Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/106751
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Type: Journal article
Title: Geographic clustering of cardiometabolic risk factors in metropolitan centres in France and Australia
Author: Paquet, C.
Chaix, B.
Howard, N.
Coffee, N.
Adams, R.
Taylor, A.
Thomas, F.
Daniel, M.
Citation: International Journal of Environmental Research and Public Health, 2016; 13(5):519-1-519-17
Publisher: MDPI AG
Issue Date: 2016
ISSN: 1661-7827
1660-4601
Statement of
Responsibility: 
Catherine Paquet, Basile Chaix, Natasha J. Howard, Neil T. Coffee, Robert J. Adams, Anne W. Taylor, Frédérique Thomas and Mark Daniel
Abstract: Understanding how health outcomes are spatially distributed represents a first step in investigating the scale and nature of environmental influences on health and has important implications for statistical power and analytic efficiency. Using Australian and French cohort data, this study aimed to describe and compare the extent of geographic variation, and the implications for analytic efficiency, across geographic units, countries and a range of cardiometabolic parameters (Body Mass Index (BMI) waist circumference, blood pressure, resting heart rate, triglycerides, cholesterol, glucose, HbA1c). Geographic clustering was assessed using Intra-Class Correlation (ICC) coefficients in biomedical cohorts from Adelaide (Australia, n = 3893) and Paris (France, n = 6430) for eight geographic administrative units. The median ICC was 0.01 suggesting 1% of risk factor variance attributable to variation between geographic units. Clustering differed by cardiometabolic parameters, administrative units and countries and was greatest for BMI and resting heart rate in the French sample, HbA1c in the Australian sample, and for smaller geographic units. Analytic inefficiency due to clustering was greatest for geographic units in which participants were nested in fewer, larger geographic units. Differences observed in geographic clustering across risk factors have implications for choice of geographic unit in sampling and analysis, and highlight potential cross-country differences in the distribution, or role, of environmental features related to cardiometabolic health.
Keywords: Intra-Class Correlation; cross-country comparison; geographic clustering; geographic variation; cardiometabolic risk factors
Description: Published: 21 May 2016
Rights: © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
RMID: 0030048745
DOI: 10.3390/ijerph13050519
Grant ID: http://purl.org/au-research/grants/nhmrc/631917
http://purl.org/au-research/grants/nhmrc/570150
http://purl.org/au-research/grants/nhmrc/570139
Appears in Collections:Medicine publications

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