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Apple intake and cancer risk: a systematic review and meta-analysis of observational studies

Published online by Cambridge University Press:  22 March 2016

Roberto Fabiani*
Affiliation:
Department of Chemistry, Biology and Biotechnology, University of Perugia, Via del Giochetto, 06126 Perugia, Italy
Liliana Minelli
Affiliation:
Department of Experimental Medicine, University of Perugia, Perugia, Italy
Patrizia Rosignoli
Affiliation:
Department of Chemistry, Biology and Biotechnology, University of Perugia, Via del Giochetto, 06126 Perugia, Italy
*
*Corresponding author: Email roberto.fabiani@unipg.it
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Abstract

Objective

Conflicting results on the association between fruit consumption and cancer risk have been reported. Little is known about the cancer preventive effects of different fruit types. The present meta-analysis investigates whether an association exists between apple intake and cancer risk.

Design

Relevant observational studies were identified by literature search (PubMed, Web of Science and Embase). A random-effect model was used to estimate the cancer risk in different anatomical sites. Between-study heterogeneity and publication bias were assessed using adequate statistical tests.

Results

Twenty case–control (three on lung, five on colorectal, five on breast, two on oesophageal, three on oral cavity, two on prostate and one each on pancreas, bladder, larynx, ovary, kidney and brain cancer) and twenty-one cohort (seven on lung, two on colorectal, three on breast and one each on oesophageal, pancreas, bladder, kidney, endometrial, head–neck, urothelial and stomach cancer) studies met the inclusion criteria. Comparing the highest v. lowest level of apple consumption, the reduction of lung cancer risk was statistically highly significant in both case–control (OR=0·75; 95% CI 0·63, 0·88; P=0·001, I2=0 %) and cohort studies (relative risk=0·89; 95% CI 0·84, 0·94; P<0·001, I2=53 %). Instead, in the case of colorectal (OR=0·66; 95% CI 0·54, 0·81; P<0·001, I2=55%), breast (OR=0·79; 95% CI 0·73, 0·87; P<0·001, I2=1 %) and overall digestive tract (OR=0·50; 95% CI 0·36, 0·69; P<0·001, I2=90 %) cancers a significant preventive effect of apples was found only in case–control studies while prospective studies indicated no effect. No evidence of publication bias could be detected for colorectal, oral cavity, oesophageal and breast cancer. However, some confounding effects may be present and related to the consumption of other fruit which have not been considered as adjusting factors.

Conclusions

The present meta-analysis indicates that consumption of apples is associated with a reduced risk of cancer in different anatomical sites.

Type
Review Article
Copyright
Copyright © The Authors 2016 

Cancer is a chronic degenerative disease causing major morbidity and mortality in Western countries. It has been estimated that in the year 2012, 14·1 million new cancer cases were diagnosed and 8·2 million cancer deaths were established( Reference Ferlay, Soerjomataram and Ervik 1 ). The overall age-standardized cancer incidence rates vary three- to fivefold across different regions of the world( Reference Vineis and Wild 2 ). These variations may be related to different modifiable risk and preventive factors among which diet may play a central role. It has been estimated that about one-third of all cancer could be avoidable by changes in eating habits( Reference Willett 3 ).

Foods of plant origin have received particular interest over the years as potential cancer-preventive components of a healthy diet. Fruit and vegetables contain a myriad of bioactive phytochemicals that, through various molecular mechanisms, show chemopreventive properties in both in vitro and in vivo models of carcinogenesis( Reference Liu 4 ). However, from an epidemiological point of view, while early data from case–control studies suggested a clear preventive role for fruit and vegetables on cancer in different sites, recent large prospective studies have questioned this conclusion( Reference Norat, Aune and Chan 5 ). Indeed, while an expert panel report from the World Cancer Research Fund/American Institute for Cancer Research published in 1997 stated that there was ‘convincing’ evidence that a high intake of fruit and/or vegetables prevents cancers, an updated report published 10 years later downgraded the evidence to either ‘probable’ or ‘limited-suggestive’( 6 ).

Because of the peculiar chemical composition and the potential molecular mechanisms involved, it is possible that some types of fruit/vegetable may be much more strongly associated with cancer risk than others. This may be hidden in epidemiological studies examining the association of cancer risk with total fruit/vegetable intake. In this respect, our interest was attracted by apples considering that they are the most consumed fruit in European countries and they are a rich source of bioactive phytochemicals (phenols and flavonoids) possessing strong chemopreventive and antioxidant activities( Reference Hyson 7 ). We therefore conducted a systematic review of the literature on the relationship between apple intake and cancer risk, and for the first time undertook a meta-analysis to provide quantitative estimates of the association.

Materials and methods

Literature search strategy

We carried out a comprehensive literature search, without restrictions, up to December 2015 through PubMed (http://www.ncbi.nlm.nih.gov/pubmed/), Web of Science (http://wokinfo.com/) and Embase (http://www.embase.com) to identify all original articles on the association between apple intake and cancer risk using the following search keywords: (apple OR apples OR Rosaceae OR Malus domestica) AND (cancer OR neoplastic disease OR neoplasm). Furthermore, the reference lists of included articles and recent relevant reviews were manually examined to identify additional relevant publications. The standard procedures for conducting and reporting meta-analysis according to the guidelines from the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group were followed( Reference Stroup, Berlin and Morton 8 ).

Selection criteria

Potential identified articles were included if they met the following criteria: (i) used a case–control or prospective study design; (ii) evaluated the association between apple intake and cancer risk; and (iii) presented OR, relative risk (RR) or hazard ratio (HR) estimates with 95 % CI. When there were several publications from the same study, the publication with the largest number of cases was selected. Although useful to have background information, reviews and meta-analysis were excluded.

Data abstraction and quality assessment

For each potential study included, two investigators independently carried out the selection evaluation, data abstraction and quality assessment; disagreements between evaluators concerning the selected studies were resolved by discussion or in consultation with a third author. From the selected studies we extracted the following data: the first author’s last name, year of publication, study region and design, tumour site, sample size (number of cases and controls; cohort size and incident cases), age, duration of follow-up for cohort studies, dietary assessment method, apple intake and OR/RR/HR estimates with 95 % CI for the highest v. lowest category of apple intake. When multiple estimates were reported in the article, we abstracted those that adjusted for the most confounding factors. If separate risk estimates for males and females were available in one study, we treated them as two separate studies.

The study quality was assessed by a nine-star system based on the Newcastle–Ottawa Scale method( Reference Wells, Shea and O’Connell 9 ). The full score was 9 and a total score ≥7 was used to indicate a high-quality study. To avoid selection bias, no study was excluded because of these quality criteria.

Statistical analysis

For the overall estimation, the HR and RR were taken to be approximations to OR, and the meta-analysis was done as if all types of ratio were OR. The combined risk estimates were calculated using the random-effects model.

The χ 2-based Cochran’s Q statistic and the I 2 statistic were used to evaluate heterogeneity in results across studies. For the Q statistic, a P value <0·1 was considered to be representative of statistically significant heterogeneity. The I 2 statistic yields results ranging from 0 to 100 % (I 2=0–25 %, absent; I 2=25–50 %, low; I 2=50–75 %, moderate; and I 2=75–100 %, high heterogeneity).

Analysis of publication bias was carried out by both Egger’s linear regression test and Begg’s rank correlation test. Both methods test for funnel plot asymmetry, the former being based on the rank correlation between the effect estimates and their sampling variances, and the latter on a linear regression of a standard normal deviate on its precision. If a potential bias was detected, we further conducted a sensitivity analysis to assess the robustness of combined effect estimates and the possible influence of the bias and to have the bias corrected. A sensitivity analysis was conducted to investigate the influence of a single study on the risk estimate by omitting each study in turn. Funnel plots were considered asymmetric if the intercept of Egger’s regression line deviated from zero with a P value of <0·05. The ProMeta Version 2·0 statistical program (Internovi) was used for the analysis. All reported P values are from two-sided statistical tests and differences with P≤0·05 were considered significant.

Results

Literature search

As shown in Fig. 1, 2923 articles were obtained by searching the three different databases (PubMed, Web of Science and Embase). After excluding 997 duplicates, 1926 records were identified for title and abstract revision. Of the 1926 articles screened, 1883 were excluded because they were not observational studies, leaving forty-three articles for full-text revision. Hand searching of reference lists of both selected articles and recent relevant reviews led to the identification of eight additional items. Ten papers were subsequently excluded because they did not met the inclusion criteria as follows: two studies did not report the amount of apple intake; three articles reported the same data of a previous publication; two publications (lowest case numbers) were from the same study; one study did not report the risk estimate and another did not report the CI; and one evaluated the cancer risk in association with apple juice and cider. Therefore, at the end of the selection process, forty-one studies met the inclusion criteria and were included in the systematic review and meta-analysis( Reference Askari, Parizi and Jessri 10 Reference Koushik, Spiegelman and Albanes 50 ).

Fig. 1 Flowchart of the selection process for inclusion of studies in the meta-analysis

Study characteristics and quality assessment

Of the forty-one selected papers, twenty were case–control studies( Reference Askari, Parizi and Jessri 10 Reference Giles, McNeil and Donnan 29 ), seventeen were cohort studies( Reference Boggs, Palmer and Wise 30 Reference Botterweck, van den Brandt and Goldbohm 46 ) and four were pooled analyses of cohort studies( Reference Smith-Warner, Spiegelman and Yaun 47 Reference Koushik, Spiegelman and Albanes 50 ). General characteristics of case–control and cohort studies are shown in Tables 1 and 2, respectively.

Table 1 Characteristics of case–control studies on apple consumption in association with various types of cancer included in the systematic review

N/A, not available; EPIIC, European Prospective Investigation into Cancer and Nutrition; EI, energy intake; PA, physical activity; SES, socio-economic status; CRC, colorectal cancer; NSAID; non-steroidal anti-inflammatory drugs; WHR, waist-to-hip ratio.

Table 2 Characteristics of cohort studies on apple consumption in association with various types of cancer included in the systematic review

HR, hazard ratio; RR, risk ratio; EPIC, European Prospective Investigation into Cancer and Nutrition (Denmark, France, Germany, Greece, Italy, the Netherlands, Norway, Spain, Sweden, UK); NHS, Nurses’ Health Study; HPFS, Health Professionals Follow-up Study; ESCC, oesophageal squamous cell carcinoma; EAC, oesophageal adenocarcinoma; EI, energy intake; PA, physical activity; CRC, colorectal cancer; OC, oral contraceptives; NSAID, non-steroidal anti-inflammatory drugs.

*Rosaceae = apples, peaches, nectarines, plums, pears, strawberries.

Case–control studies were published between 1994 and 2014; three were conducted in Italy( Reference Rossi, Lugo and Lagiou 13 , Reference Sacerdote, Matullo and Polidoro 19 , Reference Gallus, Talamini and Giacosa 22 ), two each in Iran( Reference Askari, Parizi and Jessri 10 , Reference Hajizadeh, Jessri and Moasheri 15 ), China( Reference Bao, Shu and Zheng 12 , Reference Malin, Qi and Shu 23 ) and Australia( Reference Annema, Heyworth and McNaughton 14 , Reference Giles, McNeil and Donnan 29 ), and one each in Poland( Reference Jedrychowski, Maugeri and Popiela 16 ), Spain( Reference Tarrazo-Antelo, Ruano-Ravina and Abal Arca 11 ), Czech Republic( Reference Kubik, Zatloukal and Tomasek 17 ), Brazil( Reference Di Pietro, Medeiros and Vieira 18 ), UK( Reference Theodoratou, Kyle and Cetnarskyj 20 ), India( Reference Rajkumar, Sridhar and Balaram 24 ), Hawaii( Reference Le Marchand, Murphy and Hankin 25 ), Mexico( Reference Torres-Sánchez, López-Carrillo and López-Cervantes 26 ), Sweden( Reference Lindblad, Wolk and Bergström 27 ) and Uruguay( Reference Deneo-Pellegrini, De Stefani and Ronco 28 ). One was a multinational study conducted in nine countries worldwide (Italy, Spain, Poland, Northern Ireland, India, Cuba, Canada, Australia and Sudan)( Reference Kreimer, Randi and Herrero 21 ). Three case–control studies were on lung cancer (2049 cases and 4044 controls), five on colorectal cancer (3319 cases and 10 158 controls), five on breast cancer (7682 cases and 11 880 controls), two on oesophageal cancer (447 cases and 6725 controls), three on oral cavity cancer (2859 cases and 8943 controls), two on prostate cancer (1344 cases and; 6729 controls) and one each on pancreas, bladder, larynx, ovary, kidney and brain (glioma) cancer.

Cohort studies were published between 1998 and 2012; nine were conducted in the USA( Reference Boggs, Palmer and Wise 30 , Reference Kabat, Park and Hollenbeck 31 , Reference Wang, Lee and Zhang 34 Reference Freedman, Park and Subar 37 , Reference Lin, Zhang and Wu 39 , Reference Adebamowo, Cho and Sampson 40 , Reference Feskanich, Ziegler and Michaud 45 ) and eight were conducted in Europe( Reference Büchner, Bueno-de-Mesquita and Linseisen 32 , Reference Büchner, Bueno-de-Mesquita and Ros 33 , Reference Linseisen, Rohrmann and Miller 38 , Reference Rashidkhani, Lindblad and Wolk 41 Reference Zeegers, Goldbohm and van den Brandt 44 , Reference Botterweck, van den Brandt and Goldbohm 46 ). Pooled analysis were conducted in the USA, Canada, Europe and Australia and included from seven to fourteen prospective studies( Reference Smith-Warner, Spiegelman and Yaun 47 Reference Koushik, Spiegelman and Albanes 50 ). Seven cohort studies were on lung cancer (1 912199 cohort and 12 913 incident cases), two on colorectal cancer (796 305 cohort and 6367 incident cases), three on breast cancer (479 219 cohort and 9195 incident cases), and one each on oesophageal, pancreatic, bladder, kidney, endometrial, head–neck, urothelial, stomach and all types of cancer.

Study-specific quality scores are summarized in the supplementary material, Table S1 and Table S2 for case–control and cohort studies, respectively. The range of quality score was from 4 to 8 (median=6, mean=6·25, sd=1·20) and from 7 to 9 (median=8, mean=8·1, sd=0·85) for case–control and cohort studies, respectively. High-quality studies (i.e. those studies that had seven awarded stars) included eight case–control( Reference Askari, Parizi and Jessri 10 , Reference Rossi, Lugo and Lagiou 13 Reference Hajizadeh, Jessri and Moasheri 15 , Reference Theodoratou, Kyle and Cetnarskyj 20 , Reference Gallus, Talamini and Giacosa 22 , Reference Malin, Qi and Shu 23 , Reference Torres-Sánchez, López-Carrillo and López-Cervantes 26 ) and all twenty-one cohort( Reference Boggs, Palmer and Wise 30 Reference Koushik, Spiegelman and Albanes 50 ) studies.

Apple intake and lung cancer risk

Using the random-effect model, we found that the high intake of apple was significantly associated with a reduced risk of lung cancer in both case–control (OR=0·75; 95 % CI 0·63, 0·88; P=0·001, I 2=0 %; Fig. 2(a)) and cohort (RR=0·89; 95 % CI 0·84, 0·94; P<0·001, I 2=68 %; Fig. 2(b)) studies. A pooled analysis performed by combining case–control and cohort studies resulted in a significant 12 % reduction of lung cancer risk (RR=0·88; 95% CI 0·83, 0·92; P<0·001, I 2=65 %) and allowed stratification based on both the sex and smoking status of the subjects (Table 3). A significant reduction of lung cancer risk was observed in current smokers (RR=0·88; 95% CI 0·77, 1·00; P<0·042, I 2=62 %) and in studies where smokers and non-smokers were considered together (RR=0·82; 95 % CI 0·72, 0·92; P=0·001, I 2=76 %), while the effect was not statistically significant in never smokers (Table 3). When stratifying the studies according to sex, apple intake was found to be significantly associated with lung cancer risk in males (RR=0·79; 95% CI 0·73, 0·85; P<0·001, I 2=3 %) but not in females (RR=0·92; 95% CI 0·82, 1·03; P=0·146, I 2=26 %).

Fig. 2 Forest plots of case–control (a) and cohort (b) studies on apple consumption (highest v. lowest category) and lung cancer risk. Squares indicate the study-specific effect size (ES) derived from comparison between the highest and the lowest apple intake (size of square reflects the study’s statistical weight, i.e. inverse of variance); horizontal lines indicate 95 % confidence interval; diamond indicates the summary effect size estimate with its corresponding 95 % confidence interval

Table 3 Results of stratified analysis of the risk estimates for the highest compared with the lowest apple intake on the basis of study type and cancer siteFootnote *,Footnote

* The analysis was performed when two or more studies were available,

The risk estimates were calculated using the random-effect model.

Number of studies used to calculate the risk is indicated in parentheses.

§ Analysis was performed on case–control and cohort studies combined together.

|| Colorectal, oral cavity, oesophageal and stomach cancers.

Apple intake and risk of digestive tract cancers

A significant reduction of colorectal cancer risk, associated with apple intake, was observed in case–control (OR=0·56; 95 % CI 0·54, 0·81; P<0·001, I 2=55 %; Fig. 3(a)) but not in cohort (RR=0·93; 95 % CI 0·79, 1·10; P=0·4, I 2=13 %; Fig. 3(b)) studies. Combining case–control and cohort studies together resulted in a significant preventive effect of apple intake on colorectal cancer (RR=0·72; 95 % CI 0·59, 0·88; P=0·001, I 2=77%; Table 3). No cohort studies were found on oral cavity cancer risk and apple intake; however, the analysis on case–control studies showed a significant reduction of risk (OR=0·25; 95 % CI 0·08, 0·77; P=0·015, I 2=97 %) even if high heterogeneity was observed (Table 3). Instead, no preventive effect of apples was observed on oesophageal cancer risk both in case–control and cohort studies. The pooled analysis of digestive tract cancers (colorectal, oral cavity, oesophageal and stomach) indicated that apple intake was inversely associated with the risk in case–control studies (OR=0·50; 95 % CI 0·36, 0·69; P<0·001, I 2=90 %) but not in the cohort studies (RR=0·79; 95 % CI 0·61, 1·01; P=0·063, I 2=61 %).

Fig. 3 Forest plots of case–control (a) and cohort (b) studies on apple consumption (highest v. lowest category) and colorectal cancer risk. Squares indicate the study-specific effect size (ES) derived from comparison between the highest and the lowest apple intake (size of square reflects the study’s statistical weight, i.e. inverse of variance); horizontal lines indicate 95 % confidence interval; diamond indicates summary effect size estimate with its corresponding 95 % confidence interval

Apple intake and breast cancer risk

A significant reduction of risk was observed for breast cancer only in case–control (OR=0·79; 95 % CI 0·73, 0·87; P<0·001, I 2=1 %; Fig. 4(a)) but not in cohort (RR=0·97; 95 % CI 0·94, 1·01; P=0·192, I 2=0 %; Fig. 4(b)) studies. Pooled analysis resulted in a slightly significant effect (RR=0·89; 95 % CI 0·79, 1·00; P=0·047, I 2=69 %; Table 3).

Fig. 4 Forest plots of case–control (a) and cohort (b) studies on apple consumption (highest v. lowest category) and breast cancer risk. Squares indicate the study-specific effect size (ES) derived from comparison between the highest and the lowest apple intake (size of square reflects the study’s statistical weight, i.e. inverse of variance); horizontal lines indicate 95 % confidence interval; diamond indicates summary effect size estimate with its corresponding 95 % confidence interval

Apple intake and cancer risk in other anatomical sites

In the case of prostate cancer, two case–control studies were found useful for the analysis that showed no association with apple intake (OR=0·93; 95 % CI 0·79, 1·09; P=0·369, I 2=0 %; Table 3). For other anatomical sites, the availability of a single study did not allow the analysis.

Publication bias and sensitivity analysis

No evidence of publication bias could be detected for risk of colorectal, oral cavity, oesophageal and breast cancer. For the lung and overall digestive tract cancers no publication bias was observed in case–control studies. On the other hand, there was some evidence for publication bias regarding the risk of lung cancer in cohort studies and in pooled analysis as shown by both the Egger’s regression test and funnel plot asymmetry (not shown). However, no publication bias could be detected by Begg’s rank correlation test (the details are shown in Table 3).

Sensitivity analyses investigating the influence of a single study on the lung cancer risk estimate suggested that the risk estimates were not substantially modified by any single study. The lung risk estimates ranged from 0·85 (95 % CI 0·78, 0·91; P<0·001, I 2=36 %) omitting the study of Büchner et al. ( Reference Büchner, Bueno-de-Mesquita and Linseisen 32 ) to 0·92 (95 % CI 0·87, 0·99; P=0·015, I 2=67 %) omitting the study of Wright et al.( Reference Wright, Park and Subar 36 ). Of note, omitting the study of Büchner et al.( Reference Büchner, Bueno-de-Mesquita and Linseisen 32 ) resulted in the absence of publication bias as evidenced by both Egger’s regression (P=0·659) and Begg’s rank correlation (P=0·528) tests.

Discussion

To the best of our knowledge, the present meta-analysis is the first one investigating the association between apple consumption and cancer risk in different anatomical sites. Apples are a cheap fruit, easy to store and transport, abundantly present and marketed all year, and therefore are among the most popular fruits in the world. For these reasons, we wondered whether an apple a day keeps the oncologist away( Reference Gallus, Talamini and Giacosa 22 ). It is important to underline that in some studies the consumption of apple was asked as a single item( Reference Askari, Parizi and Jessri 10 , Reference Tarrazo-Antelo, Ruano-Ravina and Abal Arca 11 , Reference Annema, Heyworth and McNaughton 14 Reference Theodoratou, Kyle and Cetnarskyj 20 , Reference Gallus, Talamini and Giacosa 22 , Reference Malin, Qi and Shu 23 , Reference Le Marchand, Murphy and Hankin 25 Reference Giles, McNeil and Donnan 29 , Reference Wright, Park and Subar 36 , Reference Adebamowo, Cho and Sampson 40 Reference Arts, Hollman and Bueno De Mesquita 43 ) while in others the assessment regarded Rosaceae ( Reference Bao, Shu and Zheng 12 , Reference Kabat, Park and Hollenbeck 31 , Reference Freedman, Park and Subar 35 Reference Freedman, Park and Subar 37 ) and ‘apples and pears’ together( Reference Rossi, Lugo and Lagiou 13 , Reference Kreimer, Randi and Herrero 21 , Reference Rajkumar, Sridhar and Balaram 24 , Reference Büchner, Bueno-de-Mesquita and Linseisen 32 , Reference Büchner, Bueno-de-Mesquita and Ros 33 , Reference Linseisen, Rohrmann and Miller 38 , Reference Zeegers, Goldbohm and van den Brandt 44 Reference Koushik, Spiegelman and Albanes 50 ). It would have been interesting to make a stratified analysis as a function of apple intake assessment to highlight the extent to which it influenced the results, but due to the small number of studies this was not possible. Therefore, confounding effects by the intake of other fruits may not be excluded. In particular, when considering the confounding adjusting factors (reported in the last column of Tables 1 and 2) the consumption of other fruit was taken into account only in a few cases( Reference Bao, Shu and Zheng 12 , Reference Jedrychowski, Maugeri and Popiela 16 , Reference Gallus, Talamini and Giacosa 22 , Reference Wright, Park and Subar 36 , Reference Zeegers, Goldbohm and van den Brandt 44 ). Due to the small number of studies recovered for each tumour site and to summarize the overall effect size, the data derived from case–control and cohort studies have also been combined. The pooled results indicated that apple consumption (comparisons between the highest and the lowest category) was significantly associated with lower risk of different cancer types. However, when separately analysed on the basis of study type (case–control v. cohort), we generally found that the effect size was more consistent in case–control studies compared with cohort studies. In many cases the analysis of cohort studies did not evidence a significant effect of apple intake on cancer risk, while case–control studies showed a preventive effect. In particular, in the case of lung cancer, the reduction of risk associated with apple intake was statistically highly significant in both case–control and cohort studies. Instead, a significant preventive effect of apples on colorectal, breast and overall digestive tract cancers was found only in case–control studies. Similarly to our finding, a previous meta-analysis reported that prospective studies provide weaker evidence than case–control studies on the association of fruit and vegetable consumption with reduced cancer risk( Reference Riboli and Norat 51 ). It is common in meta-analysis to find higher effect size in case–control studies compared with cohort data( Reference Kaaks and Riboli 52 ). In general, case–control studies have several weaknesses and critical points which can lead to an overestimation of the effect. They can be affected by recall and selection bias, producing misclassification of exposure between case and control groups, and the control group may not be representative of the general population. On the other hand, it should be also considered that dietary assessment questionnaires used in prospective studies may be somewhat less accurate than those used in retrospective case–control settings. In the current meta-analysis we also found that case–control studies had lower median quality score than prospective studies (6 v. 8), so suggesting that findings derived from retrospective studies should be interpreted with caution. In any event, when data from case–control studies were combined with those from cohort studies the meta-analysis showed a significant reduction in risk of lung (12 %), colorectal (28 %), oesophageal (34 %), digestive tract (41 %) and breast (11 %) cancer.

Regardless of the absolute value of the effect size, the inverse association between apple intake and cancer risk is biologically plausible. Apples are a rich source of many different bioactive phenolic compounds (hydroxybenzoic and hydroxycinnamic acids, flavonols, dihydrochalcones, anthocyanids, monomeric and oligomeric flavanols) which may prevent cancer by several mechanisms( Reference Hyson 7 ). First, phenols have a potent antioxidant activity which may protect DNA from oxidative damage. It has been estimated that a 100 g portion of apples has an antioxidant activity equal to 1·500 mg of vitamin C. In addition, in vitro studies have demonstrated that apple phenols are able to inhibit tumour cell proliferation, induce cell cycle arrest and apoptosis, suppress angiogenesis and metastasis, modulate carcinogen metabolism and signal transduction pathways, and enhance the immune system. Accordingly, cancer chemopreventive properties of apple in vivo have also been demonstrated on several animal models for chemically or genetically induced tumours of the skin, breast and colon, as well as in xenograft models for solid tumours. These data demonstrate that apple constituents may have a systemic effect at the level of different organs, in addition to the more reasonable effect on the gastrointestinal tract.

In this regard, our results on the preventive effect of apples on lung cancer are very consistent in both case–control and cohort studies, even if in this last case a significant publication bias was found by the Egger test. Obviously, smoking status greatly influences lung cancer risk; therefore it would be important to stratify the analysis according to this variable. Unfortunately, only one case–control( Reference Kubik, Zatloukal and Tomasek 17 ) and two cohort( Reference Wright, Park and Subar 36 , Reference Linseisen, Rohrmann and Miller 38 ) studies reported the risk of lung cancer in association with apple intake for smokers and non-smokers separately. Using these few data, we found a statistically significant effect of apple intake on lung cancer risk in current smokers but not in never smokers. Therefore, further studies are necessary to clarify the potential preventive effects of apples on lung cancer in smokers and never smokers. In contrast to lung cancer, the risk of colorectal and breast cancer resulted to be significantly reduced in case–control studies (34 % and 21 %, respectively) while no significant effect was found in cohort studies. These discrepancies may be in part due to the low number of cohort studies, two for colon–rectum( Reference Lin, Zhang and Wu 39 , Reference Koushik, Hunter and Spiegelman 49 ) and three for breast( Reference Boggs, Palmer and Wise 30 , Reference Adebamowo, Cho and Sampson 40 , Reference Smith-Warner, Spiegelman and Yaun 47 ). It should be considered, however, that two pooled analyses were included in our meta-analysis, one on colorectal cancer( Reference Koushik, Hunter and Spiegelman 49 ) and the other on breast cancer( Reference Smith-Warner, Spiegelman and Yaun 47 ), which considered eleven and seven cohort studies, respectively. Furthermore, a recent pooled analysis of twenty cohort studies on breast cancer (not included in our meta-analysis) showed a small but significant effect (RR=0·92; 95 % CI 0·85, 0·99) of apples, together with pears and applesauce, on oestrogen receptor-negative breast cancer( Reference Jung, Spiegelman and Baglietto 53 ). Therefore, as a result of the complexity and variety of the carcinogenic process, it is possible that the stratification of cases according to molecular targets may highlight associations that until now have not been considered. Further studies are needed to investigate these aspects.

There were some limitations in our meta-analysis. Heterogeneity was evident and, in some cases, particularly high. One reason for this could be the wide range of values for the cut-off points for the lowest and highest categories of apple intake. In addition, the number of studies included in the meta-analysis for each cancer type was not large enough to stratify the analysis according to geographic region, sex and adjustment for confounding factors to try to determine the source of heterogeneity. In the case of lung cancer risk, publication bias was also detected in cohort studies. Stratification according to smoking and sex did not clearly reduce both heterogeneity and publication bias in studies on lung cancer. However, the exclusion of one study( Reference Büchner, Bueno-de-Mesquita and Linseisen 32 ) did not significantly modify the lung cancer risk estimate but eliminated both heterogeneity and publication bias. Although when multiple estimates were available, we abstracted those that adjusted for the most confounding factors, many of the studies included in the analysis varied in the number of potential diet confounding variables (i.e. meat, dairy products, fibre) for which they had not been adjusted. Furthermore, most of the studies were not designed solely to evaluate the association between apple consumption and cancer risk and there were wide variations in dietary assessments of the frequency/quantity of apple intake. For these reasons, in addition to the low number of data available for each cancer site, it was not possible to calculate the dose–response relationship between apple intake and cancer risk in different anatomical organs.

Conclusion

In summary, the current meta-analysis provides convincing evidence supporting the hypothesis of the protective ability of apples in the aetiology of cancer. However, some confounding effects may be present and related to the consumption of other fruit which have not been considered as adjusting factors. Apple consumption was associated with a reduced risk of cancer in the lung, colon–rectum, oral cavity, digestive tract and breast. Further studies will be needed to clarify the effect of apples on cancer risk in other anatomical sites.

Acknowledgements

Financial support: All work was completed at the University of Perugia, Italy. The authors thank their home institution for financial support. Conflict of interest: The authors declare that they have no conflict of interest. Authorship: Study concept and design: R.F., L.M. and P.R. Acquisition of data: R.F. and M.L. Analysis and interpretation of data: R.F., L.M. and P.R. All authors contributed substantively to this manuscript, were involved with critical revisions to the manuscript and provided approval for its publication. Ethics of human subject participation: Not applicable.

Supplementary material

To view supplementary material for this article, please visit http://dx.doi.org/10.1017/S136898001600032X

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Figure 0

Fig. 1 Flowchart of the selection process for inclusion of studies in the meta-analysis

Figure 1

Table 1 Characteristics of case–control studies on apple consumption in association with various types of cancer included in the systematic review

Figure 2

Table 2 Characteristics of cohort studies on apple consumption in association with various types of cancer included in the systematic review

Figure 3

Fig. 2 Forest plots of case–control (a) and cohort (b) studies on apple consumption (highest v. lowest category) and lung cancer risk. Squares indicate the study-specific effect size (ES) derived from comparison between the highest and the lowest apple intake (size of square reflects the study’s statistical weight, i.e. inverse of variance); horizontal lines indicate 95 % confidence interval; diamond indicates the summary effect size estimate with its corresponding 95 % confidence interval

Figure 4

Table 3 Results of stratified analysis of the risk estimates for the highest compared with the lowest apple intake on the basis of study type and cancer site*,†

Figure 5

Fig. 3 Forest plots of case–control (a) and cohort (b) studies on apple consumption (highest v. lowest category) and colorectal cancer risk. Squares indicate the study-specific effect size (ES) derived from comparison between the highest and the lowest apple intake (size of square reflects the study’s statistical weight, i.e. inverse of variance); horizontal lines indicate 95 % confidence interval; diamond indicates summary effect size estimate with its corresponding 95 % confidence interval

Figure 6

Fig. 4 Forest plots of case–control (a) and cohort (b) studies on apple consumption (highest v. lowest category) and breast cancer risk. Squares indicate the study-specific effect size (ES) derived from comparison between the highest and the lowest apple intake (size of square reflects the study’s statistical weight, i.e. inverse of variance); horizontal lines indicate 95 % confidence interval; diamond indicates summary effect size estimate with its corresponding 95 % confidence interval

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