily green tea. Although studies conducted in Europe did not report the type of tea, it is generally known that people in Europe and North America mainly consume black tea [1,53]. Green tea and black tea go through different manufacturing processes, and their composition varies accordingly. The most abundant polyphenols in green tea are catechins such as epicatechin, epicatechin-3-gallate, epigallocatechin, and epigallocatechin-3-gallate (EGCG). Meanwhile, the major polyphenolic components of black tea are theaflavin and thearubigin [53]. These differences in the composition of green tea and black tea may have influenced the difference in their associations with mortality risk. Most of the studies included in this meta-analysis did not report the ES by type of tea. The single study that reported ES by tea types found a significant inverse association between green tea consumption and mortality from all causes and CVD [27]. Specifically, drinking green tea 3 or more times a week was associated with a 21% lower risk of mortality from all causes and a 22% lower risk of mortality from CVD than drinking it fewer than 3 times a week. The researchers did not find a significant association between black tea consumption and mortality risk. It appears that more large-scale cohort studies need to be conducted in the future to determine whether mortality risk varies depending on the type of tea. Another explanation for the differences by geographical region in the association between tea consumption and mortality may be differences in how tea is consumed. In Europe, especially in the United Kingdom, it is common to add milk to tea [9]. Proteins in milk can combine with polyphenols in tea [54], reducing the polyphenols’ antioxidant capacity by inhibiting absorption and decreasing their bioavailability [55]. An experimental study found that the ferric iron-reducing antioxidant power value, an indicator of antioxidant activity, decreased as milk was added to tea [56]. The reduced antioxidant capacity of flavonoids after binding to proteins such as casein in milk may have attenuated the association between tea consumption and mortality. To understand more clearly the effects of adding milk to tea on the association between tea consumption and mortality, future prospective cohort studies that include information on how tea is consumed would need to be performed.
Because of the antioxidant properties of the polyphenols contained in tea, drinking tea has generally been considered a healthy dietary habit [57]. Antioxidative ability is an important factor in preventing disease and lowering the risk of premature death because oxidative stress is known to cause chronic disease by damaging normal cells and DNA. Tea flavonoids such as catechins or theaflavins have been found to decrease the oxidation of low-density lipoproteins, which cause atherosclerosis and increase the risk of CVD [58]. In addition, EGCG has been shown to have preventive effects against cancer by inhibiting the activity of urokinase, which invades cells and forms metastases in human cancers [59], or by inducing apoptosis and cell cycle arrest specific to cancer cells [60].
This study has offered a comprehensive meta-analysis of prospective cohort studies to examine the associations between tea consumption and the risks of mortality from all causes, CVD, and cancer. Prospective cohort studies have relatively less recall or selection bias than other observational study designs. The present meta-analysis included a large number of people (1,956,549 total participants), including recently published large cohorts, and thus, the results could have considerably more statistical power. To identify the appropriate tea consumption level for minimizing mortality risk, we performed a dose-response analysis that could show changes in ESs as tea intake increased. Additionally, unlike previous meta-analyses on the association between tea consumption and mortality, we excluded studies where all participants were patients suffering from a specific disease to examine the effect of tea consumption on mortality risk in the general population. Despite these strengths, several limitations should be mentioned as well. First, in most of the included studies, the data on tea consumption were assessed through a food frequency questionnaire, which allowed the possibility of misclassification. Fortunately, such misclassification of dietary intake tends to lead to a null result, so it is unlikely that the associations between tea consumption and mortality risk were exaggerated. Second, the volume of tea consumption was usually reported in cups, but cup size may differ from study to study. Third, the chemical composition of each cup of tea, such as its polyphenols, could vary by season, climate, and plant age, which may affect the associations between tea consumption and the risk of mortality [53]. Finally, the adjustment factors differed across the studies, which might have affected the pooled estimates in the meta-analysis. Most included studies controlled for potential confounders including smoking, alcohol consumption, and BMI, but the possibility of additional confounding factors cannot be completely ruled out.
The current systematic review and meta-analysis of prospective cohort studies suggested that moderate daily tea consumption (1.5-2.0 cup/day) was associated with lower risks of mortality from all causes, CVD, and cancer in the general population. Future well-designed, large-scale prospective cohort studies analyzing different types of tea are needed to develop dietary guidelines for tea consumption to reduce the risk of chronic disease and premature death.
Supplementary materials are available at https://doi.org/10.4178/epih.e2024056.

Supplementary Material 1.

Quality assessment scores according to Newcastle-Ottawa Quality Assessment Scale.
epih-46-e2024056-Supplementary-1.docx

Supplementary Material 2.

Sensitivity analysis results by excluding one study at a time for the association between highest versus lowest levels of tea consumption and all-cause mortality.
epih-46-e2024056-Supplementary-2.docx

Supplementary Material 3.

Sensitivity analysis results by excluding one study at a time for the association between highest versus lowest levels of tea consumption and CVD mortality.
epih-46-e2024056-Supplementary-3.docx

Supplementary Material 4.

Sensitivity analysis results by excluding one study at a time for the association between highest versus lowest levels of tea consumption and cancer mortality.
epih-46-e2024056-Supplementary-4.docx

Conflict of interest

The authors have no conflicts of interest to declare for this study.

Funding

This work was supported by the National Research Foundation of Korea, funded by the Ministry of Science, ICT, and Future Planning (grant No. NRF-2021R1F1A1050847).

Author contributions

Both authors contributed equally to conceiving the study, analyzing the data, and writing this paper.

The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Figure 1.
Flow chart of study selection.
epih-46-e2024056f1.jpg
Figure 2.
Forest plots of the prospective cohort studies of all-cause mortality for high versus low tea consumption. ES, effect estimate; CI, confidence interval.
epih-46-e2024056f2.jpg
Figure 3.
Pooled dose-response association between tea consumption and all-cause mortality. Solid lines represent effect estimates (ESs); dashed lines represent 95% confidence intervals (CIs).
epih-46-e2024056f3.jpg
Figure 4.
Forest plots of the prospective cohort studies of cardiovascular disease mortality for high versus low tea consumption. ES, effect estimate; CI, confidence interval.
epih-46-e2024056f4.jpg
Figure 5.
Pooled dose-response association between tea consumption and cardiovascular disease (CVD) mortality. Solid lines represent effect estimates (ESs); dashed lines represent 95% confidence intervals (CIs).
epih-46-e2024056f5.jpg
Figure 6.
Forest plots of the prospective cohort studies of cancer mortality for high versus low tea consumption. ES, effect estimate; CI, confidence interval.
epih-46-e2024056f6.jpg
Figure 7.
Pooled dose-response association between tea consumption and cancer mortality. Solid lines represent effect estimates (ESs); dashed lines represent 95% confidence intervals (CIs).
epih-46-e2024056f7.jpg
epih-46-e2024056f8.jpg
Table 1.
Characteristics of studies included in the meta-analysis of tea consumption and mortality from all causes, CVD, and cancer
Study Country Cohort name Follow-up period (yr) Age at baseline (yr) Study size
 Gender Tea consumption Cause of death Adjustment for covariates
Subjects No. of deaths
Kahn et al., 1984 [6] USA Seventh-Day Adventists 21 ≥30 21,022 5,679 Men and women <1 vs. ≥1 cup/day All causes Age, gender, smoking history, history of heart disease, stroke, hypertension, diabetes, or cancer; age at initial exposure to the Adventist Church
Hertog et al., 1993 [7] Netherlands Zutphen Elderly Study 5 65-84 805 43 Men 0-250 vs. >500 mL/day CHD Age, intake of total energy, saturated fatty acids, cholesterol, alcohol, coffee, vitamin C, vitamin E, beta-carotene, dietary fiber, history of myocardial infarction, BMI, smoking, serum total and HDL cholesterol, systolic blood pressure
Klatsky et al., 1993 [8] USA Northern California Kaiser Permanente Medical Care Program 8 N/A 125,356 4,208 Men and women 0 vs. ≥4 cup/day All causes Age, gender, BMI, smoking, alcohol, race, education, marital status
Hertog et al., 1997 [9] UK Caerphilly study 14 45-59 1,900 3383 Men 0-300 vs. >1,200 mL/day All causes Age, smoking, social class, BMI, intakes of total energy, alcohol, fat, vitamin C, vitamin E, and β-carotene
1044 Cancer
Woodward et al., 1999 [10] Scotland Scottish Heart Health Study 7.7 40-59 11,507 5883 Men and women 0 vs. ≥5 cup/day All causes Age, housing tenure, activity at work, activity in leisure, cigarette smoking status, BMI, Bortner score, cotinine, systolic blood pressure, fibrinogen, total cholesterol, HDL cholesterol, triglycerides, alcohol, vitamin C, and coffee
2065 CHD
Nakachi et al., 2000 [11] Japan Saitama 11 >40 8,552 222 Men and women ≤3 vs. ≥10 cup/day CVD Age, cigarette smoking, alcohol consumption, intake of meat, and relative body weight
Prefecture
Hirvonen et al., 2001 [12] Finland Alpha-Tocopherol, Beta-Carotene Cancer Prevention 6.1 50-69 25,372 815 Men <1 vs. ≥1 cup/day CVD Age, supplementation group, systolic and diastolic blood pressure, serum total cholesterol, serum HDL cholesterol, BMI, smoking years, number of cigarettes smoked daily, history of diabetes mellitus and CHD, marital status, education, leisure-time physical activity
Study
Iwai et al., 2002 [13] Japan Tottori Prefecture 9.9 40-79 2,855 3613 Men and women <0.5 vs. ≥4 cup/day All causes Age, smoking, alcohol, history of selected diseases, physical activity, educational status
614 Cancer
Khan et al., 2004 [14] Japan Hokkaido 13.8 ≥40 3,158 244 Men and women Never+several times/yr+several times/mo vs. several times/wk+daily Cancer Age, health education, health examination, health status, smoking
Prefecture
Andersen et al., 2006 [15] USA Iowa Woman’s Health Study 15 55-69 27,312 4,2653 Women 0 vs. >3 cup/day All causes Age, smoking, intake of alcohol, BMI, waist-hip ratio, education, physical activity, use of estrogens, use of multivitamin supplements, energy intake, and intakes of whole and refined grain, red meat, fish, seafood, total fruit and vegetables
1,4116 CVD
Paganini-Hill et al., 2007 [16] USA Leisure World Cohort Study 23 ≥44 13,624 11,386 Men and women 0 vs. ≥2 cup/day All causes Age, gender, smoking, exercise, BMI, alcohol intake, and histories of hypertension, angina, heart attack, stroke, diabetes, rheumatoid arthritis, and cancer
Suzuki et al., 2009 [17] Japan Shizuoka Elderly Cohort 6 65-84 12,251 1,2243 Men and women <1 vs. ≥7 cup/day All causes Age, gender, smoking status, alcohol consumption, BMI, frequency of physical activity
4056 CVD
4004 Cancer
de Koning Gans et al., 2010 [18] Netherlands European Prospective Investigation into Cancer and Nutrition-Netherlands (EPIC-NL), MORGEN 13 20-69 37,514 1,4053 Men and women <1 vs. >6 cup/day All causes Age, gender, cohort (strata), education, physical activity, smoking status, waist circumference, menopausal status, alcohol, coffee, vitamin C, level, fiber, consumption, energy, saturated fat
1236 CVD
Mineharu et al., 2011 [19] Japan Japan Collaborative Cohort Study for Evaluation of Cancer Risk (JACC) 13.1 40-79 82,655 3,125 Men and women <1 cup/wk vs. ≥6 cup/day CVD Age, BMI, smoking status, alcohol intake, history of hypertension, history of diabetes, education, waking hours, hours of sports participation, perceived mental stress, multivitamin use, vitamin E supplement use; total consumption of fruits, vegetables, beans, meat, and fish; and total daily energy intake
Bertoia et al., 2013 [20] USA Women’s Health Initiative Observational Study (WHI) 11 50–79 92,847 205 Women 0 vs. ≥4 cup/day CVD Age, total energy intake, race, income, smoking status, physical activity, waist-to-hip ratio, BMI, atrial fibrillation, coronary artery disease, heart failure, diabetes, high cholesterol, hypertension, pulse in 60 seconds, and hormone use
Gardner et al., 2013 [21] USA Northern Manhattan Study 11 >40 2,461 8633 Men and women 1 cup/mo vs. ≥2 cup/day All causes Age, gender, BMI, race, education, pack-years of smoking, alcohol consumption, energy, protein, carbohydrates, total fat, saturated fat, history of vascular risk factors, other non-water beverage consumption, coffee additives (milk, cream, nondairy creamer), coffee
3426 CVD
1604 Cancer
Liu et al., 2016 [22] China Chinese Prospective Smoking Study 11 >40 164,681 32,700 Men 0 vs. >10 g/day All causes Age, BMI, marital status, urban locality, education, job status, smoking status, alcohol drinking; times of weekly consumption for fish, meat, poultry consumption, egg, and milk; black tea drinker, jasmine tea drinker, other tea drinker
CVD
Cancer
Ivey et al., 2017 [23] USA Nurses’ Health Study II 18 25-42 93,145 1,8943 Women 0 vs. >1 time/wk All causes Age, BMI, smoking status, menopausal status, family history (of diabetes, cancer, and myocardial infarction), multivitamin supplement use, aspirin use, race, type 2 diabetes, hypercholesterolemia, hypertension, physical activity, energy intake, alcohol consumption, and the Alternative Health Eating Index (minus alcohol) score
1896 CVD
8874 Cancer
Lim et al., 2017 [24] Australia Calcium Intake Fracture Outcome Study 10 ≥70 1,055 3623 Women 1 cup/day increment All causes Age, smoking history, SES, diabetes status, hypertension, blood pressure, prevalent CVD, medications and treatment code (calcium supplementation vs. no calcium supplementation), fluid status, BMI, estimated glomerular filtration rate
1426 CVD
Yan et al., 2017 [25] USA Aerobics Center Longitudinal Study 16 20-82 11,808 8423 Men and women 0 vs. >14 cup/wk All causes Age, gender, baseline examination year, regular coffee use, decaffeinated coffee use, herbal tea use, physical inactivity, BMI, smoking, alcohol consumption, metabolic equivalents
2506 CVD
3454 Cancer
van den Brandt, 2018 [26] Netherlands Netherlands Cohort Study (NLCS) 10 55-69 120,852 8,6653 Men and women 0 vs. ≥5 cup/day All causes Age, cigarette smoking status, number of cigarettes smoked per day, years of smoking, history of physician-diagnosed hypertension and diabetes, body height, BMI, non-occupational physical activity, highest level of education, intake of alcohol, nuts, vegetables and fruit, tea, energy, use of nutritional supplements, postmenopausal hormone replacement therapy (in women)
2,9276 CVD
3,8494 Cancer
Wang et al., 2020 [27] China China-PAR project (3 cohorts)1 7.3 52, mean 100,902 5,4793 Men and women <3 vs. ≥3 time/wk All causes Age, gender, region, residential area, cohort, educational level, family history of atherosclerotic CVD, smoking, drinking, physical activity level, dietary factors, BMI, systolic blood pressure, fasting blood glucose, total cholesterol, HDL cholesterol
1,4776 CVD
Teramoto et al., 2021 [32] Japan Japan Collaborative Cohort Study for Evaluation of Cancer Risk (JACC) 18.5 40-79 44,521 8,666 Men and women 0 vs. ≥7 cup/day All causes Age, gender, coffee consumption, history of hypertension, history of diabetes, BMI, smoking status, alcohol consumption, hours of exercise, hours of walking, perceived mental stress, educational level, regular employment, dietary intakes of vegetable, fish, fruits, and soybeans
Chen et al., 2022 [28] UK UK Biobank 12.1 37-73 498,158 34,6993 Men and women 0 vs. ≥5 cup/day All causes Age, gender, ethnicity, educational level, BMI, smoking status, alcohol intake frequency, physical activity, dietary pattern, general health status, hypertension, diabetes, depression, coffee consumption
6,6636 CVD
Inoue-Choi et al., 2022 [29] UK UK Biobank 11.2 40-69 498,043 15,790 Men and women 0 vs. ≥10 cup/day Cancer Age, gender, race and ethnicity, Townsend deprivation score, general health status, cancer, CVD, diabetes, BMI, tobacco smoking, physical activity, alcohol intake, coffee intake; dietary intake including vegetables, fruits, red meat, and processed meat; assessment centers
Shin et al., 2022 [30] Asia Asia Cohort Consortium (12 cohorts)2 6.5-22.7 54.3 mean 528,504 94,7443 Men and women 0 vs. ≥5 cup/day All causes Age, BMI, smoking status, alcohol intake, educational level, energy intake, coffee consumption
22,8506 CVD
27,2074 Cancer
Qiu et al., 2023 [31] China China Health and Nutrition Survey (CHNS) 17.9 54.4 mean 6,387 580 Men and women 0 vs. 3-4 cup/day All causes Age, gender, marital status, educational level, nationality, residential area, smoking status, occupation, level of annual income, mean systolic blood pressure, mean BMI, mean waist and hip circumferences, hypertension, diabetes mellitus, myocardial infarction, stroke, malignant tumor

CVD, cardiovascular disease; CHD, coronary heart disease; BMI, body mass index; HDL, high-density lipoprotein; SES, socioeconomic status; N/A, not available.

1 China 3 cohort is China Multi-Center Collaborative Study of Cardiovascular Epidemiology, International Collaborative Study of CVD in Asia, and Community Intervention of Metabolic Syndrome in China & Chinese Family Health Study.

2 Asia Cohort Consortium includes Japan Public Health Center-based Prospective Study (JPHC) I, II, Miyagi Cohort, Ohsaki National Health Insurance Cohort Study, Life Span Study Cohort (RERF), 3 Prefecture Miyagi, 3 Prefecture Aichi, Seoul Male Cancer Cohort (Seoul Male), Korean Multi-center Cancer Cohort Study (KMCC), Shanghai Men’s Health Study (SMHS), Shanghai Women’s Health Study (SWHS), and Singapore Chinese Health Study (SCHS).

3 Death from all causes.

4 Death from cancer.

5 Death from CHD.

6 Death from CVD.

Table 2.
Summary of pooled ESs of mortality from all causes, CVD, and cancer by tea consumption
Variables No. of studies ES (95% CI) p for difference
All-cause mortality
 High vs. low tea consumption
 All studies 20 0.90 (0.86, 0.95)
 Stratified by gender
  Men 8 0.87 (0.77, 0.98) 0.97
  Women 9 0.90 (0.79, 1.01)
 Stratified by geographical region
  Asia 7 0.84 (0.77, 0.91)
  USA 7 0.92 (0.83, 1.02) 0.321
  Europe 5 1.12 (0.88, 1.42) 0.051
  Oceania 1 0.92 (0.86, 0.98) 0.571
 Stratified by follow-up years
  ≥Median 10 0.96 (0.88, 1.05) 0.17
  <Median 10 0.86 (0.81, 0.92)
 Stratified by no. of subjects
  ≥Median 10 0.89 (0.85, 0.94) 0.87
  <Median 10 0.91 (0.80, 1.04)
CVD mortality
 High vs. low tea consumption
 All studies 18 0.86 (0.79, 0.94)
 Stratified by gender
  Men 10 0.84 (0.71, 0.99) 0.83
  Women 11 0.86 (0.75, 0.99)
 Stratified by geographical region
  Asia 6 0.75 (0.65, 0.88)
  USA 5 0.91 (0.72, 1.14) 0.312
  Europe 6 1.00 (0.78, 1.26) 0.172
  Oceania 1 0.90 (0.79, 0.94) 0.552
 Stratified by follow-up years
  ≥Median 11 0.86 (0.80, 0.92) 0.76
  <Median 7 0.84 (0.68, 1.03)
 Stratified by no. of subjects
  ≥Median 9 0.84 (0.79, 0.89) 0.76
  <Median 9 0.84 (0.69, 1.03)
Cancer mortality
 High vs. low tea consumption
 All studies 11 0.90 (0.78, 1.03)
 Stratified by gender
  Men 7 0.91 (0.77, 1.09) 0.93
  Women 5 0.93 (0.70, 1.23)
 Stratified by geographical region
  Asia 5 0.92 (0.74, 1.15)
  USA 3 0.70 (0.46, 1.07) 0.253
  Europe 3 1.00 (0.80, 1.24) 0.643
 Stratified by follow-up years
  ≥Median 6 0.97 (0.82, 1.14) 0.24
  <Median 5 0.80 (0.70, 0.92)
 Stratified by no. of subjects
  ≥Median 6 0.88 (0.76, 1.03) 0.72
  <Median 5 0.94 (0.65, 1.35)

ES, effect estimate; CVD, cardiovascular disease; CI, confidence interval.

1 ESs of all-cause mortality for USA vs. Asia (p=0.32), Europe vs. Asia (p=0.05), and Oceania vs. Asia (p=0.57).

2 ESs of CVD mortality for USA vs. Asia (p=0.31), Europe vs. Asia (p=0.17), and Oceania vs. Asia (p=0.55).

3 ESs of cancer mortality for USA vs. Asia (p=0.25) and Europe vs. Asia (p=0.64).

Figure & Data

References

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    Tea consumption and risk of all-cause, cardiovascular disease, and cancer mortality: a meta-analysis of thirty-eight prospective cohort data sets
    Image Image Image Image Image Image Image Image
    Figure 1. Flow chart of study selection.
    Figure 2. Forest plots of the prospective cohort studies of all-cause mortality for high versus low tea consumption. ES, effect estimate; CI, confidence interval.
    Figure 3. Pooled dose-response association between tea consumption and all-cause mortality. Solid lines represent effect estimates (ESs); dashed lines represent 95% confidence intervals (CIs).
    Figure 4. Forest plots of the prospective cohort studies of cardiovascular disease mortality for high versus low tea consumption. ES, effect estimate; CI, confidence interval.
    Figure 5. Pooled dose-response association between tea consumption and cardiovascular disease (CVD) mortality. Solid lines represent effect estimates (ESs); dashed lines represent 95% confidence intervals (CIs).
    Figure 6. Forest plots of the prospective cohort studies of cancer mortality for high versus low tea consumption. ES, effect estimate; CI, confidence interval.
    Figure 7. Pooled dose-response association between tea consumption and cancer mortality. Solid lines represent effect estimates (ESs); dashed lines represent 95% confidence intervals (CIs).
    Graphical abstract

    Figure 1.

    Figure 2.

    Figure 3.

    Figure 4.

    Figure 5.

    Figure 6.

    Figure 7.

    Graphical abstract

    Tea consumption and risk of all-cause, cardiovascular disease, and cancer mortality: a meta-analysis of thirty-eight prospective cohort data sets
    Study Country Cohort name Follow-up period (yr) Age at baseline (yr) Study size
    		 Gender Tea consumption Cause of death Adjustment for covariates
    Subjects No. of deaths
    Kahn et al., 1984 [6] USA Seventh-Day Adventists 21 ≥30 21,022 5,679 Men and women <1 vs. ≥1 cup/day All causes Age, gender, smoking history, history of heart disease, stroke, hypertension, diabetes, or cancer; age at initial exposure to the Adventist Church
    Hertog et al., 1993 [7] Netherlands Zutphen Elderly Study 5 65-84 805 43 Men 0-250 vs. >500 mL/day CHD Age, intake of total energy, saturated fatty acids, cholesterol, alcohol, coffee, vitamin C, vitamin E, beta-carotene, dietary fiber, history of myocardial infarction, BMI, smoking, serum total and HDL cholesterol, systolic blood pressure
    Klatsky et al., 1993 [8] USA Northern California Kaiser Permanente Medical Care Program 8 N/A 125,356 4,208 Men and women 0 vs. ≥4 cup/day All causes Age, gender, BMI, smoking, alcohol, race, education, marital status
    Hertog et al., 1997 [9] UK Caerphilly study 14 45-59 1,900 3383 Men 0-300 vs. >1,200 mL/day All causes Age, smoking, social class, BMI, intakes of total energy, alcohol, fat, vitamin C, vitamin E, and β-carotene
    1044 Cancer
    Woodward et al., 1999 [10] Scotland Scottish Heart Health Study 7.7 40-59 11,507 5883 Men and women 0 vs. ≥5 cup/day All causes Age, housing tenure, activity at work, activity in leisure, cigarette smoking status, BMI, Bortner score, cotinine, systolic blood pressure, fibrinogen, total cholesterol, HDL cholesterol, triglycerides, alcohol, vitamin C, and coffee
    2065 CHD
    Nakachi et al., 2000 [11] Japan Saitama 11 >40 8,552 222 Men and women ≤3 vs. ≥10 cup/day CVD Age, cigarette smoking, alcohol consumption, intake of meat, and relative body weight
    Prefecture
    Hirvonen et al., 2001 [12] Finland Alpha-Tocopherol, Beta-Carotene Cancer Prevention 6.1 50-69 25,372 815 Men <1 vs. ≥1 cup/day CVD Age, supplementation group, systolic and diastolic blood pressure, serum total cholesterol, serum HDL cholesterol, BMI, smoking years, number of cigarettes smoked daily, history of diabetes mellitus and CHD, marital status, education, leisure-time physical activity
    Study
    Iwai et al., 2002 [13] Japan Tottori Prefecture 9.9 40-79 2,855 3613 Men and women <0.5 vs. ≥4 cup/day All causes Age, smoking, alcohol, history of selected diseases, physical activity, educational status
    614 Cancer
    Khan et al., 2004 [14] Japan Hokkaido 13.8 ≥40 3,158 244 Men and women Never+several times/yr+several times/mo vs. several times/wk+daily Cancer Age, health education, health examination, health status, smoking
    Prefecture
    Andersen et al., 2006 [15] USA Iowa Woman’s Health Study 15 55-69 27,312 4,2653 Women 0 vs. >3 cup/day All causes Age, smoking, intake of alcohol, BMI, waist-hip ratio, education, physical activity, use of estrogens, use of multivitamin supplements, energy intake, and intakes of whole and refined grain, red meat, fish, seafood, total fruit and vegetables
    1,4116 CVD
    Paganini-Hill et al., 2007 [16] USA Leisure World Cohort Study 23 ≥44 13,624 11,386 Men and women 0 vs. ≥2 cup/day All causes Age, gender, smoking, exercise, BMI, alcohol intake, and histories of hypertension, angina, heart attack, stroke, diabetes, rheumatoid arthritis, and cancer
    Suzuki et al., 2009 [17] Japan Shizuoka Elderly Cohort 6 65-84 12,251 1,2243 Men and women <1 vs. ≥7 cup/day All causes Age, gender, smoking status, alcohol consumption, BMI, frequency of physical activity
    4056 CVD
    4004 Cancer
    de Koning Gans et al., 2010 [18] Netherlands European Prospective Investigation into Cancer and Nutrition-Netherlands (EPIC-NL), MORGEN 13 20-69 37,514 1,4053 Men and women <1 vs. >6 cup/day All causes Age, gender, cohort (strata), education, physical activity, smoking status, waist circumference, menopausal status, alcohol, coffee, vitamin C, level, fiber, consumption, energy, saturated fat
    1236 CVD
    Mineharu et al., 2011 [19] Japan Japan Collaborative Cohort Study for Evaluation of Cancer Risk (JACC) 13.1 40-79 82,655 3,125 Men and women <1 cup/wk vs. ≥6 cup/day CVD Age, BMI, smoking status, alcohol intake, history of hypertension, history of diabetes, education, waking hours, hours of sports participation, perceived mental stress, multivitamin use, vitamin E supplement use; total consumption of fruits, vegetables, beans, meat, and fish; and total daily energy intake
    Bertoia et al., 2013 [20] USA Women’s Health Initiative Observational Study (WHI) 11 50–79 92,847 205 Women 0 vs. ≥4 cup/day CVD Age, total energy intake, race, income, smoking status, physical activity, waist-to-hip ratio, BMI, atrial fibrillation, coronary artery disease, heart failure, diabetes, high cholesterol, hypertension, pulse in 60 seconds, and hormone use
    Gardner et al., 2013 [21] USA Northern Manhattan Study 11 >40 2,461 8633 Men and women 1 cup/mo vs. ≥2 cup/day All causes Age, gender, BMI, race, education, pack-years of smoking, alcohol consumption, energy, protein, carbohydrates, total fat, saturated fat, history of vascular risk factors, other non-water beverage consumption, coffee additives (milk, cream, nondairy creamer), coffee
    3426 CVD
    1604 Cancer
    Liu et al., 2016 [22] China Chinese Prospective Smoking Study 11 >40 164,681 32,700 Men 0 vs. >10 g/day All causes Age, BMI, marital status, urban locality, education, job status, smoking status, alcohol drinking; times of weekly consumption for fish, meat, poultry consumption, egg, and milk; black tea drinker, jasmine tea drinker, other tea drinker
    CVD
    Cancer
    Ivey et al., 2017 [23] USA Nurses’ Health Study II 18 25-42 93,145 1,8943 Women 0 vs. >1 time/wk All causes Age, BMI, smoking status, menopausal status, family history (of diabetes, cancer, and myocardial infarction), multivitamin supplement use, aspirin use, race, type 2 diabetes, hypercholesterolemia, hypertension, physical activity, energy intake, alcohol consumption, and the Alternative Health Eating Index (minus alcohol) score
    1896 CVD
    8874 Cancer
    Lim et al., 2017 [24] Australia Calcium Intake Fracture Outcome Study 10 ≥70 1,055 3623 Women 1 cup/day increment All causes Age, smoking history, SES, diabetes status, hypertension, blood pressure, prevalent CVD, medications and treatment code (calcium supplementation vs. no calcium supplementation), fluid status, BMI, estimated glomerular filtration rate
    1426 CVD
    Yan et al., 2017 [25] USA Aerobics Center Longitudinal Study 16 20-82 11,808 8423 Men and women 0 vs. >14 cup/wk All causes Age, gender, baseline examination year, regular coffee use, decaffeinated coffee use, herbal tea use, physical inactivity, BMI, smoking, alcohol consumption, metabolic equivalents
    2506 CVD
    3454 Cancer
    van den Brandt, 2018 [26] Netherlands Netherlands Cohort Study (NLCS) 10 55-69 120,852 8,6653 Men and women 0 vs. ≥5 cup/day All causes Age, cigarette smoking status, number of cigarettes smoked per day, years of smoking, history of physician-diagnosed hypertension and diabetes, body height, BMI, non-occupational physical activity, highest level of education, intake of alcohol, nuts, vegetables and fruit, tea, energy, use of nutritional supplements, postmenopausal hormone replacement therapy (in women)
    2,9276 CVD
    3,8494 Cancer
    Wang et al., 2020 [27] China China-PAR project (3 cohorts)1 7.3 52, mean 100,902 5,4793 Men and women <3 vs. ≥3 time/wk All causes Age, gender, region, residential area, cohort, educational level, family history of atherosclerotic CVD, smoking, drinking, physical activity level, dietary factors, BMI, systolic blood pressure, fasting blood glucose, total cholesterol, HDL cholesterol
    1,4776 CVD
    Teramoto et al., 2021 [32] Japan Japan Collaborative Cohort Study for Evaluation of Cancer Risk (JACC) 18.5 40-79 44,521 8,666 Men and women 0 vs. ≥7 cup/day All causes Age, gender, coffee consumption, history of hypertension, history of diabetes, BMI, smoking status, alcohol consumption, hours of exercise, hours of walking, perceived mental stress, educational level, regular employment, dietary intakes of vegetable, fish, fruits, and soybeans
    Chen et al., 2022 [28] UK UK Biobank 12.1 37-73 498,158 34,6993 Men and women 0 vs. ≥5 cup/day All causes Age, gender, ethnicity, educational level, BMI, smoking status, alcohol intake frequency, physical activity, dietary pattern, general health status, hypertension, diabetes, depression, coffee consumption
    6,6636 CVD
    Inoue-Choi et al., 2022 [29] UK UK Biobank 11.2 40-69 498,043 15,790 Men and women 0 vs. ≥10 cup/day Cancer Age, gender, race and ethnicity, Townsend deprivation score, general health status, cancer, CVD, diabetes, BMI, tobacco smoking, physical activity, alcohol intake, coffee intake; dietary intake including vegetables, fruits, red meat, and processed meat; assessment centers
    Shin et al., 2022 [30] Asia Asia Cohort Consortium (12 cohorts)2 6.5-22.7 54.3 mean 528,504 94,7443 Men and women 0 vs. ≥5 cup/day All causes Age, BMI, smoking status, alcohol intake, educational level, energy intake, coffee consumption
    22,8506 CVD
    27,2074 Cancer
    Qiu et al., 2023 [31] China China Health and Nutrition Survey (CHNS) 17.9 54.4 mean 6,387 580 Men and women 0 vs. 3-4 cup/day All causes Age, gender, marital status, educational level, nationality, residential area, smoking status, occupation, level of annual income, mean systolic blood pressure, mean BMI, mean waist and hip circumferences, hypertension, diabetes mellitus, myocardial infarction, stroke, malignant tumor
    Variables No. of studies ES (95% CI) p for difference
    All-cause mortality
     High vs. low tea consumption
     All studies 20 0.90 (0.86, 0.95)
     Stratified by gender
      Men 8 0.87 (0.77, 0.98) 0.97
      Women 9 0.90 (0.79, 1.01)
     Stratified by geographical region
      Asia 7 0.84 (0.77, 0.91)
      USA 7 0.92 (0.83, 1.02) 0.321
      Europe 5 1.12 (0.88, 1.42) 0.051
      Oceania 1 0.92 (0.86, 0.98) 0.571
     Stratified by follow-up years
      ≥Median 10 0.96 (0.88, 1.05) 0.17
      <Median 10 0.86 (0.81, 0.92)
     Stratified by no. of subjects
      ≥Median 10 0.89 (0.85, 0.94) 0.87
      <Median 10 0.91 (0.80, 1.04)
    CVD mortality
     High vs. low tea consumption
     All studies 18 0.86 (0.79, 0.94)
     Stratified by gender
      Men 10 0.84 (0.71, 0.99) 0.83
      Women 11 0.86 (0.75, 0.99)
     Stratified by geographical region
      Asia 6 0.75 (0.65, 0.88)
      USA 5 0.91 (0.72, 1.14) 0.312
      Europe 6 1.00 (0.78, 1.26) 0.172
      Oceania 1 0.90 (0.79, 0.94) 0.552
     Stratified by follow-up years
      ≥Median 11 0.86 (0.80, 0.92) 0.76
      <Median 7 0.84 (0.68, 1.03)
     Stratified by no. of subjects
      ≥Median 9 0.84 (0.79, 0.89) 0.76
      <Median 9 0.84 (0.69, 1.03)
    Cancer mortality
     High vs. low tea consumption
     All studies 11 0.90 (0.78, 1.03)
     Stratified by gender
      Men 7 0.91 (0.77, 1.09) 0.93
      Women 5 0.93 (0.70, 1.23)
     Stratified by geographical region
      Asia 5 0.92 (0.74, 1.15)
      USA 3 0.70 (0.46, 1.07) 0.253
      Europe 3 1.00 (0.80, 1.24) 0.643
     Stratified by follow-up years
      ≥Median 6 0.97 (0.82, 1.14) 0.24
      <Median 5 0.80 (0.70, 0.92)
     Stratified by no. of subjects
      ≥Median 6 0.88 (0.76, 1.03) 0.72
      <Median 5 0.94 (0.65, 1.35)
    Table 1. Characteristics of studies included in the meta-analysis of tea consumption and mortality from all causes, CVD, and cancer

    CVD, cardiovascular disease; CHD, coronary heart disease; BMI, body mass index; HDL, high-density lipoprotein; SES, socioeconomic status; N/A, not available.

    China 3 cohort is China Multi-Center Collaborative Study of Cardiovascular Epidemiology, International Collaborative Study of CVD in Asia, and Community Intervention of Metabolic Syndrome in China & Chinese Family Health Study.

    Asia Cohort Consortium includes Japan Public Health Center-based Prospective Study (JPHC) I, II, Miyagi Cohort, Ohsaki National Health Insurance Cohort Study, Life Span Study Cohort (RERF), 3 Prefecture Miyagi, 3 Prefecture Aichi, Seoul Male Cancer Cohort (Seoul Male), Korean Multi-center Cancer Cohort Study (KMCC), Shanghai Men’s Health Study (SMHS), Shanghai Women’s Health Study (SWHS), and Singapore Chinese Health Study (SCHS).

    Death from all causes.

    Death from cancer.

    Death from CHD.

    Death from CVD.

    Table 2. Summary of pooled ESs of mortality from all causes, CVD, and cancer by tea consumption

    ES, effect estimate; CVD, cardiovascular disease; CI, confidence interval.

    ESs of all-cause mortality for USA vs. Asia (p=0.32), Europe vs. Asia (p=0.05), and Oceania vs. Asia (p=0.57).

    ESs of CVD mortality for USA vs. Asia (p=0.31), Europe vs. Asia (p=0.17), and Oceania vs. Asia (p=0.55).

    ESs of cancer mortality for USA vs. Asia (p=0.25) and Europe vs. Asia (p=0.64).

    Table 1.

    Table 2.

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