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Background/Objectives <p>Prenatal visceral (VAT) and total (TAT) adipose tissue are associated with gestational diabetes and preeclampsia risk, yet cannot be routinely assessed in clinical or epidemiologic settings. Although anthropometric measures reflect adiposity in non-pregnant individuals, their utility in early pregnancy remains unclear. We examined associations between anthropometrics and TAT and VAT in the early second trimester and evaluated differences by prepregnancy BMI.</p> Subjects/Methods <p>Among pregnant women (<i>n</i> = 61) in the Mother and Infant NuTrition (MINT) cohort, TAT and VAT were assessed via whole-body MRI at 15-weeks gestation. Anthropometrics included waist (WC), hip (HC), mid-upper arm (MUAC), calf (CC), thigh (TC), and skinfolds (SF) for iliac crest, subscapular, thigh, and triceps. Linear regression evaluated predictors of TAT and VAT by BMI category.</p> Results <p>TAT demonstrated strong positive correlations with BMI, WC, HC, MUAC, and TC (<i>r</i> = 0.76–0.92) while VAT demonstrated moderate positive correlations with BMI, MUAC, HC (<i>r</i> = 0.48–0.58), and strongest with WC (<i>r</i> = 0.60). The healthy BMI (<i>n</i> = 36) TAT prediction model included MUAC, HC, and iliac SF (R<sup>2</sup> = 0.86), and VAT model included MUAC and iliac SF (R<sup>2</sup> = 0.60). The overweight and obesity (<i>n</i> = 25) TAT prediction model (R<sup>2</sup> = 0.93) included WC and HC and the VAT model (R<sup>2</sup> = 0.79) included HC and subscapular SF.</p> Conclusions <p>Anthropometric measures associated with prenatal adiposity differed by prepregnancy BMI. The TAT prediction model showed an acceptable R<sup>2</sup> and included HC, MUAC, and iliac SF for healthy BMI, and WC and HC for overweight or obesity. Incorporating comprehensive anthropometrics into prenatal research and clinical care may improve risk identification and understanding of prenatal adiposity.</p>

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Prenatal adipose tissue estimation using early second trimester anthropometry

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年8月5日

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  • Marcela R. Abrego,
  • Sara Dube,
  • Daniel A. Powers,
  • Jeffrey Luci,
  • Isaiah Janumala,
  • Jack Virostko,
  • Adrienne N. Dula,
  • Amy R. Nichols,
  • Rachel R. Rickman,
  • Saralyn F. Foster,
  • Lorie M. Harper,
  • Dana Dabelea,
  • Alison G. Cahill,
  • Elizabeth M. Widen

摘要

Background/Objectives

Prenatal visceral (VAT) and total (TAT) adipose tissue are associated with gestational diabetes and preeclampsia risk, yet cannot be routinely assessed in clinical or epidemiologic settings. Although anthropometric measures reflect adiposity in non-pregnant individuals, their utility in early pregnancy remains unclear. We examined associations between anthropometrics and TAT and VAT in the early second trimester and evaluated differences by prepregnancy BMI.

Subjects/Methods

Among pregnant women (n = 61) in the Mother and Infant NuTrition (MINT) cohort, TAT and VAT were assessed via whole-body MRI at 15-weeks gestation. Anthropometrics included waist (WC), hip (HC), mid-upper arm (MUAC), calf (CC), thigh (TC), and skinfolds (SF) for iliac crest, subscapular, thigh, and triceps. Linear regression evaluated predictors of TAT and VAT by BMI category.

Results

TAT demonstrated strong positive correlations with BMI, WC, HC, MUAC, and TC (r = 0.76–0.92) while VAT demonstrated moderate positive correlations with BMI, MUAC, HC (r = 0.48–0.58), and strongest with WC (r = 0.60). The healthy BMI (n = 36) TAT prediction model included MUAC, HC, and iliac SF (R2 = 0.86), and VAT model included MUAC and iliac SF (R2 = 0.60). The overweight and obesity (n = 25) TAT prediction model (R2 = 0.93) included WC and HC and the VAT model (R2 = 0.79) included HC and subscapular SF.

Conclusions

Anthropometric measures associated with prenatal adiposity differed by prepregnancy BMI. The TAT prediction model showed an acceptable R2 and included HC, MUAC, and iliac SF for healthy BMI, and WC and HC for overweight or obesity. Incorporating comprehensive anthropometrics into prenatal research and clinical care may improve risk identification and understanding of prenatal adiposity.