|Year : 2017 | Volume
| Issue : 1 | Page : 1-7
Factors influencing the incidence of gestational diabetes mellitus in Omani patients
Havagiray R Chitme, Sumaiya Abdallah Abdallah Said Al Shibli, Raya Mahmood Al-Shamiry
Department of Pharmacy, Oman Medical College, Muscat, Sultanate of Oman
|Date of Web Publication||25-Jan-2017|
Havagiray R Chitme
Department of Pharmacy, Oman Medical College, Bowshar Campus, Postal Code 130, P. O. Box: 620, Azaiba, Muscat
Sultanate of Oman
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Gestational diabetes mellitus (GDM) risk factors identification and modifying them appropriately will assist in reducing the incidence of maternal and fetal complications for high-risk individuals. Aim: The present cross-sectional case–control multicentered study was conducted with an objective to understand the modifiable risk factors in GDM patients of different regions in Oman. Materials and Methods: The study was conducted by involving 291 women diagnosed with GDM and 300 normal pregnant women with euglycemia. Primary information including body weight, waist circumference, body mass index (BMI), history of pregnancy complications, diet, lifestyle, exercise, occupation, education, and use of steroids was collected by face-to-face interview with an assistance of staff nurse working at respective hospitals. Secondary information was collected from hospital records. Results: GDM cases on an average have 5.47 kg body weight significantly (P < 0.001) higher than the control group. A maximum number of GDM cases were seen in women with waist circumference of more than 99.9 cm having a significant (P < 0.001) mean difference of 6.4 cm between GDM and normal population.;Deg;BM;Deg;I of GDM population was significantly (P < 0.001) higher 30.59 ± 7 kg/m2 compared to 27.89 ± 6.93 kg/m2 of normal population with a likelihood ratio of 300.85. The use of corticosteroids significantly is seen to be associated with an increase in the incidence of GDM (P < 0.001). Physical inactivity has significantly (P < 0.001) increase the risk of GDM by 3.7 times. Whereas walking for more than 30 min/day has significantly reduced the GDM risk by 0.356 times. Prior history of stillbirth is significantly (P < 0.05) associated with GDM cases compared to control. Conclusion: Screening of patients for GDM and following a strategy to modify the identified risk factors will be advantageous and may help to identify those most likely to benefit from intervention.
Keywords: Corticosteroids, gestational diabetes, modifiable, Oman, risk factor, women
|How to cite this article:|
Chitme HR, Al Shibli SA, Al-Shamiry RM. Factors influencing the incidence of gestational diabetes mellitus in Omani patients
. Int J Nutr Pharmacol Neurol Dis 2017;7:1-7
|How to cite this URL:|
Chitme HR, Al Shibli SA, Al-Shamiry RM. Factors influencing the incidence of gestational diabetes mellitus in Omani patients
. Int J Nutr Pharmacol Neurol Dis [serial online] 2017 [cited 2017 Dec 14];7:1-7. Available from: http://www.ijnpnd.com/text.asp?2017/7/1/1/199067
| Introduction|| |
Gestational diabetes mellitus (GDM) is defined as impaired glucose tolerance or impaired fasting glucose with first onset or recognition during pregnancy. The development of GDM is related to physiological insulin resistance mediated by pregnancy-related hormones, especially during the third trimester and increasing the risk of developing Type 2 diabetes in both mother and child. GDM is linked to the transient progressive insulin resistance associated with adverse maternal, fetal, and neonatal complications. Maternal complications include cesarean delivery, microalbuminuria, macrosomia, preterm delivery, preeclampsia, induction of labor, polyhydramnios, and oligohydramnios. Fetal and neonatal complications include admission to Intensive Care Units, congenital anomalies, perinatal mortality, neonatal hyperbilirubinemia, neonatal hypoglycemia, lower Apgar score, and respiratory distress syndrome., Despite glycemic regulation by dietary interventions, insulin use, and glyburide and metformin therapies, the mother and fetus/neonate are not totally free from consequences. Recent studies stressed on the need of early gestational screening to avoid the development of GDM but not on its prevention.
Global prevalence of GDM varies from 1% to 14% depending on the population studied and the diagnostic tests used. However, a wide variation in modifiable and nonmodifiable risk factors within the country, country to country, and between the regions has been noticed. A study carried out in Iran reported a positive family history of DM and GDM, multiparity, older age, obesity, weight gain during pregnancy, history of infertility, chronic hypertension, history of stillbirth, and abortions as major risk factors. A cross-sectional study in the Philippines indicated body mass index (BMI), hormonal contraceptives, androgens, limited physical activity, cigarette smoking, and family history of diabetes are increasing the risk of GDM associated with incidence. The retrospective study carried out in the UAE identified advanced age, multiparity, and obese women to be at higher risk for gestational diabetes. A study in Sudan reported that proteinuria, preeclampsia, higher blood pressure, and glucosuria as major risk factors leading to GDM.
A study carried out by retrospective review of records of delivery room and linkage to records of diabetic clinic at Sohar-Oman hospital indicated that patients with GDM have three times higher risk of developing hypertension, higher BMI, and macrosomia. Whereas 5 times more number of neonates born to women with GDM were admitted to special care units. The rate of macrosomia was 16% in neonates born to mother with GDM. Approximately, 26% of women with GDM have undergone cesarean section. According to the Ministry of Health annual statistical reports 2001 and 2002, 670 of 51,559 and 780 of 52,033 pregnant women screened for glucose intolerance were diagnosed with GDM. An exploratory cross-sectional study conducted to assess the risk for diabetes among Oman adults in Muscat showed that 17.2% had slightly higher risk of developing Type 2 DM within 10 years. It is also been noted that 30% of the Omani population is overweight, 20% are obese, and 41% have high cholesterol. Recently, published article states that 5% of all pregnant women are diagnosed with GDM in Oman. In addition, 14.3% of fetal deaths are attributed to GDM. A study from Sultan Qaboos University Hospital, Oman, published very recently highlighted that 27.9% of GDM patients have undergone cesarean section and 23.9% had to undergo labor induction. Highest number (12.9%) of neonates were admitted to Neonatal Intensive Care Unit, 8.8% of the babies were with low birth weight, and 4.9% of them were macrosomic. However, there are no detailed studies carried out to know the underlying risk factors for GDM and their extent in Omani population.
The present study is based on the hypothesis that the modifiable risk factors for GDM in Omani patients vary from other countries due to the growing prevalence of Type 2 diabetes in Oman; increase in pregnancy complications, congenital malformations; increased urbanization and number of affluent families and obesity;, heterogenic structure of Omani population; traditional dietary and social culture;, higher level of female education and occupation; higher female fertility rate, early marriage, multiparity, and other gestational factors., The main aim of this study was to determine the frequency and examine the extent of relationship of GDM with BMI, waist circumference, dietary, physical activity, occupation, level of education, gestational complications, and use of steroids.
| Materials and Methods|| |
This was a hospital-based, cross-sectional, case–control, multicenter study carried out from February 2015 to July 2015 at Nizwa polyclinic, Sohar regional hospital, and Rustaq hospitals of Ministry of Health in Oman, after obtaining approval from Research and Ethics Committee, Ministry of Health, Oman. Primary data were collected from face-to-face interview conducted in assistance of staff nurses at respective hospitals and a retrospective review of GDM cases and controls. The normal control group includes pregnant women with normal glycemic control and no prior history of diabetes.
Selection of participants
Data were collected from 591 cases of which 291 were diagnosed with GDM and 300 were normal control. Pregnant patients visiting the selected hospitals during the study period February 2015 to July 2015 were considered. Patients with pregestational diabetes, fluctuating glucose level, pancreatitis, pancreatectomy, no prenatal check-up, and not following-up their gestational glycemia were excluded from the study.
Literature-based questionnaire, was developed. Questionnaire developed for the study helped in collecting the data on demography, education level, obstetric history, gestational outcomes, glucose profile, diabetic history, nutritional and medication supplementation, BMI, waist circumference, medical history, and others. The Human Ethical Committee of the Office of Ministry of Health, Oman, vide ref MH/DGP/R and S/PROPOSAL_APPROVED/10/2015 has approved this study.
Each case was given a case number and the information collected in this study were entered directly into SPSS version 19.0 (IBM Corporation, USA) and analyzed using descriptive statistics such as mean and standard deviation for continuous numerical data, and for categorical data, percentage frequency distribution were used. Any difference in continuous and categorical variables of control and case group was described by descriptive analysis of frequencies, Chi-square test for categorical variables, Student’s t-test for independent samples, and Pearson’s test for correlations, with the level of significance set at 5%.
| Results|| |
Frequency of samples selected from each hospital
Present study was multicenter systematic randomized as 98, 94, and 99 number of GDM patients were from Nizwa polyclinic, Sohar hospital, and Rustaq Hospital, respectively, whereas 100 number of normal control cases were selected from each hospital for comparison with cases.
Anthropometric data of the gestational diabetes mellitus and control group
Number of GDM cases were dominantly increasing with respect to increase in body weight over the normal. However, cross-correlation was statistically insignificant. A maximum number of GDM cases were between 71 and 75 kg, whereas highest number of normal pregnancy cases were between 61 and 65 kg. Mean body weight of normal cases was 73.09 ± 17.42 compared to 78.56 ± 17.35 of GDM cases with a significant (P < 0.001) mean difference of 5.468 (confidence interval [CI]: 2.6578–8.2792). The body weight of GDM cases was consistently higher than the normal, which indicate that risk for GDM is higher with respect to increase in body weight during pregnancy [Figure 1]. Women with gestational weight of <70 kg have lesser percent of developing GDM. Mean waist circumference of GDM population was 108.13 ± 15.26 cm significantly (P < 0.001) higher than normal group of population 101.73 ± 18.91 cm with a mean difference of 6.4 (CI: 3.6003–9.2101) which is significantly (P < 0.001) higher in GDM cases compared to control. Likelihood ratio of association between waist circumference and incidence of GDM was 173.03 and linear by linear association was 19.47. A maximum number of GDM cases were seen in women with waist circumference of more than 99.9 cm. However, number of normal cases were increasing with decreased waist circumference [Figure 2]. Mean BMI of GDM population studied was significantly (P < 0.001) higher 30.59 ± 7 kg/m2 than 27.89 ± 6.93 kg/m2 of normal population. Statistically significant (P < 0.001) mean difference of 2.7 (CI: 95%, 1.575–3.8272) was recorded between these two groups. Median BMI of incidence of GDM was at 30 kg/m2, whereas in control, it was 26.5 kg/m2. Likelihood ratio of 300.85 and linear by linear association was 22.17 indicating a strong relationship between incidences of GDM with an increased BMI. A maximum number of GDM cases were found in women with BMI of more than 30 kg/m2. However, risk was found to be lesser with women having BMI lesser than 27 kg/m2 [Figure 3].
|Figure 1: Distribution of body weight in control and gestational diabetes mellitus cases. GDM: Gestational diabetes mellitus|
Click here to view
|Figure 2: Stratified distribution of waist circumference (cm) in normal and gestational diabetes mellitus cases. GDM: Gestational diabetes mellitus|
Click here to view
|Figure 3: Simple Boxplot comparative analysis of body mass index in the study sample. GDM: Gestational diabetes mellitus; *P < 0.05 (Pearson Chi-square analysis)|
Click here to view
Lifestyle and dietary factors in the study population
Frequencies of dietary intake including fruits, vegetables, chicken, and meat consumption were found to have no significant influence on incidence of GDM compared to control group [Table 1]. Odds ratio (OR) for consumption of fruits, vegetables, chicken, and meat was 0.933 (CI: 0.818–1.065) (P > 0.05), 1.015 (CI: 0.882–1.169) (P > 0.05), 1.147 (CI: 1.012–1.301) (P < 0.05), and 0.931 (0.84–1.032) (P > 0.05), respectively. A significantly (P < 0.05) higher number of GDM was consuming chicken compared to control group. However, there is no change in risk with frequencies of consumption of fruits, vegetables, and meat. Frequency of intake of tea and coffee was found to have no significant influence on incidence of GDM compared to control group [Table 1]. However, the risk for GDM was significantly lowered to 0.836 times in patients consuming tea (CI: 0.735–0.951) (P < 0.05) compared to control, but consumption of coffee insignificantly (P > 0.05) increase the risk for GDM by 1.126 times (CI: 0.98–1.293).
Occupation, exercise, and educational characteristics in selected population of the study
In our study, there were no significant differences noted in incidence of GDM and control group with respect to occupation. Almost equal percent of women in normal control and GDM group was employed and homemakers. Linear regression analysis shows that risk for homemaker was 1.083 times that of control (CI: 0.752–1.561) and employed women was lowered by 0.94 times (CI: 0.653–1.353) compared to control group. However, significant (P < 0.05) risk of incidence of GDM was increased by 1.531 times in secondary school educated women compared to control (CI: 1.08–2.172). In this study, 72.85% of women with GDM were having secondary school education compared to 63.66% of the normal [Table 2]. Physical inactivity has significantly (P < 0.001) increase the risk for GDM by 3.711 times (CI: 1.847–7.458) compared to control group. Walking for <30 min/day has no significant difference with a risk of 1.005 times (CI: 0.72–1.403) in incidence of GDM compared to control. However, walking for more than 30 min/day has significantly (P < 0.05) reduced the risk by 0.356 times (CI: 0.155–0.817) compared to control.
|Table 2: Occupation, education, and exercise characteristics in normal and gestational diabetes mellitus population|
Click here to view
Comparative analysis of use of corticosteroids in gestational diabetes mellitus and normal cases
Pearson’s Chi-square analysis of data on use of corticosteroids and incidence of GDM has shown to be at that there is a significantly (P < 0.001) higher risk. This is due to the combined use of dexamethasone and other corticosteroids than normal. It is important to mention that the ratio of normal pregnant women taking prednisolone compared to GDM was 26:1, likelihood ratio was 58.04, and linear-by-linear association was 1.243. Whereas significantly higher risk (P < 0.05) was associated with the use of hydrocortisone. Mean duration of use of corticosteroids in control group was 72.78 ± 113.11 days significantly (P < 0.001) lower than GDM group of patients was 75.22 ± 86.55 days with mean difference of −2.439 (−43.31–37.44) indicated that lower the duration of use of steroids lower the risk of developing GDM. Patients who are not on corticosteroids have significantly (P < 0.05) lowered the risk of GDM by 0.715 times (CI: 0.476–1.073) compared to the control group of population [Table 3].
|Table 3: Comparative analysis of corticosteroid use in the study population|
Click here to view
Correlation between gestational complications and incidence of gestational diabetes
Number of cases was having prior history of pregnancy complications. However, Pearson’s Chi-square analysis has shown a significant correlation between incidence of GDM and history of gestational problems (P < 0.001) higher than normal with a likelihood ratio of 42.62. Prior history of stillbirth in women is also significantly (P < 0.05) associated with GDM cases compared to control. Duration of existence of gestational problems has no significant (P > 0.05) influence on incidence of GDM with mean difference of 2.559 (CI: −1.3107–6.4292) compared to control group. However, the risk of GDM was significantly (P < 0.001) reduced to 0.616 times (CI: 0.421–0.901) in population having no history of gestational complications [Table 4].
|Table 4: Correlation between gestational complications and incidence of gestational diabetes|
Click here to view
| Discussion|| |
The present cross-over, case–control, multicenter systematic randomized study involving 98, 94, and 99 GDM patients and 300 normal patients from three different hospitals of Ministry of Health, Oman, shows some of the risk factors for gestational diabetes is similar to risk factors identified globally; however, some of them differ from other population. It is well known that the prevalence and incidence of GDM vary with respect to urban and rural region, race, and ethnicity., Therefore, the present study was conducted in different regions of Oman to include population of different regions. The present module used in GDM risk factors analysis in Omani women was valid with Nagelkerke R2 value found to be 0.5823 having significantly variable factors.
Several studies have identified anthropometric parameters influencing the incidence of GDM. In our study, number of GDM cases were predominantly increased with respect to increase in body weight over the normal. However, cross-correlation was statistically insignificant in-line with the results obtained among Chinese women. The mean waist circumference of GDM population was 108.13 ± 15.26 cm significantly (P < 0.01) higher than normal group of population 101.73 ± 18.91 cm. A maximum number of GDM cases were seen in women with waist circumference of more than 99.9 cm. The mean waist circumference increasing the risk for GDM is higher than the earlier studies reported., It is well established that higher the BMI higher will be the risk of developing GDM. In this study, mean BMI of GDM population was significantly (P < 0.001) higher compared to normal population. A maximum number of GDM cases were found in women with BMI of more than 30 kg/m2 similar to the recent study report. These results also support the guidelines recommending to prevent GDM by maintaining BMI of <25 kg/m2.
There are many prophylactic steps including dietary modification, physical activity, and exercise recommended to prevent the development of GDM., Frequencies of dietary intake including fruits, vegetables, chicken, and meat consumption were found to have no significant influence on the incidence of GDM compared to control group [Table 1]. OR for consumption of fruits, vegetables, chicken, and meat was 0.93, 1.02, 1.15 (P < 0.05), and 0.931 respectively. A significantly higher number of GDM cases were consuming chicken compared to control group. Frequency of intake of tea and coffee was found to have no significant influence on the incidence of GDM compared to control group [Table 1]. However, the risk for GDM was significantly lowered to 0.836 times in patients consuming tea compared to control, but consumption of coffee insignificantly increase the risk for GDM by 1.126 times. These results are in-line and support the data of Chinese studies., These results also support the view that vegetable pattern dies is associated with decreased risk of GDM; therefore, dietary counseling during pregnancy is very important in regulating blood glucose level. Data collected have shown no difference in incidence of GDM with respect to occupation compared to control. However, significantly (P < 0.05) higher rate of incidence of GDM was recorded in secondary school level educated women 72.85% compared to 63.66% normal control group. Differing from a cross-sectional study carried out in Sweden and a dietary habit-based study. In this study, a maximum number of women with GDM were having secondary school education compared to control. It could be the reason for increased risk of GDM, 1.5 times higher than the control. Physical inactivity has significantly increased the risk for GDM by 3.711 times compared to control group. Walking for more than 30 min/day has significantly reduced the risk by 0.356 times of that control group. Reemphasizing the need of structured moderate physical exercise during pregnancy to decrease the risk of GDM, diminish maternal weight gain, ant improve the safety of mother and the neonate.
One of the important findings of this study is that the use of corticosteroids has shown a significant increase in incidence of GDM. Highest risk for GDM is associated with the use of dexamethasone and other corticosteroids in combinations than normal. Whereas significantly higher risk is associated with the use of hydrocortisone. It is well-known fact that there is an increase in level of cortisone during pregnancy to support metabolic functions of mother and fetus. Therefore, external steroid supplementation has significantly increased the number of GDM cases compared to normal control group. Use of betamethasone followed by dexamethasone and hydrocortisone is recommended as drugs of choice for fetal maturation without extensive study in gestational and pregestational patients. Inconsideration of lack of extensive evidences corticosteroids must be used with caution as they have significantly increased the risk of GDM.
A significant number of GDM cases were having correlation between a prior history of pregnancy complications including history of stillbirth, macrosomic infant, proteinuria, preterm birth, and multiple pregnancies compared to control population. However, duration of existence of gestational problems has no significant influence on incidence of GDM with a mean difference. There are a varied percent and relative risk of developing GDM in patients having a history of pregnancy complications similar to the results obtained in this study., Recent retrospective study carried out in Omani women between 15 and 49 years old states that pregestational diabetes has a higher number of gestational complications than gestational diabetes and their nonmodifiable risk factors are significantly different from non-GDM patients.
| Conclusion|| |
The present study states that the increase in body weight, waist circumference, BMI, and previous history of gestational complications will increase the risk of GDM and increased physical activity, vegetable diet, and consumption of tea will lower the risk of GDM. This study also shows that occupation, level of education, and regional distribution of Omani patients have a very limited role in either increasing or decreasing the risk of GDM. However, the present study data cautions against the use of corticosteroids other than prednisolone due to increased risk of GDM.
Financial support and sponsorship
This study was financially supported by the Research Council, Oman.
Conflicts of interest
There are no conflicts of interest.
| References|| |
Zhu Y, Zhang C. Prevalence of gestational diabetes and risk of progression to type 2 diabetes: A global perspective. Curr Diab Rep 2016;16:7.
Buchanan TA, Xiang AH, Page KA. Gestational diabetes mellitus: Risks and management during and after pregnancy. Nat Rev Endocrinol 2012;8:639–49.
Gasim T. Gestational diabetes mellitus: Maternal and perinatal outcomes in 220 Saudi women. Oman Med J 2012;27:140–4.
Reece EA, Leguizamón G, Wiznitzer A. Gestational diabetes: The need for a common ground. Lancet 2009;373:1789–97.
Petry CJ. Gestational diabetes: Risk factors and recent advances in its genetics and treatment. Br J Nutr 2010;104:775–87.
Nanda S, Savvidou M, Syngelaki A, Akolekar R, Nicolaides KH. Prediction of gestational diabetes mellitus by maternal factors and biomarkers at 11 to 13 weeks. Prenat Diagn 2011;31:135–41.
Garshasbi A, Faghihzadeh S, Naghizadeh MM, Ghavam M. Prevalence and risk factors for gestational diabetes mellitus in Tehran. J Family Reprod Health 2008;2:75–80.
Lim-Uy SW, Cunanan EC, Andag-Silva AA. Prevalence and risk factors of gestational diabetes mellitus at the university of Santo Tomas Hospital. Philipp J Intern Med 2010;48:24–31.
Abdel-Warethi LO, Kumari AS, Haq A, Bakir A, Sainudeen A, Sedaghatian MR et al.
An evaluation of the latest ADA criteria for screening and diagnosing gestational diabetes at a tertiary care hospital in the United Arab Emirates. Int J Diabetes Metab 2006;14:55–60.
Mardi TG, Lutfi MF. Risk factors for gestational diabetes mellitus in Sudanese pregnant women. Int Med Biomed Res 2012;1:79–84.
Barakat MN, Youssef RM, Al-Lawati JA. Pregnancy outcomes of diabetic women: Charting Oman’s progress towards the goals of the Saint Vincent Declaration. Ann Saudi Med 2010;30:265–70.
Ministry of Health, Oman. Diabetes Mellitus Management Guidelines for Primary Health Care. 2nd ed. Muscat: Ministry of Health; 2003. pp. 35–43.
D’Souza MS, Amirtharaj A, Venkatesaperumal R, Isac C, Maroof S. Risk-assessment score for screening diabetes mellitus among Omani adults. SAGE Open Med 2013;1:2050312113508390.
Boutayeb A, Lamlili ME, Boutayeb W, Maamri A, Ziyyat A, Ramdani N. The rise of diabetes prevalence in the Arab region. Open J Epidemiol 2012;2:55–60.
Abu-Heija AT, Al-Bash M, Mathew M. Gestational and pregestational diabetes mellitus in Omani women. Sultan Qaboos Univer Med J 2015;15:445–9.
Musaiger AO, AbdulKhalek N. Nutritional problems among pregnant women in the GCC countries. Bahrain Med Bull 1998;20:95–7.
Dubai Declaration on Diabetes and chronic non-communicable diseases in the Middle East and North Africa region. The MENA Diabetes Leadership Forum; 12-13 December, 2010. Dubai.
Kahr MK, Suter MA, Ballas J, Ramin SM, Monga M, Lee W et al.
Geospatial analysis of food environment demonstrates associations with gestational diabetes. Am J Obstet Gynecol 2016;214:110.e1–9.
Foetal death among Omani women. Community Health and Disease Surveillance Newsletter, Directorate General of Health Affairs, Ministry of Health, Oman 1999;8(2):6–11.
Dode MA, dos Santos IS. Non classical risk factors for gestational diabetes mellitus: A systematic review of the literature. Cad Saude Publica 2009;25 Suppl 3:S341–59.
Shannon A, Wong CK. Risk factors associated with gestational diabetes mellitus. Int J Bioautomation 2010;14:15–26.
Gray RG, Kousta E, McCarthy MI, Godsland IF, Venkatesan S, Anyaoku V et al.
Ethnic variation in the activity of lipid desaturases and their relationships with cardiovascular risk factors in control women and an at-risk group with previous gestational diabetes mellitus: A cross-sectional study. Lipids Health Dis 2013;12:25.
Kirke AB, Evans SF, Walters BN. Gestational diabetes in a rural, regional centre in South Western Australia: Predictors of risk. Rural Remote Health 2014;14:2667.
Hui AL, Back L, Ludwig S, Gardiner P, Sevenhuysen G, Dean HJ et al.
Effects of lifestyle intervention on dietary intake, physical activity level, and gestational weight gain in pregnant women with different pre-pregnancy body mass index in a randomized control trial. BMC Pregnancy Childbirth 2014;14:331.
Liu Z, Ao D, Yang H, Wang Y. Gestational weight gain and risk of gestational diabetes mellitus among Chinese women. Chin Med J (Engl) 2014;127:1255–60.
Bolognani CV, de Sousa Moreira Reis LB, de Souza SS, Dias A, Rudge MV, de Mattos Paranhos Calderon I. Waist circumference in predicting gestational diabetes mellitus. J Matern Fetal Neonatal Med 2014;27:943–8.
Gur EB, Ince O, Turan GA, Karadeniz M, Tatar S, Celik E et al.
Ultrasonographic visceral fat thickness in the first trimester can predict metabolic syndrome and gestational diabetes mellitus. Endocrine 2014;47:478–84.
Xu Q, Gao ZY, Li LM, Wang L, Zhang Q, Teng Y et al.
The association of maternal body composition and dietary intake with the risk of gestational diabetes mellitus during the second trimester in a cohort of Chinese pregnant women. Biomed Environ Sci 2016;29:1–11.
Rasmussen KM, Yatine AL. Weight Gain During Pregnancy: Reexamining the Guidelines. Washington, DC: Institute of Medicine and National Research Council of the National Academies, The National Academies Press; 2009.
Hui A, Back L, Ludwig S, Gardiner P, Sevenhuysen G, Dean H et al.
Lifestyle intervention on diet and exercise reduced excessive gestational weight gain in pregnant women under a randomised controlled trial. BJOG 2012;119:70–7.
He JR, Yuan MY, Chen NN, Lu JH, Hu CY, Mai WB et al.
Maternal dietary patterns and gestational diabetes mellitus: A large prospective cohort study in China. Br J Nutr 2015;113:1292–300.
Li Q, Xiong R, Wang L, Cui J, Shi L, Liu Y et al.
Associations of dietary habits, physical activity and cognitive views with gestational diabetes mellitus among Chinese women. Public Health Nutr 2014;17:1850–7.
Lindqvist M, Persson M, Lindkvist M, Mogren I. No consensus on gestational diabetes mellitus screening regimes in Sweden: Pregnancy outcomes in relation to different screening regimes2011 to 2012, a cross-sectional study. BMC Pregnancy Childbirth 2014;31:185.
Ferranti EP, Narayan KM, Reilly CM, Foster J, McCullough M, Ziegler TR et al.
Dietary self-efficacy predicts AHEI diet quality in women with previous gestational diabetes. Diabetes Educ 2014;40:688–99.
Sanabria-Martínez G, García-Hermoso A, Poyatos-León R, Álvarez-Bueno C, Sánchez-López M, Martínez-Vizcaíno V. Effectiveness of physical activity interventions on preventing gestational diabetes mellitus and excessive maternal weight gain: A meta-analysis. BJOG 2015;122:1167–74.
Krishnaveni GV, Veena SR, Jones A, Srinivasan K, Osmond C, Karat SC et al.
Exposure to maternal gestational diabetes is associated with higher cardiovascular responses to stress in adolescent Indians. J Clin Endocrinol Metab 2015;100:986–93.
Miracle X, Di Renzo GC, Stark A, Fanaroff A, Carbonell-Estrany X, Saling E; Coordinators of World Associatin of Perinatal Medicine Prematurity Working Group. Guideline for the use of antenatal corticosteroids for fetal maturation. J Perinat Med 2008;36:191–6.
Bas-Lando M, Srebnik N, Farkash R, Ioscovich A, Samueloff A, Grisaru-Granovsky S. Elective induction of labor in women with gestational diabetes mellitus: An intervention that modifies the risk of cesarean section. Arch Gynecol Obstet 2014;290:905–12.
Pintaudi B, Di Vieste G, Corrado F, Lucisano G, Pellegrini F, Giunta L et al.
Improvement of selective screening strategy for gestational diabetes through a more accurate definition of high-risk groups. Eur J Endocrinol 2013;170:87–93.
Chitme HR, Al Shibli SA, Al-Shamiry RM. Risk factors and plasma glucose profile of gestational diabetes in Omani women. Oman Med J 2016;31:370–7.
[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2], [Table 3], [Table 4]