Literature DB >> 29490964

Mediating effects of metabolic factors on the association between fruit or vegetable intake and cardiovascular disease: the Korean National Health and Nutrition Examination Survey.

Hye Ah Lee1, Dohee Lim2, Kyungwon Oh2, Eun Jung Kim3, Hyesook Park4.   

Abstract

OBJECTIVE: We assessed the mediating effects of metabolic components on the relationship between fruit or vegetable intake and cardiovascular disease (CVD).
DESIGN: Cross-sectional study.
SETTING: This study was conducted using data from the 2013-2015 Korean National Health and Nutrition Examination Survey, which is a national representative cross-sectional survey to assess health and nutritional status in the Korean population. METHOD AND ANALYSIS: A total of 9040 subjects (3555 males and 5485 females) aged ≥25 years were included in the study. Physician-diagnosed CVD via self-report was used as the outcome. Fruit or vegetable intake was measured via a dish-based semiquantitative food frequency questionnaire and grouped into categories (<1 time/day, 1 time/day, 2 times/day and ≥3 times/day). Systolic blood pressure (SBP), cholesterol and fasting glucose were considered metabolic mediators, and the bootstrap method was used to assess mediating effect.
RESULTS: About 1.8% of adults aged 25-64 years had CVD. According to the result of 'process' macro, the confounder-adjusted risk for CVD decreased by 14% (OR=0.86, 95% CI 0.74 to 0.98) as fruit, but not vegetable, intake was increased by one unit per day. After additional adjustment for three metabolic factors simultaneously, the OR was attenuated to 0.89 (95% CI 0.77 to 1.03). This result indicates that the indirect effect of three metabolic factors accounted for 21.4% of the relationship between fruit intake and CVD. SBP was a more important metabolic mediator than the other factors. The indirect effect by metabolic factors accounted for 30.0% when body mass index was additionally controlled as a mediator, and SBP still had an independent effect compared with the other mediators.
CONCLUSIONS: Our results indicate that controlling SBP may lessen the CVD risk, and a diet rich in fruits can regulate SBP which, in turn, reduces CVD risk. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Entities:  

Keywords:  blood pressure; cardiovascular disease

Mesh:

Substances:

Year:  2018        PMID: 29490964      PMCID: PMC5855238          DOI: 10.1136/bmjopen-2017-019620

Source DB:  PubMed          Journal:  BMJ Open        ISSN: 2044-6055            Impact factor:   2.692


In this study, we assessed how fruit or vegetable intake is related to cardiovascular disease by assessing the indirect effect of systolic blood pressure, total cholesterol and fasting glucose, including body mass index. Given studies were not interested in this topic, so this study has scientific value. Using national representative data source, we sought to generalise the research findings. However, these results were derived from a cross-sectional study design, so causal relationships could not be effectively drawn. Therefore, it is necessary to pay attention to the interpretation of research results.

Introduction

Cardiovascular diseases (CVDs) are responsible for mortality worldwide; a report from the WHO stated that CVDs accounted for 31% of all deaths worldwide in 2015.1 Although mortality from ischaemic heart disease has shown a flat trend and that from cerebrovascular disease has shown a declining trend in the Republic of Korea since 2005, these causes of death remain highly ranked.2 Several risk factors for CVDs, including metabolic factors, such as high glucose, high blood pressure and high cholesterol, have been suggested.3 Several studies have suggested that these metabolic factors are also linked to risk factors (eg, body mass index (BMI) and dietary factors) and CVD risk as mediators.4 5 The causal link between these mediators and disease risk can help explain how intervention of risk factors works. However, previous studies focused on a single relationship between a risk factor and a disease rather than the mediating effects. Excessive risk for CVD caused by poor diet and chronic diseases was reported from a study of global burden of disease (GBD). In addition, the GBD study established possible causal mediating relationships between a diet poor in fruits or vegetables, metabolic mediators (blood pressure, cholesterol and glucose) and disease.4 Moreover, a recent meta-analysis reported that the beneficial effects of fruits and vegetables intake were also shown in CVD, as well as in cancer and all-cause mortality.6 The metabolic mediators mentioned above have also been linked to BMI and CVD.4 The effect of a diet rich in fruits and vegetables on BMI has been reported through epidemiological studies,7 but few studies have assessed BMI as a mediator. There is a need to study the degree to which these metabolic factors contribute to the relationship between risk factors and disease. Although the evidence for the association between fruit/vegetable intake and CVD is relatively strong,8 9 clarifying the potential biological pathway mechanisms could substantially add to our knowledge. Thus, using cross-sectional survey data from the 2013–2015 Korean National Health and Nutrition Examination Survey (KNHANES), we assessed the mediating effects of metabolic components applied to a confirmatory model. Furthermore, we assessed how the BMI contributes to the relationship between fruit or vegetable intake and CVD as a confounder or mediator.

Methods

Study subjects

This study was conducted using data from the 2013–2015 KNHANES, which is a national representative cross-sectional survey to assess health and nutritional status in the Korean population (response rate=78.3%). It consists of a health interview, health examination and a nutrition survey. A number of variables were collected by trained staff, including physicians, medical technicians and dietitians. The detailed KNHANES survey method has already been described.10 The food frequency questionnaire (FFQ) was changed to a dish-based semiquantitative FFQ based on a 2012 survey. The survey assessed subjects 19–64 years of age. Details regarding the development process and validation results of the FFQ tool have been previously published elsewhere.11 12 We used the sixth survey from 2013 to 2015 by sampling according to the survey cycle. This study included subjects ≥25 years. Additionally, the eligible study population included the respondents with data from all three parts of the survey. Of the subjects aged 25–64 who participated in the survey (n=12 258), 73.7% participated in all three parts of the survey. A total of 9040 subjects (3555 males and 5485 females) were included in the study.

Fruit and vegetable intake

The dish-based semiquantitative FFQ was composed of 112 items and provided information on typical dietary consumption for 1 year using a nine-point scale (less than once per month or never, once per month, two to three times per month, once per week, two to four times per week, five to six times per week, once per day, twice per day and three times per day) and three levels to represent the amount consumed by referring to a standard amount (less, standard and more). Based on a previous study,4 we excluded pickled and salted vegetables, kimchi and fruit juice. Vegetable intake and fruit intake were evaluated based on 15 items and 12 items, respectively (online supplementary table 1). The frequency of fruit intake was used after adjusting for seasonal fruit. Estimated intakes of fruits and vegetables were calculated on the FFQ by multiplying the frequency of each food (as described above) by the selected amount consumed: small (0.5), medium (1) and large (1.5). Fruit and vegetable intake was expressed in four categories (<1 time/day, 1 time/day, 2 times/day and ≥3 times/day).

Outcome and covariate data

We used data from the health-related questionnaire for the diseases diagnosed by physicians. We selected the questions about stroke, myocardial infarction and angina pectoris for the CVD-related diseases. If a subject answered ‘yes’ to any of the three diseases, we considered that the subject had CVD. Additionally, we separately considered subjects who answered ‘yes’ on the question about current illness with a physician’s diagnosis and those who responded ‘yes’ to a question about receiving treatment for a disease. Using the measured height and weight information, BMI was calculated in units of kg/m2. Blood pressure was measured three times in total, and the average value of the second and third measurements was used. Total cholesterol and glucose were measured by taking blood from fasting state. We used data on sex, age, quartiles of income, region (urban/rural), current smoker and survey year as covariates through a literature review13 and the results of a univariate analysis. We used quartile data for income instead of education level as a socioeconomic indicator because income may be directly linked to food purchases.14 The question about physical activity was changed from the 2014 survey, so we did not consider physical activity.

Statistical analysis

The basic characteristics of the study subjects are presented as weighted percentages or weighted means with SEs by considering the multistage sampling survey method. The distributions of the basic characteristics according to fruit or vegetable intake level were assessed using the trend test under the random sampling condition. In the main analysis, CVD was considered the outcome (Y), and fruit or vegetable intake was considered an independent variable (X). Systolic blood pressure (SBP) (M1), total cholesterol (M2) and fasting glucose (M3) were applied as metabolic mediators (M). Additionally, BMI was considered as either a covariate or mediator. We used the ‘process’ macro based on the bootstrap method (V.2.16.3) suggested by Andrew to assess the mediating effects.15 In this analysis, we applied 10 000 bootstraps. We separately or simultaneously assessed the indirect effect of the metabolic mediators on the association between dietary factors and CVD. First, we examined the association under the controlling covariates (sex, age, income, region (urban/rural), present smoking and survey year) through four basic steps to assess mediation.16 Step 1: association between dietary factors and CVD (X → Y; total effect and was marked path ‘c’); step 2: association between dietary factors and metabolic mediators (X → Mi; marked path ‘a’); step 3: association between metabolic mediators and CVD after controlling for metabolic mediators (Mi → Y; marked path ‘b’); and step 4: association between dietary factors and CVD disease after controlling for metabolic mediators (direct effect; marked path ‘c'’). Subsequently, we evaluated the multiple mediator model and the serial mediator model. The exponential regression coefficient is equal to the OR when considering the CVD as an outcome variable. The percentage of risk mediated by the metabolic mediator was calculated as17: OR (confounder adjusted) − OR (confounder and mediator adjusted)/OR (confounder adjusted) − 1×100. All statistical analyses were conducted under a random sampling condition excluding the basic characteristics given in table 1 using SAS V.9.4 software. A two-sided P value <0.05 was considered significant.
Table 1

Basic characteristics of the study subjects

Weighted % (SE)
Sex
 Male49.92 (0.51)
 Female50.08 (0.51)
Age range25–64 years
Age (years)*43.68 (0.18)
Region
 Urban83.87 (1.52)
 Rural16.13 (1.52)
Income level (quartiles)
 Q123.46 (0.73)
 Q225.61 (0.72)
 Q325.03 (0.71)
 Q425.90 (0.97)
Current smoking
 No75.83 (0.60)
 Yes24.17 (0.60)
Disease
  Cardiovascular disease1.81 (0.16)
  Stroke0.98 (0.13)
  Ischaemic heart disease0.90 (0.10)
Metabolic factors*
 Systolic blood pressure (mm Hg)115.01 (0.21)
 Total cholesterol (mg/dL)190.98 (0.47)
 Fasting plasma glucose (mg/dL)98.58 (0.30)
 Body mass index (kg/m2)23.92 (0.05)

*Weighted mean with SE.

Basic characteristics of the study subjects *Weighted mean with SE.

Results

The basic characteristics of the study subjects are presented in table 1. Mean age was 43.7 years, and 1.81% of subjects (n=189) had CVD. In addition, 0.98% and 0.90% of subject had stroke (n=102) and ischaemic heart disease (n=97), respectively. Subjects with a higher income ate more fruits or vegetables than those with a lower income. Those who ate more fruit were more likely to be non-smokers and female than their counterparts (online supplemental tables 2 and 3). The total effect of fruit intake on CVD showed an inverse association without controlling for metabolic mediators (adjusted OR (aOR) 0.86, 95% CI 0.74 to 0.98), but the effect of vegetable intake was not significant (aOR 0.93; 95% CI 0.81 to 1.06) after controlling for sex, age, income, region (urban/rural), current smoker and survey year (data not shown). The direct effect of fruit intake on CVD was borderline significant after further considering each metabolic mediator. The effect of fruit intake on SBP (X → M) and the effect of SBP on CVD (M → Y) were significant, and subsequently the indirect effect of SBP did not include zero in the 95% CI range, unlike other metabolic mediators. The effect of fruit intake on BMI showed borderline significance, and the effect of BMI on CVD was significant, but the indirect effect of BMI was not significant. Additionally, the effect of SBP was significant even after controlling for BMI as a covariate (table 2). SBP, cholesterol and BMI were associated with CVD, but vegetable intake did not contribute to either metabolic mediator or CVD (table 3). The mediating effect of SBP on the association between fruit intake and outcome was dominant even when the outcome was restricted to those with a current illness or undergoing treatment.
Table 2

The effect of metabolic mediators (M) in the association between fruit intake (X) and cardiovascular disease (Y)

Metabolic factors (M)Fruit intake
X → M (a)M → Y (b)X → Y (c′=direct effect)Indirect effect (a*b)
βSEpβSEpβSEpβ95% CI
SBP*−0.4840.1440.0010.0130.0040.002−0.1370.0720.06−0.007−0.014−0.002
TC*−0.1560.3570.66−0.0190.003<0.0001−0.1440.0750.050.003−0.0110.017
FPG*−0.6650.217<0.010.0040.0030.20−0.1440.0740.05−0.002−0.0060.001
BMI*−0.0590.0340.080.0780.0220.001−0.1430.072<0.05−0.005−0.0120.001
SBP†−0.4200.139<0.010.0110.0050.01−0.1270.0720.08−0.005−0.011−0.0004
TC†−0.0640.3520.86−0.0190.003<0.0001−0.1260.0750.090.001−0.0120.015
FPG†−0.6140.214<0.010.0020.0030.42−0.1300.0740.08−0.002−0.0050.002

All analyses were performed separately according to each metabolic mediator.

*Adjusted for sex, age, income, region (urban/rural), current smoking and survey year.

†Adjusted for sex, age, income, region (urban/rural), current smoking, survey year and BMI.

BMI, body mass index; FPG, fasting plasma glucose; SBP, systolic blood pressure; TC, total cholesterol;.

Table 3

The effect of metabolic mediators (M) in the association between vegetable intake (X) and cardiovascular disease (Y)

Metabolic factors (M)Vegetable intake
X → M (a)M → Y (b)X → Y (c′=direct effect)Indirect effect (a*b)
βSEPβSEPβSEPβ95% CI
SBP*−0.0420.1690.800.0140.0040.002−0.1320.0860.13−0.001−0.0060.004
TC*0.2360.4200.57−0.0190.003<0.0001−0.1210.0890.18−0.005−0.0210.012
FPG*−0.0540.2560.830.0040.0030.18−0.1320.0880.14−0.0002−0.0030.002
BMI*0.0570.0400.160.0800.022<0.001−0.1450.0860.090.005−0.0020.013
SBP†−0.1140.1630.480.0120.0050.01−0.1310.0860.13−0.001−0.0060.002
TC†0.1420.4150.73−0.0190.003<0.0001−0.1220.0890.17−0.003−0.0190.014
FPG†−0.1210.2520.630.0030.0030.4−0.1320.0880.14−0.0003−0.0030.002

All analyses were performed separately according to each metabolic mediator.

*Adjusted for sex, age, income, region (urban/rural), current smoking and survey year.

†Adjusted for sex, age, income, region (urban/rural), current smoking, survey year and BMI.

BMI, body mass index; FPG, fasting plasma glucose; SBP, systolic blood pressure; TC, total cholesterol.

The effect of metabolic mediators (M) in the association between fruit intake (X) and cardiovascular disease (Y) All analyses were performed separately according to each metabolic mediator. *Adjusted for sex, age, income, region (urban/rural), current smoking and survey year. †Adjusted for sex, age, income, region (urban/rural), current smoking, survey year and BMI. BMI, body mass index; FPG, fasting plasma glucose; SBP, systolic blood pressure; TC, total cholesterol;. The effect of metabolic mediators (M) in the association between vegetable intake (X) and cardiovascular disease (Y) All analyses were performed separately according to each metabolic mediator. *Adjusted for sex, age, income, region (urban/rural), current smoking and survey year. †Adjusted for sex, age, income, region (urban/rural), current smoking, survey year and BMI. BMI, body mass index; FPG, fasting plasma glucose; SBP, systolic blood pressure; TC, total cholesterol. When the beta coefficient was expressed as OR, the OR of the effect of fruit intake on CVD was attenuated to 0.89 (95% CI 0.77 to 1.03) while simultaneously controlling for three metabolic mediators, indicating a 21.4% indirect effect for CVD (ie, (0.8555–0.8864)/(0.8555–1)*100=21.4%). SBP showed an independent indirect effect. Higher fruit intake had a beneficial effect on fasting glucose, but its effect was not associated with CVD. The direct effect of fruit intake on CVD presented an inverse association (ß=−0.121, P=0.11), but it did not reach statistical significance (figure 1). In addition, similar results were observed when adding BMI as covariate, with an OR (the effect of fruit intake on CVD) of 0.90 (95% CI 0.78 to 1.04; data not shown). The indirect effect of the four metabolic factors accounted for 30.0% of the relationship between fruit intake and CVD (ie, (0.8555–0.8989)/(0.8555–1)*100=30.0%).
Figure 1

The effect of multiple metabolic factor (Mi) mediators in the association between fruit intake (X) and CVDs (Y). Coefficients were adjusted for sex, age, income, region (urban/rural), current smoker and survey year using the bootstrapping method. aP<0.01; bP<0.001. CVD, cardiovascular disease; SBP, systolic blood pressure.

The effect of multiple metabolic factor (Mi) mediators in the association between fruit intake (X) and CVDs (Y). Coefficients were adjusted for sex, age, income, region (urban/rural), current smoker and survey year using the bootstrapping method. aP<0.01; bP<0.001. CVD, cardiovascular disease; SBP, systolic blood pressure. We analysed the serial mediator model to assess whether BMI influenced SBP (figure 2). Although the effect of fruit intake on BMI showed borderline significance, the influence of BMI on SBP and the effect of SBP on CVD reached statistical significance. Of the three possible indirect paths, the fruit intake path → SBP → CVD was the only one to show an independent association.
Figure 2

The effect of multiple serial mediators of metabolic factors (Mi) in the association between fruit intake (X) and cardiovascular diseases (Y). Coefficients were adjusted for sex, age, income, region (urban/rural), current smoker, and survey year using the bootstrapping method. aP<0.1, bP< 0.05, cP<0.01, dP< 0.001. BMI, body mass index, SBP, systolic blood pressure.

The effect of multiple serial mediators of metabolic factors (Mi) in the association between fruit intake (X) and cardiovascular diseases (Y). Coefficients were adjusted for sex, age, income, region (urban/rural), current smoker, and survey year using the bootstrapping method. aP<0.1, bP< 0.05, cP<0.01, dP< 0.001. BMI, body mass index, SBP, systolic blood pressure. Fruit intake was directly linked to subjects who suffered a stroke, but not ischaemic heart disease, regardless of which metabolic factors were controlled. In addition, the mediating effect of SBP was dominant in patients who suffered a stroke or ischaemic heart disease even after controlling for BMI (online supplemental tables 4 and 5).

Discussion

In this study, we assessed how fruit or vegetable intake is related to CVD by assessing the indirect effect of metabolic mediators. Based on the suggested causal link, SBP, total cholesterol and fasting glucose were considered metabolic mediators, and the effect of BMI was additionally assessed. Of them, the indirect effect of SBP on the relationship between fruit intake and CVD was significant even after considering BMI, but not vegetable intake. The indirect effect of the four metabolic factors accounted for 30.0% of the relationship between fruit intake and CVD. The beneficial effects of high fruit or vegetable intake on CVD and the unfavourable effects of high blood pressure, glucose and cholesterol on CVD are well known. Thus, previous studies considered metabolic factors together, and mediators were reported to attenuate the association of a direct effect.5 One large prospective study conducted in 10 regions in China indicated that higher fresh fruit intake is linked to CVD death, and its effect was attenuated by HRs from 0.63 (95% CI 0.56 to 0.72) to 0.70 (95% CI 0.61 to 0.79) after adjusting for BMI, blood pressure, glucose and waist circumference.18 Another study conducted in Shanghai, China, showed an attenuated association between fruit intake and incident coronary heart disease after controlling for a history of diabetes, hypertension or dyslipidaemia, but no association or attenuation was observed for vegetable intake.5 The Women’s Health Study reported by Liu et al19 also showed that the effect of fruits and vegetables on CVD risk became stronger after excluding subjects with a history of diabetes, hypertension and high cholesterol. It seems that these mediators largely attribute to the relationship between fruit and/or vegetable intake and CVD risk. However, biological pathways by metabolic factors between fruit and/or vegetable intake and CVD risk have not been investigated. The assessment of a mediating effect could help understand how fruit and/or vegetable intake affects CVDs. In addition, an effect of poor dietary risk by metabolic mediators on CVD was suggested by the GBD study, so that was considered to estimate the disease burden. The mediating effect of blood pressure on the association between fruit and/or vegetable intake and CVD was suggested by a prospective cohort study of patients in the first National Health and Nutrition Examination Survey.13 Blood pressure contributed 22.2% to the relationship between fruit and vegetable intake and CVD death. This was similar to the results adjusted for BMI, cholesterol and blood pressure. That study also showed that the direct effect of fruit and vegetable intake was notable in patients who suffered a stroke but not those with ischaemic heart disease. These results are in line with those of the present study. We assessed a potential role for BMI on the association between fruit intake and CVD using various models. Several reports, including the above-mentioned study, considered BMI as a potential mediator.13 18 Additionally, a causal link between BMI and CVD risk is mediated through metabolic factors. Two pooled studies of prospective cohorts assessed the effect of BMI on coronary heart disease and stroke as mediated by metabolic components. They reported that blood pressure was a more important mediator compared with cholesterol and glucose.17 20 Other pooled data from an Asian cohort also indicate that estimated mediating proportions through hypertension were 62.3%, 35.7% and 92.4% for the association between BMI and death due to CVD, coronary heart disease and stroke, respectively, but not by diabetes.21 The GBD study restricted total calories to 2000 kcal instead of considering BMI.22 In the present study, higher fruit intake was inversely associated with BMI, but it was borderline significant (β=−0.06, P=0.08), which affected the results of the fruit intake path → BMI → SBP → CVD in the serial multiple mediator model. Our study found that the mediating effect due to BMI was about 7.9%, but previous studies showed a <3.0% mediating effect by BMI on the association between fruit only or fruit and vegetable intake and CVD deaths by presenting little change in the adjusted risk value.13 18 However, it is difficult to make a direct comparison due to discrepancies in study design, study populations, the definition of disease and fruit and/or vegetable intake. Eating more vegetables was not significantly associated with either a direct or indirect effect. In Korea, vegetables in the general population are easily accessible by a side dish. Indeed, statistics from the Organisation for Economic Co-operation and Development have reported that daily vegetable consumption among adults was the highest in Korea.23 However, the manner of preparation and/or cooking can influence nutrient content.7 The favourable effects of fruit and vegetable intake can be explained by nutrients, such as dietary fibre, folate, potassium and antioxidant vitamins (ie, vitamin E, vitamin C, polyphenols, flavonoids and carotenoids) and other components. These nutrients might be involved with controlling glucose, lipid level, and blood pressure and reducing the risk of CVD along with weight control.7 However, because foods contain various nutrients, food recommendations help subjects follow a prevention strategy. In addition, healthy eating is also associated with other health behaviours, such as not smoking and regular physical activity.13 24 The present study has some limitations. First, the results were derived from a cross-sectional study design, so causal relationships could not be effectively drawn. Our study design is also open to the problem of reverse causation. If the reverse causation affects the results, the association will appear to be null or reverse direction to what is expected. However, the indirect effect by SBP was significant, and some parts of our results were consistent with previous studies.13 24 Furthermore, the results were also consistent when stroke and ischaemic heart disease were analysed separately. Because the survey was conducted through a household visit and excludes people in the hospital, subjects with diseases might be the relatively less serious cases. Measurement error in FFQ survey or self-reported disease status may influence the results. In addition, residual confounding factors such as physical activity may have influenced the association. Finally, because the number of participants with CVD was very low (1.8%), the study had inadequate statistical power that might explain some of the non-significant findings. Nevertheless, our study focused on the mediating effects of metabolic factors on CVD and assessed which metabolic factors affect CVD. Our results were produced using the bootstrapping method and did not impose the assumption of normality of the sampling distribution; thus, it was an appropriate design for multiple mediations.16 The given evidence was conceptually approached and was not statistically tested for an indirect effect. Taken together, our study suggests that diets rich in fruits may contribute to a lower CVD risk partly through lowered SBP. Further prospective studies are needed for confirmation.
  18 in total

1.  Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models.

Authors:  Kristopher J Preacher; Andrew F Hayes
Journal:  Behav Res Methods       Date:  2008-08

2.  Mediators of the effect of body mass index on coronary heart disease: decomposing direct and indirect effects.

Authors:  Yuan Lu; Kaveh Hajifathalian; Eric B Rimm; Majid Ezzati; Goodarz Danaei
Journal:  Epidemiology       Date:  2015-03       Impact factor: 4.822

3.  Reproducibility and validity of an FFQ developed for the Korea National Health and Nutrition Examination Survey (KNHANES).

Authors:  Dong Woo Kim; Sujin Song; Jung Eun Lee; Kyungwon Oh; Jeeseon Shim; Sanghui Kweon; Hee Young Paik; Hyojee Joung
Journal:  Public Health Nutr       Date:  2014-08-28       Impact factor: 4.022

Review 4.  Fruits, vegetables and coronary heart disease.

Authors:  Luc Dauchet; Philippe Amouyel; Jean Dallongeville
Journal:  Nat Rev Cardiol       Date:  2009-08-04       Impact factor: 32.419

5.  Fruit and vegetable intake and risk of cardiovascular disease in US adults: the first National Health and Nutrition Examination Survey Epidemiologic Follow-up Study.

Authors:  Lydia A Bazzano; Jiang He; Lorraine G Ogden; Catherine M Loria; Suma Vupputuri; Leann Myers; Paul K Whelton
Journal:  Am J Clin Nutr       Date:  2002-07       Impact factor: 7.045

6.  Global burden of stroke and risk factors in 188 countries, during 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.

Authors:  Valery L Feigin; Gregory A Roth; Mohsen Naghavi; Priya Parmar; Rita Krishnamurthi; Sumeet Chugh; George A Mensah; Bo Norrving; Ivy Shiue; Marie Ng; Kara Estep; Kelly Cercy; Christopher J L Murray; Mohammad H Forouzanfar
Journal:  Lancet Neurol       Date:  2016-06-09       Impact factor: 44.182

Review 7.  Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality-a systematic review and dose-response meta-analysis of prospective studies.

Authors:  Dagfinn Aune; Edward Giovannucci; Paolo Boffetta; Lars T Fadnes; NaNa Keum; Teresa Norat; Darren C Greenwood; Elio Riboli; Lars J Vatten; Serena Tonstad
Journal:  Int J Epidemiol       Date:  2017-06-01       Impact factor: 7.196

8.  Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.

Authors:  Mohammad H Forouzanfar; Lily Alexander; H Ross Anderson; Victoria F Bachman; Stan Biryukov; Michael Brauer; Richard Burnett; Daniel Casey; Matthew M Coates; Aaron Cohen; Kristen Delwiche; Kara Estep; Joseph J Frostad; K C Astha; Hmwe H Kyu; Maziar Moradi-Lakeh; Marie Ng; Erica Leigh Slepak; Bernadette A Thomas; Joseph Wagner; Gunn Marit Aasvang; Cristiana Abbafati; Ayse Abbasoglu Ozgoren; Foad Abd-Allah; Semaw F Abera; Victor Aboyans; Biju Abraham; Jerry Puthenpurakal Abraham; Ibrahim Abubakar; Niveen M E Abu-Rmeileh; Tania C Aburto; Tom Achoki; Ademola Adelekan; Koranteng Adofo; Arsène K Adou; José C Adsuar; Ashkan Afshin; Emilie E Agardh; Mazin J Al Khabouri; Faris H Al Lami; Sayed Saidul Alam; Deena Alasfoor; Mohammed I Albittar; Miguel A Alegretti; Alicia V Aleman; Zewdie A Alemu; Rafael Alfonso-Cristancho; Samia Alhabib; Raghib Ali; Mohammed K Ali; François Alla; Peter Allebeck; Peter J Allen; Ubai Alsharif; Elena Alvarez; Nelson Alvis-Guzman; Adansi A Amankwaa; Azmeraw T Amare; Emmanuel A Ameh; Omid Ameli; Heresh Amini; Walid Ammar; Benjamin O Anderson; Carl Abelardo T Antonio; Palwasha Anwari; Solveig Argeseanu Cunningham; Johan Arnlöv; Valentina S Arsic Arsenijevic; Al Artaman; Rana J Asghar; Reza Assadi; Lydia S Atkins; Charles Atkinson; Marco A Avila; Baffour Awuah; Alaa Badawi; Maria C Bahit; Talal Bakfalouni; Kalpana Balakrishnan; Shivanthi Balalla; Ravi Kumar Balu; Amitava Banerjee; Ryan M Barber; Suzanne L Barker-Collo; Simon Barquera; Lars Barregard; Lope H Barrero; Tonatiuh Barrientos-Gutierrez; Ana C Basto-Abreu; Arindam Basu; Sanjay Basu; Mohammed O Basulaiman; Carolina Batis Ruvalcaba; Justin Beardsley; Neeraj Bedi; Tolesa Bekele; Michelle L Bell; Corina Benjet; Derrick A Bennett; Habib Benzian; Eduardo Bernabé; Tariku J Beyene; Neeraj Bhala; Ashish Bhalla; Zulfiqar A Bhutta; Boris Bikbov; Aref A Bin Abdulhak; Jed D Blore; Fiona M Blyth; Megan A Bohensky; Berrak Bora Başara; Guilherme Borges; Natan M Bornstein; Dipan Bose; Soufiane Boufous; Rupert R Bourne; Michael Brainin; Alexandra Brazinova; Nicholas J Breitborde; Hermann Brenner; Adam D M Briggs; David M Broday; Peter M Brooks; Nigel G Bruce; Traolach S Brugha; Bert Brunekreef; Rachelle Buchbinder; Linh N Bui; Gene Bukhman; Andrew G Bulloch; Michael Burch; Peter G J Burney; Ismael R Campos-Nonato; Julio C Campuzano; Alejandra J Cantoral; Jack Caravanos; Rosario Cárdenas; Elisabeth Cardis; David O Carpenter; Valeria Caso; Carlos A Castañeda-Orjuela; Ruben E Castro; Ferrán Catalá-López; Fiorella Cavalleri; Alanur Çavlin; Vineet K Chadha; Jung-Chen Chang; Fiona J Charlson; Honglei Chen; Wanqing Chen; Zhengming Chen; Peggy P Chiang; Odgerel Chimed-Ochir; Rajiv Chowdhury; Costas A Christophi; Ting-Wu Chuang; Sumeet S Chugh; Massimo Cirillo; Thomas K D Claßen; Valentina Colistro; Mercedes Colomar; Samantha M Colquhoun; Alejandra G Contreras; Cyrus Cooper; Kimberly Cooperrider; Leslie T Cooper; Josef Coresh; Karen J Courville; Michael H Criqui; Lucia Cuevas-Nasu; James Damsere-Derry; Hadi Danawi; Lalit Dandona; Rakhi Dandona; Paul I Dargan; Adrian Davis; Dragos V Davitoiu; Anand Dayama; E Filipa de Castro; Vanessa De la Cruz-Góngora; Diego De Leo; Graça de Lima; Louisa Degenhardt; Borja del Pozo-Cruz; Robert P Dellavalle; Kebede Deribe; Sarah Derrett; Don C Des Jarlais; Muluken Dessalegn; Gabrielle A deVeber; Karen M Devries; Samath D Dharmaratne; Mukesh K Dherani; Daniel Dicker; Eric L Ding; Klara Dokova; E Ray Dorsey; Tim R Driscoll; Leilei Duan; Adnan M Durrani; Beth E Ebel; Richard G Ellenbogen; Yousef M Elshrek; Matthias Endres; Sergey P Ermakov; Holly E Erskine; Babak Eshrati; Alireza Esteghamati; Saman Fahimi; Emerito Jose A Faraon; Farshad Farzadfar; Derek F J Fay; Valery L Feigin; Andrea B Feigl; Seyed-Mohammad Fereshtehnejad; Alize J Ferrari; Cleusa P Ferri; Abraham D Flaxman; Thomas D Fleming; Nataliya Foigt; Kyle J Foreman; Urbano Fra Paleo; Richard C Franklin; Belinda Gabbe; Lynne Gaffikin; Emmanuela Gakidou; Amiran Gamkrelidze; Fortuné G Gankpé; Ron T Gansevoort; Francisco A García-Guerra; Evariste Gasana; Johanna M Geleijnse; Bradford D Gessner; Pete Gething; Katherine B Gibney; Richard F Gillum; Ibrahim A M Ginawi; Maurice Giroud; Giorgia Giussani; Shifalika Goenka; Ketevan Goginashvili; Hector Gomez Dantes; Philimon Gona; Teresita Gonzalez de Cosio; Dinorah González-Castell; Carolyn C Gotay; Atsushi Goto; Hebe N Gouda; Richard L Guerrant; Harish C Gugnani; Francis Guillemin; David Gunnell; Rahul Gupta; Rajeev Gupta; Reyna A Gutiérrez; Nima Hafezi-Nejad; Holly Hagan; Maria Hagstromer; Yara A Halasa; Randah R Hamadeh; Mouhanad Hammami; Graeme J Hankey; Yuantao Hao; Hilda L Harb; Tilahun Nigatu Haregu; Josep Maria Haro; Rasmus Havmoeller; Simon I Hay; Mohammad T Hedayati; Ileana B Heredia-Pi; Lucia Hernandez; Kyle R Heuton; Pouria Heydarpour; Martha Hijar; Hans W Hoek; Howard J Hoffman; John C Hornberger; H Dean Hosgood; Damian G Hoy; Mohamed Hsairi; Guoqing Hu; Howard Hu; Cheng Huang; John J Huang; Bryan J Hubbell; Laetitia Huiart; Abdullatif Husseini; Marissa L Iannarone; Kim M Iburg; Bulat T Idrisov; Nayu Ikeda; Kaire Innos; Manami Inoue; Farhad Islami; Samaya Ismayilova; Kathryn H Jacobsen; Henrica A Jansen; Deborah L Jarvis; Simerjot K Jassal; Alejandra Jauregui; Sudha Jayaraman; Panniyammakal Jeemon; Paul N Jensen; Vivekanand Jha; Fan Jiang; Guohong Jiang; Ying Jiang; Jost B Jonas; Knud Juel; Haidong Kan; Sidibe S Kany Roseline; Nadim E Karam; André Karch; Corine K Karema; Ganesan Karthikeyan; Anil Kaul; Norito Kawakami; Dhruv S Kazi; Andrew H Kemp; Andre P Kengne; Andre Keren; Yousef S Khader; Shams Eldin Ali Hassan Khalifa; Ejaz A Khan; Young-Ho Khang; Shahab Khatibzadeh; Irma Khonelidze; Christian Kieling; Daniel Kim; Sungroul Kim; Yunjin Kim; Ruth W Kimokoti; Yohannes Kinfu; Jonas M Kinge; Brett M Kissela; Miia Kivipelto; Luke D Knibbs; Ann Kristin Knudsen; Yoshihiro Kokubo; M Rifat Kose; Soewarta Kosen; Alexander Kraemer; Michael Kravchenko; Sanjay Krishnaswami; Hans Kromhout; Tiffany Ku; Barthelemy Kuate Defo; Burcu Kucuk Bicer; Ernst J Kuipers; Chanda Kulkarni; Veena S Kulkarni; G Anil Kumar; Gene F Kwan; Taavi Lai; Arjun Lakshmana Balaji; Ratilal Lalloo; Tea Lallukka; Hilton Lam; Qing Lan; Van C Lansingh; Heidi J Larson; Anders Larsson; Dennis O Laryea; Pablo M Lavados; Alicia E Lawrynowicz; Janet L Leasher; Jong-Tae Lee; James Leigh; Ricky Leung; Miriam Levi; Yichong Li; Yongmei Li; Juan Liang; Xiaofeng Liang; Stephen S Lim; M Patrice Lindsay; Steven E Lipshultz; Shiwei Liu; Yang Liu; Belinda K Lloyd; Giancarlo Logroscino; Stephanie J London; Nancy Lopez; Joannie Lortet-Tieulent; Paulo A Lotufo; Rafael Lozano; Raimundas Lunevicius; Jixiang Ma; Stefan Ma; Vasco M P Machado; Michael F MacIntyre; Carlos Magis-Rodriguez; Abbas A Mahdi; Marek Majdan; Reza Malekzadeh; Srikanth Mangalam; Christopher C Mapoma; Marape Marape; Wagner Marcenes; David J Margolis; Christopher Margono; Guy B Marks; Randall V Martin; Melvin B Marzan; Mohammad T Mashal; Felix Masiye; Amanda J Mason-Jones; Kunihiro Matsushita; Richard Matzopoulos; Bongani M Mayosi; Tasara T Mazorodze; Abigail C McKay; Martin McKee; Abigail McLain; Peter A Meaney; Catalina Medina; Man Mohan Mehndiratta; Fabiola Mejia-Rodriguez; Wubegzier Mekonnen; Yohannes A Melaku; Michele Meltzer; Ziad A Memish; Walter Mendoza; George A Mensah; Atte Meretoja; Francis Apolinary Mhimbira; Renata Micha; Ted R Miller; Edward J Mills; Awoke Misganaw; Santosh Mishra; Norlinah Mohamed Ibrahim; Karzan A Mohammad; Ali H Mokdad; Glen L Mola; Lorenzo Monasta; Julio C Montañez Hernandez; Marcella Montico; Ami R Moore; Lidia Morawska; Rintaro Mori; Joanna Moschandreas; Wilkister N Moturi; Dariush Mozaffarian; Ulrich O Mueller; Mitsuru Mukaigawara; Erin C Mullany; Kinnari S Murthy; Mohsen Naghavi; Ziad Nahas; Aliya Naheed; Kovin S Naidoo; Luigi Naldi; Devina Nand; Vinay Nangia; K M Venkat Narayan; Denis Nash; Bruce Neal; Chakib Nejjari; Sudan P Neupane; Charles R Newton; Frida N Ngalesoni; Jean de Dieu Ngirabega; Grant Nguyen; Nhung T Nguyen; Mark J Nieuwenhuijsen; Muhammad I Nisar; José R Nogueira; Joan M Nolla; Sandra Nolte; Ole F Norheim; Rosana E Norman; Bo Norrving; Luke Nyakarahuka; In-Hwan Oh; Takayoshi Ohkubo; Bolajoko O Olusanya; Saad B Omer; John Nelson Opio; Ricardo Orozco; Rodolfo S Pagcatipunan; Amanda W Pain; Jeyaraj D Pandian; Carlo Irwin A Panelo; Christina Papachristou; Eun-Kee Park; Charles D Parry; Angel J Paternina Caicedo; Scott B Patten; Vinod K Paul; Boris I Pavlin; Neil Pearce; Lilia S Pedraza; Andrea Pedroza; Ljiljana Pejin Stokic; Ayfer Pekericli; David M Pereira; Rogelio Perez-Padilla; Fernando Perez-Ruiz; Norberto Perico; Samuel A L Perry; Aslam Pervaiz; Konrad Pesudovs; Carrie B Peterson; Max Petzold; Michael R Phillips; Hwee Pin Phua; Dietrich Plass; Dan Poenaru; Guilherme V Polanczyk; Suzanne Polinder; Constance D Pond; C Arden Pope; Daniel Pope; Svetlana Popova; Farshad Pourmalek; John Powles; Dorairaj Prabhakaran; Noela M Prasad; Dima M Qato; Amado D Quezada; D Alex A Quistberg; Lionel Racapé; Anwar Rafay; Kazem Rahimi; Vafa Rahimi-Movaghar; Sajjad Ur Rahman; Murugesan Raju; Ivo Rakovac; Saleem M Rana; Mayuree Rao; Homie Razavi; K Srinath Reddy; Amany H Refaat; Jürgen Rehm; Giuseppe Remuzzi; Antonio L Ribeiro; Patricia M Riccio; Lee Richardson; Anne Riederer; Margaret Robinson; Anna Roca; Alina Rodriguez; David Rojas-Rueda; Isabelle Romieu; Luca Ronfani; Robin Room; Nobhojit Roy; George M Ruhago; Lesley Rushton; Nsanzimana Sabin; Ralph L Sacco; Sukanta Saha; Ramesh Sahathevan; Mohammad Ali Sahraian; Joshua A Salomon; Deborah Salvo; Uchechukwu K Sampson; Juan R Sanabria; Luz Maria Sanchez; Tania G Sánchez-Pimienta; Lidia Sanchez-Riera; Logan Sandar; Itamar S Santos; Amir Sapkota; Maheswar Satpathy; James E Saunders; Monika Sawhney; Mete I Saylan; Peter Scarborough; Jürgen C Schmidt; Ione J C Schneider; Ben Schöttker; David C Schwebel; James G Scott; Soraya Seedat; Sadaf G Sepanlou; Berrin Serdar; Edson E Servan-Mori; Gavin Shaddick; Saeid Shahraz; Teresa Shamah Levy; Siyi Shangguan; Jun She; Sara Sheikhbahaei; Kenji Shibuya; Hwashin H Shin; Yukito Shinohara; Rahman Shiri; Kawkab Shishani; Ivy Shiue; Inga D Sigfusdottir; Donald H Silberberg; Edgar P Simard; Shireen Sindi; Abhishek Singh; Gitanjali M Singh; Jasvinder A Singh; Vegard Skirbekk; Karen Sliwa; Michael Soljak; Samir Soneji; Kjetil Søreide; Sergey Soshnikov; Luciano A Sposato; Chandrashekhar T Sreeramareddy; Nicolas J C Stapelberg; Vasiliki Stathopoulou; Nadine Steckling; Dan J Stein; Murray B Stein; Natalie Stephens; Heidi Stöckl; Kurt Straif; Konstantinos Stroumpoulis; Lela Sturua; Bruno F Sunguya; Soumya Swaminathan; Mamta Swaroop; Bryan L Sykes; Karen M Tabb; Ken Takahashi; Roberto T Talongwa; Nikhil Tandon; David Tanne; Marcel Tanner; Mohammad Tavakkoli; Braden J Te Ao; Carolina M Teixeira; Martha M Téllez Rojo; Abdullah S Terkawi; José Luis Texcalac-Sangrador; Sarah V Thackway; Blake Thomson; Andrew L Thorne-Lyman; Amanda G Thrift; George D Thurston; Taavi Tillmann; Myriam Tobollik; Marcello Tonelli; Fotis Topouzis; Jeffrey A Towbin; Hideaki Toyoshima; Jefferson Traebert; Bach X Tran; Leonardo Trasande; Matias Trillini; Ulises Trujillo; Zacharie Tsala Dimbuene; Miltiadis Tsilimbaris; Emin Murat Tuzcu; Uche S Uchendu; Kingsley N Ukwaja; Selen B Uzun; Steven van de Vijver; Rita Van Dingenen; Coen H van Gool; Jim van Os; Yuri Y Varakin; Tommi J Vasankari; Ana Maria N Vasconcelos; Monica S Vavilala; Lennert J Veerman; Gustavo Velasquez-Melendez; N Venketasubramanian; Lakshmi Vijayakumar; Salvador Villalpando; Francesco S Violante; Vasiliy Victorovich Vlassov; Stein Emil Vollset; Gregory R Wagner; Stephen G Waller; Mitchell T Wallin; Xia Wan; Haidong Wang; JianLi Wang; Linhong Wang; Wenzhi Wang; Yanping Wang; Tati S Warouw; Charlotte H Watts; Scott Weichenthal; Elisabete Weiderpass; Robert G Weintraub; Andrea Werdecker; K Ryan Wessells; Ronny Westerman; Harvey A Whiteford; James D Wilkinson; Hywel C Williams; Thomas N Williams; Solomon M Woldeyohannes; Charles D A Wolfe; John Q Wong; Anthony D Woolf; Jonathan L Wright; Brittany Wurtz; Gelin Xu; Lijing L Yan; Gonghuan Yang; Yuichiro Yano; Pengpeng Ye; Muluken Yenesew; Gökalp K Yentür; Paul Yip; Naohiro Yonemoto; Seok-Jun Yoon; Mustafa Z Younis; Zourkaleini Younoussi; Chuanhua Yu; Maysaa E Zaki; Yong Zhao; Yingfeng Zheng; Maigeng Zhou; Jun Zhu; Shankuan Zhu; Xiaonong Zou; Joseph R Zunt; Alan D Lopez; Theo Vos; Christopher J Murray
Journal:  Lancet       Date:  2015-09-11       Impact factor: 79.321

Review 9.  Association between body mass index and cardiovascular disease mortality in east Asians and south Asians: pooled analysis of prospective data from the Asia Cohort Consortium.

Authors:  Yu Chen; Wade K Copeland; Rajesh Vedanthan; Eric Grant; Jung Eun Lee; Dongfeng Gu; Prakash C Gupta; Kunnambath Ramadas; Manami Inoue; Shoichiro Tsugane; Akiko Tamakoshi; Yu-Tang Gao; Jian-Min Yuan; Xiao-Ou Shu; Kotaro Ozasa; Ichiro Tsuji; Masako Kakizaki; Hideo Tanaka; Yoshikazu Nishino; Chien-Jen Chen; Renwei Wang; Keun-Young Yoo; Yoon-Ok Ahn; Habibul Ahsan; Wen-Harn Pan; Chung-Shiuan Chen; Mangesh S Pednekar; Catherine Sauvaget; Shizuka Sasazuki; Gong Yang; Woon-Puay Koh; Yong-Bing Xiang; Waka Ohishi; Takashi Watanabe; Yumi Sugawara; Keitaro Matsuo; San-Lin You; Sue K Park; Dong-Hyun Kim; Faruque Parvez; Shao-Yuan Chuang; Wenzhen Ge; Betsy Rolland; Dale McLerran; Rashmi Sinha; Mark Thornquist; Daehee Kang; Ziding Feng; Paolo Boffetta; Wei Zheng; Jiang He; John D Potter
Journal:  BMJ       Date:  2013-10-01

10.  Data resource profile: the Korea National Health and Nutrition Examination Survey (KNHANES).

Authors:  Sanghui Kweon; Yuna Kim; Myoung-jin Jang; Yoonjung Kim; Kirang Kim; Sunhye Choi; Chaemin Chun; Young-Ho Khang; Kyungwon Oh
Journal:  Int J Epidemiol       Date:  2014-02       Impact factor: 7.196

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  2 in total

Review 1.  Antioxidant Food Components for the Prevention and Treatment of Cardiovascular Diseases: Effects, Mechanisms, and Clinical Studies.

Authors:  Dan-Dan Zhou; Min Luo; Ao Shang; Qian-Qian Mao; Bang-Yan Li; Ren-You Gan; Hua-Bin Li
Journal:  Oxid Med Cell Longev       Date:  2021-01-28       Impact factor: 6.543

2.  Development, validation and utilisation of dish-based dietary assessment tools: a scoping review.

Authors:  Nana Shinozaki; Xiaoyi Yuan; Kentaro Murakami; Satoshi Sasaki
Journal:  Public Health Nutr       Date:  2020-08-06       Impact factor: 4.022

  2 in total

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