Caffeine and Blood Pressure
Associations of Ambulatory Blood Pressure With Urinary
Caffeine and Caffeine Metabolite Excretions
Idris Guessous, Menno Pruijm, Belén Ponte, Daniel Ackermann, Georg Ehret, Nicolas Ansermot,
Philippe Vuistiner, Jan Staessen, Yumei Gu, Fred Paccaud, Markus Mohaupt, Bruno Vogt,
Antoinette Pechère-Bertschi, Pierre-Yves Martin, Michel Burnier, Chin B. Eap, Murielle Bochud
Downloaded from http://hyper.ahajournals.org/ by guest on March 22, 2018
Abstract—Intake of caffeinated beverages might be associated with reduced cardiovascular mortality possibly via the lowering
of blood pressure. We estimated the association of ambulatory blood pressure with urinary caffeine and caffeine metabolites
in a population-based sample. Families were randomly selected from the general population of Swiss cities. Ambulatory
blood pressure monitoring was conducted using validated devices. Urinary caffeine, paraxanthine, theophylline, and
theobromine excretions were measured in 24 hours urine using ultrahigh performance liquid chromatography tandem mass
spectrometry. We used mixed models to explore the associations of urinary excretions with blood pressure although adjusting
for major confounders. The 836 participants (48.9% men) included in this analysis had mean age of 47.8 and mean 24-hour
systolic and diastolic blood pressure of 120.1 and 78.0 mm Hg. For each doubling of caffeine excretion, 24-hour and nighttime systolic blood pressure decreased by 0.642 and 1.107 mm Hg (both P values <0.040). Similar inverse associations
were observed for paraxanthine and theophylline. Adjusted night-time systolic blood pressure in the first (lowest), second,
third, and fourth (highest) quartile of paraxanthine urinary excretions were 110.3, 107.3, 107.3, and 105.1 mm Hg,
respectively (P trend <0.05). No associations of urinary excretions with diastolic blood pressure were generally found,
and theobromine excretion was not associated with blood pressure. Anti-hypertensive therapy, diabetes mellitus, and
alcohol consumption modify the association of caffeine urinary excretion with systolic blood pressure. Ambulatory
systolic blood pressure was inversely associated with urinary excretions of caffeine and other caffeine metabolites. Our
results are compatible with a potential protective effect of caffeine on blood pressure. (Hypertension. 2015;65:691-696.
DOI: 10.1161/HYPERTENSIONAHA.114.04512.) Online Data Supplement
•
Key Words: ambulatory blood pressure ◼ caffeine ◼ paraxanthine ◼ population ◼ theophylline
H
ypertension is a major risk factor for cardiovascular disease
and results from a complex interplay between genetic and
environmental factors.1 Intake of caffeinated beverages might be
associated with lower cardiovascular mortality.2 Caffeine, >70%
of which is provided by coffee consumption,3 is metabolized by
the liver CYP1A2 enzyme into paraxanthine (≈80%), theobromine (≈12%), and theophylline (≈4%). Caffeine and caffeine
metabolites are methylxanthines: a family of nonspecific adenosine receptor antagonist with several properties, including diuretic
and natriuretic properties.4,5 The urinary excretion of caffeine and
caffeine metabolites is a valid measure of caffeine intake.6
The relation of blood pressure (BP) with caffeine and caffeine
metabolites is of major interest, given their widespread consumption in foods and beverages (eg, coffee, tea, cola drinks, chocolate
products) and the public health burden of high BP. Studies on the
effect of acute consumption of caffeine at dietary levels on BP
produced inconsistent results,7 with a recent study restricted to
nonsmokers showing a decrease in systolic BP (SBP).8 In a crosssectional study, high reported caffeine intake was associated with
a lower prevalence of hypertension only in nonsmokers.9
To date, studies on the association of caffeine and BP have
been limited by the use of reported caffeine intake instead of
Received August 27, 2014; first decision September 16, 2014; revision accepted November 7, 2014.
From the Unit of Population Epidemiology, Department of Community Medicine and Primary Care and Emergency Medicine (I.G.), Service of Nephrology,
Department of Specialties (B.P., P.-Y.M.), Department of Cardiology (G.E.), and Unit of Hypertension, Department of Community Medicine and Primary
Care and Emergency Medicine (I.G., A.P.-B.), University Hospital of Geneva, Switzerland; Institute of Social and Preventive Medicine (IUMSP) (I.G.,
B.P., G.E., P.V., F.P., M.B.), and Department of Medicine, Service of Nephrology (M.P., M.B.), University Hospital of Lausanne, Switzerland; Department
of Nephrology and Hypertension, Clinic for Nephrology, Hypertension and Clinical Pharmacology, Inselspital, Bern University Hospital and University of
Bern, Switzerland (D.A., M.M., B.V.); Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neurosciences, Department of
Psychiatry, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Hospital of Cery, Prilly, Switzerland (N.A., C.B.E.); Studies Coordinating
Centre, Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven, Department of Cardiovascular Sciences, University Leuven, Belgium
(J.S., Y.G.); Department of Epidemiology, Maastricht University, Maastricht, Netherlands (J.S.); and Department of Pharmaceutical Sciences, School of
Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland (C.B.E.).
This paper was sent to L. Gabriel Navar, Consulting Editor, for review by expert referees, editorial decision, and final disposition.
The online-only Data Supplement is available with this article at http://hyper.ahajournals.org/lookup/suppl/doi:10.1161/HYPERTENSIONAHA.
114.04512/-/DC1.
Correspondence to Murielle Bochud, Institute of Social and Preventive Medicine, Route de la Corniche 10, 1010 Lausanne, Switzerland, E-mail murielle.
bochud@chuv.ch or Idris Guessous, Unit of Population Epidemiology, Division of Primary Care Medicine, Department of Community Medicine, Primary
Care and Emergency Medicine, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, 1205 Geneva, Switzerland, E-mail idris.guessous@hcuge.ch
© 2014 American Heart Association, Inc.
Hypertension is available at http://hyper.ahajournals.org
DOI: 10.1161/HYPERTENSIONAHA.114.04512
691
692 Hypertension March 2015
measured caffeine and caffeine metabolites and the use of
office BP instead of ambulatory BP measurement (ABPM).10
Recognizing this, we aimed to analyze the associations
between ambulatory BP with urinary caffeine and caffeine
metabolites excretions in the general adult population with
the hypothesis that caffeine and metabolites excretions are
inversely associated with BP.
Methods
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SKIPOGH (Swiss Kidney Project on Genes in Hypertension) is a
family and population-based cross-sectional study that examines the
genetic determinants of BP. SKIPOGH is nested within the larger
family-based international EPOGH study (European Project on Genes
in Hypertension). SKIPOGH uses the same methods as that implemented and validated in the EPOGH study.11 SKIPOGH has been
described elsewhere.12,13 Briefly, SKIPOGH is a multicenter study
with participants being recruited in the cantons of Bern and Geneva
and the city of Lausanne. Recruitment began in December 2009 and
ended in April 2012 in Lausanne, in October 2012 in Geneva, and
in April 2013 in Bern. Index cases were randomly selected from the
population-based CoLaus study14 in Lausanne and from the population-based Bus Santé study in Geneva.15 In Bern, index participants
were randomly selected using the cantonal phone directory. The
SKIPOGH study was approved by the institutional ethical committees of the 3 participating university hospitals. All study participants
provided written informed consent. The study population included
1128 participants coming from 273 nuclear families.
Participants filled in a detailed health questionnaire at home and
attended the respective study centers in the morning where blood
samples were collected after an overnight fast. Participants were also
asked to collect a 24-hour urine sample, with separate day and night
collections, for the measurement of urinary volume and electrolytes.
Urinary sodium and potassium were measured using a Modular analyzer (Roche Diagnostics, Basel, Switzerland) in Lausanne and in
Bern, and using the UniCel DxC 800 (Beckman Coulter, California,
United States) in Geneva. Inter-center comparison based on 60 participants showed high Lin’s correlation (0.99–1.00 for urinary sodium and 0.93–0.99 for urinary potassium). The CKD-EPI formula
was used to calculate the estimated glomerular filtration rate.16 Body
weight and height were measured using precision electronic scales
(Seca™, Hamburg, Germany). Body mass index was calculated as
weight (kilogram) divided by height squared (meter). Diabetes mellitus was defined as a fasting glucose ≥7 mmol/L or presence of antidiabetic drug treatment (insulin or oral drugs). Participants were
defined as smokers if currently smoking, non smokers otherwise.
Ambulatory Blood Pressure
Twenty-four hour ABPM was measured using validated Diasys Integra
devices (Novacor, Rueil-Malmaison, France), which have fulfilled
validation criteria of the British Hypertension Society and Association
for the Advancement of Medical Instrumentation (AAMI) protocols.17
Measurements were taken every 15 minutes during the day and every
30 minutes during the night (from 10 pm to 7 am). Invalid BP values
were defined as SBP >280 mm Hg or <60 mm Hg, diastolic BP (DBP)
>200 mm Hg or <40 mm Hg, heart rate >200 bpm or <40 bpm, or DBP
≥SBP.18 We used the awake and asleep periods as reported by participants to define day and night. Mean BP readings were then calculated
using the valid 24-hour, daytime, and night-time measurements. The
mean (min–max) number of 24-hour, daytime, and night-time measurements were 68.5 (18–100), 50.6 (3–82), and 17.9 (2–33).
Urinary Caffeine and Caffeine Metabolites
Quantification of caffeine, paraxanthine, theobromine, and theophylline in urine samples was performed by ultrahigh performance liquid
chromatography (Waters ACQUITY UPLC I-Class) coupled to tandem mass spectrometry with electrospray ionization (Waters Xevo
TQ-S). Sample preparation was performed by simple dilution. Limit
of quantification was 10 ng/mL for caffeine, paraxanthine, and theophylline and 20 ng/mL for theobromine. The methods were fully
validated according to the latest international guidelines using a
stable isotope-labeled internal standard for each analyte. Expanded
uncertainty (95% confidence level) calculated during routine use of
the method was 8.2% for caffeine, 7.6% for paraxanthine, 7.8% for
theobromine, and 8.1% for theophylline, respectively (Ansermot et
al, manuscript in preparation, detailed method available on request).
Statistical Analysis
Continuous variables were described with mean or median and SD, SE,
or interquartile range. Categorical variables were described with percentages. Twenty-four hours caffeine and paraxanthine urinary excretions were categorized into quartiles and associations with ABPM tested
and illustrated. To satisfy normality assumptions, caffeine and caffeine
metabolites were log-transformed. Association sizes were expressed as
a 2-fold increase in the explanatory variables (without back transformation). Log base 2 was used so that the transformed beta coefficients can
be interpreted as the effect on BP when the excretion of caffeine, respectively, caffeine metabolites, is doubled. We used mixed linear models to
explore the associations of caffeine and caffeine metabolites levels with
ambulatory SBP and DBP, although adjusting for major confounders,
including sodium and potassium blood concentrations and 24-hour urinary excretions, and familial correlations. We used an independent covariance structure to accommodate familial dependencies. The estimations
of the standard errors for the fixed effect parameters were model-based.
Variables included in models as potential confounders were a priori
considered, given their reported or potential influence on BP, methylxanthines, or both. The following variables were included in the models
as potential confounders: age, sex, body mass index, oral contraceptive use, diabetes mellitus, current alcohol use and smoking, CKD-EPI
estimated glomerular filtration rate, antihypertensive therapy (based on
participants’ self-reports list of drugs), blood Na+ and K+, and Na+ and
K+ excretion. Models were further adjusted for study center to take into
account the potential clustering of caffeine excretion and BP measurements by center. Relationship between 24-hour, daytime, and night-time
SBP with 24-hour urinary excretions of caffeine and paraxanthine in
quartiles are presented. After verifying that the linearity of association failed to be rejected, linear trends by urinary excretion of caffeine
(respectively, paraxanthine) in quartiles (coded from 1 to 4) were tested
using multilevel mixed-effects linear regression and P values reported
(P for linear trend across quartiles). We also assessed the association of
24-hour, daytime, and night-time urinary caffeine and metabolites separately with the corresponding 24-hour, daytime, and night-time SBP
and DBP. The actual awake and asleep periods were used, as reported
by participants, to define daytime and night-time. BP and urine were,
respectively, monitored and collected during 24-hour. Daytime collection usually started between 6 am and 10 am and ended at reported
bedtime. Night-time collection started at bedtime and ended after the
first morning urine. Creatinine excretion per body weight (kg) and urine
volume were entered as covariates in sensitivity analysis models to
account for the quality of urine collections. Sensitivity analyses were
conducted to explore the association of ABPM with urinary caffeine
and its major metabolite, paraxanthine, by participants’ characteristics.
For these sensitivity analyses, medians of continuous variables were
used to categorize participants (except for body mass index and estimated glomerular filtration rate for which the general cutoff of 25 kg/m2
and 60 mL/min/1.73 m2 were used, respectively). Statistical interactions between participants’characteristics and urinary caffeine excretion were tested using Wald tests. Significant interaction product terms
were then included in the adjusted models. Given the apparent increased
association between caffeine urinary excretion and BP in adults with
antihypertensive therapy in preliminary analysis, stratified analyses by
antihypertensive therapy were performed. Statistical significances for
association and interaction were set at P value <0.05. Only those individuals for whom all covariates of interest for the purpose of this study
were available were included in the analysis. All analyses were conducted using Stata, version 12.0 (StataCorp LP, College Station, TX).
Results
Among the 4173 eligible subjects invited to participate in the
SKIPOGH study, 1128 (27.1%) participated and 836/1128
Guessous et al Ambulatory Blood Pressure and Urinary Caffeine 693
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(74%) were included in the analysis. The main reason for participants to be excluded from the analysis were missing data
on night-time BP (N=233) or day time BP (N=166), no data
on 24-hour Na+, K+, or caffeine urinary excretions (N=38).
Participants not included differed from participants included
by urinary methylxanthines excretions, urinary 24-hour
sodium excretion, smoking status, and night-time BP. Among
the participants included (Table 1), the overall mean (±SD) of
age, 24-hour SBP, and DBP were 47.8 (±17.5), 120.1 (±13.9)
mm Hg, and 78.0 (±8.6) mm Hg, respectively. Urinary excretions of caffeine, paraxanthine, theophylline, and theobromine
were highly skewed with medians of 3140.3, 10 177.5, 935.0,
and 11 134.6 μg/24-hour, respectively. Night-time methylxanthines excretions were lower than daytime excretions. Fifteen
percent were on antihypertensive therapy.
Figure presents, respectively, adjusted relationship of 24-hour,
daytime, and night-time SBP with caffeine and, respectively,
paraxanthine quartiles urinary excretions. Adjusted night-time
SBP in the first (lowest), second, third, and fourth (highest)
quartile of caffeine urinary excretions were 110.2 (0.9), 107.5
(0.9), 106.0 (0.9), and 106.2 (0.9) mm Hg, respectively. Adjusted
night-time SBP in the second, third, and fourth quartiles differed
significantly from the first (reference) quartiles. Adjusted nighttime SBP in the first (lowest), second, third, and fourth (highest) quartile of paraxanthine urinary excretions were 110.3 (0.9),
107.3 (0.9), 107.3 (0.9), and 105.1 (0.9) mm Hg, respectively.
Adjusted night-time SBP in the second, third, and fourth quartiles differed significantly from the first (reference) quartiles.
Table 2 displays the adjusted associations of 24-hour, daytime, and night-time SBP and DBP with urinary caffeine and
caffeine metabolite excretions, respectively. Log-transformed
urinary caffeine excretions were associated inversely with
24-hour and night-time ambulatory SBP. 24-hour and nighttime ambulatory SBP decreased by 0.642 (SE, 0.296) and
1.107 (0.315) mm Hg (both P values <0.040) for each doubling excretion of caffeine. Stronger inverse associations with
night-time ambulatory SBP were observed for paraxanthine
and theophylline. Night-time ambulatory SBP decreased by
1.376 (SE, 0.364) and 1.183 (0.363) mm Hg (both P values
<0.020) for each doubling excretion of paraxanthine and theophylline, respectively. No associations of theobromine levels
with 24-hour or night-time ambulatory SBP were observed.
No associations of 24-hour, daytime, or night-time diastolic
BP with 24-hour urinary excretions of caffeine, paraxanthine,
theophylline, or theobromine were generally found (Table 2).
Adjusted associations of 24-hour, daytime, and night-time
SBP and DBP separately with daytime and night-time urinary
caffeine and caffeine metabolite excretions are displayed in
Table S1 in the online-only Data Supplement. These separate
analyses showed that the associations of SBP with methylxanthines are generally driven by daytime methylxanthine excretions. In addition, DBP—especially 24-hour and daytime
DBP—appeared to be positively associated with night-time
excretions of caffeine, paraxanthine, and theophylline.
Table S2 in the online-only Data Supplement displays the
adjusted associations of 24-hour, daytime, and night-time SBP
and DBP with 24-hour urinary caffeine and caffeine metabolite
excretions by antihypertensive therapy status. Inverse associations were stronger among participants with antihypertensive
Table 1. Participants’ Characteristics, SKIPOGH Study
(N=836)
Charateristics
All (N=836, 100%)
Male sex, %
409 (48.9)
Smokers, %
188 (22.5)
Contraceptive use, % among women
347 (81.3)
Current alcohol use, %
532 (63.6)
Diabetes mellitus, %
38 (4.5)
Anti-hypertensive treatment, %
132 (15.8)
Age, mean (SD)
47.8 (17.5)
BMI, kg/m2, mean (SD)
24.9 (4.3)
eGFR (CKD-EPI), mL/min/1.72 m2 (SD)
96.4 (17.8)
Serum Na+, mmol/L (SD)
140.4 (2.5)
Serum K , mmol/L (SD)
+
4.1 (0.3)
24-hour Na+ urinary excretion (SD)
144.8 (62.7)
24-hour K+ urinary excretion (SD)
64.5 (22.9)
Urinary methylxanthine excretions
24-hour
Caffeine median (IQR), μg/24 h
3140.3 (3967.8)
Paraxanthine median (IQR), μg/24 h
10 177.5 (10 966.8)
Theophylline median (IQR), μg/24 h
935.0 (999.2)
Theobromine median (IQR), μg/24 h
11 134.6 (12 498.3)
Day time
Caffeine median (IQR), μg/d
Paraxanthine median (IQR), μg/d
2250.0 (3004.645)
6840.0 (7836.7)
Theophylline median (IQR), μg/d
600.7 (722.3)
Theobromine median (IQR), μg/d
6936.1 (8504.8)
Night-time
Caffeine median (IQR), μg/night
617.2 (1033.6)
Paraxanthine median (IQR), μg/night
2925.9 (3598.1)
Theophylline median (IQR), μg/night
288.5 (334.4)
Theobromine median (IQR), μg/night
3273.2 (4414.9)
Ambulatory blood pressure (mm Hg)
24-hour SBP (SD)
120.1 (13.9)
Day SBP (SD)
124.0 (14.7)
Night SBP (SD)
107.5 (14.4)
24-hour DBP (SD)
78.0 (8.6)
Day DBP (SD)
81.1 (9.6)
Night DBP (SD)
68.1 (8.3)
BMI indicates body mass index; DBP, diastolic blood pressure; IQR, interquartile
range; SBP, systolic blood pressure; SD, standard deviation; and SKIPOGH, Swiss
Kidney Project on Genes in Hypertension.
therapy than participants without antihypertensive therapy.
Twenty-four hour, daytime, and night-time ambulatory SBP
decreased by >3 mm Hg (all P values <0.005) for each doubling excretion of caffeine and caffeine metabolites (except
theobromine). Inverse associations among participants without
antihypertension therapy were found for night-time SBP.
Figures S1 in the online-only Data Supplement illustrates
the adjusted associations of 24-hour, daytime, and night-time
SBP with log-transformed urinary caffeine excretions for different participants’ characteristics. The associations of SBP with
urinary caffeine excretions were modified by antihypertensive
694 Hypertension March 2015
Figure. Adjusted associations (standard
error) of 24-hour, daytime, night-time
systolic blood pressure with quartiles of
24-hour urinary caffeine and paraxanthine
excretions (N=836). adjusted for age,
sex, body mass index, study center,
contraceptive use, diabetes mellitus, current
alcohol use, smoking, glomerular filtration
rate (CKD-EPI), blood Na+ and K+, and Na+
and K+ excretion.
Downloaded from http://hyper.ahajournals.org/ by guest on March 22, 2018
therapy, diabetes mellitus, and alcohol consumption. When these
3 interaction terms were all included in the adjusted models, all
3 interaction terms remained statistically significant with respect
to night-time SBP (P values for interaction <0.05), whereas only
antihypertensive and alcohol consumption modified the association of caffeine with both 24-hour and daytime SBP.
Discussion
In this population-based sample, we found that urinary caffeine, paraxanthine, and theophylline excretions were, in general, inversely associated with ambulatory SBP. To the best
of our knowledge, no previous population-based study has
Table 2. Adjusted Associations of Systolic and Diastolic
Ambulatory Blood Pressure With 24-Hour Urinary
Methylxanthines Excretions
Systolic BP
Methylxanthine
Diastolic BP
Beta, SE
P Value
Beta, SE
P Value
−0.642, 0.296
0.030
0.252, 0.182
0.166
Caffeine*
24 h
Day
−0.505, 0.313
0.107
0.342, 0.202
0.091
Night
−1.107, 0.315
<0.001
−0.074, 0.183
0.686
−0.718, 0.343
0.036
0.353, 0.211
0.094
Paraxanthine*
24 h
Day
−0.545, 0.362
0.132
0.442, 0.234
0.059
Night
−1.376, 0.364
<0.001
−0.039, 0.212
0.851
−0.633, 0.341
0.064
0.391, 0.209
0.062
Theophylline*
24 h
Day
−0.458, 0.360
0.204
0.530, 0.232
0.022
Night
−1.183, 0.363
0.001
−0.032, 0.211
0.881
24 h
0.302, 0.338
0.372
0.237, 0.208
0.254
Day
0.325, 0.357
0.363
0.263, 0.230
0.254
Night
0.003, 0.361
0.993
−0.015, 0.209
0.942
Theobromine*
Models are adjusted for age, sex, BMI, study center, contraceptive
use, diabetes mellitus, current alcohol use and smoking, GFR (CKD-EPI),
antihypertensive treatment, blood Na+ and K+, and Na+ and K+ excretion. P
values highlighted in bold are statistically significant (P<0.05). BMI indicates
body mass index; BP, blood pressure; and GFR, glomerular filtration rate.
*Log-transformed.
looked at the association of measured urinary caffeine and caffeine metabolites on ambulatory BP. Our results are compatible with a protective effect of caffeine on high BP and hence
on arterial hypertension.
Each doubling of the excretion of caffeine was associated
with a 0.6 mm Hg lower 24-hour ambulatory SBP. Studies
have shown that caffeine induces diuresis and natriuresis, and
animal models have shown that intact adenosine receptors are
required for the natriuretic action of caffeine.19 Natriuresis
associated with adenosine receptor blockade is thought to
be caused by inhibition of proximal tubular reabsorption.19
Further studies should ideally measure sodium proximal tubular reabsorption and determine its role in the caffeine–BP
relation. Other methylxanthine-related mechanisms possibly
involved include sympathomimetic effects, smooth muscle
relaxation, and phosphodiesterase inhibition.20,21
We found no consistent association of 24-hour caffeine and
caffeine metabolite excretions with DBP. Although the reason
of the differential associations of caffeine and caffeine metabolites on SBP and DBP is not entirely clear, it is compatible
with the hypothesis that methylxanthines influence BP via their
natriuretic property. Previous studies with 24-hour urine collection reported that Na+ excretion predominantly affect SBP and
generally not DBP.22,23 An experimental study that explored the
effects of acute caffeine on BP found no effect on DBP.24 It is also
possible that the adaptation of SBP and DBP to caffeine is different. DBP has been shown to adapt to repeated caffeine exposure, whereas SBP seems to consistently change in response to
caffeine.25,26 Interestingly, our additional analyses based on daytime and night-time excretions separately revealed that DBP—
especially 24-hour and daytime DBP—was in fact positively
associated with night-time excretions of caffeine, paraxanthine,
and theophylline. Although the reasons of the observed differential associations between SBP and DBP, on the one hand, and
between daytime and night-time methylxanthine excretions, on
the other hand, remained speculative, it may explain, in part, the
inconsistencies reported from previous studies that explored the
association of caffeine with BP or hypertension. Inverse associations of 24-hour caffeine and caffeine metabolite excretions with
SBP were strong during night-time. This could be explained, in
part, by the fact that night-time BP is less influenced by environmental factors than daytime (and therefore 24-hour) BP, a
Guessous et al Ambulatory Blood Pressure and Urinary Caffeine 695
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phenomenon previously reported in studies investigating the
genetics of hypertension.27 It is also possible that the inverse
association during daytime is blunted by an acute pressure effect
of caffeine intake during the morning. The stronger associations
of night-time BP than daytime BP with caffeine is of importance, given the increasing evidence that night-time BP provides
the greatest information regarding cariovascular risk.28
Similar results were observed for paraxanthine and theophylline. In fact, among all caffeine and caffeine metabolites,
strong inverse association of paraxanthine with SBP was found.
This is in line with the fact that paraxanthine is slightly more
potent than caffeine in antagonising the effects of adenosine.29
Although theobromine has also been shown to increase
natriuresis and to present similar properties than other methylxanthines,21 we found no significant association of theobromine with BP. Theobromine has one fifth the stimulant effect
of caffeine, and acute theobromine and caffeine intake have
previously been shown to exert opposite results on BP among
24 healthy female volunteers.30
Interaction analysis suggested that antihypertensive therapy, diabetes mellitus, and alcohol consumption modify the
association of caffeine urinary excretion with ambulatory
SBP. It is possible that the potential diuretic effect of methylxanthines provides a synergistic effect to antihypertensive
drugs. Of note, among participants with antihypertensive therapy, daytime SBP was also inversely associated with caffeine
urinary excretions. Previous systematic reviews and metaanalysis on the effect of caffeinated beverages on BP have not
stratified their analysis by diabetes mellitus status, and we are
not aware of previous studies showing a differential association of caffeine with BP among individuals with and without
type 2 diabetes mellitus.31 The particularly strong associations
in patients with antihypertensive therapy or diabetes mellitus
deserve to be further explored. The stronger inverse association observed in participants who reported no alcohol consumption than participants who reported alcohol consumption
is in line with previous evidence showing that long-term ethanol consumption masks the induction of CYP1A2 activity.32
The significant interactions further suggest that the association of caffeine with BP is modified by multiple factors.
All together, our results are compatible with a protective effect
of caffeine on BP. Although of major interest, definitive answer
on the relation of BP with caffeine is currently lacking.10 Also,
cumulative evidence from clinical trials suggests that the acute
and chronic effects of caffeine intake on BP may actually differ.33
Limitations and Strengths
The validity of caffeine and caffeine metabolites urinary excretion measurements depends on the quality of urine collection.
The mean urinary volume corrected for 24 hour, and creatinine
excretion corrected for body weight of the participants included
in the analysis suggested that the quality of urine collection
was satisfactory. Further adjustment for 24-hour urine volume
and creatinine excretion did not change the associations (data
not shown). Previous studies suggested that associations of
caffeinated beverages (ie, coffee intake) with cardiovascular
outcomes (ie, myocardial infarction) or risk factors (ie, hypertension) were modified by CYP1A2 genotype.9,34,35 Genetic
information was not available in the present analysis. Although
we considered major factors, the biological half-life of caffeine is highly variable among individuals (2–10 hours)36 and
is influenced by several genetic and nongenetic determinants
(eg, liver function) that we could not account for.
The cross-sectional nature of our study limits causal inference. Similarly, we cannot exclude reverse causality. Yet,
participants with antihypertensive therapy tended to have a
greater urinary caffeine excretion than participants without
antihypertensive therapy (3530.5 versus 3002.4 μg/24 h; P
value 0.058). Finally, we performed multiple comparisons,
and concern about false-positive associations could be raised.
Many comparisons were, however, correlated or subgroup
analysis (and thus need not be corrected) and all night-time
BP-related associations would remain significant using a conservative approach, such as the Bonferroni correction.37
Strengths of our study include its population-based nature,
the large sample size, the availability of ABPM, and the use of
a standardized protocol across 3 study centers. Studies have
shown that ambulatory BP is superior to office BP in predicting
future cardiovascular events and target organ damage.38 A large
number of compounds other than caffeine are present in coffee,
which limits the interpretation of many previous studies that
assessed the role of caffeine on BP based on self-reported coffee intake. In addition, the caffeine content of coffee is highly
variable.39 To better disentangle the role of caffeine per se on
BP, we directly measured caffeine and its main metabolites.
Perspectives
Ambulatory SBP was inversely associated with urinary caffeine and caffeine metabolites, paraxanthine and theophylline,
in adults from the general population. Given the ubiquitous
nature of caffeinated beverages and foods in the population,
our results may have important public health effect.
Acknowledgments
We are extremely grateful to the SKIPOGH (Swiss Kidney Project on
Genes in Hypertension) study participants.
Sources of Funding
The study is supported by the Swiss National Science Foundation FN
33CM30-124087 and FN 33CM30-140331.
Disclosures
None.
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Novelty and Significance
What Is New?
Summary
• No previous study has ever addressed in a population-based study wheth-
Results from this population-based study with 24-hour caffeine urinary excretion and ambulatory blood pressure are compatible with
a protective effect of caffeine on blood pressure.
er caffeine urinary excretion is associated with ambulatory blood pressure.
What Is Relevant?
• In our study, ambulatory systolic blood pressure was inversely associated with urinary excretions of caffeine and other caffeine metabolites.
Downloaded from http://hyper.ahajournals.org/ by guest on March 22, 2018
Associations of Ambulatory Blood Pressure With Urinary Caffeine and Caffeine
Metabolite Excretions
Idris Guessous, Menno Pruijm, Belén Ponte, Daniel Ackermann, Georg Ehret, Nicolas
Ansermot, Philippe Vuistiner, Jan Staessen, Yumei Gu, Fred Paccaud, Markus Mohaupt, Bruno
Vogt, Antoinette Pechère-Bertschi, Pierre-Yves Martin, Michel Burnier, Chin B. Eap and
Murielle Bochud
Hypertension. 2015;65:691-696; originally published online December 8, 2014;
doi: 10.1161/HYPERTENSIONAHA.114.04512
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Correction
In the article by Guessous et al (Guessous I, Pruijm M, Ponte B, Ackermann D, Ehret G, Ansermot
N, Vuistiner P, Staessen J, Gu Y, Paccaud F, Mohaupt M, Vogt B, Pechère-Bertschi A, Martin
PY, Burnier M, Eap CB, Bochud M. Associations of ambulatory blood pressure with urinary
caffeine and caffeine metabolite excretions. Hypertension. 2015;65:691–696. doi: 10.1161/
HYPERTENSIONAHA.114.04512), which published online ahead of print December 8, 2014,
and appeared in the March 2015 issue of the journal, a correction was needed.
One of the author surnames was misspelled. Antoinette Pechère-Berstchi has been corrected to
read Antoinette Pechère-Bertschi.
The authors apologize for this error.
This correction has been made to the print version and the current online version of the article,
which is available at http://hyper.ahajournals.org/content/65/3/691.full.
(Hypertension. 2016;67:e2. DOI: 10.1161/HYP.0000000000000039.)
© 2016 American Heart Association, Inc.
Hypertension is available at http://hyper.ahajournals.org
DOI: 10.1161/HYP.0000000000000039
e2
ONLINE SUPPLEMENT ASSOCIATIONS OF AMBULATORY BLOOD PRESSURE WITH URINARY CAFFEINE AND CAFFEINE METABOLITE EXCRETIONS Idris Guessous1,2,*, Menno Pruijm3, Belén Ponte2,4, Daniel Ackermann5, Georg Ehret2,6, Nicolas Ansermot7, Philippe Vuistiner2, Jan Staessen8,9, Yumei Gu 8, Fred Paccaud2, Markus Mohaupt 5, Bruno Vogt5, Antoinette Pechere‐Berstchi10, Pierre‐Yves Martin4, Michel Burnier3, Chin B Eap7,11, Murielle Bochud2,* Affiliations: 1) Unit of Population Epidemiology, Department of Community Medicine and Primary Care and Emergency Medicine, University Hospital of Geneva, Switzerland; 2) Institute of Social and Preventive Medicine (IUMSP), University Hospital of Lausanne, Switzerland; 3) Service of Nephrology, University Hospital of Lausanne, Switzerland; 4) Service of Nephrology, Department of Specialties, University Hospital of Geneva, Switzerland, 5) Clinic for Nephrology, Hypertension and Clinical Pharmacology, Inselspital, Bern University Hospital and University of Bern, Switzerland; 6) Department of Cardiology, University Hospital of Geneva, Switzerland; 7) Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neurosciences, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Hospital of Cery, Prilly, Switzerland; 8) Studies Coordinating Centre, Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven, Department of Cardiovascular Sciences, University Leuven, Belgium; 9) Department of Epidemiology, Maastricht University, Maastricht, Netherlands; 10) Unit of Hypertension, Department of Community Medicine and Primary Care and Emergency Medicine, University Hospital of Geneva, Switzerland, 11) School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland Table S1. Adjusted associations of systolic and diastolic ambulatory blood pressure with day and night‐time urinary methylxanthines excretions Daytime urinary methylxanthines excretions
Night‐time urinary methylxanthines excretions
Systolic Systolic Methylxanthine Caffeine* Diastolic
SBP 24h Beta, SE ‐0.718, 0.280 P value 0.010
DBP 24h
Beta, SE 0.172, 0.172
P value 0.319
SBP day ‐0.547, 0.313 0.065
DBP day
0.281, 0.191
SBP night ‐1.323, 0.315 <0.001
DBP night
Paraxanthine* SBP 24h ‐0.748, 0.320 0.019
SBP day ‐0.568, 0.338 SBP night Theophylline* Diastolic
SBP 24h Beta, SE 0.028, 0.252
P value 0.911
0.142
SBP day 0.063, 0.266
‐0.246, 0.173
0.155
SBP night DBP 24h
0.318, 0.197
0.106
0.093
DBP day
0.414, 0.218
‐1.509, 0.339 <0.001
DBP night
SBP 24h ‐0.706, 0.321 0.028
SBP day ‐0.521, 0.340 SBP night Theobromine* DBP 24h
Beta, SE 0.373, 0.154
P value 0.016 0.814
DBP day
0.408, 0.171
0.017 ‐0.048, 0.269
0.858
DBP night
0.308, 0.155
0.048 SBP 24h ‐0.235, 0.304
0.439
DBP 24h
0.360, 0.186
0.053 0.058
SBP day ‐0.125, 0.321
0.696
DBP day
0.415, 0.207
0.044 ‐0.159, 0.198
0.422
SBP night ‐0.505, 0.324
0.119
DBP night
0.242, 0.187
0.196 DBP 24h
0.341, 0.198
0.085
SBP 24h ‐0.268, 0.314
0.393
DBP 24h
0.381, 0.192
0.048 0.125
DBP day
0.485, 0.219
0.027
SBP day ‐0.141, 0.331
0.671
DBP day
0.482, 0.213
0.024 ‐1.378, 0.341 <0.001
DBP night
‐0.169, 0.199
0.394
SBP night ‐0.523, 0.334
0.118
DBP night
0.199, 0.194
0.304 SBP 24h 0.121, 0.325 0.710
DBP 24h
0.212, 0.200
0.287
SBP 24h ‐0.389, 0.289
0.179
DBP 24h
0.166, 0.178
0.350 SBP day 0.144, 0.343 0.675
DBP day
0.237, 0.221
0.284
SBP day ‐0.383, 0.305
0.209
DBP day
0.177, 0.197
0.369 SBP ‐0.237, 0.495 DBP ‐0.084, 0.67 SBP 0.342, 0.309 0.26 DBP 0.113, night 0.347 night 0.201 4 night 8 night 0.179 Models are adjusted for age, sex, BMI, study center, contraceptive use, diabetes, current alcohol use and smoking, GFR (CKD‐EPI), anti‐hypertensive treatment, blood Na+ and K+, and Na+ and K+ excretion. *log‐transformed
0.527 Table S2. Adjusted associations of systolic (SBP) and diastolic (DBP) blood pressure with 24‐hour urinary methylanthines excretions NOT on anti‐hypertensive therapy (N=704, 84.2%)
On anti‐hypertensive therapy (N=132, 15.8%)
Systolic Systolic Methylxanthine Caffeine* Diastolic
SBP 24h Beta, SE ‐0.451, 0.311 P value 0.147
DBP 24h
Beta, SE 0.212, 0.186
P value 0.255
SBP day ‐0.312, 0.330 0.344
DBP day
0.280, 0.206
SBP night ‐0.901, 0.325 0.006
DBP night
Paraxanthine* SBP 24h ‐0.533, 0.361 0.140
SBP day ‐0.347, 0.382 SBP night Theophylline* Diastolic
SBP 24h Beta, SE ‐3.192, 0.960
P value 0.001
DBP 24h
Beta, SE ‐0.408, 0.626
P value 0.515 0.174
SBP day ‐3.088, 0.994
0.002
DBP day
‐0.186, 0.707
0.793 ‐0.064, 0.194
0.741
SBP night ‐3.616, 1.091
0.001
DBP night
‐1.093, 0.542
0.044 DBP 24h
0.314, 0.216
0.145
SBP 24h ‐3.235, 1.090
0.003
DBP 24h
‐0.448, 0.706
0.526 0.365
DBP day
0.414, 0.239
0.083
SBP day ‐3.186, 1.127
0.005
DBP day
‐0.501, 0.796
0.529 ‐1.209, 0.377 0.001
DBP night
‐0.092, 0.224
0.681
SBP night ‐3.558, 1.242
0.004
DBP night
‐0.565, 0.617
0.360 SBP 24h ‐0.374, 0.362 0.303
DBP 24h
0.338, 0.216
0.119
SBP 24h ‐3.481, 1.020
0.001
DBP 24h
‐0.342, 0.667
0.608 SBP day ‐0.186, 0.384 0.628
DBP day
0.476, 0.239
0.047
SBP day ‐3.415, 1.056
0.001
DBP day
‐0.228, 0.753
0.762 SBP night ‐0.928, 0.379 0.014
DBP night
‐0.069, 0.225
0.759
SBP night ‐3.798, 1.163
0.001
DBP night
‐0.839, 0.581
0.149 Theobromine* SBP 24h 0.474, 0.359 0.187
DBP 24h
0.261, 0.214
0.224
SBP 24h ‐1.021, 1.024
0.319
DBP 24h
0.320, 0.644
0.619 SBP day 0.497, 0.380 0.191
DBP day
0.297, 0.238
0.211
SBP day ‐0.995, 1.056
0.346
DBP day
‐0.334, 0.726
0.646 SBP night 0.215, 0.377 0.568
DBP night
0.014, 0.223
0.949
SBP night ‐1.527, 1.160
0.188
DBP night
‐0.656, 0.562
0.244 Models are adjusted for age, sex, BMI, study center, contraceptive use, diabetes, current alcohol use and smoking, GFR (CKD‐EPI), blood Na+ and K+, and Na+ and K+ excretion. *log‐transformed Figure S1. Figure S1 Adjusted associations of 24‐hour, daytime, and night‐time systolic blood pressure with log transformed urinary 24‐hour caffeine excretions, by participants’ characteristics (N=836) Footnote: adjusted for age, sex, BMI, study center, contraceptive use, diabetes, current alcohol use, smoking, GFR (CKD‐EPI), blood Na+ and K+, and Na+ and K+ excretion. 
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