Research paper The association between banana consumption and the depressive symptoms T in Chinese Adults

Journal of Affective Disorders 264 (2020) 1–6

  

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generaladultpopulation: A cross-sectional study

Tong Jia, Xiaoyue Lia, Ge Menga,c,⁎, Yeqing Gua, Qing Zhangb, Li Liub, Hongmei Wua, Zhanxin Yaod, Shunming Zhanga, Yawen Wanga, Tingjing Zhanga, Xuena Wanga, Xingqi Caoa, Huiping Lia, Yunyun Liua, Xiaohe Wanga, Xing Wangb, Shaomei Sunb, Ming Zhoub, Qiyu Jiab, Kun Songb, Zhong Suna, Xiao-Hui Wue, Kaijun Niua,b,f,g

a Nutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin 300070, China
b Health Management Centre, Tianjin Medical University General Hospital, Tianjin, China
c Department of Toxicology and Sanitary Chemistry, School of Public Health, Tianjin Medical University, Tianjin, China d Tianjin Institute of Health and Environmental Medicine, Tianjin, China
e College of Pharmacy, Tianjin Medical University, Tianjin, China
f Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
g Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin, China

 

ARTICLE INFO

Keywords:

Depressive symptoms Banana consumption Cross-sectional study Males and females

ABSTRACT

Background: Banana contains many kinds of substances that are beneficial to depressive symptoms. However, there are no epidemiological researches directly to explore the association between banana consumption and depressive symptoms. This study aimed to investigate whether the banana consumption is related to depressive symptoms in a general adult population.

Methods: A cross-sectional study was performed in 24,673 adults in Tianjin. Banana consumption was evaluated via a validated food frequency questionnaire. Depressive symptoms were assessed by using Self-Rating Depression Scale (SDS). The association between banana consumption and depressive symptoms was analyzed by multiple logistic regression analysis.

Results: The prevalence of depressive symptoms was 16.1% in males and 18.4% in females (SDS ≥ 45), re- spectively. In males, comparing to the reference group (almost never), the multivariable adjusted odds ratios (ORs) (95% confidence intervals) of depressive symptoms across banana consumption were 0.86 (0.74, 0.99) for <1 time/week, 0.76 (0.66, 0.88) for 1–3 times/week and 0.97 (0.82, 1.16) for ≥4 times/week. By contrast, the multivariable adjusted ORs (95% confidence intervals) were 1.11 (0.94, 1.32) for <1 time/week, 0.99 (0.85, 1.16) for 1–3 times/week and 1.22 (1.02, 1.46) for ≥4 times/week in females. Similar association was observed when other cut-offs (SDS ≥ 48 and 50) were used to define depressive symptoms.

Limitation: This is a cross-sectional study, causality remains unknown.
Conclusion: Findings from this study suggested a negative association between moderate banana consumption and depressive symptoms in males. In females, high banana consumption is positively related to depressive symptoms.

  

1. Introduction

Depression normally accompanies with the feeling of worthlessness, changing in appetite and depressed moods (Zhao et al., 2017), which might affect people’s healthy condition. The World Health Organization (WHO) estimated that depression affects about 350 million people around the world and reported depression as the major factor for the

global burden of diseases about 4.4% (Mello et al., 2014). Depression contributed to diabetes, heart diseases, and increased the total mor- tality (Akker et al., 2003; Asghar et al., 2007; Luo et al., 2018). How- ever, there are no effective therapies to cure depression. Therefore, more correlated studies for modifiable risk factors in daily lives to de- crease the prevalence of depression are indispensable.

Several epidemiology studies provided evidence that fruits and

⁎ Correspondence author at: Nutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, 22 Qixiangtai Road, Heping District, Tianjin 300070, China.

E-mail address: mengge@tijmu.edu.cn (G. Meng).

https://doi.org/10.1016/j.jad.2019.12.008

Received 15 September 2019; Received in revised form 1 December 2019; Accepted 4 December 2019

Available online 05 December 2019 0165-0327/ © 2019 Published by Elsevier B.V.

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Journal of Affective Disorders 264 (2020) 1–6

vegetables intake was protectively associated with depression (Baharzadeh et al., 2018; McMartin et al., 2013; Mihrshahi et al., 2015). In spite of this, the relationship between banana consumption and depressive symptoms is still unclear. The banana, as a delicious and healthy food, is a commonly eaten fruit with no seasonal growth re- strictions. It was reported that the consumption of banana in China ranked fifth in 2017. According to the United States Department of Agriculture (USDA) Food Composition Database, every 100 g of raw banana contains 74.91 g water, 89.00 g energy, 12.23 g sugar, 1.09 g protein and other nutrients, such as fiber. Bananas contain several minerals and vitamins that have been proved to be beneficial to nervous system function (Stefanska et al., 2014). For instance, magnesium (Mg) (Ryszewska-Pokrasniewicz et al., 2018), iron (Fe) (Sheikh et al., 2017), potassium (K) (Fullana et al., 2018), and vitamin B (Mikkelsen et al., 2016) have been shown to alleviate depressive symptoms. Accumulated evidence suggested that decreased in serotonin is a significant me- chanism of depression (Stockmeier et al., 1998). Animal experiments also demonstrated that serotonin had positive effects on depressive symptoms (Lanfumey et al., 2000). Although the serotonin in banana does not cross the blood-brain barrier (Young, 2007), banana contains tryptophan which is the sole precursor of both peripherally and cen- trally produced serotonin (Colle et al., 2019). Furthermore, one study showed that phyto-antioxidants in bananas’ fruit pulp and peel could relieve the symptoms of depression in mice when performing the forced swim test (FST) and tail suspension test (TST) (Samad et al., 2017). However, conversely, according to the data of USDA, every 100 g of raw banana contains 12.23 g sugar. Additional animal studies indicated that excessive sugar consumption could inhibit sugar from binding to dopamine and mu-opioid receptors in the brain, thereby restraining the activity of brain (Colantuoni et al., 2001). Sanchez-Villegas et al. found that the sugar increased the risk of depressive symptoms in 15,546 Spanish university graduates (Sanchez-Villegas et al., 2018). The study of Gangwisch et al. and Hu et al. also found that a progressively higher dietary GI and higher consumption of dietary added sugars were asso- ciated with increasing odds of incident depression (Gangwisch et al., 2015; Hu et al., 2019). In addition, there is an ecological study prove that there was a highly significant correlation between sugar con- sumption and the annual rate of depression (Westover and Marangell, 2002). Thus, it was hypothesized that banana consumption might both have positive and negative effects on the development of depressive symptoms.

However, to our knowledge, there are no explicit epidemiological studies specifically evaluating the association of banana consumption with depressive symptoms. Hence, the objective of the study was to assess the association between banana consumption and depressive symptoms in a large general adult population.

2. Methods

2.1. Study participants

The data of this cross-sectional study were collected from the Tianjin Chronic Low-grade System Inflammation and Health (TCLSIH) Cohort Study that was initiated in 2007. This study is a large pro- spective dynamic cohort that is focused on association between chronic low-grade inflammation and the health status of the population living in Tianjin of China (Yu et al., 2018b). In this study, we asked the par- ticipants to complete a questionnaire to evaluate their overall bodily status, mental health status, food intake, in addition to other related questions. This cohort is included nearly all occupations and retired persons over the age of 18 that living in residential communities of Tianjin. Therefore, this sample is comparatively representative and comprehensive. In this study, a total of 28,171 participants were sam- pled. Moreover, the participants who not complete the questionnaire (n = 2104), and subjects with cardiovascular disease (n = 1198) or cancer (n = 196) were excluded. Finally, 24,673 subjects were

comprised, including 13,327 males (mean ± standard deviation age: 42.3 ± 12.0 years) and 11,346 females (mean ± standard deviation age: 40.6 ± 11.7 years).

Study protocols and procedures were approved by the Institutional Review Board of Tianjin Medical University. At the same time, written informed consent was obtained from all participants.

2.2. Evaluation of depressive symptoms

Depressive symptoms were evaluated via the Chinese version of the Self-Rating Depression Scale (SDS), which has been confirmed as a re- liable and valid measure in Chinese population (Lee et al., 1994). In the SDS, there are 10 symptom-positive and 10 symptom-negative items used to assess depressive symptoms. Summary scores range from 20 to 80, and higher score indicated that depressive symptoms were serious. In our present study, three cut-off points (45, 48 and 50) were used to define depressive symptoms.

2.3. Evaluation of dietary intake

The participants were instructed to finish a food frequency ques- tionnaire (FFQ) including 100 items (the original version of FFQ in- cluded 81 items (Jia et al., 2015)) with specified serving sizes (Yu et al., 2018a). This FFQ included seven frequencies of foods (ranging from hardly ever to twice or more per day) and the eight frequencies of drinks (ranging from hardly ever to twice or more per day). The fre- quency of banana consumption was asked as follows: please recall the mean frequency of banana consumption in the last month and select from the seven frequency categories (almost never, <1 time/week, 1 time/week, 2–3 times/week, 4–6 times/week, 1 time/day, and ≥2 times/day). Finally, we summarized the categories of banana con- sumption frequency in the following way: almost never, <1 time/week, 1–3 times/week, and ≥4 times/week. The reproducibility and validity of the FFQ were assessed among 150 participants who were drawn randomly from the cohort and the detail information was described elsewhere (Gu et al., 2019). The mean daily nutrients intake and total energy intake (kcal/day) were calculated by a computer program based on the Chinese Food Consumption Table to analyze the questionnaire.

Factor analysis was used to generate major dietary patterns and factor loadings for each of food item (gram) after removing the banana. Varimax rotation was used to enhance interpretability. By combining criteria of the eigenvalue, scree plot test and the interpretability, three factors were determined. Food with factor loading greater than |0.30| is the main factor affecting the dietary patterns and represents the char- acter of each pattern. Factors were named descriptively according to the food items showing high loading (absolute value) with respect to each dietary pattern as follows: “Sweets pattern,” “Healthy pattern,” and “Animal foods pattern” (Zhang et al., 2019). Similar dietary pat- terns have been observed in our previous studies.

2.4. Evaluation of other variables

All participants received body’s measures with standardized phy- sical examinations. Height and body weight were recorded using a standard equipment. Body mass index (BMI) was calculated using weight in kilograms (kg) divided by square of the height (m2). Waist circumference was measured at the navel level and participants were asked to stand and breathe normally.

Sociodemographic variables including, age, education, occupation, household income and social connection (married and frequency of visiting friends) were also collected. We also evaluated the grade of a close relationship with their relatives. For lifestyle and habits, we also evaluate the situation of smoking and drinking. And the participants were asked to answer some questions with “yes” or “no”, including the detailed personal and family history of physical illness. Physical activity (PA) in recent was evaluated by using the International Physical

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Journal of Affective Disorders 264 (2020) 1–6

Activity Questionnaire (Craig et al., 2003). Total PA was estimated as metabolic equivalent hours/week (MET × hours/week).

Blood samples were collected in siliconized vacuum plastic tubes for analyzing fasting blood glucose (FBG) and lipid. FBG was measured by the method of glucose oxidase. Triglycerides (TG) and total cholesterol (TC) were measured by using the method of enzymatic colorimetric. Low-density lipoprotein cholesterol (LDL) was measured by using the method of polyvinyl sulfuric acid precipitation, and the high-density lipoprotein cholesterol (HDL) was measured by the method of chemical precipitation using appropriate kits on a Cobas 8000 analyzer (Roche, Mannheim, Germany). Blood pressure (BP) was measured twice from the upper left arm using a device of TM-2655P (A&D company, Ltd., Tokyo, Japan) and calculated the mean of the two data. The partici- pants were considered to have hypertension if the participants had systolic BP ≥ 140 mmHg and/or diastolic BP ≥ 90 mmHg or hy- pertension diagnosed by physician or using medication of anti- hypertension. Diabetes was defined as FBG level ≥7 mmol/L or diag- nosed diabetes or current use of antidiabetic medication. The participants were considered have hyperlipidemia if the participants had a TC level ≥ 5.17 mmol/L or TG level ≥ 1.7 mmol/L or LDL-C level ≥ 3.37 mmol/L or having history of hyperlipidemia or use anti- hyperlipidemic medication. And the situation of medication for the past six months was obtained by questionnaire.

2.5. Statistical analysis

The descriptive data of study participants were described by using the geometric means (with 95% confidence interval, CI) or percentages where appropriate. For further analysis, the frequency of banana con- sumption was used as independent variable, whereas the depressive symptoms as dependent variable. Multivariate logistic regression models were used to evaluate the association between categories of bananas consumption and depressive symptoms by sex (P interaction for sex <0.0001). The odds ratios (ORs) and the corresponding 95% CI were calculated using the almost never eat as the reference. Model 1 was adjusted total energy intake. Model 2 was adjusted for age, BMI and total energy intake. Model 3 was adjusted for age, BMI, smoking status, drinking status, education level, occupation, household income, total energy intake, PA, marital status, frequency of visiting friends, individual history of disease (including hypertension, hyperlipidemia, and diabetes), family history of disease (including cardiovascular dis- ease, hypertension, hyperlipidemia, and diabetes). Model 4 was further adjusted for “Sweets” dietary pattern score, “Healthy” dietary pattern score and “Animal foods” dietary pattern score. Model 5 was further adjusted for pineapple, kiwi fruit, tomatoes, and walnut intake. We included a covariate in the study if it changed the estimate of the main determinants by more than 10% or if the covariate predicted depressive symptoms (P < 0.05). Based on these criteria, these covariates were not included in the full model. Moreover, a multiple regression analysis was performed by using intake frequency multiply by serving size and in- vestigate whether there is a linear association between banana con- sumption and depressive symptoms in males and females. Two-sided P < 0.05 was considered as statistically significant. The statistical analyses were performed by SAS version 9.3 (SAS Institute Inc., Gary, NC, USA).

2. Result

Among 24,673 subjects, 54.0% (13,327 of 24,673) of the subjects were males and 46.0% (11,346 of 24,673) of subjects were females. The prevalence of depressive symptoms was 16.1% (2144 of 13,327) and 18.4% (2085 of 11,346) respectively for males and females when the cut-off point set as 45.

Age-adjusted characteristics of the participants according to de- pressive symptoms were presented in Table 1. In males, comparing to the subjects without depressive symptoms, the patients had lower level

of BMI (p < 0.01), were less likely to be employed as managers (p < 0.0001) and other occupation (p < 0.001). They had less physical activity, lower level of education, less household income, and fewer visiting friends (all pvalues < 0.0001). And the participants with de- pressive symptoms tended to intake less sweets (p = 0.0001), more healthy foods and animal foods (p < 0.0001). In addition, the partici- pants with depressive symptoms had a higher proportion of current- smoker and lower proportion non-smoker (p < 0.0001). In females, the patients had less physical activity, intake less total energy, more healthy foods, more animal foods, and less sweets (all p va- lues < 0.0001) than participants without depressive symptoms. They were more likely to be unmarried (p < 0.001), and tended to living alone (p < 0.01). Moreover, patients had lower level of education, less household income, fewer visiting friends (all p values < 0.0001), higher proportion of current-smoker and lower proportion of non- smoker (p = 0.001). Otherwise, no statistically significant differences were observed between groups.

The gender-specific and adjusted association between banana con- sumption and depressive symptom is shown in Table 2. In males, comparing to the reference group (almost never), the multivariable adjusted ORs (95% CIs) of depressive symptoms of banana consumption were 0.86 (95% CI: 0.74, 0.99) for <1 time/week, 0.76 (95% CI: 0.66, 0.88) for 1–3 times/week and 0.97 (95% CI: 0.82, 1.16) for ≥4 times/ week. In females, the multivariable adjusted ORs (95% CIs) were 1.11 (95% CI: 0.94, 1.32) for <1 time/week, 0.99 (95% CI: 0.85, 1.16) for 1–3times/week and 1.22 (95% CI: 1.02, 1.46) for ≥4 times/week. Si- milar association was observed when other cut-offs (SDS ≥ 48 and 50) were used to define depressive symptoms.

Moreover, to confirm the trend association between banana con- sumption and depressive symptoms, we performed a multiple regres- sion analysis by using banana intake frequency multiply by serving size. After adjustment for potential confounding factors, the multiple re- gression model still showed a sort of U-shape association not a linear association in males (P = 0.46), and banana consumption might have a negative effect on depressive symptoms after a certain threshold maybe reached in females (p = 0.52).

3. Discussion

This is the first study that assessed the association between banana consumption and depressive symptoms in a large adult population. Findings indicated that the association between banana consumption and depressive symptoms is different in males and females. The asso- ciations were not linear. In males, the moderate banana consumption was negatively associated with depressive symptoms and the associa- tion was not apparent in the group of highest banana consumption. By contrast, the positive association was only apparent in the group of highest banana consumption in females.

We adjusted for multiple potential confounding factors in this study. Firstly, in epidemiology, extraneous variation in nutrient intake re- sulting caused by variation in total energy intake that is unrelated to disease risk may weaken associations (Willett et al., 1997). Thus, ad- justment for total energy intake is usually appropriate in epidemiologic studies and we adjusted total energy intake in all models. The adjust- ment did not change the association between banana consumption and depressive symptoms in males and females. Age and BMI are related to depressive symptoms (Cameron et al., 2019; Uljarevic et al., 2019), thus we adjusted these two variables. The similar association still exists between banana consumption and depressive symptoms in both sexes. Secondly, because the sociodemographic factors, lifestyle factors, nu- tritional factors, and chronic diseases also have effects on depressive symptoms (Chireh et al., 2019; Lyu et al., 2019), we subsequently ad- justed for these relative potential factors (including smoking status, drinking status, education level, occupation, household income, total energy intake, physical activity, marital status, visiting friends, in- dividual and family history of diseases). However, adjustments for these

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Journal of Affective Disorders 264 (2020) 1–6

Table 1

Age-adjusted characteristics of the participants according to depressive symptoms (n = 24,673)a.

Characteristics

No. of subjects Age (years) BMI (kg/m2) WC (cm)

SBP (mmHg)
DBP (mmHg)
PA (MET × hour/week)
Total energy intake (kcal/day) “Sweets” dietary pattern score “Healthy” dietary pattern score “Animal foods” dietary pattern score Smoking status (%)

Current smoker Ex-smoker Non-smoker

Drinking status (%) Everyday Sometime Ex-drinker Non-drinker

Married (%)
Living alone
Education level (college or higher,%) Occupation (%)

Managers Professionals Other

Household income (≥10,000 Yuan,%) Visiting friends (%)
Individual history of disease (%)

Hypertension Hyperlipidemia Diabetes

Family history of disease (%) CVD

Depressive symptoms (males)

P valuec Depressive symptoms (females)

P valuec

0.57 0.18 0.94 0.46 0.87 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001

0.001 0.33 0.001

0.12 0.54 0.23 0.73 <0.001 <0.01 <0.0001

<0.0001 0.74 <0.0001 <0.0001 <0.0001

0.44 0.95 0.32

0.56 0.64 0.66 0.28

  

a b c

BMI, body mass index; CVD, cardiovascular disease; DBP, diastolic blood pressure; PA, physical activity; SBP, systolic blood pressure; WC, waist circumference. Continuous variable are expressed as least square geometric means (95% confidence intervals) (all such values).
Analysis of covariance or logistic regression analysis adjusted for age where appropriate.

Hypertension Hyperlipidemia Diabetes

No 11,183

40.6 (40.6, 40.6)b
25.6 (25.5, 25.7)
88.2 (88.0, 88.4)
123.4 (123.1, 123.7) 78.8 (78.6, 79.0)
12.1 (11.9, 12.5)
2097.8 (2087.9, 2107.6) 0.11 (0.09, 0.12)

−0.18 (−0.2, −0.16) 0.21 (0.19, 0.23)

36.3 9.75 54.0

8.73 71.9 9.46 9.87 87.7 9.52 69.9

45.5 20.3 34.2 39.3 57.2

31.0 56.4 4.45

29.0 49.9 0.36 25.4

Yes

2144
40.6 (40.5, 40.7)
25.4 (25.2, 25.5)
88.0 (87.57, 88.36) 123.2 (122.6, 123.9) 78.67 (78.22, 79.11) 8.74 (8.27, 9.25)
2079.7 (2057.6, 2102.2) 0.01 (−0.03, 0.06)
0.07 (0.03, 0.12)
0.59 (0.54, 0.63)

43.0 9.46 47.6

9.04 70.7 9.79 10.4 87.4 10.4 61.9

40.1 21.5 38.4 27.2 51.8

30.6 58.2 4.86

30.0 48.4 0.42 24.8

No

– 9261
0.86 39.0 (39.0, 39.1)
<0.01 22.8 (22.8, 22.9)
0.34 75.4 (75.3, 75.6)
0.54 114.9 (114.6, 115.2) 0.49 71.7 (71.5, 71.9) <0.0001 9.42 (9.17, 9.67)
0.15 1940.4 (1928.8, 1952.0) 0.0001 −0.09 (−0.11, −0.07) <0.0001 0.13 (0.12, 0.15) <0.0001 −0.37 (−0.39, −0.36)

<0.0001 1.31 0.72 0.72 <0.0001 98.0

0.52 0.65 0.21 40.1 0.64 9.36 0.41 49.9 0.81 85.4 0.25 6.89 <0.0001 66.3

<0.0001 42.5 0.23 13.0 <0.001 44.5 <0.0001 36.3 <0.0001 66.1

0.87 13.2 0.10 37.4 0.31 1.94

0.29 31.0 0.24 50.5 0.66 0.37 0.60 26.7

Yes

2085
39.0 (38.9, 39.1)
22.7 (22.6, 22.9)
75.4 (75.1, 75.8)
114.6 (114.1, 115.2) 71.7 (71.4, 72.1)
6.92 (6.55, 7.32)
1883.5 (1859.9, 1907.4) −0.18 (−0.22, −0.14) 0.28 (0.24, 0.32)
−0.06 (−0.09, −0.02)

2.32 0.93 96.8

0.96 39.4 10.2 49.5 82.4 8.60 59.0

37.0 12.7 50.3 25.9 56.5

13.6 37.6 1.58

31.5 51.0 0.43 25.6

factors did ‘not change this association in males and females. Thirdly, since the dietary patterns may affect the depressive symptoms (Sadeghi et al., 2019), we additional adjusted for three main dietary patterns (“Sweets” dietary pattern, “Healthy” dietary pattern and “Animal foods” dietary pattern). A similar association between banana consumption and depressive symptoms in males and females was still observed. Fi- nally, because pineapple, kiwi fruit, tomatoes, and walnut have a re- latively high serotonin concentration (Feldman and Lee, 1985), we additional adjusted these substances intake. After these adjustments, this association has not changed.

The present study suggested that the moderate banana consumption was inversely associated with depressive symptoms in males. Although the exact mechanisms have not been elucidated, serotonin might be the candidate for this positive association. Serotonin selectively enhanced excitatory synapses formed by the tempotoammonic pathway with CA1 pyramidal cells by activating serotonin receptors (Cai et al., 2013). Meanwhile, a prospective study also demonstrated that serotonin transporter (5-HTT) gene can attenuate the influence of negative life events on depressive symptoms in a representative birth cohort (Caspi et al., 2003). Serotonin in banana cannot cross the blood-brain barrier (Young, 2007), but the tryptophan in banana is the sole pre- cursor of both peripherally and centrally produced serotonin (Colle et al., 2019). Moreover, minerals and vitamin in banana, such as vi- tamin B and Mg, have also been shown to relieve depressive symptoms

(Mikkelsen et al., 2016; Stefanska et al., 2014). An animal experiment also suggested that phyto-antioxidants in banana can against the de- pressive symptoms (Samad et al., 2017). Hence, the beneficial asso- ciation between banana consumption and depressive symptoms is bio- logically plausible. Further elaborate information is needed to confirm the mechanisms involved in the association between them.

Interestingly, the present results revealed that the females are more likely to suffer from depressive symptoms when the bananas are taken more than 4 times/week, while this association disappeared in males. According to the USDA, the banana contains 12.23 g of sugar per 100 g. Over consumption of banana may cause sugar excess consumption that has been proven to be associated with depressive symptoms in Whitehall cohort study at age 35–55 years (Knuppel et al., 2017). Previous an ecological study has also corroborated that excessive sugar consumption was increased the annual rate of depression (Westover and Marangell, 2002). Moreover, a prospective cohort study suggested progressively higher consumption of dietary added sugars was also associated with increasing odds of incident depression (Gangwisch et al., 2015). Further studies will be required to clarify the exact mechanisms of banana consumption in depressive symptoms in females.

The following mechanisms related to the development of depressive symptoms might be explained by differences between the male and female sexes. Firstly, bananas contain a large amount of sugar, and an

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Journal of Affective Disorders 264 (2020) 1–6

Table 2

The association of banana consumption with depressive symptoms (n = 24,673)a.

Logistic regression models

No. of males
No. of depressive symptom (SDS ≥ 45)

Model 1 Model 2 Model 3 Model 4 Model 5

No. of females
No. of depressive symptom (SDS ≥ 45)

Model 1 Model 2 Model 3 Model 4 Model 5

Frequency of banana consumption

all most never

2299
418
1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1531
279
1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference) 1.00 (reference)

<1 time/week

3209
498
0.83 (0.72, 0.95)b 0.82 (0.71, 0.94) 0.86 (0.74, 1.00) 0.86 (0.74, 0.99) 0.86 (0.74, 0.99) 2430
457
1.05 (0.89, 1.24) 1.05 (0.89, 1.24) 1.09 (0.92, 1.29) 1.12 (0.94, 1.32) 1.11 (0.94, 1.32)

1–3 times/week 5628

807
0.75 (0.66, 0.85) 0.74 (0.65, 0.85) 0.80 (0.70, 0.91) 0.76 (0.66, 0.88) 0.76 (0.66, 0.88) 4954
840
0.95 (0.81, 1.10) 0.94 (0.81, 1.10) 0.97 (0.83, 1.13) 0.99 (0.85, 1.16) 0.99 (0.85, 1.16)

≥4 times/week 2191

421
1.06 (0.91, 1.24) 1.05 (0.90, 1.22) 1.13 (0.96, 1.32) 0.97 (0.82, 1.15) 0.97 (0.82, 1.16) 2431
509
1.26 (1.06, 1.49) 1.26 (1.06, 1.49) 1.27 (1.07, 1.51) 1.23 (1.03, 1.47) 1.22 (1.02, 1.46)

 

Model 1 was adjusted total energy intake.
Model 2 was adjusted for age, BMI and total energy intake.
Model 3 was adjusted for age, BMI, smoking status, drinking status, education level, occupation, household income, total energy intake, physical activity, marital status, visiting friends, individual history of disease (including hypertension, hyperlipidemia, and diabetes), family history of disease (including cardiovascular disease, hypertension, hyperlipidemia, and diabetes).
Model 4 was further adjusted for “Sweets” dietary pattern score, “Healthy” dietary pattern score and “Animal foods” dietary pattern score.
Model 5 was further adjusted for pineapple, kiwi fruit, tomatoes, walnut intake.

. a  SDS, self-rating depression scale; BMI, body mass index.

. b  Odds ratio (95% confidence interval) (all such values).

experiment in rats showed that ingestion of diets high in sugar de- creased serotonin metabolism more in female rats than male rats (Inam et al., 2016), which could explain the lower serotonin levels in females compared with males after a large number of bananas were consumed. Secondly, sudden estrogen changes and sustained estrogen deficit were shown to be associated with a higher risk of depressive symptoms in females (Douma et al., 2005). One study indicated that a downward trend in the total magnesium levels in relation to the rising estrogens (Grossi et al., 2017). Therefore, magnesium in banana might decrease the estrogen level after a lot of bananas intake in females. Thirdly, the finding of our study can strengthen our understanding re- garding the different lifestyle between females and males (Fiala and Brazdova, 2000). Females might follow the advice in popular media to consume more bananas when having low mood. The data from our study showed that a relatively large bananas are consumed by females (52.6%) compared with males (47.4%). Moreover, we performed a chi- square to confirm that there is a statistical difference between females and males in the highest banana consumption groups (P < 0.0001). Further studies are required to determine which mechanism contributes more to the difference between males and females.

The present study firstly assessed the association between banana consumption and depressive symptoms in a large-scale adult popula- tion. Moreover, we adjusted for many potential confounders, such as age, BMI, smoking status, drinking status, education level, occupation, household income, total energy intake, physical activity, marital status, visiting friends, individual and family history of diseases, three main dietary patterns and other four substances with a high serotonin con- centration. However, some limitations should be noted in the present study. Firstly, because this was a cross-sectional study, we could not conclude that more banana consumption increases or decreases the occurrence of depressive symptoms. A prospective study or trail should be taken to confirm the association between banana consumption and depressive symptoms in males and females. Secondly, although a lot of confounders were adjusted in this study, some potential residual con- founding factors are still inevitable. Therefore, we did ‘not have any evidence to directly confirm the association between banana con- sumption and depressive symptoms. Finally, depressive symptoms were evaluated by a self-reported questionnaire in this study rather than a

precise diagnostic criterion in clinical practice. However, a precise di- agnostic criterion is difficult to carry out in a large-scale adult popu- lation.

In conclusion, the associations between banana consumption and depressive symptoms were not linear in males and females. Findings from this study suggested a negative association between moderate banana consumption and depressive symptoms and the association was not apparent in the group of highest banana consumption in males. In females, only the group of highest banana consumption is positively related to depressive symptoms. Further prospective study with long term follow-up will be necessary to confirm these findings.

4. Conclusion

This study adds to the evidence that banana consumption might have effects on depressive symptoms, and the present study suggested that the association between banana consumption and depressive symptoms are different in males and females. Further large prospective epidemiologic studies and random control trails (RCT) to investigate the impact of banana consumption on mental health in Chinese popu- lation are needed in the future.

Data availability statement

Data described in the manuscript, code book, and analytic code will not be made available because public availability would comprise participant privacy. For data access, researchers can contact the Nutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, Tianjin, China

Declaration of Competing Interest

None.

Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.jad.2019.12.008.

5

T. Ji, et al.

Journal of Affective Disorders 264 (2020) 1–6

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