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Combining social network and activity space data for health research: tools and methods
Naud Alexandre1, Sueur Cédric2, Basile Chaix3
1Ecole de Sante Publique, Département de Médecine Sociale et Préventive, Université de Montréal, 7101, Avenue du Parc, Montréal, Qc, H3N 1X9, Canada; Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Axe de Recherche Santé des Populations, Pavillon S, 900 Rue Saint-Denis, Montréal, QC H2X 0A9, Canada; Universite de Strasbourg, CNRS, IPHC UMR 7178, 23 Rue du Loess, 67200, Strasbourg, France.
This study introduces a new tool to collect social network and activity space data simultaneously. This allows for better understanding of how social and spatial contexts impact population health.
Area of Science:
- Public Health
- Social Epidemiology
- Urban Health
Background:
- Population health is influenced by social networks and built environments.
- Simultaneous analysis of spatial and social contexts in health research is limited by data availability.
- Existing research often analyzes social and spatial factors in isolation.
Purpose of the Study:
- To present a novel tool for collecting relational data on social networks and activity spaces.
- To demonstrate the utility of network analysis for integrating social and spatial health determinants.
- To address the gap in research examining the interplay between social and spatial contexts.
Main Methods:
- Development of a data collection tool extending a map-based questionnaire with a name generator.
- Integration of social network data with activity space information.
- Application of network analysis techniques to analyze collected data.
Main Results:
- The presented tool successfully collects integrated social and spatial relational data.
- Network analysis reveals connections between social and spatial contexts.
- Data from the Contrasted Urban settings for Healthy Aging project illustrate the framework's application.
Conclusions:
- The new tool facilitates simultaneous collection of social and spatial data.
- Network analysis offers a robust framework for studying combined health influences.
- This approach enhances understanding of population health in diverse urban settings.
