Several papers studied dietary protein intake as a potential influence factor for esophageal cancer, but their findings were inconsistent. Thus, this meta-analysis was performed to identify the effect of protein intake on esophageal cancer risk. Potential case–control studies or cohort studies from the databases of Embase, Web of Science and PubMed were searched. The strength of association was quantified by pooling odds ratio (OR) and 95% confidence interval (CI). In total, 11 articles involving 2537 cases and 11432 participants were included in this meta-analysis. As a result, dietary protein intake had non-significant association on esophageal cancer risk overall (pooled OR = 1.11, 95% CI = 0.88–1.40). Meanwhile, we obtained consistent results in the subgroups analyses by study design, protein type, geographic locations and number of cases. Interestingly, dietary protein intake could significantly increase the risk of esophageal squamous cell carcinoma (pooled OR = 1.29, 95% CI = 1.02–1.62), instead of other disease type. To sum up, dietary protein intake had no significant association with esophageal cancer risk in the overall analysis; but, protein intake may be associated with the risk of esophageal squamous cell carcinoma. While some limitations existed in the present paper, more studies with large sample size are warranted to further confirm this result.

Esophageal cancer is considered as the eighth most common cancer worldwide [1]. It was estimated that there were 572034 new esophageal cancer cases in 2018 [2]. Meanwhile, it is a multifactorial disease, which may be affected by numerous genetic factors [3,4] or some environmental factors [5,6]. Furthermore, dietary factors [7] may affect the risk of esophageal cancer. Previous studies suggested that vitamins intake [8,9], fiber intake [10], folate intake [11,12], could decrease the development of esophageal cancer. Intakes of bioactive compounds from various plant sources also reduced the risk of cancer [13–16]. Previous meta-analyses had been published to assess the association between dietary protein intake and many cancers, such as prostate cancer [17], colorectal cancer [18], ovarian cancer [19] etc. However, no meta-analysis was conducted about protein intake and esophageal cancer risk. Up to now, many original articles were published regarding protein intake on esophageal cancer risk. The findings of these studies were inconclusive and inconsistent through review of the original articles. This may be attributed to the small sample sizes, heterogeneity or ethnic differences. To solve the inconsistency among these studies, we designed this meta-analysis to clarify the potential relationship about protein intake and esophageal cancer risk.

Literature search and inclusion criteria

Two reviewers systematically and independently searched Embase, Web of Science and PubMed to find potential studies without any restriction. The search time was from beginning to 31 July 2019. The keywords included ‘dietary’ AND ‘protein’ AND (‘esophageal cancer’ OR ‘esophageal adenocarcinoma’ OR ‘esophageal squamous cell carcinoma’). The search strategy for computerized literature search conducted in PubMed is listed in Supplementary Table S1. References of identified studies were manually screened to search any omitted articles. The inclusion criteria were (1) case–control studies or cohort studies; (2) having available odd ratios (ORs) and its 95% confidence intervals (CIs) or enough data for calculating them; (3) evaluation of the relationship about protein intake and esophageal cancer risk; (4) human studies. All papers were searched if they met our inclusion criteria no matter full-text available or not.

Quality assessment and data isolation

The quality assessment was using the Newcastle–Ottawa Scale (NOS) [20]. Based on the inclusion criteria, two reviewers independently extracted the data of interest, including first author, year, study type, sample sizes (cases and participants), cancer type, age, protein type, assessment of dietary protein, country of origin and ORs with their 95% CIs. If data were unavailable in an article, we contacted the authors for relevant data.

Statistical analysis

Statistical analysis was conducted by Stata 12.0 (StataCorp, College Station, U.S.A.). Pooled ORs with their 95% CIs was calculated using the independent OR and its 95% CI in each individual study [21]. Stratified analyses were also conducted. Regarding potential heterogeneity among studies, we defined significant heterogeneity at the levels P<0.10 or I2 > 50% [22]. A random-effect model was used in the pooled analysis. The effect on heterogeneity test and the stability of results were evaluated via meta-regression [23] and sensitivity analysis by eliminating one study each time. Publication bias was tested by visually inspecting the symmetry of Begg’s funnel plot [24] and assessing Egger’s test [25]. Statistical significance was set at P<0.05.

Characteristics of included articles

The initial search returned 1039 articles from the above-mentioned databases. One additional record was identified from the reference of a review. Then 408 duplicated articles from different databases were excluded, and 593 articles were omitted after title and abstract examination. Of the remaining 39 articles, full texts were reviewed. Twenty-eight articles were further excluded due to the reason present in Figure 1. Finally, 11 articles [26–36] with 2537 cases and 11432 participants were included. The characteristics of each study are listed in Table 1. The detailed quality assessment of each included study was present in Supplementary Table S2.

Flow chart of meta-analysis for exclusion/inclusion of studies

Figure 1
Flow chart of meta-analysis for exclusion/inclusion of studies
Figure 1
Flow chart of meta-analysis for exclusion/inclusion of studies
Close modal
Table 1
Characteristics of the studies between dietary protein intake and the risk of esophageal cancer
Study, yearDesignAgeParticipants, casesCountryDisease typeAssessment of intakeQuality scoreCategoryOR (95% CI)Adjusted for or matched for
Chen et al., 2002 PBCC 62.3 ± 12.4 573, 124 United States Esophageal adenocarcinoma HHHQ Q4 vs. Q1 0.5 (0.3–1.0) Age, age squared, sex, respondent type, BMI, alcohol use, tobacco use, education, family history of cancers, and vitamin supplement use 
De Stefani et al., 1999 HBCC NA 459, 66 Uruguay Esophageal cancer FFQ Highest vs. Lowest 1.5 (1.1–2.2) Age, sex, residence, urban/rural status, education, BMI, tobacco smoking, total alcohol intake and total energy intake 
De Stefani et al., 2006 HBCC 40-89 1170, 234 Uruguay Esophageal squamous cell carcinoma FFQ Q4 vs. Q1 1.01 (0.61–1.67) Age, sex, residence, urban/rural status, birthplace, education, body mass index, smoking status, years since quit smoking, number of cigarettes smoked per day, alcohol drinking, mate consumption, and total energy intake 
Jessri et al., 2011 HBCC 40-75 143, 47 Iran Esophageal squamous cell carcinoma FFQ T3 vs. T1 1.93 (0.6–3.18) Age, sex, reflux, BMI, smoking, physical activity, and education 
Lagergren et al., 2013 PBCC <80 1008, 188 Sweden Esophageal adenocarcinoma FFQ Q4 vs. Q1 0.86 (0.51–1.45) Age, sex, reflux, BMI, smoking, alcohol consumption, education grade, and total energy intake 
Lagergren et al., 2013 PBCC <80 987, 167 Sweden Esophageal squamous cell carcinoma FFQ Q4 vs. Q1 1.15 (0.68–1.94) Age, sex, reflux, BMI, smoking, alcohol consumption, education grade, and total energy intake 
Mayne et al., 2001 PBCC 30-80 969, 282 United States Esophageal adenocarcinoma FFQ T3 vs. T1 1.49 (1.02–2.18) Age, site, sex, race, proxy status, BMI, income, education, smoking, and alcohol consumption 
Mayne et al., 2001 PBCC 30–80 893, 206 United States Esophageal squamous cell carcinoma FFQ T3 vs. T1 1.75 (1.07–2.88) Age, site, sex, race, proxy status, BMI, income, education, smoking, and alcohol consumption 
Tuyns et al., 1987 PBCC NA 2718, 743 France Esophageal cancer FFQ Heavy vs. Low consumers 0.51 (0.33–0.79) Age, alcohol consumption, and tobacco smoking 
Tzonou et al., 1996 HBCC NA 256, 56 Greece Esophageal adenocarcinoma FFQ Highest vs. Lowest 0.84 (0.56–1.27) Age, sex, birth place, schooling, height, analgesics, coffee drinking, alcohol intake, tobacco smoking, and energy intake 
Tzonou et al., 1996 HBCC NA 243, 43 Greece Esophageal squamous cell carcinoma FFQ Highest vs. Lowest 1.13 (0.72–1.76) Age, sex, birth place, schooling, height, analgesics, coffee drinking, alcohol intake, tobacco smoking, and energy intake 
Wolfgarten et al., 2001 PBCC 62.2 ± 1.9 140, 40 Germany Esophageal adenocarcinoma FFQ >75 vs. <50 g/day 2.3 (0.7–6.8) Age, gender, height, weight, BMI and socioeconomic data such as marital status and earning capacity 
Wolfgarten et al., 2001 PBCC 58.1 ± 1.2 145, 45 Germany Esophageal squamous cell carcinoma FFQ >75 vs. <50 g/day 1.7 (0.4–6.2) Age, gender, height, weight, BMI and socioeconomic data such as marital status and earning capacity 
Wu et al., 2007 PBCC 30–74 1514, 206 United States Esophageal adenocarcinoma FFQ Q4 vs. Q1 2.22 (1.20–3.90) Age, sex, race, birth place, education, smoking, BMI, reflux, use of vitamins, total calories, and fat 
Zhang et al. 1997 HBCC NA 214, 90 United States Esophageal adenocarcinoma HHHQ Q4 vs. Q1 0.8 (0.6–1.2) Age, sex, race, education, smoking, alcohol intake, BMI, and total dietary intake in calories 
Study, yearDesignAgeParticipants, casesCountryDisease typeAssessment of intakeQuality scoreCategoryOR (95% CI)Adjusted for or matched for
Chen et al., 2002 PBCC 62.3 ± 12.4 573, 124 United States Esophageal adenocarcinoma HHHQ Q4 vs. Q1 0.5 (0.3–1.0) Age, age squared, sex, respondent type, BMI, alcohol use, tobacco use, education, family history of cancers, and vitamin supplement use 
De Stefani et al., 1999 HBCC NA 459, 66 Uruguay Esophageal cancer FFQ Highest vs. Lowest 1.5 (1.1–2.2) Age, sex, residence, urban/rural status, education, BMI, tobacco smoking, total alcohol intake and total energy intake 
De Stefani et al., 2006 HBCC 40-89 1170, 234 Uruguay Esophageal squamous cell carcinoma FFQ Q4 vs. Q1 1.01 (0.61–1.67) Age, sex, residence, urban/rural status, birthplace, education, body mass index, smoking status, years since quit smoking, number of cigarettes smoked per day, alcohol drinking, mate consumption, and total energy intake 
Jessri et al., 2011 HBCC 40-75 143, 47 Iran Esophageal squamous cell carcinoma FFQ T3 vs. T1 1.93 (0.6–3.18) Age, sex, reflux, BMI, smoking, physical activity, and education 
Lagergren et al., 2013 PBCC <80 1008, 188 Sweden Esophageal adenocarcinoma FFQ Q4 vs. Q1 0.86 (0.51–1.45) Age, sex, reflux, BMI, smoking, alcohol consumption, education grade, and total energy intake 
Lagergren et al., 2013 PBCC <80 987, 167 Sweden Esophageal squamous cell carcinoma FFQ Q4 vs. Q1 1.15 (0.68–1.94) Age, sex, reflux, BMI, smoking, alcohol consumption, education grade, and total energy intake 
Mayne et al., 2001 PBCC 30-80 969, 282 United States Esophageal adenocarcinoma FFQ T3 vs. T1 1.49 (1.02–2.18) Age, site, sex, race, proxy status, BMI, income, education, smoking, and alcohol consumption 
Mayne et al., 2001 PBCC 30–80 893, 206 United States Esophageal squamous cell carcinoma FFQ T3 vs. T1 1.75 (1.07–2.88) Age, site, sex, race, proxy status, BMI, income, education, smoking, and alcohol consumption 
Tuyns et al., 1987 PBCC NA 2718, 743 France Esophageal cancer FFQ Heavy vs. Low consumers 0.51 (0.33–0.79) Age, alcohol consumption, and tobacco smoking 
Tzonou et al., 1996 HBCC NA 256, 56 Greece Esophageal adenocarcinoma FFQ Highest vs. Lowest 0.84 (0.56–1.27) Age, sex, birth place, schooling, height, analgesics, coffee drinking, alcohol intake, tobacco smoking, and energy intake 
Tzonou et al., 1996 HBCC NA 243, 43 Greece Esophageal squamous cell carcinoma FFQ Highest vs. Lowest 1.13 (0.72–1.76) Age, sex, birth place, schooling, height, analgesics, coffee drinking, alcohol intake, tobacco smoking, and energy intake 
Wolfgarten et al., 2001 PBCC 62.2 ± 1.9 140, 40 Germany Esophageal adenocarcinoma FFQ >75 vs. <50 g/day 2.3 (0.7–6.8) Age, gender, height, weight, BMI and socioeconomic data such as marital status and earning capacity 
Wolfgarten et al., 2001 PBCC 58.1 ± 1.2 145, 45 Germany Esophageal squamous cell carcinoma FFQ >75 vs. <50 g/day 1.7 (0.4–6.2) Age, gender, height, weight, BMI and socioeconomic data such as marital status and earning capacity 
Wu et al., 2007 PBCC 30–74 1514, 206 United States Esophageal adenocarcinoma FFQ Q4 vs. Q1 2.22 (1.20–3.90) Age, sex, race, birth place, education, smoking, BMI, reflux, use of vitamins, total calories, and fat 
Zhang et al. 1997 HBCC NA 214, 90 United States Esophageal adenocarcinoma HHHQ Q4 vs. Q1 0.8 (0.6–1.2) Age, sex, race, education, smoking, alcohol intake, BMI, and total dietary intake in calories 

Abbreviations: BMI, body mass index; FFQ, food frequency questionnaire; HBCC, hospital-based case–control study; HHHQ, health habits and history questionnaire; NA, not available; PBCC, population-based case–control study; Q1, Quartile 1; Q4, Quartile 4; T1, Tertile 1; T3, Tertile 3.

Meta-analysis results

In our included articles, four texts (Lagergren et al. (2013) [30], Mayne et al. (2001) [31], Tzonou et al. (1996) [33] and Wolfgarten et al. (2001) [34]) studied esophageal adenocarcinoma and esophageal squamous cell carcinoma at the same time. Therefore, 11 articles with 15 independent studies were used for the analysis.

Our data showed that highest category of dietary protein intake compared with lowest category had no significant association with esophageal cancer risk in the overall analysis (pooled OR = 1.11, 95% CI = 0.88–1.40, I2 = 67.0%, Pfor heterogeneity<0.001) (Figure 2).

The forest plot of the association between dietary protein intake and esophageal cancer risk

Figure 2
The forest plot of the association between dietary protein intake and esophageal cancer risk
Figure 2
The forest plot of the association between dietary protein intake and esophageal cancer risk
Close modal

Hierarchical analyses by study design, protein type (animal protein and vegetable protein), geographic locations (Europe, North America and South America) and number of cases were performed; the association was not significant in all the subgroups. Interestingly, dietary protein intake could significantly increase the risk of esophageal squamous cell carcinoma (pooled OR = 1.29, 95% CI = 1.02–1.62), instead of other disease types, when we performed the analysis between dietary protein intake and disease type (Figure 2). The detailed results are shown in Table 2.

Table 2
Summarized results of the protein intake and the risk of esophageal cancer
SubgroupsNumber of studiesNumber of casesOR (95% CI)P for trendHeterogeneity test
I2 (%)P
Total 15 2537 1.112 (0.883–1.400) 0.367 67.0 <0.001 
 Disease type       
  Esophageal adenocarcinoma 986 1.051 (0.736–1.500) 0.786 71.5 0.002 
  Esophageal squamous cell carcinoma 742 1.285 (1.019–1.620) 0.034 0.0 0.558 
 Study design       
  PBCC 2001 1.142 (0.774–1.686) 0.502 75.5 <0.001 
  HBCC 536 1.080 (0.839–1.390) 0.551 48.6 0.083 
 Protein type       
  Animal protein 701 1.330 (0.598–2.958) 0.484 91.7 <0.001 
  Vegetable protein 615 0.544 (0.249–1.187) 0.126 89.7 <0.001 
 Geographic locations       
  Europe 1282 0.931 (0.688–1.261) 0.645 49.5 0.064 
  North America 908 1.183 (0.736–1.902) 0.486 80.9 <0.001 
  South America 300 1.286 (0.881–1.877) 0.192 37.8 0.205 
  Asia 47 
 Number of cases       
  <200 10 866 1.041 (0.816–1.328) 0.748 51.2 0.030 
  ≥200 1671 1.228 (0.741–2.036) 0.425 82.5 <0.001 
SubgroupsNumber of studiesNumber of casesOR (95% CI)P for trendHeterogeneity test
I2 (%)P
Total 15 2537 1.112 (0.883–1.400) 0.367 67.0 <0.001 
 Disease type       
  Esophageal adenocarcinoma 986 1.051 (0.736–1.500) 0.786 71.5 0.002 
  Esophageal squamous cell carcinoma 742 1.285 (1.019–1.620) 0.034 0.0 0.558 
 Study design       
  PBCC 2001 1.142 (0.774–1.686) 0.502 75.5 <0.001 
  HBCC 536 1.080 (0.839–1.390) 0.551 48.6 0.083 
 Protein type       
  Animal protein 701 1.330 (0.598–2.958) 0.484 91.7 <0.001 
  Vegetable protein 615 0.544 (0.249–1.187) 0.126 89.7 <0.001 
 Geographic locations       
  Europe 1282 0.931 (0.688–1.261) 0.645 49.5 0.064 
  North America 908 1.183 (0.736–1.902) 0.486 80.9 <0.001 
  South America 300 1.286 (0.881–1.877) 0.192 37.8 0.205 
  Asia 47 
 Number of cases       
  <200 10 866 1.041 (0.816–1.328) 0.748 51.2 0.030 
  ≥200 1671 1.228 (0.741–2.036) 0.425 82.5 <0.001 

Abbreviations: HBCC, hospital-based case–control study; PBCC, population-based case–control study.

Sensitivity analyses and publication bias

Sensitivity analyses detected that no single study largely affected the overall data, indicating our results are statistically stable (data are shown in Supplementary Table S3). Neither Begg’s funnel plot (Figure 3) nor Egger’s test (P=0.429) found any significant publication bias.

Funnel plot for the analysis of publication bias between dietary protein intake and esophageal cancer risk

Figure 3
Funnel plot for the analysis of publication bias between dietary protein intake and esophageal cancer risk
Figure 3
Funnel plot for the analysis of publication bias between dietary protein intake and esophageal cancer risk
Close modal

Our study showed that no significant relationship was found between protein intake and esophageal cancer risk in the overall analysis, as well as in the subgroup analyses by study design, protein type, geographic locations and number of cases. However, stratified analysis of disease type showed that protein intake may be a risk factor on the development of esophageal squamous cell carcinoma, instead of esophageal adenocarcinoma.

Protein is involved in the organization of human tissues. Meanwhile, it is vital for our body’s growth and development, as well as the transport of some essential substances and the provision of bioenergy [37,38]. However, protein may affect the cancer differently with different sources [39], such as meat (red meat and processed meat), egg, soy food and milk [39]. In our study, we pooled the results for total protein intake. We only performed a subgroup analysis by animal protein and vegetable protein because no specific classification of protein intake was available in each study. Pournaghi et al. performed a study about animal protein intake with esophageal cancer risk [7]. Results from their study suggested meat intake including beef, processed meats (sausages) and chicken with skin had a positive association with esophageal cancer risk. The use of lamb meat and fish had no significant association with esophageal cancer risk [7]. Therefore, further studies with detailed sources of protein are warranted to explore some other potential results.

In a previous meta-analysis published by Mao et al. [17], dietary protein intake had no significant effects on prostate cancer risk. Pang and Wang [19] tried to assess the association about dietary protein intake and ovarian cancer risk. Similarly, they failed to find a positive result between them [19]. Results from a meta-analysis by Lai et al. [18] suggested that protein intake had no significant association with colorectal cancer risk. Our study got a consistent result with the above-mentioned meta-analyses. However, we found an increased risk on esophageal squamous cell carcinoma with high protein intake when we conducted a subgroup analysis by cancer subtypes. Different cancer pathogenesis may exist in different cancer subtypes, regarding the effect of dietary proteins [30,31].

Significant between-study heterogeneity (I2 = 67.0%, Pfor heterogeneity<0.001) was found in the overall results. As introduced in the ‘Methods’ section, we then used meta-regression to explore the causes of heterogeneity by the covariates of disease type, protein type, study design, geographic locations and assessment of intake. We did not find any covariates which caused this high between-study heterogeneity. Subgroup analyses were performed and the between-study heterogeneity also existed in some subgroup analyses. However, sensitivity analysis showed that no single study largely affected the overall data. Therefore, our results, in whole or in subgroup analyses, were stable.

This meta-analysis had several limitations. First, subgroup analyses of age, sex, smoking or drinking status were not conducted due to data shortage. Although we did not perform the subgroup analyses by the factors we mentioned above, most of the included studies had adjusted for age, sex, smoking or drinking status and some other related factors. Therefore, they may not affect the overall result. Second, our meta-analysis included 11 articles, which were all case–control studies. The selection bias, recall bias and some other confounding factors cannot be excluded in the case–control studies. Therefore, some cohort studies should be conducted to further confirm this result. Third, different protein types may have different effects on esophageal cancer risk. However, most of the included articles did not report the protein type with esophageal cancer risk, respectively. Fourth, dose–response analysis was not done because of the limited data in each study. Dose–response analysis would use the detailed amount of dietary protein, detailed cases and controls in each category, however, only one study (Wolfgarten et al. (2001) [34]) met the criterion of dose–response analysis. Therefore, further studies with detailed amounts of protein intake, detailed cases and controls in each category are warranted to get a dose–response result. Fifth, patients with esophageal cancer may not follow a ‘healthy diet’, such as high vegetable, fruit etc. This may increase some between-study heterogeneity and publication bias. At last, all the included articles were with English language. This may omit some articles which were with other languages. However, no publication bias was detected in our study.

In conclusion, dietary protein intake had no significant association on esophageal cancer risk in the overall analysis; but, protein intake may be associated with the risk of esophageal squamous cell carcinoma. While some limitations exited in the present paper, more studies with large sample size are warranted to further confirm this result.

The conception and design of this research, and the data extraction: F.K., E.G. and J.N. Calculated the data: Z.L. and A.W. Wrote the manuscript: F.K. Reviewed and revised the manuscript: S.Z. and H.W. All the authors approved the final manuscript.

The authors declare that there are no competing interests associated with the manuscript.

The authors declare that there are no sources of funding to be acknowledged.

CI

confidence interval

OR

odds ratio

1.
Fitzmaurice
C.
,
Allen
C.
,
Barber
R.M.
,
Barregard
L.
,
Bhutta
Z.A.
,
Brenner
H.
,
Global Burden of Disease Cancer, C.
et al
, (
2017
)
Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-years for 32 Cancer Groups, 1990 to 2015: A Systematic Analysis for the Global Burden of Disease Study
.
JAMA Oncol.
3
,
524
548
[PubMed]
2.
Ferlay
J.
,
Colombet
M.
,
Soerjomataram
I.
,
Mathers
C.
,
Parkin
D.M.
,
Pineros
M.
et al.
(
2019
)
Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods
.
Int. J. Cancer
144
,
1941
1953
[PubMed]
3.
Mao
N.
,
Nie
S.
,
Hong
B.
,
Li
C.
,
Shen
X.
and
Xiong
T.
(
2016
)
Association between alcohol dehydrogenase-2 gene polymorphism and esophageal cancer risk: a meta-analysis
.
World J. Surg. Oncol.
14
,
191
[PubMed]
4.
Wang
L.
,
Yu
X.
,
Li
J.
,
Zhang
Z.
,
Hou
J.
and
Li
F.
(
2016
)
Prognostic significance of p53 expression in patients with esophageal cancer: a meta-analysis
.
BMC Cancer
16
,
373
[PubMed]
5.
Zhang
Y.
(
2013
)
Epidemiology of esophageal cancer
.
World J. Gastroenterol.
19
,
5598
5606
[PubMed]
6.
Lin
Y.
,
Totsuka
Y.
,
He
Y.
,
Kikuchi
S.
,
Qiao
Y.
,
Ueda
J.
et al.
(
2013
)
Epidemiology of esophageal cancer in Japan and China
.
J. Epidemiol.
23
,
233
242
[PubMed]
7.
Sardana
R.K.
,
Chhikara
N.
,
Tanwar
B.
and
Panghal
A.
(
2018
)
Dietary impact on esophageal cancer in humans: a review
.
Food Funct.
9
,
1967
1977
[PubMed]
8.
Ma
J.L.
,
Zhao
Y.
,
Guo
C.Y.
,
Hu
H.T.
,
Zheng
L.
,
Zhao
E.J.
et al.
(
2018
)
Dietary vitamin B intake and the risk of esophageal cancer: a meta-analysis
.
Cancer Manag. Res.
10
,
5395
5410
[PubMed]
9.
Cui
L.
,
Li
L.
,
Tian
Y.
,
Xu
F.
and
Qiao
T.
(
2018
)
Association between dietary vitamin E intake and esophageal cancer risk: an updated meta-analysis
.
Nutrients
10
,
pii: E801
10.
McRae
M.P.
(
2018
)
The benefits of dietary fiber intake on reducing the risk of cancer: an umbrella review of meta-analyses
.
J. Chiropr. Med.
17
,
90
96
[PubMed]
11.
Liu
W.
,
Zhou
H.
,
Zhu
Y.
and
Tie
C.
(
2017
)
Associations between dietary folate intake and risks of esophageal, gastric and pancreatic cancers: an overall and dose-response meta-analysis
.
Oncotarget
8
,
86828
86842
[PubMed]
12.
Zhao
Y.
,
Guo
C.
,
Hu
H.
,
Zheng
L.
,
Ma
J.
,
Jiang
L.
et al.
(
2017
)
Folate intake, serum folate levels and esophageal cancer risk: an overall and dose-response meta-analysis
.
Oncotarget
8
,
10458
10469
[PubMed]
13.
Chhikara
N.
,
Kushwaha
K.
,
Sharma
P.
,
Gat
Y.
and
Panghal
A.
(
2019
)
Bioactive compounds of beetroot and utilization in food processing industry: a critical review
.
Food Chem.
272
,
192
200
[PubMed]
14.
Chhikara
N.
,
Kour
R.
,
Jaglan
S.
,
Gupta
P.
,
Gat
Y.
and
Panghal
A.
(
2018
)
Citrus medica: nutritional, phytochemical composition and health benefits - a review
.
Food Funct.
9
,
1978
1992
[PubMed]
15.
Chhikara
N.
,
Devi
H.R.
,
Jaglan
S.
,
Sharma
P.
,
Gupta
P.
and
Panghal
A.
(
2018
)
Bioactive compounds, food applications and health benefits of Parkia speciosa (stinky beans): a review
.
Agric. Food Secur.
7
,
46
54
16.
Chhikara
N.
,
Kaur
R.
,
Jaglan
S.
,
Sharma
P.
,
Gat
Y.
and
Panghal
A.
(
2018
)
Bioactive compounds and pharmacological and food applications of Syzygium cumini - a review
.
Food Funct.
9
,
6095
6115
17.
Mao
Y.
,
Tie
Y.
and
Du
J.
(
2018
)
Association between dietary protein intake and prostate cancer risk: evidence from a meta-analysis
.
World J. Surg. Oncol.
16
,
152
[PubMed]
18.
Lai
R.
,
Bian
Z.
,
Lin
H.
,
Ren
J.
,
Zhou
H.
and
Guo
H.
(
2017
)
The association between dietary protein intake and colorectal cancer risk: a meta-analysis
.
World J. Surg. Oncol.
15
,
169
[PubMed]
19.
Pang
Y.
and
Wang
W.
(
2018
)
Dietary protein intake and risk of ovarian cancer: evidence from a meta-analysis of observational studies
.
Biosci. Rep.
38
,
pii: BSR20181857
20.
Stang
A.
(
2010
)
Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses
.
Eur. J. Epidemiol.
25
,
603
605
[PubMed]
21.
DerSimonian
R.
and
Laird
N.
(
1986
)
Meta-analysis in clinical trials
.
Control. Clin. Trials
7
,
177
188
[PubMed]
22.
Higgins
J.P.
,
Thompson
S.G.
,
Deeks
J.J.
and
Altman
D.G.
(
2003
)
Measuring inconsistency in meta-analyses
.
BMJ
327
,
557
560
[PubMed]
23.
Higgins
J.P.
and
Thompson
S.G.
(
2004
)
Controlling the risk of spurious findings from meta-regression
.
Stat. Med.
23
,
1663
1682
[PubMed]
24.
Begg
C.B.
and
Mazumdar
M.
(
1994
)
Operating characteristics of a rank correlation test for publication bias
.
Biometrics
50
,
1088
1101
[PubMed]
25.
Egger
M.
,
Davey Smith
G.
,
Schneider
M.
and
Minder
C.
(
1997
)
Bias in meta-analysis detected by a simple, graphical test
.
BMJ
315
,
629
634
[PubMed]
26.
Chen
H.
,
Tucker
K.L.
,
Graubard
B.I.
,
Heineman
E.F.
,
Markin
R.S.
,
Potischman
N.A.
et al.
(
2002
)
Nutrient intakes and adenocarcinoma of the esophagus and distal stomach
.
Nutr. Cancer
42
,
33
40
[PubMed]
27.
De Stefani
E.
,
Ronco
A.
,
Mendilaharsu
M.
and
Deneo-Pellegrini
H.
(
1999
)
Diet and risk of cancer of the upper aerodigestive tract–II. Nutrients
.
Oral Oncol.
35
,
22
26
28.
De Stefani
E.
,
Ronco
A.L.
,
Boffetta
P.
,
Deneo-Pellegrini
H.
,
Acosta
G.
,
Correa
P.
et al.
(
2006
)
Nutrient intake and risk of squamous cell carcinoma of the esophagus: a case-control study in Uruguay
.
Nutr. Cancer
56
,
149
157
[PubMed]
29.
Jessri
M.
,
Rashidkhani
B.
,
Hajizadeh
B.
,
Jessri
M.
and
Gotay
C.
(
2011
)
Macronutrients, vitamins and minerals intake and risk of esophageal squamous cell carcinoma: a case-control study in Iran
.
Nutr. J.
10
,
137
[PubMed]
30.
Lagergren
K.
,
Lindam
A.
and
Lagergren
J.
(
2013
)
Dietary proportions of carbohydrates, fat, and protein and risk of oesophageal cancer by histological type
.
PLoS ONE
8
,
e54913
[PubMed]
31.
Mayne
S.T.
,
Risch
H.A.
,
Dubrow
R.
,
Chow
W.H.
,
Gammon
M.D.
,
Vaughan
T.L.
et al.
(
2001
)
Nutrient intake and risk of subtypes of esophageal and gastric cancer
.
Cancer Epidemiol. Biomarkers Prev.
10
,
1055
1062
[PubMed]
32.
Tuyns
A.J.
,
Riboli
E.
,
Doornbos
G.
and
Pequignot
G.
(
1987
)
Diet and esophageal cancer in Calvados (France)
.
Nutr. Cancer
9
,
81
92
[PubMed]
33.
Tzonou
A.
,
Lipworth
L.
,
Garidou
A.
,
Signorello
L.B.
,
Lagiou
P.
,
Hsieh
C.
et al.
(
1996
)
Diet and risk of esophageal cancer by histologic type in a low-risk population
.
Int. J. Cancer
68
,
300
304
[PubMed]
34.
Wolfgarten
E.
,
Rosendahl
U.
,
Nowroth
T.
,
Leers
J.
,
Metzger
R.
,
Holscher
A.H.
et al.
(
2001
)
Coincidence of nutritional habits and esophageal cancer in Germany
.
Onkologie
24
,
546
551
[PubMed]
35.
Wu
A.H.
,
Tseng
C.C.
,
Hankin
J.
and
Bernstein
L.
(
2007
)
Fiber intake and risk of adenocarcinomas of the esophagus and stomach
.
Cancer Causes Control.
18
,
713
722
[PubMed]
36.
Zhang
Z.F.
,
Kurtz
R.C.
,
Yu
G.P.
,
Sun
M.
,
Gargon
N.
,
Karpeh
M.
Jr
et al.
(
1997
)
Adenocarcinomas of the esophagus and gastric cardia: the role of diet
.
Nutr. Cancer
27
,
298
309
[PubMed]
37.
Wolfe
R.R.
(
2015
)
Update on protein intake: importance of milk proteins for health status of the elderly
.
Nutr. Rev.
73
,
41
47
[PubMed]
38.
Lauber
S.N.
,
Ali
S.
and
Gooderham
N.J.
(
2004
)
The cooked food derived carcinogen 2-amino-1-methyl-6-phenylimidazo[4,5-b] pyridine is a potent oestrogen: a mechanistic basis for its tissue-specific carcinogenicity
.
Carcinogenesis
25
,
2509
2517
[PubMed]
39.
Wu
J.
,
Zeng
R.
,
Huang
J.
,
Li
X.
,
Zhang
J.
,
Ho
J.C.
et al.
(
2016
)
Dietary protein sources and incidence of breast cancer: a dose-response meta-analysis of prospective studies
.
Nutrients
10
,
pii: E730

Author notes

*

These authors contributed equally to this work.

This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY).

Supplementary data