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Low Carbohydrate Diets and Risk of Incident Atrial Fibrillation: A Prospective Cohort Study

Authors:
  • Sun Yat-Sen University First Affiliated Hospital

Abstract and Figures

Background The influences of low‐carbohydrate diets in cardiovascular disease are controversial. Few studies have examined the relationship of carbohydrate intake and risk of incident atrial fibrillation (AF). We aimed to evaluate the association between carbohydrate intake and the risk of incident AF in the ARIC (Atherosclerosis Risk in Communities) Study. Methods and Results We included 13 385 participants (age, 54.2±5.8 years; 45.1% men and 74.7% white) who completed a dietary questionnaire at baseline (1987–1989) in the ARIC Study. The primary outcome was incident AF, which was identified by ECG performed during study examinations, hospital discharge codes, and death certificates. We used multivariable Cox hazard regression models to assess the association between carbohydrate intake and incident AF. We further explored the effects of specific food source (animal versus plant based) used to replace carbohydrate intake in the low‐carbohydrate intake setting. During a median follow‐up of 22.4 years, 1808 cases (13.5%) of AF occurred. The hazard ratio for incident AF associated with a 1‐SD (9.4%) increase in carbohydrate intake as a percentage of energy intake was 0.82 (95% CI, 0.72–0.94), after adjustment for traditional AF risk factors and other diets factors. Results were similar when individuals were categorized by carbohydrate intake quartiles (hazard ratio, 0.64; 95% CI, 0.49–0.84; comparing extreme quartiles). No association was found between the type of protein or fat used to replace the carbohydrate and risk of incident AF. Conclusions Low‐carbohydrate diets were associated with increased risk of incident AF, regardless of the type of protein or fat used to replace the carbohydrate.
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Low-Carbohydrate Diets and Risk of Incident Atrial Fibrillation:
A Prospective Cohort Study
Shaozhao Zhang, MD;* Xiaodong Zhuang, PhD;* Xiaoyu Lin, MD; Xiangbin Zhong, PhD; Huimin Zhou, MD; Xiuting Sun, PhD;
Zhenyu Xiong, PhD; Yiquan Huang, MD; Yongqiang Fan, MD; Yue Guo, PhD; Zhimin Du, MD; Xinxue Liao, PhD
Background-The inuences of low-carbohydrate diets in cardiovascular disease are controversial. Few studies have examined the
relationship of carbohydrate intake and risk of incident atrial brillation (AF). We aimed to evaluate the association between
carbohydrate intake and the risk of incident AF in the ARIC (Atherosclerosis Risk in Communities) Study.
Methods and Results-We included 13 385 participants (age, 54.25.8 years; 45.1% men and 74.7% white) who completed a
dietary questionnaire at baseline (19871989) in the ARIC Study. The primary outcome was incident AF, which was identied by
ECG performed during study examinations, hospital discharge codes, and death certicates. We used multivariable Cox hazard
regression models to assess the association between carbohydrate intake and incident AF. We further explored the effects of
specic food source (animal versus plant based) used to replace carbohydrate intake in the low-carbohydrate intake setting. During
a median follow-up of 22.4 years, 1808 cases (13.5%) of AF occurred. The hazard ratio for incident AF associated with a 1-SD
(9.4%) increase in carbohydrate intake as a percentage of energy intake was 0.82 (95% CI, 0.720.94), after adjustment for
traditional AF risk factors and other diets factors. Results were similar when individuals were categorized by carbohydrate intake
quartiles (hazard ratio, 0.64; 95% CI, 0.490.84; comparing extreme quartiles). No association was found between the type of
protein or fat used to replace the carbohydrate and risk of incident AF.
Conclusions-Low-carbohydrate diets were associated with increased risk of incident AF, regardless of the type of protein or fat
used to replace the carbohydrate. (J Am Heart Assoc. 2019;8:e011955. DOI: 10.1161/JAHA.119.011955.)
Key Words: atrial brillation diet epidemiology risk factor
Atrial brillation (AF) is the most common arrhythmia in
clinical practice, with an estimated lifetime risk of
25%.
1,2
As AF is related to substantial increased morbidity,
mortality, and economic costs,
3
it is important to recognize
modiable risk factors, such as dietary factors, as a step to
provide preventive strategies for this disease.
Low-carbohydrate diets, which restrict carbohydrate
intake, in favor of increased protein or fat intake, have
gained substantial popularity because of their ability to induce
short-term weight loss.
4,5
Nevertheless, the long-term effect
of carbohydrate restriction is still controversial, especially in
the inuence on cardiovascular disease.
69
Recently, the
2017 PURE (Prospective Urban-Rural Epidemiology) Study, of
135 335 participants from 18 countries across 5 continents,
reported that higher carbohydrate intake was associated with
an increased risk of total mortality but not with the risk of
cardiovascular disease (myocardial infarction, stroke, and
heart failure) or cardiovascular disease mortality.
10
Another
recent study of a large cohort, the ARIC (Atherosclerosis Risk
in Communities) Study, reported a U-shaped association
between carbohydrate intake and total mortality, whereas no
association was found with cardiovascular mortality.
5
How-
ever, to the best of our knowledge, no study has examined
the relationship of carbohydrate intake and risk of incident
From the Cardiology Department, First Afliated Hospital of Sun Yat-Sen University, Guangzhou, China (S.Z., X. Zhuang, X. Zhong, H.Z., X.S., Z.X., Y.H., Y.F., Y.G., Z.D.,
X. Liao); NHC Key Laboratory of Assisted Circulation (Sun Yat-sen University), Guangzhou, China (S.Z., X. Zhuang, X. Zhong, H.Z., X.S., Z.X., Y.H., Y.F., Y.G., Z.D.,
X. Liao); and Department of Anesthesiology, The Third Afliated Hospital of Sun Yat-Sen University, Guangzhou, China (X. Lin).
Accompanying Tables S1 through S10 are available at https://www.ahajournals.org/doi/suppl/10.1161/JAHA.119.011955
*Dr Zhang and Dr Zhuang contributed equally to this work.
Correspondence to: Xinxue Liao and Zhimin Du, Cardiology Department, First Afliated Hospital of Sun Yat-Sen University, 58 Zhongshan Second Rd, Guangzhou
510080, China. E-mails: liaoxinx@mail.sysu.edu.cn; dujiaoshou7890@126.com
Received January 4, 2019; accepted February 27, 2019.
ª2019 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley. This is an open access article under the terms of the Creative Commons
Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-
commercial and no modications or adaptations are made.
DOI: 10.1161/JAHA.119.011955 Journal of the American Heart Association 1
ORIGINAL RESEARCH
AF. As a result, we analyzed the ARIC Study data set to
assess the association of carbohydrate intake and incident
AF.
Methods
The data, analytic methods, and study materials will not be
made available to other researchers for purposes of
reproducing the results or replicating the procedure because
of human subjectsrestrictions. However, interested investi-
gators can contact the ARIC Study Coordinating Center at the
University of North CarolinaChapel Hill to request overall
access to ARIC Study data.
11
Study Populations
The ARIC Study is a population-based, prospective, cohort
study of cardiovascular risk factors in 4 US communities
(Forsyth County, North Carolina; Jackson, MD; suburbs of
Minneapolis, MN; and Washington County, Maryland), initially
consisting of 15 792 participants, aged 45 to 64 years,
recruited between 1987 and 1989 (visit 1). Four subsequent
study visits were conducted: visit 2 (19901992), visit 3
(19931995), visit 4 (19961998), and visit 5 (20112013).
Participants are being followed up by annual or semiannual
telephone interviews and active surveillance of ARIC Study
community hospitals. Further details about the study design
have been previously described.
12
The ARIC Study has been
approved by institutional review boards at all participating
institutions, and all participants provided written informed
consent. In the present analysis, of 15 792 participants at
baseline (visit 1), we excluded participants who had race
other than white or black (n=103), participants with preva-
lent AF or missing data of AF (n=243), participants with
missing dietary information or with extreme caloric intake
(dened as <600 or >4200 kcal/d for men and <500 or
>3600 kcal/d for women) (n=327), and participants missing
other covariates (n=1734). The nal sample size was 13 385
(Figure 1).
Dietary Assessment
At visits 1 and 3, participants completed an interview that
included a 66-item semiquantitative food frequency question-
naire, a modied version of the 61-item instrument developed
by Willett et al.
13
Participants reported the frequency of
particular foods and beverages consumed on a 9-category
scale, ranging from never or <1 time per month to 6 times per
day. Standard portion sizes were provided as a reference based
on picture and food models. Foods were grouped into dairy
foods, fruits, vegetables, meats, sweets, baked goods, cereals,
miscellaneous, beverages, and other dietary items. In addition,
detailed information about alcohol intake was ascertained on a
separate interview form. Nutrient intakes were derived from the
food frequency questionnaire responses using the Harvard
Nutrient Database. The macronutrients (carbohydrate, fat, and
protein) were expressed as percentage of energy, calculated as
the daily calories of the macronutrient divided by the total
number of calories for the day.
13
AF Ascertainment
Detailed ascertainment of AF, including both AF proper and
atrial utter, has been described previously.
14
Incident AF was
identied by ECGs performed during study examinations,
hospital discharge codes, and death certicates. At each
study visit, a 12-lead ECG was performed with the participant
lying in a supine position. Electrocardiographic data were
transmitted electronically to a reading center (EpiCare, Wake
Forest University, Winston-Salem, NC), reviewed, and ana-
lyzed using the GE Marquette 12-SL program (GE Marquette,
Milwaukee, WI). ECGs automatically coded as AF or atrial
utter were visually checked and conrmed by a cardiologist.
Hospitalizations during follow-up were identied through
annual telephone calls and surveillance of local hospitals.
Trained abstractors collected information from all
participantshospitalizations, including all International Clas-
sication of Diseases, Ninth Revision, Clinical Modication
(ICD-9-CM), codes for diagnoses. AF was considered to be
present if the ICD-9-CM code 427.31 (AF) or 427.32 (atrial
utter) was present in any hospitalization. AF events
associated with open cardiac surgery were excluded.
Besides, AF was also dened if ICD-9-CM code 427.31 or
427.32 was listed as a cause of death.
Clinical Perspective
What Is New?
In this large, prospective, community-based cohort study
with a long-term follow-up, we were the rst to evaluate the
association of carbohydrate intake with incident atrial
brillation and found that people with a low-carbohydrate
diet may have had a higher risk of incident atrial brillation,
regardless of the type of protein or fat used to replace the
carbohydrate.
What Are the Clinical Implications?
Low-carbohydrate diets are associated with increased risk
of incident atrial brillation, indicating that this popular
weight control method, by restricting carbohydrate intake,
should be recommended cautiously and more studies
should be conducted to evaluate the effect.
DOI: 10.1161/JAHA.119.011955 Journal of the American Heart Association 2
Carbohydrate Intake and Atrial Fibrillation Zhang et al
ORIGINAL RESEARCH
Measurement of Other Covariates
All covariates were assessed at visit 1, except for body mass
index, which was also a measure at visits 2 and 3. Race,
age, sex, education level, smoking, and alcohol consumption
status were self-reported. Height and weight were measured
with the participant wearing light clothes, and body mass
index was calculated as weight (in kilograms) divided by
squared height (in meters). Body surface area was calculated
according to the Mosteller formula as the square root of
[height (cm)9weight (kg)/3600]. Sport and physical activity
during leisure time was accessed using the validated Baecke
questionnaire. Hypertension was dened as systolic blood
pressure 140 mm Hg and/or diastolic blood pressure
90 mm Hg, or blood pressure medicine use in the past
2 weeks. Diabetes mellitus was dened if the participants
had fasting blood glucose 126 mg/dL, nonfasting blood
glucose 200 mg/dL, use of antidiabetic medicines, or self-
reported physician diagnosis of diabetes mellitus. Stroke
was identied by 6 associated symptoms (speech, vision,
double vision, numbness, paralysis, and dizziness) corre-
sponding to the specic artery. Prevalent coronary heart
disease and heart failure were dened as previously
described.
15,16
Total cholesterol, high-density lipoprotein
cholesterol, and triglycerides were measured using stan-
dardized enzymatic assays, and low-density lipoprotein
cholesterols were than calculated on the basis of the
Friedewald formula.
17
Creatinine was measured using a
modied kinetic Jaffe method, and uric acid was measured
by the method of Haeckel.
12
Statistical Analysis
We primarily modeled carbohydrate intake as a continuous
variable, and we rescaled the data by dividing by the SD
(1 SD=9.4%). Then, we categorized carbohydrate intake into
quartiles based on the sample distribution. Baseline charac-
teristics of participants were compared between groups using
the 1-way ANOVA test, the v
2
test, and the Kruskal-Wallis
test, as appropriate. We used multivariable Cox hazard
regression models to assess the association between baseline
carbohydrate intake and incident AF. Time of follow-up was
dened as time from visit 1 (baseline) to incident of AF, loss to
follow-up, death, or December 31, 2012, whichever occurred
rst. We also used a restricted cubic spline with 4 knots to
express the dose-response association between total energy
from carbohydrate intake and incident AF. The initial model
adjusted for age, sex, and race. A second model additionally
adjusted for total energy intake, total fat intake as a
percentage of energy, animal fat intake as a percentage of
energy, total protein intake as a percentage of energy, animal
protein intake as a percentage of energy, dietary ber intake,
glycemic index, and glycemic load. In a nal model, we further
adjusted for body mass index, body surface area, smoking,
drinking, education level, sport, physical activity, total
cholesterol, high-density lipoprotein cholesterol, low-density
lipoprotein cholesterol, triglycerides, creatinine, uric acid,
hypertension, stroke, diabetes mellitus, prevalent coronary
artery disease, and prevalent heart failure. We did a time-
varying sensitivity analysis for participants who were identi-
ed with incident AF, loss to follow-up, or death before visit 3;
Figure 1. Flow diagram of participants in the ARIC (Atherosclerosis Risk in Communities) Study. AF
indicates atrial brillation.
DOI: 10.1161/JAHA.119.011955 Journal of the American Heart Association 3
Carbohydrate Intake and Atrial Fibrillation Zhang et al
ORIGINAL RESEARCH
carbohydrate intake was calculated on the basis of responses
from the baseline (visit 1) food frequency questionnaire. From
visit 3 onwards, the carbohydrate intake was calculated on
the basis of the mean of visit 1 and visit 3 food frequency
questionnaire responses. Carbohydrate exposures were not
updated for participants who developed heart disease,
diabetes mellitus, or stroke before visit 3 for reducing
potential confounding from changes in diet that could arise
from the diagnosis. For the missing of dietary information at
visit 3 in 2743 participants, we did a further sensitivity
analysis: we excluded the missing data in the rst analysis,
and in the second we used dietary information in visit 1 to
replace missing data. In addition, we performed prespecied
subgroup analysis by age, sex, and race and tested for
potential interactions of these covariates with carbohydrate
intake separately. To minimize the potential of reverse
causation, we did a sensitivity analysis whereby individuals
with prevalent coronary artery disease, heart failure, stroke, or
diabetes mellitus at baseline were excluded from the analysis.
Because of the high rate of hypertension at the baseline, we
also did a subgroup analysis of participants with or without
hypertension and tested for interaction of hypertension and
carbohydrate intake.
To further explore the effects of specic food sources
(animal versus plant based) that are used to replace
carbohydrate intake in the low-carbohydrate intake setting,
we created animal- and plant-based low-carbohydrate diet
scores, as previously described.
8
Either animal- or plant-based
fat and protein and carbohydrate intake as a percentage of
energy were divided into deciles. For carbohydrate, partici-
pants got 10 points in the lowest decile and 0 points in the
highest decile. The order was reversed for animal- or plant-
based fat and protein. Animal-based low-carbohydrate diet
scores were calculated by summing up the points for
carbohydrate, animal-based fat, and animal-based protein.
Plant-based low-carbohydrate diet scores were calculated by
summing up the points for carbohydrate, plant-based fat, and
plant-based protein (Table S1). As a result, the highest score
represented low-carbohydrate and high animal- or plant-based
fat and protein intake. We used the Cox hazard regression
model to determine the association of incident AF with
animal- or plant-based low-carbohydrate scores.
Results
Baseline characteristics are shown in Table 1. The mean value
of carbohydrate intake as a percentage of energy for 13 384
participants was 44.89.4%. The average age was
54.25.8 years, and 45.1% of participants were men. Partic-
ipants with a relatively low percentage of energy from
carbohydrate were more likely to be young, men, white,
smokers, and ever drinkers; and to have diabetes mellitus, a
high education level, a high high-density lipoprotein choles-
terol level, a high uric acid level, high total fat intake, high
animal fat intake, high total protein intake, high animal protein
intake, low plant protein intake, low dietary ber intake, a low
glycemic index, and a low glycemic load. Total energy intake
or plant fat intake had reverse U-shaped relationship across
carbohydrate intake quartiles: participants in both the rst
and fourth quartiles had lower total energy intake and plant
fat intake than those in the intermediate quartiles. There was
no signicant difference in change in body mass index at the
time points of 3 and 6 years from baseline across carbohy-
drate quartiles. The prevalence of hypertension, stroke,
coronary artery disease, and heart failure was similar across
carbohydrate quartiles (Table 1).
During a median follow-up of 22.4 years, 1808 cases
(13.5%) of AF occurred. In the model that measured
carbohydrate intake as a continuous variable, an increase of
9.4% in carbohydrate intake (corresponding to 1 SD) was
associated with an 18% lower rate of incident AF (hazard ratio,
0.82; 95% CI, 0.720.94), after adjusting for all covariates
(Table 2). Results were similar when we categorized individ-
uals by carbohydrate intake quartiles: the highest risk of
incident AF was observed in the lowest carbohydrate intake
subgroup, in both unadjusted and adjusted models (P<0.001,
Table 2). In the nal model, the hazard ratios for incident AF
comparing the second, third, and fourth quartiles of carbo-
hydrate intake as a percentage of energy with the rst quartile
were 0.79 (95% CI, 0.680.92), 0.77 (95% CI, 0.640.93), and
0.64 (95% CI, 0.490.84) separately (Table 2, Figure 2).
Figure 3 shows the restricted cubic splines of the risk of
incident AF across levels of carbohydrate intake as a
percentage of energy intake. Consistent with the analysis
using quartiles of sample distribution, the risk of incident AF
increased in participants with a lower carbohydrate intake.
However, there was no signicant difference for risk of
incident AF in participants with carbohydrate intake as a
percentage of energy >62%, compared with the reference
level of 50% (Figure 3).
There were similar results in the time-varying sensitivity
analysis (Tables S2 and S3). When stratied by age, sex, race,
and presence of hypertension, the associations between
carbohydrate intake and incident AF were stronger in white
participants, women, older participants, and participants with
hypertension; however, all interactions were not statistically
signicant (P>0.05 for all interactions, Tables S4 through S7).
In sensitivity analysis, the association between carbohydrate
intake and incident AF persisted after excluding participants
with prevalent coronary artery disease, prevalent heart failure,
prevalent stroke, or diabetes mellitus at baseline (Table S8).
To further explore the effects of source of fat and protein
alternatives to low-carbohydrate intake, we analyzed the
association of animal- or plant-based low-carbohydrate diet
DOI: 10.1161/JAHA.119.011955 Journal of the American Heart Association 4
Carbohydrate Intake and Atrial Fibrillation Zhang et al
ORIGINAL RESEARCH
Table 1. Baseline Characteristics of Study Participants by Quartiles of Carbohydrate Intake as a Percentage of Energy
Characteristic Total (n=13 384) Quartile 1 (n=3344) Quartile 2 (n=3345) Quartile 3 (n=3349) Quartile 4 (n=3347) PValue
Carbohydrate, % of energy 48.89.4 37.24.7 45.81.7 51.51.8 60.85.3 <0.001
Age, y 54.25.8 53.95.7 54.25.8 54.35.8 54.35.8 0.018
Sex <0.001
Men 6036 (45.1) 1772 (53.0) 1547 (46.2) 1477 (44.1) 1240 (37.0)
Women 7349 (54.9) 1572 (47.0) 1798 (53.8) 1872 (55.9) 2107 (63.0)
Race <0.001
Black 3393 (25.3) 730 (21.8) 814 (24.3) 879 (26.2) 970 (29.0)
White 9992 (74.7) 2614 (78.2) 2531 (75.7) 2470 (73.8) 2377 (71.0)
BMI, kg/m
2
27.65.3 27.85.1 27.85.3 27.55.3 27.35.5 <0.001
Change in BMI, kg/m
2
3-y Change 0.361.7 0.351.7 0.341.7 0.331.7 0.421.7 0.127
6-y Change 0.932.1 0.912.3 0.922.2 0.922.1 0.962.1 0.812
BSA, m
2
1.910.2 1.940.2 1.920.2 1.900.2 1.870.2 <0.001
Hypertension 4750 (34.1) 1116 (33.4) 1118 (33.4) 1136 (33.9) 1200 (35.9) 0.108
Stroke 625 (4.7) 160 (4.8) 151 (4.5) 159 (4.7) 155 (4.6) 0.953
Diabetes mellitus 1239 (9.3) 356 (10.6) 334 (10.0) 278 (8.3) 271 (8.1) <0.001
Coronary artery disease 643 (4.8) 151 (4.5) 155 (4.6) 151 (4.5) 186 (5.6) 0.132
Heart failure 607 (4.5) 144 (4.3) 137 (4.1) 147 (4.4) 179 (5.3) 0.067
Smoking <0.001
Current smoker 3504 (26.2) 1056 (31.6) 897 (26.8) 785 (23.4) 766 (22.9)
Former smoker 4377 (32.7) 1191 (35.6) 1100 (32.9) 1105 (33.0) 981 (29.3)
Never smoker 5504 (41.1) 1097 (32.8) 1348 (40.3) 1459 (43.6) 1600 (47.8)
Drinking <0.001
Current drinker 7650 (57.2) 2379 (71.1) 2034 (60.8) 1801 (53.8) 1436 (42.9)
Former drinker 2488 (18.6) 480 (14.4) 575 (17.2) 625 (18.7) 808 (24.1)
Never drinker 3247 (24.3) 485 (14.5) 736 (22.0) 923 (27.6) 1103 (33.0)
Education level <0.001
Basic or 0 y 3048 (22.8) 662 (19.8) 730 (21.8) 780 (23.3) 876 (26.2)
Intermediate 5492 (41.0) 1319 (39.4) 1319 (39.4) 1369 (40.9) 1404 (41.9)
Advanced 4845 (36.2) 1363 (40.8) 1246 (37.2) 1165 (34.8) 1071 (32.0)
Sport 2.3 (1.83.0) 2.3 (1.83.0) 2.3 (1.83.0) 2.3 (1.83.0) 2.3 (1.83.0) 0.003
Physical activity 2.3 (2.02.8) 2.3 (2.02.8) 2.3 (2.02.8) 2.3 (2.02.8) 2.3 (2.02.8) <0.001
Total cholesterol, mmol/L 5.51.1 5.51.1 5.51.1 5.51.1 5.61.1 0.266
HDL-C, mmol/L 1.30.4 1.40.5 1.30.4 1.30.4 1.30.4 <0.001
LDL-C, mmol/L 3.61.0 3.51.0 3.61.0 3.51.0 3.61.0 0.042
Lg triglycerides, lg(mmol/L) 0.0990.21 0.0970.21 0.0960.21 0.0990.21 0.1040.21 0.345
Creatinine, mg/dL 1.10.4 1.10.4 1.10.5 1.10.3 1.10.3 0.007
Uric acid, mg/dL 6.01.6 6.21.6 6.01.6 6.01.5 6.01.6 <0.001
Total energy intake, kcal 1623.4609.0 1592.9604.2 1660.0601.5 1656.3596.3 1584.6629.9 <0.001
Total fat, % of energy 32.96.8 38.46.3 35.14.5 31.94.0 26.14.8 <0.001
Animal fat, % of energy 19.96.2 25.65.9 21.44.4 18.53.9 14.34.0 <0.001
Continued
DOI: 10.1161/JAHA.119.011955 Journal of the American Heart Association 5
Carbohydrate Intake and Atrial Fibrillation Zhang et al
ORIGINAL RESEARCH
scores with incident AF using Cox hazard regression analysis.
However, no signicant relationship could be found (Tables S9
and S10).
Discussion
In this large, prospective, cohort study with a long-term
follow-up of >20 years, we found that low-carbohydrate
intake as a percentage of energy was associated with a
higher risk of incident AF, which was independent of other
well-known risk factors for incident AF. The association was
consistently observed in several sensitivity analyses (Tables
S2 through S8). No relationship was found in the further
exploration of the effects of source of fat and protein
alternatives to low-carbohydrate intake. To the best of our
knowledge, it is the rst large prospective cohort study to
assess the relationship of carbohydrate intake with risk of
incident AF.
Previous assessments of dietary exposures in relation to
AF mostly focused on the effect of omega-3 fatty acid from
sh, although with controversial conclusions.
1824
In the
PREDIMED (Prevenci
on con Dieta Mediterr
anea) trial,
25
Martinez-Gonzalez et al found that extravirgin olive oil in the
context of a Mediterranean dietary pattern may reduce the
risk of AF. Other studies
2628
also found inconsistent
associations between chocolate, coffee, and AF. Similarly,
our study also evaluated the relationship between diet factors
and incident AF. The adverse association of carbohydrate
intake with incident AF found in our study supplemented the
relationship of macronutrient and risk of AF.
A low-carbohydrate diet, with the reduction of carbohy-
drate intake and thereby encouragement of high protein or fat
intake, is now widely recommended for weight control, for the
effect of signicant weight loss in the short-term without
feeling hungery.
29
However, the long-term effectiveness and
safety of low-carbohydrate diets remain controversial. Several
studies reported that the weight loss effect of a low-
carbohydrate diet was observed for 6 months only and was
no longer signicant after 12 months, compared with the
energy-restricted low-fat diet.
3032
The effect of weight loss
Table 1. Continued
Characteristic Total (n=13 384) Quartile 1 (n=3344) Quartile 2 (n=3345) Quartile 3 (n=3349) Quartile 4 (n=3347) PValue
Plant fat, % of energy 13.05.1 12.95.4 13.85.1 13.44.8 11.84.6 <0.001
Total protein, % of energy 17.94.2 20.34.3 18.63.5 17.53.4 15.33.6 <0.001
Animal protein, % of energy 13.54.3 16.44.5 14.23.6 12.93.4 10.63.3 <0.001
Plant protein, % of energy 4.41.2 4.01.1 4.41.1 4.61.2 4.71.5 <0.001
Dietary fiber, g 17.28.2 14.06.7 17.07.2 18.47.7 19.69.8 <0.001
Glycemic index 588.6263.3 447.7196.6 574.8226.6 641.8259.4 689.9294.7 <0.001
Glycemic load 10 4394673 75323189 99283661 11 2954168 12 9955516 <0.001
Data are median (interquartile range), meanSD, or number (percentage), unless otherwise indicated. Baseline characteristics are from the study population (n=13 384) at baseline visit 1,
according to quartiles of carbohydrate intake as a percentage of energy intake. BMI indicates body mass index; BSA, body surface area; HDL-C, high-density lipoprotein choleste rol; LDL-C,
low-density lipoprotein cholesterol.
Table 2. Risk of Incident AF for Carbohydrate Intake as a Percentage of Energy
Carbohydrate Intake (% of Energy)
Model 1* Model 2
Model 3
HR (95% CI) PValue HR (95% CI) PValue HR (95% CI) PValue
Quartiles
1(42.70) 1.00 (Reference)  1.00 (Reference)  1.00 (Reference) 
2 (42.7148.55) 0.84 (0.740.95) 0.007 0.77 (0.670.90) 0.001 0.79 (0.680.92) 0.002
3 (48.5654.74) 0.84 (0.740.96) 0.008 0.73 (0.610.88) 0.001 0.77 (0.640.93) 0.007
4(54.75) 0.79 (0.690.90) <0.001 0.62 (0.480.81) <0.001 0.64 (0.490.84) 0.001
Per 1 SD (9.4%) 0.93 (0.890.98) 0.003 0.79 (0.700.91) 0.001 0.82 (0.720.94) 0.005
AF indicates atrial brillation; HR, hazard ratio.
*Adjusted for age, sex, and race.
Further adjusted for total energy intake, total fat intake as a percentage of energy, animal fat intake as a percentage of energy, total protein intake as a percentage of energy, animal
protein intake as a percentage of energy, dietary ber intake, glycemic index, and glycemic load.
Further adjusted for body mass index, body surface area, smoking, drinking, education level, sport, physical activity, total cholesterol, high-density lipoprotein cholesterol, low-density
lipoprotein cholesterol, triglycerides, creatinine, uric acid, hypertension, stroke, diabetes mellitus, coronary artery disease, and heart failure.
DOI: 10.1161/JAHA.119.011955 Journal of the American Heart Association 6
Carbohydrate Intake and Atrial Fibrillation Zhang et al
ORIGINAL RESEARCH
might be attributable to excretion of bound water; decreased
energy intake, by appetite suppression or satiation; and
increased energy expenditure.
29,33
For the safety of a low-
carbohydrate diet, previous studies reported inconsistent
conclusions. In the study by Lagiou et al,
9
low-carbohydrate
high-protein diets were associated with increased risk of
cardiovascular disease. On the contrary, Bazzano et al
6
reported the reduction of cardiovascular risk factors in a
low-carbohydrate diet; and in the study by Halton et al,
8
a
lower-carbohydrate diet was not associated with increased
risk of coronary artery disease. Two recent studies for 2 large
prospective cohorts (the PURE and ARIC Studies), combined
with a meta-analysis study of several previous studies,
reported a U-shaped association of carbohydrate intake and
total mortality, whereas no association was found between
carbohydrate intake and risk of cardiovascular disease
(myocardial infarction, stroke, and heart failure) or cardiovas-
cular mortality.
5,10
However, none of these studies assessed
the potential relationship between carbohydrate intake and
incident AF, which is also a common cardiovascular disease in
clinical practice, with high mortality. Interestingly, our study,
for the rst time, discovered the adverse effect of a low-
carbohydrate diet to AF, which provided a novel potential risk
factor for the primary prevention of AF. In view of the different
effect of food source used to replace carbohydrate to the risk
of total mortality, as the previous study described,
5
we further
explored the association of animal- or plant-based low-
carbohydrate diet scores with incident AF; no association could
be found, which suggests that the increased risk of AF caused
by a low-carbohydrate intake was not related to the source of
food used to replace carbohydrate.
Several potential mechanisms may explain the observed
inverse association. First, a low-carbohydrate diet may lead to
lower intake of vegetables, fruits, and grain, as well as the
vitamins they contain, which may reduce their anti-inamma-
tory effects
34
and stimulate inammatory pathways. As the
association between a proinammatory state and incidence of
AF has been extensively demonstrated,
25,35
reducing intake of
these anti-inammatory foods may be one of the important
mechanisms for the risk of incident AF. Second, a low-
carbohydrate diet with increased protein and fat consumption
may stimulate oxidative stress,
36
which was also demon-
strated to be associated with incident AF.
37
Finally, the effect
could result from the increased risk of other cardiovascular
disease during the follow-up, which is a known risk factor for
AF.
38
Nevertheless, the effect of a low-carbohydrate intake on
other cardiovascular disease is still controversial, as men-
tioned above.
Strengths and Limitations
Our analysis has important strengths. We used a large
community-based biracial cohort with a long follow-up
duration and adequate AF events to test our hypotheses.
Figure 2. Kaplan-Meier curve of incident atrial brillation (AF) by quartiles of carbohydrate intake as a
percentage of energy.
DOI: 10.1161/JAHA.119.011955 Journal of the American Heart Association 7
Carbohydrate Intake and Atrial Fibrillation Zhang et al
ORIGINAL RESEARCH
The ARIC Studys design, with the extensive and rigorous
measurement of covariates, allows us to perform compre-
hensive statistical adjustment and reduce confounding as
much as possible. AF incidence in the ARIC Study is
consistent with other population-based studies, and the use
of hospital discharge records for the AF ascertainment has
been previously validated in the ARIC Study.
14,3941
There
are also some limitations to consider. First, in the method of
AF ascertainment, most AF events were found through
hospital discharge codes. As a result, individuals with
asymptomatic AF or those managed in an outpatient setting,
not requiring hospital admission, were unable to be identi-
ed. Second, we are unable to classify AF type (paroxysmal,
persistent, or permanent AF) accurately in the ARIC Study,
so the relationship between carbohydrate intake and
incident AF we found was not detailed enough. Third, our
study was based on the diet information at the baseline, and
dietary patterns could change during >20 years of follow-up.
We conducted a time-varying sensitivity analysis spanning
6 years to minimize the bias as possible, and the result was
similar, although the change after 6 years could not be
assessed because of the unavailable data in the ARIC Study.
Fourth, some degree of measurement error is unavoidable
for the dietary assessment methods. As a result, the
interpretation of absolute intakes should be cautious. Last,
as it is an observational study, we could not exclude residual
confounding, despite the fact that we adjusted for potential
covariates as much as possible. More randomized controlled
trials, with rigorously controlled food types and alternative
energy sources, are needed to conrm this hypothesis,
although it is difcult because of the long duration of study
required.
In conclusion, we found that a low-carbohydrate intake was
associated with increased risk of incident AF, regardless of
the type of protein and fat used to replace the carbohydrate.
A low-carbohydrate diet, a way to control weight, should be
cautiously recommended, especially considering the potential
inuence on arrhythmia.
Figure 3. Adjusted hazard ratios of atrial brillation by baseline carbohydrate intake as a percentage of
energy. Each hazard ratio was computed with a carbohydrate intake level of 50% as the reference. The hazard
ratio was adjusted for age, race, total energy intake, total fat intake as a percentage of energy, animal fat intake
as a percentage of energy, total protein intake as a percentage of energy, animal protein intake as a percentage
of energy, dietary ber intake, glycemic index, glycemic load, body mass index, smoking, drinking, education
level, sport, physical activity, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein
cholesterol, triglycerides, creatine, uric acid, hypertension, stroke, diabetes mellitus, coronary artery disease,
and heart failure. Red solid line represents the hazard ratio of carbohydrate intake across the whole range.
Red dotted lines represent the 95% CI. Black dotted lines is the reference line as hazard ratio =1. Histograms
represent the frequency distribution of carbohydrate intake as a percentage of energy at baseline.
DOI: 10.1161/JAHA.119.011955 Journal of the American Heart Association 8
Carbohydrate Intake and Atrial Fibrillation Zhang et al
ORIGINAL RESEARCH
Acknowledgments
We thank the staff and participants of the ARIC (Atherosclerosis Risk
in Communities) Study for their important contributions.
Sources of Funding
The ARIC (Atherosclerosis Risk in Communities) Study is
performed as a collaborative trial supported by National
Heart, Lung, and Blood Institute contracts (HHSN268201
100005C, HHSN268201100006C, HHSN268201100007C,
HHSN268201100008C, HHSN268201100009C, HHSN2682
01100010C, HHSN268201100011C, and HHSN268201100
012C). Liao is also supported by the National Natural Science
Foundation of China (81600206) and the Natural Science
Foundation of Guangdong Province (2016A030310140/2016
0903).
Disclosures
None.
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The jury is still out on whether a low-carbohydrate, ketosis-inducing diet is an effective and safe adjunctive therapy to insulin in type 1 diabetes. The limited published literature reports an association with weight loss and improved glycemic control and may, over the long-term, lead to reduced macrovascular and microvascular harm. However, the attendant increased risk of dyslipidemia, diabetic ketoacidosis, and hypoglycemia warrant caution, close monitoring of patients who embark on the diet, and further research.
... Low-carbohydrate diets, which are low in carbohydrate and high in fat and protein, have become a particularly popular approach for weight reduction in recent years (7). Observational studies have found that low-carbohydrate diets are associated with increased risks of type 2 diabetes (8), atrial fibrillation (9) and mortality (10) but a reduced risk of cardiovascular disease (11). However, the effects of low-carbohydrate diets on carcinogenesis remain largely unknown. ...
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Low-carbohydrate diets have become a popular approach for weight loss in recent years. However, whether low-carbohydrate diets are associated with the risk of pancreatic cancer remains to be elucidated. Hence, we examined the association of low-carbohydrate diets with the risk of pancreatic cancer in a US population. A population-based cohort of 95962 individuals was identified. A low-carbohydrate-diet score was calculated to quantify adherence to this dietary pattern, with higher scores indicating greater adherence. Cox regression was used to calculate risk estimate for the association of the low-carbohydrate-diet score with the risk of pancreatic cancer. Subgroup analysis was used to identify the potential effect modifiers. After an average follow-up of 8.87 years (875856.9 person-years), we documented a total of 351 pancreatic cancer cases. In the fully adjusted model, the highest vs. the lowest quartiles of the overall low-carbohydrate-diet score was found to be associated with a reduced risk of pancreatic cancer (hazard ratioquartile 4 vs. 1: 0.61; 95% confidence interval: 0.45, 0.82; Ptrend<0.001). Subgroup analysis found that the inverse association of low-carbohydrate diets with the risk of pancreatic cancer was more pronounced in individuals aged ≥65 years than in those aged <65 years (Pinteraction=0.015). Similar results were obtained for animal and vegetable low-carbohydrate-diet scores. In conclusion, low-carbohydrate diets, regardless of the type of protein and fat, are associated with a lower risk of pancreatic cancer in the US population, suggesting that adherence to low-carbohydrate-diets may be beneficial for pancreatic cancer prevention. Future studies should validate our findings in other populations.
... The Prevención con Dieta Mediterránea (PREDIMED) trial demonstrated that extra-virgin olive oil in a Mediterranean diet may reduce AF risk [18]. Low-carbohydrate diets were associated with increased risk of AF [19]. In AF patients, plasma LPS levels predicted major cardiovascular events and were negatively affected by adherence to a Mediterranean diet [14]. ...
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Atrial fibrillation (AF) reduces the quality of life by triggering stroke and heart failure. The association between AF onset and gut metabolites suggests a causal relationship between AF and gut microbiota dysbiosis; however, the relationship remains poorly understood. We prospectively enrolled 34 hospitalized patients with AF and 66 age-, sex-, and comorbidity-matched control subjects without a history of AF. Gut microbial compositions were evaluated by amplicon sequencing targeting the 16S ribosomal RNA gene. We assessed differences in dietary habits by using a brief-type self-administered diet history questionnaire (BDHQ). Gut microbial richness was lower in AF patients, although the diversity of gut microbiota did not differ between the two groups. At the genus level, Enterobacter was depleted, while Parabacteroides, Lachnoclostridium, Streptococcus, and Alistipes were enriched in AF patients compared to control subjects. The BDHQ revealed that the intake of n-3 polyunsaturated fatty acids and eicosadienoic acid was higher in AF patients. Our results suggested that AF patients had altered gut microbial composition in connection with dietary habits.
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Objectives: This is a protocol for a Cochrane Review (intervention). The objectives are as follows:. To determine the effectiveness of Dietary Approaches to Stop Hypertension (DASH) for the primary and secondary prevention of CVD. Copyright © 2020 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.
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Alcohol abuse is positively associated with cardiovascular disease. Dietary low-carbohydrate/high-protein (LCHP) intake confers a greater mortality risk. Here, the impact of ethanol consumption in combination with dietary LCHP intake on left ventricular (LV) systolic function and lethal ventricular arrhythmia susceptibility were investigated in apolipoprotein E/low-density lipoprotein receptor double-knockout (AL) mice. The underlying mechanisms, cardiac sympathovagal balance, beta-adrenergic receptor (ADRB) levels, and gap junction channel protein connexin 43 (Cx43) expression, were examined. Male AL mice fed an LCHP diet with or without ethanol were bred for 16 weeks. Age-matched male AL and wild-type mice received standard chow diet and served as controls. The following were used to assess LV systolic function, lethal ventricular arrhythmia susceptibility, cardiac sympathovagal balance, Cx43 expression, and ADRB levels: •echocardiography •electrocardiography and a ventricular arrhythmia-evoked test •LV tyrosine hydroxylase (TH) expression shown by a fluorescence immunohistochemical examination and the ratio of low-frequency power to high-frequency power (LF/HF) as indicated by the heart rate variability (HRV) •Cx43 expression in both a fluorescence immunohistochemical examination and polymerase chain reaction (PCR); and ADRB1 and ADRB2 expressions in fluorescence immunohistochemical examination The results demonstrated that ethanol consumption in combination with dietary LCHP intake worsened LCHP-induced LV systolic dysfunction in AL mice and enhanced their susceptibility in the ventricular arrhythmia-evoked test. There were concomitant increases in LV weight, LF/HF ratio shown by HRV, TH, ADRB1, ADRB2, and Cx43 expressions by LV fluorescence immunohistochemistry, and LV Cx43 messenger ribonucleic acid expression by PCR. In AL mice, alcohol consumption combined with dietary LCHP intake may thus promote a shift in cardiac sympathovagal balance toward sympathetic predominance, the increases in beta-adrenergic receptors (ADRB1 and ADRB2), and then affect the gap junction channel protein Cx43, which in turn could contribute to increased risks of LV systolic dysfunction and susceptibility to lethal ventricular arrhythmia.
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Objective To determine the effects of diets varying in carbohydrate to fat ratio on total energy expenditure. Design Randomized trial. Setting Multicenter collaboration at US two sites, August 2014 to May 2017. Participants 164 adults aged 18-65 years with a body mass index of 25 or more. Interventions After 12% (within 2%) weight loss on a run-in diet, participants were randomly assigned to one of three test diets according to carbohydrate content (high, 60%, n=54; moderate, 40%, n=53; or low, 20%, n=57) for 20 weeks. Test diets were controlled for protein and were energy adjusted to maintain weight loss within 2 kg. To test for effect modification predicted by the carbohydrate-insulin model, the sample was divided into thirds of pre-weight loss insulin secretion (insulin concentration 30 minutes after oral glucose). Main outcome measures The primary outcome was total energy expenditure, measured with doubly labeled water, by intention-to-treat analysis. Per protocol analysis included participants who maintained target weight loss, potentially providing a more precise effect estimate. Secondary outcomes were resting energy expenditure, measures of physical activity, and levels of the metabolic hormones leptin and ghrelin. Results Total energy expenditure differed by diet in the intention-to-treat analysis (n=162, P=0.002), with a linear trend of 52 kcal/d (95% confidence interval 23 to 82) for every 10% decrease in the contribution of carbohydrate to total energy intake (1 kcal=4.18 kJ=0.00418 MJ). Change in total energy expenditure was 91 kcal/d (95% confidence interval −29 to 210) greater in participants assigned to the moderate carbohydrate diet and 209 kcal/d (91 to 326) greater in those assigned to the low carbohydrate diet compared with the high carbohydrate diet. In the per protocol analysis (n=120, P<0.001), the respective differences were 131 kcal/d (−6 to 267) and 278 kcal/d (144 to 411). Among participants in the highest third of pre-weight loss insulin secretion, the difference between the low and high carbohydrate diet was 308 kcal/d in the intention-to-treat analysis and 478 kcal/d in the per protocol analysis (P<0.004). Ghrelin was significantly lower in participants assigned to the low carbohydrate diet compared with those assigned to the high carbohydrate diet (both analyses). Leptin was also significantly lower in participants assigned to the low carbohydrate diet (per protocol). Conclusions Consistent with the carbohydrate-insulin model, lowering dietary carbohydrate increased energy expenditure during weight loss maintenance. This metabolic effect may improve the success of obesity treatment, especially among those with high insulin secretion. Trial registration ClinicalTrials.gov NCT02068885 .
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Background: Low carbohydrate diets, which restrict carbohydrate in favour of increased protein or fat intake, or both, are a popular weight-loss strategy. However, the long-term effect of carbohydrate restriction on mortality is controversial and could depend on whether dietary carbohydrate is replaced by plant-based or animal-based fat and protein. We aimed to investigate the association between carbohydrate intake and mortality. Methods: We studied 15 428 adults aged 45-64 years, in four US communities, who completed a dietary questionnaire at enrolment in the Atherosclerosis Risk in Communities (ARIC) study (between 1987 and 1989), and who did not report extreme caloric intake (<600 kcal or >4200 kcal per day for men and <500 kcal or >3600 kcal per day for women). The primary outcome was all-cause mortality. We investigated the association between the percentage of energy from carbohydrate intake and all-cause mortality, accounting for possible non-linear relationships in this cohort. We further examined this association, combining ARIC data with data for carbohydrate intake reported from seven multinational prospective studies in a meta-analysis. Finally, we assessed whether the substitution of animal or plant sources of fat and protein for carbohydrate affected mortality. Findings: During a median follow-up of 25 years there were 6283 deaths in the ARIC cohort, and there were 40 181 deaths across all cohort studies. In the ARIC cohort, after multivariable adjustment, there was a U-shaped association between the percentage of energy consumed from carbohydrate (mean 48·9%, SD 9·4) and mortality: a percentage of 50-55% energy from carbohydrate was associated with the lowest risk of mortality. In the meta-analysis of all cohorts (432 179 participants), both low carbohydrate consumption (<40%) and high carbohydrate consumption (>70%) conferred greater mortality risk than did moderate intake, which was consistent with a U-shaped association (pooled hazard ratio 1·20, 95% CI 1·09-1·32 for low carbohydrate consumption; 1·23, 1·11-1·36 for high carbohydrate consumption). However, results varied by the source of macronutrients: mortality increased when carbohydrates were exchanged for animal-derived fat or protein (1·18, 1·08-1·29) and mortality decreased when the substitutions were plant-based (0·82, 0·78-0·87). Interpretation: Both high and low percentages of carbohydrate diets were associated with increased mortality, with minimal risk observed at 50-55% carbohydrate intake. Low carbohydrate dietary patterns favouring animal-derived protein and fat sources, from sources such as lamb, beef, pork, and chicken, were associated with higher mortality, whereas those that favoured plant-derived protein and fat intake, from sources such as vegetables, nuts, peanut butter, and whole-grain breads, were associated with lower mortality, suggesting that the source of food notably modifies the association between carbohydrate intake and mortality. Funding: National Institutes of Health.
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Background: The relationship between macronutrients and cardiovascular disease and mortality is controversial. Most available data are from European and North American populations where nutrition excess is more likely, so their applicability to other populations is unclear. Methods: The Prospective Urban Rural Epidemiology (PURE) study is a large, epidemiological cohort study of individuals aged 35-70 years (enrolled between Jan 1, 2003, and March 31, 2013) in 18 countries with a median follow-up of 7·4 years (IQR 5·3-9·3). Dietary intake of 135 335 individuals was recorded using validated food frequency questionnaires. The primary outcomes were total mortality and major cardiovascular events (fatal cardiovascular disease, non-fatal myocardial infarction, stroke, and heart failure). Secondary outcomes were all myocardial infarctions, stroke, cardiovascular disease mortality, and non-cardiovascular disease mortality. Participants were categorised into quintiles of nutrient intake (carbohydrate, fats, and protein) based on percentage of energy provided by nutrients. We assessed the associations between consumption of carbohydrate, total fat, and each type of fat with cardiovascular disease and total mortality. We calculated hazard ratios (HRs) using a multivariable Cox frailty model with random intercepts to account for centre clustering. Findings: During follow-up, we documented 5796 deaths and 4784 major cardiovascular disease events. Higher carbohydrate intake was associated with an increased risk of total mortality (highest [quintile 5] vs lowest quintile [quintile 1] category, HR 1·28 [95% CI 1·12-1·46], ptrend=0·0001) but not with the risk of cardiovascular disease or cardiovascular disease mortality. Intake of total fat and each type of fat was associated with lower risk of total mortality (quintile 5 vs quintile 1, total fat: HR 0·77 [95% CI 0·67-0·87], ptrend<0·0001; saturated fat, HR 0·86 [0·76-0·99], ptrend=0·0088; monounsaturated fat: HR 0·81 [0·71-0·92], ptrend<0·0001; and polyunsaturated fat: HR 0·80 [0·71-0·89], ptrend<0·0001). Higher saturated fat intake was associated with lower risk of stroke (quintile 5 vs quintile 1, HR 0·79 [95% CI 0·64-0·98], ptrend=0·0498). Total fat and saturated and unsaturated fats were not significantly associated with risk of myocardial infarction or cardiovascular disease mortality. Interpretation: High carbohydrate intake was associated with higher risk of total mortality, whereas total fat and individual types of fat were related to lower total mortality. Total fat and types of fat were not associated with cardiovascular disease, myocardial infarction, or cardiovascular disease mortality, whereas saturated fat had an inverse association with stroke. Global dietary guidelines should be reconsidered in light of these findings. Funding: Full funding sources listed at the end of the paper (see Acknowledgments).
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Background Chocolate consumption has been inconsistently associated with risk of atrial fibrillation (AF). We investigated the association between chocolate consumption and risk of AF in Swedish adults from two cohort studies and conducted a meta-analysis to summarize available evidence from cohort studies on this topic. Methods Our study population comprised 40,009 men from the Cohort of Swedish Men and 32,486 women from the Swedish Mammography Cohort. Incident AF cases were ascertained through linkage with the Swedish National Patient Register. Published cohort studies of chocolate consumption in relation to risk of AF were identified by a PubMed search through September 14, 2017. Results During a mean follow-up of 14.6 years, AF was diagnosed in 9978 Swedish men and women. Compared with non-consumers, the multivariable hazard ratio of AF for those in the highest category of chocolate consumption (≥3-4 servings/week) was 0.96 (95% CI 0.88-1.04). In a random-effects meta-analysis of 5 cohort studies, including 180,454 participants and 16,356 AF cases, the hazard ratios of AF were 0.97 (95% CI 0.94-1.01) per 2 servings/week increase in chocolate consumption and 0.96 (95% CI 0.90-1.03) for the highest versus lowest category of chocolate consumption. Conclusion Available data provide no evidence of an association of chocolate consumption with risk of AF.
Article
Objective To evaluate the association between chocolate intake and incident clinically apparent atrial fibrillation or flutter (AF). Methods The Danish Diet, Cancer, and Health Study is a large population-based prospective cohort study. The present study is based on 55 502 participants (26 400 men and 29 102 women) aged 50–64 years who had provided information on chocolate intake at baseline. Incident cases of AF were ascertained by linkage with nationwide registries. Results During a median of 13.5 years there were 3346 cases of AF. Compared with chocolate intake less than once per month, the rate of AF was lower for people consuming 1–3 servings/month (hazard ratio (HR) 0.90, 95% confidence interval (CI) 0.82 to 0.98), 1 serving/week (HR 0.83, 95% CI 0.74 to 0.92), 2–6 servings/week (HR 0.80, 95% CI 0.71 to 0.91) and ≥1 servings/day (HR 0.84, 95% CI 0.65 to 1.09; p-linear trend <0.0001), with similar results for men and women. Conclusions Accumulating evidence indicates that moderate chocolate intake may be inversely associated with AF risk, although residual confounding cannot be ruled out.
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Atherosclerosis Risk in Communities (ARIC) is a new prospective study to investigate the etiology of atherosclerosis and its clinical sequelae and variation in cardiovascular risk factors, medical care, and disease by race, sex, place, and time. in each of four US communities—Forsyth County, North Carolina, Jackson, Mississippi, suburbs of Minneapolis, Minnesota, and Washington County, Maryland—4, 000 adults aged 45–64 years will be examined twice, three years apart. ARIC has coordinating, ultrasound, pulmonary, and electrocardiographic centers and three central laboratories. Three cohorts represent the ethnic mix of their communities; the Jackson cohort, its black population. Examinations include ultrasound scanning of carotid and popliteal arteries; lipids, lipoprotelns, and apolipoproteins assayed in the Lipid Laboratory; and coagulation, inhibition, and platelet and fibrinolytic actmty assayed in the Hemostasis Laboratory. Surveil lance for coronary heart disease will involve review of hospitalizations and deaths among community residents aged 35–74 years. ARIC aims to study atheroscle rosis by direct observation of the disease and by use of modem biochemistry.
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Background: Data on the long-term association between low-carbohydrate diets and mortality are sparse. Objective: To examine the association of low-carbohydrate diets with mortality during 26 years of follow-up in women and 20 years in men. Design: Prospective cohort study of women and men who were followed from 1980 (women) or 1986 (men) until 2006. Low-carbohydrate diets, either animal-based (emphasizing animal sources of fat and protein) or vegetable-based (emphasizing vegetable sources of fat and protein), were computed from several validated food-frequency questionnaires assessed during follow-up. Setting: Nurses' Health Study and Health Professionals' Follow-up Study. Participants: 85 168 women (aged 34 to 59 years at baseline) and 44 548 men (aged 40 to 75 years at baseline) without heart disease, cancer, or diabetes. Measurements: Investigators documented 12 555 deaths (2458 cardiovascular-related and 5780 cancer-related) in women and 8678 deaths (2746 cardiovascular-related and 2960 cancer-related) in men. Results: The overall low-carbohydrate score was associated with a modest increase in overall mortality in a pooled analysis (hazard ratio [HR] comparing extreme deciles, 1.12 [95% CI, 1.01 to 1.24]; P for trend = 0.136). The animal low-carbohydrate score was associated with higher all-cause mortality (pooled HR comparing extreme deciles, 1.23 [CI, 1.11 to 1.37]; P for trend = 0.051), cardiovascular mortality (corresponding HR, 1.14 [CI, 1.01 to 1.29]; P for trend = 0.029), and cancer mortality (corresponding HR, 1.28 [CI, 1.02 to 1.60]; P for trend = 0.089). In contrast, a higher vegetable low-carbohydrate score was associated with lower all-cause mortality (HR, 0.80 [CI, 0.75 to 0.85]; P for trend </= 0.001) and cardiovascular mortality (HR, 0.77 [CI, 0.68 to 0.87]; P for trend < 0.001). Limitations: Diet and lifestyle characteristics were assessed with some degree of error. Sensitivity analyses indicated that results were probably not substantively affected by residual confounding or an unmeasured confounder. Participants were not a representative sample of the U.S. population. Conclusion: A low-carbohydrate diet based on animal sources was associated with higher all-cause mortality in both men and women, whereas a vegetable-based low-carbohydrate diet was associated with lower all-cause and cardiovascular disease mortality rates. Primary funding source: National Institutes of Health.
Article
BACKGROUND: Low-carbohydrate diets are popular for weight loss, but their cardiovascular effects have not been well-studied, particularly in diverse populations. OBJECTIVE: To examine the effects of a low-carbohydrate diet compared with a low-fat diet on body weight and cardiovascular risk factors. DESIGN: A randomized, parallel-group trial. (ClinicalTrials.gov: NCT00609271). SETTING: A large academic medical center. PARTICIPANTS: 148 men and women without clinical cardiovascular disease and diabetes. INTERVENTION: A low-carbohydrate (<40 g/d) or low-fat (<30% of daily energy intake from total fat [<7% saturated fat]) diet. Both groups received dietary counseling at regular intervals throughout the trial. MEASUREMENTS: Data on weight, cardiovascular risk factors, and dietary composition were collected at 0, 3, 6, and 12 months. RESULTS: Sixty participants (82%) in the low-fat group and 59 (79%) in the low-carbohydrate group completed the intervention. At 12 months, participants on the low-carbohydrate diet had greater decreases in weight (mean difference in change, -3.5 kg [95% CI, -5.6 to -1.4 kg]; P = 0.002), fat mass (mean difference in change, -1.5% [CI, -2.6% to -0.4%]; P = 0.011), ratio of total-high-density lipoprotein (HDL) cholesterol (mean difference in change, -0.44 [CI, -0.71 to -0.16]; P = 0.002), and triglyceride level (mean difference in change, -0.16 mmol/L [-14.1 mg/dL] [CI, -0.31 to -0.01 mmol/L {-27.4 to -0.8 mg/dL}]; P = 0.038) and greater increases in HDL cholesterol level (mean difference in change, 0.18 mmol/L [7.0 mg/dL] [CI, 0.08 to 0.28 mmol/L {3.0 to 11.0 mg/dL}]; P < 0.001) than those on the low-fat diet. LIMITATION: Lack of clinical cardiovascular disease end points. CONCLUSION: The low-carbohydrate diet was more effective for weight loss and cardiovascular risk factor reduction than the low-fat diet. Restricting carbohydrate may be an option for persons seeking to lose weight and reduce cardiovascular risk factors.