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Low-carbohydrate diet and cardiovascular diseases in Iranian population: Tehran Lipid and Glucose Study
Journal Pre-proof Low carbohydrate diet and cardiovascular diseases in Iranian population: Tehran Lipid and Glucose study Hossein Farhadnejad, Golaleh Asghari, Farshad Teymoori, Zhaleh Tahmasebinejad, Parvin Mirmiran, Fereidoun Azizi PII:
S0939-4753(19)30442-9
DOI:
https://doi.org/10.1016/j.numecd.2019.11.012
Reference:
NUMECD 2187
To appear in:
Nutrition, Metabolism and Cardiovascular Diseases
Received Date: 24 June 2019 Revised Date:
23 November 2019
Accepted Date: 25 November 2019
Please cite this article as: Farhadnejad H, Asghari G, Teymoori F, Tahmasebinejad Z, Mirmiran P, Azizi F, Low carbohydrate diet and cardiovascular diseases in Iranian population: Tehran Lipid and Glucose study, Nutrition, Metabolism and Cardiovascular Diseases, https://doi.org/10.1016/ j.numecd.2019.11.012. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.
Low carbohydrate diet and cardiovascular diseases in Iranian population: Tehran Lipid and Glucose study Hossein
Farhadnejada,
Golaleh
Asgharib,
Farshad
Teymoorib,c,
Zhaleh
Tahmasebinejadd, Parvin Mirmiranb, Fereidoun Azizie
a
student research committee, Nutrition and Endocrine Research Center, Research Institute for
Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran b
Nutrition and Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid
Beheshti University of Medical Sciences, Tehran, Iran c
Department of Nutrition, School of Public Health, Iran University of Medical Sciences,
Tehran, Iran d
Department of Epidemiology and Biostatistics, Research Institute for Endocrine Sciences,
ShahidBeheshti University of Medical Sciences, Tehran, Iran e
Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti
University of Medical Sciences, Tehran, Iran Correspondence to: Parvin Mirmiran Nutrition and Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran P.O. Box: 19395-4741 Phone: +98 (21) 22357484 Fax: +98 (21) 22360657 E-mail: [email protected] Alternative E-mail: [email protected] Running title: low carbohydrate diet and cardiovascular diseases
1
1
Abstract
2
Background and Aims: Studies indicated that risk of cardiovascular disease (CVD) in
3
association to greater adherence to low carbohydrate diet (LCD) differs in various
4
populations. In the current study, we aimed to assess the association of LCD score with risk
5
of CVD events in a prospective population-based study.
6
Methods: CVD free participants (n=2188) were recruited from the Tehran Lipid and Glucose
7
Study (2006-2008) and followed for a mean of 6.7 years. Using a valid and reliable 168 item
8
semi-quantitative food frequency questionnaire, LCD score was determined based on the
9
percentage of energy as carbohydrate, protein, and fat, which ranged from 0 to 12. Cox
10
proportional hazard regression models, adjusted for potential confounders, were used to
11
estimate the hazard ratios (HRs) and 95% confidence interval (CI) of CVD across tertiles of
12
LCD score in women and men.
13
Results: Mean±SD age of participants (44.8% male) was 38.8±13.0 years, and median (25-
14
75 interquartile range) of the LCD score was 6 (4-8) at baseline. During follow-up, 77 (3.5%)
15
new cases of CVD were identified. After adjustment for sex, age, body mass index, physical
16
activity, smoking, energy intake, diabetes, and hypertension, there was no association
17
between LCD score and risk of CVD outcomes in all participants (HR=0.93;95%CI:0.86-
18
1.02) and women (HR=1.13; 95%CI:0.94-1.36); however, LCD score was associated with a
19
10% reduced incident of CVD events in men (HR=0.89;95%
20
trend:0.028).
21
Conclusion: Findings showed that higher adherence to LCD may be associated with a lower
22
risk of CVD outcomes in men but not in women.
23
Keywords: low carbohydrate diet; LCD; heart diseases; cardiovascular diseases; CVD
2
CI:0.80-0.98), (P for
24
Introduction
25
Cardiovascular disease (CVD) is a major public health problem worldwide [1]. Recent
26
reports showed that the greatest burden of CVD is in low- and middle-income countries, and
27
an estimated eighty percent of global CVD deaths occur in these countries [2, 3]. The risk of
28
CVD is determined by the interplay of genetic, metabolic, and environmental factors.
29
Diabetes, hypertension, dyslipidemia, tobacco use, obesity, physical inactivity, and dietary
30
factors are major risk factors for the development of CVD [3]. Among these factors, changes
31
in worldwide dietary habits, which is described as “epidemiologic transition”, and reduction
32
of physical activity are thought to be responsible for a large part of the CVD burden [3, 4].
33
Therefore, sedentary lifestyle and dietary patterns, as important modifiable risk factors for
34
CVD, have received much more attention.
35
Meals consist of a wide variety of foods with a mixture of nutrients; and also, the potential
36
synergistic and interactive effects among foods and nutrients are not always evaluated when
37
investigating a single food or nutrient; therefore, investigation of dietary patterns instead of a
38
single food or nutrient in the pathogenesis of a chronic disease is more applicable [5, 6]. The
39
Iranians population, like most people in the Middle East and North Africa (MENA) region,
40
traditionally consume large amounts of carbohydrate foods including cereals, rice, and potato
41
as main sources of energy intake [7]; therefore, assessing the effect of dietary macronutrients,
42
in the form of a dietary pattern, on risk of metabolic syndrome, diabetes, and cardiovascular
43
diseases are reasonable and warranted [8-12].
44
Currently, controversial data are available on the association between LCD and risk of CVD
45
morbidity and mortality [13-18]. Nakamura et al showed that greater adherence to diets low
46
in carbohydrate and high in protein and fat are inversely associated with CVD and total
47
mortality in women but not in men [14]. However, some cohorts conducted in european
3
48
societies, reported that low carbohydrate-high protein diets, especially with high animal
49
protein, were positively associated with CVD mortality [13, 16-18]. Furthermore, in the
50
Nurses' Health Study, diets low in carbohydrate and high in protein and fat were not related
51
to risk of coronary heart disease in women. This study indicated that diets with fat and
52
protein intake from vegetable sources moderately reduce the risk of coronary heart disease in
53
women [15].
54
Since the population of MENA region, such as the Iranian population, traditionally consume
55
large amounts of carbohydrate foods including refined grains, rice and potato, and foods with
56
higher content of simple sugars, the potential association between a dietary pattern based on
57
lower intakes of carbohydrate and the risk of CVD is currently unclear in this region, with
58
high rate of CVD incidence. Therefore, in the current study, we aimed to assess the
59
association between higher adherence to LCD score and risk of CVD events among
60
Tehranian adults. We also aimed priorly to perform stratified subgroup analysis to assess the
61
association of LCD score and risk of CVD based on sex.
62
Methods
63
Subjects
64
The current study was conducted within the framework of the Tehran Lipid and Glucose
65
Study (TLGS), an ongoing community-based prospective study performed to investigate and
66
prevent non-communicable diseases, in a representative urban population of Tehran,
67
including 15005 participants aged ≥3 years [19]. The TLGS was performed using multistage
68
cluster random sampling methods on a sample of residents from district 13 of Tehran, the
69
capital city of Iran. The first phase of TLGS began in March 1999, and data collection which
70
is conducted at 3-year intervals, is ongoing; The baseline survey was a cross-sectional study
71
conducted from 1999 to 2001, and surveys II (2002-2005), III (2006-2008), IV (2009-2011),
72
and V (2012–2015) were prospective follow-up surveys. In the third survey of the TLGS 4
73
(2006–2008), of 12523 participants, 3462 were randomly selected and agreed to complete the
74
dietary assessment.
75
For the current study, participants (aged ≥19 year) from the third TLGS examination (2006–
76
2008) were recruited based on the following eligibility criteria: those who were free of CVD,
77
had complete demographic, anthropometric, biochemical, and dietary data. Participants with
78
under- or over-reported energy intake (< 800 kcal/d or > 4200 kcal/d, respectively) (n=163),
79
or specific diets for hypertension, diabetes or dyslipidemia (n=376), and pregnant and
80
lactating women (n=52) were excluded. Participants were also excluded if they had a history
81
of CVD (n=40); some individuals fell into more than one exclusion category. The remaining
82
eligible participants (n=2352) were followed until March 2014, for a mean period of 6.7
83
years. Participants who left the study (n=164) were excluded, and final analyses were
84
performed on the data of 2188 adults.
85
The study protocol was approved by the ethics committee of the Research Institute for
86
Endocrine Sciences, affiliated to Shahid Beheshti University of Medical Sciences, Tehran,
87
Iran. A written informed consent was obtained from all subjects.
88
Dietary intake assessment
89
Dietary intake was assessed using a valid and reliable semi-quantitative 168-item food
90
frequency questionnaire (FFQ) at the baseline [20]. During a face-to-face interview,
91
participants’ intake frequency for each food item during the previous year on a daily, weekly,
92
or monthly basis was collected by trained and experienced dieticians. Portion sizes of
93
consumed foods, reported in household measures, were then converted to grams. The United
94
States Department of Agriculture (USDA) food composition table (FCT), was used for
95
computing energy and nutrient contents because the Iranian FCT was incomplete, and had
96
limited data on nutrient content of raw foods and beverages. For local food items that were
97
not available in USDA FCT, the Iranian FCT was used. 5
98
To calculate LCD score, we divided the total population into quintiles of carbohydrate (Q1:≤
99
51.59, Q2:51.60-55.84, Q3:55.85-59.21, Q4:59.22-63.30, and Q5:≥63.31%), protein
100
(Q1:≤11.79, Q2:11.80-12.94, Q3:12.95-14.05, Q4:14.06-15.40, and Q5:≥15.41%), and fat
101
(Q1:≤25.72, Q2:25.73-29.72, Q3:29.73-32.87, Q4:32.88-36.98, and Q5≥ 36.99%) intakes as
102
percentage of energy intake [21]. For carbohydrate, participants in the highest quintile
103
received 0 points, individuals in the next quintile received 1 point, and so on, down to adults
104
in the lowest quintile, who received 4 points. For protein and total fat, the order of the strata
105
was reversed; those with the highest protein and fat intakes received 4 points and those with
106
the lowest protein and fat intakes received 0 points. The scores for each macronutrient were
107
then summed to calculate LCD score, which ranged from 0 (the lowest fat and protein intakes
108
and the highest carbohydrate intakes) to 12 (the highest protein and fat intakes and the lowest
109
carbohydrate intakes). Therefore, the higher LCD score shows higher adherence of
110
individuals to the pattern of a low carbohydrate diet.
111
Physical activity assessment
112
Physical activity level of participants was determined using a Modifiable Activity
113
Questionnaire (MAQ), previously modified and validated among Iranians [22]. Individuals
114
were asked to report and identify the frequency and time spent on activities of light,
115
moderate, hard, and very hard intensity during the past 12 months, according to a list of
116
common activities of daily life; physical activity levels were expressed as metabolic
117
equivalent hours per week (MET-h/wk).
118
Clinical and biological measurements
119
Demographic, anthropometric, and biochemical data were determined at baseline (2006–
120
2008). Trained interviewers collected data on age, sex, medical history, medication use, and
121
smoking habits using a pretested questionnaire. The participant's weight was measured and
122
recorded in light clothing, without shoes or socks, using a digital scale with an accuracy of up 6
123
to 100. Height was measured to the nearest 0.1 cm in standing position without shoes, using a
124
stadiometer. BMI was computed as weight (kg) divided by height (m2).
125
Socioeconomic status (SES) was determined using two variables, education (academic and
126
non-academic education), and occupation status (employed, non-employed). For computing
127
SES score, individuals were given a score of 1 if they had academic education, or were
128
employed. Participants were given a score of 0 if they had non-academic education, or were
129
non-employed. Then, SES score was calculated by summing up the assigned scores
130
(minimum SES score of 0 to maximum score of 2); scores 0, 1, and 2 were considered as low,
131
moderate, and high SES, respectively.
132
Arterial blood pressure was measured twice on the right arm, using a mercury
133
sphygmomanometer and the Korotkoff sound technique with an accuracy of 2 mmHg for
134
each participant after a 15-minute rest while sitting on a chair, with a minimum interval of 30
135
s; the mean of the two measurements was considered as the subjects blood pressure. The
136
systolic blood pressure (SBP) was recorded when the first sound was heard and the diastolic
137
blood pressure (DBP) when the sound disappeared.
138
A blood sample was taken in a sitting position after 12-14 h of overnight fasting according to
139
standard protocol and centrifuged within 30-45 min of collection. All blood analyses were
140
done at the TLGS research laboratory on the day of blood collection. The samples were
141
analyzed using the Selectra 2 auto-analyzer (Vital Scientific, Spankeren, and Netherlands).
142
Fasting plasma glucose (FPG) was measured using an enzymatic colorimetric method with
143
glucose oxidase. Both inter- and intra-assay coefficients of variations were 2.2% for FPG.
144
These analyses were performed using commercial kits (Pars Azmoon, Tehran, Iran).
145
Definitions
7
146
The data collection of CVD outcomes has been previously provided in details [23, 24].
147
Participants are asked about any medical event during the previous year or whether related
148
events have occurred by a trained nurse. When appropriate, a trained physician collects
149
complementary data during a home visit and or a visit to the respective hospital to collect
150
data from the participants’ medical records. In the case of mortality, data are collected from
151
the hospital or the death certificate by an authorized local physician. Collected data are
152
evaluated by an outcome committee consisting of a principal investigator, an internist, an
153
endocrinologist, a cardiologist, an epidemiologist, and the physician who collects the
154
outcome data. Other experts are invited for evaluation of non-communicable disorders on an
155
as-needed basis. CVD outcomes was defined as any coronary heart disease (CHD) event,
156
stroke, or CVD death (definite fatal myocardial infarction, definite fatal CHD, and definite
157
fatal stroke) [25]. Coronary heart disease-related events included cases of definite MI
158
(diagnostic ECG and biomarkers), probable MI (positive ECG findings, cardiac symptoms or
159
signs, and missing biomarkers; or positive ECG findings and equivocal biomarkers), and
160
angiographic confirmed CHD. Stroke was considered as new neurological deficit that lasted
161
at least 24 h. History of CVD was considered as previous ischemic heart disease and/or
162
cerebrovascular accidents.
163
Eighth Joint National Committee (JNC 8) criteria was used to define hypertension as follows:
164
SBP ≥ 140mmHg, DBP ≥ 90mmHg, or taking antihypertensive medications for subjects,
165
aged <60 years, and SBP≥ 150mmHg, DBP≥90mmHg or taking antihypertensive
166
medications for those aged ≥60 years [26]. Diabetes was defined using the American
167
Diabetes Association criteria as follows [27]: fasting plasma glucose (FPG) ≥126 mg/dl or 2-
168
h post 75 gram glucose load≥200 mg/dl or taking anti-diabetic medication.
169
Statistical analysis
8
170
The Statistical Package for Social Sciences (Version 15.0; SPSS, Chicago, IL) was used for
171
all analyzes. The normality of the variables was checked using histogram charts and
172
Kolmogorov–Smirnov analysis. The baseline characteristics of the individuals are presented
173
as mean ± SD for continuous variables and percentages for categorical variables. Independent
174
two sample T test and Chi-square analyses were used to compare the continuous and
175
categorical variables, respectively, between men and women.
176
Time to event was defined as the time to end of follow-up (censored cases) or time to
177
occurance of an event, whichever occurred first. We censored participants at incase the time
178
of death due to non-CVD causes, leaving the district, or end of study follow-up at March
179
2014. Cox proportional hazard regression models were used to assess the hazard ratios (HRs)
180
and 95% confidence interval (CI) of the LCD score for CVD in all the population.We also
181
performed stratified subgroup analysis to assess the association of LCD score and risk of
182
CVD events based on sex. The potential confounders were sex, age, BMI, physical activity,
183
smoking, daily energy intake, diabetes, and hypertension. P-values <0.05 were considered to
184
be statistically significant.
185
Results
186
The mean ± SD age of participants (44.8% male) was 38.8 ±13.0 years at baseline. The
187
median (25-75 interquartile range) of LCD score was 6 (4-8), and the incidence rate of CVD
188
outcomes (per 10000 person-year) was 53 in all population. The incidence rate of CVD
189
outcomes (per 10000 person-year) was 31 and 82 in women and men, respectively. Also,
190
during 6.7 years of follow-up, 52 and 25 new cases of CVDs in men and women were
191
identified, respectively. Baseline characteristics of all population based on tertiles of LCD
192
score are shown in Table 1. Participants with higher LCD score at baseline were significantly
193
more likely to be female, younger, and had lower percentage of hypertension in compared to
194
those with the lowest score. Also, dietary intakes of whole grains, refined grain, fruits,
9
195
energy, total carbohydrate, magnesium, and total dietary fiber significantly decreased across
196
these tertiles (P <0 .05), whereas intakes of dairy, red and processed meat, nuts and legumes,
197
total fat, SAFA, MUFA, PUFA, and calcium significantly increased in subjects across the
198
tertiles of the LCD score (P <0 .05).
199
According to Table 2, in men, subjects with higher LCD score were significantly more likely
200
to be lower age and more smoked in compared to those with the lowest score. Men in the
201
highest tertile of LCD score also had higher intakes of dairy, red and processed meat, nuts
202
and legumes, protein, total fat, SAFA, MUFA, PUFA, and calcium but had lower intakes of
203
whole grain, refined grain, fruits, carbohydrate, and total dietary fiber (P<0.05). In women,
204
individuals with higher LCD score were significantly more likely to be lower age and had
205
lower hypertension prevalence in compared to those with the lowest score. Also, in women,
206
dietary intakes of whole grains, refined grain, fruits, total carbohydrate, magnesium, and total
207
dietary fiber significantly decreased across these tertiles (P<0.05), whereas intakes of dairy,
208
red and processed meat, nuts and legumes, total fat, SAFA, MUFA, PUFA, and calcium
209
significantly increased in subjects across the tertiles of the LCD score (P<0.05) (Table 3).
210
The association between LCD score and risk of CVD outcomes is shown in Table 4. In the
211
multivariable-adjusted model, there is no association between LCD score and CVD outcomes
212
in all participants (HR=0.93; 95% CI: 0.86-1.02). In the current study, stratified subgroup
213
analysis was performed to assess the association of LCD score and risk of CVD based on
214
gender. Although, there was no association between LCD score and CVD outcomes in
215
women (HR=1.13; 95% CI: 0.94-1.36), LCD score was associated with a 11% reduced
216
incidence of CVD events in men (HR=0.89; 95% CI: 0.80-0.98), (P for trend: 0.028).
217
Discussion
218
In this prospective cohort study, conducted on a representative urban Tehran population,
219
greater adherence to LCD can contribute to decreased risk of CVD-related events in men,
10
220
independent of confounding factors during a mean 6.7-year follow-up. However, there was
221
no significant association between LCD and risk for incident CVD in women and in the total
222
population.
223
Several studies indicated controversy on the association of LCD with risk of CVD outcomes
224
[13-15] or its related mortality [16-18]. Studies on young Swedish women [13, 16], general
225
population in Greece [18], or elderly men in Sweden [17] showed that low carbohydrate-high
226
protein diets were positively associated with CVD outcomes. However, in the Nurses' Health
227
Study with 20 years of follow-up, diet low in carbohydrate and high in protein was not
228
associated with increased risk of CHD [15]. The most important reason for differences in our
229
findings and those of previous studies conducted in western countries may be related to the
230
amount of carbohydrate intake and its food sources. Compared to western countries, Iranians
231
traditionally consume large amounts of carbohydrate foods such as cereals, rice, and potato as
232
main sources of energy intake [7]. It is estimated that Iranians consume more than 55% of
233
energy from carbohydrate, which is higher than the amounts consumed in western countries
234
[28, 29]. In the current study, the daily carbohydrate intake of participants was from 393 g in
235
the 1st LCD score decile to 273 g in the 10th decile. However, in a study on American
236
population, the carbohydrate intake ranged from 234.4 g in the 1st decile to 116.7 g in the 10th
237
decile [15]. The mean carbohydrate, protein, fat intakes of our population (324, 77, and 79
238
g/d, respectively) was also different with Swedish women (196, 62, and 54 g/d, respectively).
239
Furthermore, in a low carbohydrate dietary pattern, main sources of protein intake (animal
240
versus plant) among Iranians is different from those among Western populations [30];
241
Iranians have high protein intake with plant sources such as cereals, rice, potato, and legumes
242
[7, 31], which most of them are components of healthy dietary patterns [32, 33]. However, in
243
the western countries, people mainly have a high protein intake from animal sources, which
244
have been shown to increase the risk of CVD in some reports [4, 34].
11
245
Our study results are somewhat consistent with the results of the study conducted in Japan
246
[14]. Similar to Iranians, people in Japan consume about 60% of energy from carbohydrate
247
and 15% of energy from protein, which is much higher than that in Western populations [15,
248
35]. In this cohort study with long follow-up time in Japan [14], a significant negative
249
association was reported between higher adherence to LCD and risk of CVD events and
250
mortality in women. However, none of the associations were statistically significant in men
251
[14]. The mentioned study has declared that men had higher variation in dietary reports,
252
because they have more chances of eating out and cannot estimate dietary intakes accurately,
253
in comparison to women. Furthermore, higher prevalence of smoking and alcohol drinking in
254
men leads to an unhealthy lifestyle and eating pattern compared to women, which could be
255
considered as other effective factors on the association of LCD with risk of CVD [14].
256
The current study indicated an inverse association between LCD and risk of CVD outcomes
257
in men, but not in women. Dietary intakes such as carbohydrate, fat, and protein and its food
258
sources such as whole grains, cereals, fruits, legumes, red meat, and dairy across tertiles of
259
LCD score were similar in both men and women. However, the incidence rate of CVD
260
outcomes in women (31 per 10000 person-year) was lower compared to men (82 per 10000
261
person-year) after 6.7 years of follow-up. Therefore, it may be declared that the low power of
262
study due to limited number of CVD cases in women in each tertile of the LCD score has led
263
to non-significant findings in total population and women.
264
Although the mechanisms underlying the role of LCD-style diet on risk of CVD are not yet
265
fully understood, however, in general, greater adherence to carbohydrate restricted diet with
266
higher intake of vegetable protein, but not animal protein, was associated with decreased risk
267
of CVD outcomes or its related mortality [15, 34, 36]. In fact, a higher plant protein- low-
268
carbohydrate diet score leads to greater intake of unsaturated fats, fiber, and micronutrients or
269
bioactive compounds such as vitamins, minerals (magnesium and potassium), and
12
270
phytochemicals which can be effective in decreasing the risk of CVD [34, 37]. These
271
nutrients
272
hypocholesterolemic effects, increase fibrinolysis, decrease in serum LDL-C and
273
inflammatory indices such as interleukin 1β, hs-CRP, and TNF-α, and effects on body weight
274
regulation [38-40]. However, low-carbohydrate and high animal protein diet with higher
275
intake of some high protein or saturated fat content food groups such as red meat and high fat
276
dairy products may be associated with increased risk of CVD events or mortality [34, 36].
277
Considering the large population-based sample of Tehranian adults in the current study, our
278
findings on beneficial effects of plant protein-based LCD diet may potentially be
279
generalizable to the Iranians. Therefore, higher compliance of LCD–style dietary pattern with
280
higher intakes of whole grain, vegetables, legumes, and fruits could be associated with
281
decrease in risk of CVD outcomes in general population. However, given that data on the
282
association between LCD score and risk of CVD outcomes in female were non-significant;
283
more observational studies with large sample size and longer follow-up time are
284
recommended.
285
Several strengths of the current study should be noted; this cohort study was the first
286
population-based study that examined the association of LCD and risk of CVD events in the
287
MENA region. Also the food-frequency questionnaire and physical activity questionnaires
288
were valid and reliable. Furthermore, several potential confounding variables were controlled
289
in our analysis. The present study has some limitations. First, we used the USDA FCT
290
because the Iranian FCT is incomplete in some food items and micronutrients, which possibly
291
can cause measurement error. Second, the low power of study due to low sample size and
292
limited number of CVD cases especially in women was observed. Third, although we used
293
valid and reliable questionnaires for dietary and physical activity measurements, some
294
measurement bias was unavoidable. Fourth, in our country, due to cultural and religious
may be
protective
against
CVD
13
via
increase
in
insulin
sensitivity,
295
beliefs, alcohol consumption is forbidden, and estimation of alcohol consumption is not
296
possible. Therefore, we cannot consider alcohol consumption as a confounding factor.
297
Furthermore, As in observational studies, residual confounding from unmeasured or
298
unknown variables cannot be confidently excluded.
299
In conclusion, the evidence from the present study suggests that greater adherence to LCD
300
may be associated with a lower risk of CVD outcomes in men. To clarify the role of diets
301
lower in carbohydrate and higher in protein in the risk of CVD, more prospective studies with
302
long term follow up are recommended.
303
Acknowledgements
304
This study is related to the project NO. 1397/69216 From Student Research Committee,
305
Shahid Beheshti University of Medical Sciences (SBMU), Tehran, Iran. We also appreciate
306
the Student Research Committee and Research & Technology Chancellor and Research
307
Institute for Endocrine Sciences in SBMU for their financial support of this study. We
308
express our appreciation to the participants of the Tehran Lipid and Glucose Study for their
309
enthusiastic support and to the staff of the Research Institute for Endocrine Sciences, Tehran
310
Lipid and Glucose Study Unit for their valuable help. We also wish to acknowledge Dr.
311
Forough Ghanbari for critical editing of the English grammar and syntax of the manuscript.
312
Funding
313
This work was funded by a grant NO. 1397/69216 From Student Research Committee,
314
Shahid Beheshti University of Medical Sciences (SBMU), Tehran, Iran. We also appreciate
315
the Student Research Committee and Research & Technology Chancellor and Research
316
Institute for Endocrine Sciences in SBMU for their financial support of this study.
317
Disclosure of interest
318
The authors report no conflict of interest
319
Authorship 14
320
H.F, G.A, and Zh.T contributed in conception, design, and statistical analysis. G.A, F.T, and
321
H.F contributed in data collection and manuscript drafting. P.M and F.A supervised the study.
322
All
authors
approved
the
final
15
version
of
the
manuscript.
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[13] Lagiou P, Sandin S, Lof M, Trichopoulos D, Adami HO, Weiderpass E. Low carbohydrate-high protein diet and incidence of cardiovascular diseases in Swedish women: prospective cohort study. Bmj. 2012;344:e4026. [14] Nakamura Y, Okuda N, Okamura T, et al. Low-carbohydrate diets and cardiovascular and total mortality in Japanese: a 29-year follow-up of NIPPON DATA80. Br J Nutr. 2014;112:916-24. [15] Halton TL, Willett WC, Liu S, et al. Low-carbohydrate-diet score and the risk of coronary heart disease in women. N Engl J Med. 2006;355:1991-2002. [16] Lagiou P, Sandin S, Weiderpass E, et al. Low carbohydrate-high protein diet and mortality in a cohort of Swedish women. J Intern Med. 2007;261:366-74. [17] Sjogren P, Becker W, Warensjo E, et al. Mediterranean and carbohydrate-restricted diets and mortality among elderly men: a cohort study in Sweden. Am J Clin Nutr. 2010;92:96774. [18] Trichopoulou A, Psaltopoulou T, Orfanos P, Hsieh CC, Trichopoulos D. Lowcarbohydrate-high-protein diet and long-term survival in a general population cohort. Eur J Clin Nutr. 2007;61:575-81. [19] Azizi F, Ghanbarian A, Momenan AA, et al. Prevention of non-communicable disease in a population in nutrition transition: Tehran Lipid and Glucose Study phase II. Trials. 2009;10:5. [20] Mirmiran P, Esfahani FH, Mehrabi Y, Hedayati M, Azizi F. Reliability and relative validity of an FFQ for nutrients in the Tehran lipid and glucose study. Public Health Nutr. 2010;13:654-62. [21] Shirani F, Esmaillzadeh A, Keshteli AH, Adibi P, Azadbakht L. Low-carbohydrate-diet score and metabolic syndrome: An epidemiologic study among Iranian women. Nutrition. 2015;31:1124-30. [22] Momenan AA, Delshad M, Sarbazi N, Rezaei Ghaleh N, Ghanbarian A, Azizi F. Reliability and validity of the Modifiable Activity Questionnaire (MAQ) in an Iranian urban adult population. Arch Iran Med. 2012;15:279-82. [23] Hadaegh F, Harati H, Ghanbarian A, Azizi F. Association of total cholesterol versus other serum lipid parameters with the short-term prediction of cardiovascular outcomes: Tehran Lipid and Glucose Study. Eur J Cardiovasc Prev Rehabil. 2006;13:571-7. [24] Barkhordari M, Padyab M, Sardarinia M, Hadaegh F, Azizi F, Bozorgmanesh M. Survival Regression Modeling Strategies in CVD Prediction. Int J Endocrinol Metab. 2016;14:e32156. 17
[25] Nejat A, Mirbolouk M, Mohebi R, et al. Changes in lipid measures and incident coronary heart disease: Tehran Lipid & Glucose Study. Clin Biochem. 2014;47:1239-44. [26] Page MR. The JNC 8 hypertension guidelines: an in-depth guide. Am J Manag Care. 2014;20:E8. [27] Diagnosis and classification of diabetes mellitus. Diabetes Care. 2010;33 Suppl 1:S62-9. [28] Heidari Z, Feizi A, Azadbakht L, Mohammadifard N, Maghroun M, Sarrafzadegan N. Usual energy and macronutrient intakes in a large sample of Iranian middle-aged and elderly populations. Nutrition & Dietetics.0. [29] Heidari Z, Feizi A, Azadbakht L, Mohammadifard N, Maghroun M, Sarrafzadegan N. Usual energy and macronutrient intakes in a large sample of Iranian middle-aged and elderly populations. Nutrition & Dietetics. 2019;76:174-83. [30] Farhadnejad H, Asghari G, Emamat H, Mirmiran P, Azizi F. Low-Carbohydrate HighProtein Diet is Associated With Increased Risk of Incident Chronic Kidney Diseases Among Tehranian Adults. Journal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation. 2018. [31] Aljefree N, Ahmed F. Association between dietary pattern and risk of cardiovascular disease among adults in the Middle East and North Africa region: a systematic review. Food & nutrition research. 2015;59:27486-. [32] Roth GA, Johnson C, Abajobir A, et al. Global, Regional, and National Burden of Cardiovascular Diseases for 10 Causes, 1990 to 2015. Journal of the American College of Cardiology. 2017;70:1-25. [33] Trichopoulou A, Costacou T, Bamia C, Trichopoulos D. Adherence to a Mediterranean diet and survival in a Greek population. N Engl J Med. 2003;348:2599-608. [34] Fung TT, van Dam RM, Hankinson SE, Stampfer M, Willett WC, Hu FB. Lowcarbohydrate diets and all-cause and cause-specific mortality: two cohort studies. Ann Intern Med. 2010;153:289-98. [35] Zhou BF, Stamler J, Dennis B, et al. Nutrient intakes of middle-aged men and women in China, Japan, United Kingdom, and United States in the late 1990s: the INTERMAP study. J Hum Hypertens. 2003;17:623-30. [36] Kelemen LE, Kushi LH, Jacobs DR, Jr., Cerhan JR. Associations of dietary protein with disease and mortality in a prospective study of postmenopausal women. Am J Epidemiol. 2005;161:239-49. [37] Hu FB, Willett WC. Optimal diets for prevention of coronary heart disease. Jama. 2002;288:2569-78. 18
[38] Pereira MA, Pins JJ. Dietary fiber and cardiovascular disease: experimental and epidemiologic advances. Curr Atheroscler Rep. 2000;2:494-502. [39] Rangel-Huerta OD, Pastor-Villaescusa B, Aguilera CM, Gil A. A Systematic Review of the Efficacy of Bioactive Compounds in Cardiovascular Disease: Phenolic Compounds. Nutrients. 2015;7:5177-216. [40] Mozaffarian D, Kumanyika SK, Lemaitre RN, Olson JL, Burke GL, Siscovick DS. Cereal, fruit, and vegetable fiber intake and the risk of cardiovascular disease in elderly individuals. Jama. 2003;289:1659-66.
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Table 1- Baseline characteristics of participants of the Tehran Lipid and Glucose Study (2006-2008) across tertiles of low carbohydrate diet score. Tertile 1 Tertile 2 Tertile 3 P for Baseline characteristics (n=734) (n=965) (n=489) trend* Low carbohydrate diet score 2.4 ± 1.3 6.5 ± 1.1 10.0 ± 1.0 Age (years) 40.3 ± 13.5 38.2 ± 12.6 37.7 ± 12.9 < 0.001 Male (%) 54.8 42.9 33.7 < 0.001 2 Body mass index (kg/m ) 26.9 ± 4.8 26.6 ± 4.7 26.7 ± 4.8 0.360 Physical activity (MET-h/week) 13.8 (3.4-31.7) 13.8 (4.0-34.8) 13.8 (3.9-30.5) 0.589 Current smoker (%) 24.1 22.0 21.7 0.494 Diabetes (%) 4.2 3.4 4.3 0.602 Hypertension (%) 11.4 6.8 8.4 0.015 Daily dietary intakes Whole grain (serving) 2.1 (0.90-4.4) 1.7 (0.86-3.5) 1.7 (0.81-3.0) < 0.001 Refined grain (serving) 6.9 ± 4.6 4.9 ± 2.7 3.7 ± 2.1 < 0.001 Vegetable (serving) 2.8 ± 2.2 2.8 ± 1.6 2.9 ± 1.8 0.381 Fruit (serving) 3.7 ± 3.0 3.1 ± 2.3 2.4 ± 1.8 < 0.001 Nut and legume (serving) 0.26 (0.14-0.45) 0.30 (0.17-0.53) 0.30 (0.16-0.57) < 0.001 Red and processed meats (serving) 0.67 ± 0.54 0.94 ± 0.77 1.1 ± 1.0 < 0.001 Total dairy (serving) 1.5 ± 0.9 2.0 ± 1.2 2.5 ± 1.5 < 0.001 Energy (kcal) 2311 ± 750 2244 ± 701 2227 ± 697 0.027 Carbohydrate (% of energy) 64.6 ± 4.0 55.7 ± 4.5 49.4 ± 4.1 < 0.001 Fat (% of energy) 25.1 ± 4.3 33.2 ± 5.5 37.5 ± 4.3 < 0.001 Saturated fatty acids (% of energy) 8.2 ± 2.0 11.2 ± 6.4 13.1 ± 2.6 < 0.001 Monounsaturated fatty acids (% of energy) 8.6 ± 1.7 11.6 ± 2.5 13.0 ± 2.0 < 0.001 Polyunsaturated fatty acids (% of energy) 5.3 ± 1.5 7.0 ± 2.4 7.4 ± 2.1 < 0.001 Protein (% of energy) 12.8 ± 1.7 13.5 ± 2.3 15.3 ± 2.4 < 0.001 Fiber (g/1000 kcal) 19.0 ± 8.1 15.8 ± 5.6 13.4 ± 4.8 < 0.001 Sodium (mg) 4331 ± 2850 4580 ± 3819 4402 ± 3009 0.483 * Chi-square and linear regression were used to test the trend of qualitative and quantitative variables across tertiles of low carbohydrate diet (median value in each tertile), respectively.
20
Table 2- Baseline characteristics of male participants of the Tehran Lipid and Glucose Study (2006-2008) across tertiles of low carbohydrate diet score. Baseline characteristics
Tertile 1 (n=402)
Tertile 2 (n=414)
Tertile 3 (n=165)
P for trend*
Low carbohydrate diet score 2.4 ± 1.2 6.4 ± 1.1 10.0 ± 1.0 Age (years) 41.2 ± 14.2 39.1 ± 13.4 38.4 ± 14.1 0.019 2 Body mass index (kg/m ) 26.4 ± 4.1 26.6 ± 4.2 26.2 ± 4.3 0.892 Physical activity (MET-h/week) 12.5 (3.3-36.0) 11.9 (2.6-33.8) 13.0 (1.9-39.6) 0.756 Current smoker (%) 36.8 38.2 47.3 0.030 Diabetes (%) 3.2 4.1 1.8 0.535 Hypertension (%) 12.4 9.9 13.3 0.971 Daily dietary intakes Whole grain (serving) 2.4 (1.0-4.9) 2.3 (1.0-4.2) 2.0 (1.1-3.7) < 0.001 Refined grain (serving) 7.6 ± 4.7 5.4 ± 3.0 4.5 ± 2.4 < 0.001 Vegetable (serving) 2.5 ± 1.8 2.5 ± 1.5 2.5 ± 1.4 0.740 Fruit (serving) 3.5 ± 2.9 3.0 ± 2.2 2.3 ± 1.8 < 0.001 Nut and legume (serving) 0.27 (0.14-0.47) 0.32 (0.17-0.61) 0.32 (0.18-0.63) 0.003 Red and processed meats (serving) 0.56 (0.32-0.95) 0.82 (0.44-1.37) 0.97 (0.54-1.59) < 0.001 Total dairy (serving) 1.5 ± 0.9 2.0 ± 1.1 2.7 ± 1.7 < 0.001 Energy (kcal) 2407 ± 751 2346 ± 714 2455 ± 749 0.703 Carbohydrate (% of energy) 64.7 ± 3.9 56.3 ± 4.1 49.5 ± 3.9 < 0.001 Fat (% of energy) 24.7 ± 4.1 32.3 ± 5.3 36.8 ± 3.9 < 0.001 Saturated fatty acids (% of energy) 8.0 ± 1.8 11.3 ± 9.5 13.0 ± 2.8 < 0.001 Monounsaturated fatty acids (% of energy) 8.4 ± 1.7 11.1 ± 2.3 12.7 ± 1.7 < 0.001 Polyunsaturated fatty acids (% of energy) 5.2 ± 1.4 6.7 ± 2.2 7.1 ± 1.9 < 0.001 Protein (% of energy) 12.9 ± 1.6 13.7 ± 2.2 15.6 ± 2.6 < 0.001 Fiber (g/1000 kcal) 19.3 ± 8.2 15.6 ± 5.8 12.8 ± 4.9 < 0.001 Sodium (mg) 4287 ± 2783 4725 ± 4040 4078 ± 2419 0.828 * Chi-square and linear regression were used to test the trend of qualitative and quantitative variables across tertiles of low carbohydrate diet (median value in each tertile), respectively.
21
Table 3- Baseline characteristics of female participants of the Tehran Lipid and Glucose Study (20062008) across tertiles of low carbohydrate diet score. Baseline characteristics Low carbohydrate diet score Age (years) Body mass index (kg/m2) Physical activity (MET-h/week) Current smoker (%) Diabetes (%) Hypertension (%) Daily dietary intakes Whole grain (serving) Refined grain(serving) Vegetable (serving) Fruit (serving) Nut and legume (serving) Red and processed meats (serving)
Tertile 1 (n=332)
Tertile 2 (n=551)
Tertile 3 (n=324)
P for trend*
2.5 ± 1.3 39.3 ± 12.6 27.5 ± 5.5 16.3 (3.9-29.7)
6.7 ± 1.1 37.6 ± 11.9 26.6 ± 5.0 15.2 (5.5-35.7)
9.9 ± 1.0 37.3 ± 12.2 26.9 ± 5.0 13.8 (5.3-29.7)
0.028 0.090 0.589
8.7 5.4 10.2
9.8 2.9 4.5
8.6 5.6 5.9
0.977 0.884 0.012
1.7 (0.8-3.6) 6.1 ± 4.3 3.1 ± 2.6 4.0 ± 3.2 0.26 (0.14-0.44) 0.50 (0.28-0.81)
1.4 (0.8-2.9) 4.5 ± 2.3 3.0 ± 1.7 3.1 ± 2.3 0.28 (0.16-0.50) 0.67 (0.39-1.09)
1.4 (0.7-2.8) 3.2 ± 1.8 3.1 ± 2.0 2.5 ± 1.8 0.29 (0.16-0.53) 0.81 (0.46-1.46)
< 0.001 < 0.001 0.973 < 0.001 < 0.001 < 0.001
Total dairy(serving/d) 1.5 ± 1.0 1.9 ± 1.2 2.4 ± 1.3 < 0.001 Energy (kcal) 2195 ± 733 2167 ± 681 2110 ± 639 0.125 Carbohydrate (% of energy) 64.5 ± 4.1 55.2 ± 4.7 49.4 ± 4.1 < 0.001 Fat (% of energy) 25.7 ± 4.4 33.9 ± 6.1 37.8 ± 4.5 < 0.001 Saturated fatty acids (% of energy) 8.4 ± 2.2 11.1 ± 2.4 13.2 ± 2.5 < 0.001 Monounsaturated fatty acids (% of energy) 8.8 ± 1.8 11.9 ± 2.6 13.2 ± 2.1 < 0.001 Polyunsaturated fatty acids (% of energy) 5.4 ± 1.6 7.2 ± 2.5 7.6 ± 2.2 < 0.001 Protein (% of energy) 12.6 ± 1.8 13.3 ± 2.4 15.1 ± 2.3 < 0.001 Fiber (g/1000 kcal) 18.7 ± 7.9 16.0 ± 5.4 13.7 ± 4.7 < 0.001 Sodium (mg) 4385 ± 2932 4471 ± 3645 4567 ± 3260 0.490 * Chi-square and linear regression were used to test the trend of qualitative and quantitative variables across tertiles of low carbohydrate diet (median value in each tertile), respectively.
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Table 4- Risk of cardiovascular disease according to low carbohydrate diet score in the Tehran Lipid and Glucose Study* Variables Number of person-years Number of events Incidence rate per 10000 personyears (95% CI) Hazard ratio (95% CI) Model 1 Model 2 Model 3
Total population (n=2188) 2390 77 53 (43-67)
Male (n=981) 2350 52 82 (62-108)
Female (n=1207) 2423 25 31 (21-46)
0.91 (0.84-0.98) 0.94 (0.87-1.01) 0.93 (0.86-1.02)
0.91 (0.82-1.00) 0.91 (0.83-1.01) 0.89 (0.80-0.98)
0.96 (0.85-1.10) 1.00 (0.88-1.14) 1.13 (0.94-1.36)
*Cox proportional hazard regression models were used to estimate hazard ratio (HR) and 95% confidence intervals (CI) for cardiovascular disease per one score increase in LCD diet. Model 1: crude model Model 2: Adjusted for age and sex (only in all population). Model 3: Additionally adjusted for body mass index, physical activity, smoking, and daily energy intake, diabetes, hypertension, and socio-economic status.
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Highlights
•
Higher adherence to low carbohydrate diet score was not associated with risk of CVD in all population.
•
Higher adherence to low carbohydrate diet score was associated with a 11% reduced incidence of CVD events in men and can play an important role in development of CVD.
•
Greater adherence to low carbohydrate diet score was not associated with risk of CVD in women
S0939-4753(19)30442-9
DOI:
https://doi.org/10.1016/j.numecd.2019.11.012
Reference:
NUMECD 2187
To appear in:
Nutrition, Metabolism and Cardiovascular Diseases
Received Date: 24 June 2019 Revised Date:
23 November 2019
Accepted Date: 25 November 2019
Please cite this article as: Farhadnejad H, Asghari G, Teymoori F, Tahmasebinejad Z, Mirmiran P, Azizi F, Low carbohydrate diet and cardiovascular diseases in Iranian population: Tehran Lipid and Glucose study, Nutrition, Metabolism and Cardiovascular Diseases, https://doi.org/10.1016/ j.numecd.2019.11.012. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.
Low carbohydrate diet and cardiovascular diseases in Iranian population: Tehran Lipid and Glucose study Hossein
Farhadnejada,
Golaleh
Asgharib,
Farshad
Teymoorib,c,
Zhaleh
Tahmasebinejadd, Parvin Mirmiranb, Fereidoun Azizie
a
student research committee, Nutrition and Endocrine Research Center, Research Institute for
Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran b
Nutrition and Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid
Beheshti University of Medical Sciences, Tehran, Iran c
Department of Nutrition, School of Public Health, Iran University of Medical Sciences,
Tehran, Iran d
Department of Epidemiology and Biostatistics, Research Institute for Endocrine Sciences,
ShahidBeheshti University of Medical Sciences, Tehran, Iran e
Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti
University of Medical Sciences, Tehran, Iran Correspondence to: Parvin Mirmiran Nutrition and Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran P.O. Box: 19395-4741 Phone: +98 (21) 22357484 Fax: +98 (21) 22360657 E-mail: [email protected] Alternative E-mail: [email protected] Running title: low carbohydrate diet and cardiovascular diseases
1
1
Abstract
2
Background and Aims: Studies indicated that risk of cardiovascular disease (CVD) in
3
association to greater adherence to low carbohydrate diet (LCD) differs in various
4
populations. In the current study, we aimed to assess the association of LCD score with risk
5
of CVD events in a prospective population-based study.
6
Methods: CVD free participants (n=2188) were recruited from the Tehran Lipid and Glucose
7
Study (2006-2008) and followed for a mean of 6.7 years. Using a valid and reliable 168 item
8
semi-quantitative food frequency questionnaire, LCD score was determined based on the
9
percentage of energy as carbohydrate, protein, and fat, which ranged from 0 to 12. Cox
10
proportional hazard regression models, adjusted for potential confounders, were used to
11
estimate the hazard ratios (HRs) and 95% confidence interval (CI) of CVD across tertiles of
12
LCD score in women and men.
13
Results: Mean±SD age of participants (44.8% male) was 38.8±13.0 years, and median (25-
14
75 interquartile range) of the LCD score was 6 (4-8) at baseline. During follow-up, 77 (3.5%)
15
new cases of CVD were identified. After adjustment for sex, age, body mass index, physical
16
activity, smoking, energy intake, diabetes, and hypertension, there was no association
17
between LCD score and risk of CVD outcomes in all participants (HR=0.93;95%CI:0.86-
18
1.02) and women (HR=1.13; 95%CI:0.94-1.36); however, LCD score was associated with a
19
10% reduced incident of CVD events in men (HR=0.89;95%
20
trend:0.028).
21
Conclusion: Findings showed that higher adherence to LCD may be associated with a lower
22
risk of CVD outcomes in men but not in women.
23
Keywords: low carbohydrate diet; LCD; heart diseases; cardiovascular diseases; CVD
2
CI:0.80-0.98), (P for
24
Introduction
25
Cardiovascular disease (CVD) is a major public health problem worldwide [1]. Recent
26
reports showed that the greatest burden of CVD is in low- and middle-income countries, and
27
an estimated eighty percent of global CVD deaths occur in these countries [2, 3]. The risk of
28
CVD is determined by the interplay of genetic, metabolic, and environmental factors.
29
Diabetes, hypertension, dyslipidemia, tobacco use, obesity, physical inactivity, and dietary
30
factors are major risk factors for the development of CVD [3]. Among these factors, changes
31
in worldwide dietary habits, which is described as “epidemiologic transition”, and reduction
32
of physical activity are thought to be responsible for a large part of the CVD burden [3, 4].
33
Therefore, sedentary lifestyle and dietary patterns, as important modifiable risk factors for
34
CVD, have received much more attention.
35
Meals consist of a wide variety of foods with a mixture of nutrients; and also, the potential
36
synergistic and interactive effects among foods and nutrients are not always evaluated when
37
investigating a single food or nutrient; therefore, investigation of dietary patterns instead of a
38
single food or nutrient in the pathogenesis of a chronic disease is more applicable [5, 6]. The
39
Iranians population, like most people in the Middle East and North Africa (MENA) region,
40
traditionally consume large amounts of carbohydrate foods including cereals, rice, and potato
41
as main sources of energy intake [7]; therefore, assessing the effect of dietary macronutrients,
42
in the form of a dietary pattern, on risk of metabolic syndrome, diabetes, and cardiovascular
43
diseases are reasonable and warranted [8-12].
44
Currently, controversial data are available on the association between LCD and risk of CVD
45
morbidity and mortality [13-18]. Nakamura et al showed that greater adherence to diets low
46
in carbohydrate and high in protein and fat are inversely associated with CVD and total
47
mortality in women but not in men [14]. However, some cohorts conducted in european
3
48
societies, reported that low carbohydrate-high protein diets, especially with high animal
49
protein, were positively associated with CVD mortality [13, 16-18]. Furthermore, in the
50
Nurses' Health Study, diets low in carbohydrate and high in protein and fat were not related
51
to risk of coronary heart disease in women. This study indicated that diets with fat and
52
protein intake from vegetable sources moderately reduce the risk of coronary heart disease in
53
women [15].
54
Since the population of MENA region, such as the Iranian population, traditionally consume
55
large amounts of carbohydrate foods including refined grains, rice and potato, and foods with
56
higher content of simple sugars, the potential association between a dietary pattern based on
57
lower intakes of carbohydrate and the risk of CVD is currently unclear in this region, with
58
high rate of CVD incidence. Therefore, in the current study, we aimed to assess the
59
association between higher adherence to LCD score and risk of CVD events among
60
Tehranian adults. We also aimed priorly to perform stratified subgroup analysis to assess the
61
association of LCD score and risk of CVD based on sex.
62
Methods
63
Subjects
64
The current study was conducted within the framework of the Tehran Lipid and Glucose
65
Study (TLGS), an ongoing community-based prospective study performed to investigate and
66
prevent non-communicable diseases, in a representative urban population of Tehran,
67
including 15005 participants aged ≥3 years [19]. The TLGS was performed using multistage
68
cluster random sampling methods on a sample of residents from district 13 of Tehran, the
69
capital city of Iran. The first phase of TLGS began in March 1999, and data collection which
70
is conducted at 3-year intervals, is ongoing; The baseline survey was a cross-sectional study
71
conducted from 1999 to 2001, and surveys II (2002-2005), III (2006-2008), IV (2009-2011),
72
and V (2012–2015) were prospective follow-up surveys. In the third survey of the TLGS 4
73
(2006–2008), of 12523 participants, 3462 were randomly selected and agreed to complete the
74
dietary assessment.
75
For the current study, participants (aged ≥19 year) from the third TLGS examination (2006–
76
2008) were recruited based on the following eligibility criteria: those who were free of CVD,
77
had complete demographic, anthropometric, biochemical, and dietary data. Participants with
78
under- or over-reported energy intake (< 800 kcal/d or > 4200 kcal/d, respectively) (n=163),
79
or specific diets for hypertension, diabetes or dyslipidemia (n=376), and pregnant and
80
lactating women (n=52) were excluded. Participants were also excluded if they had a history
81
of CVD (n=40); some individuals fell into more than one exclusion category. The remaining
82
eligible participants (n=2352) were followed until March 2014, for a mean period of 6.7
83
years. Participants who left the study (n=164) were excluded, and final analyses were
84
performed on the data of 2188 adults.
85
The study protocol was approved by the ethics committee of the Research Institute for
86
Endocrine Sciences, affiliated to Shahid Beheshti University of Medical Sciences, Tehran,
87
Iran. A written informed consent was obtained from all subjects.
88
Dietary intake assessment
89
Dietary intake was assessed using a valid and reliable semi-quantitative 168-item food
90
frequency questionnaire (FFQ) at the baseline [20]. During a face-to-face interview,
91
participants’ intake frequency for each food item during the previous year on a daily, weekly,
92
or monthly basis was collected by trained and experienced dieticians. Portion sizes of
93
consumed foods, reported in household measures, were then converted to grams. The United
94
States Department of Agriculture (USDA) food composition table (FCT), was used for
95
computing energy and nutrient contents because the Iranian FCT was incomplete, and had
96
limited data on nutrient content of raw foods and beverages. For local food items that were
97
not available in USDA FCT, the Iranian FCT was used. 5
98
To calculate LCD score, we divided the total population into quintiles of carbohydrate (Q1:≤
99
51.59, Q2:51.60-55.84, Q3:55.85-59.21, Q4:59.22-63.30, and Q5:≥63.31%), protein
100
(Q1:≤11.79, Q2:11.80-12.94, Q3:12.95-14.05, Q4:14.06-15.40, and Q5:≥15.41%), and fat
101
(Q1:≤25.72, Q2:25.73-29.72, Q3:29.73-32.87, Q4:32.88-36.98, and Q5≥ 36.99%) intakes as
102
percentage of energy intake [21]. For carbohydrate, participants in the highest quintile
103
received 0 points, individuals in the next quintile received 1 point, and so on, down to adults
104
in the lowest quintile, who received 4 points. For protein and total fat, the order of the strata
105
was reversed; those with the highest protein and fat intakes received 4 points and those with
106
the lowest protein and fat intakes received 0 points. The scores for each macronutrient were
107
then summed to calculate LCD score, which ranged from 0 (the lowest fat and protein intakes
108
and the highest carbohydrate intakes) to 12 (the highest protein and fat intakes and the lowest
109
carbohydrate intakes). Therefore, the higher LCD score shows higher adherence of
110
individuals to the pattern of a low carbohydrate diet.
111
Physical activity assessment
112
Physical activity level of participants was determined using a Modifiable Activity
113
Questionnaire (MAQ), previously modified and validated among Iranians [22]. Individuals
114
were asked to report and identify the frequency and time spent on activities of light,
115
moderate, hard, and very hard intensity during the past 12 months, according to a list of
116
common activities of daily life; physical activity levels were expressed as metabolic
117
equivalent hours per week (MET-h/wk).
118
Clinical and biological measurements
119
Demographic, anthropometric, and biochemical data were determined at baseline (2006–
120
2008). Trained interviewers collected data on age, sex, medical history, medication use, and
121
smoking habits using a pretested questionnaire. The participant's weight was measured and
122
recorded in light clothing, without shoes or socks, using a digital scale with an accuracy of up 6
123
to 100. Height was measured to the nearest 0.1 cm in standing position without shoes, using a
124
stadiometer. BMI was computed as weight (kg) divided by height (m2).
125
Socioeconomic status (SES) was determined using two variables, education (academic and
126
non-academic education), and occupation status (employed, non-employed). For computing
127
SES score, individuals were given a score of 1 if they had academic education, or were
128
employed. Participants were given a score of 0 if they had non-academic education, or were
129
non-employed. Then, SES score was calculated by summing up the assigned scores
130
(minimum SES score of 0 to maximum score of 2); scores 0, 1, and 2 were considered as low,
131
moderate, and high SES, respectively.
132
Arterial blood pressure was measured twice on the right arm, using a mercury
133
sphygmomanometer and the Korotkoff sound technique with an accuracy of 2 mmHg for
134
each participant after a 15-minute rest while sitting on a chair, with a minimum interval of 30
135
s; the mean of the two measurements was considered as the subjects blood pressure. The
136
systolic blood pressure (SBP) was recorded when the first sound was heard and the diastolic
137
blood pressure (DBP) when the sound disappeared.
138
A blood sample was taken in a sitting position after 12-14 h of overnight fasting according to
139
standard protocol and centrifuged within 30-45 min of collection. All blood analyses were
140
done at the TLGS research laboratory on the day of blood collection. The samples were
141
analyzed using the Selectra 2 auto-analyzer (Vital Scientific, Spankeren, and Netherlands).
142
Fasting plasma glucose (FPG) was measured using an enzymatic colorimetric method with
143
glucose oxidase. Both inter- and intra-assay coefficients of variations were 2.2% for FPG.
144
These analyses were performed using commercial kits (Pars Azmoon, Tehran, Iran).
145
Definitions
7
146
The data collection of CVD outcomes has been previously provided in details [23, 24].
147
Participants are asked about any medical event during the previous year or whether related
148
events have occurred by a trained nurse. When appropriate, a trained physician collects
149
complementary data during a home visit and or a visit to the respective hospital to collect
150
data from the participants’ medical records. In the case of mortality, data are collected from
151
the hospital or the death certificate by an authorized local physician. Collected data are
152
evaluated by an outcome committee consisting of a principal investigator, an internist, an
153
endocrinologist, a cardiologist, an epidemiologist, and the physician who collects the
154
outcome data. Other experts are invited for evaluation of non-communicable disorders on an
155
as-needed basis. CVD outcomes was defined as any coronary heart disease (CHD) event,
156
stroke, or CVD death (definite fatal myocardial infarction, definite fatal CHD, and definite
157
fatal stroke) [25]. Coronary heart disease-related events included cases of definite MI
158
(diagnostic ECG and biomarkers), probable MI (positive ECG findings, cardiac symptoms or
159
signs, and missing biomarkers; or positive ECG findings and equivocal biomarkers), and
160
angiographic confirmed CHD. Stroke was considered as new neurological deficit that lasted
161
at least 24 h. History of CVD was considered as previous ischemic heart disease and/or
162
cerebrovascular accidents.
163
Eighth Joint National Committee (JNC 8) criteria was used to define hypertension as follows:
164
SBP ≥ 140mmHg, DBP ≥ 90mmHg, or taking antihypertensive medications for subjects,
165
aged <60 years, and SBP≥ 150mmHg, DBP≥90mmHg or taking antihypertensive
166
medications for those aged ≥60 years [26]. Diabetes was defined using the American
167
Diabetes Association criteria as follows [27]: fasting plasma glucose (FPG) ≥126 mg/dl or 2-
168
h post 75 gram glucose load≥200 mg/dl or taking anti-diabetic medication.
169
Statistical analysis
8
170
The Statistical Package for Social Sciences (Version 15.0; SPSS, Chicago, IL) was used for
171
all analyzes. The normality of the variables was checked using histogram charts and
172
Kolmogorov–Smirnov analysis. The baseline characteristics of the individuals are presented
173
as mean ± SD for continuous variables and percentages for categorical variables. Independent
174
two sample T test and Chi-square analyses were used to compare the continuous and
175
categorical variables, respectively, between men and women.
176
Time to event was defined as the time to end of follow-up (censored cases) or time to
177
occurance of an event, whichever occurred first. We censored participants at incase the time
178
of death due to non-CVD causes, leaving the district, or end of study follow-up at March
179
2014. Cox proportional hazard regression models were used to assess the hazard ratios (HRs)
180
and 95% confidence interval (CI) of the LCD score for CVD in all the population.We also
181
performed stratified subgroup analysis to assess the association of LCD score and risk of
182
CVD events based on sex. The potential confounders were sex, age, BMI, physical activity,
183
smoking, daily energy intake, diabetes, and hypertension. P-values <0.05 were considered to
184
be statistically significant.
185
Results
186
The mean ± SD age of participants (44.8% male) was 38.8 ±13.0 years at baseline. The
187
median (25-75 interquartile range) of LCD score was 6 (4-8), and the incidence rate of CVD
188
outcomes (per 10000 person-year) was 53 in all population. The incidence rate of CVD
189
outcomes (per 10000 person-year) was 31 and 82 in women and men, respectively. Also,
190
during 6.7 years of follow-up, 52 and 25 new cases of CVDs in men and women were
191
identified, respectively. Baseline characteristics of all population based on tertiles of LCD
192
score are shown in Table 1. Participants with higher LCD score at baseline were significantly
193
more likely to be female, younger, and had lower percentage of hypertension in compared to
194
those with the lowest score. Also, dietary intakes of whole grains, refined grain, fruits,
9
195
energy, total carbohydrate, magnesium, and total dietary fiber significantly decreased across
196
these tertiles (P <0 .05), whereas intakes of dairy, red and processed meat, nuts and legumes,
197
total fat, SAFA, MUFA, PUFA, and calcium significantly increased in subjects across the
198
tertiles of the LCD score (P <0 .05).
199
According to Table 2, in men, subjects with higher LCD score were significantly more likely
200
to be lower age and more smoked in compared to those with the lowest score. Men in the
201
highest tertile of LCD score also had higher intakes of dairy, red and processed meat, nuts
202
and legumes, protein, total fat, SAFA, MUFA, PUFA, and calcium but had lower intakes of
203
whole grain, refined grain, fruits, carbohydrate, and total dietary fiber (P<0.05). In women,
204
individuals with higher LCD score were significantly more likely to be lower age and had
205
lower hypertension prevalence in compared to those with the lowest score. Also, in women,
206
dietary intakes of whole grains, refined grain, fruits, total carbohydrate, magnesium, and total
207
dietary fiber significantly decreased across these tertiles (P<0.05), whereas intakes of dairy,
208
red and processed meat, nuts and legumes, total fat, SAFA, MUFA, PUFA, and calcium
209
significantly increased in subjects across the tertiles of the LCD score (P<0.05) (Table 3).
210
The association between LCD score and risk of CVD outcomes is shown in Table 4. In the
211
multivariable-adjusted model, there is no association between LCD score and CVD outcomes
212
in all participants (HR=0.93; 95% CI: 0.86-1.02). In the current study, stratified subgroup
213
analysis was performed to assess the association of LCD score and risk of CVD based on
214
gender. Although, there was no association between LCD score and CVD outcomes in
215
women (HR=1.13; 95% CI: 0.94-1.36), LCD score was associated with a 11% reduced
216
incidence of CVD events in men (HR=0.89; 95% CI: 0.80-0.98), (P for trend: 0.028).
217
Discussion
218
In this prospective cohort study, conducted on a representative urban Tehran population,
219
greater adherence to LCD can contribute to decreased risk of CVD-related events in men,
10
220
independent of confounding factors during a mean 6.7-year follow-up. However, there was
221
no significant association between LCD and risk for incident CVD in women and in the total
222
population.
223
Several studies indicated controversy on the association of LCD with risk of CVD outcomes
224
[13-15] or its related mortality [16-18]. Studies on young Swedish women [13, 16], general
225
population in Greece [18], or elderly men in Sweden [17] showed that low carbohydrate-high
226
protein diets were positively associated with CVD outcomes. However, in the Nurses' Health
227
Study with 20 years of follow-up, diet low in carbohydrate and high in protein was not
228
associated with increased risk of CHD [15]. The most important reason for differences in our
229
findings and those of previous studies conducted in western countries may be related to the
230
amount of carbohydrate intake and its food sources. Compared to western countries, Iranians
231
traditionally consume large amounts of carbohydrate foods such as cereals, rice, and potato as
232
main sources of energy intake [7]. It is estimated that Iranians consume more than 55% of
233
energy from carbohydrate, which is higher than the amounts consumed in western countries
234
[28, 29]. In the current study, the daily carbohydrate intake of participants was from 393 g in
235
the 1st LCD score decile to 273 g in the 10th decile. However, in a study on American
236
population, the carbohydrate intake ranged from 234.4 g in the 1st decile to 116.7 g in the 10th
237
decile [15]. The mean carbohydrate, protein, fat intakes of our population (324, 77, and 79
238
g/d, respectively) was also different with Swedish women (196, 62, and 54 g/d, respectively).
239
Furthermore, in a low carbohydrate dietary pattern, main sources of protein intake (animal
240
versus plant) among Iranians is different from those among Western populations [30];
241
Iranians have high protein intake with plant sources such as cereals, rice, potato, and legumes
242
[7, 31], which most of them are components of healthy dietary patterns [32, 33]. However, in
243
the western countries, people mainly have a high protein intake from animal sources, which
244
have been shown to increase the risk of CVD in some reports [4, 34].
11
245
Our study results are somewhat consistent with the results of the study conducted in Japan
246
[14]. Similar to Iranians, people in Japan consume about 60% of energy from carbohydrate
247
and 15% of energy from protein, which is much higher than that in Western populations [15,
248
35]. In this cohort study with long follow-up time in Japan [14], a significant negative
249
association was reported between higher adherence to LCD and risk of CVD events and
250
mortality in women. However, none of the associations were statistically significant in men
251
[14]. The mentioned study has declared that men had higher variation in dietary reports,
252
because they have more chances of eating out and cannot estimate dietary intakes accurately,
253
in comparison to women. Furthermore, higher prevalence of smoking and alcohol drinking in
254
men leads to an unhealthy lifestyle and eating pattern compared to women, which could be
255
considered as other effective factors on the association of LCD with risk of CVD [14].
256
The current study indicated an inverse association between LCD and risk of CVD outcomes
257
in men, but not in women. Dietary intakes such as carbohydrate, fat, and protein and its food
258
sources such as whole grains, cereals, fruits, legumes, red meat, and dairy across tertiles of
259
LCD score were similar in both men and women. However, the incidence rate of CVD
260
outcomes in women (31 per 10000 person-year) was lower compared to men (82 per 10000
261
person-year) after 6.7 years of follow-up. Therefore, it may be declared that the low power of
262
study due to limited number of CVD cases in women in each tertile of the LCD score has led
263
to non-significant findings in total population and women.
264
Although the mechanisms underlying the role of LCD-style diet on risk of CVD are not yet
265
fully understood, however, in general, greater adherence to carbohydrate restricted diet with
266
higher intake of vegetable protein, but not animal protein, was associated with decreased risk
267
of CVD outcomes or its related mortality [15, 34, 36]. In fact, a higher plant protein- low-
268
carbohydrate diet score leads to greater intake of unsaturated fats, fiber, and micronutrients or
269
bioactive compounds such as vitamins, minerals (magnesium and potassium), and
12
270
phytochemicals which can be effective in decreasing the risk of CVD [34, 37]. These
271
nutrients
272
hypocholesterolemic effects, increase fibrinolysis, decrease in serum LDL-C and
273
inflammatory indices such as interleukin 1β, hs-CRP, and TNF-α, and effects on body weight
274
regulation [38-40]. However, low-carbohydrate and high animal protein diet with higher
275
intake of some high protein or saturated fat content food groups such as red meat and high fat
276
dairy products may be associated with increased risk of CVD events or mortality [34, 36].
277
Considering the large population-based sample of Tehranian adults in the current study, our
278
findings on beneficial effects of plant protein-based LCD diet may potentially be
279
generalizable to the Iranians. Therefore, higher compliance of LCD–style dietary pattern with
280
higher intakes of whole grain, vegetables, legumes, and fruits could be associated with
281
decrease in risk of CVD outcomes in general population. However, given that data on the
282
association between LCD score and risk of CVD outcomes in female were non-significant;
283
more observational studies with large sample size and longer follow-up time are
284
recommended.
285
Several strengths of the current study should be noted; this cohort study was the first
286
population-based study that examined the association of LCD and risk of CVD events in the
287
MENA region. Also the food-frequency questionnaire and physical activity questionnaires
288
were valid and reliable. Furthermore, several potential confounding variables were controlled
289
in our analysis. The present study has some limitations. First, we used the USDA FCT
290
because the Iranian FCT is incomplete in some food items and micronutrients, which possibly
291
can cause measurement error. Second, the low power of study due to low sample size and
292
limited number of CVD cases especially in women was observed. Third, although we used
293
valid and reliable questionnaires for dietary and physical activity measurements, some
294
measurement bias was unavoidable. Fourth, in our country, due to cultural and religious
may be
protective
against
CVD
13
via
increase
in
insulin
sensitivity,
295
beliefs, alcohol consumption is forbidden, and estimation of alcohol consumption is not
296
possible. Therefore, we cannot consider alcohol consumption as a confounding factor.
297
Furthermore, As in observational studies, residual confounding from unmeasured or
298
unknown variables cannot be confidently excluded.
299
In conclusion, the evidence from the present study suggests that greater adherence to LCD
300
may be associated with a lower risk of CVD outcomes in men. To clarify the role of diets
301
lower in carbohydrate and higher in protein in the risk of CVD, more prospective studies with
302
long term follow up are recommended.
303
Acknowledgements
304
This study is related to the project NO. 1397/69216 From Student Research Committee,
305
Shahid Beheshti University of Medical Sciences (SBMU), Tehran, Iran. We also appreciate
306
the Student Research Committee and Research & Technology Chancellor and Research
307
Institute for Endocrine Sciences in SBMU for their financial support of this study. We
308
express our appreciation to the participants of the Tehran Lipid and Glucose Study for their
309
enthusiastic support and to the staff of the Research Institute for Endocrine Sciences, Tehran
310
Lipid and Glucose Study Unit for their valuable help. We also wish to acknowledge Dr.
311
Forough Ghanbari for critical editing of the English grammar and syntax of the manuscript.
312
Funding
313
This work was funded by a grant NO. 1397/69216 From Student Research Committee,
314
Shahid Beheshti University of Medical Sciences (SBMU), Tehran, Iran. We also appreciate
315
the Student Research Committee and Research & Technology Chancellor and Research
316
Institute for Endocrine Sciences in SBMU for their financial support of this study.
317
Disclosure of interest
318
The authors report no conflict of interest
319
Authorship 14
320
H.F, G.A, and Zh.T contributed in conception, design, and statistical analysis. G.A, F.T, and
321
H.F contributed in data collection and manuscript drafting. P.M and F.A supervised the study.
322
All
authors
approved
the
final
15
version
of
the
manuscript.
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19
Table 1- Baseline characteristics of participants of the Tehran Lipid and Glucose Study (2006-2008) across tertiles of low carbohydrate diet score. Tertile 1 Tertile 2 Tertile 3 P for Baseline characteristics (n=734) (n=965) (n=489) trend* Low carbohydrate diet score 2.4 ± 1.3 6.5 ± 1.1 10.0 ± 1.0 Age (years) 40.3 ± 13.5 38.2 ± 12.6 37.7 ± 12.9 < 0.001 Male (%) 54.8 42.9 33.7 < 0.001 2 Body mass index (kg/m ) 26.9 ± 4.8 26.6 ± 4.7 26.7 ± 4.8 0.360 Physical activity (MET-h/week) 13.8 (3.4-31.7) 13.8 (4.0-34.8) 13.8 (3.9-30.5) 0.589 Current smoker (%) 24.1 22.0 21.7 0.494 Diabetes (%) 4.2 3.4 4.3 0.602 Hypertension (%) 11.4 6.8 8.4 0.015 Daily dietary intakes Whole grain (serving) 2.1 (0.90-4.4) 1.7 (0.86-3.5) 1.7 (0.81-3.0) < 0.001 Refined grain (serving) 6.9 ± 4.6 4.9 ± 2.7 3.7 ± 2.1 < 0.001 Vegetable (serving) 2.8 ± 2.2 2.8 ± 1.6 2.9 ± 1.8 0.381 Fruit (serving) 3.7 ± 3.0 3.1 ± 2.3 2.4 ± 1.8 < 0.001 Nut and legume (serving) 0.26 (0.14-0.45) 0.30 (0.17-0.53) 0.30 (0.16-0.57) < 0.001 Red and processed meats (serving) 0.67 ± 0.54 0.94 ± 0.77 1.1 ± 1.0 < 0.001 Total dairy (serving) 1.5 ± 0.9 2.0 ± 1.2 2.5 ± 1.5 < 0.001 Energy (kcal) 2311 ± 750 2244 ± 701 2227 ± 697 0.027 Carbohydrate (% of energy) 64.6 ± 4.0 55.7 ± 4.5 49.4 ± 4.1 < 0.001 Fat (% of energy) 25.1 ± 4.3 33.2 ± 5.5 37.5 ± 4.3 < 0.001 Saturated fatty acids (% of energy) 8.2 ± 2.0 11.2 ± 6.4 13.1 ± 2.6 < 0.001 Monounsaturated fatty acids (% of energy) 8.6 ± 1.7 11.6 ± 2.5 13.0 ± 2.0 < 0.001 Polyunsaturated fatty acids (% of energy) 5.3 ± 1.5 7.0 ± 2.4 7.4 ± 2.1 < 0.001 Protein (% of energy) 12.8 ± 1.7 13.5 ± 2.3 15.3 ± 2.4 < 0.001 Fiber (g/1000 kcal) 19.0 ± 8.1 15.8 ± 5.6 13.4 ± 4.8 < 0.001 Sodium (mg) 4331 ± 2850 4580 ± 3819 4402 ± 3009 0.483 * Chi-square and linear regression were used to test the trend of qualitative and quantitative variables across tertiles of low carbohydrate diet (median value in each tertile), respectively.
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Table 2- Baseline characteristics of male participants of the Tehran Lipid and Glucose Study (2006-2008) across tertiles of low carbohydrate diet score. Baseline characteristics
Tertile 1 (n=402)
Tertile 2 (n=414)
Tertile 3 (n=165)
P for trend*
Low carbohydrate diet score 2.4 ± 1.2 6.4 ± 1.1 10.0 ± 1.0 Age (years) 41.2 ± 14.2 39.1 ± 13.4 38.4 ± 14.1 0.019 2 Body mass index (kg/m ) 26.4 ± 4.1 26.6 ± 4.2 26.2 ± 4.3 0.892 Physical activity (MET-h/week) 12.5 (3.3-36.0) 11.9 (2.6-33.8) 13.0 (1.9-39.6) 0.756 Current smoker (%) 36.8 38.2 47.3 0.030 Diabetes (%) 3.2 4.1 1.8 0.535 Hypertension (%) 12.4 9.9 13.3 0.971 Daily dietary intakes Whole grain (serving) 2.4 (1.0-4.9) 2.3 (1.0-4.2) 2.0 (1.1-3.7) < 0.001 Refined grain (serving) 7.6 ± 4.7 5.4 ± 3.0 4.5 ± 2.4 < 0.001 Vegetable (serving) 2.5 ± 1.8 2.5 ± 1.5 2.5 ± 1.4 0.740 Fruit (serving) 3.5 ± 2.9 3.0 ± 2.2 2.3 ± 1.8 < 0.001 Nut and legume (serving) 0.27 (0.14-0.47) 0.32 (0.17-0.61) 0.32 (0.18-0.63) 0.003 Red and processed meats (serving) 0.56 (0.32-0.95) 0.82 (0.44-1.37) 0.97 (0.54-1.59) < 0.001 Total dairy (serving) 1.5 ± 0.9 2.0 ± 1.1 2.7 ± 1.7 < 0.001 Energy (kcal) 2407 ± 751 2346 ± 714 2455 ± 749 0.703 Carbohydrate (% of energy) 64.7 ± 3.9 56.3 ± 4.1 49.5 ± 3.9 < 0.001 Fat (% of energy) 24.7 ± 4.1 32.3 ± 5.3 36.8 ± 3.9 < 0.001 Saturated fatty acids (% of energy) 8.0 ± 1.8 11.3 ± 9.5 13.0 ± 2.8 < 0.001 Monounsaturated fatty acids (% of energy) 8.4 ± 1.7 11.1 ± 2.3 12.7 ± 1.7 < 0.001 Polyunsaturated fatty acids (% of energy) 5.2 ± 1.4 6.7 ± 2.2 7.1 ± 1.9 < 0.001 Protein (% of energy) 12.9 ± 1.6 13.7 ± 2.2 15.6 ± 2.6 < 0.001 Fiber (g/1000 kcal) 19.3 ± 8.2 15.6 ± 5.8 12.8 ± 4.9 < 0.001 Sodium (mg) 4287 ± 2783 4725 ± 4040 4078 ± 2419 0.828 * Chi-square and linear regression were used to test the trend of qualitative and quantitative variables across tertiles of low carbohydrate diet (median value in each tertile), respectively.
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Table 3- Baseline characteristics of female participants of the Tehran Lipid and Glucose Study (20062008) across tertiles of low carbohydrate diet score. Baseline characteristics Low carbohydrate diet score Age (years) Body mass index (kg/m2) Physical activity (MET-h/week) Current smoker (%) Diabetes (%) Hypertension (%) Daily dietary intakes Whole grain (serving) Refined grain(serving) Vegetable (serving) Fruit (serving) Nut and legume (serving) Red and processed meats (serving)
Tertile 1 (n=332)
Tertile 2 (n=551)
Tertile 3 (n=324)
P for trend*
2.5 ± 1.3 39.3 ± 12.6 27.5 ± 5.5 16.3 (3.9-29.7)
6.7 ± 1.1 37.6 ± 11.9 26.6 ± 5.0 15.2 (5.5-35.7)
9.9 ± 1.0 37.3 ± 12.2 26.9 ± 5.0 13.8 (5.3-29.7)
0.028 0.090 0.589
8.7 5.4 10.2
9.8 2.9 4.5
8.6 5.6 5.9
0.977 0.884 0.012
1.7 (0.8-3.6) 6.1 ± 4.3 3.1 ± 2.6 4.0 ± 3.2 0.26 (0.14-0.44) 0.50 (0.28-0.81)
1.4 (0.8-2.9) 4.5 ± 2.3 3.0 ± 1.7 3.1 ± 2.3 0.28 (0.16-0.50) 0.67 (0.39-1.09)
1.4 (0.7-2.8) 3.2 ± 1.8 3.1 ± 2.0 2.5 ± 1.8 0.29 (0.16-0.53) 0.81 (0.46-1.46)
< 0.001 < 0.001 0.973 < 0.001 < 0.001 < 0.001
Total dairy(serving/d) 1.5 ± 1.0 1.9 ± 1.2 2.4 ± 1.3 < 0.001 Energy (kcal) 2195 ± 733 2167 ± 681 2110 ± 639 0.125 Carbohydrate (% of energy) 64.5 ± 4.1 55.2 ± 4.7 49.4 ± 4.1 < 0.001 Fat (% of energy) 25.7 ± 4.4 33.9 ± 6.1 37.8 ± 4.5 < 0.001 Saturated fatty acids (% of energy) 8.4 ± 2.2 11.1 ± 2.4 13.2 ± 2.5 < 0.001 Monounsaturated fatty acids (% of energy) 8.8 ± 1.8 11.9 ± 2.6 13.2 ± 2.1 < 0.001 Polyunsaturated fatty acids (% of energy) 5.4 ± 1.6 7.2 ± 2.5 7.6 ± 2.2 < 0.001 Protein (% of energy) 12.6 ± 1.8 13.3 ± 2.4 15.1 ± 2.3 < 0.001 Fiber (g/1000 kcal) 18.7 ± 7.9 16.0 ± 5.4 13.7 ± 4.7 < 0.001 Sodium (mg) 4385 ± 2932 4471 ± 3645 4567 ± 3260 0.490 * Chi-square and linear regression were used to test the trend of qualitative and quantitative variables across tertiles of low carbohydrate diet (median value in each tertile), respectively.
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Table 4- Risk of cardiovascular disease according to low carbohydrate diet score in the Tehran Lipid and Glucose Study* Variables Number of person-years Number of events Incidence rate per 10000 personyears (95% CI) Hazard ratio (95% CI) Model 1 Model 2 Model 3
Total population (n=2188) 2390 77 53 (43-67)
Male (n=981) 2350 52 82 (62-108)
Female (n=1207) 2423 25 31 (21-46)
0.91 (0.84-0.98) 0.94 (0.87-1.01) 0.93 (0.86-1.02)
0.91 (0.82-1.00) 0.91 (0.83-1.01) 0.89 (0.80-0.98)
0.96 (0.85-1.10) 1.00 (0.88-1.14) 1.13 (0.94-1.36)
*Cox proportional hazard regression models were used to estimate hazard ratio (HR) and 95% confidence intervals (CI) for cardiovascular disease per one score increase in LCD diet. Model 1: crude model Model 2: Adjusted for age and sex (only in all population). Model 3: Additionally adjusted for body mass index, physical activity, smoking, and daily energy intake, diabetes, hypertension, and socio-economic status.
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Highlights
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Higher adherence to low carbohydrate diet score was not associated with risk of CVD in all population.
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Higher adherence to low carbohydrate diet score was associated with a 11% reduced incidence of CVD events in men and can play an important role in development of CVD.
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Greater adherence to low carbohydrate diet score was not associated with risk of CVD in women