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Fruit and vegetable consumption and the risk of depression: A meta-analysis
Nutrition 32 (2016) 296–302
Contents lists available at ScienceDirect
Nutrition journal homepage: www.nutritionjrnl.com
Review
Fruit and vegetable consumption and the risk of depression: A meta-analysis Xiaoqin Liu M.D. a, Ying Yan Ph.D. b, Fang Li M.D. a, Dongfeng Zhang M.D. a, * a b
Department of Epidemiology and Health Statistics, The Medical College of Qingdao University, Qingdao, Shandong, People’s Republic of China Department of Teaching Research, The Medical College of Qingdao University, Qingdao, Shandong, People’s Republic of China
a r t i c l e i n f o
a b s t r a c t
Article history: Received 13 August 2015 Accepted 13 September 2015
Objective: Epidemiologic investigations evaluating the association of fruit and vegetable consumption with depression risk have yielded controversial results. Therefore, a meta-analysis was carried out to qualitatively summarize the evidence regarding association of fruit and vegetable intake with risk of depression in the general population. Methods: PubMed, Embase, and Web of Knowledge were searched for relevant articles published up to June 2015. To evaluate the association of fruit and vegetable intake with depression risk, combined relative risks were calculated with the fixed or random effects model. Meta-regression was conducted to explore potential sources of heterogeneity. Publication bias was estimated by the Egger’s test and the funnel plot. Results: Ten studies involving 227 852 participants for fruit intake and eight studies involving 218 699 participants for vegetable intake were finally included in this study. The combined relative risk (95% confidence interval) of depression for the highest versus lowest category of fruit and vegetable intake was 0.86 (0.81, 0.91; P < 0.01) and 0.89 (0.83, 0.94; P < 0.01), respectively. In subgroup analyses stratified by study design, the inverse association of fruit (0.83 [0.77, 0.91; P ¼ 0.006]) and vegetable (0.88 [0.79, 0.96; P ¼ 0.007]) intake with risk of depression was also observed in the cohort study. Conclusions: This meta-analysis indicated that fruit and vegetable consumption might be inversely associated with the risk of depression, respectively. Crown Copyright Ó 2016 Published by Elsevier Inc. All rights reserved.
Keywords: Fruit Vegetable Depression Meta-analysis
Introduction Depression is a common mental health disorder On a worldwide scale, about 400 million people suffer from depression [1]. According to the report of World Health Organization, depression accounts for 4.3% of the global burden of disease alone and is one of the largest single causes of disability worldwide [2]. Although the etiology of depression has not been fully explained, the dysfunction of noradrenergic and dopaminergic neurotransmission, disturbance of cellular plasticity, including reduction of neurogenesis, chronic inflammation, and higher oxidative stress may be related to pathogenesis of depression [3–5]. Considering the serious consequences of * Corresponding author. Tel.: þ8653282991712; fax: þ8653283801449. E-mail address: [email protected] (D. Zhang). http://dx.doi.org/10.1016/j.nut.2015.09.009 0899-9007/Crown Copyright Ó 2016 Published by Elsevier Inc. All rights reserved.
depression, it is especially and extremely important to identify the modifiable risk factors and develop prevention and control strategy. Some lifestyle behaviors have been reported to increase the risk of depression, such as sedentary behavior [6], long-term stress [7], and short or long hours of sleep [8]. In recent years, the association between diet and depression has also drawn much attention. Among the dietary factors, consumption of fruits and vegetables, which are rich in antioxidants and antiinflammatory components, was hypothesized to play an important role in depression development [9]. Several epidemiology studies have been carried out to investigate the role of fruit and vegetable intake in the development of depression, but the results are inconsistent. For fruit intake, although an inverse association with the risk of depression was found in some studies [9–12], the association was not observed in other studies [13–17]. For vegetable intake, though an inverse association was reported
X. Liu et al. / Nutrition 32 (2016) 296–302
in three studies [12,13,18], no association was found in the others [9,10,14–16]. Therefore, a meta-analysis was systematically performed to evaluate the association of fruit and vegetable consumption with the risk of depression. Materials and methods Literature search strategy A literature search was performed on the databases of PubMed, Embase, and Web of Knowledge for relevant articles published up to June 2015, using the following search terms: “depression,” “depressive disorder,” “depressive symptoms,” “fruit,” “vegetable,” and “diet” without restrictions. Moreover, the references of related reviews and original articles were also reviewed. The detailed steps of the literature search are shown in Figure 1. Inclusion criteria The inclusion criteria were as follows: 1) observational study published as an original article; 2) the exposure variable of interest was fruit or vegetable consumption; 3) the outcome of interest was depression; 4) relative risks (RRs) or odds ratio estimates (all results are presented with RRs in this study) with their 95% confidence intervals (95% CIs) were available. Depression was determined by self-report based on doctor’s diagnosis, regular use of antidepressant drugs, or depression rating scales. Studies on the postpartum depression and depression in pregnancy were not included in this meta-analysis. If data were duplicated in more than one study, the latest one or the one with the largest number of samples was included. Two investigators searched articles and reviewed all retrieved studies independently. If the two investigators could not reach a consensus about the eligibility of an article, it was solved through discussion with a third investigator. Data extraction Data extracted from each study were as follows: publication year, the first author’s name, country where the study was performed, follow-up years, study design, sample size, mean age or age range at baseline years, fruit and vegetable consumption assessment, determination method of depression, RRs with corresponding 95% CIs for the highest versus lowest categories of fruit and vegetable intake, and adjustment of covariates in the analysis. The RRs adjusted with the most confounders in the original studies were extracted.
297
Statistical analyses Pooled measure was calculated as the inverse-variance weighted mean of the logarithm of RR (95% CI) of depression for the highest versus lowest category of fruit and vegetable intake, respectively. The I2 [19] was used to assess heterogeneity among studies. If I2 50% [20], the random effect model (REM) was adopted as the pooling method; otherwise (I2 < 50%), the fixed effect model (FEM) was employed. Meta-regression was performed to access the potentially important covariates (including publication year, continent, study design, status for physical activity adjustment, and ascertainment method of depression) that might exert substantial impacts on between-study heterogeneity [21]. To assess whether the results could have been affected distinctly by a single study, an influence analysis was carried out with one study removed at a time [22]. The leave-one-out sensitive analysis was conducted to evaluate the key studies that have remarkable impact on the between-study heterogeneity. Publication bias was evaluated with the visual inspection of funnel plot and Egger regression asymmetry test [23]. Subgroup analysis was performed by study design (crosssectional or cohort study). All statistical analyses were conducted using Stata V.12.0 (Stata Corp., College Station, TX, USA). A two-tailed P < 0.05 was considered statistically significant.
Results Literature search and study characteristics The flowchart for study inclusion is shown in Figure 1, and 4950 articles from PubMed, 2544 articles from Embase, and 5484 articles from Web of Knowledge were identified by the search strategy. After excluding duplicates and reviewing the tiles or abstracts, 104 possible related articles concerning fruit and vegetable intake and depression risk were identified. Among these articles, 4 were removed because of duplicate participants [24–27], 62 were excluded because RR or 95% CI was not provided, and 28 were ruled out because the study subjects were the patients of postpartum depression or depression in pregnancy. Overall, 10 articles involving 4 cohort studies and 7 cross-sectional studies were included in this meta-analysis. Table 1 displays the baseline characteristics of the studies.
Quantitative synthesis
Fig. 1. Flowchart of the selection of studies included in the meta-analysis.
Fruit intake and the risk of depression For fruit intake, four cohort studies from four articles [9,10,12, 16] and six cross-sectional studies from five articles [11,13–15,17] involving 227 852 participants were included. Among these studies, three were conducted in Asia [11,13,16], four in Europe [10,15,17], one in Oceania [9], one in North America [14], and one in South America [12]. With regard to the depression diagnostic criteria, eight studies used the scales or questionnaires [9,11–13, 15–17], and two studies were ascertained by interview or self-reported physician diagnosis or use of regular antidepressant medication [10,14]. The major adjusted confounding factors included age, sex, education, body mass index, marital status, smoking status, and physical activity. Among the 10 studies, 4 reported that high fruit intake could decrease the risk of depression [9–12], whereas the other 6 indicated no significant association [13–17]. The pooled RR (95% CI) of depression for the highest versus lowest category of fruit intake was 0.86 (0.81, 0.91; Pfor significance < 0.01, FEM, I2 ¼ 48.2%, Pfor heterogeneity ¼ 0.043; Fig. 2). The pooled RRs for cross-sectional and cohort studies were 0.84 (0.75, 0.95; Pfor significance ¼ 0.006, REM, I2 ¼ 55.7%, Pfor heterogeneity ¼ 0.046) and 0.83 (0.77, 0.91; Pfor significance ¼ 0.001, FEM, I2 ¼ 41.2%, Pfor heterogeneity ¼ 0.164), respectively, for subgroup analysis stratified by study design (Fig. 3).
298
Table 1 Characteristics of included studies on fruit and vegetable intake and depression risk Study design
Country
Year
Age range or mean age
Sex
Allgower et al. [17]
Cross-sectional study Cross-sectional study Cross-sectional study Cross-sectional study
16 countries in Europe Finland
2001 2005
Hong Kong
2006
Chengdu, Hangzhou, Shenyang, Wuhan, Harbin, Kunming, Qingdao Spain
2007
21.6 21.6 44.04 44.04 65 65 20.4
F M FþM FþM FþM FþM FþM
3438 2091 2011 2011 3394 3394 2541
2009
37.18 37.18
FþM FþM
10094 10094
Malaysia
2011
68.56–70.44
FþM
71
12 12 55.45 55.45 53 53 50–79 50–79
FþM FþM F F FþM FþM F F
125428 125428 6271 5117 2630 2630 69954 69954
Hintikka et al. [15] Woo et al. [13] Liu et al. [11]
Sanchez-Villegas et al. [10]
Cohort study
Shahar et al. [18]
Canada
2013
Mihrshahi et al. [9]
Cross-sectional study Cross-sectional study Cohort study
Australia
2014
Chi et al. [16]
Cohort study
Taiwan
2015
Gangwisch et al. [12]
Cohort study
Columbia
2015
McMartin et al. [14]
Sample
RR (95% CI) 0.81 0.85 0.92 0.95 0.71 0.63 0.69
(0.66, (0.62, (0.79, (0.78, (0.48, (0.44, (0.57,
1.01) 1.17) 1.07) 1.17) 1.05) 0.92) 0.84)
for for for for for for for
fruit fruit fruit vegetable fruit vegetable fruit
Method
Depression method
Interview
13-item short BDI 5
FFQ
21-item BDI 15
7-d food frequency questionnaire FFQ
GDS 8
0.61 (0.45, 0.82) for fruit 0.93 (0.69, 1.24) for vegetable
Validated 136-item food frequency
0.3 (0.1, 0.94) for vegetable
1-d food weighing and 24-h diet recall Dietary history method
0.97 0.91 0.82 0.83 0.82 0.79 0.88 0.88
(0.87, 1.08) for fruit (0.83, 1.01) for vegetable (0.7, 0.96) for fruit (0.62, 1.1) for vegetable (0.64, 1.07) for fruit (0.49, 1.27) for vegetable (0.79, 0.99) for fruit (0.79, 0.99) for vegetable
20-item CES-D
Self-reported physician diagnosis of depression or use of regular antidepressant medication or DSM-IV GDS 5
FFQ
CIDI-SF 5 or self-reported physician diagnosis of depression CES-D 10
FFQ
CES-D 10
145-item FFQ
Burnam 8-item scale
BDI, Beck Depression Inventory; BMI, body mass index; CES-D, Center for Epidemiologic Studies Depression Rating Scale; CI, confidence interval; CIDI-SF, Composite International Diagnostic Interview-Short form; DSM, Diagnostic and Statistical Manual of Mental Disorders; FFQ, Food Frequency Questionnaire; GDS, Geriatric Depression Scale; RR, relative risk.
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Author [Ref.]
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299
Fig. 2. Meta-analysis of the association between fruit intake and depression risk. The size of gray box is positively proportional to the weight assigned to each study, which is inversely proportional to the standard error of the relative risks (RRs), and horizontal lines represent the 95% confidence intervals (95% CI).
Vegetable intake and the risk of depression For vegetable intake, four cohort studies [9,10,12,16] and four cross-sectional studies [13–15,18] involving 218 699 participants were included. Among these studies, three were conducted in Asia [13,16,18], two in Europe [10,15], one in Oceania [9], one in North America [14], and one in South America [12]. With regard to the depression diagnostic criteria, six studies used the scales or questionnaires [9,12,13,15,16,18], and two were ascertained by interview or self-reported physician diagnosis or use of regular antidepressant medication [10,14]. The major confounding factors adjusted in studies included age, sex, education, body mass index, and physical activity. Among the eight studies, three reported that high vegetable intake could decrease the risk of depression [12,13,18], whereas the other five indicated no significant association [9,10,14–16]. The pooled RR (95% CI) of depression for the highest versus lowest category of vegetable intake was 0.89 (0.83, 0.94; Pfor significance < 0.01, FEM, I2 ¼ 14.1%, Pfor heterogeneity ¼ 0.319; Fig. 4). The pooled RRs for cross-sectional and cohort studies were 0.83 (0.68, 1.02; Pfor significance ¼ 0.078, REM, I2 ¼ 60.4%, Pfor heterogeneity ¼ 0.056) and 0.88 (0.79, 0.96; Pfor significance ¼ 0.007, FEM, I2 ¼ 0.0%, Pfor heterogeneity ¼ 0.923), respectively, for subgroup analysis stratified by study design. Sources of heterogeneity and sensitive analysis As shown in Figure 2, moderate heterogeneity (I2 ¼ 48.2%, Pfor heterogeneity ¼ 0.043) was found in the analysis of fruit intake and depression. Therefore, univariate meta-regression was performed with the covariates of publication year (P ¼ 0.513), continent (P ¼ 0.089), study design (P ¼ 0.610), status for physical activity adjustment (P ¼ 0.134), and depression ascertainment (P ¼ 0.751) to investigate potential sources of the heterogeneity. None of these covariates had an excessive
influence on the pooled effects (P > 0.05). For the leave-one-out sensitivity analysis, one study [14] was found to contribute to the between-study heterogeneity. After excluding this study, the heterogeneity (I2 ¼ 27.5%, P ¼ 0.200) was reduced and the pooled RR was 0.83 (0.78, 0.88).
Influence analysis and publication bias Influence analysis showed that no individual study had an excessive influence on the pooled association of fruit and vegetable intake with the risk of depression. The visual inspection of the funnel plot (Fig. 5) and Egger’s test showed no evidence of publication bias for the analysis of vegetable intake with depression (P ¼ 0.053). For fruit intake, publication bias was found in both the Egger’s test (P ¼ 0.022) and the visual inspection of the funnel plot. However, after excluding one study [14], the publication bias was not evident with the Egger’s test (P ¼ 0.078).
Discussion To our knowledge, this is the first meta-analysis to explore the relationship between fruit and vegetable intake and depression risk. A total of 227 852 participants for fruit intake and 218 699 participants for vegetable intake were included in this metaanalysis. Findings from the meta-analysis indicated that both fruit intake and vegetable intake were significantly associated with the decreased risk of depression. Subgroup analysis was also conducted by study design. The significantly inverse association was observed in both cross-sectional and cohort studies for fruit intake and depression risk. For vegetable intake, the significantly inverse association was also found in the cohort studies.
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Fig. 3. Forest plot of the relative risks (RRs) with corresponding 95% confidence intervals (95% CI) of studies on fruit intake and depression for cross-sectional and cohort studies. The size of gray box is positively proportional to the weight assigned to each study, which is inversely proportional to the standard error of the RRs, and horizontal lines represent the 95% CIs.
The exact biological mechanisms underlying fruit and vegetable intake and depression risk are still not fully understood. First, various minerals and vitamins, such as magnesium, zinc, selenium, and vitamin B12, are present in fruits and vegetables. Some of them were found to exert influence on the mechanisms of depression. For instance, magnesium intake could reduce plasma concentrations of C-reactive protein, which is a marker of low-grade inflammation, and depression was found to be related to chronic inflammation [14]. Vitamin B12 affects the biochemical processes in the central nervous system. Vitamin B12 deficiency could lead to hyperhomocysteinemia by activation of Nmethyl-D-aspartate receptors, oxidative stress, and lesions in vascular endothelium, which could result in neurotoxicity and then lead to the depression incident [28]. Zinc deficiency induces neurologic and somatic symptoms as well as psychopathological symptoms that are connected with depressive disorder [29,30]. In addition, antioxidants such as vitamin C, vitamin E, and folic acid, which play an important role in the endothelial cell signaling cascades, could dampen the detrimental effects of oxidative stress on mental health [31,32]. As a good source of antioxidants, fruit and vegetable intake might be beneficial to protect against depression. Between-study heterogeneity occurs frequently in metaanalysis [20], and it is essential to explore the potential sources of between-study heterogeneity. In this meta-analysis, moderate heterogeneity was found in the analysis between fruit intake and depression risk. An indeterminate number of characteristics that
varied among the studies could be the sources, such as publication year, continent, study design, status for physical activity adjustment, depression ascertainment, and other covariates. Thus, meta-regression for fruit intake analysis was performed to explore the potentially important causes for between-study heterogeneity. Meta-regression analysis did not find any of the above-mentioned covariates as the important contributors to the between-study heterogeneity. To further explore the potential sources of between-study heterogeneity, the leave-one-out sensitivity analysis was carried out. After excluding one study that had a strong effect on the heterogeneity, the heterogeneity decreased to 27.5% and no publication bias was found in the analysis between fruit intake and depression risk. What’s more, the results still remained significant after reducing the heterogeneity in the analysis of fruit intake and depression, strongly identified the stability of results. The study has several strengths. First, a large number of participants were included in this study, allowing a much greater possibility of achieving reasonable conclusions. Second, an inverse association was found in cohort studies, indicating a potential causal relationship between fruit and vegetable intake and depression. Third, RRs with the most adjusted covariates were extracted, which could reduce the confounding. Fourth, after excluding one study, the heterogeneity was decreased, and the summary result of sensitive analysis did not change substantially. However, this meta-analysis was limited in some aspects as well. First, confounders adjusted in each study were inconsistent.
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301
Fig. 4. Meta-analysis of the association between vegetable intake and depression risk. The size of gray box is positively proportional to the weight assigned to each study, which is inversely proportional to the standard error of the relative risks (RRs), and horizontal lines represent the 95% confidence intervals (95% CI).
For example, body mass index and physical activity were adjusted in some studies, whereas not adjusted in other studies. Second, publication bias was observed in the analysis of fruit intake and depression. However, after removing one study that had a strong effect on the heterogeneity, the bias was not evident anymore, and the overall summary RR did not substantially change, suggesting that the result was stable. Third, the diagnostic criteria of depression were inconsistent. Different scales, including Beck Depression Inventory, Geriatric Depression Scale, and Center for Epidemiologic Studies Depression Rating Scale, were used in some studies, and depression was ascertained by physician diagnosis or beginning use of regular antidepressant medication in the others. Fourth, diet assessment methods varied among the studies and dose-response relationship could not
Fig. 5. Funnel plot for the analysis of vegetable intake and depression risk.
be accessed because of the limited information in the included studies. In summary, the present meta-analyses indicated that fruit and vegetable intake was inversely associated with the risk of depression.
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Contents lists available at ScienceDirect
Nutrition journal homepage: www.nutritionjrnl.com
Review
Fruit and vegetable consumption and the risk of depression: A meta-analysis Xiaoqin Liu M.D. a, Ying Yan Ph.D. b, Fang Li M.D. a, Dongfeng Zhang M.D. a, * a b
Department of Epidemiology and Health Statistics, The Medical College of Qingdao University, Qingdao, Shandong, People’s Republic of China Department of Teaching Research, The Medical College of Qingdao University, Qingdao, Shandong, People’s Republic of China
a r t i c l e i n f o
a b s t r a c t
Article history: Received 13 August 2015 Accepted 13 September 2015
Objective: Epidemiologic investigations evaluating the association of fruit and vegetable consumption with depression risk have yielded controversial results. Therefore, a meta-analysis was carried out to qualitatively summarize the evidence regarding association of fruit and vegetable intake with risk of depression in the general population. Methods: PubMed, Embase, and Web of Knowledge were searched for relevant articles published up to June 2015. To evaluate the association of fruit and vegetable intake with depression risk, combined relative risks were calculated with the fixed or random effects model. Meta-regression was conducted to explore potential sources of heterogeneity. Publication bias was estimated by the Egger’s test and the funnel plot. Results: Ten studies involving 227 852 participants for fruit intake and eight studies involving 218 699 participants for vegetable intake were finally included in this study. The combined relative risk (95% confidence interval) of depression for the highest versus lowest category of fruit and vegetable intake was 0.86 (0.81, 0.91; P < 0.01) and 0.89 (0.83, 0.94; P < 0.01), respectively. In subgroup analyses stratified by study design, the inverse association of fruit (0.83 [0.77, 0.91; P ¼ 0.006]) and vegetable (0.88 [0.79, 0.96; P ¼ 0.007]) intake with risk of depression was also observed in the cohort study. Conclusions: This meta-analysis indicated that fruit and vegetable consumption might be inversely associated with the risk of depression, respectively. Crown Copyright Ó 2016 Published by Elsevier Inc. All rights reserved.
Keywords: Fruit Vegetable Depression Meta-analysis
Introduction Depression is a common mental health disorder On a worldwide scale, about 400 million people suffer from depression [1]. According to the report of World Health Organization, depression accounts for 4.3% of the global burden of disease alone and is one of the largest single causes of disability worldwide [2]. Although the etiology of depression has not been fully explained, the dysfunction of noradrenergic and dopaminergic neurotransmission, disturbance of cellular plasticity, including reduction of neurogenesis, chronic inflammation, and higher oxidative stress may be related to pathogenesis of depression [3–5]. Considering the serious consequences of * Corresponding author. Tel.: þ8653282991712; fax: þ8653283801449. E-mail address: [email protected] (D. Zhang). http://dx.doi.org/10.1016/j.nut.2015.09.009 0899-9007/Crown Copyright Ó 2016 Published by Elsevier Inc. All rights reserved.
depression, it is especially and extremely important to identify the modifiable risk factors and develop prevention and control strategy. Some lifestyle behaviors have been reported to increase the risk of depression, such as sedentary behavior [6], long-term stress [7], and short or long hours of sleep [8]. In recent years, the association between diet and depression has also drawn much attention. Among the dietary factors, consumption of fruits and vegetables, which are rich in antioxidants and antiinflammatory components, was hypothesized to play an important role in depression development [9]. Several epidemiology studies have been carried out to investigate the role of fruit and vegetable intake in the development of depression, but the results are inconsistent. For fruit intake, although an inverse association with the risk of depression was found in some studies [9–12], the association was not observed in other studies [13–17]. For vegetable intake, though an inverse association was reported
X. Liu et al. / Nutrition 32 (2016) 296–302
in three studies [12,13,18], no association was found in the others [9,10,14–16]. Therefore, a meta-analysis was systematically performed to evaluate the association of fruit and vegetable consumption with the risk of depression. Materials and methods Literature search strategy A literature search was performed on the databases of PubMed, Embase, and Web of Knowledge for relevant articles published up to June 2015, using the following search terms: “depression,” “depressive disorder,” “depressive symptoms,” “fruit,” “vegetable,” and “diet” without restrictions. Moreover, the references of related reviews and original articles were also reviewed. The detailed steps of the literature search are shown in Figure 1. Inclusion criteria The inclusion criteria were as follows: 1) observational study published as an original article; 2) the exposure variable of interest was fruit or vegetable consumption; 3) the outcome of interest was depression; 4) relative risks (RRs) or odds ratio estimates (all results are presented with RRs in this study) with their 95% confidence intervals (95% CIs) were available. Depression was determined by self-report based on doctor’s diagnosis, regular use of antidepressant drugs, or depression rating scales. Studies on the postpartum depression and depression in pregnancy were not included in this meta-analysis. If data were duplicated in more than one study, the latest one or the one with the largest number of samples was included. Two investigators searched articles and reviewed all retrieved studies independently. If the two investigators could not reach a consensus about the eligibility of an article, it was solved through discussion with a third investigator. Data extraction Data extracted from each study were as follows: publication year, the first author’s name, country where the study was performed, follow-up years, study design, sample size, mean age or age range at baseline years, fruit and vegetable consumption assessment, determination method of depression, RRs with corresponding 95% CIs for the highest versus lowest categories of fruit and vegetable intake, and adjustment of covariates in the analysis. The RRs adjusted with the most confounders in the original studies were extracted.
297
Statistical analyses Pooled measure was calculated as the inverse-variance weighted mean of the logarithm of RR (95% CI) of depression for the highest versus lowest category of fruit and vegetable intake, respectively. The I2 [19] was used to assess heterogeneity among studies. If I2 50% [20], the random effect model (REM) was adopted as the pooling method; otherwise (I2 < 50%), the fixed effect model (FEM) was employed. Meta-regression was performed to access the potentially important covariates (including publication year, continent, study design, status for physical activity adjustment, and ascertainment method of depression) that might exert substantial impacts on between-study heterogeneity [21]. To assess whether the results could have been affected distinctly by a single study, an influence analysis was carried out with one study removed at a time [22]. The leave-one-out sensitive analysis was conducted to evaluate the key studies that have remarkable impact on the between-study heterogeneity. Publication bias was evaluated with the visual inspection of funnel plot and Egger regression asymmetry test [23]. Subgroup analysis was performed by study design (crosssectional or cohort study). All statistical analyses were conducted using Stata V.12.0 (Stata Corp., College Station, TX, USA). A two-tailed P < 0.05 was considered statistically significant.
Results Literature search and study characteristics The flowchart for study inclusion is shown in Figure 1, and 4950 articles from PubMed, 2544 articles from Embase, and 5484 articles from Web of Knowledge were identified by the search strategy. After excluding duplicates and reviewing the tiles or abstracts, 104 possible related articles concerning fruit and vegetable intake and depression risk were identified. Among these articles, 4 were removed because of duplicate participants [24–27], 62 were excluded because RR or 95% CI was not provided, and 28 were ruled out because the study subjects were the patients of postpartum depression or depression in pregnancy. Overall, 10 articles involving 4 cohort studies and 7 cross-sectional studies were included in this meta-analysis. Table 1 displays the baseline characteristics of the studies.
Quantitative synthesis
Fig. 1. Flowchart of the selection of studies included in the meta-analysis.
Fruit intake and the risk of depression For fruit intake, four cohort studies from four articles [9,10,12, 16] and six cross-sectional studies from five articles [11,13–15,17] involving 227 852 participants were included. Among these studies, three were conducted in Asia [11,13,16], four in Europe [10,15,17], one in Oceania [9], one in North America [14], and one in South America [12]. With regard to the depression diagnostic criteria, eight studies used the scales or questionnaires [9,11–13, 15–17], and two studies were ascertained by interview or self-reported physician diagnosis or use of regular antidepressant medication [10,14]. The major adjusted confounding factors included age, sex, education, body mass index, marital status, smoking status, and physical activity. Among the 10 studies, 4 reported that high fruit intake could decrease the risk of depression [9–12], whereas the other 6 indicated no significant association [13–17]. The pooled RR (95% CI) of depression for the highest versus lowest category of fruit intake was 0.86 (0.81, 0.91; Pfor significance < 0.01, FEM, I2 ¼ 48.2%, Pfor heterogeneity ¼ 0.043; Fig. 2). The pooled RRs for cross-sectional and cohort studies were 0.84 (0.75, 0.95; Pfor significance ¼ 0.006, REM, I2 ¼ 55.7%, Pfor heterogeneity ¼ 0.046) and 0.83 (0.77, 0.91; Pfor significance ¼ 0.001, FEM, I2 ¼ 41.2%, Pfor heterogeneity ¼ 0.164), respectively, for subgroup analysis stratified by study design (Fig. 3).
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Table 1 Characteristics of included studies on fruit and vegetable intake and depression risk Study design
Country
Year
Age range or mean age
Sex
Allgower et al. [17]
Cross-sectional study Cross-sectional study Cross-sectional study Cross-sectional study
16 countries in Europe Finland
2001 2005
Hong Kong
2006
Chengdu, Hangzhou, Shenyang, Wuhan, Harbin, Kunming, Qingdao Spain
2007
21.6 21.6 44.04 44.04 65 65 20.4
F M FþM FþM FþM FþM FþM
3438 2091 2011 2011 3394 3394 2541
2009
37.18 37.18
FþM FþM
10094 10094
Malaysia
2011
68.56–70.44
FþM
71
12 12 55.45 55.45 53 53 50–79 50–79
FþM FþM F F FþM FþM F F
125428 125428 6271 5117 2630 2630 69954 69954
Hintikka et al. [15] Woo et al. [13] Liu et al. [11]
Sanchez-Villegas et al. [10]
Cohort study
Shahar et al. [18]
Canada
2013
Mihrshahi et al. [9]
Cross-sectional study Cross-sectional study Cohort study
Australia
2014
Chi et al. [16]
Cohort study
Taiwan
2015
Gangwisch et al. [12]
Cohort study
Columbia
2015
McMartin et al. [14]
Sample
RR (95% CI) 0.81 0.85 0.92 0.95 0.71 0.63 0.69
(0.66, (0.62, (0.79, (0.78, (0.48, (0.44, (0.57,
1.01) 1.17) 1.07) 1.17) 1.05) 0.92) 0.84)
for for for for for for for
fruit fruit fruit vegetable fruit vegetable fruit
Method
Depression method
Interview
13-item short BDI 5
FFQ
21-item BDI 15
7-d food frequency questionnaire FFQ
GDS 8
0.61 (0.45, 0.82) for fruit 0.93 (0.69, 1.24) for vegetable
Validated 136-item food frequency
0.3 (0.1, 0.94) for vegetable
1-d food weighing and 24-h diet recall Dietary history method
0.97 0.91 0.82 0.83 0.82 0.79 0.88 0.88
(0.87, 1.08) for fruit (0.83, 1.01) for vegetable (0.7, 0.96) for fruit (0.62, 1.1) for vegetable (0.64, 1.07) for fruit (0.49, 1.27) for vegetable (0.79, 0.99) for fruit (0.79, 0.99) for vegetable
20-item CES-D
Self-reported physician diagnosis of depression or use of regular antidepressant medication or DSM-IV GDS 5
FFQ
CIDI-SF 5 or self-reported physician diagnosis of depression CES-D 10
FFQ
CES-D 10
145-item FFQ
Burnam 8-item scale
BDI, Beck Depression Inventory; BMI, body mass index; CES-D, Center for Epidemiologic Studies Depression Rating Scale; CI, confidence interval; CIDI-SF, Composite International Diagnostic Interview-Short form; DSM, Diagnostic and Statistical Manual of Mental Disorders; FFQ, Food Frequency Questionnaire; GDS, Geriatric Depression Scale; RR, relative risk.
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Author [Ref.]
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Fig. 2. Meta-analysis of the association between fruit intake and depression risk. The size of gray box is positively proportional to the weight assigned to each study, which is inversely proportional to the standard error of the relative risks (RRs), and horizontal lines represent the 95% confidence intervals (95% CI).
Vegetable intake and the risk of depression For vegetable intake, four cohort studies [9,10,12,16] and four cross-sectional studies [13–15,18] involving 218 699 participants were included. Among these studies, three were conducted in Asia [13,16,18], two in Europe [10,15], one in Oceania [9], one in North America [14], and one in South America [12]. With regard to the depression diagnostic criteria, six studies used the scales or questionnaires [9,12,13,15,16,18], and two were ascertained by interview or self-reported physician diagnosis or use of regular antidepressant medication [10,14]. The major confounding factors adjusted in studies included age, sex, education, body mass index, and physical activity. Among the eight studies, three reported that high vegetable intake could decrease the risk of depression [12,13,18], whereas the other five indicated no significant association [9,10,14–16]. The pooled RR (95% CI) of depression for the highest versus lowest category of vegetable intake was 0.89 (0.83, 0.94; Pfor significance < 0.01, FEM, I2 ¼ 14.1%, Pfor heterogeneity ¼ 0.319; Fig. 4). The pooled RRs for cross-sectional and cohort studies were 0.83 (0.68, 1.02; Pfor significance ¼ 0.078, REM, I2 ¼ 60.4%, Pfor heterogeneity ¼ 0.056) and 0.88 (0.79, 0.96; Pfor significance ¼ 0.007, FEM, I2 ¼ 0.0%, Pfor heterogeneity ¼ 0.923), respectively, for subgroup analysis stratified by study design. Sources of heterogeneity and sensitive analysis As shown in Figure 2, moderate heterogeneity (I2 ¼ 48.2%, Pfor heterogeneity ¼ 0.043) was found in the analysis of fruit intake and depression. Therefore, univariate meta-regression was performed with the covariates of publication year (P ¼ 0.513), continent (P ¼ 0.089), study design (P ¼ 0.610), status for physical activity adjustment (P ¼ 0.134), and depression ascertainment (P ¼ 0.751) to investigate potential sources of the heterogeneity. None of these covariates had an excessive
influence on the pooled effects (P > 0.05). For the leave-one-out sensitivity analysis, one study [14] was found to contribute to the between-study heterogeneity. After excluding this study, the heterogeneity (I2 ¼ 27.5%, P ¼ 0.200) was reduced and the pooled RR was 0.83 (0.78, 0.88).
Influence analysis and publication bias Influence analysis showed that no individual study had an excessive influence on the pooled association of fruit and vegetable intake with the risk of depression. The visual inspection of the funnel plot (Fig. 5) and Egger’s test showed no evidence of publication bias for the analysis of vegetable intake with depression (P ¼ 0.053). For fruit intake, publication bias was found in both the Egger’s test (P ¼ 0.022) and the visual inspection of the funnel plot. However, after excluding one study [14], the publication bias was not evident with the Egger’s test (P ¼ 0.078).
Discussion To our knowledge, this is the first meta-analysis to explore the relationship between fruit and vegetable intake and depression risk. A total of 227 852 participants for fruit intake and 218 699 participants for vegetable intake were included in this metaanalysis. Findings from the meta-analysis indicated that both fruit intake and vegetable intake were significantly associated with the decreased risk of depression. Subgroup analysis was also conducted by study design. The significantly inverse association was observed in both cross-sectional and cohort studies for fruit intake and depression risk. For vegetable intake, the significantly inverse association was also found in the cohort studies.
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Fig. 3. Forest plot of the relative risks (RRs) with corresponding 95% confidence intervals (95% CI) of studies on fruit intake and depression for cross-sectional and cohort studies. The size of gray box is positively proportional to the weight assigned to each study, which is inversely proportional to the standard error of the RRs, and horizontal lines represent the 95% CIs.
The exact biological mechanisms underlying fruit and vegetable intake and depression risk are still not fully understood. First, various minerals and vitamins, such as magnesium, zinc, selenium, and vitamin B12, are present in fruits and vegetables. Some of them were found to exert influence on the mechanisms of depression. For instance, magnesium intake could reduce plasma concentrations of C-reactive protein, which is a marker of low-grade inflammation, and depression was found to be related to chronic inflammation [14]. Vitamin B12 affects the biochemical processes in the central nervous system. Vitamin B12 deficiency could lead to hyperhomocysteinemia by activation of Nmethyl-D-aspartate receptors, oxidative stress, and lesions in vascular endothelium, which could result in neurotoxicity and then lead to the depression incident [28]. Zinc deficiency induces neurologic and somatic symptoms as well as psychopathological symptoms that are connected with depressive disorder [29,30]. In addition, antioxidants such as vitamin C, vitamin E, and folic acid, which play an important role in the endothelial cell signaling cascades, could dampen the detrimental effects of oxidative stress on mental health [31,32]. As a good source of antioxidants, fruit and vegetable intake might be beneficial to protect against depression. Between-study heterogeneity occurs frequently in metaanalysis [20], and it is essential to explore the potential sources of between-study heterogeneity. In this meta-analysis, moderate heterogeneity was found in the analysis between fruit intake and depression risk. An indeterminate number of characteristics that
varied among the studies could be the sources, such as publication year, continent, study design, status for physical activity adjustment, depression ascertainment, and other covariates. Thus, meta-regression for fruit intake analysis was performed to explore the potentially important causes for between-study heterogeneity. Meta-regression analysis did not find any of the above-mentioned covariates as the important contributors to the between-study heterogeneity. To further explore the potential sources of between-study heterogeneity, the leave-one-out sensitivity analysis was carried out. After excluding one study that had a strong effect on the heterogeneity, the heterogeneity decreased to 27.5% and no publication bias was found in the analysis between fruit intake and depression risk. What’s more, the results still remained significant after reducing the heterogeneity in the analysis of fruit intake and depression, strongly identified the stability of results. The study has several strengths. First, a large number of participants were included in this study, allowing a much greater possibility of achieving reasonable conclusions. Second, an inverse association was found in cohort studies, indicating a potential causal relationship between fruit and vegetable intake and depression. Third, RRs with the most adjusted covariates were extracted, which could reduce the confounding. Fourth, after excluding one study, the heterogeneity was decreased, and the summary result of sensitive analysis did not change substantially. However, this meta-analysis was limited in some aspects as well. First, confounders adjusted in each study were inconsistent.
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Fig. 4. Meta-analysis of the association between vegetable intake and depression risk. The size of gray box is positively proportional to the weight assigned to each study, which is inversely proportional to the standard error of the relative risks (RRs), and horizontal lines represent the 95% confidence intervals (95% CI).
For example, body mass index and physical activity were adjusted in some studies, whereas not adjusted in other studies. Second, publication bias was observed in the analysis of fruit intake and depression. However, after removing one study that had a strong effect on the heterogeneity, the bias was not evident anymore, and the overall summary RR did not substantially change, suggesting that the result was stable. Third, the diagnostic criteria of depression were inconsistent. Different scales, including Beck Depression Inventory, Geriatric Depression Scale, and Center for Epidemiologic Studies Depression Rating Scale, were used in some studies, and depression was ascertained by physician diagnosis or beginning use of regular antidepressant medication in the others. Fourth, diet assessment methods varied among the studies and dose-response relationship could not
Fig. 5. Funnel plot for the analysis of vegetable intake and depression risk.
be accessed because of the limited information in the included studies. In summary, the present meta-analyses indicated that fruit and vegetable intake was inversely associated with the risk of depression.
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