Table 5. Details of studies included in the systematic review.
| ID | References | Study design | Sample size | Geographic region | Age(year) | Diagnostic criteria of GDM | Anthropometric indices | applying Time | Accompanying factors | Results | QS |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Jitngamsujarit et al.(2021) [43] | Cross-sectional | 212 | Thailand | 27.1 ± 6.7 | WHO | WC≥82: (OR 7.85, 95%CI 1.80–34.32 | <18 | • maternal age • history of diabetes in family • history of giving birth to a fetal anomaly • History of giving birth to an infant ≥ 4,000 gm |
Significant | 8 |
| 2 | Saif Elnasr et al.2021 [44] | Cohort | 83 | Egypt | 26.8 | ADA | VAT: 5.85 ± 0.47 cm SAT:1.80±0.57 cm |
11–14 | BMI | VAT depth ranged from 1.4 to 9.1 cm, with a mean of 3.9 ± 1.6 cm is associated with GDM. | 8 |
| 3 | Cremona et al.2021 [45] | Cohort | 187 | Ireland | 18–50 | IADPSG | • abdominal SAT:1.99 (1.64–2.31) mm • abdominal VAT:1.41 (1.11–1.65) mm • FMP: 45.6 (39.2–49.0) • MUAC:32.9 (30.1–36.4) cm • WC = 90.3 (85.9–96.2) cm • HC: 108.6 (99.9–111.6) cm total SFT:226.4 (184.1–244.7) mm |
10–16 | • BMI • Parity >3 • Family Hx diabetes Age >40 • Smoking • High risk ethnicity • Previous perinatal death • Glucosuria • Previous baby ≥4.0 kg • Previous macrosomia (≥4.5 kg) |
Significant for VAT, SAT, WC, HC and total SFT | 7 |
| 4 | Barforoush et al.2021 [46] | cohort | 372 | Iran | 28.1 ±4.4 | ADA | NC: 35.1 ±2.7 cm | 14–16 | Age Gravidity Family -history of type 2 diabetes Pre-pregnancy weight Height |
NC ≥34.3 cm can be deemed as a predictor of GDM | 8 |
| 5 | Aydin et al.2021 [41] | Cohort | 142 | Turkey | 31.24±5.11 | IADPSG | • Intraperitoneal fat thickness:51.59 ± 22.49 mm • SAT: 19.79 ± 12.52 mm • WC:95.25±15 cm HC:115.38±15.41 cm WHR: 0.82±0.06 cm Perirenal fat thickness: 11.77±8.79 mm, SFTmax: 19.79±12.52 mm |
11–14 | • Pre-pregnancy BMI • BMI • smoking • history of DM in the first degree relatives • GDM during previous pregnancy |
Significant for all except Perirenal fat thickness | 7 |
| 6 | Zhang et al.2020 [47] | Cohort | 22,223 | China | 28.09 ± 4.48 | IADPSG | FM: 17.95 ± 5.65 kg, 1.085 (1.079–1.091) FFM: 40.56 ± 4.92 kg, 1.080 (1.100–1.115) Fat mass percentage: 30.09 ± 5.69%, 1.057 (1.052–1.063) MM:21.87 ± 2.96 kg, 1.114 (1.106–1.121) VF level:8.48 ± 0.56, 2.604 (2.459–2.758) Lean trunk mass: 18.32 ± 2.47 kg, 1.226 (1.209–1.243) |
<17 | • BMI • Total body water • Proteins • Bone minerals • Basal metabolic rate |
Significant | 7 |
| 7 | Rocha et al.2020 [48] | Cohort | 133 | Brazil | 26±6.2 | IADSPG | VAT: 55.4 ±11.4 mm | ≤20 | BMI | Significant | 9 |
| 8 | Alves et al.2020 [28] | cohort | 518 | Brazil | 26.25±5.8 | IADPSG | VAT: 5.44 ±1.27mm | 14 | • age • Pre-pregnancy BMI |
significant | 8 |
| 9 | Hancerliogullari et al.2020 [29] | cohort | 525 | Turkey | 27 (18–44) | Carpenter and Coustan | NC:37.14 ± 3.34 cm WC: 91.78 ± 11.41 cm |
11–14 | • Age • Parity • BMI |
Significant | 8 |
| 10 | Liu et al.2020 [30] | cohort | 1318 | China | 32.6±5.1 | IADPSG | FMI: 7.14±2.26 SMMP: 40.0±8.3 FMP: 30.1±5.8 |
13 | • Age • pre-pregnancy BMI • Pre-pregnancy weight |
Significant | 8 |
| 11 | Thaware et al.2019 [49] | Cohort | 80 | UK | 18–40 | IADPSG /WHO | VAT: 4.36±1.31 cm SAT: 2.24±1.01 cm |
9–18 | • Early pregnancy BMI ≥30 kg/m2 • Family history of diabetes in first-degree relative |
Significant for VAT of ≥ 4.27 cm (p = 0.03) | 8 |
| 12 | Takmaz et al.2019 [50] | cohort | 261 | Turkey | 30.57±5.78 | IADPSG | WC: 103.91±14.13 cm 8.36(0.74–0.84) |
20–24 | • Age • Parity • Weight gain • PPBMI • BMI |
Significant | 7 |
| 13 | Budak et al.2019 [42] | Case control | 100 | Turkey | 33.5 (27–37) | Carpenter and Coustan | SFT: 21.1 (16.6–26.4)**mm | 24–28 | • Age • Parity • Weight gain |
Significant | 9 |
| 14 | Kawanabe et al.2019 [51] | Cohort | 96 | Japan | 34.4 ± 4.8 | IADPSG | ASM: 17.0 ± 2.1 kg FM: 18.8 ± 8.2 kg ASM/FM ratio: 1.02 ± 0.34 |
16–30 | • ISI • Age • HbA1c • pre-pregnancy BMI • Family history of diabetes |
Significant | 8 |
| 15 | Marshall et al.2019 [52] | cohort | 1,775,984 | California | 18–40 | ICD-9 | MH: 1.68 (1.58–1.66) m | nine months prior to birth | • Age • BMI |
Taller women were less likely to have GDM 0.81 (0.80, 0.82)*. | 8 |
| 16 | Ulubasoglu et al.2019 [53] | cohort | 148 | Turkey | 28.4±3.8 | ADA | WC = 87.7 ±13.6 cm | 11–14 | • Total triglycerides • BMI |
Significant | 8 |
| 17 | Wang et al.2019 [54] | Case-control | 2698 | China | 30.95± 4.01 | IADPSG | • FFMP: 68.45±4.81 • FMP: 31.55±4.81 FMI: 7.00±1.81 WHR: 0.86±0.04 MUAC: 27.64±2.30 cm FM/FFM ratio: 0.47 ±0.14 |
13–20 | • Age • PPBMI |
Significant | 7 |
| 18 | Zhu et al.2019 [31] | Cohort | 1750 | California | 18–45 | Carpenter and Coustan | WHR = 0.91 ±0.06 WC = 102.4 ±18.5 cm |
10–13 | • Smoking • Family history of diabetes • Previous GDM • Preexisting hypertension • Physical inactivity in early pregnancy |
Significant | 7 |
| 19 | Nombo et al.2018 [55] | Cross sectional | 609 | Tanzania | 27.5 ± 5.0 | WHO | MUAC = 27.3± 3.8 cm | 20–38 | • Previous stillbirth • Family history of type 2 diabetes • Diet habits |
Significant | 9 |
| 20 | Anafcheh et al.2018 [56] | Case control | 195 | Iran | 32.35± 0.68 | WHO | H = 159.72±6.72 | <24–28 | • Blood group • GWG • Age • History of stillbirth • History of GDM • History of type 2 diabetes in first-degree relatives • Birth -History of a baby weighing≥ 4 kg • History of a birth with a congenital anomaly • History of PCO |
NS | 7 |
| 21 | Balani et al.2018 [57] | cohort | 302 | UK | 31 | WHO |
PBF VFM<210 WHR |
15 | Age BMI • History of PCOs • Family history of diabetes, • History of hypertension and Previous macrosomia |
Significant | 7 |
| 22 | Bourdages et al.2018 [58] | cohort | 1048 | Canada | 28.9 ± 4.1 | IADPSG | • SAT: 0.66 (0.59–0.73) • TAT:0.68 (0.61–0.76) • VAT: 0.65 (0.58–0.73)*** |
11–14 | • Age≥35 • BMI≥31.6 |
Significant | 8 |
| 23 | Kansu-Celik et al.2018 [40] | Cross sectional | 223 | Turkey | 27.46± 5.9 | Carpenter and Coustan | • SAT: 19 (11–28) mm • WC: 95 (72–111) cm • WHR: 0.89 ± 0.59 |
24–28 | • BMI |
Significant | 9 |
| 24 | KhushBakht et al. 2018 [59] | Cross sectional | 90 | Pakistan | 30.8 ± 3.2 | ADA | • NC: 36.1 ± 2.8 cm • H: 1.61 ± 0.03 m • WC: 104.2 ± 9.0 cm |
16 | • BMI • Fasting lipid profile • Serum albumin • Uric acid • Age Gravidity |
cut-off value of neck circumference for predicting GDM was 35.70 cm with a sensitivity of 51.4% and specificity of 81.2%. |
9 |
| 25 | Nassr et al.2018 [60] | cohort | 389 | USA | 29.7±4.67 | ACOG | Pre-peritoneal fat: 12 (9–16)**** mm SFT: 11 (8–14) mm BFI: 0.78 (0.42 - 1.26) |
18–24 | • Age>30 • Parity • History of GDM • History of bariatric surgery • Current gestational hypertension or preeclampsia |
Significant | 8 |
| 26 | D’Ambrosi et al.2017 [61] | Case control | 168 | Italy | 34.5±5.1 | IADPSG | SAT: 107±4.8 mm VAT: 10.1±3.0 mm |
24–28 | • Age • BMI • Family history of diabetes |
Significant | 8 |
| 27 | Han et al.2017 [62] | Cohort | 17803 | China | 28.5±2.8 | IADPSG | WC: 82.8±9.7 cm | 4–12 | • BP • BMI |
Significant | 7 |
| 28 | He et al. 2017 [63] | Case control | 255 | China | 29.1 ±3.7 | ADA | NC: 35.20 ±2.56 cm WC: 103.16±8.00 cm |
16 | • Age • Gravidity • HbA1c • Lipid profile • BMI |
Significant | 7 |
| 29 | Li et al.2017 [64] | cohort | 371 | china | 31.0±3.0 | IADPSG | NC: 34.3±1.5 cm | 11–13 | • Age • PPBMI • Lipid profile |
Significant | 7 |
| 30 | Yang et al.2017 [65] | cohort | 333 | Korea | 32±3.9 | National Diabetes Data Group | SFT:2.7±0.6 cm |
10–13 | • Age • PPBMI • GWG |
Significant | 7 |
| 31 | Alptekin et al.2016 [66] |
Cohort | 227 | Turkey | 28.8 ± 4.8 | Carpenter and Coustan | WC: 89.7 ± 11.9 cm HC: 105.8 ± 14.2 cm WHR: 0.84 ± 0.04 |
7–12 | • HOMA-IR • BMI WGDP |
Significant | 8 |
| 32 | Basraon et al.2016 [67] | Cohort | 2300 | USA | 23.3±4.9 | Guidelines of each clinical center | WHR: 0.88 ± 0.07 |
9–16 | • IR • BMI • Ethnicity |
Significant | 8 |
| 33 | White et al.2016 [68] | Cohort | 1303 | UK | 32.0 ±4.9 | IADPSG | • NC: 37.4 ±2.5 cm • WC: 110 (103–116) cm • MUAC:37 (35–40) cm • HC: 123 (116–130) cm • WHR: 0.89 ±0.07 |
15–18 | • Age • BP • Ethnicity • Parity • IR • Previous GDM • HgbA1C -Adiponectin • Sex hormone binding globulin • Triglycerides • PCOs • Smoking |
Significant | 8 |
| 34 | De Souza et al.2015 [69] | Cohort | 485 | Canada | 32.9 ±4.8 | IADPSG | • SAT: 1.9± 0.80 cm • VAT: 4.1±1.7 cm • TAT: 5.9±2.1 cm |
11–14 | • AgeSi • BMI |
Significant for TAT & VAT | |
| 35 | Kennedy et al.2015 [70] | Cohort | 1350 | Canada | 29.3 ± 5.1 | NR | • SAT1: 21.2 mm (6.9– • 73.9) SAT2: 20.3 mm (7.5–68.0) |
11–14 (SAT1) 18–22 (SAT2) |
• BMI | Significant | 7 |
| 36 | Sina et al.2015 [71] | Case control | 131 | Australia | 23.7 ±5.5 | ICD-9 and ICD -10 | ▪ WC:90.3 ±16.4 cm ▪ HC: 98.3 ±16.3 cm ▪ WHR: 0.92 ±0.05 |
- | • BMI | Significant for WC and HC | 9 |
| 37 | Balani et al.2014 [72] | Case control | 302 | UK | 32.1±5.5 | WHO | ▪ WHR: 1.02±0.07 ▪ TPBF: 49.8±3.5 ▪ VAT: 199.2±40.5 |
14–17 | • BMI | Significant for BMI, WHR, VFM | 7 |
| 38 | Bolognani et al.2014 [73] | Cross sectional | 240 | Brazil | 17–40 | WHO | WC: 93.548±8.873 cm | 20–24 | • PPBMI • BMI • GWG |
Significant | 8 |
| 39 | Gur et al. 2014 [74] | Cohort | 94 | Turkey | 43.4 | WHO | WC:65.3 cm minimum subcutaneous fat (Smin): 66.7 mm maximum pre-peritoneal visceral fat (Vmax):67.2 mm |
4–14 | • BMI • FBG • Metabolic • syndrome • Lipid profile • BP • HOMA-IR Smoking |
Significant | 8 |
| 40 | Mameghani et al.2013 [75] | Cohort | 1140 | Iran | 17–40 | WHO | WC: 81.84 ± 0.35 cm | <12 | • BMI | Significant | 8 |
| 41 | Suresh et al.2012 [76] | Cohort | 1200 | Australia | 17–45 | The Royal Australian and New Zealand College of Obstetricians and Gynaecologists. C-Obs guideline | -SAT: 18.2 mm (range 6.3–50.9 mm) | 18–22 | • BMI | Significant | 8 |
ICD9: International Classification of Diseases, 9th Revision-Clinical Modification, H: height, WGDP: weight gained during pregnancy, HOMA-IR: homeostasis model assessment insulin resistance, WHR: Waist/Hip Ratio, QUICKI: quantitative insulin sensitivity check index, VAD: Visceral Adipose Tissue Depth, BMI: Body Mass Index, VFM: visceral fat mass, PBF: percentage body fat, IR: insulin resistance, WC: waist circumference, SAT: subcutaneous tissues thickness, TAT: total adipose tissues thickness, VAT: visceral tissues thickness, ASFT: abdominal subcutaneous fat thickness, FBG: fasting blood glucose, NC: Neck circumference, ISI: insulin sensitivity index, ASM: appendicular skeletal muscle mass, FM: fat mass, HbA1c: glycosylated hemoglobin A1c,SFT: subcutaneous fat thickness, IADPSG: International Association of Diabetes and Pregnancy Study Groups, FMP: fat mass percentage, SMMP: skeletal muscle mass percentage, FMI: Fat mass index, BFI: Body Fat Index = (pre-peritoneal fat x subcutaneous fat/height), FFM: fat free mass, MM: muscular mass, PP: Pre pregnancy, PPBMI: Pre pregnancy BMI, ADA: American Diabetes Association, WHO: World health Organization, ACOG: American College of Obstetricians and Gynecologists, AC: arm circumference, NS: Not Significant
*: OR
**: median (IQR)
***: AUC (CI)
****: median (max-min)