(2022) 20:449
Chen et al. BMC Medicine
https://doi.org/10.1186/s12916-022-02636-2

Open Access

RESEARCH ARTICLE

Consumption of coffee and tea
with all‑cause and cause‑specific mortality:
a prospective cohort study
Yanchun Chen1†, Yuan Zhang1†, Mengnan Zhang1, Hongxi Yang2 and Yaogang Wang1*   

Abstract
Background: Previous studies suggested that moderate coffee and tea consumption are associated with lower
risk of mortality. However, the association between the combination of coffee and tea consumption with the risk ofmortality remains unclear. This study aimed to evaluate the separate and combined associations of coffee and tea
consumption with all-cause and cause-specific mortality.
Methods: This prospective cohort study included 498,158 participants (37–73 years) from the UK Biobank between
2006 and 2010. Coffee and tea consumption were assessed at baseline using a self-reported questionnaire. All-cause
and cause-specific mortalities, including cardiovascular disease (CVD), respiratory disease, and digestive disease mortality, were obtained from the national death registries. Cox regression analyses were conducted to estimate hazard
ratios (HRs) and 95% confidence intervals (CIs).
Results: After a median follow-up of 12.1 years, 34,699 deaths were identified. The associations of coffee and tea
consumption with all-cause and cause-specific mortality attributable to CVD, respiratory disease, and digestive
disease were nonlinear (all P nonlinear < 0.001). The association between separate coffee consumption and the risk of
all-cause mortality was J-shaped, whereas that of separate tea consumption was reverse J-shaped. Drinking one cupof coffee or three cups of tea per day seemed to link with the lowest risk of mortality. In joint analyses, compared toneither coffee nor tea consumption, the combination of < 1–2 cups/day of coffee and 2–4 cups/day of tea had lower
mortality risks for all-cause (HR, 0.78; 95% CI: 0.73–0.85), CVD (HR, 0.76; 95% CI: 0.64–0.91), and respiratory disease (HR,0.69; 95% CI: 0.57–0.83) mortality. Nevertheless, the lowest HR (95% CI) of drinking both < 1–2 cup/day of coffee and≥ 5 cups/day of tea for digestive disease mortality was 0.42 (0.34–0.53).
Conclusions: In this large prospective study, separate and combined coffee and tea consumption were inversely
associated with all-cause and cause-specific mortality.
Keywords: Coffee consumption, Tea consumption, All-cause mortality, Cause-specific mortality, Prospective study†

Yanchun Chen and Yuan Zhang contributed equally to this manuscript.

*Correspondence: wangyg@tmu.edu.cn
1School of Public Health, Tianjin Medical University, Qixiangtai Road 22,
Heping District, Tianjin 300070, China
Full list of author information is available at the end of the article

Background
Globally, coffee and tea are among the most widely consumed beverages and become part of people’s dietary
patterns [1]. Epidemiologic studies have found that
separate coffee and tea consumption were associatedwith non-communicable diseases, like cardiovasculardisease (CVD), type 2 diabetes, and esophageal cancer[2–4]. Accumulating evidence suggests that separate© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of thislicence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. The Creative Commons Public Domain Dedication waiver (http://​creat​iveco​
mmons.​org/​publi​cdoma​in/​zero/1.​0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Chen et al. BMC Medicine(2022) 20:449

coffee and tea consumption are associated with mortality[5–10]; however, the shape of the association is controversial, since studies have found that there are different
types of U-shaped, J-shaped, linear, or null associations
between separate coffee and tea consumption and mortality [6–8]. Montagnana et al. reported a U-shaped
association between coffee and mortality, with the highest risk at intermediate consumption (2 to 4 cups/day)[9], while another study revealed that coffee consumption was inversely associated with mortality even among
those who drank 8 or more cups/day [10]. Given coffee
and tea drinking are often considered unhealthy lifestyles
because of the caffeine they contain [11], identifying
the effect of coffee and tea on mortality requires further
study.
Of note, emerging evidence has confirmed the interaction between coffee and tea with lower risks of serious
diseases such as stroke and dementia [12, 13]. Up to now,
only one cohort study from the Japanese population has
examined the combination of coffee and tea consumption with the risk of mortality [14], and it was found thatthe combined effect of green tea and coffee on mortality
appeared to be additive in patients with type 2 diabetes.
However, this study is limited by the small sample size,
single evaluation of covariates (lifestyle, diet), and insufficient adjustment for important confounding factors.
Additionally, it remains unclear whether such findings
apply to other populations with different genetic andenvironmental backgrounds.
Therefore, this study aimed to examine the separate
and combined associations of coffee and tea consumption
with total and cause-specific mortality (including cardiovascular disease [CVD], respiratory disease, and digestive
disease) using data from a population-based longitudinalcohort of UK Biobank. Furthermore, we aimed to conduct stratification analyses according to important baseline factors, including various lifestyles and the presenceor absence of chronic diseases, to examine whether the
association between mortality and the joint exposures ofcoffee and tea varied by these factors.

Methods
Study design and population

The UK Biobank is a large-scale prospective study that
recruited 502,507 participants aged 37–73 years fromthe general population between 2006 and 2010 [15]. Participants attended 1 of 22 dedicated assessment centers
nationally across England, Wales, and Scotland where
they provided information on health-related aspects
through touch-screen questionnaires and physical measurements [16]. The details of the study design and methods have been described in previous studies [17]. In thepresent study, we excluded participants who were lost

Page 2 of 13

to follow-up (n = 1346) or with missing information oncoffee or tea consumption (n = 3003) at baseline, leaving
498,158 participants for the primary analysis (Additional
file 1: Fig. S1).
Assessment of coffee and tea consumption

The touchscreen questionnaire included part of a dietaryassessment of a series of common food and beverage
items. Participants were asked about their average intake
of coffee in the last year “How many cups of coffee doyou drink each day (including decaffeinated coffee)?” and“How many cups of tea do you drink each day (including black and green tea)?” Participants either selected thenumber of cups, “Less than 1,” “Do not know,” or “Prefer
not to answer.” If coffee and tea consumption exceeded
10 and 20 cups/day, respectively, then participants wereasked to confirm their answers.
Assessment of covariates

To guide covariates selection, we constructed a directed
acyclic graph (DAG) based on sociodemographic characteristics and a prior knowledge of potential confounding
factors associated with all-cause mortality [10, 18, 19].
Additional file 1: Fig. S2 shows the DAG depicted causal
relationships between measured variables in the current
analysis. The program of DAGitty was used to identify
the minimally sufficient adjustment set [20]. We used
the baseline touch-screen questionnaire to collect sociodemographic, behavioral, and other factors. Sociodemographic factors were documented including sex, age,
ethnicity (White, Asian or Asian British, Black or Black
British, and others), and education levels (college or university degree, upper secondary, lower secondary, vocational, and others). Behavioral factors included smoking
status (never, previous, and current), alcohol intake frequency (never, special occasions only, one to three times
a month, once or twice a week, three or four times a week,
daily or almost daily), physical activity (low, middle, andhigh, measured using the International Physical Activity Questionnaire [IPAQ]), and dietary pattern (healthy
and unhealthy, healthy diet was based on consumptionof at least 4 of 7 dietary components: fruits: ≥ 3 servings/day, vegetables: ≥ 3 servings/day, fish: ≥ 2 servings/
week, processed meats: ≤ 1 serving/week, unprocessed
red meats: ≤ 1.5 servings/week, whole grains: ≥ 3 servings/day, refined grains: ≤ 1.5 servings/day) (Additional
file 1: Table S1) [21, 22]. Body mass index (BMI) (< 25, 25
to < 30, ≥ 30 kg/m2) was derived from physical measurement and calculated by dividing weight (kg) over height(m) squared. General health status was categorized as
excellent, good, fair, and poor. Information on chronic
diseases (e.g., hypertension, diabetes, and depression)

Chen et al. BMC Medicine(2022) 20:449

was collected from touchscreen questionnaires, medical
examinations, and hospital inpatient records.
Ascertainment of outcomes

Mortality information was obtained from death certificates, which were provided by the NHS Information Centre (England and Wales) and the NHS Central Register
Scotland (Scotland) for the date of death. International
Classification of Diseases (ICD-10) codes were used toclassify deaths from CVD (ICD 10 codes I00-I79), respiratory disease (ICD 10 codes J09-J18 and J40-J47), digestive disease (ICD 10 codes K20-K93), and other causes.
Statistical analyses

We summarized baseline characteristics according tocoffee and tea consumption categories as percentages for
categorical variables, while means with standard deviations (SDs) for normal continuous variables and medianand interquartile range (IQR) for non-normal variables.
Normality test was applied by Shapiro-Wilk normality test. Multiple imputations using the chained equations (MICE) method were performed to handle missing
covariates. Five imputed datasets were constructed andRubin’s rule was used to combine the results [23].
To assess the dose-response associations of separate
coffee and tea consumption with all-cause mortality
and cause-specific mortality, we used restricted cubic
splines models with 4 knots at the 25th, 50th, 75th, and95th centiles. Tests for linearity or nonlinearity used theWald test to calculate P-values, which was performed totest the null hypothesis that the coefficient of the second
spline is equal to 0 [24]. In our analysis, the null hypothesis was rejected (P < 0.05) and concluded that there wasa nonlinear relationship between separate coffee and tea
consumption with all-cause mortality and cause-specificmortality. In the spline models, we adjusted for potential confounders including sex, age, ethnicity, educationlevels, BMI, smoking status, alcohol intake frequency,
physical activity, dietary pattern, general health status,
hypertension, diabetes, and depression. Coffee and tea
consumption were mutually adjusted. Then, we divided
coffee and tea consumption into four groups using priorvalidated thresholds based on the restricted cubic splineof association between separate consumption of coffee
and tea with mortality. Participants who drank ≥ 5 cups/
day of coffee or tea were defined as excess consumption based on previous studies [25]. Finally, we defined
the categories as follows: coffee: none, < 1–2, 3–4, and≥ 5 cups/day; tea: none, < 1–1, 2–4, and ≥ 5 cups/day.
Cox proportional hazards models were used to estimate
the hazard ratios (HRs) and 95% confidence intervals(CIs) of separate coffee and tea consumption groups
with all-cause mortality and cause-specific mortality.

Page 3 of 13

Proportional hazard assumptions were verified using the
Schoenfeld residuals method, and no significant deviations were observed. Follow-up time was calculated fromthe date of questionnaire completion in which the baseline coffee and tea consumption were available, lost tofollow-up, death, or end of follow-up (23 March 2021),
whichever came first. The multi-adjusted models were
adjusted with the same covariates as the restricted cubic
spline. Furthermore, to quantify the magnitude of combined consumption of coffee and tea with mortality, participants were categorized into 16 groups according tocoffee and tea consumption categories, with participants
who had neither coffee nor tea consumption comprising
the reference group. Coffee consumption of < 1–2 cups/
day and tea consumption of 2–4 cups/day were combined into one category because these participants had
the highest proportion and the lowest mortality rate.
In addition, we performed subgroup analyses to assess
potential modification effects and determine whether
there was any population heterogeneity according to age,sex, BMI, physical activity, smoking status, alcohol intake
frequency, dietary pattern, hypertension, diabetes, anddepression. The interactions between baseline characteristics and combined coffee and tea consumption (combined < 1–2 cups/day of coffee and 2–4 cups/day of tea
vs. neither coffee nor tea consumption) were examinedusing the likelihood ratio test (LRT).
Sensitivity analysis

Additional analyses were further conducted. First,
we repeated the main analyses by excluding mortality cases that occurred in the first 3 years of follow-up.
Second, we conducted the main analyses using available
data before multiple imputations for missing covariates.
Third, because severe diseases could confound results,
we defined a population that excluded participants withprevalent CVD and cancer at baseline. Fourth, smoking
may have potential effect modification because there may
be unmeasured confounders between previous and current smokers. Therefore, we repeated the main analyses
adjusted for pack-years categories of cigarette smoking (nonsmokers: having smoked zero pack-years; lightsmokers: fewer than 20 pack-years; and heavy smokers:
20 or more pack-years). Pack-years of cigarette smoking were calculated as the number of cigarettes smoked
per day divided by 20 and then multiplied by the numberof years of smoking [26]. Fifth, the information on bothcoffee and tea consumption and potential confounders were collected at the baseline; it is very difficult toassess the role of depression in these associations. We
performed main analyses without adjusting for baseline
depression. Furthermore, we also investigated coffee andtea consumption interaction on mortality in the above

Chen et al. BMC Medicine(2022) 20:449

sensitivity analyses. All analyses were performed using
R (version 3.6.3, R Foundation for Statistical Computing)and STATA 15 statistical software (StataCorp). The twosided P < 0.05 was considered statistically significant.

Results
Characteristics of the study population

In total, 498,158 participants (median (IQR) age: 58 [5063]; 54% female) were included in this analysis. The proportion of < 1–2 cups/day of coffee and 2–4 cups/day oftea were 46.1% (n = 229,498) and 43.7% (n = 217,454),
respectively. Additional file 1: Fig. S3 shows the distribution for the combination of coffee and tea consumption.
Drinking both < 1–2 cups/day of coffee and 2–4 cups/
day of tea was more prevalent accounting for the largest proportion with 23.0% (n = 114,629). Table 1 presents
the baseline characteristics of participants according tocoffee and tea consumption. Compared with non-coffee
consumers, those who consumed < 1–2 cups/day of coffee were more likely to be older, male, white, non-drinker,
more likely to have a university education level, highphysical activity, healthy diet, and more likely to report“excellent” health; but they were less likely to be obese,
non-smoker, and less likely to have diabetes, hypertension, and depression. Likewise, as compared to non-tea
consumers, those who consumed 2–4 cups/day of tea
were more likely to be older, male, white, non-drinker,
more likely to have high physical activity, healthy diet,
hypertension, and more likely to report “excellent” health,but they were less likely to be obese, non-smoker, and lesslikely to have a university education level, diabetes, anddepression. Over 15 years of follow-up (median [IQR]
length of follow-up, 12.1 [11.4–12.8] years; total personyears, 5,900,033), we documented 34,699 (7.0%) deaths.
Among them, 6663 (1.3%) participants died from CVD,
6018 (1.2%) participants died from respiratory disease,and 2864 (0.6%) participants died from digestive disease.
Nonlinear association between separate coffee and tea
consumption with mortality

In Fig. 1, the dose-response relationship of separate
coffee and tea consumption with all-cause, CVD, respiratory disease, and digestive disease mortality weresignificantly nonlinear (all P-nonlinear < 0.001). A multivariable-adjusted model showed J-shaped associations
between separate coffee consumption with all-cause,
CVD, and respiratory disease mortality and separate
tea consumption with respiratory disease mortality.
The reverse J-shaped associations were observed forseparate tea consumption with all-cause and CVD mortality. The threshold consumption for the lowest mortality risk was about 1 cup/day of coffee and 3 cups/dayof tea. Particularly, reverse J-shaped associations were

Page 4 of 13

observed between separate coffee and tea consumption
with digestive disease mortality, and participants who
consumed about 5 cups/day of coffee and 6 cups/day oftea showed the lowest risk.
Separate coffee and tea consumption with mortality

To quantify the magnitude of relationships between
coffee and tea consumption with mortality, we categorized coffee (none, < 1–2, 3–4, and ≥ 5 cups/day) andtea (none, < 1–1, 2–4, and ≥ 5 cups/day) consumption
groups according to prior validated results of restrictedcubic spline analyses in the present study. After adjusting for potential confounders, < 1–2 cups/day of coffee
was inversely associated with a lower risk of health outcomes: 0.91 (0.88–0.93) for all-cause, 0.94 (0.88–1.00)
for CVD, and 0.84 (0.78–0.89) for respiratory diseasemortality (Table 2). Participants who drank 2–4 cups/
day of tea had a lower risk for all-cause (HR, 0.86; 95%
CI: 0.83–0.88), CVD (HR, 0.88; 95% CI: 0.81–0.94),
and respiratory disease mortality (HR, 0.80; 95% CI:
0.74–0.87). Additionally, we found that ≥ 5 cups/day ofcoffee (HR, 0.67; 95% CI: 0.59–0.77) and ≥ 5 cups/dayof tea (HR, 0.65; 95% CI: 0.58–0.73) showed the lowest
risk for digestive disease mortality, which was similar to
the results of restricted cubic splines.
Effects of combined coffee and tea consumption
on mortality

We further explored the relationship of the combined
associations of coffee and tea consumption with mortality. We found significant interactions between coffee and tea consumption with all-cause and digestive
disease mortality. (P for interaction < 0.01). As shownin Fig. 2 and Additional file 1: Table S2, for individuals with low coffee consumption, the increasing tea
consumption was almost linearly associated with allcause mortality, whereas for those with high coffee
consumption, the relationship was U-shaped. However,
the increasing coffee consumption showed a U-shaped
relationship with all-cause mortality for those with low
or high tea consumption. Specifically, compared withthose who did not drink coffee and tea, participants
who drank both < 1–2 cups of coffee and 2–4 cups oftea per day were associated with a 22% lower risk for
all-cause (HR, 0.78; 95% CI: 0.73–0.85), 24% lower
risk for CVD (HR, 0.76; 95% CI: 0.64–0.91), and 31%
lower risk for respiratory disease mortality (HR, 0.69;
95% CI: 0.57–0.83). Nevertheless, the lowest HR (95%
CI) of drinking both < 1–2 cup/day of coffee and ≥ 5cups/day of tea for digestive disease mortality was 0.42
(0.34–0.53).

Chen et al. BMC Medicine(2022) 20:449

Page 5 of 13

Table 1 Baseline characteristics according to coffee and tea consumption
Characteristic

Coffee consumption (cups/day)

Tea consumption (cups/day)

None

< 1–2

3–4

≥5

None

< 1–1

2–4

≥5

Total

110,646 (22.2)

229,498 (46.1)

102,694 (20.6)

55,320 (11.1)

73,223 (14.7)

57,438 (11.5)

217,454 (43.7)

150,043 (30.1)

Age, median (IQR), year

56 (49–62)

59 (51–64)

58 (51–63)

57 (49–62)

56 (48–62)

56 (48–63)

58 (51–64)

58 (51–63)

Female64,412 (58.2)

127,729 (55.7)

52,750 (51.4)

26,246 (47.4)

41,350 (56.5)

29,958 (52.2)

118,940 (54.7)

80,889 (53.9)

College/university degree

30,021 (27.1)

79,979 (34.8)

36,493 (35.5)

16,436 (29.7)

23,198 (40.4)

73,844 (34.0)

43,535 (29.0)

23,198 (40.4)

Upper secondary

11,763 (10.6)

26,613 (11.6)

11,711 (11.4)

5997 (10.8)

7211 (12.6)

24,543 (11.3)

15,816 (10.5)

7211 (12.6)

Lower secondary

31,333 (28.3)

59,743 (26.0)

26,955 (26.2)

15,758 (28.5)

14,320 (24.9)

57,810 (26.6)

40,350 (26.9)

14,320 (24.9)

Vocational

7923 (7.2)

14,327 (6.2)

6585 (6.4)

4248 (7.7)

3186 (5.5)

13,755 (6.3)

11,222 (7.5)

3186 (5.5)

Others29,606 (26.8)

48,836 (21.3)

20,950 (20.4)

12,881 (23.3)

9523 (16.6)

47,502 (21.8)

39,120 (26.1)

9523 (16.6)

White

99,782 (90.2)

217,514 (94.8)

100,110 (97.5)

54,241 (98.0)

52,829 (92.0)

203,056 (93.4)

145,716 (97.1)

52,829 (92.0)

Asian/Asian British

5203 (4.7)

4910 (2.1)

807 (0.8)281 (0.5)1649 (2.9)

6928 (3.2)

1753 (1.2)

1649 (2.9)

Black/Black British

3417 (3.1)

3498 (1.5)

730 (0.7)261 (0.5)1642 (2.9)

3991 (1.8)

1005 (0.7)

1642 (2.9)

Others2244 (2.0)

3576 (1.6)

1047 (1.0)

537 (1.0)1318 (2.3)

3479 (1.6)

1569 (1.0)

1318 (2.3)< 25

36,251 (32.8)

80,076 (34.9)

30,886 (30.1)

14,455 (26.1)

18,952 (33.0)

73,452 (33.8)

48,043 (32.0)

18,952 (33.0)

25 to < 30

45,545 (41.2)

97,643 (42.5)

45,602 (44.4)

24,213 (43.8)

24,148 (42.0)

93,778 (43.1)

65,325 (43.5)

24,148 (42.0)≥ 30

28,850 (26.1)

51,779 (22.6)

26,206 (25.5)

16,652 (30.1)

14,338 (25.0)

50,224 (23.1)

36,675 (24.4)

14,338 (25.0)

Low

22,579 (20.4)

41,187 (17.9)

19,398 (18.9)

11,907 (21.5)

11,486 (20.0)

40,070 (18.4)

28,267 (18.8)

11,486 (20.0)

Middle43,656 (39.5)

95,257 (41.5)

42,526 (41.4)

21,547 (38.9)

23,770 (41.4)

90,245 (41.5)

59,957 (40.0)

23,770 (41.4)

High44,411 (40.1)

93,054 (40.5)

40,770 (39.7)

21,866 (39.5)

22,182 (38.6)

87,139 (40.1)

61,819 (41.2)

22,182 (38.6)

Never65,038 (58.8)

130,528 (56.9)

53,733 (52.3)

23,467 (42.4)

31,320 (54.5)

123,264 (56.7)

80,012 (53.3)

31,320 (54.5)

Previous

34,794 (31.4)

80,371 (35.0)

37,635 (36.6)

19,961 (36.1)

19,840 (34.5)

76,086 (35.0)

51,831 (34.5)

19,840 (34.5)

Current

10,814 (9.8)

18,599 (8.1)

11,326 (11.0)

11,892 (21.5)

6278 (10.9)

18,104 (8.3)

18,200 (12.1)

6278 (10.9)

Never

16,033 (14.5)

49,119 (21.4)

24,778 (24.1)

11,460 (20.7)

15,204 (20.8)

14,410 (25.1)

46,723 (21.5)

25,053 (16.7)

Special occasions only

19,469 (17.6)

56,404 (24.6)

26,768 (26.1)

12,304 (22.2)

14,603 (19.9)

13,544 (23.6)

53,378 (24.5)

33,420 (22.3)

One to three times a month

27,509 (24.9)

60,925 (26.5)

26,177 (25.5)

14,066 (25.4)

17,602 (24.0)

13,512 (23.5)

56,771 (26.1)

40,792 (27.2)

Once or twice a week

13,926 (12.6)

24,886 (10.8)

10,223 (10.0)6531 (11.8)

8482 (11.6)

5938 (10.3)

22,641 (10.4)

18,505 (12.3)

Three or four times a week

17,582 (15.9)

24,070 (10.5)

9239 (9.0)

6634 (12.0)9647 (13.2)

5940 (10.3)

22,339 (10.3)

19,599 (13.1)

Daily or almost daily

16,127 (14.6)

14,094 (6.1)

5509 (5.4)

4325 (7.8)

7685 (10.5)

4094 (7.1)

15,602 (7.2)

12,674 (8.4)

Excellent

15,864 (14.3)

39,346 (17.1)

18,172 (17.7)

8283 (15.0)

11,834 (16.2)

10,433 (18.2)

36,796 (16.9)

22,602 (15.1)

Good61,382 (55.5)

135,704 (59.1)

60,741 (59.1)

30,764 (55.6)

40,536 (55.4)

33,089 (57.6)

129,023 (59.3)

85,943 (57.3)

Fair26,455 (23.9)

45,511 (19.8)

20,069 (19.5)

13,108 (23.7)

16,616 (22.7)

11,457 (19.9)

43,352 (19.9)

33,718 (22.5)

Poor6945 (6.3)

8937 (3.9)

3712 (3.6)

3165 (5.7)

4237 (5.8)

2459 (4.3)

8283 (3.8)

7780 (5.2)

Unhealthy

62,139 (56.2)

127,531 (55.6)

58,913 (57.4)

33,628 (60.8)

42,795 (58.4)

33,271 (57.9)

120,774 (55.5)

85,371 (56.9)

Healthy

48,507 (43.8)

101,967 (44.4)

43,781 (42.6)

21,692 (39.2)

30,428 (41.6)

24,167 (42.1)

96,680 (44.5)

64,672 (43.1)

No104,157 (94.1)

218,198 (95.1)

97,350 (94.8)

52,086 (94.2)

68,596 (93.7)

54,341 (94.6)

206,292 (94.9)

142,562 (95.0)

Yes6489 (5.9)

11,300 (4.9)

5344 (5.2)

3234 (5.8)

4627 (6.3)

3097 (5.4)

11,162 (5.1)

7481 (5.0)

No

79,133 (71.5)

166,543 (72.6)

75,328 (73.4)

40,832 (73.8)

53,371 (72.9)

42,392 (73.8)

157,500 (72.4)

108,573 (72.4)

Yes

31,513 (28.5)

62,955 (27.4)

27,366 (26.6)

14,488 (26.2)

19,852 (27.1)

15,046 (26.2)

59,954 (27.6)

41,470 (27.6)

No

101,860 (92.1)

216,965 (94.5)

97,530 (95.0)

51,269 (92.7)

68,280 (93.2)

53,979 (94.0)

205,218 (94.4)

140,147 (93.4)

Yes

8786 (7.9)

12,533 (5.5)

5164 (5.0)

4051 (7.3)

4943 (6.8)

3459 (6.0)

12,236 (5.6)

9896 (6.6)

Education level

Ethnicity

BMI (kg/m2)

Physical activity

Smoking status

Alcohol intake frequency

Self-reported health

Diet pattern

Diabetes

Hypertension

Depression

Abbreviations: BMI body mass index (calculated as weight in kilograms divided by height in meters squared); IQR interquartile range (75th quartile minus 25th quartile)

Chen et al. BMC Medicine(2022) 20:449

Page 6 of 13

Fig. 1 Restricted spline curve for associations of coffee and tea consumption with all-cause and cause-specific mortality. Models were adjusted
for sex, age, ethnicity, education levels, BMI, smoking status, alcohol intake frequency, physical activity, dietary pattern, general health status,
hypertension, diabetes, and depression. Coffee and tea consumption were mutually adjusted

Chen et al. BMC Medicine(2022) 20:449

Page 7 of 13

Table 2 HRs and 95% CIs of individual coffee and tea consumption for all-cause and cause-specific mortality
Cause ofdeathAllparticipants

Coffee consumption (cups/day)

Tea consumption (cups/day)None(N = 110,646)< 1–2(N = 229,498)

3–4(N = 102,694)≥5(N = 55,320)

None(N = 73,223)< 1–1(N = 57,438)

2–4(N = 217,454)≥5(N = 150,043)

34,6997963 (22.95)

15,023 (43.30)

7124 (20.53)4589 (13.23)

5681 (16.37)

3744 (10.79)

14,206 (40.94)

11,068 (31.90)

Model

1.00 (Ref.)

0.80 (0.78–0.83)

0.84 (0.81–0.86)

1.03 (0.99–1.07) 1.00 (Ref.)

0.84 (0.80–0.87) 0.77 (0.75–0.80)

0.86 (0.83–0.89)

Model

1.00 (Ref.)

0.91 (0.88–0.93)

0.92 (0.89–0.95)

0.97 (0.93–1.01) 1.00 (Ref.)

0.92 (0.88–0.96) 0.86 (0.83–0.88)

0.87 (0.84–0.90)1528 (22.93)

2854 (42.83)

1366 (20.50)

915 (13.73)

731 (10.97)

2078 (31.19)

Model

1.00 (Ref.)

0.79 (0.74–0.84)

0.81 (0.75–0.88)

1.02 (0.94–1.12) 1.00 (Ref.)

0.84 (0.76–0.92) 0.77 (0.71–0.83)

0.82 (0.75–0.88)

Model

1.00 (Ref.)

0.94 (0.88–1.00)

0.96 (0.89–1.04)

1.04 (0.95–1.14) 1.00 (Ref.)

0.94 (0.85–1.03) 0.88 (0.81–0.94)

0.87 (0.80–0.94)

1532 (25.46)

2354 (39.12)

1173 (19.49)

959 (15.94)

549 (9.12)

2144 (35.63)

Model

1.00 (Ref.)

0.67 (0.63–0.71)

0.75 (0.69–0.81)

1.16 (1.06–1.26) 1.00 (Ref.)

0.68 (0.61–0.75) 0.69 (0.64–0.75)

0.92 (0.85–0.99)

Model

1.00 (Ref.)

0.84 (0.78–0.89)

0.90 (0.83–0.98)

1.06 (0.97–1.16) 1.00 (Ref.)

0.80 (0.72–0.88) 0.80 (0.74–0.87)

0.91 (0.84–0.99)

768 (26.82)

1189 (41.52)

544 (18.99)

363 (12.67)

351 (12.26)

825 (28.81)

Model

1.00 (Ref.)

0.66 (0.60–0.72)

0.60 (0.54–0.68)

0.72 (0.63–0.82) 1.00 (Ref.)

0.84 (0.73–0.96) 0.65 (0.58–0.72)

0.61 (0.55–0.69)

Model

1.00 (Ref.)

0.78 (0.71–0.86)

0.69 (0.62–0.78)

0.67 (0.59–0.77) 1.00 (Ref.)

0.95 (0.83–1.09) 0.76 (0.68–0.85)

0.65 (0.58–0.73)

All causes
No. ofdeaths (%)­1a­2b

Cardiovascular disease
No. ofdeaths (%)
1­ a
2­ b

6663

1106 (16.60)

2748 (41.24)

Respiratory disease
No. ofdeaths (%)
1­ a
2­ b

6018

1078 (17.91)

2247 (37.34)

Digestive disease
No. ofdeaths (%)
­1a
­2b

2864

533 (18.61)

1155 (40.33)

Abbreviations: HR hazard ratio; CI confidence intervalaAdjusted for sex and agebAdjusted for sex, age, ethnicity, education levels, BMI, smoking status, alcohol intake frequency, physical activity, dietary pattern, general health status, hypertension,
diabetes, and depression. Coffee and tea consumption were mutually adjusted

Subgroup analyses

Associations of separate coffee and tea consumption withall-cause and cause-specific mortality did not differ bysex, age, BMI, physical activity, smoking status, alcohol
intake frequency, dietary pattern, hypertension, diabetes,and depression (Additional file 1: Tables S3-S12). Figure 3
shows associations between the combined consumption of coffee and tea with mortality by subgroup analyses. Multivariable hazard ratios were calculated for total
and cause-specific mortality among study participants
who consumed < 1–2 cups/day of coffee and 2–4 cups/
day of tea compared to those who drank neither coffee
nor tea. In the analyses stratified by potential confounding factors for death, the inverse associations between
combined consumption of coffee and tea with mortality were presented in all subgroups. In terms of strata
of smoking status, the association was stronger among
current smoking participants than among never andprevious smoking participants (P for interaction = 0.01).

Similarly, a multiplicative interaction was also found in
the stratification of alcohol intake frequency (P for interaction = 0.002), and the HR of the group with low alcohol
intake frequency was lower than that of those with highalcohol intake frequency. The details of the combined
effects of coffee and tea consumption for each group wereshown in Additional file 1: Tables S3-S12, and the results
were not much altered with stratification by these factors.
Sensitivity analyses

The results were not apparently altered in the following sensitivity analyses. After excluding those who diedwithin 3 years, the association between separate andcombined coffee and tea consumption and all-cause
and cause-specific mortality remained significant (Additional file 1: Table S13). When the analyses were performed following the exclusion of all participants with
CVD and cancer at baseline, the results were not altered(Additional file 1: Table S14). When the analyses wereChen et al. BMC Medicine(2022) 20:449

Page 8 of 13

Fig. 2 Combined consumption of coffee and tea with all-cause and cause-specific mortality. Models were adjusted for sex, age, ethnicity,
education levels, BMI, smoking status, alcohol intake frequency, physical activity, dietary pattern, general health status, hypertension, diabetes, anddepression. *P < 0.05, **P < 0.01, ***P < 0.001

conducted after adjusting for pack-years categories ofcigarette smoking, the results were basically unchanged(Additional file 1: Table S15). The results also did notchange materially when the main analyses were conducted without adjusting for baseline depression(Additional file 1: Table S16). Moreover, the significant
interaction between coffee and tea consumption on allcause and digestive disease mortality remained in theabove analyses (P for interaction < 0.05). Furthermore,
the findings were similar when we repeated the analysis
using data that excluded the missing values of covariates rather than multiple imputations (Additional file 1:
Table S17).

Discussion
This large prospective study investigated the associations between separate and combined consumption ofcoffee and tea and mortality. We found that the association between separate coffee consumption and the riskof all-cause mortality was J-shaped, whereas that of separate tea consumption was reverse J-shaped. As comparedwith participants who drank neither coffee nor tea, those
who drank < 1–2 cups/day of coffee and 2–4 cups/day oftea had a 22% lower risk of mortality. Inverse associations
were also observed for CVD, respiratory disease, anddigestive disease mortality. Moreover, similar associations were sustained among all subgroups.
In recent decades, many prospective epidemiological studies have investigated the associations between
separate coffee and tea consumption with major causesof death, but the observed J-shaped and U-shaped associations remain controversial [27, 28]. A prospective
study conducted in the Health Examinees study revealed
that drinking > 3 cups/day of coffee was associated witha 21% lower risk for all-cause mortality [29]. Anotherstudy included 100,902 general Chinese adults showed
an inverse association between habitual tea drinkers andall-cause mortality compared with never or non-habitualtea drinkers [30]. Our findings are also consistent withprevious studies on CVD, respiratory disease, and digestive disease mortality [31–33]. The J-shaped association
observed in our study was inconsistent with a previous

Chen et al. BMC Medicine(2022) 20:449

study that reported excess coffee drinking (≥ 8 cups/day)
was still inversely associated with all-cause mortality in
the UK Biobank [10]. The heterogeneous findings may
be due to differences in study design, population inclusion, longer follow-up, and increased all-cause deathcases. The underlying mechanisms hypothesized to
explain the lack of further risk reduction for heavy coffee and tea drinking on mortality risk may be that caffeine, overlapping bioactive compounds to coffee andtea, could increase heart rate, blood pressure, and induce
insulin resistance [34]. Tannins in coffee and tea decreasecalcium and iron absorption, and coffee contains diterpenes that increase cholesterol levels in the blood [28,35]. Therefore, although excessive coffee and tea consumption were not associated with an increased risk ofdigestive disease mortality, the higher risk of all-cause
and other specific causes of mortality makes it imperative
to support the incorporation of moderate coffee and tea
consumption into the dietary pattern.
Beyond separate associations of coffee and tea consumption with mortality, the potential joint effect ofthese two key beverages remains largely unknown. Only
one study conducted in the Fukuoka Diabetes Registry
including 4923 patients (2790 men and 2133 women)with type 2 diabetes followed for 5.3 years revealed thatthe combined consumption of ≥ 2 cups/day of coffee and≥ 4 cups/day of green tea had 63% lowest risk for allcause mortality [14]. Although this analysis considered
the combined association and interaction effect of coffee
and tea consumption, some limitations merit consideration. First, the population size and follow-up time werelimited, which is prone to reverse causality. Second, theclassification of coffee and tea consumption in this study
was crude. We made a detailed classification of coffee
and tea consumption, which was able to accurately assess
the relationship with mortality. Third, this study focusedon patients with type 2 diabetes, and the dietary guidanceis difficult to generalize to the general population. In ourstudy, we found that the combination of < 1–2 cups/dayof coffee and 2–4 cups/day of tea had a 22% lower risk
for all-cause, 24% lower risk for CVD, and 31% lower risk
for respiratory disease mortality. Nevertheless, drinking
both < 1–2 cup/day of coffee and ≥ 5 cups/day of tea had
a 58% lower risk for digestive disease mortality. Futurestudies are needed to validate these results.
Several biological mechanisms have been hypothesized to explain why combined coffee and tea consumption is inversely associated with the risk of mortality.
First, coffee and tea, two popular refreshing beverages,
have overlapping bioactive components such as caffeine
and chlorogenic acid. They play a crucial role in antioxidants, anti-inflammation, lowering blood pressure, insulin resistance, and improving endothelial function [5, 36,

Page 9 of 1337]. The pathogenesis of most chronic diseases involved
these mechanisms. Second, some evidence that coffee
consumption was associated with inverse diseases, anddecaffeinated consumption did not change these associations [38]. It is therefore reasonable to think that different bioactive substances in coffee and tea also play aprotective role. In addition to caffeine and chlorogenic
acid, coffee also contains other compounds, such as trigonelline, melanoidins, magnesium, and cafestol, whichhave known anti-oxidant properties and may decreasemortality [39]. Tea contains unique compounds, such as
epicatechin, catechin, epigallocatechin-3-gallate (EGCG),
and other flavonoids. These can alleviate atherosclerosis, scavenge oxygen-free radicals, and attenuate inflammation [40–42]. Third, many studies have indicated thatcoffee and tea consumption are associated with a lower
risk of biological indicators related to mortality, such as
blood pressure, glucose, and triglycerides [43–45]. Therefore, biological indicators could be controlled to reduce
the risk of mortality, but their role in these associations
needs to be further studied. Fourth, several interpretations could explain the interaction of smoking and drinking. Smoking stimulates the metabolism and clearance of
caffeine, and thereby smokers have higher tolerance tocaffeine [46]. In other words, when consuming the sameamount of caffeine, nonsmokers have two to three times
higher plasma caffeine concentration than smokers [47].
For alcohol drinking, caffeine blocks the alcohol adenosine A1 receptor, which antagonizes the adverse effects ofalcohol [48]. Finally, the protective effect of coffee and tea
consumption was significant for digestive disease mortality. This is because the ingredients have the functionof secretion of bile acids, microbiome composition, andfecal output to improve the digestive system environment[49]. Future mechanistic work on the joint association
between coffee and tea consumption is needed before
more robust conclusions can be made.
The strengths of this study included the populationbased study design with a 15-year follow-up. To the bestof our knowledge, the present study is the first to assess
the combined associations of coffee and tea consumption
with mortality in the general population. More importantly, instead of assuming linearity between them, we
explored the dose-response relationship using restrictedcubic splines. We also examined the joint effect andinteraction between coffee and tea consumption, fully
adjusting for confounding factors. Despite the strengthsof the present study, several potential limitations shouldbe mentioned. First, data on coffee and tea consumption
were collected through self-reported questionnaires, andpotential response bias cannot be ruled out. Also, certain
baseline information is likely to vary with time during arather long follow-up period. Second, our conclusions

Chen et al. BMC Medicine(2022) 20:449

Page 10 of 13

Fig. 3 Multivariable HRs and 95% CIs of combined effect of coffee and tea consumption for all-cause and cause-specific mortality in subgroups.
Multivariable HRs for all-cause mortality among study participants who consumed combined < 1–2 cups/day of coffee and 2–4 cups/day of tea
versus those who drink neither coffee nor tea were adjusted for sex, age, ethnicity, education levels, BMI, smoking status, alcohol intake frequency,
physical activity, dietary pattern, general health status, hypertension, diabetes, and depression. *P for interaction between baseline characteristics
and combined consumption of coffee and tea with all-cause or cause-specific mortality. The risk estimates for other categories of combined
consumption of coffee and tea are shown in Table S3-S12 in the Supplementary Appendix

may be affected by reverse causation, although results
were similar after excluding the first 3 years of followup. Third, as with any observational study design, residual confounding is possible, especially for smoking.
Although we have adjusted for pack-years categories
of cigarette smoking, we could not avoid the possibility of residual effects due to unmeasured confounders
between former and current smokers. Fourth, due to thelarge sample size in our study, the significance we foundsuch as the interaction between coffee and tea consumption may be attained by chance, although similar results
were obtained in multiple sensitivity analyses. Finally, themajority of participants are of European descent in the
UK biobank, and they are more health-conscious than
the general population [50]. Caution is therefore needed
when generalizing our findings to other ethnicities.

Chen et al. BMC Medicine(2022) 20:449

Conclusions
Our results provided evidence that the association
between separate coffee consumption and the risk of allcause mortality was J-shaped, whereas that of separate
tea consumption was reverse J-shaped. Our findings do
not support that drinking excess coffee is inversely associated with mortality. Our study underscores that it isof vital significance to integrate < 1–2 cups/day of coffee and 2–4 cups/day of tea into diet patterns and healthmanagement programs if observed associations arecausal. Further studies are warranted to confirm our findings and clarify the potential mechanism by which combined coffee and tea consumption are associated withmortality.
Abbreviations
BMI: Body mass index; CI: Confidence intervals; CVD: Cardiovascular disease;
DAG: Directed acyclic graph; HR: Hazard ratio; ICD: International Classification of Diseases; IPAQ: The International Physical Activity Questionnaire; IQR:
Interquartile range; LRT: Likelihood ratio test; MICE: Multiple imputation using
chained equations.; SD: Standard deviation.

Supplementary Information
The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s12916-​022-​02636-2.
Additional file 1: Table S1. Diet component definitions used in the UK
Biobank study. Table S2. Multivariable HRs and 95% CIs of combined
effect of coffee and tea consumption on total and cause-specific mortality. Table S3. Multivariable HRs and 95% CIs of separate and combined
effect of coffee and tea consumption on total and cause-specific mortality
by sex. Table S4. Multivariable HRs and 95% CIs of separate and combined
effect of coffee and tea consumption on total and cause-specific mortality
by age group (<60 and ≥60 years). Table S5. Multivariable HRs and 95%
CIs of separate and combined effect of coffee and tea consumption on
total and cause-specific mortality by BMI. Table S6. Multivariable HRs and
95% CIs of separate and combined effect of coffee and tea consumption on total and cause-specific mortality by physical activity. Table S7.
Multivariable HRs and 95% CIs of separate and combined effect of coffee
and tea consumption on total and cause-specific mortality by smoking
status. Table S8. Multivariable HRs and 95% CIs of separate and combined
effect of coffee and tea consumption on total and cause-specific mortality
by alcohol intake frequency. Table S9. Multivariable HRs and 95% CIs of
separate and combined effect of coffee and tea consumption on total andcause-specific mortality by diet pattern. Table S10. Multivariable HRs and
95% CIs of separate and combined effect of coffee and tea consumption on total and cause-specific mortality by depression. Table S11.
Multivariable HRs and 95% CIs of separate and combined effect of coffee
and tea consumption on total and cause-specific mortality by diabetes.
Table S12. Multivariable HRs and 95% CIs of separate and combined
effect of coffee and tea consumption on total and cause-specific mortality
by hypertension. Table S13. Multivariable HRs and 95% CIs of separate and combined effect of coffee and tea consumption on total andcause-specific mortality after exclusion of first three years of follow-up.
Table S14. Multivariable HRs and 95% CIs of separate and combined
effect of coffee and tea consumption on total and cause-specific mortality after exclusion patients with prevalent CVD and cancer at baseline.
Table S15. Multivariable HRs and 95% CIs of separate and combined
effect of coffee and tea consumption on total and cause-specific mortality adjusted for pack-years categories of cigarette smoking at baseline.
Table S16. Multivariable HRs and 95% CIs of separate and combined
effect of coffee and tea consumption on total and cause-specific mortality
unadjusted for depression at baseline. Table S17. Multivariable HRs andPage 11 of 13

95% CIs of separate and combined effect of coffee and tea consumption
on total and cause-specific mortality using unimputed data. Figure S1.
Flowchart for the selection of the analyzed study sample from the UK
Biobank Study. Figure S2. Directed acyclic graph (DAG) derived fromprevious literature and expert knowledge. Figure S3. The distribution of
combination of coffee and tea consumption.
Acknowledgements
We thank the participants of the UK Biobank. This research has been conducted using the UK Biobank Resource under Application Number 45676.
Authors’ contributions
Y.W. conceptualized and designed the study. Y.W. and H.Y. had full access to all
data. Y.C. and Y.Z. performed the data analysis. Y.C. and Y.Z. drafted the manuscript. M.Z. contributed to analysis and interpretation of data. H.Y. contributed
to revision of the manuscript and approved the final draft. All authors contributed to the intellectual content, critical revisions to the drafts of the paper andapproved the final version.
Funding
Y.W. received grants from the National Natural Science Foundation of China(No. 71910107004) and National Natural Science Foundation of China (No.
91746205).
Availability of data and materials
The data that support the findings of this study are available from UK Biobank(https://​www.​ukbio​bank.​ac.​uk/), but restrictions apply to the availability ofthese data, which were used under license for the current study, and so are
not publicly available. Data are however available from the authors upon
reasonable request and with permission of UK Biobank.

Declarations
Ethics approval and consent to participate
UK Biobank has ethics approval from the North West Multi-Centre Research
Ethics Committee (11/NW/0382). Appropriate informed consent was obtained
from participants and ethical approval was covered by the UK Biobank. This
research has been conducted using the UK Biobank Resource under the
project number of 45676.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Author details
1
School of Public Health, Tianjin Medical University, Qixiangtai Road 22, Heping
District, Tianjin 300070, China. 2School of Basic Medical Sciences, Tianjin Medical
University, Qixiangtai Road 22, Heping District, Tianjin 300070, China.
Received: 18 July 2022 Accepted: 24 October 2022

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