Pre-pregnancy BMI and pregnancy anxiety in women with gestational diabetes mellitus: mediating effects of blood glucose and lipid levels1

Pre-pregnancy BMI and pregnancy anxiety in women with gestational diabetes mellitus: mediating effects of blood glucose and lipid levels1 | 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 Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Pre-pregnancy BMI and pregnancy anxiety in women with gestational diabetes mellitus: mediating effects of blood glucose and lipid levels 1 Hong Ouyang, Na Wu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1952539/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Body mass index (BMI) before pregnancy and blood glucose and lipid levels during and before pregnancy are associated with anxiety among pregnant women with gestational diabetes mellitus (GDM). No study has further explored the relationship between these factors. Our study is the first to explore the effects of blood glucose and lipids on the relationship between BMI and anxiety in pregnant women with GDM using mediation analysis. Methods: Pregnant women diagnosed with GDM after completing the oral glucose tolerance test during pregnancy were followed up from January 2019 to December 2021. Collecting basic information including age, education level, annual family income, pre-pregnancy BMI, gestational age, history of abortion, family history of anxiety and diabetes, sleep status, and other information. Results: After adjusting for relevant influencing factors, Pre-pregnancy BMI, FBG, HbA1c, 2hPG, and TG were still significantly correlated with the pregnancy anxiety scores . The results of the mediating effect model suggested that pre-pregnancy BMI significantly influenced the pregnancy anxiety scores in women with GDM (P<0.001); FBG, 2hPG, HbA1c, and TG significantly mediated the effect of BMI on the pregnancy anxiety scores, respectively, and played a partial mediator role between BMI and the pregnancy anxiety scores of pregnant women with GDM. Conclusion: Pre-pregnancy BMI was associated with pregnancy anxiety among pregnant women with GDM. High BMI before pregnancy can lead to increased anxiety . Blood glucose and lipid levels during pregnancy play a part in the influence of BMI before pregnancy on anxiety . anxiety blood glucose blood lipids mediating effects gestational diabetes mellitus Figures Figure 1 Figure 2 Introduction Recently, the incidence of gestational diabetes mellitus (GDM) among pregnant women is increasing [ 1 ], and poor blood glucose control in patients with GDM can lead to adverse pregnancy outcomes, posing a serious threat to both pregnant women and the fetus [ 2 ]. Therefore, pregnant women in this high-risk group suffer greater psychological pressure than healthy pregnant women [ 1 – 2 ]. The studies further showed that anxiety can increase the risk of GDM, and pregnant women diagnosed with GDM are also more susceptible to depression, anxiety, and stress [ 3 – 6 ].More than 40% of patients with GDM experience anxiety[ 7 – 8 ]. .At the same time, anxious pregnant women with gestational diabetes were more likely to have a variety of adverse maternal and infant outcomes through some studies[ 9 – 12 ]. The mediation effect model is an important method to explore the connection between factors. When an independent variable X can influence a dependent variable Y through an intermediate variable M, it indicates that M is an intermediate variable and plays an intermediate effect between X and Y. Recently, mediating effect analysis has not only been applied in psychology and other social science research fields, but also in medical research; several studies [ 14 – 16 ] have analyzed the relationship between relevant variables by establishing mediating effect models. Therefore, this study is the first to explore the effects of blood glucose and lipids on the relationship between pre-pregnancy BMI and pregnancy anxiety among pregnant women with GDM using mediation effect analysis. Research status of BMI and pregnancy anxiety in pregnant women with GDM Currently, obesity before pregnancy are increasingly common. Globally, the prevalence of overweight or obese women during pregnancy is rising rapidly, with current prevalence estimates ranging from 12.3–63.5% [ 16 – 18 ]. Overweight and obesity before pregnancy have a variety of adverse health consequences for both mother and child [ 19 ]. In a recent meta-analysis [ 20 ], the study found that women who were obese at the time of conception were more likely to have anxiety and depression symptoms during pregnancy than women of normal weight. Similarly, relevant studies also demonstrate that the BMI is positively correlated with anxiety during pregnancy[ 20 – 22 ]. Current status of research on the relationship between blood glucose level during pregnancy and pre-pregnancy BMI and pregnancy anxiety In addition to the direct influence of pre-pregnancy BMI on pregnancy anxiety, there is a close relationship between the blood glucose level and negative emotions such as anxiety and depression during pregnancy, as well as pre-pregnancy BMI. The level of glycated hemoglobin (HbA1c) is positive correlation to the scores for anxiety and depression [ 23 – 25 ]. FBG and 2hPG are closely associated with increased anxiety and depressive symptoms in GDM[ 26 – 27 ]. However, BMI levels before pregnancy have a significant influence on FBG and 2hPG levels of patients with GDM [ 28 ], suggesting that with the increase of BMI, blood glucose level increases significantly, indicating that both FBG and 2hPG levels are positively associated with BMI before pregnancy [ 28 ]. Research status of serum lipid levels, BMI before pregnancy, and pregnancy anxiety There is also a close connection between lipid levels during pregnancy and BMI before pregnancy and pregnancy anxiety. LDL-C, TC, and TG levels are positively correlated with anxiety and depression [ 29 ]; however, HDL-C is negatively correlated with anxiety[ 30 ]. Additionally, TG is positively correlated with BMI before pregnancy [ 21 ], while TC, LDL-C, and HDL-C are negatively correlated with BMI before pregnancy [ 31 ]. At present, many studies have discussed what factors contribute to anxiety in pregnant women with GDM, although these studies only discussed the relationship between a certain influencing factor and anxiety and did not study the correlation between multiple influencing factors. From the above discussion, we can see that there may be a certain relationship between BMI and blood glucose and lipid levels during pregnancy and pregnancy anxiety. Therefore, we conducted the first prospective study to link the role of pre-pregnancy BMI on pregnancy anxiety with blood glucose and lipid levels during pregnancy through mediation effect analysis and to further explore whether blood glucose and lipid levels play a mediating role in the relationship between BMI and pregnancy anxiety in pregnant women with GDM. Our hypotheses were as follows: The mediating effect analysis was conducted to further explore the influence of BMI on the pregnancy anxiety score and regulation process of blood glucose and lipid levels during pregnancy between BMI and pregnancy anxiety scores. Methods Research participants Pregnant women who visited the Department of Endocrinology or Obstetrics of the Affiliated Hospital of China Medical University from January 2019 to December 2021 were selected for long-term follow-up. These pregnant women were diagnosed with GDM.According to the 2012 World Health Organization guidelines [ 32 ], GDM is defined as meeting or exceeding at least one of the following indicators: (1) 5.1 mmol/L ≤ FPG level < 7.0 mmol/L, (2) 1-h plasma glucose level ≥ 10.0 mmol/L, and (3) 8.5 mmol/L ≤ 2h-PG level < 11.1 mmol/L. Finally, pregnant women with a GDM diagnosis were selected as the research subjects. Inclusion criteria (1) GDM was definitively diagnosed after the 75g OGTT test was completed during pregnancy. (2) Pregnant women with GDM should have completed the measurement of blood glucose (FBG, 2hPG, and HbA1c) and lipid (TG, TC, HDL, and LDL) levels in the endocrinology department or obstetrics department of our hospital during 14–28 weeks of gestation or were able to provide blood glucose or lipid indexes tested in local hospitals during 14–28 weeks of gestation. (3) Willing to accept the questionnaire survey after being informed of the survey content and able to fill in the questionnaire independently. (4) Complete clinical data. Exclusion criteria (1) Absence of basic information (2) Patients did not meet the diagnostic criteria of GDM (3) Patients with other diseases (4) Those who were unwilling to complete the questionnaire survey (5) Patients with psychological symptoms, such as compulsion, anxiety, and depression, before pregnancy The Self-rating Anxiety Scale (SAS)was conducted among pregnant women with GDM,and these women will be grouped according to their SAS scores. Data collection The data collected mainly included general demographic data, health data, personal habits, BMI before pregnancy, blood glucose (FBG, 2hPG, and HbA1c) and lipid (TG, TC, HDL, and LDL) levels, and systolic blood pressure levels during pregnancy, pregnancy anxiety, and weight gain during pregnancy. Questionnaire information The survey included: (1) Demographic data: age, education level, annual family income, and others. (2) Health data: including height before pregnancy, weight before pregnancy, weight gain during pregnancy, gestational age, history of abortion, family history of anxiety, family history of diabetes, and sleep status. Medical history (1) Evaluation of anxiety during pregnancy: After the pregnant women were definitively diagnosed with GDM, the SAS was used within 1–2 weeks to evaluate their anxiety state. The SAS, compiled by Zung in 1971, is a clinical measurement tool for assessing patients' subjective symptoms of anxiety. The SAS is a self-assessment tool for anxiety with high reliability and validity and is widely used in medical-related studies [ 33 – 36 ]. Participants filled in items according to the contents of the scale. There are a total of 20 test questions on the SAS, all of which adopt a four-level scoring method. The main evaluation items are the frequency of symptom occurrence defined by the following criteria: "A" no or little time; "B" A small part of the time; "C" quite A lot of the time; and "D" for the most part or all of the time (the "A" "B" "C" "D" for "1" "2" "3" "4 scoring points") (Figure.1). Total rough score = total score of 20 items, demarcation is 40 points. Standard points = total rough points ×1.25, demarcation points are 50 points. If SAS standard score ≤ 50, it means no anxiety; SAS standard score ≥ 50 points, indicating anxiety, including 50–59 points of mild anxiety, 60–69 points of moderate anxiety, more than 69 points of severe anxiety. (2) Blood glucose and lipid measurements: Blood glucose (FBG, 2hPG, and HbA1c) and lipid (TG, TC, HDL, LDL) levels were recorded. Variable definition and assignment Pregnant women with GDM were divided into two educational background groups (junior college and below and college and above), three annual household income groups (< 60,000RMB [low middle class], 60,000-140,000RMB [middle middle class], and ≥ 140,000RMB [upper middle class]), and three sleep time groups ( 8 h [adequate sleep]). The specific assignment is shown in Table 1 . Table1 Variable assignment table Variable Assignment Level of education 1= Junior college and below；2= University and above Annual household income（Ten thousand yuan） 1＜6；2=6-14；3＞14 History of abortion Family history of anxiety Family history of diabetes Sleep during pregnancy （h） 1 = Yes；0 = No 1 = Yes；0 = No 1 = Yes；0 = No 1＜6；2=6-8；3＞8 Quality control Participants were determined strictly in accordance with the inclusion and exclusion criteria for selection. Before filling in the questionnaire, the investigators were trained to assist participants with understanding the research content and significance of each item in the questionnaire; they could ask any questions needed to clarify their doubts in a timely manner. After that, the investigators issued the questionnaire uniformly to each participant and explained the requirements of filling in the questionnaire with the same instructions. Statistical analyses First, descriptive analyses were used to describe the general characteristics of the study population. Second, Spearman correlation analysis was used to determine whether there was any correlation between pre-pregnancy BMI, blood glucose, blood lipids, and pregnancy anxiety scores. Factors influencing the pregnancy anxiety scores were analyzed by a binary logistic regression model. Finally, SPSS macro process program designed by Hayes was used to complete data analysis. Results Basic participant characteristics Basic information of the participants is shown in Table 2. 275 pregnant women with GDM were included and divided into the anxiety group (standard score ≥50) or non-anxiety group (standard score <50) according to the anxiety scale scores. There were 85 women in the anxiety group and 190 women in the non-anxiety group, and the prevalence of anxiety was 31%. The pre-pregnancy BMI of the study population was 24.54±3.72 kg/m 2 . The pre-pregnancy BMI in the anxiety group was higher (25.54±3.68 kg/m²) than the control group (24.1±3.66 kg/m²) (P<0.01). The two groups of pregnant women were similar in age, gestational age, weight gain during pregnancy, and family history of diabetes. There were statistically significant differences in blood glucose and lipid levels, systolic blood pressure during pregnancy, history of abortion, mother's cultural degree, family income, family history of anxiety and sleep were statistically significant. Table2 Comparison of basic characteristics between two groups of pregnant women with GDM Variable Population N=275 Anxiety group n=85 N o anxiety group n=190 P Age ， Mean ± SD Gestational age ， Mean ± SD Pre-pregnancy BMI （ Kg/ m² ）， Mean ± SD Weight gain during pregnancy （ Kg ）， Mean ± SD History of abortion (%) No Yes Level of education (%) Junior college and below University and above Systolic blood pressure （ mmHg ）， Mean ± SD Anxiety scale score * ， M （ Q1,Q3 ） Blood glucose *, M （ Q1,Q3 ） FPG（mmol/L）， 2hPG（mmol/L） HbA1c（%） Lipid *, M （ Q1,Q3 ） TG（mmol/L） TC（mmol/L） HDL-C（mmol/L） LDL-C（mmol/L） 31.79±3.92 25.39±3.92 24.54±3.72 7.25±4.90 175(63.64) 100(36.36) 73(36.14) 202(63.86) 126.55±5.38 41.25(35-51.25) 5.59(5.12-6.19) 7.50(6.45-8.63) 5.50(5.20-6.10) 2.34(1.95-3.12) 4.73(4.18-5.79) 1.68(1.42-2.03) 2.89(2.35-3.49) 31.58±4.46 25.67±2.74 25.54±3.68 7.20±2.96 43(50.59) 42(49.41) 32(37.65) 53(63.25) 130.25±4.76 53.75(51.25-56.25) 6.08(5.47-7.03) 8.55(7.48-9.80) 5.97(5.40-6.70) 2.82(2.22-3.62) 5.83(4.76-6.52) 1.55(1.36-1.71) 3.29(2.84-4.07) 31.89±3.66 25.27±1.30 24.10±3.66 7.23±5.57 132（69.47） 58（30.53） 41(21.58) 149(78.42) 124.89±4.79 37.50(33.75-41.25) 5.47(5.06-5.93) 7.12(6.28-7.96) 5.40(5.10-5.87) 2.28(1.71-2.96) 4.39(3.76-5.29) 1.83(1.48-2.11) 2.65(2.20-3.37) 0.54 0.10 ＜ 0.01 0.90 ＜ 0.01 ＜ 0.01 ＜ 0.01 ＜ 0.01 ＜ 0.01 ＜ 0.01 ＜ 0.01 ＜ 0.01 ＜ 0.01 ＜ 0.01 ＜ 0.01 Annual household income （ Ten thousand yuan ） (%) ＜6 6-14 ＞14 25（9.09） 200（72.73） 50(18.18) 12（14.12） 61(71.74) 12(14.14) 13(6.84) 139(73.16) 38（20.00） ＜ 0.01 Family history of anxiety (%) No Yes Family history of diabetes (%) No Yes The amount of sleep （ h ） (%) ＜6 6-8 ＞8 263(95.64) 12(4.36) 199（72.36） 76（27.64） 34（12.36） 135（49.09） 108(38.55) 76（89.41） 9(10.59) 60(70.59) 25(29.41) 15(17.65) 56（65.88） 16（16.47） 187(98.42) 3(1.58) 139(73.16) 51(26.84) 19（10.00） 79（41.58） 92（48.48） ＜ 0.01 0.66 ＜ 0.01 Note: Continuous variables were expressed by mean ± standard deviation and compared by T test. The classification variables were expressed by frequency (percentage) and compared by Chi-square test. *Anxiety scale scores, blood glucose (FBG, 2hPG, HbA1c), and blood lipid (TG, TC, HDL, AND LDL) did not follow normal distribution after testing, so median (interquartile spacing) was used for comparison using Wilcoxon rank-sum test. Correlation analysis of blood glucose, blood lipids, pre-pregnancy BMI, and anxiety score of pregnant women with GDM The correlation between pre-pregnancy BMI, blood glucose and lipid levels during pregnancy, and anxiety scores was analyzed(Table 3). The BMI before pregnancy was positively correlated with anxiety. There was a positive correlation between FBG, 2hPG, and HbA1c and the anxiety scores of pregnant women with GDM. TG, TC, and LDL-C during pregnancy were positively correlated with anxiety, but HDL and the GDM anxiety score is irrelevant. Table3 Correlation analysis of blood glucose, blood lipid, pre-pregnancy BMI and anxiety score of GDM pregnant women Variable GDM maternal anxiety score r P Pre-pregnancy BMI 0.19** 0.002 FBG 0.27*** <0.001 2hPG 0.43*** <0.001 HbA1c 0.29*** <0.001 TG 0.31*** <0.001 TC HDL LDL-C 0.47*** -0.08 0.41*** <0.001 0.180 <0.001 *p<0.05; **p<0.01；***p<0.001 Correlation analysis between pre-pregnancy BMI and blood glucose and lipids The correlation between pre-pregnancy BMI and blood glucose and lipid levels during pregnancy was analyzed(Table 4). Pre-pregnancy BMI was positively correlated with FBG, 2hPG, and HbA1c during pregnancy. BMI before pregnancy was positively correlated with TG levels during pregnancy and was negatively correlated with HDL levels during pregnancy. There was no correlation between pre-pregnancy BMI and TCand LDL-C during pregnancy. Table4 Correlation analysis of blood glucose, blood lipids and BMI before pregnancy Variable Pre-pregnancy BMI r P FBG 0.25*** <0.001 2hPG 0.26*** <0.001 HbA1c 0.34*** <0.001 TG 0.16** 0.007 TC HDL LDL-C 0.09 -0.14* 0.09 0.143 0.018 0.129 *p<0.05; **p<0.01；***p<0.001 Association among pre-pregnancy BMI, blood glucose and lipids, and anxiety in pregnant women with GDM The above correlation analysis revealed that FBG, 2hPG, HbA1c, and TG during pregnancy were significantly positively correlated with not only the pregnancy anxiety scores, but also with pre-pregnancy BMI. Therefore, we further explored the relationship between blood glucose (FBG, 2hPG, and HbA1c) and lipid (TG) during pregnancy and pre-pregnancy BMI and the pregnancy anxiety score through regression analysis. Since the pregnancy anxiety scores for pregnant women with GDM were not normally distributed, the anxiety of pregnant women with GDM was regarded as a binary classification variable (with anxiety, without anxiety), and the relationship between pre-pregnancy BMI, pregnancy blood glucose (FBG, 2hPG, and HbA1c) and lipid (TG) levels, and anxiety of pregnant women with GDM was investigated by using a binary logistic regression model. Additionally, maternal systolic blood pressure during pregnancy, maternal education level, annual family income, previous history of abortion, family history of anxiety, and sleep during pregnancy were included in the regression model as the final adjustment factors based on the research results and reference of relevant literature. Finally, logistic regression analysis of pre-pregnancy BMI, blood glucose and lipid levels during pregnancy, and anxiety of pregnant women with GDM is shown in Table 5. Table5 Logistic regression analysis of pre-pregnancy BMI, blood glucose, blood lipids and anxiety in pregnant women with GDM Variable Anxiety in pregnant women with GDM OR （ 95%CI ） ORa （ 95%CI ） Pre-pregnancy BMI FBG 1.11 (1.04,1.19) * 2.60 (1.87,3.62) * 1.11 (1.01,1.22) * 1.86 (1.24,2.81) * 2hPG 1.99 (1.62,2.46) * 1.73 (1.33,2.27) * HbA1c 2.64 (1.85,3.77) * 2.02 (1.26,3.23) * TG 1.67 (1.32,2.17) * 1.26 (1.05,1.67) * Note: ORa: The OR value adjusted by incorporating maternal systolic blood pressure during pregnancy, maternal education level, annual family income, previous history of abortion, family history of anxiety and sleep during pregnancy into the binary Logistic regression model. * denotes p ＜ 0.05. Mediating effects of blood glucose and lipid on pre-pregnancy BMI and pregnancy anxiety scores The abovementioned research results demonstrated that FBG, 2hPG, HbA1c, and TG were not only correlated with pre-pregnancy BMI, but also significantly correlated with the pregnancy anxiety scores. In addition, a logistic regression model was used to evaluate statistical significance after adjusting maternal systolic blood pressure during pregnancy, maternal education level, annual family income, previous history of abortion, family history of anxiety, and sleep during pregnancy. Therefore, these results indicate that FBG, 2hPG, HbA1c, and TG may play a mediating role in the relationship between pre-pregnancy BMI and the pregnancy anxiety scores of pregnant women with GDM. Accordingly, a bootstrap method was used to test the mediating effect among variables, with pre-pregnancy BMI as the independent variable X, FBG, 2hPG, HbA1c, and TG levels as the mediating variable M, and the pregnancy anxiety score as the dependent variable Y [35]. Finally, the analysis results of the mediating effects of FBG, 2hPG, HbA1c, and TG between pre-pregnancy BMI and the pregnancy anxiety score are shown in Tables 6 and 7. The total effect of pre-pregnancy BMI on pregnant women with GDM was significant (P=0.001), indicating that pregnant women with GDM and high pre-pregnancy BMI are more likely to experience higher anxiety scores during pregnancy. Additionally, FBG, 2hPG, HbA1c, and TG significantly mediate the influence of pre-pregnancy BMI on the pregnancy anxiety scores of pregnant women with GDM, and the indirect effect of blood glucose (FBG, 2hPG, and HbA1c) on the pregnancy anxiety scores of pregnant women with GDM is significantly stronger than the effect of blood lipids (TG) (Table 7). In conclusion, FBG, 2hPG, HbA1c, and TG play a partially mediating role in the relationship between pre-pregnancy BMI and the pregnancy anxiety scores of pregnant women with GDM. Further, based on the relationship among the above variables, the relevant path graph was constructed (Figure 2). Table6 Test results of mediating effects of blood glucose and blood lipids on pre-pregnancy BMI and pregnancy anxiety scores Independent variable (X) Intervening variable （ M ） Dependent variable （ Y ） a b c c’ Pre-pregnancy BMI FBG Anxiety scores 0.06*** 2.88*** 0.46*** 0.29* Pre-pregnancy BMI 2hPG Anxiety scores 0.11*** 2.39*** 0.46*** 0.19 Pre-pregnancy BMI HbA1c Anxiety scores 0.06*** 2.94*** 0.46*** 0.28* Pre-pregnancy BMI TG Anxiety scores 0.05** 2.04*** 0.46*** 0.35** a：The direct effect of an independent variable on a mediator variable b：The direct effect of a mediating variable on a dependent variable c：The total effect of independent variables on dependent variables c’： Indirect effects of independent variables on dependent variables. *p<0.05; **p<0.01；***p<0.001 Table7 The mediating effects of blood glucose and blood lipids on pre-pregnancy BMI and pregnancy anxiety scores Project Effect of value Standard error 95% confidence upper bound 95% confidence lower bound Total effect （ c ） FBG Indirect effect Direct effect 0.46 0.17 0.29 0.13 0.05 0.13 0.19 0.08 0.03 0.72 0.27 0.04 2hPG Indirect effect Direct effect 0.26 0.19 0.06 0.12 0.15 -0.05 0.39 0.44 HbA1c Indirect effect Direct effect 0.18 0.28 0.05 0.13 0.09 0.18 0.28 0.53 TG Indirect effect Direct effect 0.11 0.35 0.05 0.13 0.02 0.09 0.21 0.61 Discussion Our study aimed to further investigate whether blood glucose and lipids mediate the relationship between pre-pregnancy BMI and pregnancy anxiety in pregnant women with GDM. We confirmed the bidirectional association between blood glucose and lipid levels during pregnancy and BMI and anxiety during pregnancy through correlation and regression analyses. The mediation effect analysis further confirmed that pre-pregnancy BMI had a significant effect on the pregnancy anxiety scores in pregnant women with GDM. In addition, FBG, 2hPG, HbA1c, and TG also mediated the effect of pre-pregnancy BMI on the pregnancy anxiety scores in pregnant women with GDM. Lastly, FBG, 2hPG, HbA1c, and TG did play a partial mediating role in the relationship between pre-pregnancy BMI and the pregnancy anxiety scores of GDM pregnant women. Recently, the incidence of gestational diabetes has increased and this disease can cause great harm to pregnant women and fetuses.. Clinical evidence for gestational diabetes suggests that women experience extreme mood changes during pregnancy and are more likely to experience anxiety; negative emotions during pregnancy can cause maternal and infant complications. Previous research indicates that women with GDM had a higher tendency to develop prenatal depression, anxiety, and stress[37-38]. Meanwhile, women with low income, low socioeconomic status, and low education levels have a higher incidence of prenatal anxiety and depression [39]. Adverse birth history and a family history of depression or anxiety are associated with anxiety and depression [40-43]. Our results indicate that the incidence of adverse history of abortion, family history of anxiety, low income, and low educational level in the anxious group was higher than that of those in the non-anxious group. In addition, our study also found that the average systolic blood pressure of the anxiety group is higher than the control group during pregnancy. This may be due to negative emotions, such as anxiety experienced by pregnant women with GDM for whom neuroendocrine changes occur constantly, thus enhancing the hypothalamus-pituitary-adrenal cortex system and sympathetic adrenal medullary system activity, leading to endothelial cell shrinkage and increased systolic blood pressure. Additionally, our results also revealed that pregnant women with GDM in the anxiety group had less sleep time than those in the control group. At present, the prevalence of overweight or obese women during pregnancy is rapidly increasing worldwide [16-17], and its incidence is estimated to range from 12.3% to 63.5% [18]. Recently, the incidence of GDM is also increasing, and more than 40% of patients with GDM experience anxiety during pregnancy, indicating a high prevalence of anxiety in women with GDM [10-11].Some studies [20-21,44] have found a positive dose-response correlation between BMI and prenatal anxiety, depression, and other adverse emotions. However, another recent study failed to detect an association between the two [45]. Our correlation analysis demonstrated a significant positive correlation between pre-pregnancy BMI and the pregnancy anxiety scores of pregnant women with GDM, suggesting that pregnant women with GDM with high pre-pregnancy BMI were more likely to display a high anxiety score during pregnancy. This correlation remained statistically significant after regression analysis excluding maternal systolic blood pressure during pregnancy, maternal education level, annual family income, previous history of abortion, family history of anxiety, and sleep during pregnancy, which was consistent with previous findings [17]. Most studies only discuss the relationship between BMI and prenatal anxiety before childbirth or only blood glucose and lipid levels, as well as the connection between anxiety during the second trimester; there are no further studies of the relationship between the four, lacking blood glucose and lipid level directions to explore the relationship between BMI and anxiety during pregnancy before childbirth. Pre-pregnancy BMI is not only correlated with anxiety during pregnancy, but also significantly correlated with blood lipids and glucose during pregnancy. Blood glucose and blood lipid levels during pregnancy are also correlated with anxiety during pregnancy. Therefore, this study is the first to explore the effects of blood glucose and lipids on the relationship between pre-pregnancy BMI and pregnancy anxiety in pregnant women with GDM using mediation analysis. Conclusion We found that the higher the pre-pregnancy BMI of GDM, the more serious the degree of anxiety during pregnancy. FBG, 2hPG, HbA1c, and TG of pregnant women with GDM play a role in the influence of pre-pregnancy BMI on pregnancy anxiety, and the effect of blood glucose (FBG, 2hPG, and HbA1c) on the influence of pre-pregnancy BMI on pregnancy anxiety was significantly stronger than that of blood lipids (TG). Declarations Ethics approval and consent to participate The study received ethical approval and all participants volunteered to participate Availability of data and material All data generated or analyzed during this study are included in this published article. Acknowledgments We gratefully acknowledge Wenshu Yu for providing intellectual support and technical assistance. Consent All authors agreed to publish. Authors’ Contributions We acknowledge that all authors have contributed significantly. Hong OuYang devised the project, collected material and wrote the manuscript. Na Wu helped with the discussion, supervised the project and provided critical feedback. Funding This research was supported by the National Natural Science Foundation of China (No.81700706), the 345 Talent Project of Shengjing hospital, the Clinical research project of Liaoning Diabetes Medical Nutrition Prevention Society (No.LNSTNBYXYYFZXH-RS01B), the Natural Science Foundation of Liaoning Province (No. 2021-MS-182), the Science Foundation of Liaoning Education Department (No. LK201603), and the Virtual simulation experiment teaching project of China Medical University(No.2020-47). Conflicts of Interest The authors have no conflicts of interest to declare. References Yi L, Bei N. Investigation on mental health status of gestational diabetes patients [J]. Int J Nurs. 2018;37(2):167–72. Shuiyu L. e. al. Clinical investigation on mental health status of gestational diabetes patients [J]. Medical Innovation in China,2019,16(16):109–112. Thiagayson P, Krishnaswamy G, et al. Depression and anxiety in Singaporean high-risk pregnancies - prevalence and screening[J]. 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Estimated global overweight and obesity burden in pregnant women based on panel data model. PLos One,2018,13 (8), e0202183. Ratnasiri AWG, Lee HC, et al. Trends in maternal pre-pregnancy body mass index (BMI) and its association with birth and maternal outcomes in Califormia, 2007–2016: A retrospective cohort study. PLoS ONE. 2019;14(9):e0222458. Zhao R, Xu L, Wu M, Hung SH, Ca XJ. Maternal pre-pregnancy body mass index, gestational weight gain influence birth weight. Women Birth. 2018;31(1):e20–5. Voerman E, Santos S, Golab P. B., et al. Maternal body mass index, gestational weight gain, and the risk of overweight and obesity across childhood: An individual participant data meta-analysis, PLos Med,2019,16 (2), e1002744. Dachew BA. Getinet Ayano. The impact of pre-pregnancy BMI on maternal depressive and anxiety symptoms during pregnancy and the postpartum period: A systematic review and meta-analysis, Journal of Affective Disorders,2021,281: 321–330. Huizhen G, Bin L. Effects of different body mass index before pregnancy on blood glucose and lipid and pregnancy outcome [J].Journal of Sun Yat-sen University,2017,37(2):89–94. Bogaerts R, Devlieger. Effects of lifestyle intervention in obese pregnant women on gestational weight gain and mental health: a randomized controlled trial International [J].Journal of Obesity ,2012, 1–8. Lee KW, et al., Diabetes in Pregnancy and Risk of Antepartum Depression: A Systematic Review and Meta-Analysis of Cohort Studies. International journal of environmental research and public health, 2020. 17(11). Lee KW, et al., Prevalence of anxiety among gestational diabetes mellitus patients: A systematic review and meta-analysis,World Journal of Meta-Analysis.2020,8(3): 275–284. Hongwei S. Relationship between anxiety and depression and glycosylated hemoglobin in diabetic patients [J]. Henan Medical Research,2018,27(11):2028–2029. Beka Q, Bowker S, et al. Development of Perinatal Mental Illness in Women With Gestational Diabetes Mellitus: A Population-Based Cohort Study[J]. Can J diabetes. 2018;42:350–5. Horsch A, Kang J, et al. Stress exposure and psychological stress responses are related to glucose concentrations during pregnancy[J]. Br J Health Psychol. 2016;21:712–29. Yafei W, et al. Relationship between blood glucose level and prepregnancy weight and weight gain in gestational diabetes mellitus[J]. Journal of China-Japan Friendship Hospital,2016,30(2):70–76. Wang X. Liying Yang. Association of serum lipid levels with psychotic symptoms in first-episode and drug naïve outpatients with major depressive disorder: a large-scale cross-sectional study. J Affect Disord,2022 Jan 15;297:321–326. Virtanen JK, Mursu J, Virtanen HE, et al. Associations of egg and cholesterol intakes with carotid intima-media thickness and risk of incident coronary artery disease according to apolipoprotein E phenotype in men: the Kuopio Ischaemic Heart Disease Risk Factor Study [J]. Am J Clin Nutr. 2016;103(3):895–901. Vahratian A, Misra VK, Trudeau S, et al. Prepregnancy body mass index and gestational age-dependent changes in lipid levels during pregnancy [J]. Obstet Gynecol. 2010;116(1):107–13. Diagnostic criteria and classification. of hyperglycaemia first detected in pregnancy: a World Health Organization Guideline [ J]. Diabetes Res Clin Pract. 2014;103(3):341–63. Zhenxiao S, et al. Study on reliability and validity of hospital Anxiety and depression Scale [J]. Chinese Journal of Clinical Physicians,2017,11(2):198–201. Huiyan Duan M, Gong, et al. Research on sleep status, body mass index, anxiety and depression of college students during the post-pandemic era in Wuhan, China[J]. J Affect Disord,,2022 Mar 15;301:189–192. Dongxing Cao Z, Wang, et al. Does Postoperative Anxiety/Depression Impair the Long-Term Functional Outcomes of Laparoscopic Ventral Rectopexy for Obstructed Defecation? [J]. J Laparoendosc Adv Surg Tech A.,2022. Zhonglin W, et al. Mediating effects analysis: Method and model development [J]. Advances in psychological Science,2014,22(05):731–745. Pace R, Rahme E, et al. Association between gestational diabetes mellitus and depression in parents: a retrospective cohort study[J]. Clin Epidemiol. 2018;10:1827–38. Beka Q, Bowker S, et al. Development of Perinatal Mental Illness in Women With Gestational Diabetes Mellitus: A Population-Based Cohort Study[J]. Can J diabetes. 2018;42:350–5.e1. Liqing JL, Min S. T, et al. Investigation of pregnant women's pregnancy stress and its influencing factors[J]. Chinese journal of nursing, 2013. Tsartsara E, Johnson M. The impact of miscarriage on women's pregnancy-specific anxiety and feelings of prenatal maternal-fetal attachment during the course of a subsequent pregnancy: an exploratory follow-up study[J]. J Psychosom Obstet Gynaecol. 2006;27:173–82. Lee KW, Ching SM, et al. Neonatal outcomes and its association among gestational diabetes mellitus with and without depression, anxiety and stress symptoms in Malaysia: A cross-sectional study [J].Midwifery,2020,81:102586. Lee KW, et al. Prevalence and factors associated with depressive, anxiety and stress symptoms among women with gestational diabetes mellitus in tertiary care centres in Malaysia: a cross-sectional study[J]. BMC Pregnancy Childbirth. 2019;19:367. Yanling Q. Emotional state and risk factors of pregnant women with gestational diabetes mellitus [J]. New world of diabetes,2017. Bodnar LM, Wisner KL, Moses-Kolko E, Hanusa SDK. B.H. Pre-pregnancy body mass index, gestational weight gain, and the likelihood of major depressive disorder during pregnancy. J Clin Psychiatry. 2009;70(9):1290–6. Zhao R, Xu L, Wu ML, et al. Maternal pre-pregnancy body mass index, gestational weight gain influence birth weight, 2018,31(1): e20-e25. 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 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-1952539","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":131020444,"identity":"a2d4536a-345c-47bf-99af-ab76d06d5239","order_by":0,"name":"Hong Ouyang","email":"","orcid":"","institution":"China Medical University Shengjing Hospital Nanhu Branch: Shengjing Hospital of China Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hong","middleName":"","lastName":"Ouyang","suffix":""},{"id":131020445,"identity":"c1e6f6c1-d393-4bf1-84b1-e0faa55e5f8f","order_by":1,"name":"Na Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIie3RMQuCUBDA8RPhtRy0GoF9gkARIiH6LE+CJofGtgyhqXYDP0QQuHbxwMlobQgigiYh25yixpp8bUHvv/847g5ApfrBWkBclOXDrNdDkiP2lM5Cm5PTiFIuOUZsLwIYeSvyLTmhzQQXIzxqAWX3Qw59sx1UkBqmXETdq66Fi7Ubw8DpUNWUKOOEqDMddkkTgbykisDpVhAyHRn4V0lCryMjEwaCz+SIHRDfLudDyzBSx40tiV1erxwURdmbbPbh+ZCP+2Yl+chAyde8k2+FSqVS/UVPjH1N4wikSNAAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-1156-3231","institution":"China Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Na","middleName":"","lastName":"Wu","suffix":""}],"badges":[],"createdAt":"2022-08-11 11:16:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1952539/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1952539/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":25676238,"identity":"953bedad-792f-497a-855e-8cd6a8a33505","added_by":"auto","created_at":"2022-08-25 18:16:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":64680,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSelf-Rating Anxiety Scale (SAS)\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eTotal rough score = total score of 20 items, demarcation is 40 points.\u0026nbsp;\u003c/p\u003e\u003cp\u003eStandard points = total rough points ×1.25, demarcation points are 50 points.\u0026nbsp;If SAS standard score ≤50, it means no anxiety;\u0026nbsp;SAS standard score ≥50 points, indicating anxiety, including 50-59 points of mild anxiety, 60-69 points of moderate anxiety, more than 69 points of severe anxiety.\u0026nbsp;\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-1952539/v1/ef93fd98029aecffd4362e5f.png"},{"id":25676239,"identity":"6a88b335-f7a3-4d0c-a47e-52876f11cf74","added_by":"auto","created_at":"2022-08-25 18:16:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":39090,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePath diagram of fitting coefficient between pre-pregnancy BMI, fasting blood glucose, 2h postprandial blood glucose, glycated hemoglobin, triglyceride and anxiety scores of GDM pregnant women\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-1952539/v1/27e9fa53ab3f3eca8b4722c7.png"},{"id":26630722,"identity":"cf17e231-4417-4c23-8ef9-c2390c68129e","added_by":"auto","created_at":"2022-09-19 05:06:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":860217,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1952539/v1/bbb6aae5-a07e-4151-85e7-d977849aa3c5.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003ePre-pregnancy BMI and pregnancy anxiety in women with gestational diabetes mellitus: mediating effects of blood glucose and lipid levels\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRecently, the incidence of gestational diabetes mellitus (GDM) among pregnant women is increasing [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], and poor blood glucose control in patients with GDM can lead to adverse pregnancy outcomes, posing a serious threat to both pregnant women and the fetus [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Therefore, pregnant women in this high-risk group suffer greater psychological pressure than healthy pregnant women [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The studies further showed that anxiety can increase the risk of GDM, and pregnant women diagnosed with GDM are also more susceptible to depression, anxiety, and stress [\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].More than 40% of patients with GDM experience anxiety[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. .At the same time, anxious pregnant women with gestational diabetes were more likely to have a variety of adverse maternal and infant outcomes through some studies[\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe mediation effect model is an important method to explore the connection between factors. When an independent variable X can influence a dependent variable Y through an intermediate variable M, it indicates that M is an intermediate variable and plays an intermediate effect between X and Y. Recently, mediating effect analysis has not only been applied in psychology and other social science research fields, but also in medical research; several studies [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] have analyzed the relationship between relevant variables by establishing mediating effect models. Therefore, this study is the first to explore the effects of blood glucose and lipids on the relationship between pre-pregnancy BMI and pregnancy anxiety among pregnant women with GDM using mediation effect analysis.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eResearch status of BMI and pregnancy anxiety in pregnant women with GDM\u003c/h2\u003e \u003cp\u003eCurrently, obesity before pregnancy are increasingly common. Globally, the prevalence of overweight or obese women during pregnancy is rising rapidly, with current prevalence estimates ranging from 12.3\u0026ndash;63.5% [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Overweight and obesity before pregnancy have a variety of adverse health consequences for both mother and child [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In a recent meta-analysis [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], the study found that women who were obese at the time of conception were more likely to have anxiety and depression symptoms during pregnancy than women of normal weight. Similarly, relevant studies also demonstrate that the BMI is positively correlated with anxiety during pregnancy[\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cem\u003eCurrent status of research on the relationship between blood glucose level during pregnancy and pre-pregnancy BMI and pregnancy anxiety\u003c/em\u003e \u003c/p\u003e \u003cp\u003eIn addition to the direct influence of pre-pregnancy BMI on pregnancy anxiety, there is a close relationship between the blood glucose level and negative emotions such as anxiety and depression during pregnancy, as well as pre-pregnancy BMI. The level of glycated hemoglobin (HbA1c) is positive correlation to the scores for anxiety and depression [\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. FBG and 2hPG are closely associated with increased anxiety and depressive symptoms in GDM[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. However, BMI levels before pregnancy have a significant influence on FBG and 2hPG levels of patients with GDM [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], suggesting that with the increase of BMI, blood glucose level increases significantly, indicating that both FBG and 2hPG levels are positively associated with BMI before pregnancy [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eResearch status of serum lipid levels, BMI before pregnancy, and pregnancy anxiety\u003c/h2\u003e \u003cp\u003eThere is also a close connection between lipid levels during pregnancy and BMI before pregnancy and pregnancy anxiety. LDL-C, TC, and TG levels are positively correlated with anxiety and depression [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]; however, HDL-C is negatively correlated with anxiety[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Additionally, TG is positively correlated with BMI before pregnancy [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], while TC, LDL-C, and HDL-C are negatively correlated with BMI before pregnancy [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAt present, many studies have discussed what factors contribute to anxiety in pregnant women with GDM, although these studies only discussed the relationship between a certain influencing factor and anxiety and did not study the correlation between multiple influencing factors. From the above discussion, we can see that there may be a certain relationship between BMI and blood glucose and lipid levels during pregnancy and pregnancy anxiety. Therefore, we conducted the first prospective study to link the role of pre-pregnancy BMI on pregnancy anxiety with blood glucose and lipid levels during pregnancy through mediation effect analysis and to further explore whether blood glucose and lipid levels play a mediating role in the relationship between BMI and pregnancy anxiety in pregnant women with GDM. Our hypotheses were as follows: The mediating effect analysis was conducted to further explore the influence of BMI on the pregnancy anxiety score and regulation process of blood glucose and lipid levels during pregnancy between BMI and pregnancy anxiety scores.\u003c/p\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003cdiv class=\"Section2\" id=\"Sec5\"\u003e\n \u003ch2\u003eResearch participants\u003c/h2\u003e\n \u003cp\u003ePregnant women who visited the Department of Endocrinology or Obstetrics of the Affiliated Hospital of China Medical University from January 2019 to December 2021 were selected for long-term follow-up. These pregnant women were diagnosed with GDM.According to the 2012 World Health Organization guidelines [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e], GDM is defined as meeting or exceeding at least one of the following indicators: (1) 5.1 mmol/L\u0026thinsp;\u0026le;\u0026thinsp;FPG level\u0026thinsp;\u0026lt;\u0026thinsp;7.0 mmol/L, (2) 1-h plasma glucose level\u0026thinsp;\u0026ge;\u0026thinsp;10.0 mmol/L, and (3) 8.5 mmol/L\u0026thinsp;\u0026le;\u0026thinsp;2h-PG level\u0026thinsp;\u0026lt;\u0026thinsp;11.1 mmol/L. Finally, pregnant women with a GDM diagnosis were selected as the research subjects.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec6\"\u003e\n \u003ch2\u003eInclusion criteria\u003c/h2\u003e\n \u003cp\u003e(1) GDM was definitively diagnosed after the 75g OGTT test was completed during pregnancy.\u003c/p\u003e\n \u003cp\u003e(2) Pregnant women with GDM should have completed the measurement of blood glucose (FBG, 2hPG, and HbA1c) and lipid (TG, TC, HDL, and LDL) levels in the endocrinology department or obstetrics department of our hospital during 14\u0026ndash;28 weeks of gestation or were able to provide blood glucose or lipid indexes tested in local hospitals during 14\u0026ndash;28 weeks of gestation.\u003c/p\u003e\n \u003cp\u003e(3) Willing to accept the questionnaire survey after being informed of the survey content and able to fill in the questionnaire independently.\u003c/p\u003e\n \u003cp\u003e(4) Complete clinical data.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec7\"\u003e\n \u003ch2\u003eExclusion criteria\u003c/h2\u003e\n \u003cp\u003e(1) Absence of basic information\u003c/p\u003e\n \u003cp\u003e(2) Patients did not meet the diagnostic criteria of GDM\u003c/p\u003e\n \u003cp\u003e(3) Patients with other diseases\u003c/p\u003e\n \u003cp\u003e(4) Those who were unwilling to complete the questionnaire survey\u003c/p\u003e\n \u003cp\u003e(5) Patients with psychological symptoms, such as compulsion, anxiety, and depression, before pregnancy\u003c/p\u003e\n \u003cp\u003eThe Self-rating Anxiety Scale (SAS)was conducted among pregnant women with GDM,and these women will be grouped according to their SAS scores.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec8\"\u003e\n \u003ch2\u003eData collection\u003c/h2\u003e\n \u003cp\u003eThe data collected mainly included general demographic data, health data, personal habits, BMI before pregnancy, blood glucose (FBG, 2hPG, and HbA1c) and lipid (TG, TC, HDL, and LDL) levels, and systolic blood pressure levels during pregnancy, pregnancy anxiety, and weight gain during pregnancy.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec9\"\u003e\n \u003ch2\u003eQuestionnaire information\u003c/h2\u003e\n \u003cp\u003eThe survey included:\u003c/p\u003e\n \u003cp\u003e(1) Demographic data: age, education level, annual family income, and others.\u003c/p\u003e\n \u003cp\u003e(2) Health data: including height before pregnancy, weight before pregnancy, weight gain during pregnancy, gestational age, history of abortion, family history of anxiety, family history of diabetes, and sleep status.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec10\"\u003e\n \u003ch2\u003eMedical history\u003c/h2\u003e\n \u003cp\u003e(1) Evaluation of anxiety during pregnancy: After the pregnant women were definitively diagnosed with GDM, the SAS was used within 1\u0026ndash;2 weeks to evaluate their anxiety state. The SAS, compiled by Zung in 1971, is a clinical measurement tool for assessing patients\u0026apos; subjective symptoms of anxiety. The SAS is a self-assessment tool for anxiety with high reliability and validity and is widely used in medical-related studies [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e]. Participants filled in items according to the contents of the scale. There are a total of 20 test questions on the SAS, all of which adopt a four-level scoring method. The main evaluation items are the frequency of symptom occurrence defined by the following criteria: \u0026quot;A\u0026quot; no or little time; \u0026quot;B\u0026quot; A small part of the time; \u0026quot;C\u0026quot; quite A lot of the time; and \u0026quot;D\u0026quot; for the most part or all of the time (the \u0026quot;A\u0026quot; \u0026quot;B\u0026quot; \u0026quot;C\u0026quot; \u0026quot;D\u0026quot; for \u0026quot;1\u0026quot; \u0026quot;2\u0026quot; \u0026quot;3\u0026quot; \u0026quot;4 scoring points\u0026quot;) (Figure.1).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;Total rough score\u0026thinsp;=\u0026thinsp;total score of 20 items, demarcation is 40 points.\n \u003c/div\u003e\n \u003cp\u003eStandard points\u0026thinsp;=\u0026thinsp;total rough points \u0026times;1.25, demarcation points are 50 points. If SAS standard score\u0026thinsp;\u0026le;\u0026thinsp;50, it means no anxiety; SAS standard score\u0026thinsp;\u0026ge;\u0026thinsp;50 points, indicating anxiety, including 50\u0026ndash;59 points of mild anxiety, 60\u0026ndash;69 points of moderate anxiety, more than 69 points of severe anxiety.\u003c/p\u003e\n \u003cp\u003e(2) Blood glucose and lipid measurements: Blood glucose (FBG, 2hPG, and HbA1c) and lipid (TG, TC, HDL, LDL) levels were recorded.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec11\"\u003e\n \u003ch2\u003eVariable definition and assignment\u003c/h2\u003e\n \u003cp\u003ePregnant women with GDM were divided into two educational background groups (junior college and below and college and above), three annual household income groups (\u0026lt;\u0026thinsp;60,000RMB [low middle class], 60,000-140,000RMB [middle middle class], and \u0026ge;\u0026thinsp;140,000RMB [upper middle class]), and three sleep time groups (\u0026lt;\u0026thinsp;6 h [insufficient sleep], 6\u0026ndash;8 h [average sleep], and \u0026gt;\u0026thinsp;8 h [adequate sleep]). The specific assignment is shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable1 Variable assignment table\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.7304189435337%\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"48.2695810564663%\"\u003e\n \u003cp\u003eAssignment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.7304189435337%\"\u003e\n \u003cp\u003eLevel of education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"48.2695810564663%\"\u003e\n \u003cp\u003e1= Junior college and below；2= University and above\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.7304189435337%\"\u003e\n \u003cp\u003eAnnual household income（Ten thousand yuan）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"48.2695810564663%\"\u003e\n \u003cp\u003e1＜6；2=6-14；3＞14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"51.7304189435337%\"\u003e\n \u003cp\u003eHistory of abortion\u003c/p\u003e\n \u003cp\u003eFamily history of anxiety\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eFamily history of diabetes\u003c/p\u003e\n \u003cp\u003eSleep during pregnancy\u003c/p\u003e\n \u003cp\u003e（h）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"48.2695810564663%\"\u003e\n \u003cp\u003e1 = Yes；0 = No\u003c/p\u003e\n \u003cp\u003e1 = Yes；0 = No\u003c/p\u003e\n \u003cp\u003e1 = Yes；0 = No\u003c/p\u003e\n \u003cp\u003e1＜6；2=6-8；3＞8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eQuality control\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec12\"\u003e\n \u003cp\u003eParticipants were determined strictly in accordance with the inclusion and exclusion criteria for selection. Before filling in the questionnaire, the investigators were trained to assist participants with understanding the research content and significance of each item in the questionnaire; they could ask any questions needed to clarify their doubts in a timely manner. After that, the investigators issued the questionnaire uniformly to each participant and explained the requirements of filling in the questionnaire with the same instructions.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec13\"\u003e\n \u003ch2\u003eStatistical analyses\u003c/h2\u003e\n \u003cp\u003eFirst, descriptive analyses were used to describe the general characteristics of the study population. Second, Spearman correlation analysis was used to determine whether there was any correlation between pre-pregnancy BMI, blood glucose, blood lipids, and pregnancy anxiety scores. Factors influencing the pregnancy anxiety scores were analyzed by a binary logistic regression model. Finally, SPSS macro process program designed by Hayes was used to complete data analysis.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eBasic participant characteristics\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBasic information of the participants is shown in Table 2. 275 pregnant women with GDM were included and divided into the anxiety group (standard score \u0026ge;50) or non-anxiety group (standard score \u0026lt;50) according to the anxiety scale scores. There were 85 women in the anxiety group and 190 women in the non-anxiety group, and the prevalence of anxiety was 31%. \u0026nbsp;The pre-pregnancy BMI of the study population was 24.54\u0026plusmn;3.72 kg/m\u003csup\u003e2\u003c/sup\u003e. The pre-pregnancy BMI in the anxiety group was higher (25.54\u0026plusmn;3.68 kg/m\u0026sup2;) than the control group (24.1\u0026plusmn;3.66 kg/m\u0026sup2;) (P\u0026lt;0.01).\u0026nbsp;The two groups of pregnant women were similar in age, gestational age, weight gain during pregnancy, and family history of diabetes. There were statistically significant differences in blood glucose and lipid levels, systolic blood pressure during pregnancy, history of abortion, mother\u0026apos;s cultural degree, family income, family history of anxiety and sleep were statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable2\u003c/strong\u003e \u003cstrong\u003eComparison of basic characteristics between two groups of pregnant women with GDM\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"102%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.77319587628866%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.587628865979383%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePopulation\u003c/strong\u003e \u003cstrong\u003eN=275\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.68041237113402%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnxiety group\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en=85\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.61855670103093%\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003cstrong\u003eo anxiety group\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en=190\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25.77319587628866%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003cstrong\u003e，\u003c/strong\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn;\u003c/strong\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eGestational age\u003c/strong\u003e\u003cstrong\u003e，\u003c/strong\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn;\u003c/strong\u003e\u003cstrong\u003eSD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePre-pregnancy BMI\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003eKg/ m\u0026sup2;\u003c/strong\u003e\u003cstrong\u003e），\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn;\u003c/strong\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eWeight gain during pregnancy\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003eKg\u003c/strong\u003e\u003cstrong\u003e），\u003c/strong\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn;\u003c/strong\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of abortion (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eLevel of education (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eJunior college and below\u003c/p\u003e\n \u003cp\u003eUniversity and above\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eSystolic blood pressure\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003emmHg\u003c/strong\u003e\u003cstrong\u003e），\u003c/strong\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn;\u003c/strong\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAnxiety scale score *\u003c/strong\u003e\u003cstrong\u003e，\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eM\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003eQ1,Q3\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eBlood glucose *, M\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003eQ1,Q3\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eFPG（mmol/L），\u003c/p\u003e\n \u003cp\u003e2hPG（mmol/L）\u003c/p\u003e\n \u003cp\u003eHbA1c（%）\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eLipid *, M\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003eQ1,Q3\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eTG（mmol/L）\u003c/p\u003e\n \u003cp\u003eTC（mmol/L）\u003c/p\u003e\n \u003cp\u003eHDL-C（mmol/L）\u003c/p\u003e\n \u003cp\u003eLDL-C（mmol/L）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.587628865979383%\"\u003e\n \u003cp\u003e31.79\u0026plusmn;3.92\u003c/p\u003e\n \u003cp\u003e25.39\u0026plusmn;3.92\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e24.54\u0026plusmn;3.72\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7.25\u0026plusmn;4.90\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e175(63.64)\u003c/p\u003e\n \u003cp\u003e100(36.36)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e73(36.14)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e202(63.86)\u003c/p\u003e\n \u003cp\u003e126.55\u0026plusmn;5.38\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e41.25(35-51.25)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5.59(5.12-6.19)\u003c/p\u003e\n \u003cp\u003e7.50(6.45-8.63)\u003c/p\u003e\n \u003cp\u003e5.50(5.20-6.10)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.34(1.95-3.12)\u003c/p\u003e\n \u003cp\u003e4.73(4.18-5.79)\u003c/p\u003e\n \u003cp\u003e1.68(1.42-2.03)\u003c/p\u003e\n \u003cp\u003e2.89(2.35-3.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.68041237113402%\"\u003e\n \u003cp\u003e31.58\u0026plusmn;4.46\u003c/p\u003e\n \u003cp\u003e25.67\u0026plusmn;2.74\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e25.54\u0026plusmn;3.68\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7.20\u0026plusmn;2.96\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e43(50.59)\u003c/p\u003e\n \u003cp\u003e42(49.41)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e32(37.65)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e53(63.25)\u003c/p\u003e\n \u003cp\u003e130.25\u0026plusmn;4.76\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e53.75(51.25-56.25)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6.08(5.47-7.03)\u003c/p\u003e\n \u003cp\u003e8.55(7.48-9.80)\u003c/p\u003e\n \u003cp\u003e5.97(5.40-6.70)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.82(2.22-3.62) \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5.83(4.76-6.52)\u003c/p\u003e\n \u003cp\u003e1.55(1.36-1.71)\u003c/p\u003e\n \u003cp\u003e3.29(2.84-4.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.61855670103093%\"\u003e\n \u003cp\u003e31.89\u0026plusmn;3.66\u003c/p\u003e\n \u003cp\u003e25.27\u0026plusmn;1.30\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e24.10\u0026plusmn;3.66\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7.23\u0026plusmn;5.57\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e132（69.47）\u003c/p\u003e\n \u003cp\u003e58（30.53）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e41(21.58)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e149(78.42)\u003c/p\u003e\n \u003cp\u003e124.89\u0026plusmn;4.79\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e37.50(33.75-41.25)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5.47(5.06-5.93)\u003c/p\u003e\n \u003cp\u003e7.12(6.28-7.96)\u003c/p\u003e\n \u003cp\u003e5.40(5.10-5.87)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.28(1.71-2.96)\u003c/p\u003e\n \u003cp\u003e4.39(3.76-5.29)\u003c/p\u003e\n \u003cp\u003e1.83(1.48-2.11)\u003c/p\u003e\n \u003cp\u003e2.65(2.20-3.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.34020618556701%\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25.77319587628866%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnnual household income\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003eTen thousand yuan\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e＜6\u003c/p\u003e\n \u003cp\u003e6-14\u003c/p\u003e\n \u003cp\u003e＞14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.587628865979383%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e25（9.09）\u003c/p\u003e\n \u003cp\u003e200（72.73）\u003c/p\u003e\n \u003cp\u003e50(18.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.68041237113402%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12（14.12）\u003c/p\u003e\n \u003cp\u003e61(71.74)\u003c/p\u003e\n \u003cp\u003e12(14.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.61855670103093%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e13(6.84)\u003c/p\u003e\n \u003cp\u003e139(73.16)\u003c/p\u003e\n \u003cp\u003e38（20.00）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25.77319587628866%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily history of anxiety (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFamily history of diabetes (%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eThe amount of sleep\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003eh\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003cstrong\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e＜6\u003c/p\u003e\n \u003cp\u003e6-8\u003c/p\u003e\n \u003cp\u003e＞8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.587628865979383%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e263(95.64)\u003c/p\u003e\n \u003cp\u003e12(4.36)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e199（72.36）\u003c/p\u003e\n \u003cp\u003e76（27.64）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e34（12.36）\u003c/p\u003e\n \u003cp\u003e135（49.09）\u003c/p\u003e\n \u003cp\u003e108(38.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"22.68041237113402%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e76（89.41）\u003c/p\u003e\n \u003cp\u003e9(10.59)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e60(70.59)\u003c/p\u003e\n \u003cp\u003e25(29.41)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e15(17.65)\u003c/p\u003e\n \u003cp\u003e56（65.88）\u003c/p\u003e\n \u003cp\u003e16（16.47）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.61855670103093%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e187(98.42)\u003c/p\u003e\n \u003cp\u003e3(1.58)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e139(73.16)\u003c/p\u003e\n \u003cp\u003e51(26.84)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e19（10.00）\u003c/p\u003e\n \u003cp\u003e79（41.58）\u003c/p\u003e\n \u003cp\u003e92（48.48）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.34020618556701%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote: Continuous variables were expressed by mean \u0026plusmn; standard deviation and compared by T test. The classification variables were expressed by frequency (percentage) and compared by Chi-square test. *Anxiety scale scores, blood glucose (FBG, 2hPG, HbA1c), and blood lipid (TG, TC, HDL, AND LDL) did not follow normal distribution after testing, so median (interquartile spacing) was used for comparison using Wilcoxon rank-sum test.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCorrelation analysis of blood glucose, blood lipids, pre-pregnancy BMI, and anxiety score of pregnant women with GDM\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe correlation between pre-pregnancy BMI, blood glucose and lipid levels during pregnancy, and anxiety scores was analyzed(Table 3). The BMI before pregnancy was positively correlated with anxiety. There was a positive correlation between FBG, 2hPG, and HbA1c and the anxiety scores of pregnant women with GDM. TG, TC, and LDL-C during pregnancy were positively correlated with anxiety, but HDL and the GDM anxiety score is irrelevant. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable3\u003c/strong\u003e \u003cstrong\u003eCorrelation analysis of blood glucose, blood lipid, pre-pregnancy BMI and anxiety score of GDM pregnant women\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"47.474747474747474%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52.525252525252526%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGDM maternal anxiety score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.94117647058823%\"\u003e\n \u003cp\u003e\u003cstrong\u003er\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.05882352941177%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.95918367346939%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePre-pregnancy BMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.19**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.95918367346939%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFBG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.27***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.95918367346939%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2hPG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.43***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.95918367346939%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHbA1c\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.29***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.95918367346939%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.31***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.95918367346939%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTC\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eHDL\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eLDL-C\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.47***\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e-0.08\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.41***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.180\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e*p\u0026lt;0.05; **p\u0026lt;0.01；***p\u0026lt;0.001\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCorrelation analysis between pre-pregnancy BMI and blood glucose and lipids\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe correlation between pre-pregnancy BMI and blood glucose and lipid levels during pregnancy was analyzed(Table 4).\u0026nbsp;Pre-pregnancy\u003cem\u003e\u0026nbsp;\u003c/em\u003eBMI was positively correlated with FBG, 2hPG, and HbA1c during pregnancy.\u0026nbsp;BMI before pregnancy was positively correlated with TG levels during pregnancy and was negatively correlated with HDL levels during pregnancy.\u0026nbsp;There was no correlation between pre-pregnancy BMI and TCand LDL-C during pregnancy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable4 Correlation analysis of blood glucose, blood lipids and BMI before pregnancy\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"47.474747474747474%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"52.525252525252526%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePre-pregnancy BMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.94117647058823%\"\u003e\n \u003cp\u003e\u003cstrong\u003er\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.05882352941177%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.95918367346939%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFBG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.25***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.95918367346939%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2hPG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.26***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.95918367346939%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHbA1c\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.34***\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.95918367346939%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.16**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.95918367346939%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTC\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eHDL\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eLDL-C\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-0.14*\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e0.143\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.018\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e*p\u0026lt;0.05; **p\u0026lt;0.01；***p\u0026lt;0.001\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAssociation among pre-pregnancy BMI, blood glucose and lipids, and anxiety in pregnant women with GDM\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe above correlation analysis revealed that FBG, 2hPG, HbA1c, and TG during pregnancy were significantly positively correlated with not only the pregnancy anxiety scores, but also with pre-pregnancy BMI.\u0026nbsp;Therefore, we further explored the relationship between blood glucose (FBG, 2hPG, and HbA1c) and lipid (TG) during pregnancy and pre-pregnancy BMI and the pregnancy anxiety score through regression analysis.\u0026nbsp;Since the pregnancy anxiety scores for pregnant women with GDM were not normally distributed, the anxiety of pregnant women with GDM was regarded as a binary classification variable (with anxiety, without anxiety), and the relationship between pre-pregnancy BMI, pregnancy blood glucose (FBG, 2hPG, and HbA1c) and lipid (TG) levels, and anxiety of pregnant women with GDM was investigated by using a binary logistic regression model.\u0026nbsp;Additionally, maternal systolic blood pressure during pregnancy, maternal education level, annual family income, previous history of abortion, family history of anxiety, and sleep during pregnancy were included in the regression model as the final adjustment factors based on the research results and reference of relevant literature.\u0026nbsp;Finally, logistic regression analysis of pre-pregnancy BMI, blood glucose and lipid levels during pregnancy, and anxiety of pregnant women with GDM is shown in Table 5.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable5 Logistic regression analysis of pre-pregnancy BMI, blood glucose, blood lipids and anxiety in pregnant women with GDM\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"22.22222222222222%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" width=\"77.77777777777777%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnxiety in pregnant women with GDM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.45454545454545%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"54.54545454545455%\"\u003e\n \u003cp\u003e\u003cstrong\u003eORa\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.22222222222222%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePre-pregnancy BMI\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFBG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.35353535353536%\"\u003e\n \u003cp\u003e1.11 (1.04,1.19) *\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.60 (1.87,3.62) *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.42424242424242%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.11 (1.01,1.22) *\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e1.86 (1.24,2.81) *\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.22222222222222%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2hPG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.35353535353536%\"\u003e\n \u003cp\u003e1.99 (1.62,2.46) *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.42424242424242%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.73 (1.33,2.27) *\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.22222222222222%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHbA1c\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.35353535353536%\"\u003e\n \u003cp\u003e2.64 (1.85,3.77) *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.42424242424242%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.02 (1.26,3.23) *\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.22222222222222%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.35353535353536%\"\u003e\n \u003cp\u003e1.67 (1.32,2.17) *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.42424242424242%\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.26 (1.05,1.67) *\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote: ORa: The OR value adjusted by incorporating maternal systolic blood pressure during pregnancy, maternal education level, annual family income, previous history of abortion, family history of anxiety and sleep during pregnancy into the binary Logistic regression model. * denotes p\u0026nbsp;＜\u0026nbsp;0.05.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cem\u003eMediating effects of blood glucose and lipid on pre-pregnancy BMI and pregnancy anxiety scores\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe abovementioned research results demonstrated that FBG, 2hPG, HbA1c, and TG were not only correlated with pre-pregnancy BMI, but also significantly correlated with the pregnancy anxiety scores.\u0026nbsp;In addition, a logistic regression model was used to evaluate statistical significance after adjusting maternal systolic blood pressure during pregnancy, maternal education level, annual family income, previous history of abortion, family history of anxiety, and sleep during pregnancy.\u0026nbsp;Therefore, these results indicate that FBG, 2hPG, HbA1c, and TG may play a mediating role in the relationship between pre-pregnancy BMI and the pregnancy anxiety scores of pregnant women with GDM.\u0026nbsp;Accordingly, a bootstrap method was used to test the mediating effect among variables, with pre-pregnancy BMI as the independent variable X, FBG, 2hPG, HbA1c, and TG levels as the mediating variable M, and the pregnancy anxiety score as the dependent variable Y [35].\u003c/p\u003e\n\u003cp\u003eFinally, the analysis results of the mediating effects of FBG, 2hPG, HbA1c, and TG between pre-pregnancy BMI and the pregnancy anxiety score are shown in Tables 6 and 7.\u0026nbsp;The total effect of pre-pregnancy BMI on pregnant women with GDM was significant (P=0.001), indicating that pregnant women with GDM and high pre-pregnancy BMI are more likely to experience higher anxiety scores during pregnancy.\u0026nbsp;Additionally, FBG, 2hPG, HbA1c, and TG significantly mediate the influence of pre-pregnancy BMI on the pregnancy anxiety scores of pregnant women with GDM, and the indirect effect of blood glucose (FBG, 2hPG, and HbA1c) on the pregnancy anxiety scores of pregnant women with GDM is significantly stronger than the effect of blood lipids (TG) (Table 7).\u0026nbsp;In conclusion, FBG, 2hPG, HbA1c, and TG play a partially mediating role in the relationship between pre-pregnancy BMI and the pregnancy anxiety scores of pregnant women with GDM.\u0026nbsp;Further, based on the relationship among the above variables, the relevant path graph was constructed (Figure 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable6 Test results of mediating effects of blood glucose and blood lipids on pre-pregnancy BMI and pregnancy anxiety scores\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.75%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndependent variable\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(X)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntervening variable\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003eM\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDependent variable\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003eY\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.458333333333334%\"\u003e\n \u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.541666666666666%\"\u003e\n \u003cp\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.541666666666666%\"\u003e\n \u003cp\u003e\u003cstrong\u003ec\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.458333333333334%\"\u003e\n \u003cp\u003ec\u0026rsquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.75%\"\u003e\n \u003cp\u003ePre-pregnancy BMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFBG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\"\u003e\n \u003cp\u003eAnxiety scores\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.458333333333334%\"\u003e\n \u003cp\u003e0.06***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.541666666666666%\"\u003e\n \u003cp\u003e2.88***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.541666666666666%\"\u003e\n \u003cp\u003e0.46***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.458333333333334%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;0.29*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.75%\"\u003e\n \u003cp\u003ePre-pregnancy BMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2hPG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\"\u003e\n \u003cp\u003eAnxiety scores\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.458333333333334%\"\u003e\n \u003cp\u003e0.11***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.541666666666666%\"\u003e\n \u003cp\u003e2.39***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.541666666666666%\"\u003e\n \u003cp\u003e0.46***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.458333333333334%\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.75%\"\u003e\n \u003cp\u003ePre-pregnancy BMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHbA1c\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\"\u003e\n \u003cp\u003eAnxiety scores\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.458333333333334%\"\u003e\n \u003cp\u003e0.06***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.541666666666666%\"\u003e\n \u003cp\u003e2.94***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.541666666666666%\"\u003e\n \u003cp\u003e0.46***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.458333333333334%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;0.28*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.75%\"\u003e\n \u003cp\u003ePre-pregnancy BMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.625%\"\u003e\n \u003cp\u003eAnxiety scores\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.458333333333334%\"\u003e\n \u003cp\u003e0.05**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.541666666666666%\"\u003e\n \u003cp\u003e2.04***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.541666666666666%\"\u003e\n \u003cp\u003e0.46***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.458333333333334%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;0.35**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003ea：The direct effect of an independent variable on a mediator variable \u0026nbsp;b：The direct effect of a mediating variable on a dependent variable \u0026nbsp;c：The total effect of independent variables on dependent variables \u0026nbsp;c\u0026rsquo;：\u0026nbsp;Indirect effects of independent variables on dependent variables. *p\u0026lt;0.05; **p\u0026lt;0.01；***p\u0026lt;0.001\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable7 The mediating effects of blood glucose and blood lipids on pre-pregnancy BMI and pregnancy anxiety scores\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.556701030927837%\"\u003e\n \u003cp\u003e\u003cstrong\u003eProject\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect of value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.587628865979383%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandard error\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.711340206185568%\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% confidence upper bound\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.77319587628866%\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% confidence lower bound\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.556701030927837%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal effect\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003ec\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFBG\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eIndirect effect\u003c/p\u003e\n \u003cp\u003eDirect effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.17\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.587628865979383%\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.711340206185568%\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.08\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.77319587628866%\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.27\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.556701030927837%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2hPG\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIndirect effect Direct effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.26\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.587628865979383%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.711340206185568%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.15\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.77319587628866%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.39\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.556701030927837%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHbA1c\u003c/strong\u003e \u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIndirect effect Direct effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.18\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.587628865979383%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.711340206185568%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.09\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.77319587628866%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.28\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.556701030927837%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTG\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIndirect effect Direct effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.371134020618557%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.11\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.587628865979383%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.711340206185568%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.02\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.77319587628866%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.21\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study aimed to further investigate whether blood glucose and lipids mediate the relationship between pre-pregnancy BMI and pregnancy anxiety in pregnant women with GDM. We confirmed the bidirectional association between blood glucose and lipid levels during pregnancy and BMI and anxiety during pregnancy through correlation and regression analyses. The mediation effect analysis further confirmed that pre-pregnancy BMI had a significant effect on the pregnancy anxiety scores in pregnant women with GDM. In addition, FBG, 2hPG, HbA1c, and TG also mediated the effect of pre-pregnancy BMI on the pregnancy anxiety scores in pregnant women with GDM. Lastly, FBG, 2hPG, HbA1c, and TG did play a partial mediating role in the relationship between pre-pregnancy BMI and the pregnancy anxiety scores of GDM pregnant women.\u003c/p\u003e\n\u003cp\u003eRecently, the incidence of gestational diabetes has increased and this disease can cause great harm to pregnant women and fetuses.. Clinical evidence for gestational diabetes suggests that women experience extreme mood changes during pregnancy and are more likely to experience anxiety; negative emotions during pregnancy can cause maternal and infant complications.\u0026nbsp;\u003cbr\u003e\u0026nbsp;Previous research indicates that \u0026nbsp;women with GDM had a higher tendency to develop prenatal depression, anxiety, and stress[37-38]. Meanwhile, women with low income, low socioeconomic status, and low education levels have a higher incidence of prenatal anxiety and depression [39]. Adverse birth history and a family history of depression or anxiety are associated with anxiety and depression [40-43]. Our results indicate that the incidence of adverse history of abortion, family history of anxiety, low income, and low educational level in the anxious group was higher than that of those in the non-anxious group. In addition, our study also found that the average systolic blood pressure of the anxiety group is higher than the control group during pregnancy. This may be due to negative emotions, such as anxiety experienced by pregnant women with GDM for whom neuroendocrine changes occur constantly, thus enhancing the hypothalamus-pituitary-adrenal cortex system and sympathetic adrenal medullary system activity, leading to endothelial cell shrinkage and increased systolic blood pressure. Additionally, our results also revealed that pregnant women with GDM in the anxiety group had less sleep time than those in the control group.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt present, the prevalence of overweight or obese women during pregnancy is rapidly increasing worldwide [16-17], and its incidence is estimated to range from 12.3% to 63.5% [18]. Recently, the incidence of GDM is also increasing, and more than 40% of patients with GDM experience anxiety during pregnancy, indicating a high prevalence of anxiety in women with GDM [10-11].Some studies [20-21,44] have found a positive dose-response correlation between BMI and prenatal anxiety, depression, and other adverse emotions. However, another recent study failed to detect an association between the two [45]. Our correlation analysis demonstrated a significant positive correlation between pre-pregnancy BMI and the pregnancy anxiety scores of pregnant women with GDM, suggesting that\u0026nbsp;pregnant women with GDM with high pre-pregnancy BMI were more likely to display a high anxiety score during pregnancy. This correlation remained statistically significant after regression analysis excluding maternal systolic blood pressure during pregnancy, maternal education level, annual family income, previous history of abortion, family history of anxiety, and sleep during pregnancy, which was consistent with previous findings [17].\u003c/p\u003e\n\u003cp\u003eMost studies only discuss the relationship between BMI and prenatal anxiety before childbirth or only blood glucose and lipid levels, as well as the connection between anxiety during the second trimester; there are no further studies of the relationship between the four, lacking blood glucose and lipid level directions to explore the relationship between BMI and anxiety during pregnancy before childbirth. Pre-pregnancy BMI is not only correlated with anxiety during pregnancy, but also significantly correlated with blood lipids and glucose during pregnancy. Blood glucose and blood lipid levels during pregnancy are also correlated with anxiety during pregnancy. Therefore, this study is the first to explore the effects of blood glucose and lipids on the relationship between pre-pregnancy BMI and pregnancy anxiety in pregnant women with GDM using mediation analysis.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eWe found that the higher the pre-pregnancy BMI of GDM, the more serious the degree of anxiety during pregnancy. FBG, 2hPG, HbA1c, and TG of pregnant women with GDM play a role in the influence of pre-pregnancy BMI on pregnancy anxiety, and the effect of blood glucose (FBG, 2hPG, and HbA1c) on the influence of pre-pregnancy BMI on pregnancy anxiety was significantly stronger than that of blood lipids (TG). \u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study received ethical approval and all participants volunteered to participate\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this\u0026nbsp;\u003c/p\u003e\n\u003cp\u003epublished article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe gratefully acknowledge Wenshu Yu for providing intellectual support and technical assistance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors agreed to publish.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge that all authors have contributed significantly. Hong OuYang \u0026nbsp;devised the project, collected material and wrote the manuscript. Na Wu helped with the discussion, supervised the project and provided critical feedback.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the National Natural Science Foundation of China (No.81700706), the 345 Talent Project of Shengjing hospital, the Clinical research project of Liaoning Diabetes Medical Nutrition Prevention Society (No.LNSTNBYXYYFZXH-RS01B), the Natural Science Foundation of Liaoning Province (No. 2021-MS-182), the Science Foundation of Liaoning Education Department (No. LK201603), and the Virtual simulation experiment teaching project of China Medical University(No.2020-47).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to declare.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003eYi L, Bei N. 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Maternal pre-pregnancy body mass index, gestational weight gain influence birth weight, 2018,31(1): e20-e25.\u003c/span\u003e\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":"anxiety, blood glucose, blood lipids, mediating effects, gestational diabetes mellitus","lastPublishedDoi":"10.21203/rs.3.rs-1952539/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1952539/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Body mass index (BMI) before pregnancy and blood glucose and lipid levels during and before pregnancy are associated with anxiety among pregnant women with gestational diabetes mellitus (GDM). No study has further explored the relationship between these factors. Our study is the first to explore the effects of blood glucose and lipids on the relationship between BMI and anxiety in pregnant women with GDM using mediation analysis.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003ePregnant women diagnosed with GDM after completing the oral glucose tolerance test during pregnancy were followed up from January 2019 to December 2021. Collecting basic information including age, education level, annual family income, pre-pregnancy BMI, gestational age, history of abortion, family history of anxiety and diabetes, sleep status, and other information.\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eAfter adjusting\u0026nbsp;for relevant influencing factors, Pre-pregnancy BMI, FBG, HbA1c, 2hPG, and TG were still significantly correlated with the pregnancy anxiety scores . The results of the mediating effect model suggested that pre-pregnancy BMI significantly influenced the pregnancy anxiety scores in women with GDM (P\u0026lt;0.001); FBG, 2hPG, HbA1c, and TG significantly mediated the effect of BMI on the pregnancy anxiety scores, respectively, and played a partial mediator role between BMI and the pregnancy anxiety scores of pregnant women with GDM.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003ePre-pregnancy BMI was associated with pregnancy anxiety among pregnant women with GDM.\u0026nbsp;High BMI before pregnancy can lead to increased anxiety . Blood glucose and lipid levels during pregnancy play a part in the influence of BMI before pregnancy on anxiety .\u003c/p\u003e","manuscriptTitle":"Pre-pregnancy BMI and pregnancy anxiety in women with gestational diabetes mellitus: mediating effects of blood glucose and lipid levels1","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-08-25 18:16:31","doi":"10.21203/rs.3.rs-1952539/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":"f6096d08-3b3d-487a-bbf9-39ec0e10ee73","owner":[],"postedDate":"August 25th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-09-19T05:06:09+00:00","versionOfRecord":[],"versionCreatedAt":"2022-08-25 18:16:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1952539","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1952539","identity":"rs-1952539","version":["v1"]},"buildId":"oE6Zbj460LM0Up2FdVbMZ","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}