Association of dietary patterns with anxiety and depressive symptoms during pregnancy: a cross-sectional study

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Our objective was to examine the association of dietary patterns (DPs) with anxiety and depressive symptoms in pregnant women. Methods This study was a cross-sectional study conducted in Hunan Province. Food frequency questionnaire, Self-rating Anxiety Scale and the Edinburgh Postnatal Depression Scale were used. Dietary patterns were identified through the utilization of factor analysis. The correlation analysis employed logistic regression. Results The detection rates of anxiety and depression symptoms during pregnancy were 16.8% and 51.3%, respectively. We have identified five DPs in this study. After accounting for possible confounding factors, a positive correlation was found between DP3 and the risk of anxiety (T3:T1, OR = 1.637, 95%CI:1.064–2.519). However, no significant correlations were observed between DP1, DP2, DP4, or DP5 and anxiety symptoms. Additionally, a positive correlation was identified between DP1 and the risk of depression (T3:T1, OR = 1.483, 95%CI: 1.046–2.104). While no significant associations were found between DP2, DP3, DP4 or DP5 and depressive symptoms. Conclusions This study indicates that the dietary pattern high in processed meats, fried foods, sweets, desserts, instant noodles, snacks, and pickled vegetables may potentially elevate the risk of anxiety during pregnancy. The dietary pattern dominated by milk and its products, eggs and nuts may increase the risk of depression during pregnancy. Dietary patterns Factor analysis Pregnancy anxiety Pregnancy depression Figures Figure 1 Figure 2 Figure 3 1. Introduction Mental disorders significantly contribute to the global burden of disease [ 1 ]. Research findings indicate that approximately 322 million individuals are affected by depression, while around 264 million people worldwide experience anxiety [ 2 ]. Anxiety and depressive disorders are prevalent mental health conditions, with higher prevalence rates observed in women compared to men [ 1 ]. Moreover, women face an increased risk of experiencing psychological issues during pregnancy. Prenatal anxiety and depression not only have detrimental impacts on both maternal and fetal well-being but also impact child growth, development, and neuropsychiatric well-being [ 3 – 5 ]. Additionally, subclinical symptoms of depression and anxiety are widespread in the population. Although these symptoms do not meet diagnostic criteria for clinical disorders, they still significantly affect quality of life and social occupational functioning [ 6 ]. The etiology of prenatal anxiety and depression is multifaceted, encompassing demographic factors (such as young maternal age and low educational attainment [ 7 ], unemployment during pregnancy[ 8 ], and low family income [ 9 ]), pregnancy and childbirth-related factors (including first childbirth [ 8 ], adverse pregnancy history[ 10 ]), psychosocial factors (such as poor marital relationship [ 11 ], lack of social support[ 8 ]), behavioral and lifestyle factors (including smoking [ 7 ], insomnia[ 12 ]), alongside various factors linked to an elevated risk of anxiety and depression among pregnant women. An increasing amount of evidence have underscored the significant impact of dietary choices on one's mental well-being. Adopting healthy eating patterns may mitigate the risk of depression and anxiety [ 13 , 14 ]. Previous research has demonstrated that diet can influence mental well-being by modulating inflammation, oxidative stress, gut microbiota, and other biological pathways [ 15 ]. However, prior investigations primarily focused on examining the health effects of individual nutrients or foods. Yet, it is crucial to acknowledge that a single food item or nutrient cannot adequately capture the intricate relationship between overall diet and health outcomes. Given that daily diets encompass a diverse range of foods with potential interactions among multiple nutrients present within them, relying solely on isolated components may yield inaccurate findings [ 16 ]. Consequently, dietary patterns (DPs) offer a comprehensive approach to analyze the association between diet and anxiety as well as depression from a holistic perspective. For instance, traditional dietary patterns distinguished by elevated intake of vegetables, fruits, meat, fish, and whole grains have been linked to reduced risks of major depression and anxiety disorders; conversely Western-style dietary patterns dominated by processed foods, refined grains sugary items along with alcohol intake are associated with an increased likelihood of psychological disorders [ 17 ]. Furthermore, pregnant women exhibit higher demands for optimal diet quality compared to the general population. Unfortunately, limited research has paid attention to pregnant women. Hence, it is crucial to explore the correlation between DPs and symptoms related to anxiety and depression in pregnant women. 2. Materials & Methods 2.1 Study population The data were derived from the Chinese Maternal Nutrition and Health Survey, a cross-sectional study that remains ongoing. This investigation exclusively involved participants at the Hunan Provincial Maternal and Child Health Hospital, from July 2022 to July 2023. Before commencing the survey, a consent form was duly signed by all participants. Among the pregnant women attending this hospital, we consecutively selected those aged 18 to 49 years, who had been residing in the local area for over 12 months, and volunteered to take part. Individuals with mental illness, language communication disorders, or those who refused to participate in it were not included in this survey. 2.2 Dietary assessment The dietary intake of pregnant women were evaluated over the previous month by means of a Food Frequency Questionnaire (FFQ), which examined the frequency and amount of different food categories. Food intake was estimated using food models, and standardized cutlery. Based on the frequency of food intake (times/month, times/week, times/day) and the amount consumed each time, the intake of each food type (g/day or ml/day) was calculated. Considering the dietary habits of the Hunan region, 14 food groups were included: refined grains, whole grains, vegetables, fruits, meat, aquatic products, soybeans and their products, milk and its derivatives, eggs, nuts, fried foods, processed meats, pickled vegetables, and other processed products (including sweets, desserts, instant noodles, and snacks). 2.3 Ascertainment of outcomes The Edinburgh Postnatal Depression Scale (EPDS) has 10 questions and can be utilized as a tool for assessing depression. The EPDS was scored from "0" (never) to "3" (always) using a Likert4 scale. By setting a threshold score of 9, we classified depressive symptoms into three levels based on scores of 12 and 14, with elevated scores denoting increased levels of depression [ 18 ]. The EPDS has shown favorable reliability and validity in screening for depression in pregnant women. Meanwhile, the self-rating Anxiety Scale (SAS) was employed to gauge the subjective anxiety levels of the participants. This scale comprises 20 items that are categorized into positive ratings and reverse scores, ranging from "1" (indicating minimal or no anxiety) to "4" (representing frequent or persistent anxiety). The total score was multiplied by 1.25 and rounded down to obtain the standard score. A standard score of 50 or below indicated the absence of anxiety symptoms, while scores between 60 and 70 were categorized as mild, moderate, and severe anxiety symptoms respectively. The SAS scale demonstrated high reliability and validity [ 19 ]. 2.4 Ascertainment of covariates The collection of data on various variables was accomplished using a self-defined basic information questionnaire. These variables encompassed demographic information (including age, education level, occupation, employment status while pregnant, and per capita monthly income of the household), social psychological information (including medical history, marital relationship, and relationship with parents), and health behavior information (pre-pregnancy BMI, exercise, insomnia, smoking, alcohol consumption). Additionally, data was gathered on pregnancy and childbirth-related factors (pregnancy duration, mode of conception, number of fetuses, number of deliveries, adverse pregnancy history, early pregnancy reaction, vaginal bleeding, and pregnancy preservation). Covariates ( P < 0.05) incorporated into the regression model were selected based on the results of the χ² test or Fisher's exact test (refer to additional file 1). 2.5 Statistical analysis Factor analysis was used to extract DPs, and its applicability was determined according to Kaiser-Meyer-Olkin Measure of Sample Adequacy (KMO)value and Bartlett spherical test results. The number of extracted factors was ascertained by combining the matrix eigenvalue > 1 and factor interpretability. A total of 14 food groups were incorporated into the variable model, with the factor component matrix rotated by the maximum variance method. This rotation enabled the reflection of the correlation between food groups and DPs through the rotated factor loading. In this study, factor loading > 0.30 was used as the basis to determine the extracted common factors as the main dominating variables of DPs. Regression analysis was employed to calculate factor scores for each participant across dietary patterns, with higher scores indicating a greater consumption of such foods in this dietary pattern. Finally, the factor scores of each participant were classified into low (T1), medium (T2), and high (T3) levels using the tertile method, from lowest to highest. SPSS 20.0 was utilized for statistical analysis, with the test level established at 0.05. Univariate analysis was executed using χ 2 test or Fisher's exact test. After controlling for confounding variables, we utilized a multi-factor logistic regression approach to explore the correlation between DPs and anxiety and depression during pregnancy (enter 0.05, delete 0.10). The reference group was defined as T1. 3. Results 3.1 Baseline characteristics A survey was conducted with the participation of 892 pregnant women, whose average age was 30.9 years. Baseline characteristics of the study population are provided in Additional file 1, categorized according to depressive and anxiety symptoms. Notable disparities were observed in the prevalence of anxiety among pregnant women from varying occupational backgrounds, with a history of spontaneous abortion, and those who had congenital malformations ( P < 0.05). Specifically, the highest incidence of anxiety was noted in expectant mothers employed in agriculture, forestry, animal husbandry, fishery, and water conservancy (33.3%), those with a history of spontaneous abortion (24.5%), and those with a history of congenital malformations (50%). Similarly, considerable differences were observed in the occurrence of depression among expectant mothers with varying working conditions, sleep disturbances, spousal relationships, and relationships with parents. Among these factors, the highest prevalence of depression was observed in expectant mothers with increased workload (100.0%), frequent insomnia in the past month (72.7%), frequent insomnia in the first three months of pregnancy (76.4%), poor marital relationships (100.0%), and strained parent-child relationships (80.0%). 3.2 Symptoms of anxiety and depression 150 (16.8%) pregnant women exhibited anxiety symptoms, with 129 (14.5%) experiencing mild anxiety, 18 (2.0%) displaying moderate anxiety, and 3 (0.3%) suffering from severe anxiety. Of the 458 (51.3%) pregnant women who presented depressive symptoms, 212 (23.8%) had mild depression, 108 (12.1%) experienced moderate depression, and 138 (15.5%) exhibited severe depression. 3.3 Characteristics of DPs The factor analysis method revealed the identification of five dietary patterns, with KMO = 0.648 and Bartlett's spherical test (χ 2 = 830.635, P < 0.001).The results revealed a significant association among different food groups, suggesting that factor analysis could be employed to analyze the collected data. The extracted factors, characterized by a matrix eigenvalue > 1, were determined using the maximum variance method. The eigenvalues and contribution rates of the five factors were 2.125 (15.180%), 1.594 (11.385%), 1.199 (8.561%), 1.072 (7.656%), and 1.062 (7.588%), respectively, with a cumulative contribution rate of 50.370%. DP1 was primarily composed of dairy products, eggs, and nuts. DP2 was dominated by vegetables, whole grains, soybeans and their products, nuts, and aquatic products. DP3 was characterized by processed meats, fried foods, other processed products (including sweets, desserts, instant noodles, snacks), and pickled vegetables. DP4 was mainly composed of refined grains, fruits, whole grains, and other processed products. DP5 was dominated by meat, aquatic products, and nuts. Figure 1 illustrates the loading factors and distribution of dietary patterns for each group. 3.4 Correlations between DPs and symptoms of depression and anxiety With anxiety symptoms (0 = no, 1 = yes) as the dependent variable, Fig. 2 depicts the effect of DPs on anxiety symptoms, highlighting a significant correlation between DP3 and anxiety symptoms. The results are depicted in Fig. 3 after controlling for the effects of occupation, history of spontaneous abortion, and history of deformed children. DP3 increases the likelihood of experiencing anxiety while pregnant (T3:T1, OR = 1.637, 95%CI: 1.064–2.519). DP1, DP2, DP4, and DP5 showed no significant correlation with anxiety symptoms. With depressive symptoms (0 = no, 1 = yes) as the dependent variable, Fig. 2 illustrates the influence of DPs on depressive symptoms, revealing a notable correlation between DP1 and depressive symptoms. After accounting for the impact of work situation, insomnia in the last month, insomnia in the first three months of pregnancy, marital relationship, and relationship with parents, the results are presented in Fig. 3. DP1 is a hazard factor for depressive symptoms during pregnancy (T3:T1, OR = 1.483, 95%CI: 1.046–2.104). DP2, DP3, DP4, and DP5 demonstrated no significant correlation with depressive symptoms. 4. Discussion The prevalence of prenatal anxiety in this study was determined to be 16.8%, which was higher than that in Shanghai (11.1%) [ 20 ] and Chongqing (15.04%) [ 8 ], while remaining lower than the overall prevalence of self-reported anxiety in many countries in the world (22.9%) [ 21 ]. These differences may be related to variations in measurement methodologies employed and regional disparities. However, We discovered that the prevalence of prenatal depression exceeded rates observed in numerous other countries and regions, reaching 51.3%. The prevalence of depression in Shanghai was 10.3% [ 20 ], and that in Chongqing was 5.19% [ 8 ]. Furthermore, a worldwide investigation revealed that the occurrence of prenatal depression was 20.7% [ 22 ]. This discrepancy could potentially be attributed to the investigation of symptoms rather than diseases and the use of self-report rating scales rather than structured interviews for assessment [ 23 ]. After accounting for possible confounding factors, the results indicated a positive correlation between DP3 and anxiety during pregnancy. It is distinguished by excessive consumption of processed meats, fried foods, other processed products (including sweets, desserts, instant noodles, and snacks), and pickled vegetables. This finding aligns with epidemiological research indicating that psychological disorders in women are more likely to occur when their diets primarily consist of processed or fried foods, sugary foods, and refined grains [ 17 , 24 ]. Individuals with more severe anxiety exhibit fewer healthy food choices and a higher consumption of energy-dense foods [ 25 ]. Similarly, an increased consumption of snacks may elevate the likelihood of anxiety development [ 26 ]. Furthermore, pickled vegetables possess reduced antioxidants, vitamins, and minerals compared to fresh vegetables. Pickled vegetables are often contaminated with N-nitroso compounds, which increase nitrite content and may impair human health [ 27 ]. However, existing studies have not detected any significant impact of pickled vegetables on mental well-being. Further research is necessary to establish a conclusive link between this dietary pattern and anxiety levels during pregnancy. In the context of depression during pregnancy, our research identified a positive correlation between DP1 and the likelihood of depression. This dietary pattern is distinguished by an elevated consumption of milk and its derivatives, eggs, and nuts. In single-food group studies, an increased consumption of nuts may serve as a preventative measure against the development of depression [ 28 ]. Egg consumption may be associated with a reduced likelihood of experiencing symptoms related to depression [ 29 ]. Different varieties of milk and the nutritional composition of dairy products can have varying impacts on symptoms associated with depression. Multiple studies have demonstrated that healthy dietary patterns consistent with current dietary recommendations, including recommended intakes of foods such as eggs, low-fat dairy products, nuts, etc., may alleviate depressive symptoms in both people without depression and clinically depressed patients [ 30 – 32 ]. Higher diet quality is a protective factor for depressive symptoms [ 33 ]. Fermented dairy products have the potential to modulate mood by influencing the pathway between the brain and gut, leading to a decreased likelihood of experiencing depression [ 34 ]. However, there is alternative research suggesting that an increased consumption of protein could potentially be linked to the emergence of severe depression among females [ 35 ]. Contrary to low-fat milk, whole milk posed a risk for experiencing symptoms of depression [ 36 ]. In summary, our study findings diverge from previous research and warrant further investigation. In addition, it is crucial to recognize the constraints of this research. Firstly, given its cross-sectional design, we are unable to establish a definitive causal relationship. It is possible that anxiety and depression may have induced changes in dietary intake among participants, and diet quality might have arisen as a consequence of psychological symptoms rather than a contributing factor. Consequently, further prospective studies are warranted. Secondly, we requested pregnant women to reminisce about their diet over the past month, which is often prone to recall bias and may lead to an inaccurate estimation of actual food intake. Thirdly, the factor analysis revealed subjectivity in dietary patterns that could have influenced the results. Given the constraints of sample selection and the inability to establish causal relationships, additional research is necessary to investigate the correlation between dietary patterns and symptoms of anxiety and depression during pregnancy. This can be achieved by selecting subjects from various hospitals and regions, as well as conducting longitudinal studies. 5. Conclusions In summary, our findings suggest that a dietary pattern consisting of processed meats, fried foods, sweets, desserts, instant noodles, snacks, and pickled vegetables may elevate the risk of anxiety during pregnancy. Conversely, a diet dominated by dairy products, eggs, and nuts seems to be associated with an elevated risk of developing depression while being pregnant. Our results emphasize that pregnant women should reduce their consumption of processed foods, foods containing free sugars, fried foods, and preserved vegetables. Future studies should focus on investigating the specific effects of different types of dairy products on depression during pregnancy and exploring potential interactions between milk consumption and egg/nut intake. Abbreviations dietary patterns (DPs) Food Frequency Questionnaire (FFQ) The Edinburgh Postnatal Depression Scale (EPDS) the self-rating Anxiety Scale (SAS) Kaiser-Meyer-Olkin Measure of Sample Adequacy (KMO) Declarations Ethics approval and consent to participate The Chinese Maternal Nutrition and Health Survey was approved by the Research Ethics Committee of Hunan Provincial Maternal and Child Health Care Hospital (202153). All the participants provided written informed consent. Consent for publication Not applicable. Availability of data and materials The datasets used during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study was supported by National Science and Technology Basic Resources Special Project of China (2019FY101000). The funding source was not involved in the study design, analysis, interpretation of the data, writing the manuscript or in the decision to submit the manuscript for publication. Authors' contributions Rusi Yang: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing-original draft, Writing-review & editing. Panzi Yang: Conceptualization, Validation, Writing-review & editing. Yangzhenlin Luo: Investigation, Writing-review & editing. Yixin Zhang: Investigation, Writing-review & editing. Zhaolong Xie: Investigation, Writing-review & editing. Ming Hu: Conceptualization, Methodology, Writing-review & editing. Guilian Yang: Resources, Supervision, Funding acquisition, Project administration, Writing-review & editing. All authors critically evaluated and approved the final manuscript. Acknowledgements Not applicable. 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legend\u003c/p\u003e","description":"","filename":"figures1.png","url":"https://assets-eu.researchsquare.com/files/rs-3831840/v1/3e588686b32d6438cfceb1f2.png"},{"id":49216211,"identity":"fde10f6e-9321-4f8b-b26b-c5b13b0bbc7f","added_by":"auto","created_at":"2024-01-05 10:38:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":42507,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Figures2.png","url":"https://assets-eu.researchsquare.com/files/rs-3831840/v1/c4827ebf5f3dbbc5901eec9e.png"},{"id":49215986,"identity":"3eb94056-b13b-4893-bcb0-1e3ecad44966","added_by":"auto","created_at":"2024-01-05 10:30:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":48530,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Figures3.png","url":"https://assets-eu.researchsquare.com/files/rs-3831840/v1/ef2e25029aff4b9e112ce7bd.png"},{"id":49487799,"identity":"aacb055b-6652-462c-bad8-d1a62283aff2","added_by":"auto","created_at":"2024-01-11 16:52:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":628400,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3831840/v1/79f803c0-2132-40db-aa11-89102a789a3f.pdf"},{"id":49216502,"identity":"9b6fd5b6-4e2a-437a-889f-742f8ae8d86e","added_by":"auto","created_at":"2024-01-05 10:46:30","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":31396,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-3831840/v1/c313d7a92799c693e148e5b0.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of dietary patterns with anxiety and depressive symptoms during pregnancy: a cross-sectional study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eMental disorders significantly contribute to the global burden of disease [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Research findings indicate that approximately 322\u0026nbsp;million individuals are affected by depression, while around 264\u0026nbsp;million people worldwide experience anxiety [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Anxiety and depressive disorders are prevalent mental health conditions, with higher prevalence rates observed in women compared to men [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Moreover, women face an increased risk of experiencing psychological issues during pregnancy. Prenatal anxiety and depression not only have detrimental impacts on both maternal and fetal well-being but also impact child growth, development, and neuropsychiatric well-being [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Additionally, subclinical symptoms of depression and anxiety are widespread in the population. Although these symptoms do not meet diagnostic criteria for clinical disorders, they still significantly affect quality of life and social occupational functioning [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The etiology of prenatal anxiety and depression is multifaceted, encompassing demographic factors (such as young maternal age and low educational attainment [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], unemployment during pregnancy[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], and low family income [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]), pregnancy and childbirth-related factors (including first childbirth [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], adverse pregnancy history[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]), psychosocial factors (such as poor marital relationship [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], lack of social support[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]), behavioral and lifestyle factors (including smoking [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], insomnia[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]), alongside various factors linked to an elevated risk of anxiety and depression among pregnant women. An increasing amount of evidence have underscored the significant impact of dietary choices on one's mental well-being.\u003c/p\u003e \u003cp\u003eAdopting healthy eating patterns may mitigate the risk of depression and anxiety [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Previous research has demonstrated that diet can influence mental well-being by modulating inflammation, oxidative stress, gut microbiota, and other biological pathways [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, prior investigations primarily focused on examining the health effects of individual nutrients or foods. Yet, it is crucial to acknowledge that a single food item or nutrient cannot adequately capture the intricate relationship between overall diet and health outcomes. Given that daily diets encompass a diverse range of foods with potential interactions among multiple nutrients present within them, relying solely on isolated components may yield inaccurate findings [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConsequently, dietary patterns (DPs) offer a comprehensive approach to analyze the association between diet and anxiety as well as depression from a holistic perspective. For instance, traditional dietary patterns distinguished by elevated intake of vegetables, fruits, meat, fish, and whole grains have been linked to reduced risks of major depression and anxiety disorders; conversely Western-style dietary patterns dominated by processed foods, refined grains sugary items along with alcohol intake are associated with an increased likelihood of psychological disorders [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Furthermore, pregnant women exhibit higher demands for optimal diet quality compared to the general population. Unfortunately, limited research has paid attention to pregnant women. Hence, it is crucial to explore the correlation between DPs and symptoms related to anxiety and depression in pregnant women.\u003c/p\u003e"},{"header":"2. Materials \u0026 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study population\u003c/h2\u003e \u003cp\u003eThe data were derived from the Chinese Maternal Nutrition and Health Survey, a cross-sectional study that remains ongoing. This investigation exclusively involved participants at the Hunan Provincial Maternal and Child Health Hospital, from July 2022 to July 2023. Before commencing the survey, a consent form was duly signed by all participants. Among the pregnant women attending this hospital, we consecutively selected those aged 18 to 49 years, who had been residing in the local area for over 12 months, and volunteered to take part. Individuals with mental illness, language communication disorders, or those who refused to participate in it were not included in this survey.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Dietary assessment\u003c/h2\u003e \u003cp\u003eThe dietary intake of pregnant women were evaluated over the previous month by means of a Food Frequency Questionnaire (FFQ), which examined the frequency and amount of different food categories. Food intake was estimated using food models, and standardized cutlery. Based on the frequency of food intake (times/month, times/week, times/day) and the amount consumed each time, the intake of each food type (g/day or ml/day) was calculated. Considering the dietary habits of the Hunan region, 14 food groups were included: refined grains, whole grains, vegetables, fruits, meat, aquatic products, soybeans and their products, milk and its derivatives, eggs, nuts, fried foods, processed meats, pickled vegetables, and other processed products (including sweets, desserts, instant noodles, and snacks).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Ascertainment of outcomes\u003c/h2\u003e \u003cp\u003eThe Edinburgh Postnatal Depression Scale (EPDS) has 10 questions and can be utilized as a tool for assessing depression. The EPDS was scored from \"0\" (never) to \"3\" (always) using a Likert4 scale. By setting a threshold score of 9, we classified depressive symptoms into three levels based on scores of 12 and 14, with elevated scores denoting increased levels of depression [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The EPDS has shown favorable reliability and validity in screening for depression in pregnant women. Meanwhile, the self-rating Anxiety Scale (SAS) was employed to gauge the subjective anxiety levels of the participants. This scale comprises 20 items that are categorized into positive ratings and reverse scores, ranging from \"1\" (indicating minimal or no anxiety) to \"4\" (representing frequent or persistent anxiety). The total score was multiplied by 1.25 and rounded down to obtain the standard score. A standard score of 50 or below indicated the absence of anxiety symptoms, while scores between 60 and 70 were categorized as mild, moderate, and severe anxiety symptoms respectively. The SAS scale demonstrated high reliability and validity [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Ascertainment of covariates\u003c/h2\u003e \u003cp\u003eThe collection of data on various variables was accomplished using a self-defined basic information questionnaire. These variables encompassed demographic information (including age, education level, occupation, employment status while pregnant, and per capita monthly income of the household), social psychological information (including medical history, marital relationship, and relationship with parents), and health behavior information (pre-pregnancy BMI, exercise, insomnia, smoking, alcohol consumption). Additionally, data was gathered on pregnancy and childbirth-related factors (pregnancy duration, mode of conception, number of fetuses, number of deliveries, adverse pregnancy history, early pregnancy reaction, vaginal bleeding, and pregnancy preservation). Covariates (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) incorporated into the regression model were selected based on the results of the χ\u0026sup2; test or Fisher's exact test (refer to additional file 1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e \u003cp\u003eFactor analysis was used to extract DPs, and its applicability was determined according to Kaiser-Meyer-Olkin Measure of Sample Adequacy (KMO)value and Bartlett spherical test results. The number of extracted factors was ascertained by combining the matrix eigenvalue\u0026thinsp;\u0026gt;\u0026thinsp;1 and factor interpretability. A total of 14 food groups were incorporated into the variable model, with the factor component matrix rotated by the maximum variance method. This rotation enabled the reflection of the correlation between food groups and DPs through the rotated factor loading. In this study, factor loading\u0026thinsp;\u0026gt;\u0026thinsp;0.30 was used as the basis to determine the extracted common factors as the main dominating variables of DPs. Regression analysis was employed to calculate factor scores for each participant across dietary patterns, with higher scores indicating a greater consumption of such foods in this dietary pattern. Finally, the factor scores of each participant were classified into low (T1), medium (T2), and high (T3) levels using the tertile method, from lowest to highest.\u003c/p\u003e \u003cp\u003eSPSS 20.0 was utilized for statistical analysis, with the test level established at 0.05. Univariate analysis was executed using χ\u003csup\u003e2\u003c/sup\u003e test or Fisher's exact test. After controlling for confounding variables, we utilized a multi-factor logistic regression approach to explore the correlation between DPs and anxiety and depression during pregnancy (enter 0.05, delete 0.10). The reference group was defined as T1.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Baseline characteristics\u003c/h2\u003e \u003cp\u003eA survey was conducted with the participation of 892 pregnant women, whose average age was 30.9 years. Baseline characteristics of the study population are provided in Additional file 1, categorized according to depressive and anxiety symptoms. Notable disparities were observed in the prevalence of anxiety among pregnant women from varying occupational backgrounds, with a history of spontaneous abortion, and those who had congenital malformations (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Specifically, the highest incidence of anxiety was noted in expectant mothers employed in agriculture, forestry, animal husbandry, fishery, and water conservancy (33.3%), those with a history of spontaneous abortion (24.5%), and those with a history of congenital malformations (50%). Similarly, considerable differences were observed in the occurrence of depression among expectant mothers with varying working conditions, sleep disturbances, spousal relationships, and relationships with parents. Among these factors, the highest prevalence of depression was observed in expectant mothers with increased workload (100.0%), frequent insomnia in the past month (72.7%), frequent insomnia in the first three months of pregnancy (76.4%), poor marital relationships (100.0%), and strained parent-child relationships (80.0%).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Symptoms of anxiety and depression\u003c/h2\u003e \u003cp\u003e150 (16.8%) pregnant women exhibited anxiety symptoms, with 129 (14.5%) experiencing mild anxiety, 18 (2.0%) displaying moderate anxiety, and 3 (0.3%) suffering from severe anxiety. Of the 458 (51.3%) pregnant women who presented depressive symptoms, 212 (23.8%) had mild depression, 108 (12.1%) experienced moderate depression, and 138 (15.5%) exhibited severe depression.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Characteristics of DPs\u003c/h2\u003e \u003cp\u003eThe factor analysis method revealed the identification of five dietary patterns, with KMO\u0026thinsp;=\u0026thinsp;0.648 and Bartlett's spherical test (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;830.635, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).The results revealed a significant association among different food groups, suggesting that factor analysis could be employed to analyze the collected data. The extracted factors, characterized by a matrix eigenvalue\u0026thinsp;\u0026gt;\u0026thinsp;1, were determined using the maximum variance method. The eigenvalues and contribution rates of the five factors were 2.125 (15.180%), 1.594 (11.385%), 1.199 (8.561%), 1.072 (7.656%), and 1.062 (7.588%), respectively, with a cumulative contribution rate of 50.370%. DP1 was primarily composed of dairy products, eggs, and nuts. DP2 was dominated by vegetables, whole grains, soybeans and their products, nuts, and aquatic products. DP3 was characterized by processed meats, fried foods, other processed products (including sweets, desserts, instant noodles, snacks), and pickled vegetables. DP4 was mainly composed of refined grains, fruits, whole grains, and other processed products. DP5 was dominated by meat, aquatic products, and nuts. Figure\u0026nbsp;1 illustrates the loading factors and distribution of dietary patterns for each group.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Correlations between DPs and symptoms of depression and anxiety\u003c/h2\u003e \u003cp\u003eWith anxiety symptoms (0\u0026thinsp;=\u0026thinsp;no, 1\u0026thinsp;=\u0026thinsp;yes) as the dependent variable, Fig.\u0026nbsp;2 depicts the effect of DPs on anxiety symptoms, highlighting a significant correlation between DP3 and anxiety symptoms. The results are depicted in Fig.\u0026nbsp;3 after controlling for the effects of occupation, history of spontaneous abortion, and history of deformed children. DP3 increases the likelihood of experiencing anxiety while pregnant (T3:T1, OR\u0026thinsp;=\u0026thinsp;1.637, 95%CI: 1.064\u0026ndash;2.519). DP1, DP2, DP4, and DP5 showed no significant correlation with anxiety symptoms. With depressive symptoms (0\u0026thinsp;=\u0026thinsp;no, 1\u0026thinsp;=\u0026thinsp;yes) as the dependent variable, Fig.\u0026nbsp;2 illustrates the influence of DPs on depressive symptoms, revealing a notable correlation between DP1 and depressive symptoms. After accounting for the impact of work situation, insomnia in the last month, insomnia in the first three months of pregnancy, marital relationship, and relationship with parents, the results are presented in Fig.\u0026nbsp;3. DP1 is a hazard factor for depressive symptoms during pregnancy (T3:T1, OR\u0026thinsp;=\u0026thinsp;1.483, 95%CI: 1.046\u0026ndash;2.104). DP2, DP3, DP4, and DP5 demonstrated no significant correlation with depressive symptoms.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe prevalence of prenatal anxiety in this study was determined to be 16.8%, which was higher than that in Shanghai (11.1%) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] and Chongqing (15.04%) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], while remaining lower than the overall prevalence of self-reported anxiety in many countries in the world (22.9%) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. These differences may be related to variations in measurement methodologies employed and regional disparities.\u003c/p\u003e \u003cp\u003eHowever, We discovered that the prevalence of prenatal depression exceeded rates observed in numerous other countries and regions, reaching 51.3%. The prevalence of depression in Shanghai was 10.3% [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and that in Chongqing was 5.19% [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Furthermore, a worldwide investigation revealed that the occurrence of prenatal depression was 20.7% [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This discrepancy could potentially be attributed to the investigation of symptoms rather than diseases and the use of self-report rating scales rather than structured interviews for assessment [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAfter accounting for possible confounding factors, the results indicated a positive correlation between DP3 and anxiety during pregnancy. It is distinguished by excessive consumption of processed meats, fried foods, other processed products (including sweets, desserts, instant noodles, and snacks), and pickled vegetables. This finding aligns with epidemiological research indicating that psychological disorders in women are more likely to occur when their diets primarily consist of processed or fried foods, sugary foods, and refined grains [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Individuals with more severe anxiety exhibit fewer healthy food choices and a higher consumption of energy-dense foods [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Similarly, an increased consumption of snacks may elevate the likelihood of anxiety development [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Furthermore, pickled vegetables possess reduced antioxidants, vitamins, and minerals compared to fresh vegetables. Pickled vegetables are often contaminated with N-nitroso compounds, which increase nitrite content and may impair human health [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. However, existing studies have not detected any significant impact of pickled vegetables on mental well-being. Further research is necessary to establish a conclusive link between this dietary pattern and anxiety levels during pregnancy.\u003c/p\u003e \u003cp\u003eIn the context of depression during pregnancy, our research identified a positive correlation between DP1 and the likelihood of depression. This dietary pattern is distinguished by an elevated consumption of milk and its derivatives, eggs, and nuts. In single-food group studies, an increased consumption of nuts may serve as a preventative measure against the development of depression [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Egg consumption may be associated with a reduced likelihood of experiencing symptoms related to depression [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Different varieties of milk and the nutritional composition of dairy products can have varying impacts on symptoms associated with depression. Multiple studies have demonstrated that healthy dietary patterns consistent with current dietary recommendations, including recommended intakes of foods such as eggs, low-fat dairy products, nuts, etc., may alleviate depressive symptoms in both people without depression and clinically depressed patients [\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Higher diet quality is a protective factor for depressive symptoms [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Fermented dairy products have the potential to modulate mood by influencing the pathway between the brain and gut, leading to a decreased likelihood of experiencing depression [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. However, there is alternative research suggesting that an increased consumption of protein could potentially be linked to the emergence of severe depression among females [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Contrary to low-fat milk, whole milk posed a risk for experiencing symptoms of depression [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In summary, our study findings diverge from previous research and warrant further investigation.\u003c/p\u003e \u003cp\u003eIn addition, it is crucial to recognize the constraints of this research. Firstly, given its cross-sectional design, we are unable to establish a definitive causal relationship. It is possible that anxiety and depression may have induced changes in dietary intake among participants, and diet quality might have arisen as a consequence of psychological symptoms rather than a contributing factor. Consequently, further prospective studies are warranted. Secondly, we requested pregnant women to reminisce about their diet over the past month, which is often prone to recall bias and may lead to an inaccurate estimation of actual food intake. Thirdly, the factor analysis revealed subjectivity in dietary patterns that could have influenced the results. Given the constraints of sample selection and the inability to establish causal relationships, additional research is necessary to investigate the correlation between dietary patterns and symptoms of anxiety and depression during pregnancy. This can be achieved by selecting subjects from various hospitals and regions, as well as conducting longitudinal studies.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eIn summary, our findings suggest that a dietary pattern consisting of processed meats, fried foods, sweets, desserts, instant noodles, snacks, and pickled vegetables may elevate the risk of anxiety during pregnancy. Conversely, a diet dominated by dairy products, eggs, and nuts seems to be associated with an elevated risk of developing depression while being pregnant. Our results emphasize that pregnant women should reduce their consumption of processed foods, foods containing free sugars, fried foods, and preserved vegetables. Future studies should focus on investigating the specific effects of different types of dairy products on depression during pregnancy and exploring potential interactions between milk consumption and egg/nut intake.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003edietary patterns (DPs)\u003c/p\u003e\n\u003cp\u003eFood Frequency Questionnaire (FFQ)\u003c/p\u003e\n\u003cp\u003eThe Edinburgh Postnatal Depression Scale (EPDS)\u003c/p\u003e\n\u003cp\u003ethe self-rating Anxiety Scale (SAS)\u003c/p\u003e\n\u003cp\u003eKaiser-Meyer-Olkin Measure of Sample Adequacy (KMO)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe Chinese Maternal Nutrition and Health Survey was approved by the Research Ethics Committee of Hunan Provincial Maternal and Child Health Care Hospital (202153). All the participants provided written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by National Science and Technology Basic Resources Special Project of China (2019FY101000). The funding source was not involved in the study design, analysis, interpretation of the data, writing the manuscript or in the decision to submit the manuscript for publication.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthors' contributions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eRusi Yang: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing-original draft, Writing-review \u0026amp; editing. Panzi Yang: Conceptualization, Validation, Writing-review \u0026amp; editing. Yangzhenlin Luo: Investigation, Writing-review \u0026amp; editing. Yixin Zhang: Investigation, Writing-review \u0026amp; editing. Zhaolong Xie: Investigation, Writing-review \u0026amp; editing. Ming Hu: Conceptualization, Methodology, Writing-review \u0026amp; editing. Guilian Yang: Resources, Supervision, Funding acquisition, Project administration, Writing-review \u0026amp; editing. All authors critically evaluated and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFerrari AJ, Santomauro DF, Herrera AMM, Shadid J, Ashbaugh C, Erskine HE, et al. Global, regional, and national burden of 12 mental disorders in 204 countries and territories, 1990\u0026ndash;2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Psychiatry. 2022;9(2):137\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOrganization WH. Depression and other common mental disorders: global health estimates. World Health Organization; 2017.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStaneva A, Bogossian F, Pritchard M, Wittkowski A. 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JAMA. 1992;267(11):1478\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFellenzer JL, Cibula DA. Intendedness of Pregnancy and Other Predictive Factors for Symptoms of Prenatal Depression in a Population-Based Study. Matern Child Health J. 2014;18(10):2426\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTang X, Lu Z, Hu D, Zhong X. Influencing factors for prenatal Stress, anxiety and depression in early pregnancy among women in Chongqing, China. J Affect Disord. 2019;253:292\u0026ndash;302.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePampaka D, Papatheodorou SI, AlSeaidan M, Al Wotayan R, Wright RJ, Buring JE, et al. Depressive symptoms and comorbid problems in pregnancy - results from a population based study. J Psychosom Res. 2018;112:53\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCouto ER, Couto E, Vian B, Gregorio Z, Nomura ML, Zaccaria R, et al. 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Br J Psychiatry. 2017;210(5):315\u0026ndash;.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYin X, Sun N, Jiang N, Xu X, Gan Y, Zhang J et al. Prevalence and associated factors of antenatal depression: Systematic reviews and meta-analyses. Clin Psychol Rev. 2021;83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBennett HA, Einarson A, Taddio A, Koren G, Einarson TR. Prevalence of depression during pregnancy: Systematic review. Obstet Gynecol. 2004;103(4):698\u0026ndash;709.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHosseinzadeh M, Vafa M, Esmaillzadeh A, Feizi A, Majdzadeh R, Afshar H, et al. Empirically derived dietary patterns in relation to psychological disorders. Public Health Nutr. 2016;19(2):204\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eForsyth AK, Williams PG, Deane FP. Nutrition status of primary care patients with depression and anxiety. 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Nutrition. 2012;28(9):896\u0026ndash;900.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMolendijk M, Molero P, Ortuno Sanchez-Pedreno F, Van der Does W, Angel Martinez-Gonzalez M. Diet quality and depression risk: A systematic review and dose-response meta-analysis of prospective studies. J Affect Disord. 2018;226:346\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuo Y, Li Z, Gu L, Zhang K. Fermented dairy foods consumption and depressive symptoms: A meta-analysis of cohort studies. PLoS ONE. 2023;18(2).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWolfe AR, Arroyo C, Tedders SH, Li Y, Dai Q, Zhang J. Dietary protein and protein-rich food in relation to severely depressed mood: a 10 year follow-up of a national cohort. Prog Neuropsychopharmacol Biol Psychiatry. 2011;35(1):232\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun J, Wang W, Zhang D. Associations of different types of dairy intakes with depressive symptoms in adults. J Affect Disord. 2020;274:326\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Dietary patterns, Factor analysis, Pregnancy anxiety, Pregnancy depression","lastPublishedDoi":"10.21203/rs.3.rs-3831840/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3831840/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDietary intake plays a significant role in mental health. Our objective was to examine the association of dietary patterns (DPs) with anxiety and depressive symptoms in pregnant women.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis study was a cross-sectional study conducted in Hunan Province. Food frequency questionnaire, Self-rating Anxiety Scale and the Edinburgh Postnatal Depression Scale were used. Dietary patterns were identified through the utilization of factor analysis. The correlation analysis employed logistic regression.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe detection rates of anxiety and depression symptoms during pregnancy were 16.8% and 51.3%, respectively. We have identified five DPs in this study. After accounting for possible confounding factors, a positive correlation was found between DP3 and the risk of anxiety (T3:T1, OR\u0026thinsp;=\u0026thinsp;1.637, 95%CI:1.064\u0026ndash;2.519). However, no significant correlations were observed between DP1, DP2, DP4, or DP5 and anxiety symptoms. Additionally, a positive correlation was identified between DP1 and the risk of depression (T3:T1, OR\u0026thinsp;=\u0026thinsp;1.483, 95%CI: 1.046\u0026ndash;2.104). While no significant associations were found between DP2, DP3, DP4 or DP5 and depressive symptoms.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis study indicates that the dietary pattern high in processed meats, fried foods, sweets, desserts, instant noodles, snacks, and pickled vegetables may potentially elevate the risk of anxiety during pregnancy. The dietary pattern dominated by milk and its products, eggs and nuts may increase the risk of depression during pregnancy.\u003c/p\u003e","manuscriptTitle":"Association of dietary patterns with anxiety and depressive symptoms during pregnancy: a cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-05 10:22:25","doi":"10.21203/rs.3.rs-3831840/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"249b3d08-beaa-4f4e-a13c-75889ab3d2a3","owner":[],"postedDate":"January 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-01-11T16:44:22+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-05 10:22:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3831840","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3831840","identity":"rs-3831840","version":["v1"]},"buildId":"oE6Zbj460LM0Up2FdVbMZ","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}