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Association between dietary protein intake and risk of stroke: A meta-analysis of prospective studies
Association between dietary protein intake and risk of stroke: A meta-analysis of prospective studies Xiao-Wei Zhang, Zhen Yang, Min Li, Kun Li, You-Qing Deng, ZhenYu Tang PII: DOI: Reference:
S0167-5273(16)31810-1 doi: 10.1016/j.ijcard.2016.08.106 IJCA 23373
To appear in:
International Journal of Cardiology
Received date: Accepted date:
3 July 2016 5 August 2016
Please cite this article as: Zhang Xiao-Wei, Yang Zhen, Li Min, Li Kun, Deng YouQing, Tang Zhen-Yu, Association between dietary protein intake and risk of stroke: A meta-analysis of prospective studies, International Journal of Cardiology (2016), doi: 10.1016/j.ijcard.2016.08.106
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. 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.
ACCEPTED MANUSCRIPT Association between dietary protein intake and risk of stroke: A meta-analysis of prospective studies
a
SC R
IP
T
Xiao-Wei Zhang a, c, 1, Zhen Yang b, 1, Min Li a, Kun Li a, You-Qing Deng c*, Zhen-Yu Tang a*
Department of Neurology, the Second Affiliated Hospital, Nanchang University, No. 1,
Minde Road, Nanchang330006, Jiangxi Province, People’s Republic of China. Department of Gastroenterology, Jiangxi Zhonghuan Hospital, No. 1, Zhonghuan Road,
NU
b
c
MA
Nanchang330038, Jiangxi Province, People’s Republic of China. Department of Neurology, the First Hospital of Nanchang, the Third Affiliated Hospital of
D
Nanchang University, Nanchang University, No. 128, Xiangshan Road, Nanchang330008,
Xiao-Wei Zhang and Zhen Yang contributed equally to this work.
CE P
1
TE
Jiangxi Province, People’s Republic of China.
* Zhen-Yu Tang and You-Qing Deng are common corresponding authors:
AC
E-mail: [email protected] Tel: +86 791 86311759; Fax: +86 791 86292217. Keywords: Protein intake, stroke, meta-analysis, prospective studies
ACCEPTED MANUSCRIPT Stroke is often regulated by a number of modifiable and nonmodifiable risk factors [1]. The result from a global research suggest that over 90% of the stroke risk is explained by
IP
T
modifiable risk factors, and behavioral control maybe a priority way to reduce the risk of
SC R
stroke [2]. Recently, there have evidence that dietary protein intake may be associated with the risk of stroke. A previous meta-analysis combined the results from seven prospective studies and found a significant association between dietary animal protein intake and stroke
NU
risk (RR 0.71; 95% CI 0.50-0.99) [3]. But, the data from studies included by previous
MA
meta-analyses were limited to November 2013. To our knowledge, some new prospective studies involving relationship between protein intake and risk of stroke were published from
D
then on and drawn inconsistent conclusions [4-8]. Therefore, we conducted this
TE
meta-analysis to quantitatively estimate dietary protein intake and risk of stroke, using the
CE P
most recent data.
A systematic search of published articles (through June 27, 2016) was performed using
AC
PubMed, Embase and Cochrane Library. The search was conducted using the following keywords: “protein intake”, “stroke”, “cerebrovascular accident”, “cerebrovascular disease”, “cerebral infarct”, “ischemic stroke”, “brain ischemic”, “intracranial hemorrhage”, “longitudinal studies”, “cohort studies”, “prospective studies”, “follow-up studies”. Studies were selected if: (1) community-based or population-based prospective design; (2) the study duration was longer than one year of follow-up; (3) clear definition of exposures (dietary protein intake) and outcomes (stroke); (4) reported multivariate-adjusted risk ratio (RR) or odds ratio (OR) with their confidence intervals (CIs) for estimates of stroke risk along with dietary protein intake. Study quality was assessed based on the item of Newcastle–Ottawa
ACCEPTED MANUSCRIPT Scale (NOS) [9]. Data analysis used multivariate-adjusted RRs and 95% CIs. Heterogeneity among studies
IP
T
was examined by Cochrane Q-statistic (P > 0.10 as significant heterogeneity) and the I2
SC R
statistic (I2 ≥ 50% as significant heterogeneity). In addition, stratified analyses and sensitivity analysis were performed to evaluate the potential effect modification of these variables on the
NU
results. The Begg test and Egger test were used to assess potential publication bias. For all tests, P < 0.05 was considered statistically significant. All statistical analyses were conducted
MA
with Stata 12.0 (StataCorp, College Station, TX).
We retrieved 719 articles from initial database search. Finally, a total of 12 prospective
TE
D
studies with 528,982 participants were included in the meta-analysis [4-8, 10-16]. The characteristics of the studies are presented in Table-1. Figure-1 showed the results from
CE P
random-effects models combining the pooled RR for stroke risk along with the highest versus lowest categories of dietary protein intake. In Figure-1, dietary protein intake showed
AC
no evidence for stroke risk (RR 0.98; 95% CI 0.89–1.07; I2= 66.5%). The detailed results stratified by stroke subtype, protein type, gender, population and study quality are shown in Table-2. In Table-2, dietary vegetable protein intake may reduce the risk of stroke (RR 0.9; 95% CI 0.82–0.99; I2= 0.0%). But, there was no evidence in stroke subtype, gender, population and study quality that the dietary protein intake is associated with stroke. Sensitivity analysis indicated that there was little influence in the quantitative pooled measure of RR or 95% CI when omissions of any one study. There was no statistical evidence of publication bias among studies for dietary protein intake and stroke by using Begg’s test (P = 0.163) and Egger’s test (P = 0.106).
ACCEPTED MANUSCRIPT Our meta-analysis with 12 prospective cohort studies involving 528,982 participants showed no statistically significant association between dietary protein intake and risk of
IP
T
stroke. In addition, dietary vegetable protein intake may decrease the risk of stroke.
SC R
It is notable that the result of our meta-analysis was inconsistent with a previous study [3]. However, compared with the previous meta-analysis, our study included more number of
NU
researches and participants. We assessed the quality of individual studies using the NewcastleeOttawa Scale [9], all of them were high quality. Therefore, the results of our
MA
meta-analysis should be more reliable. For the moment, the mechanisms underlying the decrease of stroke risk with dietary vegetable protein are still not completely understood.
TE
D
Results in blood pressure- lowering effect [17, 18] may link the association between dietary protein intake and the risk of stroke.
CE P
However, the potential limitations of this meta-analysis should deserve mention. First, the complicated source of protein may affect our meta-analysis results, although we stratified by protein
and
AC
animal
vegetable
protein.
In
the
included
studies,
there
were
various types of protein which possibly have different physiological functions. For instance, white meat, such as fish, maybe contains more unsaturated FAs which may reduce the risk of stroke [19], While red meat contains amounts of both saturated fat and cholesterol which has been associated with increased stroke risk [5,7]. Second, all included studies of the participants were dietary intake of protein, which were also intake of other nutrients such as fat, cholesterol and carbohydrates at the same time. These unmeasured confounding factors could be partly influenced our results, although the included researches adjusting for a wide range of confounding factors.
ACCEPTED MANUSCRIPT In conclusion, this meta-analysis of prospective studies suggests that dietary protein intake may not decrease the risk of stroke. More large-scaled and randomized controlled trials are
SC R
the stroke risk with specific protein source consumption.
IP
T
needed to confirm the effects of protein intake on stroke risk. Future study should conduct
Declaration of interest
NU
None
MA
Acknowledgments
D
ZYT and XWZ conceived and designed the experiments. ZY and YQD analyzed the data.
TE
XWZ and ZY wrote the paper. ML and KL performed the literature search and the data
AC
CE P
extraction. All authors saw and approved the final version of the manuscript.
ACCEPTED MANUSCRIPT Reference
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[1] C.L. Allen, U. Bayraktutan, Risk factors for ischaemic stroke, Int J Stroke 3 (2008)
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105-116.
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[2] V.L. Feigin, G.A. Roth, M. Naghavi, P. Parmar, R. Krishnamurthi, S. Chugh, G.A. Mensah, B. Norrving, I. Shiue, M. Ng, K. Estep, K. Cercy, C.J. Murray, M.H. Forouzanfar, Global
NU
burden of stroke and risk factors in 188 countries, during 1990-2013: a systematic
10.1016/S1474-4422(16)30073-4.
MA
analysis for the Global Burden of Disease Study 2013, Lancet Neurol (2016). DOI:
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[3] Z. Zhang, G. Xu, F. Yang, W. Zhu, X. Liu, Quantitative analysis of dietary protein intake
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and stroke risk, Neurology 83 (2014) 19-25. [4] P. Lagiou, S. Sandin, M. Lof, D. Trichopoulos, H.O. Adami, E. Weiderpass, Low
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carbohydrate-high protein diet and incidence of cardiovascular diseases in Swedish women: prospective cohort study, BMJ 344 (2012) e4026.
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[5] A.M. Bernstein, A. Pan, K.M. Rexrode, M. Stampfer, F.B. Hu, D. Mozaffarian, W.C. Willett, Dietary protein sources and the risk of stroke in men and women, Stroke 43 (2012) 637-644. [6] M. Talaei, W.P. Koh, van Dam RM, J.M. Yuan, A. Pan, Dietary soy intake is not associated with risk of cardiovascular disease mortality in Singapore Chinese adults, J. Nutr. 144 (2014) 921-928. [7] B. Haring, J.R. Misialek, C.M. Rebholz, N. Petruski-Ivleva, R.F. Gottesman, T.H. Mosley, A. Alonso, Association of Dietary Protein Consumption With Incident Silent Cerebral Infarcts and Stroke: The Atherosclerosis Risk in Communities (ARIC) Study, Stroke 46
ACCEPTED MANUSCRIPT (2015) 3443-3450. [8] C. Nagata, K. Wada, T. Tamura, T. Kawachi, K. Konishi, M. Tsuji, K. Nakamura, Dietary
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intakes of glutamic acid and glycine are associated with stroke mortality in Japanese
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adults, J. Nutr. 145 (2015) 720-728.
[9] Wells GA, Shea B, O’Connell D, et al., The Newcastle-Ottawa Scale (NOS) for Assessing the Quality of Nonrandomised Studies in Meta-Analyses:
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http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp.
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[10] K.T. Khaw, E. Barrett-Connor, Dietary potassium and stroke-associated mortality. A 12-year prospective population study, N. Engl. J. Med. 316 (1987) 235-240.
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[11] H. Iso, M.J. Stampfer, J.E. Manson, K. Rexrode, F. Hu, C.H. Hennekens, G.A. Colditz,
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F.E. Speizer, W.C. Willett, Prospective study of fat and protein intake and risk of
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intraparenchymal hemorrhage in women, Circulation 103 (2001) 856-863. [12] H. Iso, S. Sato, A. Kitamura, Y. Naito, T. Shimamoto, Y. Komachi, Fat and protein
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intakes and risk of intraparenchymal hemorrhage among middle-aged Japanese, Am. J. Epidemiol. 157 (2003) 32-39. [13] C. Sauvaget, J. Nagano, M. Hayashi, M. Yamada, Animal protein, animal fat, and cholesterol intakes and risk of cerebral infarction mortality in the adult health study, Stroke 35 (2004) 1531-1537. [14] S.R. Preis, M.J. Stampfer, D. Spiegelman, W.C. Willett, E.B. Rimm, Lack of association between dietary protein intake and risk of stroke among middle-aged men, Am. J. Clin. Nutr. 91 (2010) 39-45. [15] R.L. Prentice, Y. Huang, L.H. Kuller, L.F. Tinker, L.V. Horn, M.L. Stefanick, G. Sarto, J.
ACCEPTED MANUSCRIPT Ockene, K.C. Johnson, Biomarker-calibrated energy and protein consumption and cardiovascular disease risk among postmenopausal women, Epidemiology 22 (2011)
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170-179.
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[16] S.C. Larsson, J. Virtamo, A. Wolk, Dietary protein intake and risk of stroke in women, Atherosclerosis 224 (2012) 247-251.
Curr Opin Lipidol 14 (2003) 55–59.
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[17] L.J. Appel, The effects of protein intake on blood pressure and cardiovascular disease,
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[18] L.J. Appel, F.M. Sacks, V.J. Carey, et al., Effects of protein, monounsaturated fat, and carbohydrate intake on blood pressure and serum lipids: results of the OmniHeart
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Randomized Trial, JAMA 294 (2005) 2455–2464.
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[19] T. Shimazu, S. Kuriyama, A. Hozawa, K. Ohmori, Y. Sato, N. Nakaya, Y. Nishino, Y.
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Tsubono, I. Tsuji, Dietary patterns and cardiovascular disease mortality in Japan: a
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prospective cohort study, Int J Epidemiol 36 (2007) 600-609.
ACCEPTED MANUSCRIPT Figure-1. RR and 95% CI from dietary protein intake and stroke risk in a random effects model.
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Study year
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0.85 (0.45, 1.61) 0.32 (0.10, 1.00) 0.58 (0.26, 1.28) 0.42 (0.20, 0.85) 1.14 (0.90, 1.43) 0.87 (0.78, 0.98) 0.74 (0.61, 0.91) 1.22 (1.07, 1.40) 1.05 (1.01, 1.10) 1.05 (0.96, 1.14) 0.91 (0.78, 1.08) 1.26 (0.81, 1.96) 0.89 (0.56, 1.14) 0.81 (0.52, 1.26) 1.14 (0.72, 1.80) 1.21 (0.87, 1.69) 0.98 (0.89, 1.07)
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TE
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Khaw (1987) Iso (2001) Iso (2003) Sauvaget (2004) Preis (2010) Prentice (2011) Larsson (2012) Bernstein (2012) Lagiou (2012) Lagiou (2012) Talaei (2014) Nagata (2015) Nagata (2015) Nagata (2015) Nagata (2015) Haring (2015) Overall (I-squared = 66.5%, p = 0.000)
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RR (95% CI)
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.2
1
10
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Adjustment for covariates
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MA Japan\ Asian
14
Preis et al, 2010
USA
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Sauvaget et al, 2004
40– 69
4,775()
24-h dietary recall
Quartil e (IV vs I)
3,731(3 8)
24-h diary
Tertile (III vs I)
43,960( 100)
FFQ
Quintil e (V vs I)
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14
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Japan/ Asian
35– 89
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Iso et al, 2003
18
40– 75
Stud y qual ity 9
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Age, sex, potassium, and calories.
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Table-1. Baseline characterization of the included studies First Count Foll Partici Protein Age Intake author, ry/ ow-u pants intake (ye compa publicatio Popul p(ye (% assessm ar) rison n (year) ation ar) male) ent Khaw et al, USA 12 50– 859(61) 24-h Contin 1987 79 dietary uous recall variabl e Iso et al, USA 14 34– 85,764( FFQ Quintil 2001 59 0) e (V vs I)
Age, smoking, time interval, BMI, alcohol, menopausal status and postmenopausal hormone use, exercise, aspirin, multivitamin use, vitamin E use, n-3 fatty acid, calcium, histories of hypertension, diabetes, high cholesterol levels, total energy intake, cholesterol, fat, and protein. Age, sex, quartiles of total energy intake and BMI, hypertension, diabetes, serum total cholesterol, smoking, ethanol, and menopausal status. Age, sex, radiation dose, city, BMI, smoking status, alcohol habits, and medical history of hypertension and diabetes. Age, quintiles of percentage of energy from saturated fat, monounsaturated fat, polyunsaturated fat, trans fat, quintiles of calories, fiber, folate, vitamin B6, vitamin B12, potassium, vitamin C, magnesium, total omega-3 fatty acids, glycemic index, physical activity, family history of MI, BMI, smoking, alcohol, multivitamin use,
9
9
8
8
ACCEPTED MANUSCRIPT
USA
12
50– 79
80,730( 0)
10.4
49– 83
34,670( 0)
FFQ
Contin uous variabl e
Quintil e (V vs I)
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FFQ
Bernstein et al, 2012
Lagiou al, 2012
USA
et
USA
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Larsson et Swede al, n/ 2012 Europe an
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MA
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Prentice et al, 2011
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hypertension, hypercholesterolemia, and diabetes.
26 and 22
3055 and 4075
127,160 FFQ (34)
Quintil e (V vs I)
15.7
3049
43,396( 0)
Quintil e (V vs I)
FFQ
Ethnicity, education, history of cardiovascular disease, family history of premature cardiovascular disease, smoking status, hypertension, treated diabetes, statin use, aspirin use, prior hormone use, and recreational physical activity. Age, combination of smoking status and pack years of smoking, education, BMI, total physical activity, history of hypertension and diabetes, aspirin use, family history of MI, intakes of total energy, alcohol, calcium, cholesterol, total fat, fruits, and vegetables. age, time period, body mass index, cigarette smoking, physical exercise, parental history of early myocardial infarction, menopausal status in women, multivitamin Height, body mass index, smoking status, physical activity, education, diagnosis of hypertension, energy intake, unsaturated lipid intake, saturated lipid intake, and alcohol intake.
9
9
8
8
ACCEPTED MANUSCRIPT Singap ore/ Asian
5
45– 75
63,257( 44)
FFQ
Quartil e (IV vs I)
Age, sex, dialect, year of 8 interview, educational level, BMI, physical activity, smoking duration, cigarette smoking per day, alcohol use, baseline history of self-reported diabetes, hypertension, CHD, stroke, and total energy intake; multivariate model 2 further adjusted for dietary fiber, SFAs, MUFAs, v-3 PUFAs, and v-6 PUFAs. et Germa 22.7 45– 11,601( FFQ Quintil Age, sex, race, study center, 9 ny/ 64 44) e total energy intake, smoking, Europe (V vs cigarette years, education, an I) systolic blood pressure, use of antihypertensive medication, high-density lipoprotein cholesterol, total cholesterol, use of lipid lowering medication, body mass index, waist/hip ratio, alcohol intake, sports-related physical activity, leisure-related physical activity, carbohydrate intake, fiber intake, fat intake, and magnesium intake. et Japan/ 16 35– 29,079( FFQ Quartil Age, energy, height, BMI, 9 Asian 101 46) e physical activity, smoking (IV vs status, education, marital I) status, histories of diabetes and hypertension, and intakes of alcohol, total protein, saturated fat, polyunsaturated fat, salt, and dietary fiber. Abbreviations: BMI = body mass index; FFQ = food frequency questionnaire; MI = myocardial infarction; USA = the United States of America; CHD = Coronary Heart Disease; SFAs = Saturated Fatty Acid Sfa; MUFAs = Mono Unsaturated Fatty Acids; PUFAs = polyunsaturated fatty acids.
Nagata al, 2015
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Haring al, 2015
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Talaei et al, 2014
ACCEPTED MANUSCRIPT
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Table 2. Stratification analyses of dietary protein intake and stroke risk Heterogeneity test Group No.of studies RR(95%CI) 2 X P Total stroke 12 0.98 (0.89 - 1.07) 44.72 0.000 Ischemic stroke 8 0.94 (0.80 - 1.10) 26.06 0.000 hemorrhage stroke 4 1.05 (0.97 - 1.14) 0.62 0.892 Protein type Animal protein 8 0.94 (0.75 - 1.17) 30.89 0.000 Vegetable protein 8 0.90 (0.82 - 0.99) 2.11 0.977 Gender Women 4 0.97 (0.87 - 1.08) 28.40 0.000 Men 1 1.15 (0.99 - 1.32) 2.85 0.416 Population American 6 1.04 (0.94 - 1.14) 20.05 0.003 European 2 0.93 (0.57 - 1.50) 8.91 0.179 Asian 4 0.90 (0.74 - 1.08) 6.18 0.013 Quality score 9 7 0.89 (0.78 - 1.03) 14.35 0.110 <9 5 1.05 (0.96 - 1.15) 14.37 0.013 Abbreviations: RR = relative risk; CI = confidence interval.
I2 66.5% 73.1% 0.0% 74.1% 0.0% 75.4% 0.0% 70.1% 32.6% 83.8% 37.3% 65.2%
S0167-5273(16)31810-1 doi: 10.1016/j.ijcard.2016.08.106 IJCA 23373
To appear in:
International Journal of Cardiology
Received date: Accepted date:
3 July 2016 5 August 2016
Please cite this article as: Zhang Xiao-Wei, Yang Zhen, Li Min, Li Kun, Deng YouQing, Tang Zhen-Yu, Association between dietary protein intake and risk of stroke: A meta-analysis of prospective studies, International Journal of Cardiology (2016), doi: 10.1016/j.ijcard.2016.08.106
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. 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.
ACCEPTED MANUSCRIPT Association between dietary protein intake and risk of stroke: A meta-analysis of prospective studies
a
SC R
IP
T
Xiao-Wei Zhang a, c, 1, Zhen Yang b, 1, Min Li a, Kun Li a, You-Qing Deng c*, Zhen-Yu Tang a*
Department of Neurology, the Second Affiliated Hospital, Nanchang University, No. 1,
Minde Road, Nanchang330006, Jiangxi Province, People’s Republic of China. Department of Gastroenterology, Jiangxi Zhonghuan Hospital, No. 1, Zhonghuan Road,
NU
b
c
MA
Nanchang330038, Jiangxi Province, People’s Republic of China. Department of Neurology, the First Hospital of Nanchang, the Third Affiliated Hospital of
D
Nanchang University, Nanchang University, No. 128, Xiangshan Road, Nanchang330008,
Xiao-Wei Zhang and Zhen Yang contributed equally to this work.
CE P
1
TE
Jiangxi Province, People’s Republic of China.
* Zhen-Yu Tang and You-Qing Deng are common corresponding authors:
AC
E-mail: [email protected] Tel: +86 791 86311759; Fax: +86 791 86292217. Keywords: Protein intake, stroke, meta-analysis, prospective studies
ACCEPTED MANUSCRIPT Stroke is often regulated by a number of modifiable and nonmodifiable risk factors [1]. The result from a global research suggest that over 90% of the stroke risk is explained by
IP
T
modifiable risk factors, and behavioral control maybe a priority way to reduce the risk of
SC R
stroke [2]. Recently, there have evidence that dietary protein intake may be associated with the risk of stroke. A previous meta-analysis combined the results from seven prospective studies and found a significant association between dietary animal protein intake and stroke
NU
risk (RR 0.71; 95% CI 0.50-0.99) [3]. But, the data from studies included by previous
MA
meta-analyses were limited to November 2013. To our knowledge, some new prospective studies involving relationship between protein intake and risk of stroke were published from
D
then on and drawn inconsistent conclusions [4-8]. Therefore, we conducted this
TE
meta-analysis to quantitatively estimate dietary protein intake and risk of stroke, using the
CE P
most recent data.
A systematic search of published articles (through June 27, 2016) was performed using
AC
PubMed, Embase and Cochrane Library. The search was conducted using the following keywords: “protein intake”, “stroke”, “cerebrovascular accident”, “cerebrovascular disease”, “cerebral infarct”, “ischemic stroke”, “brain ischemic”, “intracranial hemorrhage”, “longitudinal studies”, “cohort studies”, “prospective studies”, “follow-up studies”. Studies were selected if: (1) community-based or population-based prospective design; (2) the study duration was longer than one year of follow-up; (3) clear definition of exposures (dietary protein intake) and outcomes (stroke); (4) reported multivariate-adjusted risk ratio (RR) or odds ratio (OR) with their confidence intervals (CIs) for estimates of stroke risk along with dietary protein intake. Study quality was assessed based on the item of Newcastle–Ottawa
ACCEPTED MANUSCRIPT Scale (NOS) [9]. Data analysis used multivariate-adjusted RRs and 95% CIs. Heterogeneity among studies
IP
T
was examined by Cochrane Q-statistic (P > 0.10 as significant heterogeneity) and the I2
SC R
statistic (I2 ≥ 50% as significant heterogeneity). In addition, stratified analyses and sensitivity analysis were performed to evaluate the potential effect modification of these variables on the
NU
results. The Begg test and Egger test were used to assess potential publication bias. For all tests, P < 0.05 was considered statistically significant. All statistical analyses were conducted
MA
with Stata 12.0 (StataCorp, College Station, TX).
We retrieved 719 articles from initial database search. Finally, a total of 12 prospective
TE
D
studies with 528,982 participants were included in the meta-analysis [4-8, 10-16]. The characteristics of the studies are presented in Table-1. Figure-1 showed the results from
CE P
random-effects models combining the pooled RR for stroke risk along with the highest versus lowest categories of dietary protein intake. In Figure-1, dietary protein intake showed
AC
no evidence for stroke risk (RR 0.98; 95% CI 0.89–1.07; I2= 66.5%). The detailed results stratified by stroke subtype, protein type, gender, population and study quality are shown in Table-2. In Table-2, dietary vegetable protein intake may reduce the risk of stroke (RR 0.9; 95% CI 0.82–0.99; I2= 0.0%). But, there was no evidence in stroke subtype, gender, population and study quality that the dietary protein intake is associated with stroke. Sensitivity analysis indicated that there was little influence in the quantitative pooled measure of RR or 95% CI when omissions of any one study. There was no statistical evidence of publication bias among studies for dietary protein intake and stroke by using Begg’s test (P = 0.163) and Egger’s test (P = 0.106).
ACCEPTED MANUSCRIPT Our meta-analysis with 12 prospective cohort studies involving 528,982 participants showed no statistically significant association between dietary protein intake and risk of
IP
T
stroke. In addition, dietary vegetable protein intake may decrease the risk of stroke.
SC R
It is notable that the result of our meta-analysis was inconsistent with a previous study [3]. However, compared with the previous meta-analysis, our study included more number of
NU
researches and participants. We assessed the quality of individual studies using the NewcastleeOttawa Scale [9], all of them were high quality. Therefore, the results of our
MA
meta-analysis should be more reliable. For the moment, the mechanisms underlying the decrease of stroke risk with dietary vegetable protein are still not completely understood.
TE
D
Results in blood pressure- lowering effect [17, 18] may link the association between dietary protein intake and the risk of stroke.
CE P
However, the potential limitations of this meta-analysis should deserve mention. First, the complicated source of protein may affect our meta-analysis results, although we stratified by protein
and
AC
animal
vegetable
protein.
In
the
included
studies,
there
were
various types of protein which possibly have different physiological functions. For instance, white meat, such as fish, maybe contains more unsaturated FAs which may reduce the risk of stroke [19], While red meat contains amounts of both saturated fat and cholesterol which has been associated with increased stroke risk [5,7]. Second, all included studies of the participants were dietary intake of protein, which were also intake of other nutrients such as fat, cholesterol and carbohydrates at the same time. These unmeasured confounding factors could be partly influenced our results, although the included researches adjusting for a wide range of confounding factors.
ACCEPTED MANUSCRIPT In conclusion, this meta-analysis of prospective studies suggests that dietary protein intake may not decrease the risk of stroke. More large-scaled and randomized controlled trials are
SC R
the stroke risk with specific protein source consumption.
IP
T
needed to confirm the effects of protein intake on stroke risk. Future study should conduct
Declaration of interest
NU
None
MA
Acknowledgments
D
ZYT and XWZ conceived and designed the experiments. ZY and YQD analyzed the data.
TE
XWZ and ZY wrote the paper. ML and KL performed the literature search and the data
AC
CE P
extraction. All authors saw and approved the final version of the manuscript.
ACCEPTED MANUSCRIPT Reference
T
[1] C.L. Allen, U. Bayraktutan, Risk factors for ischaemic stroke, Int J Stroke 3 (2008)
IP
105-116.
SC R
[2] V.L. Feigin, G.A. Roth, M. Naghavi, P. Parmar, R. Krishnamurthi, S. Chugh, G.A. Mensah, B. Norrving, I. Shiue, M. Ng, K. Estep, K. Cercy, C.J. Murray, M.H. Forouzanfar, Global
NU
burden of stroke and risk factors in 188 countries, during 1990-2013: a systematic
10.1016/S1474-4422(16)30073-4.
MA
analysis for the Global Burden of Disease Study 2013, Lancet Neurol (2016). DOI:
D
[3] Z. Zhang, G. Xu, F. Yang, W. Zhu, X. Liu, Quantitative analysis of dietary protein intake
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and stroke risk, Neurology 83 (2014) 19-25. [4] P. Lagiou, S. Sandin, M. Lof, D. Trichopoulos, H.O. Adami, E. Weiderpass, Low
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carbohydrate-high protein diet and incidence of cardiovascular diseases in Swedish women: prospective cohort study, BMJ 344 (2012) e4026.
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[5] A.M. Bernstein, A. Pan, K.M. Rexrode, M. Stampfer, F.B. Hu, D. Mozaffarian, W.C. Willett, Dietary protein sources and the risk of stroke in men and women, Stroke 43 (2012) 637-644. [6] M. Talaei, W.P. Koh, van Dam RM, J.M. Yuan, A. Pan, Dietary soy intake is not associated with risk of cardiovascular disease mortality in Singapore Chinese adults, J. Nutr. 144 (2014) 921-928. [7] B. Haring, J.R. Misialek, C.M. Rebholz, N. Petruski-Ivleva, R.F. Gottesman, T.H. Mosley, A. Alonso, Association of Dietary Protein Consumption With Incident Silent Cerebral Infarcts and Stroke: The Atherosclerosis Risk in Communities (ARIC) Study, Stroke 46
ACCEPTED MANUSCRIPT (2015) 3443-3450. [8] C. Nagata, K. Wada, T. Tamura, T. Kawachi, K. Konishi, M. Tsuji, K. Nakamura, Dietary
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intakes of glutamic acid and glycine are associated with stroke mortality in Japanese
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adults, J. Nutr. 145 (2015) 720-728.
[9] Wells GA, Shea B, O’Connell D, et al., The Newcastle-Ottawa Scale (NOS) for Assessing the Quality of Nonrandomised Studies in Meta-Analyses:
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http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp.
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[10] K.T. Khaw, E. Barrett-Connor, Dietary potassium and stroke-associated mortality. A 12-year prospective population study, N. Engl. J. Med. 316 (1987) 235-240.
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[11] H. Iso, M.J. Stampfer, J.E. Manson, K. Rexrode, F. Hu, C.H. Hennekens, G.A. Colditz,
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F.E. Speizer, W.C. Willett, Prospective study of fat and protein intake and risk of
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intraparenchymal hemorrhage in women, Circulation 103 (2001) 856-863. [12] H. Iso, S. Sato, A. Kitamura, Y. Naito, T. Shimamoto, Y. Komachi, Fat and protein
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intakes and risk of intraparenchymal hemorrhage among middle-aged Japanese, Am. J. Epidemiol. 157 (2003) 32-39. [13] C. Sauvaget, J. Nagano, M. Hayashi, M. Yamada, Animal protein, animal fat, and cholesterol intakes and risk of cerebral infarction mortality in the adult health study, Stroke 35 (2004) 1531-1537. [14] S.R. Preis, M.J. Stampfer, D. Spiegelman, W.C. Willett, E.B. Rimm, Lack of association between dietary protein intake and risk of stroke among middle-aged men, Am. J. Clin. Nutr. 91 (2010) 39-45. [15] R.L. Prentice, Y. Huang, L.H. Kuller, L.F. Tinker, L.V. Horn, M.L. Stefanick, G. Sarto, J.
ACCEPTED MANUSCRIPT Ockene, K.C. Johnson, Biomarker-calibrated energy and protein consumption and cardiovascular disease risk among postmenopausal women, Epidemiology 22 (2011)
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170-179.
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[16] S.C. Larsson, J. Virtamo, A. Wolk, Dietary protein intake and risk of stroke in women, Atherosclerosis 224 (2012) 247-251.
Curr Opin Lipidol 14 (2003) 55–59.
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[17] L.J. Appel, The effects of protein intake on blood pressure and cardiovascular disease,
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[18] L.J. Appel, F.M. Sacks, V.J. Carey, et al., Effects of protein, monounsaturated fat, and carbohydrate intake on blood pressure and serum lipids: results of the OmniHeart
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Randomized Trial, JAMA 294 (2005) 2455–2464.
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[19] T. Shimazu, S. Kuriyama, A. Hozawa, K. Ohmori, Y. Sato, N. Nakaya, Y. Nishino, Y.
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Tsubono, I. Tsuji, Dietary patterns and cardiovascular disease mortality in Japan: a
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prospective cohort study, Int J Epidemiol 36 (2007) 600-609.
ACCEPTED MANUSCRIPT Figure-1. RR and 95% CI from dietary protein intake and stroke risk in a random effects model.
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Study year
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0.85 (0.45, 1.61) 0.32 (0.10, 1.00) 0.58 (0.26, 1.28) 0.42 (0.20, 0.85) 1.14 (0.90, 1.43) 0.87 (0.78, 0.98) 0.74 (0.61, 0.91) 1.22 (1.07, 1.40) 1.05 (1.01, 1.10) 1.05 (0.96, 1.14) 0.91 (0.78, 1.08) 1.26 (0.81, 1.96) 0.89 (0.56, 1.14) 0.81 (0.52, 1.26) 1.14 (0.72, 1.80) 1.21 (0.87, 1.69) 0.98 (0.89, 1.07)
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Khaw (1987) Iso (2001) Iso (2003) Sauvaget (2004) Preis (2010) Prentice (2011) Larsson (2012) Bernstein (2012) Lagiou (2012) Lagiou (2012) Talaei (2014) Nagata (2015) Nagata (2015) Nagata (2015) Nagata (2015) Haring (2015) Overall (I-squared = 66.5%, p = 0.000)
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Table-1. Baseline characterization of the included studies First Count Foll Partici Protein Age Intake author, ry/ ow-u pants intake (ye compa publicatio Popul p(ye (% assessm ar) rison n (year) ation ar) male) ent Khaw et al, USA 12 50– 859(61) 24-h Contin 1987 79 dietary uous recall variabl e Iso et al, USA 14 34– 85,764( FFQ Quintil 2001 59 0) e (V vs I)
Age, smoking, time interval, BMI, alcohol, menopausal status and postmenopausal hormone use, exercise, aspirin, multivitamin use, vitamin E use, n-3 fatty acid, calcium, histories of hypertension, diabetes, high cholesterol levels, total energy intake, cholesterol, fat, and protein. Age, sex, quartiles of total energy intake and BMI, hypertension, diabetes, serum total cholesterol, smoking, ethanol, and menopausal status. Age, sex, radiation dose, city, BMI, smoking status, alcohol habits, and medical history of hypertension and diabetes. Age, quintiles of percentage of energy from saturated fat, monounsaturated fat, polyunsaturated fat, trans fat, quintiles of calories, fiber, folate, vitamin B6, vitamin B12, potassium, vitamin C, magnesium, total omega-3 fatty acids, glycemic index, physical activity, family history of MI, BMI, smoking, alcohol, multivitamin use,
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34,670( 0)
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Quintil e (V vs I)
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Ethnicity, education, history of cardiovascular disease, family history of premature cardiovascular disease, smoking status, hypertension, treated diabetes, statin use, aspirin use, prior hormone use, and recreational physical activity. Age, combination of smoking status and pack years of smoking, education, BMI, total physical activity, history of hypertension and diabetes, aspirin use, family history of MI, intakes of total energy, alcohol, calcium, cholesterol, total fat, fruits, and vegetables. age, time period, body mass index, cigarette smoking, physical exercise, parental history of early myocardial infarction, menopausal status in women, multivitamin Height, body mass index, smoking status, physical activity, education, diagnosis of hypertension, energy intake, unsaturated lipid intake, saturated lipid intake, and alcohol intake.
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Age, sex, dialect, year of 8 interview, educational level, BMI, physical activity, smoking duration, cigarette smoking per day, alcohol use, baseline history of self-reported diabetes, hypertension, CHD, stroke, and total energy intake; multivariate model 2 further adjusted for dietary fiber, SFAs, MUFAs, v-3 PUFAs, and v-6 PUFAs. et Germa 22.7 45– 11,601( FFQ Quintil Age, sex, race, study center, 9 ny/ 64 44) e total energy intake, smoking, Europe (V vs cigarette years, education, an I) systolic blood pressure, use of antihypertensive medication, high-density lipoprotein cholesterol, total cholesterol, use of lipid lowering medication, body mass index, waist/hip ratio, alcohol intake, sports-related physical activity, leisure-related physical activity, carbohydrate intake, fiber intake, fat intake, and magnesium intake. et Japan/ 16 35– 29,079( FFQ Quartil Age, energy, height, BMI, 9 Asian 101 46) e physical activity, smoking (IV vs status, education, marital I) status, histories of diabetes and hypertension, and intakes of alcohol, total protein, saturated fat, polyunsaturated fat, salt, and dietary fiber. Abbreviations: BMI = body mass index; FFQ = food frequency questionnaire; MI = myocardial infarction; USA = the United States of America; CHD = Coronary Heart Disease; SFAs = Saturated Fatty Acid Sfa; MUFAs = Mono Unsaturated Fatty Acids; PUFAs = polyunsaturated fatty acids.
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Table 2. Stratification analyses of dietary protein intake and stroke risk Heterogeneity test Group No.of studies RR(95%CI) 2 X P Total stroke 12 0.98 (0.89 - 1.07) 44.72 0.000 Ischemic stroke 8 0.94 (0.80 - 1.10) 26.06 0.000 hemorrhage stroke 4 1.05 (0.97 - 1.14) 0.62 0.892 Protein type Animal protein 8 0.94 (0.75 - 1.17) 30.89 0.000 Vegetable protein 8 0.90 (0.82 - 0.99) 2.11 0.977 Gender Women 4 0.97 (0.87 - 1.08) 28.40 0.000 Men 1 1.15 (0.99 - 1.32) 2.85 0.416 Population American 6 1.04 (0.94 - 1.14) 20.05 0.003 European 2 0.93 (0.57 - 1.50) 8.91 0.179 Asian 4 0.90 (0.74 - 1.08) 6.18 0.013 Quality score 9 7 0.89 (0.78 - 1.03) 14.35 0.110 <9 5 1.05 (0.96 - 1.15) 14.37 0.013 Abbreviations: RR = relative risk; CI = confidence interval.
I2 66.5% 73.1% 0.0% 74.1% 0.0% 75.4% 0.0% 70.1% 32.6% 83.8% 37.3% 65.2%