Literature DB >> 34479738

DXA Versus Clinical Measures of Adiposity as Predictors of Cardiometabolic Diseases and All-Cause Mortality in Postmenopausal Women.

Deepika R Laddu1, FeiFei Qin2, Haley Hedlin2, Marcia L Stefanick3, JoAnn E Manson4, Oleg Zaslavsky5, Charles Eaton6, Lisa Warsinger Martin7, Thomas Rohan8, Themistocles L Assimes9.   

Abstract

OBJECTIVE: To investigate whether dual-energy x-ray absorptiometry (DXA) estimates of adiposity improve risk prediction for cardiometabolic diseases over traditional surrogates, body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) in older women. PATIENTS AND METHODS: We analyzed up to 9744 postmenopausal women aged 50 to 79 years participating in the Women's Health Initiative who underwent a DXA scan and were free of cardiovascular disease and diabetes at baseline (October 1993 to December 1998) and followed through September 2015. Baseline BMI, WC, WHR, and DXA-derived percent total-body and trunk fat (%TrF) were incorporated into multivariable Cox proportional hazards models to estimate the risk of incident diabetes, atherosclerosis-related cardiovascular diseases (ASCVDs), heart failure, and death. Concordance probability estimates assessed the relative discriminatory value between pairs of adiposity measures.
RESULTS: A total of 1327 diabetes cases, 1266 atherosclerotic cardiovascular disease (ASCVD) cases, 292 heart failure cases, and 1811 deaths from any cause accrued during a median follow-up of up to 17.2 years. The largest hazard ratio observed per 1 standard deviation increase of an adiposity measure was for %TrF and diabetes (1.77; 95% CI, 1.66-1.88) followed by %TrF and broadly defined ASCVD (1.22; 95% CI, 1.15-1.30). These hazard ratios remained significant for both diabetes (1.47; 95% CI, 1.37-1.57) and ASCVD (1.22; 95% CI, 1.14-1.31) even after adjusting for the best traditional surrogate measure of adiposity, WC. Percentage of trunk fat was also the only adiposity measure to demonstrate statistically significant improved concordance probability estimates over BMI, WC, and WHR for diabetes and ASCVD (all P<0.05).
CONCLUSION: DXA-derived estimates of abdominal adiposity in postmenopausal women may allow for substantially improved risk prediction of diabetes over standard clinical risk models. Larger DXA studies with complete lipid biomarker profiles and clinical trials are needed before firm conclusions can be made.
Copyright © 2021 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.

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Year:  2021        PMID: 34479738      PMCID: PMC8570974          DOI: 10.1016/j.mayocp.2021.04.027

Source DB:  PubMed          Journal:  Mayo Clin Proc        ISSN: 0025-6196            Impact factor:   7.616


  23 in total

1.  Implementation of the Women's Health Initiative study design.

Authors:  Garnet L Anderson; Joann Manson; Robert Wallace; Bernedine Lund; Dallas Hall; Scott Davis; Sally Shumaker; Ching-Yun Wang; Evan Stein; Ross L Prentice
Journal:  Ann Epidemiol       Date:  2003-10       Impact factor: 3.797

Review 2.  What aspects of body fat are particularly hazardous and how do we measure them?

Authors:  M B Snijder; R M van Dam; M Visser; J C Seidell
Journal:  Int J Epidemiol       Date:  2005-12-08       Impact factor: 7.196

3.  Longitudinal changes in abdominal fat distribution with menopause.

Authors:  Ruth M Franklin; Lori Ploutz-Snyder; Jill A Kanaley
Journal:  Metabolism       Date:  2009-03       Impact factor: 8.694

4.  Screening for Osteoporosis to Prevent Fractures: US Preventive Services Task Force Recommendation Statement.

Authors:  Susan J Curry; Alex H Krist; Douglas K Owens; Michael J Barry; Aaron B Caughey; Karina W Davidson; Chyke A Doubeni; John W Epling; Alex R Kemper; Martha Kubik; C Seth Landefeld; Carol M Mangione; Maureen G Phipps; Michael Pignone; Michael Silverstein; Melissa A Simon; Chien-Wen Tseng; John B Wong
Journal:  JAMA       Date:  2018-06-26       Impact factor: 56.272

5.  Body mass index and all-cause mortality among older adults.

Authors:  Feon W Cheng; Xiang Gao; Diane C Mitchell; Craig Wood; Christopher D Still; David Rolston; Gordon L Jensen
Journal:  Obesity (Silver Spring)       Date:  2016-08-29       Impact factor: 5.002

6.  Racial and Ethnic Differences in Anthropometric Measures as Risk Factors for Diabetes.

Authors:  Juhua Luo; Michael Hendryx; Deepika Laddu; Lawrence S Phillips; Rowan Chlebowski; Erin S LeBlanc; David B Allison; Dorothy A Nelson; Yueyao Li; Milagros C Rosal; Marcia L Stefanick; JoAnn E Manson
Journal:  Diabetes Care       Date:  2018-10-23       Impact factor: 19.112

7.  Measures of obesity and cardiovascular risk among men and women.

Authors:  Rebecca P Gelber; J Michael Gaziano; E John Orav; Joann E Manson; Julie E Buring; Tobias Kurth
Journal:  J Am Coll Cardiol       Date:  2008-08-19       Impact factor: 24.094

8.  General cardiovascular risk profile for use in primary care: the Framingham Heart Study.

Authors:  Ralph B D'Agostino; Ramachandran S Vasan; Michael J Pencina; Philip A Wolf; Mark Cobain; Joseph M Massaro; William B Kannel
Journal:  Circulation       Date:  2008-01-22       Impact factor: 29.690

9.  The Association between Body Composition using Dual energy X-ray Absorptiometry and Type-2 Diabetes: A Systematic Review and Meta-Analysis of Observational studies.

Authors:  Preeti Gupta; Carla Lanca; Alfred T L Gan; Pauline Soh; Sahil Thakur; Yijin Tao; Neelam Kumari; Ryan E K Man; Eva K Fenwick; Ecosse L Lamoureux
Journal:  Sci Rep       Date:  2019-09-02       Impact factor: 4.379

10.  The impact of confounding on the associations of different adiposity measures with the incidence of cardiovascular disease: a cohort study of 296 535 adults of white European descent.

Authors:  Stamatina Iliodromiti; Carlos A Celis-Morales; Donald M Lyall; Jana Anderson; Stuart R Gray; Daniel F Mackay; Scott M Nelson; Paul Welsh; Jill P Pell; Jason M R Gill; Naveed Sattar
Journal:  Eur Heart J       Date:  2018-05-01       Impact factor: 29.983

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  1 in total

1.  Deep learning predicts all-cause mortality from longitudinal total-body DXA imaging.

Authors:  Yannik Glaser; John Shepherd; Lambert Leong; Thomas Wolfgruber; Li-Yung Lui; Peter Sadowski; Steven R Cummings
Journal:  Commun Med (Lond)       Date:  2022-08-16
  1 in total

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