Database Open Access

Visceral adipose tissue measurements during pregnancy

Alexandre da Silva Rocha Lisia von Diemen Daniela Kretzer Salete Matos Juliana Rombaldi Bernardi José Antônio Magalhães

Published: March 23, 2020. Version: 1.0.0


When using this resource, please cite: (show more options)
Rocha, A. d. S., von Diemen, L., Kretzer, D., Matos, S., Rombaldi Bernardi, J., & Magalhães, J. A. (2020). Visceral adipose tissue measurements during pregnancy (version 1.0.0). PhysioNet. https://doi.org/10.13026/p729-7p53.

Please include the standard citation for PhysioNet: (show more options)
Goldberger, A., Amaral, L., Glass, L., Hausdorff, J., Ivanov, P. C., Mark, R., ... & Stanley, H. E. (2000). PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation [Online]. 101 (23), pp. e215–e220.

Abstract

This database is from a cohort study of pregnant women up to 20 weeks of pregnancy and followed until delivery. Measurement of maternal visceral adipose tissue (VAT) was performed during routine obstetric ultrasound. At this time, the biometric evaluation was also performed, and information obtained from prenatal care. Gestational outcomes, including gestational diabetes mellitus (GDM), were obtained through evaluating the patients' medical records at the hospitals where they took place. The data was collected as part of a study that sought to evaluate if maternal VAT could predict GDM at time of delivery. Variables included in this dataset are maternal age, previous DM, blood pressure (in the same day of VAT measurement), VAT (in the periumbilical region), gestational age at time of inclusion, number of pregnancies, level of first fasting glucose, pre-gestational body mass index (BMI). Also, the pregnancy outcomes: gestational age at birth, type of delivery (vaginal or caesarean section), child birth weight and the diagnosis of GDM.


Background

There is a large body of evidence showing that visceral fat is more important in predicting metabolic risk than body mass index (BMI) in adults and the relationship seems to be higher in women [1,2]. However, due to the difficulties of using traditional methods for central fat assessment (waist-hip ratio and abdominal tomography) in pregnancy and the high costs of magnetic resonance imaging, the use of ultrasound for visceral adipose tissue (VAT) evaluation has shown promise. VAT measurements have recently been associated with GDM [3–6], impaired fasting glucose [3], and insulin resistance [7,8] even after controlling for BMI. However, these studies have typically evaluated eutrophic, overweight and obese pregnant women together.


Methods

This study sample consisted of a cohort of 154 women approached from October 2016 to December 2017 at the Ultrasound Department of the Murialdo Teaching Health Center, a clinic that provides fetal medicine services to users of the Unified Health System in the city of Porto Alegre, Rio Grande do Sul, Brazil. Participants were followed until delivery at five Unified Health System hospitals in the city. Of the 154 women selected initially, 21 (13%) were lost to follow-up, resulting in a final sample of 133 women. The inclusion criteria were singleton pregnancy and gestational age ≤20 weeks. The exclusion criteria was pre-existing type 1 or 2 diabetes mellitus.

Maternal visceral adipose tissue (VAT) measurement: VAT was assessed with ultrasound electronic calipers, placed from the aortic arch to the linea alba, 2 cm above the maternal umbilical scar with the probe in the sagittal position as described by Armellini et al. [9]. The mean of two measurements, one obtained during maternal inspiration and one during expiration, was used to estimate VAT.

Anthropometry: The first measurement of maternal weight before the 12th week of pregnancy and the maternal height measured at the time of study inclusion were used to calculate the pre-gravid BMI. If weight data before 12 weeks of pregnancy were missing, pre-gravid maternal weight records were used to calculate the pre-gravid BMI.

Clinical and laboratory data: Routine outpatient prenatal records were used to assess fasting glucose and/or GTT, parity, and ethnic characteristics.

Gestational outcomes: Hospital charts were reviewed to identify GDM diagnosis, treatment of GDM, results of GTT and glucose challenge test (GCT), newborn weight, need for cesarean section, and other maternal, fetal, and newborn conditions. GDM was determined if an abnormal GTT or GCT result, a fasting glucose level above the International Association of Diabetes and Pregnancy Study Groups (IADSPG) limit, or a diagnosis of GDM was described in medical records.

The study was submitted to the Research Ethics Committee of the municipality of Porto Alegre and received general approval number 2.132.090.


Data Description

Data related to intake (first 20 weeks of pregnancy) and outcomes from delivery (gestational diabetes mellitus, type of delivery, newborn weight and gestational age) are recorded in `visceral_fat.csv`. Variables used in the dataset are described below.

  1. Number: Unique ID for the case.
  2. Age (years): Age in years.
  3. Ethnicity: Ethnicity (0 = white; 1 = not white).
  4. Diabetes mellitus: Previous diabetes mellitus (0 = no; 1 = yes).
  5. Mean diastolic BP: Mean diastolic blood pressure in mmHg.
  6. Mean systolic BP: Mean systolic blood pressure in mmHg.
  7. Central Armellini fat (mm): Maternal visceral adipose tissue measurement in mm.
  8. Current Gestational age: Age (weeks of pregnancy, days of pregnancy).
  9. Pregnancies (number): Number of pregnancies.
  10. First fasting glucose (mg/dl): First measured fasting glucose.
  11. BMI pregestational (kg/m): Pregestational body mass index.
  12. Gestational age at birth: Age (weeks of pregnancy, days of pregnancy).
  13. Type of delivery: 0 = vaginal birth; 1 = cesarian section.
  14. Child birth weight (g): Birthweight in grams.
  15. Gestational DM (current gestational diabetes): 0 = no; 1 = yes.

Missing data is indicated by an empty cell.


Usage Notes

The authors emphasize that the study associated with this data was set up to investigate maternal visceral fat (VAT) ultrasound measurements as a predictor of gestational diabetes mellitus (GDM) in obese and non-obese pregnant women. The investigators performed additional assessments of preeclampsia, gestational hypertension, caesarean section, prematurity, labor distress, fetal trauma and macrosomia, among others, but this data is not available as part of the public dataset.

There are several limitations that should be noted. First, the diagnosis of gestational diabetes mellitus (GDM) was performed by routine prenatal care, without the participation of the research team in laboratories that integrate the Brazilian public health system (this fact may impose gauging bias). Second, the authors attributed a positive result to DMG among cases of abnormal glucose challenge test beside at other two results: abnormal fasting glucose or medical records with DMG during labor and delivery. Third, the pre-gestational BMI was calculated from the maternal height during the inclusion process, together with the reported pre-gestational weight (this fact may impose recall bias).


Release Notes

The released version comprises the first upload of data by the contributors. It is important to highlight that the available data comprises information about pregnancy, maternal nutrition and conditions at birth. 


Acknowledgements

Financial support was provided by the Hospital de Clínicas de Porto Alegre Research and Event Incentive Fund (Fundo de Incentivo à Pesquisa e Eventos, FIPE). Additional support was provided by the Porto Alegre municipal government (ultrasound equipment, research facilities) and Federal University of Rio Grande do Sul (technical and scientific support). We thank Prof. Lisia von Diemen for her indispensable assistance with statistics.


Conflicts of Interest

The authors declare that they have no competing financial interests


References

  1. Abraham TM, Pedley A, Massaro JM, Hoffmann U, Fox CS. Association between visceral and subcutaneous adipose depots and incident cardiovascular disease risk factors. Circulation [Internet]. 2015 Oct 27 [cited 2018 Jun 1];132(17):1639–47. Available from: http://circ.ahajournals.org/lookup/doi/10.1161/CIRCULATIONAHA.114.015000
  2. De Souza LR, Berger H, Retnakaran R, Maguire JL, Nathens AB, Connelly PW, et al. First-Trimester Maternal Abdominal Adiposity Predicts Dysglycemia and Gestational Diabetes Mellitus in Midpregnancy. Diabetes Care [Internet]. 2016 Jan [cited 2017 Dec 29];39(1):61–4. Available from: http://care.diabetesjournals.org/lookup/doi/10.2337/dc15-2027
  3. Martin AM, Berger H, Nisenbaum R, Lausman AY, MacGarvie S, Crerar C, et al. Abdominal visceral adiposity in the first trimester predicts glucose intolerance in later pregnancy. Diabetes Care. 2009;32(7):1308–10.
  4. D’Ambrosi F, Crovetto F, Colosi E, Fabietti I, Carbone F, Tassis B, et al. Maternal Subcutaneous and Visceral Adipose Ultrasound Thickness in Women with Gestational Diabetes Mellitus at 24-28 Weeks’ Gestation. Fetal Diagn Ther [Internet]. 2017 Jun 17 [cited 2017 Dec 29]; Available from: https://www.karger.com/?doi=10.1159/000475988
  5. 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(2):478–84.
  6. Bartha JL, Marín-Segura P, González-González NL, Wagner F, Aguilar-Diosdado M, Hervias-Vivancos B. Ultrasound evaluation of visceral fat and metabolic risk factors during early pregnancy. Obesity (Silver Spring) [Internet]. 2007;15(9):2233–9. Available from: http://www.ncbi.nlm.nih.gov/pubmed/17890491
  7. De Souza LR, Kogan E, Berger H, Alves JG, Lebovic G, Retnakaran R, et al. Abdominal adiposity and insulin resistance in early pregnancy. J Obs Gynaecol Can [Internet]. 2014;36(11):969–75. Available from: http://dx.doi.org/10.1016/S1701-2163(15)30409-6
  8. Fox CS, Massaro JM, Hoffmann U, Pou KM, Maurovich-Horvat P, Liu CY, et al. Abdominal visceral and subcutaneous adipose tissue compartments: association with metabolic risk factors in the Framingham Heart Study. Circulation [Internet]. 2007;116(1):39–48. Available from: http://www.ncbi.nlm.nih.gov/pubmed/17576866
  9. Armellini F, Zamboni M, Rigo L, Bergamo-Andreis IA, Robbi R, De Marchi M, et al. Sonography detection of small intra-abdominal fat variations. Int J Obes. 1991 Dec;15(12):847–52.

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DOI (version 1.0.0):
https://doi.org/10.13026/p729-7p53

DOI (latest version):
https://doi.org/10.13026/9q68-n048

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