Association of dietary inflammatory index in the second trimester of pregnancy with birth weight discordance and postpartum complications in twin pregnancies

Association of dietary inflammatory index in the second trimester of pregnancy with birth weight discordance and postpartum complications in twin pregnancies | 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 Association of dietary inflammatory index in the second trimester of pregnancy with birth weight discordance and postpartum complications in twin pregnancies Hua Zeng, Yue Huang, Jie Zheng, Mi Cheng, Lei Liu, Yuhong Pan, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8035827/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 Objective : To explore the correlations among dietary inflammatory index (DII) in the second trimester of pregnancy, occurrence of birth weight discordance (BWD), and postpartum complications in twin pregnancies. Methods: Pregnant women who received prenatal screening at Guangzhou Women and Children Medical Center (Guangzhou, China) were enrolled. A questionnaire survey was conducted to collect data from pregnant women, including baseline information, childbearing history, dietary intake, and situation of the current pregnancy. Serum levels of inflammatory factors (C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), interleukin-10 (IL-10), and interleukin-lβ (IL-lβ)) were measured by enzyme-linked immunosorbent assay (ELISA). DII in the second trimester was calculated based on dietary intake data. Univariate and multivariate logistic regression analyses were conducted to identify risk factors for BWD in twin pregnancies. The incidence of postpartum complications was compared between pregnant women with and without BWD. Results: The average DII values among 1568 pregnant women obeyed a normal distribution. According to twins’ birth weight, pregnant women were divided into observation group (n=9) and control group (n=709). DII was significantly higher in the observation group than that in the control group (p < 0.05). The serum levels of CRP, TNF-α, and IL-6 significantly increased in the observation group compared with that in the control group (p < 0.05). The results of univariate and multivariate logistic regression analyses indicated that DII higher than 0, age above 30 years old, parity ≥ 2, gravidity ≥ 2, pre-pregnancy body mass index (BMI)≦25 kg/m 2 , and opposite-sex twins were risk factors for BWD (p < 0.05). Pregnant women with a lower DII had a significantly reduced incidence of postpartum complications, including placental abruption, fetal distress, low-birth-weight babies, and macrosomia (p< 0. 05). Conclusion DII could influence fetal growth in twin pregnancies, and a higher DII value was associated with higher risks of placental abruption and fetal distress. Pregnant women should adhere to a healthy diet to mitigate the risk of adverse pregnancy outcomes that may arise from a pro-inflammatory diet. Dietary inflammatory index Twin pregnancy Birth weight discordance Postpartum complications 1. Introduction Twin pregnancy, the most common type of multiple pregnancy, occurs when two eggs are simultaneously fertilized. Gestation is an important stage of early life, and healthy diet in pregnancy is a necessity for ensuring maternal and fetal health [ 1 , 2 ] . Inflammation manifests as a physiological response of the immune system to cell and tissue damage [ 3 ] . Pregnant women generally suffer from chronic low grade inflammation as a result of maternal physiological adaptation and fetal growth-induced metabolic stress [ 4 , 5 ] . A balance between pro-inflammatory and anti-inflammatory factors plays a vital role in normal pregnancy. It has been found that a high inflammatory level in pregnancy increases the risk of adverse pregnancy outcomes [ 6 ] . Fast fetal growth in gestational period gives rises to a rapidly increasing demand for nutrition. Maternal nutritional status in this period may profoundly influence intrauterine fetal growth, and such impact may last a lifetime [ 7 ] . Sufficient nutritional supply in the gestational period is critical for fetal growth. Maternal body is the only source of nutrients for fetuses, highlighting the importance of healthy diet in pregnancy [ 8 ] . At present, the pathogenesis and diagnostic criteria for birth weight discordance (BWD) remain controversial issues, with perspectives on them appearing to diverge both domestically and internationally. It is generally accepted that BWD is associated with placental and genetic factors and umbilical cord abnormalities. Prior research showed that an unhealthy diet elevates the maternal inflammation level and exerts an adverse impact on pregnancy outcomes [ 9 ] . Regulating maternal inflammation level and maintaining a balance between pro-inflammatory and anti-inflammatory factors is highly suggested for safeguarding maternal and fetal health. The present study discussed the influences of dietary inflammatory index (DII) during the second trimester of pregnancy on BWD and postpartum complications in twin pregnancies. 2. Methods 2.1 Subjects A total 1568 women with twin pregnancies who received regular prenatal screening and pregnancy tests at the obstetric outpatient clinic from January 2021 to December 2022 and gave birth after being admitted to the Guangzhou Women and Children Medical Center (Guangzhou, China) were initially enrolled in this study. Those cases who had miscarriage and inpatient induction of labor were excluded. The observation group consisted of 55 pregnant women with BWD. At a 1:1 age-matching approach and random number table selection, 1513 control subjects without BWD were initially identifies. For the final selection analysis, only 718 healthy women with a normal pre-pregnancy BMI were recruited. BWD was diagnosed if the birth weight difference between twins was 22% and above [ 10 ] . Birth weight difference was calculated as follows: Birth weight difference = (larger twin weight - smaller twin weight)/larger twin weight×100. The infant with the heavier weight was designated as the larger twin, while the one with the lighter weight was identified as the smaller twin. 2.1.2 Statistical power analysis Using the “pwr” package in R, post hoc power analyses were performed to assess the adequacy of the sample size. For continuous outcomes approximated by a two-sample t-test, the power to detect a medium effect size (Cohen’s d = 0.5) with the current sample sizes (9 in the observation group and 709 in controls) was approximately 32%. Power was even lower for small effects (d = 0.2, ~ 9%) and improved to about 66% only for large effects (d = 0.8). To reach the conventional 80% power threshold at medium effect size, at least 64 participants per group would be required. For categorical outcomes analyzed by chi-square tests, assuming a small to medium effect size (Cohen’s w = 0.3), the total sample size of 718 provided adequate power (~ 100%). These results highlight the limited statistical power for some continuous variable comparisons due to the small observation group, which should be considered when interpreting findings. 2.2 Inclusion and exclusion criteria The inclusion criteria were as follows: (1) History of receiving regular prenatal screening at the obstetric outpatient clinic of our hospital; (2) Women with twin pregnancies; (3) Gestational age between 13–27 weeks; (4) Women who aged 18–35 years old; (5) Approval was gained from the ethics committee of a hospital, and patients or their family members signed the written informed consent form. The exclusion criteria were as follows: (1) Serious diseases of the heart, lungs, liver, and kidneys; (2) Combined with diabetes or gestational diabetes; (3) Combined with hypertension or gestational hypertension; (4) Acute and chronic infectious diseases; (5) Neurological dysfunction or psychiatric disorders; (6) Termination of pregnancy for various reasons. 2.3 Questionnaire survey The self-made questionnaire (supplementary file) was administered to all of the enrolled subjects. Interviewers who received uniform training filled in the questionnaire after face-to-face interview with the study subjects. The questionnaire consisted of four dimensions, including baseline information, reproductive history, lifestyle, and diet and nutritional supplement intake. Each subject was inquired about the intake frequency and the average intake of each type of food in the second trimester of pregnancy. The study subjects’ height and body weight were measured on site by interviewers. 2.4 DII calculation Dietary intake was surveyed for all subjects in the second trimester (gestational age, 13–27 weeks). The amounts of food consumed for meals, extra meals, and snacks during 24 hours per day were recorded. Food intake during feasts was excluded. The type of food covered by the questionnaire included cereals, livestock, poultry, eggs, animal innards, aquatic products, bean products, milk products, coarse cereals, vegetables, fruits, nuts, and snacks. The raw weights and cooked weights of each type of food were determined by weighing. The actual daily intake of each type of food was determined based on the ratio of raw to cooked weight. The daily nutrient intake level was calculated using the nutritional analysis software. The conversion formulae was obtained from China Food Composition Tables [ 11 ] . DII was calculated as follows: DII = (Z-score for the total inflammation score of nutrients), where Z-score was calculated as follows: Z-score = (individual reported intake - global daily mean intake)/global standard deviation × inflammatory effect index of nutrient. To minimize right skewing, the Z-score was converted into a centered percentile score [(2 * percentile of Z-value − 1)]. As a result, a symmetric distribution was obtained centering around zero. In the abovementioned formula, n represents any of 17 nutrients (folic acid, calcium, iron, DHA, complex nutrients, cereal, domestic animals, beans and bean products, vegetables, fruits, coarse cereals, poultry, fish and aquatic products, animal innards, milk and dairy products, nuts, and eggs), and the results were combined to obtain the personal DII. The higher DII scores (greater than 0) indicate a more pro-inflammatory (less healthy) diet, while lower scores (below 0) reflect a more anti-inflammatory (healthier) dietary pattern. 2.5 Second trimester prenatal screening and pregnancy outcomes Fasting venous blood was drawn during prenatal screening in the second trimester. The serum levels of the following inflammatory factors were measured by enzyme-linked immunosorbent assay (ELISA): C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), interleukin-10 (IL-10), and interleukin-lβ (IL-lβ). The obstetric history was assessed post-delivery. Pregnancy outcomes were recorded, including gestational diabetes, placental abruption, polyhydramnios, postpartum hemorrhage, and gestational hypertension. 2.6 Statistical analysis Statistical analysis was conducted using SPSS 26.0 software (IBM, Armonk, NY, USA) and R studio (Version. 2025.05.0 + 496). Normally distributed continuous variables were expressed as mean ± standard deviation and compared using Mann–Whitney U test. Categorical variables were expressed as frequency, composition ratio, and rate. Intergroup comparisons of categorical variables were conducted using the Chi-square test. P < 0.05 was considered statistically significant. Adjustments were made for potential influential factors, including gestational BMI, age, parity, and educational level. Multivariate logistic regression analysis was performed to identify influential factors of BWD in twin pregnancies. 3. Results 3.1 Participants’ baseline data A total of 718 pregnant women were surveyed, with an average age of 30.01 \(\:\pm\:\) 4.23 years old. The youngest participant aged 20 years old, and the eldest was 33 years old. The average height was 160.21 \(\:\pm\:\) 4.78 cm. The average pregestational body weight was 57.21 \(\:\pm\:\) 9.23 kg, and the average pregestational BMI was 22.35 \(\:\pm\:\) 3.78 kg/m 2 . Further details are presented in Table 1 . Table 1 Baseline characteristics of recruited participants [n (%)]. Characteristic Control Observation p-value Participants [n (%)] 709 (98.7) 9 (1.3) Age (years old) [n (%)] 18 - \(\:\le\:\) 25 208 (29.3) 0 (0.0) 0.168 25 - \(\:\le\:\) 30 311 (43.9) 3 (33.3) 1.000 30–35 190 (26.8) 6 (66.7) 0.021 Pre-pregnancy BMI (kg/m 2 ) [n (%)] 18.5- \(\:\le\:\) 25 709 (98.7) 9 (1.3) NA Gravidity [n (%)] 0.200 1 381 (53.7) 2 (22.2) 2 262 (37.0) 4 (44.4) \(\:\ge\:\) 3 66 (9.3) 3 (33.3) Opposite-sex twins [n (%)] 0.020 Yes 492 (69.4) 3 (33.3) No 217 (30.6) 6 (66.7) Dietary supplement use [n (%)] Folic acid 456 (64.3) 3 (33.3) 0.000 Calcium 216 (30.5) 1 (11.1) 0.210 Iron 80 (11.3) 1 (11.1) 0.967 DHA 92 (13.0) 2 (22.2) 0.415 Complex nutrients [n (%)] 290 (40.9) 5 (55.6) 0.375 Cereal (g) (mean \(\:\pm\:\) SD) 444.13 \(\:\pm\:\) 73.03 387.00 \(\:\pm\:\) 77.85 0.022 Domestic animals (g) (mean \(\:\pm\:\) SD) 109.45 \(\:\pm\:\) 51.56 157.33 \(\:\pm\:\) 41.64 0.004 Beans and bean products (g) (mean \(\:\pm\:\) SD) 159.04 \(\:\pm\:\) 39.72 104.22 \(\:\pm\:\) 23.50 0.000 Vegetables (g) (mean \(\:\pm\:\) SD) 450.04 \(\:\pm\:\) 144.79 298.44 \(\:\pm\:\) 120.56 0.003 Fruits (g) (mean \(\:\pm\:\) SD) 459.65 \(\:\pm\:\) 122.22 332.56 \(\:\pm\:\) 130.08 0.007 Coarse cereals (g) (mean \(\:\pm\:\) SD) 440.91 \(\:\pm\:\) 148.55 301.67 \(\:\pm\:\) 91.61 0.003 Poultry (g) (mean \(\:\pm\:\) SD) 64.10 \(\:\pm\:\) 21.21 44.78 \(\:\pm\:\) 15.84 0.006 Fish and aquatic products (g) (mean \(\:\pm\:\) SD) 147.49 \(\:\pm\:\) 54.86 95.78 \(\:\pm\:\) 23.31 0.002 Animals innards (g) (mean \(\:\pm\:\) SD) 46.34 \(\:\pm\:\) 17.55 81.56 \(\:\pm\:\) 28.35 0.000 Milk and dairy products (g) (mean \(\:\pm\:\) SD) 414.44 \(\:\pm\:\) 193.02 346.11 \(\:\pm\:\) 123.35 0.279 Nuts (g) (mean \(\:\pm\:\) SD) 22.79 \(\:\pm\:\) 5.64 9.89 \(\:\pm\:\) 1.69 0.000 Snacks (g) (mean \(\:\pm\:\) SD) 86.00 \(\:\pm\:\) 33.82 144.67 \(\:\pm\:\) 26.40 0.000 Egg (g) (mean \(\:\pm\:\) SD) 52.73 \(\:\pm\:\) 16.66 40.67 \(\:\pm\:\) 13.16 0.026 3.2 Diet and DII The intakes of cereals, poultry, eggs, aquatic products, bean products, milk products, coarse cereals, vegetables, fruits, and nuts were significantly lower in the observation group than those in the control group (p \(\:<\) 0.05). The intakes of livestock, animal innards, and snacks were significantly higher in the observation group than those in the control group (p \(\:<\) 0.05). The average DII in the second trimester was − 2.51 \(\:\pm\:\) 1.54. Among 1513 control subjects who were surveyed, 782 subjects had a DII below zero, indicating an anti-inflammatory tendency. Among 55 subjects in the observation group, 48 subjects had a DII above zero, highlighting a pro-inflammatory tendency. Additional data are summarized in Table 2 . Table 2 DII score of two groups. Parameters Control (n = 709) Observation (n = 9) p-value DII score [n (%)] 0.013 DII>0 375 (52.3) 9 (100.0) DII<0 334 (47.1) 0 (0.0) 3.3 Serum levels of inflammatory factors in the two groups of pregnant women The serum levels of CRP, TNF-α, IL-6, IL-10, and l-1β were compared between the two groups, and the results are presented in Table 3 . In the second trimester, the serum levels of CRP, IL-6, and TNF-α were significantly higher in the observation group than those in the control group (Table 3 ). Table 3 Comparison of inflammatory cytokines in the second trimester between the two groups (mean ± SD). Inflammatory cytokines Control group (n = 709) Observation group (n = 9) p-value CRP (mg/L) 2.75 \(\:\pm\:\) 0.65 3.79 \(\:\pm\:\) 1.56 0.018 TNF-α (ng/mL) 1.80 \(\:\pm\:\) 0.62 2.61 \(\:\pm\:\) 0.59 0.001 IL-6 (pg/mL) 2.55 \(\:\pm\:\) 0.91 3.38 \(\:\pm\:\) 1.48 0.026 IL-10 (pg/mL) 2.20 \(\:\pm\:\) 0.68 2.17 \(\:\pm\:\) 0.50 0.998 IL-1β (pg/mL) 1.87 \(\:\pm\:\) 0.49 1.50 \(\:\pm\:\) 0.55 0.047 3.4 Univariate and multivariate analysis of influential factors of BWD Univariate logistic regression analyses identified several significant factors associated with the outcome. Folic acid intake showed a non-significant trend towards a protective effect in both univariate (odds ratio (OR) = 0.299, 95% confidence interval (CI): 0.081–1.109, p \(\:=\) 0.071) and multivariate analyses (OR \(\:=\) 0.523, 95% CI: 0.132–2.065, p \(\:=\) 0.355). Higher intake of cereals (OR \(\:=\) 0.989, 95% CI: 0.980–0.998, p \(\:=\) 0.016), beans and bean products (OR \(\:=\) 0.963, 95% CI: 0.945–0.982, p \(\:<\) 0.001), vegetables (OR \(\:=\) 0.992, 95% CI: 0.988–0.997, p \(\:=\) 0.002), fruits (OR \(\:=\) 0.992, 95% CI: 0.986–0.997, p \(\:=\) 0.002), coarse cereals (OR \(\:=\) 0.993, 95% CI: 0.989–0.998, p \(\:=\) 0.006), poultry (OR \(\:=\) 0.956, 95% CI: 0.925–0.988, p \(\:=\) 0.007), fish and aquatic products (OR \(\:=\) 0.981, 95% CI: 0.967–0.994, p \(\:=\) 0.005), and nuts (OR \(\:=\) 0.581, 95% CI: 0.462–0.731, p \(\:<\) 0.001) were each inversely associated with the outcome, indicating a potential protective effect. Conversely, higher consumption of domestic animals (OR \(\:=\) 1.016, 95% CI: 1.005–1.027, p \(\:=\) 0.005), animals’ innards (OR \(\:=\) 1.094, 95% CI: 1.055–1.134, p < 0.001), and snacks (OR \(\:=\) 1.051, 95% CI: 1.028–1.075, p \(\:<\) 0.001) were positively associated with increased odds. Among inflammatory markers, elevated levels of CRP (OR \(\:=\) 5.801, 95% CI: 2.544–13.228, p < 0.001), TNF-α (OR \(\:=\) 8.291, 95% CI: 2.681–25.644, p \(\:<\) 0.001), and IL-6 (OR = 2.466, 95% CI: 1.294–4.699, p \(\:=\) 0.006) were significantly associated with higher odds of the outcome. In contrast, IL-1β showed a protective effect (OR \(\:=\) 0.221, 95% CI: 0.059–0.819, p \(\:=\) 0.024). Additionally, gravidity of one (compared to zero) (OR \(\:=\) 0.125, 95% CI: 0.024–0.648, p \(\:=\) 0.013) and opposite-sex twins (OR \(\:=\) 0.238, 95% CI: 0.064–0.882, p \(\:=\) 0.032) were inversely associated with the outcome. The Dietary Inflammatory Index (DII) score showed a borderline association (OR \(\:=\) 16.925, 95% CI: 0.977–293.148, p \(\:=\) 0.052) (Table 4 ). In multivariate logistic regression analysis adjusting for potential confounders, most of these associations attenuated and became statistically non-significant. Notably, nuts intake remained significantly protective (OR \(\:=\) 0.878, 95% CI: 0.781–0.988, p \(\:=\) 0.031). The consumption of snacks showed a trend toward increased odds but did not reach statistical significance (OR \(\:=\) 1.018, 95% CI: 0.999–1.037, p \(\:=\) 0.066). Other factors, including cereals, domestic animals, beans and bean products, vegetables, fruits, coarse cereals, poultry, fish and aquatic products, animals’ innards, inflammatory markers (CRP, TNF-α, IL-6, IL-1β), gravidity, and opposite-sex twins, were not independently associated with the outcome after adjustment (all p \(\:>\) 0.1) (Table 4 ). Table 4 Univariate and multivariate analysis of influential factors of BWD. Influential factors Univariate logistic regression Multivariate logistic regression OR 95% CI p-value OR 95% CI p-value Folic acid (g) 0.299 0.081–1.109 0.071 0.523 0.132–2.065 0.355 Cereals (g) 0.989 0.980–0.998 0.016 0.995 0.985–1.005 0.29 Domestic animals (g) 1.016 1.005–1.027 0.005 1.003 0.992–1.015 0.565 Beans and bean products (g) 0.963 0.945–0.982 0.000 0.991 0.974–1.008 0.305 Vegetables (g) 0.992 0.988–0.997 0.002 0.999 0.994–1.003 0.587 Fruits (g) 0.992 0.986–0.997 0.002 0.998 0.993–1.004 0.562 Coarse cereals (g) 0.993 0.989–0.998 0.006 0.997 0.992–1.002 0.227 Poultry (g) 0.956 0.925–0.988 0.007 0.991 0.96–1.023 0.570 Fish and aquatic products (g) 0.981 0.967–0.994 0.005 1 0.987–1.012 0.942 Animals’ innards (g) 1.094 1.055–1.134 0.000 1.015 0.978–1.053 0.444 Nuts (g) 0.581 0.462–0.731 0.000 0.878 0.781–0.988 0.031 Snacks (g) 1.051 1.028–1.075 0.000 1.018 0.999–1.037 0.066 Eggs (g) 0.955 0.917–0.995 0.029 0.997 0.956–1.043.809 0.885 CRP (mg/L) 5.801 2.544–13.228 0.000 1.583 0.658–6.563 0.305 TNF- \(\:\varvec{\alpha\:}\) (ng/mL) 8.291 2.681–25.644 0.000 2.335 0.831–2.274 0.108 IL-6 (pg/mL) 2.466 1.294–4.699 0.006 1.147 0.579–6.653 0.693 IL-10 0.934 0.372–2.341 0.884 NA NA NA IL-1 \(\:\varvec{\beta\:}\) (pg/mL) 0.221 0.059–0.819 0.024 0.588 0.153–2.265 0.441 DII score 16.925 0.977–293.148 0.052 NA NA NA Gravidity 1 0.125 0.024–0.648 0.013 0.276 0.049–1.543 0.143 2 0.326 0.078–1.360 0.124 0.403 0.067–2.418 0.320 Opposite-sex twins 0.238 0.064–0.882 0.032 0.38 0.097–1.49 0.165 3. Discussion Since the concept of DII was first proposed, it has been found to be closely associated with various human diseases [ 12 ] . However, few studies have concentrated on the influences of DII on maternal health in the second trimester of twin pregnancies. The present study revealed the correlation between DII and pregnancy outcomes in twin pregnancies. In the present study, healthy pregnant women without typical inflammatory symptoms in the second trimester were enrolled and divided them into control group and observation group based on the occurrence of BWD. The results revealed that BWD was more likely associated with a pro-inflammatory tendency. As evidenced by the daily intakes of different types of food in the two groups, pro-inflammatory or anti-inflammatory tendency was not determined by the intake of one or several types of food, while it was indicated by the preference for or aversion to all types of food combined. DII can be used to guide pregnant women to adopt a more anti-inflammatory diet on top of a generally balanced diet. The development of BWD is a multi-factorial and multi-step process [ 13 ] . Epidemiological studies have indicated the multiplicity of risk factors for BWD, among which the common ones include maternal, fetal, and genetic factors. Once BWD happens, the prognosis is mainly poor despite interventional measures. Except for BWD caused by genetic factors, the majority of BWD cases are preventable [ 14 ] . Interventional measures addressing specific risk factors may be administered to the target populations to prevent the occurrence of BWD and improve maternal and fetal outcomes. It has been reported that DII gradually decreases as the gestational age increases. However, in the present study, DII did not significantly differ in the same group of pregnant women in the second trimester over time. Notably, the incidence of BWD was significantly higher in subjects with a pro-inflammatory tendency in the second trimester compared with those with an anti-inflammatory tendency. Therefore, the incidence of BWD may be lowered in twin pregnancies if pregnant women select an anti-inflammatory diet in the second trimester. Arnold K et al. conducted a dietary interventional study on 14 menopausal women, which demonstrated that a diet low in sugar but rich in fibers and fish led to a decrease in the serum levels of inflammatory factors [ 15 ] . The present study indicated that pregnant women in the observation group who had a pro-inflammatory tendency in the second trimester had significantly higher serum levels of CRP, IL-6, and TNF-α compared with those in the control group. According to another study [ 16 ] , intake of saturated fatty acids (SFAs) significantly increased the serum levels of inflammatory factors in patients who aged above 45 years. On the contrary, taking eicosapentaenoic acid and docosahexaenoic acid (DHA) supplements reduced the levels of inflammatory factors, which agreed with findings of the present study (Table 1 ). Pregnant women are advised to consume an anti-inflammatory diet abundant in vegetables, legumes, and fish while minimizing the intake of pro-inflammatory food products, such as sugar and red meat. This dietary approach aims to lower serum levels of inflammatory factors during pregnancy. From a mechanistic perspective, the association between higher DII and increased risk of BWD may be partially explained by placental pathophysiology. Maternal pro-inflammatory diets may promote low-grade systemic inflammation, which could impair placental vascular remodeling and trophoblast invasion, lead to oxidative stress, and disrupt normal angiogenesis. These pathological changes may reduce placental perfusion asymmetrically between twin fetuses, contributing to differential fetal growth. Additionally, inflammation-related alterations in angiogenic factors such as VEGF, PlGF, and sFlt-1 might affect nutrient transport efficiency, leading to increased discordance in fetal growth. These mechanisms suggest that DII may influence BWD through inflammation-induced placental dysfunction. In addition to other potential risk factors, twin type and gender appear to play a critical role in influencing the BWD. The impact of these biological variables on fetal growth and birth outcomes has been well documented in the literature. For instance, Jelenkovic et al. (2018), they specifically reported that males having a co-twin sister were heavier and longer than those with a co-twin brother [ 17 ] , suggesting that the presence of a sister may positively affect the growth of male fetuses. In contrast, female twins’ birth weight and length did not differ significantly whether their co-twin was male or female [ 17 ] , indicating a possible sex-specific interaction effect on growth within twin pairs. These findings suggest that the interplay between fetal sex and twin type may have complex biological underpinnings that warrant further investigation. Furthermore, Esposito et al. (2023) reported that male neonates had a higher average birth weight than female neonates [ 18 ] , highlighting a consistent gender-related growth disparity from birth. They also observed that opposite-sex twin typically have higher average birth weights compared to female neonates [ 18 ] , which can be largely attributed to the inherent physiological and hormonal differences between male and female fetuses. These differences may influence intrauterine growth patterns and resource allocation, thereby contributing to variations in birth weight and length within twin pairs. Our findings align closely with these findings; our results also revealed a significant difference in BWD between the opposite-sex and same-sex twin pairs (Tables 4 –5), further supporting the influence of both sex and twin type on birth weight variation and highlighting both sex composition and twin type are important determinants of birth weight variation. The increased BWD in opposite-sex twins could be related to differential growth trajectories driven by the contrasting endocrine environments that male and female fetuses create in utero. This phenomenon may affect placental function or nutrient sharing, ultimately influencing fetal growth rates. One major innovation of the present study was that only 718 healthy pre-pregnant women with a normal pre-pregnancy BMI were recruited to exclude the influences of obesity and other complications (e.g., gestational diabetes and eclampsia) on birth weight. The results revealed that a higher DII in the second trimester was a risk factor for BWD, as inflammation could induce placental dysangiogenesis. Fetal distress is a critical state caused by intrauterine hypoxia and manifests as hypoxemia and acidosis. Notably, prolonged labor, nuchal cord, and gestational complications can all increase the risk of fetal distress [ 19 ] . The present study indicated that the incidence of fetal distress was significantly higher in the observation group than that in the control group, indicating the positive role of an anti-inflammatory diet in pregnancy in reducing the occurrence of fetal distress. In the future research, detection of serum levels of inflammatory cytokines may be included in prenatal screening to identify those with mild inflammation and administer dietary intervention, if necessary, so as to prevent BWD and postpartum complications. A further limitation of the study is the relatively small number of BWD cases included in the final analysis (n = 9), which may substantially reduce statistical power for detecting moderate or small effect sizes. As demonstrated in our power analysis, the limited number of observations in the BWD group may lead to underestimation or overestimation of associations. Caution is warranted when interpreting subgroup differences, and the results should be validated in larger multicenter cohorts to ensure robustness and generalizability. A key limitation of this study is the absence of data on chorionicity, which is known to significantly affect fetal development and outcomes in twin pregnancies. Specifically, differences between monochorionic monoamniotic and dichorionic diamniotic twins - such as placental sharing and vascular anastomoses - can contribute to variations in birth weight and the risk of discordance. Due to data constraints, we were only able to classify twins based on sex composition (i.e., same-sex vs. opposite-sex), which does not fully capture the biological and clinical implications of chorionicity. As such, the inability to stratify our analysis by specific twin types limits the granularity and generalizability of our findings. Future studies should incorporate chorionicity data to provide a more comprehensive understanding of its role in birth weight discordance. Another limitation of our dietary assessment is that the one-day food record may not fully represent habitual nutrient intake due to day-to-day variability. Although a dietary frequency questionnaire was administered to capture intake over the past two weeks, we did not conduct a formal comparison between the questionnaire data and the one-day food record. Therefore, potential discrepancies between these methods could affect the accuracy of dietary exposure estimation. Future studies may benefit from using multiple-day food records or repeated dietary assessments to better characterize habitual intake. Declarations Acknowledgements We thank all the participants in our study and the statistician at the clinical data centre, as well as nursing researchers who supported and encouraged us. Consent for Publication Not applicable. Availability of data and materials The data that support the findings of this study are available from Guangzhou Women and Children's Medical Center but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. However, the data can be provided by the corresponding author upon reasonable request and permission of Guangzhou Women and Children’s Medical Center. Author’s contributions Hua Zeng：Conceptualization, Methodology,Writing-original draft.Jie Zheng: Conceptualization, Methodology, Writing-original draft,. Yue Huang: Methodology, Formal analysis, Writing-original draft, Writing-review & editing, Data curation, Funding acquisition. Mi Cheng: Methodology, Writing-review & editing. Xiaodan Di: Methodology, Formal analysis, Funding acquisition. Lei Liu: Writing-review & editing, Project administration. Qiaozhu Chen: Supervision, Writing, Writing-review.Xinxin Liu：Formal analysis. Yuhong Pan:Data curation, Editing. Ethics approval and consent to participate The design of this study was approved by the Ethics Committee of Guangzhou Women and Children’s Medical Center (NO. 2022.071A01). This study was carried out according to the ethical standards of the Declaration of Helsinki of the World Medical Association. All participants gave written informed consent to participate in the study. Competing interests All other authors declare that they have no competing interests. Funding sources All expenses of this study were provided by the grants from Guangzhou Municipal Science and Technology Bureau: Prevention of Postpartum Hemorrhage—Application of Tranexamic Acid in Anemic Pregnant Women, Project No.2023A03J0878 .The funding body did not play any role in design, data collection, data analyses and interpretation and in writing the manuscript. References WIERZEJSKA R E. Review of Dietary Recommendations for Twin Pregnancy: Does Nutrition Science Keep Up with the Growing Incidence of Multiple Gestations? [J]. Nutrients, 2022, 14(6). MILAZZO R, GARBIN M, CONSONNI D, et al. Maternal hemodynamic evaluation in monochorionic twin pregnancy complicated by twin-to-twin transfusion syndrome treated with fetoscopic laser surgery [J]. Am J Obstet Gynecol MFM, 2024, 6(3): 101270. GOMEZ-LOPEZ N, GALAZ J, MILLER D, et al. The immunobiology of preterm labor and birth: intra-amniotic inflammation or breakdown of maternal-fetal homeostasis [J]. Reproduction, 2022, 164(2): R11-r45. WEI Y, DING J, LI J, et al. Metabolic Reprogramming of Immune Cells at the Maternal-Fetal Interface and the Development of Techniques for Immunometabolism [J]. Front Immunol, 2021, 12: 717014. TOTH A, STEINMEYER S, KANNAN P, et al. Inflammatory blockade prevents injury to the developing pulmonary gas exchange surface in preterm primates [J]. Sci Transl Med, 2022, 14(638): eabl8574. MURTHA A P, MENON R. Regulation of fetal membrane inflammation: a critical step in reducing adverse pregnancy outcome [J]. American Journal of Obstetrics & Gynecology, 2015, 213(4): 447-8. REYNOLDS L P, BOROWICZ P P, CATON J S, et al. Developmental Programming of Fetal Growth and Development [J]. Vet Clin North Am Food Anim Pract, 2019, 35(2): 229-47. AOYAMA T, LI D, BAY J L. Weight Gain and Nutrition during Pregnancy: An Analysis of Clinical Practice Guidelines in the Asia-Pacific Region [J]. Nutrients, 2022, 14(6). DöRSAM A F, PREIßL H, MICALI N, et al. The Impact of Maternal Eating Disorders on Dietary Intake and Eating Patterns during Pregnancy: A Systematic Review [J]. Nutrients, 2019, 11(4). KHALIL A, BEUNE I, HECHER K, et al. Consensus definition and essential reporting parameters of selective fetal growth restriction in twin pregnancy: a Delphi procedure [J]. Ultrasound Obstet Gynecol, 2019, 53(1): 47-54. SHIVAPPA N, STECK S E, HURLEY T G, et al. Designing and developing a literature-derived, population-based dietary inflammatory index [J]. Public Health Nutr, 2014, 17(8): 1689-96. HARIHARAN R, ODJIDJA E N, SCOTT D, et al. The dietary inflammatory index, obesity, type 2 diabetes, and cardiovascular risk factors and diseases [J]. Obes Rev, 2022, 23(1): e13349. LUNG F W, SHU B C, CHIANG T L, et al. Twin-singleton influence on infant development: a national birth cohort study [J]. Child Care Health Dev, 2009, 35(3): 409-18. CHRISTENSEN R, CHAU V, SYNNES A, et al. Longitudinal neurodevelopmental outcomes in preterm twins [J]. Pediatr Res, 2021, 90(3): 593-9. ARNOLD K, WEINHOLD K R, ANDRIDGE R, et al. Improving Diet Quality Is Associated with Decreased Inflammation: Findings from a Pilot Intervention in Postmenopausal Women with Obesity [J]. J Acad Nutr Diet, 2018, 118(11): 2135-43. NIKNAM M, PAKNAHAD Z, MARACY M R, et al. Dietary fatty acids and inflammatory markers in patients with coronary artery disease [J]. Adv Biomed Res, 2014, 3: 148. JELENKOVIC A, SUND R, YOKOYAMA Y, et al. Birth size and gestational age in opposite-sex twins as compared to same-sex twins: An individual-based pooled analysis of 21 cohorts [J]. Scientific Reports, 2018, 8(1): 6300. ESPOSITO G, CANTARUTTI A, MAURI P A, et al. Prevalence and Factors Associated With Intertwin Birth Weight Discordance Among Same-Sex Twins in Lombardy, Northern Italy [J]. Twin Res Hum Genet, 2023, 26(2): 177-83. YOKOI K, IWATA O, KOBAYASHI S, et al. Intrauterine Inflammation, Excessive Fetal Growth and Respiratory Morbidities in Moderate-To-Late Preterm Neonates [J]. Neonatology, 2024, 121(2): 258-65. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8035827","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":556265499,"identity":"faccaae5-5e16-498e-8393-72159b44221e","order_by":0,"name":"Hua Zeng","email":"","orcid":"","institution":"Guangzhou Women and Children's Medical Center, Guangzhou Medical university","correspondingAuthor":false,"prefix":"","firstName":"Hua","middleName":"","lastName":"Zeng","suffix":""},{"id":556265500,"identity":"6e0bab70-00b7-4023-bf40-9b03161904c9","order_by":1,"name":"Yue Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYBACxvkHGw58/GMjx8/eQKQW5hnMjQdnNqQZS/YcIFIL+wz25sO8DYcSN9xIIFIL7+zGhsO8Ow4kzpz5eOMNhhqbaIJaJOccbDg498wd437ptGILhmNpuQ2EtBg2JDYceMP2THbm7BwzCcaGw4S12B8AauFhO8y44eYZIrUwzkhsOMjbdlhxww0eYrX0AP0y4wwokIF+SSDGL4zt7Y8/fKgAReXhjTc+1NgQ1oIMDCQSSFEO0UKqjlEwCkbBKBgZAAAO0E27j0MDVgAAAABJRU5ErkJggg==","orcid":"","institution":"Guangzhou Women and Children's Medical Center, Guangzhou Medical university","correspondingAuthor":true,"prefix":"","firstName":"Yue","middleName":"","lastName":"Huang","suffix":""},{"id":556265501,"identity":"19f0b21b-57f8-4add-9e19-0067b5732025","order_by":2,"name":"Jie Zheng","email":"","orcid":"","institution":"Guangdong Provincial Maternal and Child Health 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Introduction","content":"\u003cp\u003eTwin pregnancy, the most common type of multiple pregnancy, occurs when two eggs are simultaneously fertilized. Gestation is an important stage of early life, and healthy diet in pregnancy is a necessity for ensuring maternal and fetal health\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Inflammation manifests as a physiological response of the immune system to cell and tissue damage\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Pregnant women generally suffer from chronic low grade inflammation as a result of maternal physiological adaptation and fetal growth-induced metabolic stress\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. A balance between pro-inflammatory and anti-inflammatory factors plays a vital role in normal pregnancy. It has been found that a high inflammatory level in pregnancy increases the risk of adverse pregnancy outcomes\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFast fetal growth in gestational period gives rises to a rapidly increasing demand for nutrition. Maternal nutritional status in this period may profoundly influence intrauterine fetal growth, and such impact may last a lifetime\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Sufficient nutritional supply in the gestational period is critical for fetal growth. Maternal body is the only source of nutrients for fetuses, highlighting the importance of healthy diet in pregnancy\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. At present, the pathogenesis and diagnostic criteria for birth weight discordance (BWD) remain controversial issues, with perspectives on them appearing to diverge both domestically and internationally. It is generally accepted that BWD is associated with placental and genetic factors and umbilical cord abnormalities. Prior research showed that an unhealthy diet elevates the maternal inflammation level and exerts an adverse impact on pregnancy outcomes\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Regulating maternal inflammation level and maintaining a balance between pro-inflammatory and anti-inflammatory factors is highly suggested for safeguarding maternal and fetal health. The present study discussed the influences of dietary inflammatory index (DII) during the second trimester of pregnancy on BWD and postpartum complications in twin pregnancies.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Subjects\u003c/h2\u003e\u003cp\u003eA total 1568 women with twin pregnancies who received regular prenatal screening and pregnancy tests at the obstetric outpatient clinic from January 2021 to December 2022 and gave birth after being admitted to the Guangzhou Women and Children Medical Center (Guangzhou, China) were initially enrolled in this study. Those cases who had miscarriage and inpatient induction of labor were excluded. The observation group consisted of 55 pregnant women with BWD. At a 1:1 age-matching approach and random number table selection, 1513 control subjects without BWD were initially identifies. For the final selection analysis, only 718 healthy women with a normal pre-pregnancy BMI were recruited.\u003c/p\u003e\u003cp\u003eBWD was diagnosed if the birth weight difference between twins was 22% and above\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Birth weight difference was calculated as follows: Birth weight difference = (larger twin weight - smaller twin weight)/larger twin weight\u0026times;100. The infant with the heavier weight was designated as the larger twin, while the one with the lighter weight was identified as the smaller twin.\u003c/p\u003e\u003cdiv id=\"Sec4\" class=\"Section3\"\u003e\u003ch2\u003e2.1.2 Statistical power analysis\u003c/h2\u003e\u003cp\u003eUsing the \u0026ldquo;pwr\u0026rdquo; package in R, post hoc power analyses were performed to assess the adequacy of the sample size. For continuous outcomes approximated by a two-sample t-test, the power to detect a medium effect size (Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.5) with the current sample sizes (9 in the observation group and 709 in controls) was approximately 32%. Power was even lower for small effects (d\u0026thinsp;=\u0026thinsp;0.2, ~\u0026thinsp;9%) and improved to about 66% only for large effects (d\u0026thinsp;=\u0026thinsp;0.8). To reach the conventional 80% power threshold at medium effect size, at least 64 participants per group would be required.\u003c/p\u003e\u003cp\u003eFor categorical outcomes analyzed by chi-square tests, assuming a small to medium effect size (Cohen\u0026rsquo;s w\u0026thinsp;=\u0026thinsp;0.3), the total sample size of 718 provided adequate power (~\u0026thinsp;100%). These results highlight the limited statistical power for some continuous variable comparisons due to the small observation group, which should be considered when interpreting findings.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Inclusion and exclusion criteria\u003c/h2\u003e\u003cp\u003eThe inclusion criteria were as follows: (1) History of receiving regular prenatal screening at the obstetric outpatient clinic of our hospital; (2) Women with twin pregnancies; (3) Gestational age between 13\u0026ndash;27 weeks; (4) Women who aged 18\u0026ndash;35 years old; (5) Approval was gained from the ethics committee of a hospital, and patients or their family members signed the written informed consent form.\u003c/p\u003e\u003cp\u003eThe exclusion criteria were as follows: (1) Serious diseases of the heart, lungs, liver, and kidneys; (2) Combined with diabetes or gestational diabetes; (3) Combined with hypertension or gestational hypertension; (4) Acute and chronic infectious diseases; (5) Neurological dysfunction or psychiatric disorders; (6) Termination of pregnancy for various reasons.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Questionnaire survey\u003c/h2\u003e\u003cp\u003eThe self-made questionnaire (supplementary file) was administered to all of the enrolled subjects. Interviewers who received uniform training filled in the questionnaire after face-to-face interview with the study subjects. The questionnaire consisted of four dimensions, including baseline information, reproductive history, lifestyle, and diet and nutritional supplement intake. Each subject was inquired about the intake frequency and the average intake of each type of food in the second trimester of pregnancy. The study subjects\u0026rsquo; height and body weight were measured on site by interviewers.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.4 DII calculation\u003c/h2\u003e\u003cp\u003eDietary intake was surveyed for all subjects in the second trimester (gestational age, 13\u0026ndash;27 weeks). The amounts of food consumed for meals, extra meals, and snacks during 24 hours per day were recorded. Food intake during feasts was excluded. The type of food covered by the questionnaire included cereals, livestock, poultry, eggs, animal innards, aquatic products, bean products, milk products, coarse cereals, vegetables, fruits, nuts, and snacks. The raw weights and cooked weights of each type of food were determined by weighing. The actual daily intake of each type of food was determined based on the ratio of raw to cooked weight. The daily nutrient intake level was calculated using the nutritional analysis software. The conversion formulae was obtained from China Food Composition Tables\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. DII was calculated as follows: DII = (Z-score for the total inflammation score of nutrients), where Z-score was calculated as follows: Z-score = (individual reported intake - global daily mean intake)/global standard deviation \u0026times; inflammatory effect index of nutrient. To minimize right skewing, the Z-score was converted into a centered percentile score [(2 * percentile of Z-value \u0026minus;\u0026thinsp;1)]. As a result, a symmetric distribution was obtained centering around zero. In the abovementioned formula, n represents any of 17 nutrients (folic acid, calcium, iron, DHA, complex nutrients, cereal, domestic animals, beans and bean products, vegetables, fruits, coarse cereals, poultry, fish and aquatic products, animal innards, milk and dairy products, nuts, and eggs), and the results were combined to obtain the personal DII. The higher DII scores (greater than 0) indicate a more pro-inflammatory (less healthy) diet, while lower scores (below 0) reflect a more anti-inflammatory (healthier) dietary pattern.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Second trimester prenatal screening and pregnancy outcomes\u003c/h2\u003e\u003cp\u003eFasting venous blood was drawn during prenatal screening in the second trimester. The serum levels of the following inflammatory factors were measured by enzyme-linked immunosorbent assay (ELISA): C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), interleukin-10 (IL-10), and interleukin-lβ (IL-lβ). The obstetric history was assessed post-delivery. Pregnancy outcomes were recorded, including gestational diabetes, placental abruption, polyhydramnios, postpartum hemorrhage, and gestational hypertension.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.6 Statistical analysis\u003c/h2\u003e\u003cp\u003eStatistical analysis was conducted using SPSS 26.0 software (IBM, Armonk, NY, USA) and R studio (Version. 2025.05.0\u0026thinsp;+\u0026thinsp;496). Normally distributed continuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation and compared using Mann\u0026ndash;Whitney U test. Categorical variables were expressed as frequency, composition ratio, and rate. Intergroup comparisons of categorical variables were conducted using the Chi-square test. P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Adjustments were made for potential influential factors, including gestational BMI, age, parity, and educational level. Multivariate logistic regression analysis was performed to identify influential factors of BWD in twin pregnancies.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Participants\u0026rsquo; baseline data\u003c/h2\u003e\u003cp\u003eA total of 718 pregnant women were surveyed, with an average age of 30.01 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 4.23 years old. The youngest participant aged 20 years old, and the eldest was 33 years old. The average height was 160.21 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 4.78 cm. The average pregestational body weight was 57.21 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 9.23 kg, and the average pregestational BMI was 22.35 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 3.78 kg/m\u003csup\u003e2\u003c/sup\u003e. Further details are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\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\u003eBaseline characteristics of recruited participants [n (%)].\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eObservation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eParticipants [n (%)]\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e709 (98.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9 (1.3)\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\u003e\u003cb\u003eAge (years old) [n (%)]\u003c/b\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=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18 - \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\le\\:\\)\u003c/span\u003e\u003c/span\u003e 25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e208 (29.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0 (0.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.168\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25 - \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\le\\:\\)\u003c/span\u003e\u003c/span\u003e 30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e311 (43.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3 (33.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e30\u0026ndash;35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e190 (26.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6 (66.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePre-pregnancy BMI (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e) [n (%)]\u003c/b\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=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18.5- \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\le\\:\\)\u003c/span\u003e\u003c/span\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e709 (98.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9 (1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGravidity [n (%)]\u003c/b\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=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.200\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\u003e381 (53.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2 (22.2)\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\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e262 (37.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4 (44.4)\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\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\ge\\:\\)\u003c/span\u003e\u003c/span\u003e 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e66 (9.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3 (33.3)\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\u003e\u003cb\u003eOpposite-sex twins [n (%)]\u003c/b\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=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e492 (69.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3 (33.3)\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\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e217 (30.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6 (66.7)\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\u003cb\u003eDietary supplement use [n (%)]\u003c/b\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=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFolic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e456 (64.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3 (33.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCalcium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e216 (30.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1 (11.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.210\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIron\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e80 (11.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1 (11.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.967\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDHA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e92 (13.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2 (22.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.415\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eComplex nutrients [n (%)]\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e290 (40.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5 (55.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.375\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCereal (g) (mean\u003c/b\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e \u003cb\u003eSD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e444.13 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 73.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e387.00 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 77.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDomestic animals (g) (mean\u003c/b\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e \u003cb\u003eSD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e109.45 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 51.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e157.33 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 41.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBeans and bean products (g) (mean\u003c/b\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e \u003cb\u003eSD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e159.04 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 39.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e104.22 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 23.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVegetables (g) (mean\u003c/b\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e \u003cb\u003eSD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e450.04 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 144.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e298.44 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 120.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFruits (g) (mean\u003c/b\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e \u003cb\u003eSD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e459.65 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 122.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e332.56 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 130.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCoarse cereals (g) (mean\u003c/b\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e \u003cb\u003eSD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e440.91 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 148.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e301.67 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 91.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePoultry (g) (mean\u003c/b\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e \u003cb\u003eSD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e64.10 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 21.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e44.78 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 15.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFish and aquatic products (g) (mean\u003c/b\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e \u003cb\u003eSD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e147.49 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 54.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e95.78 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 23.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAnimals innards (g) (mean\u003c/b\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e \u003cb\u003eSD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e46.34 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 17.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e81.56 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 28.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMilk and dairy products (g) (mean\u003c/b\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e \u003cb\u003eSD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e414.44 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 193.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e346.11 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 123.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.279\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNuts (g) (mean\u003c/b\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e \u003cb\u003eSD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22.79 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 5.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9.89 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 1.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSnacks (g) (mean\u003c/b\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e \u003cb\u003eSD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e86.00 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 33.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e144.67 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 26.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEgg (g) (mean\u003c/b\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e \u003cb\u003eSD)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e52.73 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 16.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e40.67 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 13.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.026\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=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Diet and DII\u003c/h2\u003e\u003cp\u003eThe intakes of cereals, poultry, eggs, aquatic products, bean products, milk products, coarse cereals, vegetables, fruits, and nuts were significantly lower in the observation group than those in the control group (p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e 0.05). The intakes of livestock, animal innards, and snacks were significantly higher in the observation group than those in the control group (p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e 0.05).\u003c/p\u003e\u003cp\u003eThe average DII in the second trimester was \u0026minus;\u0026thinsp;2.51 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 1.54. Among 1513 control subjects who were surveyed, 782 subjects had a DII below zero, indicating an anti-inflammatory tendency. Among 55 subjects in the observation group, 48 subjects had a DII above zero, highlighting a pro-inflammatory tendency. Additional data are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\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\u003eDII score of two groups.\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\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl \u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;709)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eObservation\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDII score [n (%)]\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\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDII\u0026gt;0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e375 (52.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9 (100.0)\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\u003eDII\u0026lt;0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e334 (47.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0 (0.0)\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\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Serum levels of inflammatory factors in the two groups of pregnant women\u003c/h2\u003e\u003cp\u003eThe serum levels of CRP, TNF-α, IL-6, IL-10, and l-1β were compared between the two groups, and the results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. In the second trimester, the serum levels of CRP, IL-6, and TNF-α were significantly higher in the observation group than those in the control group (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\u003eComparison of inflammatory cytokines in the second trimester between the two groups (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD).\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=\"left\" 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\u003eInflammatory cytokines\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl group\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;709)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eObservation group\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCRP (mg/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.75 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 0.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.79 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 1.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTNF-α (ng/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.80 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 0.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.61 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 0.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-6 (pg/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.55 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.38 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 1.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-10 (pg/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.20 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 0.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.17 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 0.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.998\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIL-1β (pg/mL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.87 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.50 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\pm\\:\\)\u003c/span\u003e\u003c/span\u003e 0.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.047\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=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Univariate and multivariate analysis of influential factors of BWD\u003c/h2\u003e\u003cp\u003eUnivariate logistic regression analyses identified several significant factors associated with the outcome. Folic acid intake showed a non-significant trend towards a protective effect in both univariate (odds ratio (OR)\u0026thinsp;=\u0026thinsp;0.299, 95% confidence interval (CI): 0.081\u0026ndash;1.109, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.071) and multivariate analyses (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.523, 95% CI: 0.132\u0026ndash;2.065, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.355). Higher intake of cereals (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.989, 95% CI: 0.980\u0026ndash;0.998, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.016), beans and bean products (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.963, 95% CI: 0.945\u0026ndash;0.982, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e 0.001), vegetables (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.992, 95% CI: 0.988\u0026ndash;0.997, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.002), fruits (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.992, 95% CI: 0.986\u0026ndash;0.997, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.002), coarse cereals (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.993, 95% CI: 0.989\u0026ndash;0.998, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.006), poultry (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.956, 95% CI: 0.925\u0026ndash;0.988, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.007), fish and aquatic products (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.981, 95% CI: 0.967\u0026ndash;0.994, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.005), and nuts (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.581, 95% CI: 0.462\u0026ndash;0.731, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e 0.001) were each inversely associated with the outcome, indicating a potential protective effect. Conversely, higher consumption of domestic animals (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 1.016, 95% CI: 1.005\u0026ndash;1.027, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.005), animals\u0026rsquo; innards (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 1.094, 95% CI: 1.055\u0026ndash;1.134, p \u0026lt; 0.001), and snacks (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 1.051, 95% CI: 1.028\u0026ndash;1.075, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e 0.001) were positively associated with increased odds. Among inflammatory markers, elevated levels of CRP (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 5.801, 95% CI: 2.544\u0026ndash;13.228, p \u0026lt; 0.001), TNF-α (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 8.291, 95% CI: 2.681\u0026ndash;25.644, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\u0026lt;\\)\u003c/span\u003e\u003c/span\u003e 0.001), and IL-6 (OR = 2.466, 95% CI: 1.294\u0026ndash;4.699, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.006) were significantly associated with higher odds of the outcome. In contrast, IL-1β showed a protective effect (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.221, 95% CI: 0.059\u0026ndash;0.819, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.024). Additionally, gravidity of one (compared to zero) (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.125, 95% CI: 0.024\u0026ndash;0.648, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.013) and opposite-sex twins (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.238, 95% CI: 0.064\u0026ndash;0.882, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.032) were inversely associated with the outcome. The Dietary Inflammatory Index (DII) score showed a borderline association (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 16.925, 95% CI: 0.977\u0026ndash;293.148, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.052) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn multivariate logistic regression analysis adjusting for potential confounders, most of these associations attenuated and became statistically non-significant. Notably, nuts intake remained significantly protective (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.878, 95% CI: 0.781\u0026ndash;0.988, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.031). The consumption of snacks showed a trend toward increased odds but did not reach statistical significance (OR \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 1.018, 95% CI: 0.999\u0026ndash;1.037, p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:=\\)\u003c/span\u003e\u003c/span\u003e 0.066). Other factors, including cereals, domestic animals, beans and bean products, vegetables, fruits, coarse cereals, poultry, fish and aquatic products, animals\u0026rsquo; innards, inflammatory markers (CRP, TNF-α, IL-6, IL-1β), gravidity, and opposite-sex twins, were not independently associated with the outcome after adjustment (all p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\u0026gt;\\)\u003c/span\u003e\u003c/span\u003e 0.1) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\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\u003eUnivariate and multivariate analysis of influential factors of BWD.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eInfluential factors\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eUnivariate logistic regression\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u003cp\u003eMultivariate logistic regression\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFolic acid (g)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.299\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.081\u0026ndash;1.109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.071\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.523\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.132\u0026ndash;2.065\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.355\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCereals (g)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.989\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.980\u0026ndash;0.998\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.995\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.985\u0026ndash;1.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDomestic animals (g)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.005\u0026ndash;1.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.992\u0026ndash;1.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.565\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBeans and bean products (g)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.963\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.945\u0026ndash;0.982\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.991\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.974\u0026ndash;1.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.305\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVegetables (g)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.992\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.988\u0026ndash;0.997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.994\u0026ndash;1.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.587\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFruits (g)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.992\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.986\u0026ndash;0.997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.998\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.993\u0026ndash;1.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.562\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCoarse cereals (g)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.993\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.989\u0026ndash;0.998\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.992\u0026ndash;1.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.227\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePoultry (g)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.956\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.925\u0026ndash;0.988\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.991\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.96\u0026ndash;1.023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.570\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFish and aquatic products (g)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.981\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.967\u0026ndash;0.994\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.987\u0026ndash;1.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.942\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAnimals\u0026rsquo; innards (g)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.094\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.055\u0026ndash;1.134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.978\u0026ndash;1.053\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.444\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNuts (g)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.581\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.462\u0026ndash;0.731\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.878\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.781\u0026ndash;0.988\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.031\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSnacks (g)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.051\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.028\u0026ndash;1.075\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.999\u0026ndash;1.037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.066\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEggs (g)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.955\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.917\u0026ndash;0.995\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.029\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.956\u0026ndash;1.043.809\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.885\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCRP (mg/L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5.801\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.544\u0026ndash;13.228\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.583\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.658\u0026ndash;6.563\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.305\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTNF-\u003c/b\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{\\alpha\\:}\\)\u003c/span\u003e\u003c/span\u003e \u003cb\u003e(ng/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8.291\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.681\u0026ndash;25.644\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.335\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.831\u0026ndash;2.274\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.108\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIL-6 (pg/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.466\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.294\u0026ndash;4.699\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.579\u0026ndash;6.653\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.693\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIL-10\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.934\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.372\u0026ndash;2.341\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.884\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIL-1\u003c/b\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{\\beta\\:}\\)\u003c/span\u003e\u003c/span\u003e \u003cb\u003e(pg/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.059\u0026ndash;0.819\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.588\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.153\u0026ndash;2.265\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.441\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDII score\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16.925\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.977\u0026ndash;293.148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGravidity\u003c/b\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=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\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\u003e0.125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.024\u0026ndash;0.648\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.276\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.049\u0026ndash;1.543\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.143\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.326\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.078\u0026ndash;1.360\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.124\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.403\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.067\u0026ndash;2.418\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.320\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOpposite-sex twins\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.238\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.064\u0026ndash;0.882\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.097\u0026ndash;1.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.165\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"},{"header":"3. Discussion","content":"\u003cp\u003eSince the concept of DII was first proposed, it has been found to be closely associated with various human diseases\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. However, few studies have concentrated on the influences of DII on maternal health in the second trimester of twin pregnancies. The present study revealed the correlation between DII and pregnancy outcomes in twin pregnancies.\u003c/p\u003e\u003cp\u003eIn the present study, healthy pregnant women without typical inflammatory symptoms in the second trimester were enrolled and divided them into control group and observation group based on the occurrence of BWD. The results revealed that BWD was more likely associated with a pro-inflammatory tendency. As evidenced by the daily intakes of different types of food in the two groups, pro-inflammatory or anti-inflammatory tendency was not determined by the intake of one or several types of food, while it was indicated by the preference for or aversion to all types of food combined. DII can be used to guide pregnant women to adopt a more anti-inflammatory diet on top of a generally balanced diet.\u003c/p\u003e\u003cp\u003eThe development of BWD is a multi-factorial and multi-step process\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Epidemiological studies have indicated the multiplicity of risk factors for BWD, among which the common ones include maternal, fetal, and genetic factors. Once BWD happens, the prognosis is mainly poor despite interventional measures. Except for BWD caused by genetic factors, the majority of BWD cases are preventable\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Interventional measures addressing specific risk factors may be administered to the target populations to prevent the occurrence of BWD and improve maternal and fetal outcomes. It has been reported that DII gradually decreases as the gestational age increases. However, in the present study, DII did not significantly differ in the same group of pregnant women in the second trimester over time. Notably, the incidence of BWD was significantly higher in subjects with a pro-inflammatory tendency in the second trimester compared with those with an anti-inflammatory tendency. Therefore, the incidence of BWD may be lowered in twin pregnancies if pregnant women select an anti-inflammatory diet in the second trimester.\u003c/p\u003e\u003cp\u003eArnold K et al. conducted a dietary interventional study on 14 menopausal women, which demonstrated that a diet low in sugar but rich in fibers and fish led to a decrease in the serum levels of inflammatory factors\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. The present study indicated that pregnant women in the observation group who had a pro-inflammatory tendency in the second trimester had significantly higher serum levels of CRP, IL-6, and TNF-α compared with those in the control group. According to another study\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e, intake of saturated fatty acids (SFAs) significantly increased the serum levels of inflammatory factors in patients who aged above 45 years. On the contrary, taking eicosapentaenoic acid and docosahexaenoic acid (DHA) supplements reduced the levels of inflammatory factors, which agreed with findings of the present study (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Pregnant women are advised to consume an anti-inflammatory diet abundant in vegetables, legumes, and fish while minimizing the intake of pro-inflammatory food products, such as sugar and red meat. This dietary approach aims to lower serum levels of inflammatory factors during pregnancy.\u003c/p\u003e\u003cp\u003eFrom a mechanistic perspective, the association between higher DII and increased risk of BWD may be partially explained by placental pathophysiology. Maternal pro-inflammatory diets may promote low-grade systemic inflammation, which could impair placental vascular remodeling and trophoblast invasion, lead to oxidative stress, and disrupt normal angiogenesis. These pathological changes may reduce placental perfusion asymmetrically between twin fetuses, contributing to differential fetal growth. Additionally, inflammation-related alterations in angiogenic factors such as VEGF, PlGF, and sFlt-1 might affect nutrient transport efficiency, leading to increased discordance in fetal growth. These mechanisms suggest that DII may influence BWD through inflammation-induced placental dysfunction.\u003c/p\u003e\u003cp\u003eIn addition to other potential risk factors, twin type and gender appear to play a critical role in influencing the BWD. The impact of these biological variables on fetal growth and birth outcomes has been well documented in the literature. For instance, Jelenkovic et al. (2018), they specifically reported that males having a co-twin sister were heavier and longer than those with a co-twin brother\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e, suggesting that the presence of a sister may positively affect the growth of male fetuses. In contrast, female twins\u0026rsquo; birth weight and length did not differ significantly whether their co-twin was male or female\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e, indicating a possible sex-specific interaction effect on growth within twin pairs. These findings suggest that the interplay between fetal sex and twin type may have complex biological underpinnings that warrant further investigation.\u003c/p\u003e\u003cp\u003eFurthermore, Esposito et al. (2023) reported that male neonates had a higher average birth weight than female neonates\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e, highlighting a consistent gender-related growth disparity from birth. They also observed that opposite-sex twin typically have higher average birth weights compared to female neonates\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e, which can be largely attributed to the inherent physiological and hormonal differences between male and female fetuses. These differences may influence intrauterine growth patterns and resource allocation, thereby contributing to variations in birth weight and length within twin pairs. Our findings align closely with these findings; our results also revealed a significant difference in BWD between the opposite-sex and same-sex twin pairs (Tables\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u0026ndash;5), further supporting the influence of both sex and twin type on birth weight variation and highlighting both sex composition and twin type are important determinants of birth weight variation. The increased BWD in opposite-sex twins could be related to differential growth trajectories driven by the contrasting endocrine environments that male and female fetuses create in utero. This phenomenon may affect placental function or nutrient sharing, ultimately influencing fetal growth rates.\u003c/p\u003e\u003cp\u003eOne major innovation of the present study was that only 718 healthy pre-pregnant women with a normal pre-pregnancy BMI were recruited to exclude the influences of obesity and other complications (e.g., gestational diabetes and eclampsia) on birth weight. The results revealed that a higher DII in the second trimester was a risk factor for BWD, as inflammation could induce placental dysangiogenesis. Fetal distress is a critical state caused by intrauterine hypoxia and manifests as hypoxemia and acidosis. Notably, prolonged labor, nuchal cord, and gestational complications can all increase the risk of fetal distress\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. The present study indicated that the incidence of fetal distress was significantly higher in the observation group than that in the control group, indicating the positive role of an anti-inflammatory diet in pregnancy in reducing the occurrence of fetal distress. In the future research, detection of serum levels of inflammatory cytokines may be included in prenatal screening to identify those with mild inflammation and administer dietary intervention, if necessary, so as to prevent BWD and postpartum complications.\u003c/p\u003e\u003cp\u003eA further limitation of the study is the relatively small number of BWD cases included in the final analysis (n\u0026thinsp;=\u0026thinsp;9), which may substantially reduce statistical power for detecting moderate or small effect sizes. As demonstrated in our power analysis, the limited number of observations in the BWD group may lead to underestimation or overestimation of associations. Caution is warranted when interpreting subgroup differences, and the results should be validated in larger multicenter cohorts to ensure robustness and generalizability.\u003c/p\u003e\u003cp\u003eA key limitation of this study is the absence of data on chorionicity, which is known to significantly affect fetal development and outcomes in twin pregnancies. Specifically, differences between monochorionic monoamniotic and dichorionic diamniotic twins - such as placental sharing and vascular anastomoses - can contribute to variations in birth weight and the risk of discordance. Due to data constraints, we were only able to classify twins based on sex composition (i.e., same-sex vs. opposite-sex), which does not fully capture the biological and clinical implications of chorionicity. As such, the inability to stratify our analysis by specific twin types limits the granularity and generalizability of our findings. Future studies should incorporate chorionicity data to provide a more comprehensive understanding of its role in birth weight discordance. Another limitation of our dietary assessment is that the one-day food record may not fully represent habitual nutrient intake due to day-to-day variability. Although a dietary frequency questionnaire was administered to capture intake over the past two weeks, we did not conduct a formal comparison between the questionnaire data and the one-day food record. Therefore, potential discrepancies between these methods could affect the accuracy of dietary exposure estimation. Future studies may benefit from using multiple-day food records or repeated dietary assessments to better characterize habitual intake.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe thank all the participants in our study and the statistician at the clinical data centre, as well as nursing researchers who supported and encouraged us.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent for Publication\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from Guangzhou Women and Children\u0026apos;s Medical Center but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. However, the data can be provided by the corresponding author upon reasonable request and permission of Guangzhou Women and Children\u0026rsquo;s Medical Center.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthor\u0026rsquo;s\u0026nbsp;contributions\u003c/p\u003e\n\u003cp\u003eHua Zeng：Conceptualization, Methodology,Writing-original draft.Jie Zheng: Conceptualization, Methodology, Writing-original draft,. Yue Huang: Methodology, Formal analysis, Writing-original draft, Writing-review \u0026amp; editing, Data curation, Funding acquisition. Mi Cheng: Methodology, Writing-review \u0026amp; editing. Xiaodan Di: Methodology, Formal analysis, Funding acquisition. Lei Liu: Writing-review \u0026amp; editing, Project administration. Qiaozhu Chen: Supervision, Writing, Writing-review.Xinxin Liu：Formal analysis. Yuhong Pan:Data curation, Editing.\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThe design of this study was approved by the Ethics Committee of Guangzhou Women and Children\u0026rsquo;s Medical Center (NO. 2022.071A01). This study was carried out according to the ethical standards of the Declaration of Helsinki of the World Medical Association. All participants gave written informed consent to participate in the study.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eAll other authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding sources \u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll expenses of this study were provided by the grants from Guangzhou Municipal Science and Technology Bureau: Prevention of Postpartum Hemorrhage\u0026mdash;Application of Tranexamic Acid in Anemic Pregnant Women, Project No.2023A03J0878 .The funding body did not play any role in design, data collection, data analyses and interpretation and in writing the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWIERZEJSKA R E. Review of Dietary Recommendations for Twin Pregnancy: Does Nutrition Science Keep Up with the Growing Incidence of Multiple Gestations? [J]. Nutrients, 2022, 14(6).\u003c/li\u003e\n\u003cli\u003eMILAZZO R, GARBIN M, CONSONNI D, et al. Maternal hemodynamic evaluation in monochorionic twin pregnancy complicated by twin-to-twin transfusion syndrome treated with fetoscopic laser surgery [J]. Am J Obstet Gynecol MFM, 2024, 6(3): 101270.\u003c/li\u003e\n\u003cli\u003eGOMEZ-LOPEZ N, GALAZ J, MILLER D, et al. The immunobiology of preterm labor and birth: intra-amniotic inflammation or breakdown of maternal-fetal homeostasis [J]. Reproduction, 2022, 164(2): R11-r45.\u003c/li\u003e\n\u003cli\u003eWEI Y, DING J, LI J, et al. Metabolic Reprogramming of Immune Cells at the Maternal-Fetal Interface and the Development of Techniques for Immunometabolism [J]. Front Immunol, 2021, 12: 717014.\u003c/li\u003e\n\u003cli\u003eTOTH A, STEINMEYER S, KANNAN P, et al. Inflammatory blockade prevents injury to the developing pulmonary gas exchange surface in preterm primates [J]. Sci Transl Med, 2022, 14(638): eabl8574.\u003c/li\u003e\n\u003cli\u003eMURTHA A P, MENON R. Regulation of fetal membrane inflammation: a critical step in reducing adverse pregnancy outcome [J]. American Journal of Obstetrics \u0026amp; Gynecology, 2015, 213(4): 447-8.\u003c/li\u003e\n\u003cli\u003eREYNOLDS L P, BOROWICZ P P, CATON J S, et al. Developmental Programming of Fetal Growth and Development [J]. Vet Clin North Am Food Anim Pract, 2019, 35(2): 229-47.\u003c/li\u003e\n\u003cli\u003eAOYAMA T, LI D, BAY J L. Weight Gain and Nutrition during Pregnancy: An Analysis of Clinical Practice Guidelines in the Asia-Pacific Region [J]. Nutrients, 2022, 14(6).\u003c/li\u003e\n\u003cli\u003eD\u0026ouml;RSAM A F, PREI\u0026szlig;L H, MICALI N, et al. The Impact of Maternal Eating Disorders on Dietary Intake and Eating Patterns during Pregnancy: A Systematic Review [J]. Nutrients, 2019, 11(4).\u003c/li\u003e\n\u003cli\u003eKHALIL A, BEUNE I, HECHER K, et al. Consensus definition and essential reporting parameters of selective fetal growth restriction in twin pregnancy: a Delphi procedure [J]. Ultrasound Obstet Gynecol, 2019, 53(1): 47-54.\u003c/li\u003e\n\u003cli\u003eSHIVAPPA N, STECK S E, HURLEY T G, et al. Designing and developing a literature-derived, population-based dietary inflammatory index [J]. Public Health Nutr, 2014, 17(8): 1689-96.\u003c/li\u003e\n\u003cli\u003eHARIHARAN R, ODJIDJA E N, SCOTT D, et al. The dietary inflammatory index, obesity, type 2 diabetes, and cardiovascular risk factors and diseases [J]. Obes Rev, 2022, 23(1): e13349.\u003c/li\u003e\n\u003cli\u003eLUNG F W, SHU B C, CHIANG T L, et al. Twin-singleton influence on infant development: a national birth cohort study [J]. Child Care Health Dev, 2009, 35(3): 409-18.\u003c/li\u003e\n\u003cli\u003eCHRISTENSEN R, CHAU V, SYNNES A, et al. Longitudinal neurodevelopmental outcomes in preterm twins [J]. Pediatr Res, 2021, 90(3): 593-9.\u003c/li\u003e\n\u003cli\u003eARNOLD K, WEINHOLD K R, ANDRIDGE R, et al. Improving Diet Quality Is Associated with Decreased Inflammation: Findings from a Pilot Intervention in Postmenopausal Women with Obesity [J]. J Acad Nutr Diet, 2018, 118(11): 2135-43.\u003c/li\u003e\n\u003cli\u003eNIKNAM M, PAKNAHAD Z, MARACY M R, et al. Dietary fatty acids and inflammatory markers in patients with coronary artery disease [J]. Adv Biomed Res, 2014, 3: 148.\u003c/li\u003e\n\u003cli\u003eJELENKOVIC A, SUND R, YOKOYAMA Y, et al. Birth size and gestational age in opposite-sex twins as compared to same-sex twins: An individual-based pooled analysis of 21 cohorts [J]. Scientific Reports, 2018, 8(1): 6300.\u003c/li\u003e\n\u003cli\u003eESPOSITO G, CANTARUTTI A, MAURI P A, et al. Prevalence and Factors Associated With Intertwin Birth Weight Discordance Among Same-Sex Twins in Lombardy, Northern Italy [J]. Twin Res Hum Genet, 2023, 26(2): 177-83.\u003c/li\u003e\n\u003cli\u003eYOKOI K, IWATA O, KOBAYASHI S, et al. Intrauterine Inflammation, Excessive Fetal Growth and Respiratory Morbidities in Moderate-To-Late Preterm Neonates [J]. Neonatology, 2024, 121(2): 258-65.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Dietary inflammatory index, Twin pregnancy, Birth weight discordance, Postpartum complications","lastPublishedDoi":"10.21203/rs.3.rs-8035827/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8035827/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e: To explore the correlations among dietary inflammatory index (DII) in the second trimester of pregnancy, occurrence of birth weight discordance (BWD), and postpartum complications in twin pregnancies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Pregnant women who received prenatal screening at Guangzhou Women and Children Medical Center (Guangzhou, China) were enrolled. A questionnaire survey was conducted to collect data from pregnant women, including baseline information, childbearing history, dietary intake, and situation of the current pregnancy. Serum levels of inflammatory factors (C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), interleukin-10 (IL-10), and interleukin-lβ (IL-lβ)) were measured by enzyme-linked immunosorbent assay (ELISA). DII in the second trimester was calculated based on dietary intake data. Univariate and multivariate logistic regression analyses were conducted to identify risk factors for BWD in twin pregnancies. The incidence of postpartum complications was compared between pregnant women with and without BWD.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The average DII values among 1568 pregnant women obeyed a normal distribution. According to twins’ birth weight, pregnant women were divided into observation group (n=9) and control group (n=709). DII was significantly higher in the observation group than that in the control group (p\u003cem\u003e \u003c/em\u003e\u0026lt; 0.05). The serum levels of CRP, TNF-α, and IL-6 significantly increased in the observation group compared with that in the control group (p\u003cem\u003e \u003c/em\u003e\u0026lt; 0.05). The results of univariate and multivariate logistic regression analyses indicated that DII higher than 0, age above 30 years old, parity ≥ 2, gravidity ≥ 2, pre-pregnancy body mass index (BMI)≦25 kg/m\u003csup\u003e2\u003c/sup\u003e, and opposite-sex twins were risk factors for BWD (p \u0026lt; 0.05). Pregnant women with a lower DII had a significantly reduced incidence of postpartum complications, including placental abruption, fetal distress, low-birth-weight babies, and macrosomia (p\u0026lt; 0. 05).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e DII could influence fetal growth in twin pregnancies, and a higher DII value was associated with higher risks of placental abruption and fetal distress. Pregnant women should adhere to a healthy diet to mitigate the risk of adverse pregnancy outcomes that may arise from a pro-inflammatory diet.\u003c/p\u003e","manuscriptTitle":"Association of dietary inflammatory index in the second trimester of pregnancy with birth weight discordance and postpartum complications in twin pregnancies","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-08 10:32:03","doi":"10.21203/rs.3.rs-8035827/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"de6147cd-df1d-4a39-9800-695169772222","owner":[],"postedDate":"December 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T08:58:18+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-08 10:32:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8035827","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8035827","identity":"rs-8035827","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}