
==== Front
BMC Public Health
BMC Public Health
BMC Public Health
1471-2458
BioMed Central London

19344
10.1186/s12889-024-19344-6
Research
The association between the number of food kinds and risk of depression in U.S. adults
Xu Qiu-Hui
Yang Ting
Jiang Ke-Yu
Liu Jin-Dong
Guo Hong-Hui
Xia En-Qin xiaenqin@gdmu.edu.cn

https://ror.org/04k5rxe29 grid.410560.6 0000 0004 1760 3078 School of Public Health, Shunde Women and Children’s Hospital, Guangdong Medical University, Guangdong, 524003 China
20 9 2024
20 9 2024
2024
24 257529 2 2024
2 7 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Background

The association between the number of food kinds and the risk of depression in adults was examined.

Methods

According to the inclusion and exclusion criteria, a total of 4593 adults were included in the study. The number of food kinds was collected via 24‒hour dietary recalls. Depression was assessed using the Patient Health Questionnaire‒9. Logistic regression and restricted cubic spline models were applied to assess the association between the number of food kinds and the risk of depression.

Results

This study included 4593 study participants, 451 of whom were diagnosed with depression. The revised advantage ratios (with corresponding confidence intervals) for the prevalence of depression among individuals in the fourth quartiles of the number of food kinds (Q4) in comparison to the lowest quartile (Q1) were determined to be 0.59 (0.36‒0.96), respectively. According to our subgroup analyses, the number of food kinds was negatively associated with the risk of depression in females, participants aged 18‒45 and 45‒65 years, and participants with a body mass index (BMI) of 25 to 24.9 kg/m2. According to our dose‒response analysis, the number of food kinds was linearly associated with the risk of depression (Pfor nonlinear=0.5896).

Conclusion

The risk of depression exhibited a linear and negative correlation with the number of food kinds. The results indicated that a diversified diet was an effective nonpharmacological approach that deserved further generalization.

Keywords

Depression
The number of food kinds
Association
NHANES
Guangdong Basic and Applied Basic Research Foundation2021B1515140057 Medical Fund Project of Guangdong ProvinceA2023434 issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2024
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pmcIntroduction

Depression has become a major mental health problem. Depression has been thought to affect 300 million people globally [1]. At the mental disorder level, depression ranked 2nd and 13th among the 25 leading causes of years lived with disability (YLDs) and disability‒adjusted life‒years (DALYs), respectively [2]. By 2030, Depression was predicted to be the leading cause of disease burden worldwide, endangering not only people’s health but also stable socioeconomic development [3]. However, current treatments for depression have limited efficacy. About 30‒40% of patients did not respond to depression treatment medications and suffered long‒term side effects [4]. In addition, depression is expensive to treat. Current treatments only address a third of the cost of its treatment [5]. Hence, studying the risk factors and effective prevention methods for depression is necessary.

There are many factors that influence the development of depression, including sex, age, lifestyle, behavior and diet. In recent years, a number of studies have shown a significant correlation between diet and the development of depression. Diet intervention can strongly improve in depression and other mental diseases [6, 7]. According to the research findings, a lack of dietary diversity can lead to a variety of health problems [8, 9]. Meanwhile, The Healthy Eating Index (HEI) is an indicator of poorer diet quality with lower scores. A study on the HEI‒2015 revealed a significant association between low scores and increased risk of depression in U.S. adults [10]. Several clinical trials have shown that the Mediterranean dietary pattern with a variety of foods as dietary sources was beneficial for reducing the risk of depression [11–13]. The number of food kinds is a simple, rapid and effective index for evaluating dietary diversity. According to “The Healthy U.S.‒Style Dietary Patterns”, foods included vegetables, fruits, whole grains, legumes, nuts, seeds, seafood, eggs, low‒fat or nonfat dairy products, lean meats, and poultry, with little or no added sugar, saturated fat, or sodium. The Dietary Guidelines for Chinese Residents recommended an average intake of more than 12 food items per day and more than 25 food items per week to ensure food variety and balanced nutrition. However, epidemiological studies on the associations between the number of food kinds and depression are limited.

In addition, current studies on the relationship between dietary diversity and depression have been conducted in older adults or women. A nationwide study showed that in older adults, dietary diversity was associated with improved depressive symptoms [14, 15]. A study of women showed that dietary diversity scores were negatively associated with depression [16]. A dietary pattern with an appropriate ratio of n‒6/n‒3 fatty acids promoted women’s mental health [17]. However, no studies were found on the relationship between the number of food kinds and depression in young, middle‒aged, or male populations.

Therefore, we investigated the potential relationship between the number of food kinds and the risk of depression among U.S. adults by analyzing the National Health and Nutrition Examination Survey (NHANES) data from 2007 to 2008. We hypothesized that an increase in the number of food kinds is associated with a decreased risk of depression. Stratified analyses for sex, age, and body mass index (BMI) were also conducted to explore the associations between the number of food kinds and depression in different populations.

Methods

Study population

NHANES is a cross‒sectional survey in which the health and nutritional status of adults and children are studied and assessed in the U.S. Through interviews and laboratory tests, information on the health and nutritional status of different populations was collected. The associations of health and nutritional status with disease prevention and the prevalence of and risk factors for different diseases in the population were evaluated. Initiated in the early 1960s, this program conducts a series of surveys by sampling approximately 5000 individuals from various regions nationwide.

For this study, a total of 10,149 participants from the NHANES 2007‒2008 dataset were considered. Among the participants, 6,228 were adults older than 18 years. After the exclusion of incomplete data on depression (n = 3,200) and incomplete data on dietary interviews (n = 2,311), as well as the exclusion of pregnant women (n = 45), the final analysis was conducted with a sample size of 4,593 subjects. Consequently, these adults composed the study subjects with complete data (Fig. 1).

Fig. 1 Flow chart of data merge

Depression assessment

Depression was assessed using the Patient Health Questionnaire (PHQ‒9) to determine the frequency of depressive symptoms in the past 2 weeks [18]. The questionnaire consists of 9 items, each of which were scored as “not at all”, “a few days”, “more than half”, or “almost every day” on a scale from 0 to 3. The total score for each of the 9 items was calculated. A total score ≤ 9, the person did not suffer from depression. A total score ≥ 10 indicated that the person had depression indicated that and the maximum total score was 27. This method has high specificity and sensitivity and is widely used in the diagnosis of depression [19].

The number of food kinds reported

Dietary intake data for the study participants were collected through two 24‒hour dietary recall interviews. The first interview was conducted in person at the Mobile Examination Centre (MEC), while the second interview was conducted via telephone 3 to 10 days later. Participants were given a set of measurement guides (a variety of glasses, bowls, mugs, drink boxes and bottles, household spoons, measuring cups and spoons, a ruler, thickness sticks, bean bags, and circles) and a food modeling pamphlet to assist participants in reporting food amounts during both interviews. These dietary interviews were available to all participants. The types and amounts of food consumed in the 24 h prior to the interview were estimated from the collected interview data. The amounts of nutrients such as carbohydrates, proteins, fats, and vitamins, the amount of energy and the number of food kinds were calculated for the different foods. The mean number of food kinds over the 2 days of dietary interviews was calculated. Participants were grouped by quartiles according to the number of food kinds.

Covariates

Covariates were selected based on factors associated with depression that have been previously studied in the literature [20, 21]. The demographic statistics included age, sex, educational attainment (less than 5th grade, 9th‒11th grade, high school graduation/GED or equivalent, some college or AA degree, post‒secondary education), ethnicity (Mexican American, Other Hispanic, Non‒Hispanic White, Non‒Hispanic Black, Other Race‒including multiracial), and household income to poverty ratio (based on the annual U.S. Department of Health and Human Services determined by the annual U.S. Department of Health and Human Services poverty line, which is determined by dividing annual household income by the poverty line). Dietary data included energy intake, dietary supplement use, and the number of food kinds. Individual data included smoking status and BMI which was divided into three categories: <24.9 kg/m2, 25 to 29.9 kg/m2, and ≥ 30 kg/m2. Hypertension, diabetes mellitus, and prescription medicine use were the health status factors considered in this study. Those who reported being informed by a doctor or health professional about their hypertension or diabetes were classified as hypertensive or diabetic.

Statistical analysis

All analyses were performed using SPSS 25.0 and R software (version 4.2.3). SPSS was used to analyze basic clinical characteristics of the study participants and fit logistic regression models. R software was used for restricted cubic spline regression. The NHANES survey design is a stratified, multistage sampling design for the U.S. national, civilian, and noninstitutional populations. All continuous variables had a non‒normal distribution according to Kolmogorov‒Smirnov normality test. Therefore, continuous variables were expressed as medians (P25, P75) and categorical variables were expressed as numbers and percentages. The study subjects were divided into depression‒prevalent and non‒depression‒prevalent groups for comparative analyses. One‒way analysis of variance (ANOVA) was used for normally distributed continuous variables and chi‒square analysis was used for categorical variables.

Factors associated with depression were identified using dichotomous logistic regression models. Model 1 was adjusted for age and sex. Model 2 was adjusted for age, sex, educational attainment, ethnicity, the ratio of household income to poverty, total daily energy intake (kcal/d), smoking status, BMI, hypertension, diabetes mellitus, dietary supplement use, and prescription medicine use. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Due to significant differences in the prevalence of depression according to sex and age, the study was stratified by sex or age. The dose‒response relationship between the number of food kinds and the risk of depression was assessed using restricted cubic spline analysis and represented by restricted cubic spline plots [22]. P < 0.05 indicated statistical significance (all significance tests were two‒sided, with P < 0.05 indicating statistical significance).

Results

Basic clinical characteristics of the study participants

This study included 4593 study participants, 451 of which were diagnosed with depression. The sociodemographic characteristics of the participants differed significantly by depression status, except for race. Among the participants, the mean age was 48 years, and 63% were female. Specifically, females, middle aged people, smokers, obese individuals, individuals with hypertension, diabetes, less education, lower family income, prescription medicine use, and non‒Hispanic whites were more likely to experience depressive symptoms in this sample. The number of food kinds and the energy intake of in participants with depression were significantly lower than those of participants without depression (Table 1).

Table 1 Characteristics of the study population

	Total population 4593	Non‒depression
(PHQ < 10)
4142 (90.2)	Depression
(PHQ ≥ 10)
451 (9.8)	P value	
Age (years)	50.00

(35.00, 65.00)

	51.00

(34.00, 66.00)

	48.00

(37.00, 60.00)

	0.013	
Sex (n, %)				< 0.001	
Female	2344 (51.00)	2060 (49.70)	284 (63.00)		
Male	2249 (49.00)	2082 (50.30)	167 (37.00)		
Education (n, %)				< 0.001	
Less than 9th grade	534 (12.2)	452 (11.4)	82 (18.6)		
9‒11th grade	747 (17.0)	627 (15.9)	120 (27.1)		
High school graduate/GED	1105 (25.2)	999 (25.3)	106 (24.0)		
Some college or AA degree	1143 (26.0)	1046 (26.5)	97 (21.9)		
College graduate or above	859 (19.6)	822 (20.8)	37 (8.4)		
Race, (n, %)				0.620	
Mexican American	755 (16.4)	686 (16.6)	69 (15.3)		
Other Hispanic	505 (11.0)	438 (10.6)	67 (14.9)		
Non‒Hispanic White	2251 (49.0)	2043 (49.3)	208 (46.1)		
Non‒Hispanic Black	942 (20.5)	849 (20.5)	93 (20.6)		
Other Race	140 (3.0)	126 (3.0)	14 (3.1)		
Family poverty income ratio	2.14 (1.15, 4.09)	2.22 (1.20, 4.29)	1.25 (0.72,2.19)	< 0.001	
Smoke at least 100 cigarettes

in life (n, %)

	2102 (47.9)	1832 (46.4)	270 (61.1)	< 0.001	
BMI status (n, %)				< 0.001	
< 24.9 kg/m2	1323 (29.3)	1213 (29.8)	110 (24.9)		
25 to 29.9 kg/m2	1537 (34.0)	1405 (34.5)	132 (29.9)		
≥ 30 kg/m2	1656 (36.7)	1456 (35.7)	200 (45.2)		
Energy intake (kcal/day)	1856.50

(1414.00,2424.00)

	1860.50

(1426.50,2428.12)

	1763.50

(1315.00,2327.00)

	0.007	
Dietary supplement use (n, %)	2163 (47.1)	1989 (48.0)	174 (38.6)	< 0.001	
Prescription medicine use (n, %)	2745 (59.8)	2422 (58.5)	323 (71.6)	< 0.001	
Diabetes (n, %)	572 (12.5)	495 (12.0)	77 (17.1)	< 0.001	
High blood pressure (n, %)	1634 (35.6)	1426 (34.4)	208 (46.1)	< 0.001	
The number of food kinds	16.00 (12.50,19.50)	16.50

(13.00,20.00)

	14.50

(11.50,18.00)

	< 0.001	

Association between the number of food kinds and depression

Logistic regression analyses of the relationship between the number of food kinds and depression are shown in the Table 2. According to the unadjusted model, the number of food kinds was negatively associated with depression (OR, 0.39; 95%CI, 0.27‒0.56). Model 1 adjusted for age and sex still exhibited a negative association (OR, 0.35; 95%CI, 0.24‒0.53). Model 2 for subjects in the third and fourth quartile groups revealed a lower risk of depression after fully adjusting for age, sex, educational attainment, ethnicity, the ratio of household income to poverty, total daily energy intake (kcal/d), smoking status, alcohol use, BMI, hypertension, diabetes, dietary supplement use, and prescription medicine use, using the lowest quartile as the reference category. The OR and 95% CI for quartile group 4 in Model 2 were 0.59 (0.36‒0.96).

Table 2 The association between the number of food kinds and depression

The number of food kinds	Intake cutoff	Cases/participants	Crude	Model 1a	Model 2b	
Quartile 1	< 12.5	156/1189	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	
Quartile 2	12.5 to < 16.0	143/1177	0.77 (0.58‒1.03)	0.74 (0.55‒1.00)	1.05 (0.68‒1.64)	
Quartile 3	16.0 to < 19.5	80/1080	0.43 (0.28‒0.68)	0.41 (0.27‒0.64)	0.61 (0.35‒1.07)	
Quartile 4	≥ 19.5	72/1147	0.39 (0.27‒0.56)	0.35 (0.24‒0.53)	0.59 (0.36‒0.96)	
P‒trend			0.001	0.001	0.015	
aModel 1 was adjusted for age and sex

bModel 2 was additionally adjusted for BMI, race, educational level, smoking status, family income, hypertension status, diabetes status, total daily energy intake (kcal/d), dietary supplement use, and prescription medicine use

As shown in Table 3, no significant difference was found between the number of food kinds and the risk of depression in males. However, for females, the number of food kinds remained negatively associated with the risk of depression. The multifactor corrected odds ratio (95% CI) for depression in the third and fourth quartile groups were 0.47 (0.28‒0.78) and 0.51 (0.29‒0.91). Thus, the risk of depression decreased as the number of food kinds increased.

In the age‒stratified analysis, three different age groups were categorized according to age groups: 18 ~ 45, 45 ~ 65 and 65~. The negative correlation between the number of food kinds and depression was statistically significant in both the 18 ~ 45 and 45 ~ 65 age groups, but no significant correlation was found in the 65 ~ age group (Table 4).

Table 3 The association between the number of food kinds and depression by sex

The number
of food kinds	Intake cutoff	Crude	Model 1a	Model 2b	
man					
Quartile 1	< 12.5	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	
Quartile 2	12.5 to < 16.0	0.83 (0.41‒1.65)	0.76 (0.39‒1.50)	1.16 (0.56‒2.41)	
Quartile 3	16.0 to < 19.5	0.55 (0.26‒1.20)	0.48 (0.23‒1.03)	0.95 (0.43‒2.11)	
Quartile 4	≥ 19.5	0.39 (0.16‒0.96)	0.32 (0.13‒0.83)	0.68 (0.27‒1.74)	
P‒trend		0.219	0.135	0.727	
woman					
Quartile 1	< 12.5	1.00 (ref.)	1.00 (ref.)	1.00 (ref.)	
Quartile 2	12.5 to < 16.0	0.71 (0.47‒1.08)	0.72 (0.47‒1.11)	0.99 (0.58‒1.69)	
Quartile 3	16.0 to < 19.5	0.36 (0.24‒0.55)	0.37 (0.24‒0.57)	0.47 (0.28‒0.78)	
Quartile 4	≥ 19.5	0.35 (0.22‒0.57)	0.37 (0.22‒0.60)	0.51 (0.29‒0.91)	
P‒trend		0.001	0.002	0.037	
aModel 1 adjusted for age

bModel 2 adjusted for age, BMI, race, educational level, smoking status, family income, hypertension status, diabetes status, total daily energy intake (kcal/d), dietary supplement use, and prescription medicine use

Table 4 The association between the number of food kinds and depression by age

The number of food kinds	Intake cutoff	Crude	Model 1a	Model 2b	
18~					
Quartile 1	< 12.5	1.00(ref.)	1.00(ref.)	1.00(ref.)	
Quartile 2

Quartile 3

Quartile 4

P‒trend

	12.5 to < 16.0

16.0 to < 19.5

≥ 19.5

	0.64(0.41‒0.98)

0.40(0.26‒0.60)

0.40(0.25‒0.64)

0.003

	0.61(0.40‒0.94)

0.39(0.25‒0.59)

0.37(0.23‒0.60)

0.003

	0.72(0.39‒1.31)

0.39(0.22‒0.72)

0.38(0.21‒0.70)

0.009

	
45~					
Quartile 1

Quartile 2

Quartile 3

Quartile 4

P‒trend

	< 12.5

12.5 to < 16.0

16.0 to < 19.5

≥ 19.5

	1.00(ref.)

0.97(0.56‒1.69)

0.41(0.20‒0.82)

0.35(0.16‒0.80)

0.016

	1.00(ref.)

0.97(0.56‒1.68)

0.41(0.20‒0.82)

0.35(0.15‒0.81)

0.016

	1.00(ref.)

1.74(1.09‒2.80)

0.81(0.42‒1.55)

0.80(0.37‒1.72)

0.007

	
65~					
Quartile 1

Quartile 2

Quartile 3

Quartile 4

P‒trend

	< 12.5

12.5 to < 16.0

16.0 to < 19.5

≥ 19.5

	1.00(ref.)

1.12(0.38‒3.27)

0.85(0.25‒2.89)

0.64(0.21‒1.89)

0.227

	1.00(ref.)

1.11(0.37‒3.31)

0.84(0.24‒2.87)

0.63(0.21‒1.85)

0.234

	1.00(ref.)

1.73(0.40‒7.51)

1.78(0.49‒6.49)

1.90(0.57‒6.33)

0.657

	
aModel 1 adjusted for sex

bModel 2 adjusted for sex, BMI, race, educational level, smoking status, family income, hypertension status, diabetes status, total daily energy intake (kcal/d), dietary supplement use, and prescription medicine use

As shown in Table 5, a negative association between the number of food kinds and depression was observed only in the 25 to 29.9 kg/m2 subgroup, while no significant association was found in the < 24.9 kg/m2 and ≥ 30 kg/m2 subgroups.

There was a linear relationship between the number of food kinds and the risk of depression with the dose‒response relationship (P = 0.5896). Furthermore, after stratification analysis, a linear relationship was also observed among females (P = 0.3758), as depicted in Fig. 2.

Table 5 The association between the number of food kinds and depression by BMI

The number of food kinds	Intake cutoff	Crude	Model 1a	Model 2b	
< 24.9 kg/m2					
Quartile 1	< 12.5	1.00(ref.)	1.00(ref.)	1.00(ref.)	
Quartile 2

Quartile 3

Quartile 4

P‒trend

	12.5 to < 16.0

16.0 to < 19.5

≥ 19.5

	0.51(0.25‒1.03)

0.30(0.13‒0.67)

0.34(0.16‒0.73)

0.045

	0.50(0.25‒1.00)

0.28(0.13‒0.63)

0.31(0.15‒0.66)

0.027

	0.83(0.37‒1.87)

0.47(0.19‒1.19)

0.81(0.30‒2.13)

0.452

	
25 to 29.9 kg/m 2					
Quartile 1

Quartile 2

Quartile 3

Quartile 4

P‒trend

	< 12.5

12.5 to < 16.0

16.0 to < 19.5

≥ 19.5

	1.00(ref.)

0.85(0.45‒1.60)

0.43(0.21‒0.89)

0.32(0.19‒0.52)

0.001

	1.00(ref.)

0.76(0.41‒1.40)

0.39(0.19‒0.80)

0.28(0.17‒0.49)

0.001

	1.00(ref.)

0.87(0.38‒1.97)

0.42(0.19‒0.95)

0.28(0.15‒0.52)

0.001

	
≥ 30 kg/m 2					
Quartile 1

Quartile 2

Quartile 3

Quartile 4

P‒trend

	< 12.5

12.5 to < 16.0

16.0 to < 19.5

≥ 19.5

	1.00(ref.)

0.95(0.59‒1.53)

0.55(0.31‒0.98)

0.53(0.32‒0.87)

0.112

	1.00(ref.)

0.98(0.61‒1.56)

0.58(0.31‒1.06)

0.52(0.31‒0.87)

0.129

	1.00(ref.)

1.58(0.84‒2.98)

0.94(0.44‒2.02)

0.86(0.43‒1.72)

0.165

	
aModel 1 adjusted for sex

bModel 2 adjusted for sex, BMI, race, educational level, smoking status, family income, hypertension status, diabetes status, total daily energy intake (kcal/d), dietary supplement use, and prescription medicine use

Fig. 2 A Restricted cubic spline model for the odds ratio of depression to the odds ratio of the number of food kinds. B Restricted cubic spline model for the odds ratio of the number of food kinds to depression in females

Discussion

Based on 2007‒2008 NHANES data, this study examined the relationship between the number of food kinds and depression among U.S. adults. The findings revealed a negative correlation between the number of food kinds and depression. Upon sex stratification, a negative relationship persisted among women, but no correlation was observed among men. According to the age‒stratified analyses, the number of food kinds was significantly associated with depression in young and middle‒aged adults, but no association was found in older age groups. In the BMI‒stratified analysis, a negative association between the number of food kinds and depression was observed only in the 25 to 29.9 kg/m2 subgroup.

A growing number of studies have found that an elevated risk of depression was associated with nutritional problems such as malnutrition and nutrient deficiencies. A retrospective study comparing the diets of depressed individuals revealed that depressed patients consumed significantly less legumes, fruits, and vegetables, and consumed more sweets and refined sugars [23]. A study of the relationship between nutrition and depression in young Koreans showed that depressed patients consumed less energy and nutrients and had higher rates of inappropriate nutritional intake than controls did [24]. A randomized controlled trial of patients with major depressive disorder indicated that dietary interventions effectively treated mental disorders [25]. Studies have shown that dietary trans fatty acid intake may be positively associated with depression in premenopausal women, and n‒3 polyunsaturated fatty acids may be negatively associated with depression in women with early perimenopausal onset [26, 27]. Total dietary fiber intake has been negatively associated with the onset of depression, with a 5% reduction in the risk of depression for every 5 g increase [28]. A cross‒sectional study found that protein intake from dairy products such as milk may reduce the risk of depression [29]. However, other studies have shown that although dietary diversity was negatively associated with the risk of depression, longitudinal analyses have shown that dietary diversity was not significantly associated with changes in depressive symptoms after 2 years of follow‒up [30].

In addition, few studies have been conducted to address sex differences in the diet‒depression relationship. According to a study on inflammation in diet‒depression, the dietary inflammation index was significantly associated with recurrent depressive symptoms in women but not in men [31]. Pro‒inflammatory dietary patterns increased the risk of depression by 49% in women and 27% in men, and anti‒inflammatory diets prevented depression [32]. The negative associations of dietary vitamins B2, B6, and B12 with depression were significant in women but not in men [33]. This difference may be related to sex differences in transcript levels in male and female brains [34–36]. It has also been suggested that sex differences in depression were related to changes in pro‒inflammatory and anti‒inflammatory states of microglia in the brain and to BDNF‒TrkB‒dependent pathways in the hippocampus [37]. Therefore, it is important to consider sex differences in depression when making dietary interventions.

The relationship between diet and depression is complex and can directly influence depression. Fatty acids in food can affect mood by acting on specific brain regions through pathways such as neurotransmitters and signaling pathways [38]. Tryptophan, a precursor to serotonin, played a crucial role in preventing depression through its impact on serotonin synthesis in the central nervous system. A lake of tryptophan in diets can potentially lead to depression [39]. In addition to specific nutrients, inflammation may interact with areas of pathophysiology related to depression, including trans transmitter metabolism, oxidative stress and DNA methylation [40–42]. Dietary patterns have also been established to be associated with inflammation [43]. Unhealthy diets can also indirectly contribute to the development of depression by causing obesity. Obese individuals may be at increased risk of depression due to biological pathways such as the hypothalamic‒pituitary‒adrenal (HPA) axis, neuroendocrine modulators, gut microbiota and poor self‒assessment of health [44].

This study has the following strengths. First of all, we applied the NHANES database, a representative sample of U.S. adults, to evaluate lifestyle, somatic, genetic, and environmental factors that may be associated with causation. Secondly, we adequately adjusted for confounders associated with depression to reduce the effect of confounding bias. Finally, we stratified the participants by sex to investigate the association between the number of food kinds and depression in different sex. However, there are some limitations of this study. This study is not currently supported by clinical trial studies. Furthermore, as the collection of data was based on self‒reporting, the effect of recall bias may have been greater.

Conclusion

In summary, we analyzed the correlation between the number of food kinds and depression by extracting information from the NHANES database and using logistic regression. In the sample population, a higher number of food kinds consumed was associated with a lower risk of depression. This study further explored the antidepressant mechanisms of diet and provided important insights into the prevention of depression. However, we were unable to prove whether there was a causal relationship between these results. More prospective studies are needed to elucidate the relationship between the number of food kinds and depression.

Acknowledgements

Not applicable.

Author contributions

HH Guo and EQ Xia participated in the conception and designed the study. EQ Xia and QH Xu was responsible for research design, data analysis, writing of first drafts. QH Xu, T Yang, KY Jiang and JD Liu wrote the manuscript. QH Xu, T Yang, KY Jiang and JD Liu revised the whole writing process. All authors have read and approved the final manuscript.

Funding

This research was funded by Guangdong Basic and Applied Basic Research Foundation (2021B1515140057), Medical Fund Project of Guangdong Province (A2023434), Dongguan Key Laboratory for Development and Application of Experimental Animal Resources in Biomedical Industry & Laboratory Animal Center, Guangdong Medical University.

Data availability

Data supporting this study can be obtained from the NHANES database: https://wwwn.cdc.gov/nchs/nhanes/Default.aspx.

Declarations

Ethics approval and consent to participate

The study was ethically conducted in accordance with the Declaration of Helsinki. The NHANES study protocol has been approved by the National Center for Health Statistics (NCHS). All participants signed written informed consent.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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