Alternative waist-to-height ratios associated with risk biomarkers in youth with diabetes: comparative models in the SEARCH for Diabetes in Youth Study.


Journal

International journal of obesity (2005)
ISSN: 1476-5497
Titre abrégé: Int J Obes (Lond)
Pays: England
ID NLM: 101256108

Informations de publication

Date de publication:
10 2019
Historique:
received: 17 07 2018
accepted: 07 02 2019
revised: 19 11 2018
pubmed: 31 3 2019
medline: 19 5 2020
entrez: 31 3 2019
Statut: ppublish

Résumé

The waist-to-height ratio (WHtR) estimates cardiometabolic risk in youth without need for growth charts by sex and age. Questions remain about whether waist circumference measured per protocol of the National Health and Nutrition Examination Survey (W WHtR was measured under both anthropometric protocols among participants in the SEARCH Study, who were recently diagnosed with diabetes (ages 5-19 years; N = 2 773). Biomarkers were documented concurrently with baseline anthropometry and again ~7 years later (ages 10-30 years; N = 1 712). For prediction of continuous biomarker outcomes, baseline W For the concurrent biomarkers, the proportion of variation in each outcome explained by full regression models ranged from 23 to 46%; for the prospective biomarkers, the proportions varied from 11 to 30%. Nonlinear relationships were recognized with the lipid outcomes, both at baseline and at follow-up. In full logistic models, the AUCs ranged from 0.75 (diastolic pressure) to 0.85 (systolic pressure) at baseline, and from 0.69 (triglycerides) to 0.78 (systolic pressure) at the prospective follow-up. To predict baseline elevations of the triglycerides/HDL cholesterol ratio, the AUC was 0.816 for W Among youth with recently diagnosed diabetes, measurements of WHtR by either waist circumference protocol similarly helped estimate current and prospective cardiometabolic risk biomarkers.

Sections du résumé

BACKGROUND/OBJECTIVES
The waist-to-height ratio (WHtR) estimates cardiometabolic risk in youth without need for growth charts by sex and age. Questions remain about whether waist circumference measured per protocol of the National Health and Nutrition Examination Survey (W
PARTICIPANTS/METHODS
WHtR was measured under both anthropometric protocols among participants in the SEARCH Study, who were recently diagnosed with diabetes (ages 5-19 years; N = 2 773). Biomarkers were documented concurrently with baseline anthropometry and again ~7 years later (ages 10-30 years; N = 1 712). For prediction of continuous biomarker outcomes, baseline W
RESULTS
For the concurrent biomarkers, the proportion of variation in each outcome explained by full regression models ranged from 23 to 46%; for the prospective biomarkers, the proportions varied from 11 to 30%. Nonlinear relationships were recognized with the lipid outcomes, both at baseline and at follow-up. In full logistic models, the AUCs ranged from 0.75 (diastolic pressure) to 0.85 (systolic pressure) at baseline, and from 0.69 (triglycerides) to 0.78 (systolic pressure) at the prospective follow-up. To predict baseline elevations of the triglycerides/HDL cholesterol ratio, the AUC was 0.816 for W
CONCLUSIONS
Among youth with recently diagnosed diabetes, measurements of WHtR by either waist circumference protocol similarly helped estimate current and prospective cardiometabolic risk biomarkers.

Identifiants

pubmed: 30926953
doi: 10.1038/s41366-019-0354-8
pii: 10.1038/s41366-019-0354-8
pmc: PMC9425551
mid: NIHMS1803267
doi:

Substances chimiques

Biomarkers 0

Types de publication

Comparative Study Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

1940-1950

Subventions

Organisme : NIDDK NIH HHS
ID : P30 DK057516
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U18 DP002710
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U18 DP006134
Pays : United States
Organisme : ACL HHS
ID : U18DP006138
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR000154
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U18 DP002714
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U01 DP000248
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U01 DP000244
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR000062
Pays : United States
Organisme : ACL HHS
ID : U18DP006131
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001425
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR000077
Pays : United States
Organisme : HSRD VA
ID : HIR 10-001
Pays : United States
Organisme : ACL HHS
ID : U18DP006139
Pays : United States
Organisme : NIDDK NIH HHS
ID : UC4 DK108173
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U01 DP000247
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U18 DP006139
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U18 DP006131
Pays : United States
Organisme : ACL HHS
ID : U18DP006134
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U18 DP006138
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U18 DP006136
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U18 DP002709
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U18 DP006133
Pays : United States
Organisme : NIDDK NIH HHS
ID : R01 DK127208
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR000423
Pays : United States
Organisme : ACL HHS
ID : U18DP006136
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U01 DP000250
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U01 DP000246
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U01 DP000254
Pays : United States
Organisme : ACL HHS
ID : U18DP006133
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U18 DP002708
Pays : United States

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Auteurs

Henry S Kahn (HS)

Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA, USA.

Jasmin Divers (J)

Department of Biostatistics, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA.

Nora F Fino (NF)

Biostatistics and Design Program, Oregon Health and Science University, Portland, OR, USA.

Dana Dabelea (D)

Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.

Ronny Bell (R)

Department of Public Health, East Carolina University, Greenville, NC, USA.

Lenna L Liu (LL)

Department of General Pediatrics, Seattle Children's Hospital, Seattle, WA, USA.

Victor W Zhong (VW)

Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.

Sharon Saydah (S)

Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA, USA. zle0@cdc.gov.

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Classifications MeSH