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Chung and Moon: Simple Screening Using Ultrasonography for Prediction of Gestational Diabetes Mellitus
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Obesity and Metabolic Syndrome

Diabetes & Metabolism Journal 2017; 41(6): 438-439.

Published online: 19 December 2017

DOI: https://doi.org/10.4093/dmj.2017.41.6.438

Simple Screening Using Ultrasonography for Prediction of Gestational Diabetes Mellitus

Seung Min Chung, Jun Sung Moon

Department of Internal Medicine, Yeungnam University College of Medicine, Daegu, Korea.

Corresponding author: Jun Sung Moon. Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeungnam University College of Medicine, 170 Hyeonchung-ro, Nam-gu, Daegu 42415, Korea. mjs7912@yu.ac.kr

Copyright © 2017 Korean Diabetes Association

Korean Diabetes Association

(open-access):

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Gestational diabetes mellitus (GDM) is a disease status of glucose intolerance that is first recognized during pregnancy. The ongoing epidemic of obesity has led to increased incidence of GDM and type 2 diabetes mellitus in women of childbearing age [1]. As maternal obesity and diabetes increases the risk of metabolic consequences in offspring [2], the prediction and treatment of GDM is essential. It is well-known that Asian women are at a high risk of GDM [3], and genetic factors related to pancreatic β-cell function rather than insulin resistance contribute to the development of GDM [4]. Koo et al. [5] reported the recent prevalence of GDM in Korea using data from nationwide health insurance and claimed that it is at about 7.5 %, and that the rate was steadily increasing (5.7% in 2009 vs. 9.5% in 2011). In addition, they reaffirmed the gestational age as a major risk factor of GDM (age <30 vs. age ≥30, 6.5% vs. 11.3% in 2011). Since marriage and pregnancy are being increasingly delayed in Korea, GDM screening is becoming more important.
The current screening test of GDM are performed at 24 to 28 weeks of gestation; 75-g oral glucose tolerance test (OGTT) or 50-g (non-fasting) screen followed by a 100-g OGTT for those who screen positive (Table 1) [1]. However, there is no official screening test to predict the occurrence of GDM before 24 weeks of gestation. In non-Asian populations, pre-pregnancy body mass index (BMI) is the most significant risk factor for GDM. On the other hand, in Korea, the contribution of pre-pregnancy BMI is low because of the low population fraction of GDM with BMI >25 kg/m2 [6]. Sommer et al. [7] reported that the risk of GDM increases when there is a large amount of subcutaneous fat during early pregnancy in South Asian population. In addition, Kennedy et al. [8] and Suresh et al. [9] revealed that abdominal subcutaneous fat thickness (ASFT) measurement was better for predicting adverse pregnancy outcome than pre-pregnancy BMI.
Yang et al. [10] measured ASFT at 1st trimester and performed 2-step OGTT at 2nd trimester in about 300 pregnant women. The authors found that ASFT is highly correlated with the risk of GDM than well-established risk factors such as age and BMI, and suggested a cut-off value to discriminate the high-risk groups. This could be helpful to physicians because ASFT can be easily obtained during routine obstetric screening and it is cost-effective. Furthermore, due to the limitation of choice of imaging during pregnancy, the proposed test is expected to be a preferable option for screening.
However, some questions remain about the role of subcutaneous fat in GDM. Although recent studies suggested subcutaneous adipose tissue as a surrogate of insulin resistance [1112], visceral adipose tissue has traditionally been regarded as a major cause of insulin resistance development. Visceral adipocytes are more metabolically active, lipolysis sensitive, and insulin-resistant than subcutaneous adipocytes [13]. Visceral fat thickness measurement is expected to be limited because of uterus and fetus, but it might be a more reliable indicator than ASFT measurement. In addition, further studies are warranted to determine the effect of ASFT measurement on progression from GDM to type 2 diabetes mellitus after childbirth.

Figures and Tables

Table 1

Current recommendation for screening of gestational diabetes mellitus by Korean Diabetes Association

dmj-41-438-i001
Screening test
1. All mothers should be tested for overt diabetes at their fi st prenatal visit by fasting plasma glucose, random plasma glucose, or A1C [A].
2. Gestational diabetes mellitus (GDM) can be diagnosed by either of two strategies.
 2-1. Conduct a 2-hour 75-g OGTT at 24 to 28 weeks of gestation in pregnant women not previously known to have diabetes or GDM (one-step approach) [B].
 2-2. When using “two-step approach,” conduct a 1-hour 50-g glucose loading test at 24 to 28 weeks of gestation in pregnant women not previously known to have diabetes or GDM. If the plasma glucose level measured 1-hour after the load is ≥140 mg/dL (or ≥130 mg/dL for mothers at high risk), proceed to a 100-g OGTT [E].

Adapted from Korean Diabetes Association [1].

A1C, glycosylated hemoglobin; OGTT, oral glucose tolerance test.

ACKNOWLEDGMENTS

This work was supported by Basic Science Research Program though the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2017R1C1B1003429).

Notes

CONFLICTS OF INTEREST No potential conflict of interest relevant to this article was reported.

References

1. Korean Diabetes Association. 2015 Treatment guidelines for diabetes. 5th ed. Seoul: Korean Diabetes Association;2015. p. 15.
2. Dabelea D, Crume T. Maternal environment and the transgenerational cycle of obesity and diabetes. Diabetes. 2011; 60:1849–1855.
3. Ferrara A, Kahn HS, Quesenberry CP, Riley C, Hedderson MM. An increase in the incidence of gestational diabetes mellitus: Northern California, 1991-2000. Obstet Gynecol. 2004; 103:526–533.
4. Kwak SH, Kim SH, Cho YM, Go MJ, Cho YS, Choi SH, Moon MK, Jung HS, Shin HD, Kang HM, Cho NH, Lee IK, Kim SY, Han BG, Jang HC, Park KS. A genome-wide association study of gestational diabetes mellitus in Korean women. Diabetes. 2012; 61:531–541.
5. Koo BK, Lee JH, Kim J, Jang EJ, Lee CH. Prevalence of gestational diabetes mellitus in Korea: a National Health Insurance Database Study. PLoS One. 2016; 11:e0153107.
6. Kim C. Gestational diabetes mellitus in Korean women: similarities and differences from other racial/ethnic groups. Diabetes Metab J. 2014; 38:1–12.
7. Sommer C, Jenum AK, Waage CW, Morkrid K, Sletner L, Birkeland KI. Ethnic differences in BMI, subcutaneous fat, and serum leptin levels during and after pregnancy and risk of gestational diabetes. Eur J Endocrinol. 2015; 172:649–656.
8. Kennedy NJ, Peek MJ, Quinton AE, Lanzarone V, Martin A, Benzie R, Nanan R. Maternal abdominal subcutaneous fat thickness as a predictor for adverse pregnancy outcome: a longitudinal cohort study. BJOG. 2016; 123:225–232.
9. Suresh A, Liu A, Poulton A, Quinton A, Amer Z, Mongelli M, Martin A, Benzie R, Peek M, Nanan R. Comparison of maternal abdominal subcutaneous fat thickness and body mass index as markers for pregnancy outcomes: a stratified cohort study. Aust N Z J Obstet Gynaecol. 2012; 52:420–426.
10. Yang SH, Kim C, An HS, An H, Lee JS. Prediction of gestational diabetes mellitus in pregnant Korean women based on abdominal subcutaneous fat thickness as measured by ultrasonography. Diabetes Metab J. 2017; 41:486–491.
11. Patel P, Abate N. Role of subcutaneous adipose tissue in the pathogenesis of insulin resistance. J Obes. 2013; 2013:489187.
12. Kelly AS, Dengel DR, Hodges J, Zhang L, Moran A, Chow L, Sinaiko AR, Steinberger J. The relative contributions of the abdominal visceral and subcutaneous fat depots to cardiometabolic risk in youth. Clin Obes. 2014; 4:101–107.
13. Ibrahim MM. Subcutaneous and visceral adipose tissue: structural and functional differences. Obes Rev. 2010; 11:11–18.
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ORCID iDs

Jun Sung Moon
https://orcid.org/0000-0003-1569-3068

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