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Regional Fat Distribution and Blood Pressure Level and Variability: The Dallas Heart Study.

Publication ,  Journal Article
Yano, Y; Vongpatanasin, W; Ayers, C; Turer, A; Chandra, A; Carnethon, MR; Greenland, P; de Lemos, JA; Neeland, IJ
Published in: Hypertension
September 2016

Our aim was to investigate the associations of regional fat distribution with home and office blood pressure (BP) levels and variability. Participants in the Dallas Heart Study, a multiethnic cohort, underwent 5 BP measurements on 3 occasions during 5 months (2 in home and 1 in office) and quantification of visceral adipose tissue, abdominal subcutaneous adipose tissue, and liver fat by magnetic resonance imaging, and lower body subcutaneous fat by dual x-ray absorptiometry. The relation of regional adiposity with short-term (within-visit) and long-term (overall visits) mean BP and average real variability was assessed with multivariable linear regression. We have included 2595 participants with a mean age of 44 years (54% women; 48% black), and mean body mass index was 29 kg/m(2) Mean systolic BP/diastolic BP was 127/79 mm Hg and average real variability systolic BP was 9.8 mm Hg during 3 visits. In multivariable-adjusted models, higher amount of visceral adipose tissue was associated with higher short-term (both home and office) and long-term mean systolic BP (β[SE]: 1.9[0.5], 2.7[0.5], and 2.1[0.5], respectively; all P<0.001) and with lower long-term average real variability systolic BP (β[SE]: -0.5[0.2]; P<0.05). In contrast, lower body fat was associated with lower short-term home and long-term mean BP (β[SE]: -0.30[0.13] and -0.24[0.1], respectively; both P<0.05). Neither subcutaneous adipose tissue or liver fat was associated with BP levels or variability. In conclusion, excess visceral fat was associated with persistently higher short- and long-term mean BP levels and with lower long-term BP variability, whereas lower body fat was associated with lower short- and long-term mean BP. Persistently elevated BP, coupled with lower variability, may partially explain increased risk for cardiac hypertrophy and failure related to visceral adiposity.

Duke Scholars

Published In

Hypertension

DOI

EISSN

1524-4563

Publication Date

September 2016

Volume

68

Issue

3

Start / End Page

576 / 583

Location

United States

Related Subject Headings

  • Texas
  • Subcutaneous Fat
  • Sex Factors
  • Risk Assessment
  • Prognosis
  • Obesity
  • Multivariate Analysis
  • Middle Aged
  • Male
  • Linear Models
 

Citation

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Yano, Y., Vongpatanasin, W., Ayers, C., Turer, A., Chandra, A., Carnethon, M. R., … Neeland, I. J. (2016). Regional Fat Distribution and Blood Pressure Level and Variability: The Dallas Heart Study. Hypertension, 68(3), 576–583. https://doi.org/10.1161/HYPERTENSIONAHA.116.07876
Yano, Yuichiro, Wanpen Vongpatanasin, Colby Ayers, Aslan Turer, Alvin Chandra, Mercedes R. Carnethon, Philip Greenland, James A. de Lemos, and Ian J. Neeland. “Regional Fat Distribution and Blood Pressure Level and Variability: The Dallas Heart Study.Hypertension 68, no. 3 (September 2016): 576–83. https://doi.org/10.1161/HYPERTENSIONAHA.116.07876.
Yano Y, Vongpatanasin W, Ayers C, Turer A, Chandra A, Carnethon MR, et al. Regional Fat Distribution and Blood Pressure Level and Variability: The Dallas Heart Study. Hypertension. 2016 Sep;68(3):576–83.
Yano, Yuichiro, et al. “Regional Fat Distribution and Blood Pressure Level and Variability: The Dallas Heart Study.Hypertension, vol. 68, no. 3, Sept. 2016, pp. 576–83. Pubmed, doi:10.1161/HYPERTENSIONAHA.116.07876.
Yano Y, Vongpatanasin W, Ayers C, Turer A, Chandra A, Carnethon MR, Greenland P, de Lemos JA, Neeland IJ. Regional Fat Distribution and Blood Pressure Level and Variability: The Dallas Heart Study. Hypertension. 2016 Sep;68(3):576–583.

Published In

Hypertension

DOI

EISSN

1524-4563

Publication Date

September 2016

Volume

68

Issue

3

Start / End Page

576 / 583

Location

United States

Related Subject Headings

  • Texas
  • Subcutaneous Fat
  • Sex Factors
  • Risk Assessment
  • Prognosis
  • Obesity
  • Multivariate Analysis
  • Middle Aged
  • Male
  • Linear Models