Evidence map›Paper›PMID 21406009›Full record

ArticleDiabetes technology & therapeutics2011

Developing an objective evaluation method to estimate diabetes risk in community-based settings.

Sonjia Kenya, Qing He, Robert Fullilove, Donald P Kotler

Abstract readComparative Study
In one paragraph

Article in Diabetes technology & therapeutics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Sonjia KenyaSt Luke's-Roosevelt Hospital, Columbia University College of Physicians and Surgeons, Columbia University Mailman School of Public Health, New York, New York, USA. skenya@med.miami.edu
Qing He
Robert Fullilove
Donald P Kotler

Funding

ZOLEDRONIC ACID IN PROSTATE CANCERM01RR000645 · NCRR · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI COLTEN, HARVEY R · 1985 to 2006
$27.0M
NCRR NIH HHS RR00645PHS HHS 42618
6 · The paper itself

Abstract

backgroundExercise interventions often aim to affect abdominal obesity and glucose tolerance, two significant risk factors for type 2 diabetes. Because of limited financial and clinical resources in community and university-based environments, intervention effects are often measured with interviews or questionnaires and correlated with weight loss or body fat indicated by body bioimpedence analysis (BIA). However, self-reported assessments are subject to high levels of bias and low levels of reliability. Because obesity and body fat are correlated with diabetes at different levels in various ethnic groups, data reflecting changes in weight or fat do not necessarily indicate changes in diabetes risk. To determine how exercise interventions affect diabetes risk in community and university-based settings, improved evaluation methods are warranted.

methodsWe compared a noninvasive, objective measurement technique--regional BIA--with whole-body BIA for its ability to assess abdominal obesity and predict glucose tolerance in 39 women. To determine regional BIA's utility in predicting glucose, we tested the association between the regional BIA method and blood glucose levels.

resultsRegional BIA estimates of abdominal fat area were significantly correlated (r = 0.554, P < 0.003) with fasting glucose. When waist circumference and family history of diabetes were added to abdominal fat in multiple regression models, the association with glucose increased further (r = 0.701, P < 0.001).

conclusionsRegional BIA estimates of abdominal fat may predict fasting glucose better than whole-body BIA as well as provide an objective assessment of changes in diabetes risk achieved through physical activity interventions in community settings.

Indexed as

Community Health ServicesAbdominal FatAdiposityAdultAgedBlood GlucoseCross-Sectional StudiesDiabetes Mellitus, Type 2Early DiagnosisElectric ImpedanceFamily HealthFemaleGlucose IntoleranceHumansMiddle AgedNew York CityBlood Glucose

Identifiers

PMID21406009
PMCPMC3131828

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.