Robust Indicators of Residential Mobility Derived From Longitudinal Canadian Data to Examine Population Health Across the Life Course

Sarah M. Mah, Emmalin Buajitti, Lief Pagalan, Lori M. Diemert, Michael Tjepkema, Tanya Christidis, Sabrina Chiodo, Arjumand Siddiqi, Jeffrey R. Brook, Hong Chen and Laura C. Rosella ()
Additional contact information
Sarah M. Mah: University of Toronto
Emmalin Buajitti: University of Toronto
Lief Pagalan: University of Toronto
Lori M. Diemert: University of Toronto
Michael Tjepkema: Statistics Canada
Tanya Christidis: Statistics Canada
Sabrina Chiodo: University of Toronto
Arjumand Siddiqi: University of Toronto
Jeffrey R. Brook: University of Toronto
Hong Chen: Public Health Ontario
Laura C. Rosella: University of Toronto

Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2025, vol. 177, issue 3, No 2, 937-957

Abstract: Abstract Where we live, how often we move, and where we move to have direct impacts on health and well-being. However, there is still a need for comprehensive data and robust approaches to assess long-term residential mobility and population-wide health. We accessed a record-linked cohort of 888,630 Canadian Community Health Survey respondents (2000-2017) for whom tax-based postal codes from as early as 1981 were available. We developed three indicators of residential mobility using postal code information captured 3, 5, and 10 years prior to date of survey response, compared our measures against estimates from the Canadian Census, and described their relationships with key sociodemographic characteristics. Residential histories extended an average of 21 years prior to interview date (range 0–37 years). Younger respondents had shorter histories due to their age. Overall, 28.1% moved within 3 years, 37.1% moved within 5 years, and 54% moved within 10 years prior to survey response. The 5-year moving rates derived in this study were similar to Census estimates, and both showed a decline in residential mobility over time. All measures of residential mobility differed to varying degrees by sociodemographic characteristics and self-reported health and wellbeing. Our study demonstrates that longitudinal linked tax and survey data can be used to produce reliable population-wide measures of residential mobility. Variations in different types of residential mobility across sociodemographic, health, and wellbeing characteristics suggest complex relationships exist between residential mobility and health, and highlights the value of examining multiple dimensions of residential mobility.

Keywords: Residential mobility; Residential history; Neighbourhoods; Population health; Life course; Linked data (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11205-025-03521-0

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