The National Institute on Aging at NIH has awarded NORC a 5-year grant to study the activity spaces of elderly Chicagoans using a range of innovative methods over three waves of data collection. The project is being led by PI Kathleen Cagney, NORC Senior Fellow and Professor of Sociology at the University of Chicago, in collaboration with Erin York Cornwell at Cornell University and Chris Browning at Ohio State University. The major goals of the project are to describe the social and spatial environments in which older adults spend their time and explore the extent to which these activity spaces affect, and are affected by, pre-clinical changes in health. The project aims to collect primary, multi-wave data from 450 Chicagoans aged 65 and older by:
- conducting in-person interviews to obtain baseline measures of self-reported and objective indices of health, including body mass index and a measure of physical mobility, and to identify any changes in mental, emotional, and physical health status between each of the three waves of data collection;
- using a smartphone app over week-long periods to identify latitude, longitude, and distance traveled in order to describe respondents’ physical activity spaces and to obtain real-time reports of social settings, health status, and well-being using Ecological Momentary Assessment (EMA) in order to identify day-to-day fluctuations in social environment and both emotional and physical health; and
- leveraging extant information such as Census and Area Resource File data and sensor-type data on Chicago neighborhoods collected by the NSF-funded Array of Things project in order to identify neighborhood environmental and demographic determinants of both activity space and health status.
Respondents will be randomly sampled from 8-9 different Chicago neighborhoods that vary by socioeconomic status, race/ethnicity, and location. NORC has primary responsibility for collecting the baseline, follow-up, and EMA data as shown in the exhibit below:
Project investigators will analyze the longitudinal data using multi-level models in order to measure the extent to which activity space influences health trajectories net of other biological and social determinants. Specifically, our conceptual model includes four social contexts that we theorize as interrelated and mutually constituted: household environment, neighborhood context, social networks, and activity space.