Geographic Clustering of Cardiometabolic Risk Factors in Metropolitan Centres in France and Australia

Catherine Paquet, Basile Chaix, Natasha J. Howard, Neil T. Coffee, Robert J. Adams, Anne W. Taylor, Frédérique Thomas and Mark Daniel
Additional contact information
Catherine Paquet: Centre for Population Health Research, School of Health Sciences, Sansom Institute for Health Research, University of South Australia, Adelaide SA 5001, Australia
Basile Chaix: Inserm, UMR-S 1136, Pierre Louis Institute of Epidemiology and Public Health, Nemesis Team, Paris 75012, France
Natasha J. Howard: Centre for Population Health Research, School of Health Sciences, Sansom Institute for Health Research, University of South Australia, Adelaide SA 5001, Australia
Neil T. Coffee: Centre for Population Health Research, School of Health Sciences, Sansom Institute for Health Research, University of South Australia, Adelaide SA 5001, Australia
Robert J. Adams: Discipline of Medicine, The University of Adelaide, Adelaide SA 5001, Australia
Anne W. Taylor: Discipline of Medicine, The University of Adelaide, Adelaide SA 5001, Australia
Frédérique Thomas: Centre d’Investigations Préventives et Cliniques, Paris 75116, France
Mark Daniel: Centre for Population Health Research, School of Health Sciences, Sansom Institute for Health Research, University of South Australia, Adelaide SA 5001, Australia

IJERPH, 2016, vol. 13, issue 5, 1-17

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, HbA 1c ). 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, HbA 1c 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 (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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