{"paper_id":"1bd134b5-d59e-409e-aecd-1b82217fd68c","body_text":"Effect of maternal Mala flavor preference on gestational weight gain mediated by dietary patterns in Chongqing, China: an ambispective cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effect of maternal Mala flavor preference on gestational weight gain mediated by dietary patterns in Chongqing, China: an ambispective cohort study Jing Hua Li, Di Fei Wang, Yan Yan Mao, Wu Xia Zhang, Qian Xi Zhu, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3893577/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Taste preference drives food selection, acceptance, or rejection, and influences body mass index. This study aimed to analyze the correlation of dietary status, encompassing taste preference and dietary pattern, with gestational weight gain (GWG) among pregnant women. Methods We conducted an ambispective cohort study at the Kaizhou District Maternal and Child Health Hospital in Chongqing, China. In total, 495 pregnant women aged 20–45 years who conceived naturally were recruited from May 2021 to November 2022. They had single pregnancies, no history of chronic medical and surgical diseases, and no pregnancy complications. Data on food category intake and taste preference, including fatty, salty, spicy, and Mala flavors, were collected during the third trimester. Factor analysis was used to evaluate dietary pattern. Multiple linear regression and structural equation modeling were performed to explore the relationship between taste preference and dietary pattern as well as their effects on GWG. Results “Traditional Diets” (TD) are characterized by high intakes of cereals, vegetables, fruits, meats, and dairy. “Modern Diets” (MD) are characterized by high intakes of cereals, vegetables, beans, meats, poultries, and seafood. “Quality Protein Diets” (QPD) are characterized by high intakes of seafood, eggs, and dairy. Pregnant women with a preference for Mala flavor had higher TD, MD, and QPD scores. Women with a higher TD or MD score had a higher GWG. The Mala taste preference effect on GWG was partially (41.7%) mediated by TD and MD. Conclusions Preference for Mala as the typical flavor in Chongqing has a positive effect on GWG, partially mediated by TD and MD, both of which are loaded with high amounts of cereals with high-glycemic index. Pregnant women in local areas should appropriately modify their Mala taste preference based on their current weight to maintain a reasonable GWG. pregnant women dietary patterns taste preference gestational weight gain mediation analysis Figures Figure 1 Figure 2 Background The “Developmental Origins of Health and Disease” theory proposes that nutritional status in early life affects the development of chronic conditions such as hypertension, diabetes, and cardiovascular disease in adulthood ( 1 ). Gestational weight gain (GWG) is a direct indicator of maternal nutritional status and an independent predictor of perinatal and long-term outcomes in both mother and infant ( 2 ). Research indicates that insufficient GWG may increase the risk of small for gestational age and low birth weight in infants, whereas excessive GWG may lead to the development of conditions such as pregnancy-induced hypertension syndrome, preeclampsia, gestational diabetes mellitus, large for gestational age, and need for Cesarean section ( 3 – 5 ). Moreover, excessive GWG can have long-term health consequences, contributing to conditions such as diabetes and cardiovascular issues in later life in women and childhood obesity in offspring ( 6 – 8 ). Nutrition is particularly important during pregnancy, as it not only affects the health of the mother but also profoundly influences the growth and development of the fetus ( 9 ). A well-rounded diet and balanced diet serve as the cornerstones for controlling GWG and preventing pregnancy-related diseases ( 10 ). Compared with the conventional approach of analyzing individual foods or nutrients, analyzing dietary patterns is more effective for evaluating dietary status ( 11 ). A recent Danish study highlighted the benefits of consuming a high-protein, low-glycemic index diet in reducing GWG and minimizing complications, including lowering the incidence of Cesarean deliveries in overweight or obese women ( 12 ). In another (retrospective) study, a negative association was observed between GWG and the Mediterranean dietary pattern, which is dominated by a high intake of vegetables, whole cereals, nuts, fish, and olive oil and a low intake of refined cereals, snacks, and desserts ( 13 ). Findings from another (prospective cohort) study conducted in central China indicated that a dietary pattern enriched in beans and vegetables is advantageous for effectively managing GWG and promoting increased birth weight ( 14 ). Recent studies have sought to determine whether associations exist between certain tastes, food intake, and obesity. A systematic review scrutinized 19 articles, and disclosed a potential link between obesity and taste preferences, with moderate preference for salty, bitter, and fatty flavors and higher preference for sour flavors ( 15 ). To date, there is a dearth of research examining the relationship between taste preference and GWG. Local residents in Chongqing in southwest China developed a distinctive Sichuan cuisine known for comprising Chinese prickly ash and chili, creating a distinctive “Mala” sensation in local dishes ( 16 ). According to a study, individuals in Chongqing tend to consume excessive amounts of red meat, cooking oil, and salt but low amounts of vegetables and fruits ( 17 ). There are few reports on the dietary status of pregnant women and no relevant reports on the relationship between diet and GWG in Chongqing, hindering the development of appropriate local nutritional intervention strategies. Therefore, we aimed to assess the relationship between dietary status, encompassing taste preferences and dietary patterns, and GWG among pregnant women in Chongqing. Methods Population and study design This ambispective cohort study was conducted at Chongqing Kaizhou District Maternal and Child Health Hospital, China. Pregnant women aged 20–45 years who initiated routine prenatal care in the hospital’s obstetrics department at 24–27 gestational weeks and were expected to deliver at the hospital were invited to enroll in the cohort from May 2021 to November 2022. The exclusion criteria were women who had undergone assisted reproductive technology (ART; e.g., ovulation induction, in vitro fertilization, intracytoplasmic sperm injection treatment, or intrauterine insemination); had chronic medical and surgical diseases or pregnancy complications; were confirmed to have multiple pregnancies; or had cognitive impairment, dementia, or severe mental illness. Of the 635 pregnant women screened, 135 were excluded for intending to deliver at a different hospital (n = 3), undergoing ART (n = 1), having multiple pregnancies (n = 2), and having chronic medical disease (n = 129). Of the remaining five hundred pregnant women, three were lost to follow-up and two had stillbirths. Therefore, a final sample of 495 women was analyzed. The ethics committee of the Chongqing Kaizhou District Maternal and Child Health Hospital approved this study. Written informed consent was obtained from all the participants. Data collection The participants were interviewed by trained obstetric nurses three times: at enrollment (24–27 gestational weeks), during the third trimester (32–36 gestational weeks), and at the time of delivery. Demographic information was collected at the time of enrollment. Data on dietary status, including taste preference and food intake over the previous month, were collected at 32–36 gestational weeks. Pregnancy outcomes were recorded at delivery. GWG was calculated by subtracting the pre-pregnancy weight from the weight at the end of pregnancy. Taste preference—fatty, salty, spicy, or Mala flavor—was recorded. The degree of preference was categorized as no or light, medium, or heavy. A simplified, self-designed food frequency questionnaire (FFQ) was used to gather information on dietary intake during pregnancy. The FFQ comprises 15 food items covering nine distinct categories: cereals, vegetables, fruits, beans, meat, poultry, aquatic products, eggs, and dairy. For each food item in the FFQ, participants reported the frequency of consumption and portion size. Statistical analyses GWG and daily food intake are presented as mean ± standard deviation (SD). Analysis of variance (ANOVA) was used to assess the mean differences among various characteristic groups. Taste preference was presented as frequency and proportion. Due to low frequency, heavy taste preference was combined with the medium category for analysis. Dietary intake was assessed based on the Chinese Balanced Dietary Pagoda (CBDP, 2022 version) for pregnant women. The CBDP was been established and updated by the Chinese Nutrition Association to provide guidance on the dietary intake of Chinese residents. Major dietary patterns were extracted from nine food categories by factor analysis using the principal component analysis (PCA) method, a tool commonly employed to extract a posteriori dietary pattern. Kaiser-Meyer-Olkin (KMO) and Bartlett's spherical tests were used to determine whether the data met the analysis requirements. Varimax with Kaiser normalization rotation was applied to reduce correlations between factors and increase the interpretability of the results. Food categories with a factor loading >|0.30| were included with present foods strongly associated with the identified factors. Association between taste preference, dietary pattern, and GWG was analyzed using multiple linear regression model, adjusting for potential confounders that were selected based on ANOVA. The mediating effect of dietary patterns on the relationship between taste preference and GWG was examined using structural equation modeling (SEM). Statistical analysis was performed using R software version 4.3.1 (Foundation for Statistical Computing, Vienna, Austria), with a two-tailed significance level set at P < 0.05 (two-tailed) for all analyses. Results Demography of pregnant women The pregnant women in this study had an average age of 27.8 (± 4.4) years, with a mean pre-pregnancy body mass index (BMI) of 21.4 (± 2.7 kg/m 2 ). More than one-third were primiparas (36.0%), and the majority were from agricultural households (73.9%). Additionally, more than half had a junior high school education or below (51.3%), and the majority did not hold official employment roles (71.9%). Pregnant women gained an average of 14.0 (± 4.9) kg throughout their pregnancy. Of the total participants, 23.5% experienced inadequate GWG and 30.4% dealt with excessive GWG, based on Institute of Medicine guidelines ( 18 ). Table 1 presents the distribution of GWG across the different demographic characteristics of pregnant women. We noted a difference in GWG among the three pre-pregnancy BMI groups. Table 1 Gestational weight gain according to the distinctive characteristics of pregnant women in Chongqing. Variations Number GWG(kg) P N (%) Mean ± SD 1 Age, y 0.618 ~ 25 136 (27.5) 13.7 ± 5.9 ~ 30 222 (44.8) 14.3 ± 4.4 > 30 137 (27.7) 14.0 ± 4.7 Pre-pregnancy BMI, kg/m 2 < 0.001 < 18.5 55 (11.1) 14.7 ± 3.0 18.5 ~ 23.9 358 (72.5) 14.6 ± 4.7 ≥ 24 81 (16.4) 11.4 ± 5.8 Gravidity 0.051 1 178 (36.0) 14.6 ± 4.9 > 1 317 (64.0) 13.7 ± 4.9 Place of residence 0.174 Agricultural 366 (73.9) 13.9 ± 4.9 Non-Agricultural 129 (26.1) 14.6 ± 4.9 Educational qualifications 0.381 Junior high school or below 254 (51.3) 13.8 ± 5.3 Senior high school 141 (28.5) 14.0 ± 4.4 University and above 100 (20.2) 14.6 ± 4.6 Occupation Farmer 24 (4.8) 12.4 ± 5.6 0.133 Business/Working 42 (8.5) 14.7 ± 4.0 Teachers/civil servants/staff 55 (11.1) 14.6 ± 3.9 Unemployed 356 (71.9) 14.1 ± 5.0 Others 18 (3.6) 12.2 ± 5.4 1 SD, standard deviation; GWG, gestational weight gain Dietary status of pregnant women Taste preferences and daily food intakes are shown in Fig. 1 and Table 2 , respectively. Most pregnant women had medium or heavy taste preferences for fatty, salty, and spicy flavors (82.2%, 77.6%, and 62.5%, respectively) and no or light taste preferences for Mala flavors (73.5%). Daily intake of cereals, meat, poultry, and eggs approached or exceeded the recommended levels. Intakes of vegetables, beans, and aquatic products fell significantly short, with less than 60% of the participants meeting the minimum recommended intake for these food categories. Table 2 Daily food category intakes of pregnant women in Chongqing Food categories Recommended dietary intakes (g) Mean ± SD 1 Actual dietary intakes (g) Relative intake (%) 2 Cereals 225–275 214.4 ± 108.5 95 ± 48 Vegetables 400–500 83.4 ± 70.1 21 ± 18 Fruits 200–350 129.0 ± 111.3 65 ± 56 Beans 20 10.5 ± 13.6 53 ± 68 Meats and Poultries 50–75 43.9 ± 47.4 129 ± 112 Aquatic products 75–100 12.8 ± 17.3 17 ± 23 Eggs 50 50.2 ± 27.0 101 ± 54 Dairy 300–500 205.6 ± 93.2 69 ± 31 1 SD, standard deviation 2 Relative intake was calculated as a percentage of the minimum recommended intake. In the factor analysis, the KMO test statistic yielded a value of 0.695, and the Bartlett spherical test demonstrated significance with P < 0.001, indicating that the dataset was suitable for factor analysis. According to the Kaiser criterion—an Eigen value of > 1—three dietary patterns were extracted, with a total variance contribution of 55.9%. Factor 1, accounting for 20.8% of the total variance, is labelled as “Traditional diet” (TD) and characterized by high intakes of cereals, vegetables, fruits, meats, and dairy. Factor 2, accounting for 17.8% of the total variance, is labelled as “Modern diet” (MD) and characterized by high intakes of cereals, vegetables, beans, meats, poultries, and aquatic products. Factor 3, accounting for 17.4% of total variance, is labelled as “Quality protein diet” (QPD) and characterized by high intakes of aquatic products, eggs, and dairy (Table 3 ). Table 3 Factor analysis of dietary patterns among pregnant women in Chongqing Food categories Factor 1 (Traditional diet) Factor 2 (Modern diet) Factor 3 (Quality protein diet) Cereals 0.679 0.366 Vegetables 0.441 0.589 Fruits 0.703 Beans 0.678 Meats 0.550 0.338 Poultry 0.594 Aquatic products 0.372 0.676 Eggs 0.859 Dairy 0.616 0.477 Relationship between taste preference, dietary pattern, and GWG Table 4 indicates that women with a medium or heavy preference for fatty or salty flavors had a lower MD or TD score. Women with a medium or heavy preference for spicy or Mala flavors had higher TD, MD, and QDP scores. In Table 5 , after adjusting for pre-pregnancy BMI, women with a medium or heavy preference for Mala flavors had a higher GWG (Table 5 ). Additionally, women with a higher TD or MD score also exhibited higher GWG. Table 4 Association between taste preferences and dietary patterns among pregnant women in Chongqing Independent variables* Traditional diet Modern diet Quality protein diet β P β P β P Fatty 0.193 0.227 -0.391 0.011 -0.010 0.955 Salty -0.543 < 0.001 -0.156 0.283 0.031 0.849 Spicy 0.207 0.033 0.295 0.002 -0.263 0.011 Numbing-spicy 0.698 < 0.001 0.868 < 0.001 0.227 0.038 *: Taste preference value, non or light = 0; medium or heavy = 1 Table 5 Association between dietary status and gestational weight gain among pregnant women in Chongqing Independent variables β P Taste preference 1 Fatty -1.039 0.198 Salty -0.562 0.465 Spicy 0.509 0.300 Numbing-spicy 1.545 0.003 Dietary pattern 2 Traditional diet 0.542 0.012 Modern diet 0.553 0.010 Quality protein diet 0.359 0.095 1 Adjusted for pre-pregnancy BMI and other taste preferences: taste preference value, light = 0; medium/heavy = 1. 2 Adjusted for pre-pregnancy BMI, and other dietary patterns. The mediation analysis demonstrated the model containing the independent (GWG), dependent (numbing-spicy taste preference), and mediator (TD and MD) variables was within acceptable fit (CFI = 0.959, TLI = 0.876, RMSEA = 0.067, SRMR = 0.032). As shown in Fig. 2 , SEM pathway analysis revealed that the effect of numbing-spicy taste preference on GWG (β = 1.437, P = 0.003) was partially mediated by TD and MD (β = 0.305, P = 0.057, and β = 0.371, P = 0.071 respectively). The total indirect effect (β 0.599, P = 0.012) accounted for 41.7% of variance. Discussion The occurrence of GWG surpassing the recommended levels in approximately half of pregnancies is often attributed to unhealthy lifestyles and unbalanced diets ( 19 ). Excess GWG is linked to increased risk of adverse maternal and neonatal outcomes ( 20 , 21 ). Data from China indicate that 30–50% of women experience excessive GWG ( 22 ). Multiple interventions including diet, physical activity, and combinations have been proposed to address this issue ( 23 ). A meta-analysis showed that dietary interventions are associated with reduced GWG and exert a more significant impact than physical activity alone ( 24 ). Strategies for dietary interventions in weight management should focus on reducing energy intake and consider dietary patterns related to differences in food accessibility, eating behaviors, taste preferences, and cultural background ( 25 ). A comprehensive understanding of regional dietary intake elements is crucial for devising targeted dietary interventions to prevent excessive GWG. In the current study, we evaluated dietary intake and taste preference among pregnant women in Chongqing and their impacts on GWG. Our results showed that food intake during pregnancy was notably inadequate, except for cereals, meats/poultries, and eggs, with less than 70% of the recommended minimum intake based on the CBDP. This is consistent with the 2018 Chongqing Residents’ Health Status report ( 17 ). An unbalanced diet heavily laden with carbohydrates has been reported to be associated with weight gain and obesity in Asia ( 26 ). This explains why, despite inadequate dietary intake, there are still quite a few cases of excessive GWG in Chongqing (30.4%). Using the PCA method, we identified three dietary patterns: TD, MD, and QPD. Linear regression analysis revealed that pregnant women adhering to a TD or MD, but not a QPD, experienced greater GWG. Our results are similar to those of Danish study that low-glycemic index and high-protein diet reduced GWG ( 13 ). TD and MD are both characterized by high intakes of cereals, often consisting of refined carbohydrate with high-glycemic indexes. Another prospective study in Central China showed that women following a fish-meat-egg, rice-wheat-fruit diet during the second trimester of pregnancy had a significantly higher GWG ( 14 ). Taste influences nutritional status and health. A recent systematic review evaluated the relationship between weight status and the perception of and preference for four common tastes (sweet, salty, fatty, bitter, and sour) by reviewing observational and interventional studies ( 27 ). The findings indicate that adults with overweight and obesity exhibit decreased perceptions of the four tastes and that preferences for sweetness and fat increase with weight gain ( 27 ). There is no consensus in the literature regarding the effects of spiciness on obesity. One prospective study from China suggests that high intake of spicy food is positively associated with energy intake but is inversely associated with the risk of overweight or obesity ( 28 ). A beneficial effect of spicy food consumption on weight management has been demonstrated in intervention studies with small sample sizes from Western countries ( 29 ). However, a recent meta-analysis of cross-sectional studies shows that spiciness may adversely affect overweight or obesity ( 30 ). Regarding taste preference during pregnancy, only sugar consumption has been reported to contribute to increased GWG and the development of pregnancy complications ( 31 ). In our present study, we investigated four taste preferences of pregnant women, including fatty, salty, spicy, and Mala flavors, and found that pregnant women who preferred the Mala flavor (but not fatty, salty, or spicy flavors) exhibited higher GWG. Among pregnant women with no or light preference for Mala flavor, the rate of excessive GWG was 27.4%, whereas the rate among women with a medium or heavy preference was 38.8%. Further analysis showed that the positive effect of numbing-spicy flavor on GWG was partially mediated by TD and MD. Unlike the simple spicy flavor found in other Chinese cuisines, the Mala evoked by Chinese prickly ash combined with chili peppers constitutes the distinctive feature of Sichuan cuisine ( 32 ). This Mala sensation in the mouth further affect the mediation and recognition of tastes, stimulating appetite. Our findings indicate that women who preferred Mala flavors scored higher on all three dietary patterns. It is worth mentioning that a QPD did not significantly increase GWG, indicating that it is a more favorable food choice to provide necessary nutrients and help manage weight gain during pregnancy. Our study provides an innovative analysis of the impact of the unique Mala taste preference of Sichuan cuisine on GWG. However, this study had some limitations. First, the self-designed FFQ is simple and fail to provide detailed information on specific foods. However, it is effective for collecting the frequency and amount of food category intake and analyzing dietary patterns. Second, the reliability and validity of the FFQ were not evaluated. Nevertheless, the results of our food category intake were consistent with those of the Chongqing Residents’ Health Status Report, which partially reflects the validity of the FFQ. Moreover, the FFQ showed good reproducibility. The Spearman and intra-class correlation coefficients between the two FFQ measurements 3 months apart ranged from 0.22 to 0.66 and from 0.22 to 0.60, respectively ( Additional Table 1 ). The proportion of women classified into the same or adjacent quartiles by both FFQ measurements ranged from 72–85%, whereas the rate of misclassification into opposite quartiles was < 9% ( Additional Table 2 ). Another significant limitation is that we did not adjust for food intake when analyzing the relationship between taste preferences and GWG, which could potentially introduce bias into the results. However, in the subsequent mediation analysis, dietary patterns extracted based on food category intake were included and adjusted in the model. Conclusions To the best of our knowledge, the current study is the first to comprehensively evaluate dietary intake and taste preferences in women with GWG in Southwest China. The findings revealed an unbalanced dietary intake among pregnant women in Chongqing, characterized by notably inadequate consumption of vegetables, fruits, aquatic products, beans, and dairy. Mala flavor, a typical flavor of Sichuan cuisine, positively affects GWG, and is partially mediated by TD and MD. Both dietary patterns are characterized by high intake of cereals with high glycemic indexes. Our results provide a scientific foundation for targeted nutritional guidance and health recommendations. It is advisable for pregnant women in the Chongqing area to appropriately modify their Mala taste preference based on their current weight and increase the intake of high-quality protein foods in order to control GWG, to maintain it within a reasonable range. Abbreviations ANOVA Analysis of Variance ART Assisted Reproductive Technology BMI Body Mass Index CBDP Chinese Balanced Dietary Pagoda FFQ Food Frequency Questionnaire GWG Gestational Weight Gain KMO Kaiser-Meyer-Olkin MD Modern Diet QPD Quality Protein Diet SD Standard Deviation SEM Structural Equation Modeling TD Traditional Diet Declarations Ethics approval and consent to participate The ethics committee of the Chongqing Kaizhou Maternal and Child Health Hospital approved this study. Written informed consent was obtained from all the participants. Consent for publication Not applicable. Availability of data and materials Data and materials described in this manuscript are available from the corresponding author upon request. Competing interest We declare no competing interests. Funding This study was supported by the Chongqing Medical Scientific Research Project Joint Project of the Chongqing Health Commission and Science and Technology Bureau (No. 2023MSXM024) and the Chongqing Health Commission Project (No. 2020FY103). Author contributions JHL, ML, and WJZ designed the research; FW, WXZ, and JL conducted the research; YYM, FW, and ML analyzed the data; DFW and ML wrote the initial and final drafts of the manuscript; JHL, QXZ, and JD provided feedback and revisions of the manuscript; and all authors read and approved the final manuscript. Acknowledgements We would like to thank all the participants in this study and the research team from Chongqing Kaizhou District Maternal and Child Health Hospital, Shanghai Institute for Biomedical and Pharmaceutical Technologies, and Chongqing Population and Family Planning Science and Technology Research Institute for their hard work in recruiting and interviewing participants, clearing and analyzing data, and writing the paper. Authors’ information 1 Kaizhou District Maternal and Child Health Hospital, Chongqing 405499, China. 2 Shanghai-MOST Key Laboratory of Health and Disease Genomics, NHC Key Lab of Reproduction Regulation, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai 200237, China 3 NHC Key Laboratory of Birth Defects and Reproductive Health (Chongqing Population and Family Planning Science and Technology Research Institute), Chongqing 400020, China References Godfrey KM, Barker DJ. Fetal programming and adult health. 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Wang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shanghai Institute for Biomedical and Pharmaceutical Technologies\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Di\",\"middleName\":\"Fei\",\"lastName\":\"Wang\",\"suffix\":\"\"},{\"id\":269165166,\"identity\":\"7ecea496-1119-433c-bae9-f4fe3078ff79\",\"order_by\":2,\"name\":\"Yan Yan Mao\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shanghai Institute for Biomedical and Pharmaceutical Technologies\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Yan\",\"middleName\":\"Yan\",\"lastName\":\"Mao\",\"suffix\":\"\"},{\"id\":269165167,\"identity\":\"94e67de2-01e6-4a44-ac76-8c19f3af4e1a\",\"order_by\":3,\"name\":\"Wu Xia Zhang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Kaizhou District Maternal and Child Health Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Wu\",\"middleName\":\"Xia\",\"lastName\":\"Zhang\",\"suffix\":\"\"},{\"id\":269165168,\"identity\":\"ca505fa6-8c20-482d-85dd-3591a1744cc5\",\"order_by\":4,\"name\":\"Qian Xi Zhu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shanghai Institute for Biomedical and Pharmaceutical Technologies\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Qian\",\"middleName\":\"Xi\",\"lastName\":\"Zhu\",\"suffix\":\"\"},{\"id\":269165169,\"identity\":\"55dc62af-87c6-4e08-9b32-83ea408a1bc0\",\"order_by\":5,\"name\":\"Jun Liu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Chongqing Population and Family Planning Science and Technology Research Institute\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jun\",\"middleName\":\"\",\"lastName\":\"Liu\",\"suffix\":\"\"},{\"id\":269165170,\"identity\":\"29979b3a-771d-4572-9032-a73959926630\",\"order_by\":6,\"name\":\"Jing Du\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shanghai Institute for Biomedical and Pharmaceutical Technologies\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jing\",\"middleName\":\"\",\"lastName\":\"Du\",\"suffix\":\"\"},{\"id\":269165171,\"identity\":\"5dcd8e2f-4420-49b7-8036-bf5c4236c3ec\",\"order_by\":7,\"name\":\"Wei Jin Zhou\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shanghai Institute for Biomedical and Pharmaceutical Technologies\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Wei\",\"middleName\":\"Jin\",\"lastName\":\"Zhou\",\"suffix\":\"\"},{\"id\":269165172,\"identity\":\"69af569d-4367-480b-a77f-4f0fbe4b1bf1\",\"order_by\":8,\"name\":\"Fen Wang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Kaizhou District Maternal and Child Health 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09:16:47\",\"currentVersionCode\":1,\"declarations\":{\"humanSubjects\":false,\"vertebrateSubjects\":false,\"conflictsOfInterestStatement\":false,\"humanSubjectEthicalGuidelines\":false,\"humanSubjectConsent\":false,\"humanSubjectClinicalTrial\":false,\"humanSubjectCaseReport\":false,\"vertebrateSubjectEthicalGuidelines\":false},\"doi\":\"10.21203/rs.3.rs-3893577/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-3893577/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":50328268,\"identity\":\"4ea276bb-aacb-4ff7-8a4a-e56fa206fbb9\",\"added_by\":\"auto\",\"created_at\":\"2024-01-29 20:45:50\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":28109,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eProportion of pregnant women with taste preferences in Chongqing\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"F1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3893577/v1/7ff37ac0e1aad4f8944db72c.png\"},{\"id\":50328269,\"identity\":\"1c13743c-f867-47d3-9d0c-7b4fa3ad0aa8\",\"added_by\":\"auto\",\"created_at\":\"2024-01-29 20:45:50\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":105745,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eMediating effect of Mala taste preference on gestational weight gain\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"F2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3893577/v1/9520ebabad9ca28b7446f14c.png\"},{\"id\":50394294,\"identity\":\"a9aaa6d2-e0d0-4917-989a-d19eceeaa640\",\"added_by\":\"auto\",\"created_at\":\"2024-01-30 20:58:06\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":536620,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3893577/v1/cc8dc61d-09ef-4571-a946-6b26afbc4ba3.pdf\"},{\"id\":50328270,\"identity\":\"a253992f-2dd0-496a-9bdc-04e788cb4894\",\"added_by\":\"auto\",\"created_at\":\"2024-01-29 20:45:50\",\"extension\":\"docx\",\"order_by\":9,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":16041,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Additionalfile1.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3893577/v1/098083bb7d9761eba3b091a4.docx\"},{\"id\":50328526,\"identity\":\"f139d3c4-e759-447b-b5ab-b3b3cc78c650\",\"added_by\":\"auto\",\"created_at\":\"2024-01-29 20:53:50\",\"extension\":\"docx\",\"order_by\":10,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":14586,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Additionalfile2.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3893577/v1/51d805c54ca383ea2fd58198.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Effect of maternal Mala flavor preference on gestational weight gain mediated by dietary patterns in Chongqing, China: an ambispective cohort study\",\"fulltext\":[{\"header\":\"Background\",\"content\":\"\\u003cp\\u003eThe \\u0026ldquo;Developmental Origins of Health and Disease\\u0026rdquo; theory proposes that nutritional status in early life affects the development of chronic conditions such as hypertension, diabetes, and cardiovascular disease in adulthood (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e). Gestational weight gain (GWG) is a direct indicator of maternal nutritional status and an independent predictor of perinatal and long-term outcomes in both mother and infant (\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e). Research indicates that insufficient GWG may increase the risk of small for gestational age and low birth weight in infants, whereas excessive GWG may lead to the development of conditions such as pregnancy-induced hypertension syndrome, preeclampsia, gestational diabetes mellitus, large for gestational age, and need for Cesarean section (\\u003cspan additionalcitationids=\\\"CR4\\\" citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e). Moreover, excessive GWG can have long-term health consequences, contributing to conditions such as diabetes and cardiovascular issues in later life in women and childhood obesity in offspring (\\u003cspan additionalcitationids=\\\"CR7\\\" citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eNutrition is particularly important during pregnancy, as it not only affects the health of the mother but also profoundly influences the growth and development of the fetus (\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e). A well-rounded diet and balanced diet serve as the cornerstones for controlling GWG and preventing pregnancy-related diseases (\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e). Compared with the conventional approach of analyzing individual foods or nutrients, analyzing dietary patterns is more effective for evaluating dietary status (\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e). A recent Danish study highlighted the benefits of consuming a high-protein, low-glycemic index diet in reducing GWG and minimizing complications, including lowering the incidence of Cesarean deliveries in overweight or obese women (\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e). In another (retrospective) study, a negative association was observed between GWG and the Mediterranean dietary pattern, which is dominated by a high intake of vegetables, whole cereals, nuts, fish, and olive oil and a low intake of refined cereals, snacks, and desserts (\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e). Findings from another (prospective cohort) study conducted in central China indicated that a dietary pattern enriched in beans and vegetables is advantageous for effectively managing GWG and promoting increased birth weight (\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eRecent studies have sought to determine whether associations exist between certain tastes, food intake, and obesity. A systematic review scrutinized 19 articles, and disclosed a potential link between obesity and taste preferences, with moderate preference for salty, bitter, and fatty flavors and higher preference for sour flavors (\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e). To date, there is a dearth of research examining the relationship between taste preference and GWG.\\u003c/p\\u003e \\u003cp\\u003eLocal residents in Chongqing in southwest China developed a distinctive Sichuan cuisine known for comprising Chinese prickly ash and chili, creating a distinctive \\u0026ldquo;Mala\\u0026rdquo; sensation in local dishes (\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e). According to a study, individuals in Chongqing tend to consume excessive amounts of red meat, cooking oil, and salt but low amounts of vegetables and fruits (\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e). There are few reports on the dietary status of pregnant women and no relevant reports on the relationship between diet and GWG in Chongqing, hindering the development of appropriate local nutritional intervention strategies. Therefore, we aimed to assess the relationship between dietary status, encompassing taste preferences and dietary patterns, and GWG among pregnant women in Chongqing.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003ePopulation and study design\\u003c/h2\\u003e \\u003cp\\u003eThis ambispective cohort study was conducted at Chongqing Kaizhou District Maternal and Child Health Hospital, China. Pregnant women aged 20\\u0026ndash;45 years who initiated routine prenatal care in the hospital\\u0026rsquo;s obstetrics department at 24\\u0026ndash;27 gestational weeks and were expected to deliver at the hospital were invited to enroll in the cohort from May 2021 to November 2022. The exclusion criteria were women who had undergone assisted reproductive technology (ART; e.g., ovulation induction, in vitro fertilization, intracytoplasmic sperm injection treatment, or intrauterine insemination); had chronic medical and surgical diseases or pregnancy complications; were confirmed to have multiple pregnancies; or had cognitive impairment, dementia, or severe mental illness. Of the 635 pregnant women screened, 135 were excluded for intending to deliver at a different hospital (n\\u0026thinsp;=\\u0026thinsp;3), undergoing ART (n\\u0026thinsp;=\\u0026thinsp;1), having multiple pregnancies (n\\u0026thinsp;=\\u0026thinsp;2), and having chronic medical disease (n\\u0026thinsp;=\\u0026thinsp;129). Of the remaining five hundred pregnant women, three were lost to follow-up and two had stillbirths. Therefore, a final sample of 495 women was analyzed.\\u003c/p\\u003e \\u003cp\\u003e The ethics committee of the Chongqing Kaizhou District Maternal and Child Health Hospital approved this study. Written informed consent was obtained from all the participants.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eData collection\\u003c/h2\\u003e \\u003cp\\u003eThe participants were interviewed by trained obstetric nurses three times: at enrollment (24\\u0026ndash;27 gestational weeks), during the third trimester (32\\u0026ndash;36 gestational weeks), and at the time of delivery. Demographic information was collected at the time of enrollment. Data on dietary status, including taste preference and food intake over the previous month, were collected at 32\\u0026ndash;36 gestational weeks. Pregnancy outcomes were recorded at delivery. GWG was calculated by subtracting the pre-pregnancy weight from the weight at the end of pregnancy. Taste preference\\u0026mdash;fatty, salty, spicy, or Mala flavor\\u0026mdash;was recorded. The degree of preference was categorized as no or light, medium, or heavy. A simplified, self-designed food frequency questionnaire (FFQ) was used to gather information on dietary intake during pregnancy. The FFQ comprises 15 food items covering nine distinct categories: cereals, vegetables, fruits, beans, meat, poultry, aquatic products, eggs, and dairy. For each food item in the FFQ, participants reported the frequency of consumption and portion size.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStatistical analyses\\u003c/h2\\u003e \\u003cp\\u003eGWG and daily food intake are presented as mean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;standard deviation (SD). Analysis of variance (ANOVA) was used to assess the mean differences among various characteristic groups. Taste preference was presented as frequency and proportion. Due to low frequency, heavy taste preference was combined with the medium category for analysis. Dietary intake was assessed based on the Chinese Balanced Dietary Pagoda (CBDP, 2022 version) for pregnant women. The CBDP was been established and updated by the Chinese Nutrition Association to provide guidance on the dietary intake of Chinese residents. Major dietary patterns were extracted from nine food categories by factor analysis using the principal component analysis (PCA) method, a tool commonly employed to extract a posteriori dietary pattern. Kaiser-Meyer-Olkin (KMO) and Bartlett's spherical tests were used to determine whether the data met the analysis requirements. Varimax with Kaiser normalization rotation was applied to reduce correlations between factors and increase the interpretability of the results. Food categories with a factor loading \\u0026gt;|0.30| were included with present foods strongly associated with the identified factors. Association between taste preference, dietary pattern, and GWG was analyzed using multiple linear regression model, adjusting for potential confounders that were selected based on ANOVA. The mediating effect of dietary patterns on the relationship between taste preference and GWG was examined using structural equation modeling (SEM). Statistical analysis was performed using R software version 4.3.1 (Foundation for Statistical Computing, Vienna, Austria), with a two-tailed significance level set at \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05 (two-tailed) for all analyses.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eDemography of pregnant women\\u003c/h2\\u003e \\u003cp\\u003eThe pregnant women in this study had an average age of 27.8 (\\u0026plusmn;\\u0026thinsp;4.4) years, with a mean pre-pregnancy body mass index (BMI) of 21.4 (\\u0026plusmn;\\u0026thinsp;2.7 kg/m\\u003csup\\u003e2\\u003c/sup\\u003e). More than one-third were primiparas (36.0%), and the majority were from agricultural households (73.9%). Additionally, more than half had a junior high school education or below (51.3%), and the majority did not hold official employment roles (71.9%).\\u003c/p\\u003e \\u003cp\\u003ePregnant women gained an average of 14.0 (\\u0026plusmn;\\u0026thinsp;4.9) kg throughout their pregnancy. Of the total participants, 23.5% experienced inadequate GWG and 30.4% dealt with excessive GWG, based on Institute of Medicine guidelines (\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e). Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e presents the distribution of GWG across the different demographic characteristics of pregnant women. We noted a difference in GWG among the three pre-pregnancy BMI groups.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eGestational weight gain according to the distinctive characteristics of pregnant women in Chongqing.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eVariations\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eNumber\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eGWG(kg)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eN (%)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eMean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;SD\\u003csup\\u003e1\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAge, y\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.618\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e~\\u0026thinsp;25\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e136 (27.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e13.7\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e~\\u0026thinsp;30\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e222 (44.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14.3\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026gt;\\u0026thinsp;30\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e137 (27.7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14.0\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePre-pregnancy BMI, kg/m\\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;18.5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e55 (11.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14.7\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e18.5\\u0026thinsp;~\\u0026thinsp;23.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e358 (72.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026ge;\\u0026thinsp;24\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e81 (16.4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e11.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.8\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eGravidity\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.051\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e178 (36.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026gt;\\u0026thinsp;1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e317 (64.0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e13.7\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePlace of residence\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.174\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAgricultural\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e366 (73.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e13.9\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNon-Agricultural\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e129 (26.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEducational qualifications\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.381\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eJunior high school or below\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e254 (51.3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e13.8\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSenior high school\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e141 (28.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14.0\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eUniversity and above\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e100 (20.2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOccupation\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFarmer\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e24 (4.8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e12.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.133\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBusiness/Working\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e42 (8.5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14.7\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTeachers/civil servants/staff\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e55 (11.1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eUnemployed\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e356 (71.9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14.1\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOthers\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e18 (3.6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e12.2\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003e\\u003csup\\u003e1\\u003c/sup\\u003e SD, standard deviation; GWG, gestational weight gain\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eDietary status of pregnant women\\u003c/h2\\u003e \\u003cp\\u003eTaste preferences and daily food intakes are shown in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e and Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e, respectively. Most pregnant women had medium or heavy taste preferences for fatty, salty, and spicy flavors (82.2%, 77.6%, and 62.5%, respectively) and no or light taste preferences for Mala flavors (73.5%). Daily intake of cereals, meat, poultry, and eggs approached or exceeded the recommended levels. Intakes of vegetables, beans, and aquatic products fell significantly short, with less than 60% of the participants meeting the minimum recommended intake for these food categories.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eDaily food category intakes of pregnant women in Chongqing\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eFood categories\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eRecommended dietary intakes (g)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003eMean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;SD\\u003csup\\u003e1\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eActual dietary intakes (g)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eRelative intake (%) \\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCereals\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e225\\u0026ndash;275\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e214.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;108.5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e95\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;48\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eVegetables\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e400\\u0026ndash;500\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e83.4\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;70.1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e21\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;18\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFruits\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e200\\u0026ndash;350\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e129.0\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;111.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e65\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;56\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBeans\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e20\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e10.5\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;13.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e53\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;68\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMeats and Poultries\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e50\\u0026ndash;75\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e43.9\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;47.4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e129\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;112\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAquatic products\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e75\\u0026ndash;100\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e12.8\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;17.3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e17\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;23\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEggs\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e50\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e50.2\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;27.0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e101\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;54\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDairy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e300\\u0026ndash;500\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e205.6\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;93.2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e69\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;31\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003e\\u003csup\\u003e1\\u003c/sup\\u003e SD, standard deviation\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003csup\\u003e2\\u003c/sup\\u003e Relative intake was calculated as a percentage of the minimum recommended intake.\\u003c/p\\u003e \\u003cp\\u003eIn the factor analysis, the KMO test statistic yielded a value of 0.695, and the Bartlett spherical test demonstrated significance with \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001, indicating that the dataset was suitable for factor analysis. According to the Kaiser criterion\\u0026mdash;an Eigen value of \\u0026gt;\\u0026thinsp;1\\u0026mdash;three dietary patterns were extracted, with a total variance contribution of 55.9%. Factor 1, accounting for 20.8% of the total variance, is labelled as \\u0026ldquo;Traditional diet\\u0026rdquo; (TD) and characterized by high intakes of cereals, vegetables, fruits, meats, and dairy. Factor 2, accounting for 17.8% of the total variance, is labelled as \\u0026ldquo;Modern diet\\u0026rdquo; (MD) and characterized by high intakes of cereals, vegetables, beans, meats, poultries, and aquatic products. Factor 3, accounting for 17.4% of total variance, is labelled as \\u0026ldquo;Quality protein diet\\u0026rdquo; (QPD) and characterized by high intakes of aquatic products, eggs, and dairy (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eFactor analysis of dietary patterns among pregnant women in Chongqing\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFood categories\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eFactor 1\\u003c/p\\u003e \\u003cp\\u003e(Traditional diet)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eFactor 2\\u003c/p\\u003e \\u003cp\\u003e(Modern diet)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eFactor 3\\u003c/p\\u003e \\u003cp\\u003e(Quality protein diet)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCereals\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.679\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.366\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eVegetables\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.441\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.589\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFruits\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.703\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBeans\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.678\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMeats\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.550\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.338\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePoultry\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.594\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAquatic products\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.372\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.676\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEggs\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.859\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDairy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.616\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.477\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eRelationship between taste preference, dietary pattern, and GWG\\u003c/h2\\u003e \\u003cp\\u003eTable\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e indicates that women with a medium or heavy preference for fatty or salty flavors had a lower MD or TD score. Women with a medium or heavy preference for spicy or Mala flavors had higher TD, MD, and QDP scores.\\u003c/p\\u003e \\u003cp\\u003eIn Table\\u0026nbsp;\\u003cspan refid=\\\"Tab5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e, after adjusting for pre-pregnancy BMI, women with a medium or heavy preference for Mala flavors had a higher GWG (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e). Additionally, women with a higher TD or MD score also exhibited higher GWG.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eAssociation between taste preferences and dietary patterns among pregnant women in Chongqing\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"9\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c9\\\" colnum=\\\"9\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eIndependent variables*\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003eTraditional diet\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003eModern diet\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c9\\\" namest=\\\"c8\\\"\\u003e \\u003cp\\u003eQuality protein diet\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eβ\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eβ\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eβ\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFatty\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.193\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.227\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e-0.391\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.011\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e-0.010\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e0.955\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSalty\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-0.543\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e-0.156\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.283\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.031\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e0.849\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSpicy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.207\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.033\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.295\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.002\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e-0.263\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e0.011\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNumbing-spicy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.698\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.868\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.227\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e0.038\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"9\\\"\\u003e*: Taste preference value, non or light\\u0026thinsp;=\\u0026thinsp;0; medium or heavy\\u0026thinsp;=\\u0026thinsp;1\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab5\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 5\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eAssociation between dietary status and gestational weight gain among pregnant women in Chongqing\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"3\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIndependent variables\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eβ\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTaste preference\\u003csup\\u003e1\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFatty\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-1.039\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.198\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSalty\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-0.562\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.465\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSpicy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.509\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.300\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNumbing-spicy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.545\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.003\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDietary pattern \\u003csup\\u003e2\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTraditional diet\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.542\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.012\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eModern diet\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.553\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.010\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eQuality protein diet\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.359\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.095\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003csup\\u003e1\\u003c/sup\\u003e Adjusted for pre-pregnancy BMI and other taste preferences: taste preference value, light\\u0026thinsp;=\\u0026thinsp;0; medium/heavy\\u0026thinsp;=\\u0026thinsp;1.\\u003c/p\\u003e \\u003cp\\u003e \\u003csup\\u003e2\\u003c/sup\\u003e Adjusted for pre-pregnancy BMI, and other dietary patterns.\\u003c/p\\u003e \\u003cp\\u003eThe mediation analysis demonstrated the model containing the independent (GWG), dependent (numbing-spicy taste preference), and mediator (TD and MD) variables was within acceptable fit (CFI\\u0026thinsp;=\\u0026thinsp;0.959, TLI\\u0026thinsp;=\\u0026thinsp;0.876, RMSEA\\u0026thinsp;=\\u0026thinsp;0.067, SRMR\\u0026thinsp;=\\u0026thinsp;0.032). As shown in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e, SEM pathway analysis revealed that the effect of numbing-spicy taste preference on GWG (β\\u0026thinsp;=\\u0026thinsp;1.437, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.003) was partially mediated by TD and MD (β\\u0026thinsp;=\\u0026thinsp;0.305, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.057, and β\\u0026thinsp;=\\u0026thinsp;0.371, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.071 respectively). The total indirect effect (β 0.599, \\u003cem\\u003eP\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.012) accounted for 41.7% of variance.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThe occurrence of GWG surpassing the recommended levels in approximately half of pregnancies is often attributed to unhealthy lifestyles and unbalanced diets (\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e). Excess GWG is linked to increased risk of adverse maternal and neonatal outcomes (\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e). Data from China indicate that 30\\u0026ndash;50% of women experience excessive GWG (\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e). Multiple interventions including diet, physical activity, and combinations have been proposed to address this issue (\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e). A meta-analysis showed that dietary interventions are associated with reduced GWG and exert a more significant impact than physical activity alone (\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e). Strategies for dietary interventions in weight management should focus on reducing energy intake and consider dietary patterns related to differences in food accessibility, eating behaviors, taste preferences, and cultural background (\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e). A comprehensive understanding of regional dietary intake elements is crucial for devising targeted dietary interventions to prevent excessive GWG.\\u003c/p\\u003e \\u003cp\\u003eIn the current study, we evaluated dietary intake and taste preference among pregnant women in Chongqing and their impacts on GWG. Our results showed that food intake during pregnancy was notably inadequate, except for cereals, meats/poultries, and eggs, with less than 70% of the recommended minimum intake based on the CBDP. This is consistent with the 2018 Chongqing Residents\\u0026rsquo; Health Status report (\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e). An unbalanced diet heavily laden with carbohydrates has been reported to be associated with weight gain and obesity in Asia (\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e). This explains why, despite inadequate dietary intake, there are still quite a few cases of excessive GWG in Chongqing (30.4%). Using the PCA method, we identified three dietary patterns: TD, MD, and QPD. Linear regression analysis revealed that pregnant women adhering to a TD or MD, but not a QPD, experienced greater GWG. Our results are similar to those of Danish study that low-glycemic index and high-protein diet reduced GWG (\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e). TD and MD are both characterized by high intakes of cereals, often consisting of refined carbohydrate with high-glycemic indexes. Another prospective study in Central China showed that women following a fish-meat-egg, rice-wheat-fruit diet during the second trimester of pregnancy had a significantly higher GWG (\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eTaste influences nutritional status and health. A recent systematic review evaluated the relationship between weight status and the perception of and preference for four common tastes (sweet, salty, fatty, bitter, and sour) by reviewing observational and interventional studies (\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e). The findings indicate that adults with overweight and obesity exhibit decreased perceptions of the four tastes and that preferences for sweetness and fat increase with weight gain (\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e). There is no consensus in the literature regarding the effects of spiciness on obesity. One prospective study from China suggests that high intake of spicy food is positively associated with energy intake but is inversely associated with the risk of overweight or obesity (\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e). A beneficial effect of spicy food consumption on weight management has been demonstrated in intervention studies with small sample sizes from Western countries (\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e). However, a recent meta-analysis of cross-sectional studies shows that spiciness may adversely affect overweight or obesity (\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eRegarding taste preference during pregnancy, only sugar consumption has been reported to contribute to increased GWG and the development of pregnancy complications (\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e). In our present study, we investigated four taste preferences of pregnant women, including fatty, salty, spicy, and Mala flavors, and found that pregnant women who preferred the Mala flavor (but not fatty, salty, or spicy flavors) exhibited higher GWG. Among pregnant women with no or light preference for Mala flavor, the rate of excessive GWG was 27.4%, whereas the rate among women with a medium or heavy preference was 38.8%. Further analysis showed that the positive effect of numbing-spicy flavor on GWG was partially mediated by TD and MD. Unlike the simple spicy flavor found in other Chinese cuisines, the Mala evoked by Chinese prickly ash combined with chili peppers constitutes the distinctive feature of Sichuan cuisine (\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e). This Mala sensation in the mouth further affect the mediation and recognition of tastes, stimulating appetite. Our findings indicate that women who preferred Mala flavors scored higher on all three dietary patterns. It is worth mentioning that a QPD did not significantly increase GWG, indicating that it is a more favorable food choice to provide necessary nutrients and help manage weight gain during pregnancy.\\u003c/p\\u003e \\u003cp\\u003eOur study provides an innovative analysis of the impact of the unique Mala taste preference of Sichuan cuisine on GWG. However, this study had some limitations. First, the self-designed FFQ is simple and fail to provide detailed information on specific foods. However, it is effective for collecting the frequency and amount of food category intake and analyzing dietary patterns. Second, the reliability and validity of the FFQ were not evaluated. Nevertheless, the results of our food category intake were consistent with those of the Chongqing Residents\\u0026rsquo; Health Status Report, which partially reflects the validity of the FFQ. Moreover, the FFQ showed good reproducibility. The Spearman and intra-class correlation coefficients between the two FFQ measurements 3 months apart ranged from 0.22 to 0.66 and from 0.22 to 0.60, respectively (\\u003cb\\u003eAdditional\\u003c/b\\u003e Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). The proportion of women classified into the same or adjacent quartiles by both FFQ measurements ranged from 72\\u0026ndash;85%, whereas the rate of misclassification into opposite quartiles was \\u0026lt;\\u0026thinsp;9% (\\u003cb\\u003eAdditional\\u003c/b\\u003e Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). Another significant limitation is that we did not adjust for food intake when analyzing the relationship between taste preferences and GWG, which could potentially introduce bias into the results. However, in the subsequent mediation analysis, dietary patterns extracted based on food category intake were included and adjusted in the model.\\u003c/p\\u003e\"},{\"header\":\"Conclusions\",\"content\":\"\\u003cp\\u003eTo the best of our knowledge, the current study is the first to comprehensively evaluate dietary intake and taste preferences in women with GWG in Southwest China. The findings revealed an unbalanced dietary intake among pregnant women in Chongqing, characterized by notably inadequate consumption of vegetables, fruits, aquatic products, beans, and dairy. Mala flavor, a typical flavor of Sichuan cuisine, positively affects GWG, and is partially mediated by TD and MD. Both dietary patterns are characterized by high intake of cereals with high glycemic indexes. Our results provide a scientific foundation for targeted nutritional guidance and health recommendations. It is advisable for pregnant women in the Chongqing area to appropriately modify their Mala taste preference based on their current weight and increase the intake of high-quality protein foods in order to control GWG, to maintain it within a reasonable range.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cp\\u003eANOVA \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Analysis of Variance\\u003c/p\\u003e\\n\\u003cp\\u003eART \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Assisted Reproductive Technology\\u003c/p\\u003e\\n\\u003cp\\u003eBMI \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;\\u0026nbsp;Body Mass Index\\u003c/p\\u003e\\n\\u003cp\\u003eCBDP \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Chinese Balanced Dietary Pagoda\\u003c/p\\u003e\\n\\u003cp\\u003eFFQ \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;\\u0026nbsp;Food Frequency Questionnaire\\u003c/p\\u003e\\n\\u003cp\\u003eGWG \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;\\u0026nbsp;Gestational Weight Gain\\u003c/p\\u003e\\n\\u003cp\\u003eKMO \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;\\u0026nbsp;Kaiser-Meyer-Olkin\\u003c/p\\u003e\\n\\u003cp\\u003eMD \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Modern Diet\\u003c/p\\u003e\\n\\u003cp\\u003eQPD \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Quality Protein Diet\\u003c/p\\u003e\\n\\u003cp\\u003eSD \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;\\u0026nbsp;Standard Deviation\\u003c/p\\u003e\\n\\u003cp\\u003eSEM \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;Structural Equation Modeling\\u003c/p\\u003e\\n\\u003cp\\u003eTD \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; Traditional Diet\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe ethics committee of\\u0026nbsp;the Chongqing\\u0026nbsp;Kaizhou Maternal and Child Health Hospital approved this study.\\u0026nbsp;Written informed consent was obtained from all\\u0026nbsp;the participants.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eData and materials described in this manuscript are available from the corresponding author upon request.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interest\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;We declare no competing interests.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis study was supported by\\u0026nbsp;the\\u0026nbsp;Chongqing Medical Scientific Research Project Joint Project of\\u0026nbsp;the Chongqing\\u0026nbsp;Health\\u0026nbsp;Commission\\u0026nbsp;and\\u0026nbsp;Science\\u0026nbsp;and\\u0026nbsp;Technology\\u0026nbsp;Bureau\\u0026nbsp;(No. 2023MSXM024) and\\u0026nbsp;the\\u0026nbsp;Chongqing Health Commission Project (No.\\u0026nbsp;2020FY103).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthor contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eJHL, ML, and WJZ designed\\u0026nbsp;the research; FW, WXZ, and JL conducted the research; YYM, FW, and ML analyzed the data; DFW and ML wrote the initial and final drafts of the manuscript;\\u0026nbsp;JHL, QXZ, and JD provided feedback and revisions of the manuscript; and all authors read and approved the final manuscript.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWe would like to thank all the participants in this study and the research team from\\u0026nbsp;Chongqing Kaizhou District Maternal and Child Health Hospital, Shanghai Institute for Biomedical and Pharmaceutical Technologies, and Chongqing Population and Family Planning Science and Technology Research Institute for their hard work in\\u0026nbsp;recruiting and interviewing participants, clearing and analyzing data,\\u0026nbsp;and writing\\u0026nbsp;the paper.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors\\u0026rsquo; information\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003csup\\u003e1\\u003c/sup\\u003e Kaizhou District Maternal and Child Health Hospital, Chongqing 405499, China.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003csup\\u003e2\\u003c/sup\\u003e Shanghai-MOST Key Laboratory of Health and Disease Genomics, NHC Key Lab of Reproduction Regulation, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai 200237, China\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003csup\\u003e3\\u003c/sup\\u003e NHC Key Laboratory of Birth Defects and Reproductive Health (Chongqing Population and Family Planning Science and Technology Research Institute), Chongqing 400020, China\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eGodfrey KM, Barker DJ. Fetal programming and adult health. Public Health Nutr. 2001;4(2B):611\\u0026ndash;24.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGoldstein RF, Abell SK, Ranasinha S, Misso M, Boyle JA, Black MH, et al. Association of gestational weight gain with maternal and infant outcomes: a systematic review and meta-analysis. JAMA. 2017;317(21):2207\\u0026ndash;25.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSimmons D, Devlieger R, van Assche A, Galjaard S, Corcoy R, Adelantado JM et al. Association between gestational weight gain, gestational diabetes risk, and obstetric outcomes: a Randomized controlled trial post hoc analysis. Nutrients. 2018;10(11).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSantos S, Voerman E, Amiano P, Barros H, Beilin LJ, Bergstrom A, et al. 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Maternal dietary patterns during pregnancy and their association with gestational weight gain and nutrient adequacy. Int J Environ Res Public Health. 2020;17:21.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLi Y, Zhou X, Zhang Y, Zhong C, Huang L, Chen X, et al. Association of maternal dietary patterns with birth weight and the mediation of gestational weight gain: a prospective birth cohort. Front Nutr. 2021;8:782011.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePeinado BRR, Frazao DR, Bittencourt LO, de Souza-Rodrigues RD, Vidigal MTC, da Silva DT, et al. Is obesity associated with taste alterations? a systematic review. Front Endocrinol (Lausanne). 2023;14:1167119.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLuo J, Ke J, Hou X, Li S, Luo Q, Wu H et al. Composition, structure and flavor mechanism of numbing substances in Chinese prickly ash in the genus Zanthoxylum: a review. Food Chem. 2022;373(Pt B):131454.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCommission CMH. 2018 Resident Health Status Report of Chongqing City. 2018.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eInstitute of M, National Research Council Committee to Reexamine IOMPWG. The National Academies Collection: reports funded by National Institutes of Health. In: Rasmussen KM, Yaktine AL, editors. Weight gain during pregnancy: reexamining the guidelines. Washington (DC): National Academies Press (US); 2009.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGoldstein RF, Harrison CL, Teede HJ, Editorial. The importance of gestational weight gain. Obes Rev. 2020;21(10):e13073.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJin C, Lin L, Han N, Zhao Z, Liu Z, Luo S, et al. Excessive gestational weight gain and the risk of gestational diabetes: comparison of Intergrowth-21st standards, IOM recommendations and a local reference. Diabetes Res Clin Pract. 2019;158:107912.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJiang X, Liu M, Song Y, Mao J, Zhou M, Ma Z, et al. The Institute of Medicine recommendation for gestational weight gain is probably not optimal among non-American pregnant women: a retrospective study from China. J Matern Fetal Neonatal Med. 2019;32(8):1353\\u0026ndash;8.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGou BH, Guan HM, Bi YX, Ding BJ. Gestational diabetes: weight gain during pregnancy and its relationship to pregnancy outcomes. Chin Med J (Engl). 2019;132(2):154\\u0026ndash;60.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWu S, Jin J, Hu KL, Wu Y, Zhang D. Prevention of gestational diabetes mellitus and gestational weight gain restriction in overweight/obese pregnant women: a systematic review and network meta-analysis. Nutrients. 2022;14(12).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eTeede HJ, Bailey C, Moran LJ, Bahri Khomami M, Enticott J, Ranasinha S, et al. Association of antenatal diet and physical activity-based interventions with gestational weight gain and pregnancy outcomes: a systematic review and meta-analysis. JAMA Intern Med. 2022;182(2):106\\u0026ndash;14.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSmethers AD, Rolls BJ. Dietary management of obesity: cornerstones of healthy eating patterns. Med Clin North Am. 2018;102(1):107\\u0026ndash;24.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMozaffarian D. Dietary and policy priorities for cardiovascular disease, ciabetes, and obesity: a comprehensive review. Circulation. 2016;133(2):187\\u0026ndash;225.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eFathi M, Javid AZ, Mansoori A. Effects of weight change on taste function; a systematic review. Nutr J. 2023;22(1):22.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eShi Z, Riley M, Taylor AW, Page A. Chilli consumption and the incidence of overweight and obesity in a Chinese adult population. Int J Obes (Lond). 2017;41(7):1074\\u0026ndash;9.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSirotkin AV. Peppers and their constituents against obesity. Biol Futur. 2023;74(3):247\\u0026ndash;52.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWang M, Huang W, Xu Y. Effects of spicy food consumption on overweight/obesity, hypertension and blood lipids in China: a meta-analysis of cross-sectional studies. Nutr J. 2023;22(1):29.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGoran MI, Plows JF, Ventura EE. Effects of consuming sugars and alternative sweeteners during pregnancy on maternal and child health: evidence for a secondhand sugar effect. Proc Nutr Soc. 2019;78(3):262\\u0026ndash;71.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHe W, Liang L, Zhang Y. Pungency perception and the interaction with basic taste sensations: an overview. Foods. 2023;12(12).\\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\":\"info@researchsquare.com\",\"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\":\"pregnant women, dietary patterns, taste preference, gestational weight gain, mediation analysis\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-3893577/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-3893577/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e \\u003cp\\u003eTaste preference drives food selection, acceptance, or rejection, and influences body mass index. This study aimed to analyze the correlation of dietary status, encompassing taste preference and dietary pattern, with gestational weight gain (GWG) among pregnant women.\\u003c/p\\u003e\\u003ch2\\u003eMethods\\u003c/h2\\u003e \\u003cp\\u003eWe conducted an ambispective cohort study at the Kaizhou District Maternal and Child Health Hospital in Chongqing, China. In total, 495 pregnant women aged 20\\u0026ndash;45 years who conceived naturally were recruited from May 2021 to November 2022. They had single pregnancies, no history of chronic medical and surgical diseases, and no pregnancy complications. Data on food category intake and taste preference, including fatty, salty, spicy, and Mala flavors, were collected during the third trimester. Factor analysis was used to evaluate dietary pattern. Multiple linear regression and structural equation modeling were performed to explore the relationship between taste preference and dietary pattern as well as their effects on GWG.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e \\u003cp\\u003e\\u0026ldquo;Traditional Diets\\u0026rdquo; (TD) are characterized by high intakes of cereals, vegetables, fruits, meats, and dairy. \\u0026ldquo;Modern Diets\\u0026rdquo; (MD) are characterized by high intakes of cereals, vegetables, beans, meats, poultries, and seafood. \\u0026ldquo;Quality Protein Diets\\u0026rdquo; (QPD) are characterized by high intakes of seafood, eggs, and dairy. Pregnant women with a preference for Mala flavor had higher TD, MD, and QPD scores. Women with a higher TD or MD score had a higher GWG. The Mala taste preference effect on GWG was partially (41.7%) mediated by TD and MD.\\u003c/p\\u003e\\u003ch2\\u003eConclusions\\u003c/h2\\u003e \\u003cp\\u003ePreference for Mala as the typical flavor in Chongqing has a positive effect on GWG, partially mediated by TD and MD, both of which are loaded with high amounts of cereals with high-glycemic index. Pregnant women in local areas should appropriately modify their Mala taste preference based on their current weight to maintain a reasonable GWG.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Effect of maternal Mala flavor preference on gestational weight gain mediated by dietary patterns in Chongqing, China: an ambispective cohort study\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-01-29 20:45:45\",\"doi\":\"10.21203/rs.3.rs-3893577/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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\":\"94fd5fef-b0fc-4573-90ef-8114e55ec991\",\"owner\":[],\"postedDate\":\"January 29th, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2024-01-30T20:49:57+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2024-01-29 20:45:45\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-3893577\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-3893577\",\"identity\":\"rs-3893577\",\"version\":[\"v1\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}