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Article

N-3 Fatty Acids in Seafood Influence the Association Between the Composite Dietary Antioxidant Index and Depression: A Community-Based Prospective Cohort Study

by
Junhwi Moon
1,2,†,
Minji Kim
1,2,† and
Yangha Kim
1,2,*
1
Department of Nutritional Science and Food Management, Ewha Womans University, Seoul 03670, Republic of Korea
2
Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul 03760, Republic of Korea
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Antioxidants 2024, 13(11), 1413; https://doi.org/10.3390/antiox13111413
Submission received: 12 September 2024 / Revised: 12 November 2024 / Accepted: 14 November 2024 / Published: 18 November 2024
Browse Figure
Figure 1
<p>A flowchart of the study population.</p> ">
Review Reports Versions Notes

Abstract

:
Accumulating evidence suggests that seafood and its components, such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), are associated with mental health. However, little is known regarding whether the status of n-3 polyunsaturated fatty acids (PUFAs) modify the effect of dietary antioxidants on depression. The main purpose of study is to investigate longitudinal associations between seafood consumption and depression among 2564 participants aged 40–69 years using data from the Korean Genome and Epidemiology Study. The composite dietary antioxidant index (CDAI) and dietary intake were measured by a validated 106-item food frequency questionnaire and depression was assessed using the Beck Depression Inventory (BDI). The Cox’s proportional hazard model was used to examine the risk of depression according to seafood consumption. During an 8-year follow-up period, 165 (11.9%) men and 224 (18.9%) women experienced depression. After adjustment for confounders, the risk of depression was inversely associated with seafood consumption, with a 42% lower risk (HR T5 vs. T1 = 0.58, 95% CI: 0.35–0.98, p = 0.040) only being found among women. In a group with a high n-3 PUFA intake, CDAI scores were negatively correlated with BDI scores (r = −0.146, p < 0.001) among women. Seafood consumption might lead to more favorable outcomes against depression if accompanied by an increased intake of foods that are rich in antioxidants.

1. Introduction

Depression is a common mental disorder that affects mood, behavior and overall health [1]. The global prevalence of depressive disorders was estimated to be around 3.44% in 2017, which increased sharply during the COVID-19 outbreak. The recent meta-analysis has suggested that the proportion of depression in the general population might be seven times higher over this period, accounting for 25% [2]. According to the National Mental Health Survey of Korea 2021, the lifetime prevalence of having any mental disorders among Korean adults was 27.8%, indicating that about one in four Korean adults experienced a psychiatric disorder during their lifetime [3]. Therefore, there is an increasing interest in how modifiable lifestyle factors, such as smoking, physical activity, alcohol consumption, and diet, may affect mental health [4,5].
A growing number of studies have investigated the association between seafood consumption and the risk of depression. A meta-analysis of 10 prospective cohort studies revealed that an increment of one serving/week of fish was associated with an 11% lower risk of depression [6]. In a prospective study of Japanese adult employees, increased intake of seaweed was associated with a decreased incidence of depressive symptoms at the 3-year follow-up [7]. Regarding dietary patterns, a meta-analysis of nine cross-sectional studies showed that greater adherence to the Mediterranean diet, characterized by a high intake of olive oil, plant products, fish and seafood, was associated with a 28% lower risk of depression [8]. However, no association was observed between fish consumption and depression in some cross-sectional studies [9,10,11].
N-3 polyunsaturated fatty acids (PUFAs), such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), are components of seafood that are considered to be beneficial for mental health [12]. Accumulated evidence from several studies has suggested the role of n-3 PUFA on depression through potential mechanisms involving neuroendocrine modulation and the regulation of inflammatory statuses [13].
The composite dietary antioxidant index (CDAI) is a reliable nutritional tool that assesses individual antioxidant intake profiles [14]. In the Shanghai Women’s Health Study, the Dietary Antioxidant Quality Score and CDAI are highly correlated and are inversely associated with inflammatory mediators such as interleukin-1β and tumor necrosis factor-alpha (TNF-α) [15]. Increased levels of these proinflammatory cytokines may contribute to the development of depression [13]. Taking into consideration the potential anti-inflammatory effects of n-3 PUFAs, it can be speculated that n-3 PUFA, in combination with various antioxidants, might lead to more favorable outcomes against depression. However, to our knowledge, few studies have addressed the related issues [16,17].
In the current study, we aimed to examine longitudinal associations between seafood consumption and depression using data from the Korean Genome and Epidemiology Study (KoGES), a large community-based cohort study. We also investigated whether n-3 PUFA status modifies the effect of dietary antioxidants on depression.

2. Materials and Methods

2.1. Study Population

The data used in this study were obtained from a community-based Ansan–Ansung cohort study, part of the KoGES, to identify risk factors for chronic disease among the general Korean population. Detailed information on the study has been described elsewhere [18]. Briefly, 10,030 Korean adults aged 40–69 years who lived in Ansan (urban) and Ansung (rural) were recruited at baseline between 2001 and 2002, and follow-up examinations were conducted biennially. The second follow-up examination provided information on the depression levels, so we used these data as the baseline. Data from the baseline (2005–2006) through the sixth examination (2013–2014) were used for the current study. Among the 7515 participants, we excluded participants aged 65 and over for the purpose of focusing on middle-aged Koreans (n = 1740). Participants who reported implausible total energy intakes (<500 kcal/day or >4000 kcal/day, n = 80), those who never participated in the follow-up examinations (n = 164), those with missing information on covariates (n = 16), and those who did not respond to the depression questionnaire at baseline (n = 2577) were excluded. Additionally, 374 participants with depression at baseline were excluded. Therefore, 2564 participants (1379 men and 1185 women) were included in the final analysis (Figure 1).

2.2. Ethical Approval

This study was conducted according to the guidelines laid down in the Declaration of Helsinki, and all procedures involving human subjects were approved by the Institutional Review Board of Ewha Womans University (No. 202208-0010-01). Written informed consent was obtained from all individuals who participated in the study.

2.3. Assessment of Depression

At baseline, the level of depression in participants was assessed using the Beck Depression Inventory (BDI) developed by Beck et al. [19]. The validity of the BDI has been reported elsewhere [20]. The BDI consists of 21 items, including cognitive, emotional, motivational, and physical symptoms [19,21]. Each item ranges from ‘strongly disagree’ (0) to ‘strongly agree’ (3) based on a 4-point Likert scale. The total BDI score is calculated by summing the scores of each subscale. A higher BDI score indicates a higher level of depression. Depression was defined as a total BDI score ≥16, in accordance with previous studies of the Korean population [22,23].

2.4. Assessment of Food Consumption and Nutrients Intake

Dietary data were collected using a 106-item semi-quantitative food frequency questionnaire (SQFFQ) developed for Korean adults. The validity and reproducibility of the SQFFQ have been described elsewhere [24]. The food items listed in the SQFFQ were categorized into 13 groups based on the previous study [25] (Supplementary Table S1).
Food consumption was assessed at baseline of the study, concerning the participant’s dietary intake over the past year. Participants were asked to provide their average food frequency (on a 9-point scale of ‘almost none’, ‘once a month’, ‘twice or three times a month’, ‘once or twice a week’, ‘twice or three times a week’, ‘five or six times a week’, ‘once a day’, ‘twice a day’, and ‘three times a day’) and the average portion size (on a 3-point scale of ‘0.5 times the reference’, ‘reference’, and ‘1.5–2.0 times the reference’) for each food item. The duration of the seasonal variety of fruit consumption was divided into 4 categories (on a 4-point scale of 3, 6, 9, and 12 months).
To estimate seafood consumption, which comprised fish, shellfish, and seaweed, we multiplied the reported intake frequency of each food item in the SQFFQ by the reported portion size. Participants were divided into 5 groups according to quintiles of seafood consumption. The 10th revision of the Korean food composition table (KFCT), updated every five years by the Rural Development Administration [26], was used to evaluate the daily intakes of n-3 PUFAs. Daily nutrient intakes and calories were calculated from the food intake measured by the SQFFQ using the computer-aided nutritional analysis program (CAN Pro), a nutrient database developed by the Korean Nutrition Society [27]. The participants were divided into 2 groups based on the median value of intakes regarding the effects of n-3 PUFAs status.

2.5. Assessment of Composite Dietary Antioxidant Index

The CDAI was calculated using a modified version developed by Wright et al. [28]. The CDAI was the sum of six dietary minerals and vitamins (manganese, selenium, zinc, vitamins A, C, and E), and the daily intakes were evaluated based on food consumption through the use of the KFCT. The calculation formula was as follows:
C D A I = ∑ i = 1 n = 6 I n d i v i d u a l   I n t a k e − M e a n S D

2.6. Data Collection

All participants were interviewed about their sociodemographic and lifestyle characteristics at baseline, including age, sex, alcohol consumption, smoking status, physical activity, monthly income, education level, marital status, and menopausal status. Anthropometric measurements were conducted by trained research staff. Body mass index (BMI) was calculated as body weight (kg) divided by the square of height (m2).

2.7. Statistical Analysis

The descriptive statistics are presented as the mean ± standard error for continuous variables and as numbers (percentages) for categorical variables. The generalized linear model was used to compare the differences in the means of baseline characteristics and to test for the linear trends across the quintiles of seafood consumption. A Chi-square test or Fisher’s exact test was used to determine the differences in the distributions of general characteristics of the study participants. Spearman correlations were used to assess the relationship between the CDAI and BDI scores. Because CDAI scores are not observed as normally distributed but rather with skewed distribution, they were transformed by using the natural log before analysis. Associations between seafood consumption and depression were estimated from hazard ratios (HRs) and 95% confidence intervals (CIs) by using Cox’s proportional hazard model. Person-years were calculated from the date they completed the baseline examination to the date of depression onset or the end of follow-up. For adjustment in the multivariable model, potential confounders from the previously published scientific literature were taken into account [9,29,30,31,32] with stepwise regression procedures, including age (continuous), BMI (continuous), alcohol consumption (nondrinker, former drinker, and current drinker), smoking status (nonsmoker, former smoker, and current smoker), physical activity(<30 min/day/≥30 min/day), monthly income (<200 million Korean won (KRW)/≥200 million KRW), education level (<college/≥college), marital status (married/other), menopausal status (premenopause/menopause, current hormone replacement therapy (HRT) use/menopause, past HRT use/menopause, non-HRT use/menopause, unknown HRT use), consumption of fruit, vegetables, and meat (quintile), and total energy intake (continuous). We additionally adjusted for the baseline BDI score (continuous) for men. All analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA). Statistical significance was considered at p < 0.05. Data were stratified according to sex, as previous research reported that sex influences the association between seafood consumption and depression [6,29].

3. Results

3.1. Baseline Characteristics

During a follow-up time of 8 years, 165 (11.9%) men and 224 (18.9%) women experienced depression. The baseline characteristics of participants according to quintiles of seafood consumption are described in Table 1. Among men, participants with higher seafood consumption had a lower baseline BDI score, had a higher mean BMI, had a higher proportion of current drinkers, were more physically active, and had higher levels of education (p < 0.05). In contrast, women showed no significant difference in BDI score among the groups. Among women, participants with higher seafood consumption were more likely to be younger, have a higher mean BMI, be more physically active, and have higher levels of monthly income and education (p < 0.05).

3.2. Dietary Intakes

Table 2 and Table 3 present food consumption (g/1000 kcal) and nutrient intake per 1000 kcal according to quintiles of seafood consumption. There was a positive association between seafood consumption and most of the food groups (all p < 0.05) in both men and women. However, as seafood consumption increased, the consumption of grains (p < 0.001) decreased in both men and women. In addition, as seafood consumption increased, the consumption of oils and sugars (p < 0.05) decreased among women.
Regarding nutrient intake, participants with higher seafood consumption showed a higher total energy intake (p < 0.001) in both men and women. In line with the above results, participants with higher seafood consumption showed higher intakes of most nutrients (all p < 0.05) for both sexes. In contrast, there was a negative association between seafood consumption and carbohydrate intake (p < 0.001) in both men and women.

3.3. Associations Between Seafood Consumption and the Risk of Depression

HRs with 95% CIs for the associations between seafood consumption and depression distributed by quintiles are presented in Table 4. After adjustment for potential confounders, the risk of depression was inversely associated with seafood consumption, with a 42% lower risk (HR T5 vs. T1 = 0.58, 95% CI: 0.35–0.98, p = 0.040) in the highest quintile of seafood consumption compared with the reference group among women. Seafood consumption was not significantly associated with the risk of depression among men.

3.4. Correlations Between CDAI and BDI Scores According to N-3 PUFA Status

The correlation between CDAI and BDI scores is shown in Table 5. In the group with a high n-3 PUFA intake, a significant inverse correlation was found between CDAI and BDI scores (r = −0.146, p < 0.001) among women. There was no correlation between CDAI and BDI scores among men.

4. Discussion

In this prospective cohort study of Korean middle-aged men and women, we examined seafood consumption in relation to risk of depression. Seafood consumption, which comprised fish, shellfish, and seaweed was inversely associated with risk of depression among women when comparing the highest and lowest quintiles after multivariable adjustments. Moreover, in the group with high n-3 PUFA intake, CDAI scores were negatively correlated with BDI scores among women.
In our study, socioeconomic status such as higher levels of education and income was associated with greater consumption of seafood. A systematic review of European countries revealed that the socioeconomic factors might influence dietary habits [33]. A study analyzing data of 5721 participants from the Korea National Health and Nutrition Examination Survey, reported that higher socioeconomic status was associated with the “modified” dietary pattern, which reflected good nutritional status [34]. A cross-sectional study delineating yearly trends in the daily consumption of seafood and investigating the socioeconomic factors influencing seafood consumption among elderly Koreans, showed that there was a significant correlation between seafood intake and educational level and family income [35]. Considering the possibility that socioeconomic factors might result in different dietary habits, thus affecting the risk of depression, we adjusted for these potential confounders.
Our findings showed that the risk of depression was inversely associated with seafood consumption among women. This association remained significant after adjusting for the effects of fruit and vegetable intakes, which are considered as important confounding factors. A cross-sectional study in Korea demonstrated that the highest tertile of seafood consumption was associated with a decreased risk of depression compared to the lowest tertile [30] in men and women. A population-based cohort study of older adults in Tuscany (Italy) indicated that a high intake of fish and shellfish was prospectively associated with a decrease in depressive symptoms 3 years later [31]. Subjects who ate fish ≥2 times/week at baseline had a 25% lower risk of depression during follow-up than those who ate fish <2 times/week in the longitudinal study of Australian adults among women [32]. A meta-analysis revealed that an increment of 1 serving/week of fish consumption was associated with 11% lower risk of depression [6].
Particularly, EPA and DHA, which are the most abundant n-3 PUFA present in seafood, might be the main drivers of the associations between seafood intake and the risk of depression. A meta-analysis of observational studies showed that both total n-3 PUFA and fish-derived n-3 PUFA were associated with decreased risk of depression [12]. Higher intakes of total n-3 PUFA, DHA, and EPA were associated with lower odds of depressive symptoms in the Supplementation with Antioxidant Vitamins and Minerals Study conducted in France [36]. A cohort study conducted in Japan reported that an increased intake of EPA and DHA was inversely associated with the risk of depressive symptoms, as well as n-3 PUFA [37]. Total fish consumption, EPA and DHA had a reverse J-shaped association with the risk of psychiatrist-diagnosed major depressive disorder in Japanese cohort study [38].
The beneficial effects of seafood and its components on depression might be explained by numerous mechanisms. The imbalance of neurotransmission plays an important role in the pathophysiology of depression. Intake of n-3 PUFAs positively influences the depressive status by maintaining the membrane structure and functions of brain, which may potentially modulate the serotoninergic and dopaminergic transmission [13]. The highly unsaturated nature of EPA and DHA affects membrane fluidity of several types of cells [39,40]. N-3 PUFAs also regulate the signal transductions by inducing membrane changing, such as stimulating the activity of diacylglycerol kinase [41] and Na/K-dependent ATPase [42]. Beside these neurotransmitter system as the underlying mechanisms of major depression, alterations in glutamatergic system have been implicated in age-related cognitive deficits [43,44]. The N-methyl-D-aspartate receptor, a glutamate receptor, is a binding or modulation site for antidepressant [45]. In experimental animals, deficiency of n-3 PUFAs aggravates the reductions in glutamatergic synaptic efficacy and its astroglial regulation in the hippocampal CA1, which is involved in spatial memory [43].
In the present study, as seafood consumption increased, the consumption of grains, oils and sugar decreased among women. Moreover, there was a negative association between seafood consumption and carbohydrate intake in both men and women. A study utilizing data of 75,466 participants from UK Biobank reported that the dietary pattern, which is characterized by high intakes of grain-based desserts, chocolate and confectionery, and butter, is associated with a higher risk of depressive and anxious symptoms [46]. The observational retrospective study conducted in Spain showed that a high consumption of sweet foods and refined sugars was significantly associated with depression [47]. Some studies have demonstrated that low carbohydrate intakes are correlated with a decreased risk of depression [48,49]. A cross-sectional study of United States adults reported that the low-carbohydrate-diet score, which provide a comprehensive assessment of diets with a lower intake of carbohydrate and a higher intake of protein and fat, was inversely associated with the risk of depression [50].
Dysregulation of the functional activity of the peripheral immune system is observed in major depression, which is characterized by increased levels of proinflammatory cytokines [13]. Eicosanoids produced from n-3 PUFAs affect inflammation and regulation of immune function through incorporation in cell membrane, which results in the release of 20 carbon arachidonic (AA) content from membrane phospholipids. This procedure subsequently leads to the reduction on the amount of substrate available to produce inflammatory and immunoregulatory eicosanoids [51]. Beside their action on eicosanoids, n-3 PUFA have been reported to decrease proinflammatory cytokines production, such as TNF-α and interleukin-6 [52]. Increased intake of refined carbohydrates and refined vegetable oils rich in omega-6 fatty acids led to the production of AA, thereby leading to elevated inflammation in various organs [53]. Dietary sugars may also elicit inflammatory processes. Fructose-fed rats had increased visceral adipose tissue mass along with elevated levels of inflammatory factors and increased expression of inflammatory genes [54]. Chronic stress, which might induce depressive-like behaviors, exacerbated blood–brain barrier damage and increased neuroinflammation in high fructose diet-fed mice [55].
Our study showed that in the group with high n-3 PUFA intake, significant inverse correlation was found between CDAI and BDI scores among women. As discussed above, n-3 PUFAs can exert the potential anti-inflammatory effects via preventing or decreasing the inflammatory status. Also, numerous studies have demonstrated that a protective effect of consuming a diet rich in antioxidants on the risk of depression [56,57]. In experimental animals, combined treatment of n-3 PUFA and ascorbic acid provided an additive effect in suppressing lipid peroxidation compared to n-3 PUFA or ascorbic acid alone [58]. A recent meta-analysis of human, which pooled data from 10 randomized controlled trials of n-3 fatty acids in patients with acute inflammatory lung injury, suggested that the enteral formulation which provided n-3 fatty acids in combination with antioxidant and γ-linolenic acid formulation led to more favorable outcomes [17]. Regarding the results, it might be suggested that n-3 PUFA could exert more beneficial effects against depression, which is associated with inflammatory conditions, if accompanied by increased consumption of foods rich in antioxidants.
Sex differences were also observed in our study. Generally, women were more likely to engage in health-promoting behaviors and have healthier lifestyle patterns than men [59]. According to our results, the consumption of plant-based foods, such as fruits and vegetables, was higher among women than among men. A previous intervention study designed to investigate sex hormone effects on n-3 highly unsaturated fatty acids in human subjects, revealed that DHA concentrations in plasma cholesteryl esters were higher in women than in men and that this difference was independent of dietary differences. Estrogen induced an increase in DHA status in women, probably by regulating biosynthesis of DHA [60]. These sex-dependent variations might affect the reduced risk of depression in women compared to men.
The main strength of the current study was the design as a prospective long-term follow-up for up to 8 years. Moreover, we had comprehensive information on potential confounding factors based on a questionnaire administered by skilled interviewers. Nonetheless, the study has some limitations. First, we had no data regarding to depression treatment, such as antidepressants and medication compliance. Second, self-reported dietary data might have some information bias. Third, we assessed dietary intakes only at baseline did not capture changes in the diet over the course of the follow-up period. Finally, although the study setting accounted for potential confounders, the generalizability of our results may be limited. Therefore, our results need to be replicated in other population groups with repeated dietary assessments and more diverse ethnic backgrounds.

5. Conclusions

In conclusion, findings from this longitudinal study suggest that seafood consumption was inversely associated with risk of depression in Korean women. Moreover, n-3 PUFA in seafood might have a protective effect against depression if accompanied by increased consumption of foods rich in antioxidants. Our findings will provide an important basis to further examine the benefits of seafood consumption for mental health.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/antiox13111413/s1, Table S1: Classification of food items.

Author Contributions

Y.K. contributed to the conceptualization, funding acquisition, and supervision; J.M. and M.K. contributed to the study design, data analysis, and investigation; J.M. and M.K. drafted the manuscript; Y.K. critically reviewed and edited the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by Academic Research Cooperation Program in Korea Maritime Institute (KMI) (No. 2024-0028-1002).

Institutional Review Board Statement

This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects were approved by the Institu-tional Review Board of Ewha Womans University (No. 202208-0010-01; 25 August 2022).

Informed Consent Statement

All study participants provided written informed consent before participating in the study.

Data Availability Statement

Data in this study were available from the Korean Genome and Epidemiology Study (KoGES; 6635-302) conducted by the National Institute of Health, Centers for Disease Control and Prevention, Ministry for Health and Welfare, Republic of Korea.

Conflicts of Interest

The authors declare no conflicts of interest.

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Antioxidants 13 01413 g001
Figure 1. A flowchart of the study population.
Figure 1. A flowchart of the study population.
Antioxidants 13 01413 g001
Table 1. General characteristics according to seafood-consumption quintile.
Table 1. General characteristics according to seafood-consumption quintile.
Quintile 1Quintile 2Quintile 3Quintile 4Quintile 5p-Value †
Men
 No. of participants275276276276276
 Median (g/d)14.826.137.352.281.4
 Range (g/d)0.4–20.720.8–31.331.3–44.844.9–62.462.4–272.9
 BDI score5.3 ± 0.25.5 ± 0.25.9 ± 0.35.7 ± 0.34.9 ± 0.20.035
 Age (years)51.3 ± 0.350.6 ± 0.350.6 ± 0.350.9 ± 0.350.3 ± 0.30.272
 BMI (kg/m2)24.1 ± 0.224.7 ± 0.224.3 ± 0.224.8 ± 0.225.3 ± 0.2<0.001
 Current drinker182 (66.2)206 (74.6)208 (75.4)213 (77.2)215 (77.9)0.012
 Current smoker 77 (28.0)81 (29.4)81 (29.4)93 (33.7)102 (37.0)0.127
 Physical activity, ≥30 min/d136 (49.5)164 (59.4)149 (54.0)156 (56.5)171 (62.0)0.032
 Monthly income, ≥2 million KRW206 (74.9)219 (79.4)224 (81.2)223 (80.8)232 (84.1)0.102
 Education, ≥college83 (30.2)82 (29.7)104 (37.7)104 (37.7)119 (43.1)0.003
 Marital status, married265 (96.4)266 (96.4)272 (98.6)272 (98.6)269 (97.5)0.257
Women
 No. of participants237237237237237
 Median (g/d)12.621.532.644.972.2
 Range (g/d)0.3–17.017.1–26.926.9–37.737.8–55.755.7–224.9
 BDI score7.1 ± 0.36.5 ± 0.36.0 ± 0.36.3 ± 0.36.2 ± 0.30.067
 Age (years)51.3 ± 0.450.5 ± 0.450.7 ± 0.449.9 ± 0.350.1 ± 0.30.033
 BMI (kg/m2)24.7 ±0.223.9 ± 0.224.5 ± 0.224.3 ± 0.224.8 ± 0.20.008
 Current drinker60 (25.3)67 (28.3)78 (32.9)65 (27.4)75 (31.7)0.347
 Current smoker 4 (1.7)3 (1.3)2 (0.8)5 (2.1)5 (2.1)0.809
 Physical activity, ≥30 min/d114 (48.1)131 (55.3)136 (57.4)132 (55.7)153 (64.6)0.010
 Monthly income, ≥2 million KRW142 (59.9)153 (64.6)169 (71.3)183 (77.2)174 (73.4)<0.001
 Education, ≥college23 (9.7)38 (16.0)42 (17.7)27 (11.4)51 (21.5)0.002
 Marital status, married210 (88.6)214 (90.3)220 (92.8)226 (95.4)217 (91.6)0.085
 Menopausal status 0.296
  Premenopause98 (41.4)126 (53.2)111 (46.8)120 (50.6)131 (55.3)
  Menopause, current HRT use11 (4.6)11 (4.6)13 (5.5)12 (5.1)11 (4.6)
  Menopause, past HRT use 28 (11.8)19 (8.0)29 (12.2)32 (13.5)28 (11.8)
  Menopause, non-HRT use89 (37.6)75 (31.7)77 (32.5)66 (27.9)62 (26.2)
  Menopause, unknown HRT use11 (4.6)6 (2.5)7 (3.0)7 (3.0)5 (2.1)
BDI, Beck Depression Inventory; BMI, body mass index; KRW, Korean won; HRT, hormone replacement therapy. The values are expressed as the mean ± SE for continuous variables and numbers (percentages) for categorical variables. † The p-value was obtained from the general linear models for continuous variables and a Chi-square or Fisher’s exact test for categorical variables.
Table 2. Food consumption according to seafood-consumption quintile.
Table 2. Food consumption according to seafood-consumption quintile.
Food Consumption
(g/1000 kcal)		Quintile 1Quintile 2Quintile 3Quintile 4Quintile 5p-Trend †
MeanSEMeanSEMeanSEMeanSEMeanSE
Men
 Grains438.93.7411.63.7410.04.0383.73.4359.44.1<0.001
 Potatoes5.60.46.00.46.80.56.60.57.00.50.019
 Legumes19.7 1.520.8 1.521.21.521.11.223.71.40.052
 Nuts and seeds0.40.10.50.10.60.10.80.10.60.10.010
 Fruits 104.04.098.53.9117.64.9117.84.5133.55.5<0.001
 Vegetables 30.41.133.51.136.11.041.91.345.61.5<0.001
 Mushrooms3.60.23.40.23.70.25.00.35.30.4<0.001
 Meats 19.80.825.01.027.61.030.91.131.91.2<0.001
 Eggs6.00.46.60.46.60.46.80.57.50.50.019
 Fish and shellfish7.90.213.60.218.60.325.50.440.41.0<0.001
 Seaweeds0.50.00.60.00.60.00.70.00.80.1<0.001
 Milk and dairy products54.73.8 53.53.350.53.253.03.360.73.60.152
 Oils and sugars3.80.24.20.23.30.23.70.23.60.20.206
Women
 Grains429.04.9406.34.7384.94.7369.34.2342.05.0<0.001
 Potatoes9.90.710.00.610.80.710.80.711.70.70.037
 Legumes18.81.520.81.725.01.622.81.424.11.30.017
 Nuts and seeds0.70.20.70.10.60.10.90.11.00.10.010
 Fruits 159.66.7161.45.9196.38.0179.96.3192.16.9<0.001
 Vegetables 38.71.643.01.647.61.550.71.662.42.2<0.001
 Mushrooms4.20.35.00.34.70.45.80.37.10.4<0.001
 Meats14.60.917.90.918.10.919.60.922.31.0<0.001
 Eggs6.30.46.50.47.10.57.60.57.10.40.097
 Fish and shellfish7.60.213.40.318.70.325.30.541.11.2<0.001
 Seaweeds0.70.00.90.10.90.11.00.11.20.1<0.001
 Milk and dairy products73.5 5.075.14.688.25.480.04.388.74.50.022
 Oils and sugars2.5 0.22.20.22.10.22.20.22.00.20.048
The values are expressed as the mean ± SE. † The p-trend was calculated by treating the median value of each quintile as a continuous variable in the general linear model.
Table 3. Nutrient intake according to seafood-consumption quintile.
Table 3. Nutrient intake according to seafood-consumption quintile.
Quintile 1Quintile 2Quintile 3Quintile 4Quintile 5p-Trend †
MeanSEMeanSEMeanSEMeanSEMeanSE
Men
 Total energy (kcal/d)172222.8190122.7204126.2210827.7233934.2<0.001
 Protein (g/d)29.70.231.40.232.60.234.50.337.60.3<0.001
 Fat (g/d)14.20.316.00.316.50.317.60.318.70.3<0.001
 Carbohydrate (g/d)185.20.7179.90.7177.50.7173.30.8168.10.8<0.001
 Vitamin A (RE/d)201.65.4220.75.4227.15.4243.45.5266.67.0<0.001
 Vitamin B1 (mg/d)0.50.00.60.00.60.00.60.00.60.0<0.001
 Vitamin B2 (mg/d)0.50.00.50.00.50.00.50.00.60.0<0.001
 Niacin (mg/d)7.30.17.80.17.90.18.60.19.20.1<0.001
 Vitamin C (mg/d)49.91.351.31.452.91.257.31.361.81.4<0.001
 Zinc (µg/d)3.90.04.20.04.30.04.50.04.90.0<0.001
 Vitamin B6 (mg/d)0.80.00.80.00.80.00.90.00.90.0<0.001
 Folate (µg/d)105.41.9108.02.0108.51.9117.22.1123.52.2<0.001
 Retinol (µg/d)27.21.330.71.131.61.035.81.244.21.4<0.001
 Carotene (µg/d)101229.3110030.9112830.8120331.5128340.3<0.001
 Fiber (g/d)3.10.13.00.13.10.13.10.13.20.10.013
 Vitamin E (mg/d)3.90.14.20.14.40.14.80.15.20.1<0.001
Women
 Total energy (kcal/d)151925.5162826.3173525.7184328.2204033.3<0.001
 Protein (g/d)29.70.331.00.332.80.334.20.337.80.4<0.001
 Fat (g/d)13.00.314.10.315.00.316.10.317.70.3<0.001
 Carbohydrate (g/d)188.50.8184.80.8181.90.8178.10.8171.60.9<0.001
 Vitamin A (RE/d)219.97.3229.17.8257.27.7267.77.7313.49.9<0.001
 Vitamin B1 (mg/d)0.50.00.50.00.60.00.60.00.60.0<0.001
 Vitamin B2 (mg/d)0.50.00.50.00.50.00.60.00.60.0<0.001
 Niacin (mg/d)7.10.17.40.17.70.18.10.18.90.1<0.001
 Vitamin C (mg/d)63.01.863.81.673.52.173.22.081.32.2<0.001
 Zinc (µg/d)4.00.04.20.04.30.04.40.14.70.1<0.001
 Vitamin B6 (mg/d)0.80.00.90.00.90.00.90.01.00.0<0.001
 Folate (µg/d)116.82.6116.72.5126.82.8130.62.6143.22.8<0.001
 Retinol (µg/d)29.61.333.31.437.81.540.51.444.71.5<0.001
 Carotene (µg/d)112043.0114544.1128644.0132543.3156957.9<0.001
 Fiber (g/d)3.40.13.30.13.60.13.60.13.80.1<0.001
 Vitamin E (mg/d)4.20.14.40.14.90.15.20.15.90.1<0.001
RE, retinol equivalents. The values are expressed as the mean ± SE. Nutrient intakes were expressed per 1000 kcal. † The p-trend was calculated by treating the median value of each quintile as a continuous variable in the general linear model.
Table 4. Hazard ratios and 95% confidence intervals for depression according to the seafood consumption quintile.
Table 4. Hazard ratios and 95% confidence intervals for depression according to the seafood consumption quintile.
Model 1 * Model 2 †
No. of Cases (%)Person-YearsHR95% CIp-ValueHR95% CIp-Value
Men
Quintile 1 (n = 275)32 (11.6)1907.21.00 (Reference)-1.00 (Reference)-
Quintile 2 (n = 276)26 (9.4)1833.90.850.51–1.430.5430.850.50–1.440.534
Quintile 3 (n = 276)37 (13.4)1930.91.150.72–1.840.5691.000.60–1.670.988
Quintile 4 (n = 276)31 (11.2)1889.40.980.60–1.610.9380.890.52–1.540.675
Quintile 5 (n = 276)39 (14.1)1895.51.230.77–1.970.3801.280.73–2.240.386
Women
Quintile 1 (n = 237)54 (22.8)1543.71.00 (Reference)-1.00 (Reference)-
Quintile 2 (n = 237)45 (19.0)1601.90.780.53–1.160.2200.830.55–1.250.377
Quintile 3 (n = 237)51 (21.5)1606.60.890.60–1.300.5320.940.62–1.420.775
Quintile 4 (n = 237)45 (19.0)1667.80.750.50–1.110.1490.870.56–1.340.517
Quintile 5 (n = 237)31 (13.1)1669.30.490.32–0.770.0010.580.35–0.980.040
HR, hazard ratio; CI, confidence interval. * Model 1 was unadjusted. † Model 2 was adjusted for energy intake, age, BMI, baseline BDI score, current drinker, current smoker, physical activity, monthly income, education, marital status, and consumption of fruit, vegetables, and meat (men). Model 2 was adjusted for energy intake, age, BMI, current drinker, current smoker, physical activity, monthly income, education, marital status, and consumption of fruit, vegetables, and meat (women).
Table 5. Correlation between composite dietary antioxidant index and Beck Depression Inventory scores according to n-3 PUFAs status.
Table 5. Correlation between composite dietary antioxidant index and Beck Depression Inventory scores according to n-3 PUFAs status.
Men Women
rp rp
n-3 PUFAs (g/d)
 Low (<1.14) *−0.0210.611Low (<1.07)−0.0300.492
 High (≥1.14)−0.0510.217High (≥1.07)−0.146<0.001
PUFAs, polyunsaturated fatty acids. * The participants were divided into each group, with low and high being based on a median value.
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Moon, J.; Kim, M.; Kim, Y. N-3 Fatty Acids in Seafood Influence the Association Between the Composite Dietary Antioxidant Index and Depression: A Community-Based Prospective Cohort Study. Antioxidants 2024, 13, 1413. https://doi.org/10.3390/antiox13111413

AMA Style

Moon J, Kim M, Kim Y. N-3 Fatty Acids in Seafood Influence the Association Between the Composite Dietary Antioxidant Index and Depression: A Community-Based Prospective Cohort Study. Antioxidants. 2024; 13(11):1413. https://doi.org/10.3390/antiox13111413

Chicago/Turabian Style

Moon, Junhwi, Minji Kim, and Yangha Kim. 2024. "N-3 Fatty Acids in Seafood Influence the Association Between the Composite Dietary Antioxidant Index and Depression: A Community-Based Prospective Cohort Study" Antioxidants 13, no. 11: 1413. https://doi.org/10.3390/antiox13111413

APA Style

Moon, J., Kim, M., & Kim, Y. (2024). N-3 Fatty Acids in Seafood Influence the Association Between the Composite Dietary Antioxidant Index and Depression: A Community-Based Prospective Cohort Study. Antioxidants, 13(11), 1413. https://doi.org/10.3390/antiox13111413

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