Abstract
目的
妊娠期糖尿病(gestational diabetes mellitus，GDM)是临床上常见的妊娠合并症，对母婴近期或远期的健康均会产生不良的影响。GDM的危险因素复杂、多样，孕妇年龄越大、产次越多，GDM发病风险也越高。若这两个已知的独立危险因素在各组间的分布不均衡，可能会掩盖其他危险因素的作用。因此，本研究以初产孕妇为研究对象，采用年龄1꞉1配对设计的病例对照方法探究GDM发病的危险因素，旨在对存在高危因素的孕妇进行早期干预，以降低其在孕中后期发生GDM的可能性，促进母婴健康。
方法
回顾性收集2018年8月至2019年10月在厦门大学附属妇女儿童医院产科或营养科门诊定期行产检、营养咨询的2 425例孕妇的临床资料，根据纳入和排除标准，共2 287例孕妇进入研究。在孕24~28周经口服葡萄糖耐量试验(oral glucose tolerance test，OGTT)确诊为GDM且资料完整的231例孕妇纳入GDM组。在糖耐量正常且资料完整的孕妇中，以GDM组年龄段为匹配因素进行1꞉1配对，用随机数字方法随机选择231例孕妇作为对照组进入研究。受试者总体年龄22~45(28.82±4.03)岁。收集患者孕前BMI，孕早期尿酸、空腹血糖(fasting blood glucose，FBG)、血脂指标及糖化血红蛋白(glycosylated hemoglobin，HbA1c)水平，孕13周前及孕24周前体重增长，流产次数，乙肝表面抗原是否阳性，父、母是否患有糖尿病、高血压等资料。比较2组孕前BMI、孕早期尿酸水平、孕早期FBG水平、孕13周前及孕24周前体重增长、早期血脂指标及HbAlc水平等资料。采用logistic回归分析研究GDM的危险因素。对2组孕妇孕24周前体重增长进行分层分析。
结果
GDM组孕前BMI、孕早期尿酸水平、孕早期FBG水平、孕13周前及孕24周前体重增长均高于对照组，差异均有统计学意义(均P<0.05)。GDM组孕早期LDL水平高于对照组，而HDL水平则低于对照组，差异均有统计学意义(均P<0.05)。GDM组流产超过2次、孕前超重或肥胖、孕早期FBG超过5.1 mmol/L的比例均高于对照组，差异均有统计学意义(均P<0.05)。随着孕24周前体重增长切点值的上升，GDM发病风险也逐渐增加，当切点值达到10 kg时，差异具有统计学意义(OR=1.988，P=0.004)。孕早期HDL≥1.6 mmol/L是GDM的保护因素(OR=0.460，P=0.016)，而孕24周前体重增长超过10 kg(OR=1.743，P=0.032)、孕早期FBG超过 5.1 mmol/L(OR=3.488，P=0.001)、孕早期LDL≥2.50 mmol/L(OR=2.179，P=0.032)是GDM的危险因素。其中，孕早期FBG超过5.1 mmol/L对增加孕中后期发生GDM风险的影响最大。
结论
在初产孕妇中，排除年龄的影响后，孕早期FBG及孕早期LDL水平越高，孕中后期发生GDM的风险越高。孕妇应当及早控制饮食，将孕24周前体重增长控制在10 kg以内，以降低发生GDM的风险。
Keywords: 年龄配对, 初产孕妇, 妊娠期糖尿病, 病例对照研究
Abstract
Objective
Gestational diabetes mellitus (GDM) is one of the most common complications of pregnancy. It is associated with a wide range of short and long term adverse health consequences for both mother and offspring. As we know, the risk factors of the GDM are complex and diverse, and the incidence of GDM is directly correlated with the age and the times of women delivery. In the process of exploring the risk factors of GDM, if the 2 known independent risk factors are unevenly distributed among groups, the effects of other risk factors may be concealed. To avoid the influence of the 2 factors on the research results, we collected primiparous women as the participants through the method of the case-control study of age 1꞉1 paired design. Through this way, we want to provide early intervention for the pregnant women with the high risk factors so as to reduce the possibility of the GDM during the pregnancy and promote the maternal and infant’s health.
Methods
This study was a retrospective study. A total of 2 425 pregnant women were collected as the participants, who accepted the regular prenatal examination or nutrition health guidance in the Department of Obstetrics or Nutrition in the Women and Children's Hospital, School of Medicine，Xiamen University from August 2018 to October 2019. According to the inclusion and exclusion criteria, 2 287 pregnant women were included in the study. Among them, 231 pregnant women with the complete information were collected as a case group because of the abnormal results of the oral glucose tolerance test (OGTT) that executed between the 24th and 28th weeks during the pregnancy. Meanwhile, among the participants with the normal results of the OGTT, 231 pregnant women with the complete information were selected randomly as a control group through the method of the age 1꞉1 paired with the case group. The age range of the all subjects was 22 to 45 (28.82±4.03) years old. We collected their clinical and basic data retrospectively, including the BMI before pregnancy, the level of uric acid, fasting blood glucose, serum lipid index, and glycosylated hemoglobin (HbA1c) in the early pregnancy, the body weight gain before the 13th and 24th weeks during the pregnancy, the times of the abortions, the positive of HBsAg, the family history of diabetes or hypertension etc. The differences in these indexes were compared between the 2 groups. The logistic regression analysis was used to explore the risk factors for GDM and the stratified analysis was used to explore the difference of the body weight gain before the 24th week during the pregnancy between the 2 groups.
Results
The BMI before pregnancy, the uric acid, the fasting blood glucose, the body weight gain before the 13th and 24th weeks during the pregnancy in the GDM group were higher than those in the control group, and the differences were significant (all P<0.05). The LDL level in the early pregnancy of the GDM group was higher than that of the control group, however, the HDL level in the early pregnancy of the GDM group was lower than that of the control group, and the differences were significant (both P<0.05). The rates of the pregnant women in the GDM group with more than 2 abortions, obesity or overweight before pregnancy, the fasting blood glucose in the early pregnancy over 5.1 mmol/L were significantly higher than those in the control group (all P<0.05). With the uptrend of the cut-off point of the body weight gain before the 24th week during the pregnancy, the risk of the GDM was gradually increasing. When the cut-off point reached at 10 kg, the difference was significant (OR=1.988, P=0.004). The level of HDL in the early pregnancy over 1.6 mmol/L was the protective factor for GDM (OR=0.460, P=0.016). Meanwhile, the body weight gain over 10 kg before the 24th week during the pregnancy (OR=1.743, P=0.032), the fasting blood glucose in the early pregnancy over 5.1 mmol/L (OR=3.488, P=0.001), the LDL in the early pregnancy over 2.5 mmol/L (OR=2.179, P=0.032) were the risk factors for the GDM. Among them, the fasting blood glucose in the early pregnancy over 5.1 mmol/L had the greatest impact on the increase of risk for the GDM.
Conclusion
After excluding the influence of the age, for primiparous women, the higher level of the LDL and the fasting blood glucose in the early pregnancy, the higher possibility to be the GDM. Meanwhile, the pregnant women should control their diet as soon as possible to control the body weight gain within 10 kg before the 24th week during the pregnancy so as to reduce the possibility of being GDM.
Keywords: age-matched, primiparous women, gestational diabetes mellitus, case-control study
妊娠期糖尿病(gestational diabetes mellitus，GDM)是指在妊娠期间首次发生或发现的糖代谢异常。中国的GDM发病率为2.0%~17.5%[1-2]，部分地区高达21.8%[3]。GDM不仅影响胎儿的生长发育，造成新生儿高胆红素血症、死胎、先天畸形、巨大儿等不良的妊娠结局，也会影响母体自身的健康。20%~50%的GDM孕妇产后5年内会发展为2型糖尿病[4]。因此，研究GDM的危险因素，早期发现GDM的高危人群对保障母婴健康具有十分重要的意义。高龄及既往有GDM史是GDM发病的强相关危险因素，为避免这两个因素对其他危险因素造成混杂影响，本研究采用以年龄为匹配因素的巢式病例对照研究方法来分析初产孕妇发生GDM的有关危险因素，旨在对存在高危因素的孕妇进行早期干预，以降低其在孕中后期发生GDM的可能性，促进母婴健康。
1. 对象与方法
1.1. 对象
本研究为回顾性研究。收集2018年8月至2019年10月在厦门市妇幼保健院产科及营养科门诊定期行产检、营养咨询的2 425例孕妇，根据纳入和排除标准，共2 287例孕妇进入研究。纳入标准：无心、肝、肺、肾等重要器官疾病，无良性肿瘤的单胎初产孕妇。排除孕早期空腹血糖(fasting blood glucose，FBG)≥ 7.0 mmol/L，孕早期糖化血红蛋白(glycosylated hemoglobin，HbA1c)≥6.5%，孕前有多囊卵巢综合征、胰岛素抵抗或糖尿病者。在孕24~28周308例孕妇经口服葡萄糖耐量试验(oral glucose tolerance test，OGTT)确诊为GDM，其中77例孕妇因信息资料缺失或失访，最终共有231例GDM孕妇(GDM组)。在1 979例糖耐量正常的孕妇中，排除信息资料不全的220例，剩余1 759例。在这1 759例孕妇中，以GDM组年龄段为匹配因素进行1꞉1配对，用随机数字方法随机选择231例孕妇作为对照组进入研究。受试者总体年龄22~45(28.82±4.03)岁。
1.2. 资料收集
收集患者孕前BMI，孕早期尿酸、FBG、血脂指标及HbA1c水平，孕13周前及孕24周前体重增长，流产次数，乙肝表面抗原是否阳性，父、母是否患有糖尿病、高血压等资料。
1.3. 诊断标准
依据中国肥胖问题工作组提出的标准[5]，BMI<18.5 kg/m2为消瘦，18.5~23.9 kg/m2为正常；24.0~27.9 kg/m2为超重，≥28.0 kg/m2为肥胖。GDM诊断标准[6-7]：在孕24~28周行OGTT，正常上限为FBG 5.1 mmol/L，饮糖水后1 h血糖10.0 mmol/L，2 h血糖8.5 mmol/L。任何一项超过上限，即可诊断为GDM。血脂指标包括血浆总胆固醇(total cholesterol，TC)、三酰甘油(triglyceride，TG)、低密度脂蛋白(low density lipoprotein，LDL)、高密度脂蛋白(high density lipoprotein，HDL)。
1.4. 孕24周前体重增长的分层分析
由于孕期OGTT一般在孕24~28周进行，因此GDM的诊断时间处在孕24周之后，为更好地分析孕期体重增长对GDM发病的影响，本研究对2组孕妇孕24周前体重增长进行分层分析。
1.5. 统计学处理
用SPSS 17.0统计软件进行数据分析，计量资料以均数±标准差( ±s)表示，计数资料用例(%)表示。采用两样本t检验比较2组孕妇孕前BMI、孕早期尿酸水平、孕早期FBG水平、孕13周前及孕24周前体重增长、孕早期血脂指标及HbAlc水平。采用χ2检验比较2组孕妇流产超过2次，孕前超重或肥胖，孕早期FBG超过5.1 mmol/L，乙肝表面抗原阳性，父、母患有糖尿病、高血压的比例。采用logistic回归分析研究GDM的危险因素。以P<0.05为差异有统计学意义。
2. 结 果
2.1. 两组孕妇的比较
GDM组孕前BMI、孕早期尿酸水平、孕早期FBG水平、孕13周前及孕24周前体重增长均高于对照组，差异均有统计学意义(均P<0.05，表1)。
表1.
2组孕妇一般情况的比较
Table 1 Comparison of the general conditions between the pregnant women of the 2 groups
| 组别 | 孕前BMI | 孕早期尿酸/(μmol·L-1) | 孕早期FBG/(mmol·L-1) | 体重增长/kg | ||
|---|---|---|---|---|---|---|
| 孕13周前 | 孕13~24周 | 孕24周前 | ||||
| GDM组 | 21.27±3.16 | 216.50±64.71 | 4.89±0.52 | 2.87±1.97 | 4.97±2.28 | 7.87±2.75 |
| 正常组 | 20.59±3.17 | 202.97±55.21 | 4.69±0.45 | 2.48±1.98 | 4.79±1.81 | 7.34±2.20 |
| t | 2.35 | 2.42 | 4.40 | 2.07 | 0.90 | 2.30 |
| P | 0.02 | 0.02 | <0.01 | 0.04 | 0.37 | 0.02 |
| 组别 | TG/(mmol·L-1) | TC/(mmol·L-1) | LDL/(mmol·L-1) | HDL/(mmol·L-1) | 孕早期HbAlc/% | 流产超过2次/[例(%)] |
|---|---|---|---|---|---|---|
| GDM组 | 1.46±0.58 | 4.90±0.95 | 2.22±0.69 | 1.65±0.31 | 5.13±0.31 | 39(16.9) |
| 正常组 | 1.48±0.55 | 4.92±0.94 | 2.03±0.65 | 1.78±0.38 | 5.08±0.29 | 23(10.0) |
| t/χ 2 | 0.23 | 0.27 | 2.97 | 4.18 | 1.60 | 4.77 |
| P | 0.82 | 0.78 | <0.01 | <0.01 | 0.11 | 0.03 |
| 组别 | 父亲有糖尿病/[例(%)] | 母亲有糖尿病/[例(%)] | 父亲有高血压/[例(%)] | 母亲有高血压/ [例(%)] | 孕前超重或 肥胖/[例(%)] | 乙肝表面抗原阳性/[例(%)] | 孕早期FBG> 5.1 mmol/L/[例(%)] |
|---|---|---|---|---|---|---|---|
| GDM组 | 17(7.4) | 15(6.5) | 10(4.3) | 7(3.0) | 45(19.5) | 18(7.8) | 79(34.2) |
| 正常组 | 13(5.6) | 8(3.5) | 19(8.2) | 6(2.6) | 28(12.1) | 19(8.2) | 26(11.3) |
| χ 2 | 0.57 | 2.24 | 2.98 | 0.08 | 4.70 | 0.03 | 34.62 |
| P | 0.45 | 0.13 | 0.08 | 0.78 | 0.03 | 0.86 | <0.01 |
GDM组孕早期LDL水平高于对照组，而HDL水平则低于对照组，差异均有统计学意义(均P<0.05)；2组在孕早期TG、TC及HbAlc水平方面差异均无统计学意义(均P>0.05，表1)。
GDM组流产超过2次，孕前超重或肥胖，孕早期FBG超过5.1 mmol/L的比例均高于对照组，差异均有统计学意义(均P<0.05)；而2组孕妇在乙肝表面抗原，父、母患有无糖尿病、高血压比例方面的差异均无统计学意义(均P>0.05，表1)。
2.2. 孕24周前体重增长切点值
随着孕24周前体重增长切点值的上升，GDM发病风险也逐渐增加，当切点值达到10 kg时，差异具有统计学意义(OR=1.988，P=0.004；表2)。
表2.
2组孕妇24周前体重增长切点值
Table 2 Cut-off value of the body weight gain before 24th week of the pregnant women in the 2 groups
| 切点值/kg | a | b | c | d | χ 2 | P | OR | 95% CI | |
|---|---|---|---|---|---|---|---|---|---|
| 上限 | 下限 | ||||||||
| 6 | 50 | 181 | 52 | 179 | 0.050 | 0.822 | 0.951 | 0.613 | 1.476 |
| 7 | 90 | 141 | 77 | 154 | 1.585 | 0.208 | 1.277 | 0.873 | 1.868 |
| 8 | 131 | 100 | 116 | 115 | 1.957 | 0.162 | 1.299 | 0.900 | 1.873 |
| 9 | 161 | 70 | 149 | 82 | 1.412 | 0.235 | 1.266 | 0.858 | 1.868 |
| 10 | 197 | 34 | 172 | 59 | 8.414 | 0.004 | 1.988 | 1.243 | 3.177 |
| 11 | 214 | 17 | 193 | 38 | 9.102 | 0.003 | 2.479 | 1.355 | 4.535 |
| 12 | 224 | 7 | 212 | 19 | 5.869 | 0.015 | 2.868 | 1.182 | 6.961 |
a：对照组低于该切点值的例数；b：对照组高于该切点值的例数；c：GDM组低于该切点值的例数；d：GDM组高于该切点值的例数。
2.3. GDM的影响因素
将差异有统计学意义的变量引入logistic回归模型并赋值(表3)，当α=0.05时，孕早期HDL≥1.6 mmol/L是GDM的保护因素(OR=0.460，P=0.016)，而孕24周前体重增长超过10 kg(OR=1.743，P=0.032)、孕早期FBG超过5.1 mmol/L(OR=3.488，P=0.001)、孕早期LDL≥2.50 mmol/L(OR=2.179，P=0.032)是GDM的危险因素(表4)。其中，孕早期FBG超过5.1 mmol/L对增加孕中后期发生GDM风险的影响最大。
表3.
Logistic回归分析的研究变量及赋值分层
Table 3 Research variables and assignment stratification of logistic regression analysis
| 变量 | 赋值方法及分层 |
|---|---|
| 流产次数 | ≤1次=0，≥2次=1 |
| 孕前是否存在肥胖或超重 | 无=0，有=1 |
| 孕早期FBG是否超过5.1 mmol/L | 无=0，有=1 |
| 孕24周前体重增长 | <10 kg=0，≥10 kg=1 |
| 孕早期尿酸是否超过357 μmol/L | 无=0，有=1 |
| 孕早期LDL | <1.5 mmol/L=1，1.5~<2.0 mmol/L=2，2.0~<2.5 mmol/L=3，≥2.5 mmol/L=4 |
| 孕早期HDL | <1.4 mmol/L=1，1.4~<1.6 mmol/L=2，1.6~<1.8 mmol/L=3，≥1.8 mmol/L=4 |
表4.
影响GDM影响因素的logistic 回归分析结果
Table 4 Results of the logistic regression analysis for the influential factors of GDM
| 变量 | β | SE | Wald χ2 | OR | 95% CI | P |
|---|---|---|---|---|---|---|
| 流产次数是否大于2 | 0.359 | 0.311 | 1.333 | 1.431 | 0.779~2.631 | 0.248 |
| 孕前是否存在肥胖或超重 | 0.020 | 0.296 | 0.005 | 1.020 | 0.571~1.821 | 0.946 |
| 孕早期FBG是否超过5.1 mmol/L | 1.249 | 0.262 | 22.671 | 3.488 | 2.086~5.833 | 0.001 |
| 孕24周前体重增长是否超过10 kg | 0.556 | 0.259 | 4.590 | 1.743 | 1.048~2.898 | 0.032 |
| 孕早期尿酸是否超过357 μmol/L | 1.070 | 0.815 | 1.724 | 2.916 | 0.590~14.403 | 0.189 |
| 孕早期LDL(以<1.5 mmol/L为标准) | 6.200 | 0.043 | ||||
| 1.5~<2.0 mmol/L | 0.233 | 0.335 | 0.484 | 1.263 | 0.655~2.434 | 0.486 |
| 2.0~<2.5 mmol/L | 0.220 | 0.341 | 0.415 | 1.246 | 0.638~2.430 | 0.519 |
| ≥2.5 mmol/L | 0.779 | 0.362 | 4.620 | 2.179 | 1.071~4.432 | 0.032 |
| 孕早期HDL(以<1.4 mmol/L为标准) | 12.693 | 0.005 | ||||
| 1.4~<1.6 mmol/L | -0.236 | 0.363 | 0.423 | 0.790 | 0.387~1.609 | 0.515 |
| 1.6~<1.8 mmol/L | -0.777 | 0.321 | 5.836 | 0.460 | 0.245~0.864 | 0.016 |
| ≥1.8 mmol/L | -0.979 | 0.322 | 9.266 | 0.376 | 0.200~0.706 | 0.002 |
3. 讨 论
GDM是妊娠妇女围产保健中常见的并发症之一，全球发病率在6%~13%[7]。在GDM众多的危险因素中，年龄往往会作为一种混杂因素掩盖其他危险因素的作用，而GDM病史对再生育孕妇的生殖健康有着显著影响[8]，会显著增加再生育孕妇发生GDM的风险[9]。为消除年龄及生育史对研究结果的影响，本研究在初产孕妇人群中采用了以年龄为匹配因素1꞉1配对设计的巢式病例对照研究方法来探讨与GDM发病有关的危险因素。
孕期体重增长过多会刺激胰岛β细胞产生高胰岛素血症，从而增加GDM的发病风险，也会引起产后肥胖或产后糖尿病。研究[2]发现：在孕24周前，BMI每增加1个单位，GDM的发病风险增加1.126倍，孕期体重增长过多的孕妇日后发生2型糖尿病的可能性是体重增长较少的孕妇的3~10倍[10]。本研究结果显示：GDM组孕妇在孕13周前和24周前体重增长都超过了对照组，并且孕24周前体重增长超过10 kg是GDM的危险因素。这与国内学者的研究[11]结果相近。由此可见，督促孕妇保持孕期体重的合理增长是围产保健人员的重要职责。
孕早期FBG≥5.1 mol/L是GDM强相关的危险因素，这也就意味着可以用孕早期FBG来预测孕中后期发生GDM的可能。Zhu等[12]回顾性地分析了17 186名孕妇资料后发现：在孕早期FBG为5.10~6.99 mmol/L的孕妇中，有39.77%的在孕中后期被诊断为GDM。因此，加强孕早期FBG的监测和管理，对早期FBG≥5.1 mol/L的孕妇采取有效的干预措施和营养宣教是降低GDM发病率的强有力措施。
HbAlc是葡萄糖与血红蛋白结合后形成的产物，其形成是一个缓慢、相对不可逆的非酶促反应，可以反映检测前2~3个月的平均血糖水平。研究[13]认为孕早期HbAlc可以作为GDM的预测因子。当其切点值为5.7%时，在预测GDM发病风险上，能得到74%的阳性预测值[14]，但也有不少学者[15-16]指出孕期HbAlc还不足以作为GDM的诊断标准。在本研究中，GDM组孕妇孕早期HbAlc水平虽然略高于对照组孕妇，但差异并无统计学意义。究其原因可能在于：1)本研究采用的是以年龄段为匹配因素的巢式病例对照研究，两组孕妇在年龄上具有可比性，血糖代谢初始水平可能也具有可比性，这也更有利于发现GDM的危险因素。2)在纳入和排除标准的基础上，本研究收集的是初产孕妇，并排除了孕早期HbAlc超过6.5%的人群。3)部分孕妇存在早孕反应，食物摄入量不多的状态可能会造成机体血糖处在较低的水平，从而导致孕早期HbAlc水平并不高。笔者认为：孕早期HbAlc可以起到预测GDM的作用，但其切点值目前还未见统一标准，尚需要进一步研究。
孕期血脂出现的生理性升高是为了满足胎儿及母体的营养需求，但过高的血脂水平也可能会给母婴健康带来负面影响，如孕期高TG、高LDL水平会增加子痫前期、妊娠期肝内胆汁淤积症、巨大儿的发生风险[17]。本研究发现：GDM组孕早期LDL水平高于对照组，孕早期LDL≥2.5 mmol/L是GDM发生的危险因素。因此，孕早期LDL或许可用来预测孕中后期发生GDM的可能。另外，孕早期HDL≥ 1.6 mmol/L是GDM的保护因素，提示孕早期HDL水平低也可能是GDM发病的危险因素。GDM孕妇孕早期LDL、TG水平高于对照组孕妇[18-20]，HDL水平低于对照组孕妇[21]，国内学者[22]应用受试者工作特征曲线探讨孕早期TG/HDL的比值预测GDM发病风险的效能，得到的曲线下面积为0.664，这些均提示孕早期LDL和HDL与GDM发病风险存在相关性，本研究结果与上述研究相符。但有报道显示GDM组孕妇孕早、中、晚期LDL水平与对照组孕妇均较为接近，也有学者[24]发现GDM组孕妇LDL水平低于对照组孕妇。鉴于目前临床上尚无孕期各项血脂指标的正常参考值范围和评价标准，而孕早期各项血脂指标对GDM发病风险的预测效能尚存争议。因此，笔者认为很有必要在孕期糖脂代谢相互关系方面作进一步的研究。
基金资助
中国疾病预防控制中心妇幼保健中心母婴营养与健康研究项目(2020FYH025)。
This work was supported by the Project of the Research about the Maternal and Infant's Nutrition and Health, the National Center for Women and Children's Health, CDC, China (2020FYH025).
利益冲突声明
作者声称无任何利益冲突。
原文网址
http://xbyxb.csu.edu.cn/xbwk/fileup/PDF/2021121346.pdf
参考文献
- 1. Wang H, Yang J, Du H, et al. Perfluoroalkyl substances, glucose homeostasis and gestational diabetes mellitus in Chinese pregnant women: A repeat measurement- based prospective study[J]. Environ Int, 2018, 114(8): 12-20. [DOI] [PubMed] [Google Scholar]
- 2. Zhu WW, Yang HX, Wang C, et al. High prevalence of gestational diabetes mellitus in Beijing: Effect of maternal birth weight and other risk factors[J]. Chin Med J (Engl), 2017, 130(9): 1019-1025. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Wu L, Han L, Zhan Y, et al. Prevalence of gestational diabetes mellitus and associated risk factors in pregnant Chinese women：a cross-sectional study in Huang dao, Qingdao, China[J]. Asia Pac J Clin Nutr, 2018, 27(2): 383-388. [DOI] [PubMed] [Google Scholar]
- 4. Allalou A, Nalla A, Prentice KJ, et al. A predictive metabolic signature for the transition from gestational diabetes mellitus to type 2 diabetes[J]. Diabetes, 2016, 65(9): 2529-2539. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. 全国卫生专业技术资格考试专家委员会 . 营养学[M]. 北京: 人民卫生出版社, 2015: 95. [Google Scholar]; The Expert Committee of the National Health Professional and Technical Qualification Examination . Nutrition[M]. Beijing: People’s Medical Publishing House, 2015: 95. [Google Scholar]
- 6. 中华医学会妇产科学分会产科学组 . 孕前和孕期保健指南(第1版)[J]. 中华妇产科杂志, 2011, 46(2): 150-153. [Google Scholar]; The Society of Gynaecology and Obstetrics of the Chinese Medical Association . Guidelines for the pre pregnancy and pregnancy care (first edition)[J]. Chinese Journal of Obstetrics and Gynecology, 2011, 46(2): 150-153. [Google Scholar]
- 7. Leng J, Shao P, Zhang C, et al. Prevalence of gestational diabetes mellitus and its risk factors in Chinese pregnant women: a prospective population-based study in Tianjin, China[J/OL]. PLoS One, 2015, 10(3): e0121029. (2015-03-23)[2021-2-16]. 10.1371/journal.Phone.0121029. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Ashraf M, Sheikhan F, Arabipoor A, et al. Gestational diabetes mellitus risk factors in women with polycystic ovary syndrome (PCOS)[J]. Eur J Obstet Gynecol Reprod Biol, 2014, 7(43): 195-199. [DOI] [PubMed] [Google Scholar]
- 9. Ali AD, Mehrass AA, Al-Adhroey AH, et al. Prevalence and risk factors of gestational diabetes mellitus in Yemen[J]. Int J Womens Health, 2016, 8: 35-41. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Rayanagoudar G, Hashi AA, Zamora J, et al. Quantification of the type 2 diabetes risk in women with gestational diabetes: a systematic review and meta-analysis of 95, 750 women[J]. Dialectologies, 2016, 59(7): 1403-1411. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Feng Y, Jiang CD, Chang AM, et al. Interactions among insulin resistance, inflammation factors, obesity-related gene polymorphisms, environmental risk factors, and diet in the development of gestational diabetes mellitus[J]. Matern Fetal Neonatal Med, 2019, 32(2): 339-347. [DOI] [PubMed] [Google Scholar]
- 12. Zhu WW, Yang HX, Wei YM, et al. Evaluation of the value of fasting plasma glucose in the first prenatal visit to diagnose gestational diabetes mellitus in China[J]. Diabetes Care, 2013, 36(3): 586-590. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Pezeshki B, Chiti H, Arasteh P, et al. Early screening of gestational diabetes mellitus using hemoglobin A1C: Revising current screening guidelines[J]. Caspian J Intern Med, 2019, 10(1): 16-24. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Bozkurt L, Göbl CS, Leitner K, et al. HbA1c during early pregnancy reflects beta-cell dysfunction in women developing GDM[J/OL]. BMJ Open Diab Res Care, 2020, 8(2): e001751 (2020-11-01)[2021-03-10]. 10.1136/bmjdrc-2020-001751. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Rayis DA, Ahmed ABA, Sharif ME, et al. Reliability of glycosylated hemoglobin in the diagnosis of gestational diabetes mellitus[J/OL]. J Clin Lab Anal, 2020, 34(10): e23435 (2020-07-02)[2021-03-10]. 10.1002/jcla.23435. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Lai Y, Chen H, Du Z, et al. The diagnostic accuracy of HbA1c in detecting gestational diabetes mellitus among Chinese pregnant individuals[J]. Ann Transl Med, 2020, 8(16): 1014-1023. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Agha-Jaffar R, Oliver N, Johnston D, et al. Gestational diabetes mellitus: does an effective prevention strategy exist[J]. Nat Revi Endocrinol, 2016, 12(9): 533-546. [DOI] [PubMed] [Google Scholar]
- 18. Correa PJ, Venegas P, Palmeiro Y, et al. First trimester prediction of gestational diabetes mellitus using plasma biomarkers: a case-control study[J]. J Perinat Med, 2019, 47(2): 161-168. [DOI] [PubMed] [Google Scholar]
- 19. 肖喜荣, 董欣然，李笑天, 等. 孕妇基本特征及14~20周糖脂代谢指标对妊娠期糖尿病的早期预测价值[J]. 中国实用妇科与产科杂志, 2018, 34(4): 429-432. [Google Scholar]; XIAO Xirong, DONG Xinran, LI Xiaotian, et al. Early prediction of gestational diabetes mellitus at 14-20 weeks: a practical model based on clinical characteristics and selected metabolic markers[J]. Chinese Journal of Practical Gynecology and Obstetrics, 2018, 34(4): 429-432. [Google Scholar]
- 20. 胡智颖, 胡梅, 韩静, 等. 妊娠期糖尿病患者孕早期血脂代谢状态的临床价值[J]. 标记免疫分析与临床, 2019, 26(9): 1476-1479. [Google Scholar]; HU Zhiying, HU Mei, HAN Jing, et al. The clinical value of blood lipid metabolism in patients with gestational diabetes mellitus in early pregnancy[J]. Labeled Immunoassays and Clinical Medicine, 2019, 26(9): 1476-1479. [Google Scholar]
- 21. Alyas S, Roohi N, Ashraf S, et al. Early pregnancy biochemical markers of placentation for screening of gestational diabetes mellitus[J]. Diabetes Metab Syndr, 2019, 13(4): 2353-2356. [DOI] [PubMed] [Google Scholar]
- 22. Liu PJ, Liu Y, Ma L, et al. The predictive ability of two triglyceride-Associated indices for gestational diabetes mellitus and large for gestational age infant among Chinese pregnancies: A preliminary cohort study[J]. Diabetes Metab Syndr Obes, 2020, 13: 2025-2035. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Wang J, Li Z, Lin L. Maternal lipid profiles in women with and without gestational diabetes mellitus[J/OL]. Medicine (Baltimore), 2019, 98(16): e15320 (2019-04-19) [2021-03-10]. 10.1097/MD.0000000000015320. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Chen Y, Du M, Xu J, et al. The small dense LDL particle/large buoyant LDL particle ratio is associated with glucose metabolic status in pregnancy[J]. Lipids Health Dis, 2017, 16: 244-251. [DOI] [PMC free article] [PubMed] [Google Scholar]