142nd APHA Annual Meeting and Exposition

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308234
A propensity matched analysis of population movement implicating area contributions to increased cardiometabolic risk over time

142nd APHA Annual Meeting and Exposition (November 15 - November 19, 2014): http://www.apha.org/events-and-meetings/annual
Monday, November 17, 2014 : 12:30 PM - 12:45 PM

Natasha Howard, BHSc (Hons), PhD , School of Population Health and Sansom Institute for Health Research, University of South Australia, Spatial Epidemiology and Evaluation Research Group, Adelaide, South Australia, Australia 5001, Australia
Catherine Paquet, BSc, PhD , School of Population Health and Sansom Institute for Health Research, Spatial Epidemiology and Evaluation Research Group, Adelaide, Australia
Neil Coffee, BA(Hon), MA, PhD , School of Population Health and Sansonm Institute for Health Research, Spatial Epidemiology and Evaluation Research Group, Adelaide, Australia
Graeme J. Hugo, PhD, MGEOG , Geography, Environment and Population, University of Adelaide, Adelaide, South Australia, Australia
Peter Lekkas, BPty MPty PhD (Cand) , School of Population Health and Sansom Institute for Health Research, Spatial Epidemiology and Evaluation Research Group, Adelaide, Australia
Anne W. Taylor, MPH PhD , Population Research & Outcome Studies, University of Adelaide, Adelaide, South Australia, Australia
Robert Adams, MBBS MD FRACP FRCP , The Health Observatory, University of Adelaide, Adelaide, South Australia, Australia
Mark Daniel, BSc, MSc, PhD , School of Population Health and Sansom Institute for Health Research, University of South Australia, Adelaide, Australia
Introduction:

Longitudinal cohorts have increasingly sought to account for population movement and its impact on health.  In research on place and health, the focus has centred on the self-selection of residents into local-areas, and potential biases for geospatial epidemiological analyses.  However, of equal importance are the area-level drivers of population movement and, thus corresponding links with health outcomes.  Informed by geographic mobility theories, this study aimed to implicate area-level influences by accounting for individual factors using propensity matched pairs of ‘movers’ and ‘non-movers’ to assess change in cardiometabolic risk across two time points.

Method:

Data were utilised from Wave 1 (n=4041; 2000-03) and Wave 2 (n=3507; 2005-06) of the North West Adelaide Health Study.  The outcome measure, the count of clinically measured cardiometabolic risk factors, and socio-economic and demographic information, were collected from urban-dwelling adult participants linked by residential address using a geographic information system.  Matched propensity scores were estimated by a logistic regression model in which residential mobility was regressed on: a change in marital status, work status and household income, as well as gender, age cohort and housing tenure.  Comparison between time 2 vs. time 1 change between the ‘mover’ and ‘non-mover’ matches for cardiometabolic risk scores (count of six risk measures) was evaluated by paired t-test.

Results:

Four hundred and thirteen ‘movers’ were pair-matched with ‘non-movers’ for individual-level predictors of residential movement.  ‘Non-movers’ had an increase in the count of elevated cardiometabolic risk factors (mean 0.04) than ‘mover’ counterparts (mean -0.11).

Discussion:

'Non-movers' had a greater increase in risk of cardiometabolic disease.  In so far as this analysis accounted for individual-level factors that contribute to re-location, area-level influences are potentially implicated for advancing understandings of population movement.

Learning Areas:

Epidemiology
Social and behavioral sciences

Learning Objectives:
Demonstrate propensity matched analysis of population movement for assessment of change in cardiometabolic risk across two time points.

Keyword(s): Geographic Information Systems (GIS), Epidemiology

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: Natasha is a Post-Doctoral Research Fellow within the Spatial Epidemiology and Evaluation Research Group, Sansom Institute for Health Research at the University of South Australia. She is a Social Geographer with a keen interest in exploring the social and spatial inequalities of cardiovascular risk behaviours and well-being. Her work experience spans both the Health and Social Sciences, applying population approaches to investigate how the social and built environment enables and promotes cardiometabolic health and well-being.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.