Dietary intake of antioxidant vitamins and mortality: a ...between dietary carotene, vitamin C, and...

Chronic Diseases Prevention Review 11 (2019) 20-32

Copyright@2019 by Chronic Diseases Prevention Review 20

Available at http:// www.cancercellresearch.org ISSN 2158-0820

Dietary intake of antioxidant vitamins and mortality: a meta-

analysis from large cohort studies

Yanyan Kang, Chongxiu Sun, Tianlin Gao* School of Public Health, Qingdao University, 266021, China

Abstract: The aim of the study was to assess the relationships between dietary intakes of antioxidant vitamins C, E and Vitamin A active substances (carotenes) with mortality in large cohort studies. Relevant English-language studies were identified though Medline, EMBASE, and web of science database till February 2018. Multivariate-adjusted risk ratios (RRs) for mortality in the highest verses the bottom category of baseline intake of antioxidant vitamins C, E and Vitamin A active substances (carotenes) were pooled using a fixed-effects meta-analysis and reported as relative risk (RR) with 95% confidence intervals (CIs). Meta-regression was used to assess the effect of covariates across the trials. Over the follow-up ranging from 3 to 32 years, 51,277 mortality events occurred among 419,837 adults from 14 cohort studies. Pooled relative risks comparing extreme carotene categories (high versus low) were 0.85 (95%CI, 0.80-0.91; P<0.001; I2=45.2%; Pheterogeneity=0.044) for total mortality, 0.83 (95% CI, 0.78-0.91; P<0.001; I2=23.5%; Pheterogeneity=0.258) in Eerope. Pooled relative risks comparing extreme vitamin C categories (high versus low) were 0.88 (95% CI, 0.81-0.95; P<0.001), with significant heterogeneity detected among studies (I2=87.5%; Pheterogeneity =0.0001).Vitamin E intake have no beneficial health effects 0.94 (95% CI, 0.80-1.00; P<0.001; I2=45.4%; Pheterogeneity=0.050). The present finding suggests that increased intake of vitamin C and carotene in diet may benefit prevention of death, but we do not find the evidence for higher intake of vitamin E was associated with the risk of death.

Keywords: Dietary; Antioxidant Vitamins; Mortality; Cohort Studies

Received 12 March 2019, Revised 26 May 2019, Accepted 28 May 2019

*Corresponding Author: Tianlin Gao, [email protected]

1. Introduction

There has been considerable interest in the role of

antioxidant vitamins in relation to risk of mortality.

Previous studies have showed an inverse association

of vegetable and fruit intakes and risk of all-cause

mortality[1,2]. However, whether this protective

effect is caused by antioxidant vitamins remains

unclear[3]. A series of studies have been conducted

in Western populations with good nutritional status,

which showed conflict results[4-9]. Based on the

evidence from epidemiologic research over the past

several decades, the effectiveness of antioxidant

vitamin intake on mortality should depend on

individual nutritional status[10]. However, few

studies have specifically examined the relation.

between dietary carotene, vitamin C, and vitamin E

and risk of all-cause mortality in population. We

aimed to access the relationship between dietary

carotene, vitamin C, and vitamin E intake and risk of

all cause mortality using data in large cohort studies.

2. Methods

2.1. Search Strategy

Our study followed the Meta-Analysis of

Observational Studies in Epidemiology

guidelines[11]. A literature search was performed in

Medline, EMBASE, and web of science for articles

published through February 15, 2018. We combined

search terms on exposure (antioxidant vitamins and

dietary intake and specific vitamins such as carotene,

vitamin C, and vitamin E) and outcomes (mortality

and cause of death) and (cohort studies or followed

studies) without language restriction. Details of the

search strategies are shown in the online-only Data

Supplement. Reference lists of retrieved articles were

scanned manually for additional studies.

2.2. Eligibility

Candidate articles were included if they met all of

the following criteria: They applied a prospective

cohort design; the exposure included intakes of WG

ingredients (with specified methods for calculation)

or WG foods (with specified food items); and the

outcome included mortality from all causes, CVD, or

cancer. For multiple sets of results published from

the same study population, we used results based on

the longest duration of follow-up.

2.3. Search and Data Extraction

Two authors (Yanyan Kang and Chongxiu Sun)

independently screened titles and abstracts of the

articles retrieved in the initial search, evaluated the

eligibility of the articles on the basis of a full text

review, and extracted data. Differences of opinions

were resolved by discussion among authors in order

to reach consensus. The following data were

extracted from each study: first author’s last name;

study location; year of publication; study period;

follow-up duration; number of participants; age;

amounts of food intake; methods of diet assessment;

number of deaths from all causes mortality; methods

of death confirmation; relative risks (RRs; measured

by hazard ratios in all individual studies) and



confidence intervals (CIs) for carotene, vitamin C

and vitamin E ; and covariates adjusted in

multivariable analysis. For studies reporting dietary

vitamins ingredient intake[12-16].

2.4. Statistical Analysis

Meta-analysis was based on risk estimates from

models with the most complete adjustment of

potential confounders but not components of

antioxidant vitamins such as dietary carotene,

vitamin C, and vitamin E. RRs comparing the highest

and lowest intake groups were summarized with a

random-effects model[17]. Statistical heterogeneity

was assessed with the Cochran Q test (P<0.10) and

statistic[18]. Analysis was stratified by study location

(United States, Europe, and other regions), genders.

In light of the limited number of included studies, we

performed univariate meta regressions to explore

whether these factors are potential sources of

heterogeneity. Publication bias was assessed by

funnel plot and the Egger linear regression test[19].

3. Results

Of the 3,217 records retrieved in the initial search,

1,180 were excluded after title and abstract screening,

and 1,046 were excluded after full-text search. We

further excluded 18 non-mortality reports based on

the same population, 24 reports that vitamins

supplementation was associated with existing

mortality, and 4 reports were not cohort studies

(Figure 1). 14 unique sets of results were included in

the meta-analysis, which included 419,837

participants, 51,277 total deaths (n=14). 10 studies

reported findings for vitamin C and mortality, 5

studies were conducted in US populations, 4 studies

were conducted in Europe populations, with the

remaining studies in China (n=1). 8 studies reported

findings for vitamin E and mortality. 10 studies

reported findings for carotene and mortality, with

total carotene (n=3) and β-carotene (n=4). Median

follow-up durations ranged from 3 to 32 years, and

study periods were between 1971 and 2012. Foods

accounting for dietary antioxidant vitamins intake

ranged from a single item in FFQs to a

comprehensive list of grain-based foods available

from 24-hour dietary recall (Table 1). The

association between dietary antioxidant vitamins

intake and mortality was the primary study aim of 14

investigations. Most studies applied FFQs to assess

dietary exposure (2 used FFQs and 3-days -24-hour

dietary recall, 7used baseline FFQs, 4 used 24-hour

dietary recall, and 1 used a diet history

questionnaire). Newcastle-Ottawa Scale scores

ranged from 7 to 9, with 10 studies scoring 8.

Figure 1. Flow diagram of study screening.



Figure 2. Dietary carotenes intake and mortality for the highest vs. lowest. all cause mortality(A),gender(B) and region(C)

in cohort studies. Cohort studies concerning dietary is referred to by first author, year of publication and number of

subjects, weighted and ranked according to the inverse of the variance of the logRR estimate. The relative risks (RRs)

are represented by the squares (the size is proportional to the weights used in the meta-analysis), and CIs are represented

by the error bars. P values for heterogeneity test (I square and Q test) and RR for the highest exposure quantile vs. lowest

from individual study were pooled by using random effect model.

NOTE: Weights are from random effects analysis

Overall (I-squared = 45.2%, p = 0.044)

Todd (1999)

Mursu (2011)

Study

Urszula Stepaniak (2016)

Roswall (2012)

ID

ZHAO (2016)

Todd (1999)

Pandey (1995)

ZHAO (2016)

Agudo (2007)


Agudo (2007)

Genkinger (2004)

0.85 (0.80, 0.91)

0.87 (0.61, 1.24)

1.10 (0.93, 1.30)

0.86 (0.68, 1.08)

0.79 (0.73, 0.86)

ES (95% CI)

0.87 (0.80, 0.95)

1.07 (0.63, 1.82)

0.76 (0.62, 0.93)

0.83 (0.75, 0.91)

0.75 (0.59, 0.96)

0.99 (0.83, 1.18)

0.74 (0.58, 0.95)

0.81 (0.66, 1.00)

100.00

2.97

8.97

%

5.82

16.40

Weight

15.98

1.41

7.28

14.99

5.39

8.71

5.28

6.79

0.85 (0.80, 0.91)

0.87 (0.61, 1.24)

1.10 (0.93, 1.30)

0.86 (0.68, 1.08)

0.79 (0.73, 0.86)

ES (95% CI)

0.87 (0.80, 0.95)

1.07 (0.63, 1.82)

0.76 (0.62, 0.93)

0.83 (0.75, 0.91)

0.75 (0.59, 0.96)

0.99 (0.83, 1.18)

0.74 (0.58, 0.95)

0.81 (0.66, 1.00)

100.00

2.97

8.97

%

5.82

16.40

Weight

15.98

1.41

7.28

14.99

5.39

8.71

5.28

6.79

1.55 1 1.82


.

.

.


Subtotal (I-squared = 82.8%, p = 0.000)

Paganini-Hill (2015)

Pandey (1995)

Paganini-Hill (2015)

ALL

Study

Sahyoun (1996)

Mursu (2011)

Todd (1999)

male

ZHAO (2016)

ZHAO (2016)

female



Todd (1999)



Agudo (2007)

Roswall (2012)

Genkinger (2004)

ID

0.88 (0.81, 0.95)

0.86 (0.73, 1.01)

1.05 (0.98, 1.13)

0.68 (0.51, 0.91)

0.92 (0.87, 0.97)

0.55 (0.34, 0.88)

1.01 (0.97, 1.05)

0.68 (0.47, 0.99)

0.83 (0.75, 0.91)

0.83 (0.76, 0.90)

0.83 (0.68, 1.01)

0.92 (0.78, 1.09)

0.88 (0.47, 1.64)

0.92 (0.84, 1.01)

0.91 (0.71, 1.16)

0.74 (0.70, 0.79)

0.97 (0.89, 1.06)

0.95 (0.77, 1.17)

ES (95% CI)

100.00

34.27

10.02

4.34

10.42

%

2.21

10.61

3.20

9.38

9.72

28.24

7.33

1.41

37.49

5.32

10.22

9.62

6.19

Weight

0.88 (0.81, 0.95)

0.86 (0.73, 1.01)

1.05 (0.98, 1.13)

0.68 (0.51, 0.91)

0.92 (0.87, 0.97)

0.55 (0.34, 0.88)

1.01 (0.97, 1.05)

0.68 (0.47, 0.99)

0.83 (0.75, 0.91)

0.83 (0.76, 0.90)

0.83 (0.68, 1.01)

0.92 (0.78, 1.09)

0.88 (0.47, 1.64)

0.92 (0.84, 1.01)

0.91 (0.71, 1.16)

0.74 (0.70, 0.79)

0.97 (0.89, 1.06)

0.95 (0.77, 1.17)

ES (95% CI)

100.00

34.27

10.02

4.34

10.42

%

2.21

10.61

3.20

9.38

9.72

28.24

7.33

1.41

37.49

5.32

10.22

9.62

6.19

Weight

1.342 1 2.93


.

.

.






ZHAO (2016)

Mursu (2011)

Todd (1999)

Todd (1999)

Pandey (1995)

Agudo (2007)


Agudo (2007)

ID

male

Genkinger (2004)

Study

female

ALL

Roswall (2012)

ZHAO (2016)

0.85 (0.80, 0.91)

0.86 (0.68, 1.08)

0.94 (0.82, 1.09)

0.78 (0.73, 0.84)

0.86 (0.77, 0.95)

0.87 (0.80, 0.95)

1.10 (0.93, 1.30)

1.07 (0.63, 1.82)

0.87 (0.61, 1.24)

0.76 (0.62, 0.93)

0.75 (0.59, 0.96)

0.99 (0.83, 1.18)

0.74 (0.58, 0.95)

ES (95% CI)

0.81 (0.66, 1.00)

0.79 (0.73, 0.86)

0.83 (0.75, 0.91)

100.00

5.82

32.18

33.87

33.96

15.98

8.97

1.41

2.97

7.28

5.39

8.71

5.28

Weight

6.79

%

16.40

14.99

0.85 (0.80, 0.91)

0.86 (0.68, 1.08)

0.94 (0.82, 1.09)

0.78 (0.73, 0.84)

0.86 (0.77, 0.95)

0.87 (0.80, 0.95)

1.10 (0.93, 1.30)

1.07 (0.63, 1.82)

0.87 (0.61, 1.24)

0.76 (0.62, 0.93)

0.75 (0.59, 0.96)

0.99 (0.83, 1.18)

0.74 (0.58, 0.95)

ES (95% CI)

0.81 (0.66, 1.00)

0.79 (0.73, 0.86)

0.83 (0.75, 0.91)

100.00

5.82

32.18

33.87

33.96

15.98

8.97

1.41

2.97

7.28

5.39

8.71

5.28

Weight

6.79

%

16.40

14.99

类胡萝卜素与死亡亚组分析——性别

1.55 1 1.82

C

B

A



Figure 3. dietary vitamin C intake and mortality for the highest vs. lowest. All cause mortality(A)and region(B) in cohort

studies. Cohort studies concerning dietary is referred to by first author, year of publication and number of subjects,

weighted and ranked according to the inverse of the variance of the logRR estimate. The relative risks (RRs) are

represented by the squares (the size is proportional to the weights used in the meta-analysis), and CIs are represented by

the error bars. P values for heterogeneity test (I square and Q test) and RR for the highest exposure quantile vs. lowest

from individual study were pooled by using random effect model.

A A A A

B



Figure 4. dietary vitamin C intake and mortality for the highest vs. lowest. All cause mortality(A),gender(B) and

region(C) in cohort studies. Cohort studies concerning dietary is referred to by first author, year of publication and

number of subjects, weighted and ranked according to the inverse of the variance of the logRR estimate. The relative

risks (RRs) are represented by the squares (the size is proportional to the weights used in the meta-analysis), and CIs are

represented by the error bars. P values for heterogeneity test (I square and Q test) and RR for the highest exposure

quantile vs. lowest from individual study were pooled by using random effect model.



Roswall (2012)


Todd (1999)

Todd (1999)

ID


ZHAO (2016)

Stampfer (1993)

Study

Mursu (2011)

Agudo (2007)

ZHAO (2016)

Genkinger (2004)

0.94 (0.89, 1.00)

0.85 (0.77, 0.93)

0.85 (0.67, 1.08)

0.91 (0.63, 1.31)

1.26 (0.71, 2.24)

ES (95% CI)

1.08 (0.92, 1.27)

0.91 (0.84, 0.99)

0.95 (0.73, 1.24)

1.01 (0.97, 1.06)

0.83 (0.64, 1.08)

0.95 (0.86, 1.05)

0.98 (0.80, 1.20)

100.00

15.42

4.66

2.21

0.94

Weight

8.45

17.01

3.85

%

22.67

4.00

14.55

6.25

0.94 (0.89, 1.00)

0.85 (0.77, 0.93)

0.85 (0.67, 1.08)

0.91 (0.63, 1.31)

1.26 (0.71, 2.24)

ES (95% CI)

1.08 (0.92, 1.27)

0.91 (0.84, 0.99)

0.95 (0.73, 1.24)

1.01 (0.97, 1.06)

0.83 (0.64, 1.08)

0.95 (0.86, 1.05)

0.98 (0.80, 1.20)

100.00

15.42

4.66

2.21

0.94

Weight

8.45

17.01

3.85

%

22.67

4.00

14.55

6.25

vitamin E and motality

1.446 1 2.24


.

.

.




Agudo (2007)

Todd (1999)

female



ZHAO (2016)

Genkinger (2004)

ID

Study

Mursu (2011)

ALL

ZHAO (2016)

Roswall (2012)


Stampfer (1993)

Todd (1999)

male

0.94 (0.89, 1.00)

0.85 (0.67, 1.08)

0.98 (0.90, 1.06)

0.83 (0.64, 1.08)

0.91 (0.63, 1.31)

1.08 (0.92, 1.27)

0.96 (0.89, 1.04)

0.91 (0.84, 0.99)

0.98 (0.80, 1.20)

ES (95% CI)

1.01 (0.97, 1.06)

0.95 (0.86, 1.05)

0.85 (0.77, 0.93)

0.87 (0.80, 0.94)

0.95 (0.73, 1.24)

1.26 (0.71, 2.24)

100.00

4.66

25.20

4.00

2.21

8.45

49.13

17.01

6.25

Weight

%

22.67

14.55

15.42

25.67

3.85

0.94

0.94 (0.89, 1.00)

0.85 (0.67, 1.08)

0.98 (0.90, 1.06)

0.83 (0.64, 1.08)

0.91 (0.63, 1.31)

1.08 (0.92, 1.27)

0.96 (0.89, 1.04)

0.91 (0.84, 0.99)

0.98 (0.80, 1.20)

ES (95% CI)

1.01 (0.97, 1.06)

0.95 (0.86, 1.05)

0.85 (0.77, 0.93)

0.87 (0.80, 0.94)

0.95 (0.73, 1.24)

1.26 (0.71, 2.24)

100.00

4.66

25.20

4.00

2.21

8.45

49.13

17.01

6.25

Weight

%

22.67

14.55

15.42

25.67

3.85

0.94

1.446 1 2.24


.

.

.


ZHAO (2016)

Roswall (2012)


Genkinger (2004)


Mursu (2011)

Todd (1999)

Asia

America

Stampfer (1993)


ZHAO (2016)

ID

Todd (1999)


erope


Agudo (2007)

Study

0.94 (0.89, 1.00)

0.91 (0.84, 0.99)

0.85 (0.77, 0.93)

0.93 (0.87, 0.99)

0.98 (0.80, 1.20)

1.01 (0.96, 1.05)

1.01 (0.97, 1.06)

0.91 (0.63, 1.31)

0.95 (0.73, 1.24)

1.08 (0.92, 1.27)

0.95 (0.86, 1.05)

ES (95% CI)

1.26 (0.71, 2.24)

0.85 (0.67, 1.08)

0.92 (0.82, 1.03)

0.83 (0.64, 1.08)

100.00

17.01

15.42

31.56

6.25

32.77

22.67

2.21

3.85

8.45

14.55

Weight

0.94

4.66

35.68

4.00

%

0.94 (0.89, 1.00)

0.91 (0.84, 0.99)

0.85 (0.77, 0.93)

0.93 (0.87, 0.99)

0.98 (0.80, 1.20)

1.01 (0.96, 1.05)

1.01 (0.97, 1.06)

0.91 (0.63, 1.31)

0.95 (0.73, 1.24)

1.08 (0.92, 1.27)

0.95 (0.86, 1.05)

ES (95% CI)

1.26 (0.71, 2.24)

0.85 (0.67, 1.08)

0.92 (0.82, 1.03)

0.83 (0.64, 1.08)

100.00

17.01

15.42

31.56

6.25

32.77

22.67

2.21

3.85

8.45

14.55

Weight

0.94

4.66

35.68

4.00

%

1.446 1 2.24

C

B

A



Figure 2(A) shows forest plots on mortality,

comparing the highest and lowest groups of carotene.

The pooled RR for total mortality was 0.85 (95% CI,

0.80-0.91; P<0.001), with significant heterogeneity

detected among studies (I2=45.2%;

Pheterogeneity=0.044). Figure 2(B) shows forest plots on

mortality, comparing the highest and lowest groups

of carotene in different regions. The pooled RR for

total mortality in US was 0.88 (95% CI, 0.70-1.12; P

＜ 0.001), with significant heterogeneity detected

among studies (I2=78.5%; Pheterogeneity=0.009). Figure

2(C) shows forest plots on mortality, comparing the

highest and lowest groups of carotene in male and

female. The pooled RR for total mortality in female

was 0.94 (95% CI, 0.81-1.19; P<0.001), with

significant heterogeneity detected among studies

(I2=54.3%; Pheterogeneity =0.087). Results of stratified

analysis are shown with significantly lower RRs

observed in most subgroups. Funnel plots for

publication bias are shown in Figure I. The Egger

test did not suggest publication bias for total

mortality.


comparing the highest and lowest groups of vitamin

C. The pooled RR for total mortality was 0.88 (95%

CI, 0.81-0.95; P<0.001), with significant

heterogeneity detected among studies (I2=87.5%;

Pheterogeneity=0.0001). Figure 2(B) shows forest plots

on mortality, comparing the highest and lowest

groups of carotene in different regions. The pooled

RR for total mortality in US was 0.95 (95% CI, 0.87-

1.03; P ＜ 0.001), with significant heterogeneity


Pheterogeneity=0.0001). The pooled RR for total

mortality in Europe was 0.85 (95% CI, 0.83-0.99; P

＜ 0.001), with significant heterogeneity detected

among studies (I2=82.3%; Pheterogeneity=0.0001).


comparing the highest and lowest groups of carotene.

The pooled RR for total mortality was 0.94 (95% CI,

0.80-1.00; P<0.001), with significant heterogeneity


Pheterogeneity=0.050). Figure 2(B) shows forest plots on


of carotene in different genders. The pooled RR for

total mortality female was 0.98 (95% CI, 0.89-1.04;

P＜0.001), with significant heterogeneity detected

among studies (I2=42.8%; Pheterogeneity=0.138). The

pooled RR for total mortality in male was 0.94 (95%

CI, 0.90-1.08; P ＜ 0.001), with significant

heterogeneity detected among studies (I2=0%;

Pheterogeneity=0.382). Figure 2(C) shows forest plots on


of carotene in different genders. The pooled RR for

total mortality in Europe was 0.92 (95% CI, 0.82-

1.03; P＜ 0.001), with significant heterogeneity


Pheterogeneity=0.143). The pooled RR for total mortality

in the US was 1.01 (95% CI, 0.98-1.05; P＜0.001),

with significant heterogeneity detected among

studies (I2=0%; Pheterogeneity=0.873).

4. Discussion

The analysis of carotene and the relationship for

all-cause mortality found that dietary intake of

carotenoids can reduce all-cause mortality, Similar

association patterns were observed in subgroup and

sensitivity analyses, there may be related to regional

differences and gender differences, in Europe the

study found that dietary intake of high carotene can

reduce all-cause death, but there was no relationship

in the US; intake higher carotene can reduce the all-

cause mortality of female, but no effect for male.

Dietary vitamin C can reduce all-cause mortality. In

female, dietary vitamin C has a protective effect on

death, while dietary vitamin C in men and mixed

gender groups has no effect on death. In Europe,

dietary vitamin C was associated with a protective

effect against death, while dietary vitamin C was not

associated with death in the US. Dietary vitamin E

was not associated with all-cause death. The ability

of antioxidant vitamins, such as carotene and vitamin

C, to prevent oxidative damage is thought to be

involved in the pathological process of many chronic

diseases. In previous studies, the lack of association

between vitamin intake and mortality may be due to

the study of well-nourished cohort members[17-34].

For poorly nourished populations, previous studies

have suggested beneficial effects of antioxidant

vitamins in relation to mortality[31]. We found a

non-linear relationship of total carotene and vitamin

C intake with mortality in men. Antioxidant vitamins

in the human body may need to be maintained within

a narrow concentration range for normal

physiological functioning[35].

some large, prospective cohort studies have found

significantly lower mortality with vitamin intake,

supplemental A, C, or E in women, dietary C, dietary

A or β-carotene, and total C. 17-19, 23 those studies

have not found the relationship between dietary

antioxidants and mortality.19,24-27 Many of these

studies, which were carried out in diverse

populations (United States, Europe, Sweden,

Japan)[17-30], in both younger and older adults, and

in both men and women, included adjustment for

various potential confounders. Generally such

adjustment attenuated the risks of all-cause mortality

observed with only age and sex adjustment. Some

studies suggest that confounders or chance might

account for the positive associations between vitamin

intake and mortality observed in some previous

prospective studies[33]. But a meta-analysis of all

large cohorts of dietary antioxidant vitamins and all-

cause mortality could explain the observed

phenomenon. Increased dietary intake of vitamin C

and carotene can reduce all-cause mortality, which

may vary regionally. Studies in the United States

have shown that dietary antioxidant vitamin intake is



not associated with all-cause mortality. Dietary

vitamin E intake may not be associated with all-

cause death.

The inverse association between vitamin C and

mortality was in accordance with a previous study in

Japan[35]. For dietary carotene, three prospective

studies found that carotene was associated with all

cause mortality, with a reduction of ten to thirty

percent[12, 22, 28]. A prospective study observed

dietary vitamin C or carotene intake may confound

the mortality-vitamin E association[33]. Of all the

studies exploring the associations of dietary

antioxidant vitamins with risk of mortality, only one

study was conducted in Asia[35-38]. Some studies

conducted in the US or Europe contended that the

lack of association between vitamin intake and

mortality was due to the population was well-fed[8,

27]. Additional vitamin E intake may have no

beneficial health effects.

Strengths of the present study include a large

number of participants in original studies and careful

hierarchical analysis. According to sensitivity

analyses, findings were independent of differences in

antioxidant vitamins assessment methods.

Meanwhile, our study has some limitations. First, in

this study, the dose relationship between dietary

intake of antioxidant vitamins and all-cause death

was insufficient. If the relationship between different

causes of death and antioxidant vitamins could be

stratified, there would be stronger evidence to prove

the relationship between dietary vitamins and death.

Therefore, results must be interpreted with caution.

Additionally, we cannot exclude we did dietary

supplements and their intake and death, so we can

only explain the relationship between low-dose

antioxidant vitamins and all-cause death.

5. Conclusion

The present finding suggests that increased intake

of vitamin C and carotenes in diet may benefit

prevention of death, but we do not find the evidence

for higher intake of vitamin E was associated with

the risk of death.

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Table 1. Characteristics of Studies Included in the Meta-Analysis

Sample

Age in years

Design Duration

period(year

s)

Dietary assessment Case of death

number

Exposure Outcomes

(RRs,95% CI)

Covariates

Measurement Range(H vs. L)a

Enstron

1992,USA20

NHANES Ia

11,348 adults age 15

to 74

Prospective

Study

10(1972-

1984)

24-Hour dietary

recall and FFQ

ACM:1,809

Males:1069

Females:740

Vitamin C(mg/d) 129

vs. U.S.White

Males:0.93(.084,1.02)

Females:0.93(.083,1.03)

Both sexes:0.93(.087,1.00)

Age and sex.

Stampfer

1993,USA21

87,245 femal

nurses,34 to 59

Prospective

Study

8(1980-

1988)

FFQ CVD:552 Vitamin

E(IU/day)

2.6 vs. 7.7 0.95(0.72,1.23) Age and smoking.

Pandey

1995,USA22

The Western

Electric Study

1,556 middle aged

men, 40 to 55

Prospective

Study

24(1959-

1983)

28-day diet

histories

552

Vitamin C(mg/d) Increment 100mg/d

intake of Vitamin C

0.71(0.46,1.09)

Age,systolic blood pressure, body mass

index, serum cholesterol, cigarette

smoking(where appropriate), family history

of cardiovascular disease, alcohol

consumption, and dietary intake of energy,

cholesterol, iron, saturated fatty acids, and

polyunsaturated fatty acids.

Beta-

cartotene(mg/d)

Increment 3mg/d intake

of Beta-cartotene

0.76(0.63,0.92)

Sahyoun

1995,USA23

747 elderly

population aged 60

to 101

Prospective

Study

9-12(1981-

1993)

3-day food record 217

Vitamin C ACM:0.55(0.34,0.88) Age, sex, serum cholesterol, disease status,

and disabilities affecting shopping. Vitamin E _ ACM:0.83(0.54,1.27

Todd 1999,UK24

Scottish Heart

Health Study,

11,629, 40 to 59

Prospective

Study

7.7(1984-

1993)

Semiquantitative

FFQ

591

Vitamin

C(mg/4.18MJ)

Males:15.6 vs. 18.9

Females:18.6 vs. 18.2

Males:0.68(0.46,1.01)

Females:0.88(0.47,1.63)

Age, serum total cholesterol, systolic btood

pressure, carbon monoxide, energy, previous

medical diagnosis of diabetes, body mass

index, the

Bortner personality score, triglycerides, high

density lipoprotein cholesterol, fibrinogen, a

self-reported measure of activity in leisure,

and alcohol consumption.

Vitamin

E(mg/4.18MJ)

Males:1.9 vs. 3.3

Females:12.3 vs. 3.7

Males:0.91(0.63,1.31)

Females:1.28(0.72,2.28)

Beta-

carotene(μg/4.18

MJ)

Males:692.8 vs. 1,933.6

Females:1978 vs.

2,704.5

males:0.87(0.61,1.23)

Females:1.07(0.63,1.82)



Khaw 2001,UK25

EPICb-Norfolk

19,496, 45 to 79

Prospective

Study

4(1993-

1997)

7-day diet diary ACM:496

Vitamin C(mg/d) Males:

51 vs.109

0.77(0.67,0.87) Age, systolic blood pressure, cholesterol,

body mass index (continuous variables);

cigarette smoking habit, diabetes mellitus,

any supplement use.

Females:

57 vs. 113

:0.85(0.73,0.99)

Genkinger

2004,USA26

Odyssey Cohort, 6,

151,30 to 93

Prospective

Study

13(1989-

2002)

FFQ ACM:910

Vitamin C(mg/d) 39.4 vs. 175.6 ACM:0.95(0.77,1.17) Age, smoking status, body mass index,

cholesterol concentration, and energy.

Vitamin E(mg/d) 5.1 vs. 12.4 ACM:0.98(0.80,1.19)

Beta-

carotene(μg/d)

679.2 vs. 3884.8 ACM:0.81(0.66,1.00)

Agudo 2007,

Spanic27

EPICb-Spain, 41,358

subjects aged 30 to

69 y.

Prospective

Study

6.6(1992-

1996)

Computerized

questionnaire

ACM:256

Vitamin C

(mg/d)

96.9 vs. 261.3 0.74 (0.58, 0.94) Age (time axis), sex, total energy intake,

education, BMI, physical activity,

cigarette smoking, and alcohol consumption.

Vitamin E(mg/d) 6.1 vs.19.1 0.83 (0.64, 1.08)

Provitamin Ac

(μg/d)

1224.9 vs. 3210.8 0.68 (0.53, 0.87)

Buijsse 2008,

Dutch 28

The Zutphen Elderly

Study, In 1985, 559

men (mean age 72

y)

Prospective

Study

15(1985-

2000)

Cross-check

dietary history

CVD:197 Total

carotenoids(μg/d

)

6372±3,201 0.90(0.77,1.06) Adjusted RR for 1-SD;

Adjusted for age, energy intake, and lifestyle

not including dietary factors.

Beta-

carotene(μg/d)

2766±1,474 0.88(0.74,1.05)

Vitamin C(mg/d) 88±38 0.91(0.78,1.07)

Vitamin E(mg/d) 12.5±11.9 0.92(0.78,1.09)



Kubota

2011,Japan29

The Japan

Collaborative

Cohort Study,

23,119 men and

35,611 women aged

40 to 79 years

Prospective

Study

16.5(1988-

2006)

FFQ

CVD:2,690

Male:1343

Female:1347

Male:

Vitamin A(μg/d)

270 vs. 1439 1.09(0.90,1.33) age, history of hypertension and diabetes,

smoking status, alcohol consumption, body

mass index, mental stress, walking, sports,

education levels, dietary intakes of total

energy, cholesterol, saturated fatty acids, n-3

fatty acids, and sodium.

Vitamin C(mg/d) 52 vs. 145 0.88(0.72,1.07)

Vitamin E(mg/d) 3.6 vs. 6.6 0.91(0.69,1.22)

Female:

Vitamin A(μg/d)

290 vs. 1,391 1.04(0.85,1.26)

Vitamin C(mg/d) 65 vs. 150 0.82(0.65,1.04)

Vitamin E(mg/d) 3.8 vs. 6.4 0.79(0.66,0.94)

Roswall 2012,

Danish30

55,453 middle-aged

Danes, aged 50 to

64y

Prospective

Study

13.8(1993-

2010)

FFQ ACM:6,767 Vitamin C(mg/d) ≤65.19 vs. ＞127.75 0.97(0.89,1.06) Total intake of the three other micronutrients

as well as dietary intake for the supplemental

intake and supplemental intake for the dietary

intake and further for alcohol intake, BMI,

waist circumference, smoking status,

smoking duration, smoking intensity, time

since

cessation, education, and physical activity.

Vitamin E(mg/d) ≤6.51vs. ＞10.60 0.85(0.78,0.94)

Beta-

carotene(μg/d)

≤1317.07vs. ＞4797.69 0.79(0.73,0.86)

Paganini-Hill

2014, U.S. 31

8,640 women and

4,983 men (median

age at entry, 74

years)

Prospective

Study

32(1981-

2013)

FFQ ACM:13,104

Male:4878

Vitamin A(IU/d) ＜8000 vs. ≥16,333 Male:1.00(0.93,1.07)

Female:0.99(0.93,1.04)

Age, smoking, body mass index, exercise,

alcohol intake, caffeine consumption, and

histories of hypertension, angina, heart

attack, stroke, diabetes, rheumatoid arthritis,

and cancer.

Vitamin C(mg/d) ＜155 vs. ≥225 Male:1.05(0.98,1.13)

Female: 0.97(0.92,1.02)



Stepaniak 2015,32

European

The HAPIEEd study,

28,945 men and

women aged 45-69

years

Prospective

Study

6.5-

8.1(2002-

2011)

FFQ ACM:2,371;

male:1590

Cancer:830;

male:527

CVD:997;

male:684

Vitamin C(mg/d) Male:51.1 vs. 231.3 ACM:0.92(0.78,1.09) age, country, education, smoking status,

alcohol intake, BMI, hypertension, diabetes,

hypercholesterolemia, history of CVD or

cancer, total energy intake.

Female:59.3 vs. 308.2 ACM:0.91(0.71,1.16)

Vitamin E(mg/d) Male:5.9 vs. 12.2 ACM:1.08(0.92,1.27)

Female:6.6 vs. 14.1 ACM:0.85(0.67,1.08)

Beta-

carotene(μg/d)

Male:2897.2 vs.

12,730.7

ACM:0.99(0.83,1.17)

Female:3446.9 vs.

15,033.9

ACM:0.86(0.68,1.08)

Zhao 2016,

China(Male)33

59,739 (mean

age:64)

Prospective

Study

8.3(2002-

2012)

FFQ and 24-h

dietary recalls

ACM:4170

Cancer:1789

CVD:1379

Vitamin C(mg/d) 44.55 vs. 151.69 ACM:0.83(0.75,0.91) Age, energy, birth cohort, education, income,

occupation

, smoking status, alcohol intake, body mass

index, waist-hip ratio, physical activity,

history of hypertension, diabetes, coronary

heart disease, stroke, vitamin supplements

use,menopause status, hormone

replacement therapy.


Total

carotene(μg/d)

1392.62 vs. 5099.66 ACM:0.83(0.76,0.92)

Zhao 2016,

China(Female)33

74,619(mean age:

61)

14.2(1997-

2012)

Female:5909

Cancer:2595

CVD:1819

Vitamin C(mg/d) 42.51 vs. 142.72 ACM:0.83(0.77,0.91)


Total

carotene(μg/d)

1333.63 vs. 4602.66 ACM:0.87(0.80,0.95)

a NHANES I: the First National Health and Nutrition Examination Survey

b EPIC: European Prospective Investigate into Cancer and Nutrition

c As beta-carotene equivalents: beta-carotene +0.5 * Alpha-carotene + 0.53 * beta-cryptoxanthin.

d The HAPIEE study: The Health, Alcohol and Psychosocial factors in Eastern Europe (HAPIEE) study

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