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Updated: Mar 18, 2026

A Method for Quantifying Upper Limb Performance in Daily Life Using Accelerometers
Published on: April 21, 2017
A methodology to leverage cross-sectional accelerometry to capture weather's influence in active living research
Tarun R Katapally1,2, Daniel Rainham3, Nazeem Muhajarine4,5
1Johnson-Shoyama Graduate School of Public Policy, University of Regina, 110-2 Research Drive, Innovation Place, Regina, SK, S4S 7H1, Canada. tarun.katapally@usask.ca.
Objectives:
While active living interventions focus on modifying urban design and built environment, weather variation, a phenomenon that perennially interacts with these environmental factors, is consistently underexplored. This study's objective is to develop a methodology to link weather data with existing cross-sectional accelerometry data in capturing weather variation.
Methods:
Saskatoon's neighbourhoods were classified into grid-pattern, fractured grid-pattern and curvilinear neighbourhoods. Thereafter, 137 Actical accelerometers were used to derive moderate to vigorous physical activity (MVPA) and sedentary behaviour (SB) data from 455 children in 25 sequential one-week cycles between April and June, 2010. This sequential deployment was necessary to overcome the difference in the ratio between the sample size and the number of accelerometers. A data linkage methodology was developed, where each accelerometry cycle was matched with localized (Saskatoon-specific) weather patterns derived from Environment Canada. Statistical analyses were conducted to depict the influence of urban design on MVPA and SB after factoring in localized weather patterns.
Results:
Integration of cross-sectional accelerometry with localized weather patterns allowed the capture of weather variation during a single seasonal transition. Overall, during the transition from spring to summer in Saskatoon, MVPA increased and SB decreased during warmer days. After factoring in localized weather, a recurring observation was that children residing in fractured grid-pattern neighbourhoods accumulated significantly lower MVPA and higher SB.
Conclusion:
The proposed methodology could be utilized to link globally available cross-sectional accelerometry data with place-specific weather data to understand how built and social environmental factors interact with varying weather patterns in influencing active living.

