4.1 Daily Life Gait Speed (DGS) with Built Environment
There are significant differences in the mobility of CI and non-CI samples between DGS and built environment variables (gross plot ratio and land use) in Fig. 3 and Fig. 4. Cognition plays an important role in outdoor mobility for older adults in the community. Cognition in the form of executive function plays an important role in the ability to perform both motor and cognitive tasks simultaneously in old adults while navigating outdoors (Hausdorff et al., 2008; Lamoth et al., 2011). Lamoth et al. (2011) also suggested that changes in cognitive functions contribute to changes in gait variability and stability and walking under dual-task conditions. There were small differences in DGS for both non-CI (0.75 m/s) and CI (0.73 m/s). However, when stratified according to land use, our study showed a larger differentiation in DGS. Non-CI older adults walk slower than CI older adults in a low GPR (low dense building development) and in community and residential zone areas, while non-CI older adults walk faster in a high GPR area (high dense building development) and in business and commercial zone areas. The findings were consistent for both GPR and land use results, as lower GPR is approved for community and residential use, and high GPR is approved for business and commercial use.
Both groups spent the majority of their time walking in residential areas (non-CI: 2214.7 mins, CI: 1531.0 mins), with non-CI spending more time walking. We postulate that CI and non-CI individuals may have different walking behaviours while interacting with different land uses. Various studies have shown that standardized measures such as lower extremity strength and indoor gait speed (Warren et al., 2016, (Lane et al., 2020; Yu et al., 2017)) are important for older adults to interact with their physical environments. However, the measures represent a physiologic potential in mobilizing in the community. Outdoor walking speed is more reflective of real-world interactions with the environment, which may be influenced by cultural, economic, and social factors (Bornstein & Bornstein, 1976; Kirkcaldy et al., 2001; Walmsley & Lewis, 1989).
Non-CI with a lower DGS in community and residential land use may be due to higher levels of interaction and participation with activities in the community for residential use. In Singapore, most residential land use in public housing is self-contained with shops, markets, food stalls and community activity centres, which may slow their outdoor DGS. However, the current study is not able to discern the level of cultural, economic and social participation during the 1 week of monitoring for both groups.
Older adults with CI walked with a lower DGS in business and commercial use, which may indicate a higher need for dual or multitasking. Studies have also indicated both positive and negative effects of the gross plot ratio on DGS (Bornstein & Bornstein, 1976; Kirkcaldy et al., 2001; Walmsley & Lewis, 1989). High GPR may provide shade, protecting pedestrians from excessive heat and improving comfort during walking (Vasilikou & Nikolopoulou, 2020). Additionally, the presence of high-rise buildings as landmarks can aid in wayfinding and orientation, potentially enhancing walking efficiency and speed (Yesiltepe et al., 2021). However, the impact of GPR on DGS should also be considered in the context of wind effects and visual enclosure. High-rise structures can create wind tunnels and turbulent airflows at the street level, impeding walking speed and increasing perceived effort. Furthermore, high-rise buildings can contribute to a sense of visual enclosure, reducing the perceived open space and potentially influencing individuals' walking behaviour (Zarghami et al., 2019). Non-CI with a higher DGS in business and commercial use may be influenced by the above factors.
4.2 Case example of daily life gait speed (DGS) between CI and non-CI individuals in the same neighbourhood
To further understand the differences between CI and non-CI, a case study was performed on two participants with CI (age: 82, male, MMSE: 23) and non-CI (age: 77, female, MMSE: 26) (Fig. 5). The criterion of selection is based on the demographic profiles (live in the same subzone, familiar with the neighbourhood and same age group).
Figure 6 shows the two selected participants' outdoor trajectories for 3 days; the top (a) is a participant with CI, and the bottom (b) represents a participant without CI. Both residents frequented their neighbourhood residential and commercial areas. Using heatmaps of DGS, we were able to visualize their wayfinding and navigation routes. We observed that the participant with CI had a more linear route, while the non-CI participant’s route appeared more complex. The linear trajectory of the CI participant followed a regular path (repetitive) in a relatively constant direction and speed from Day 1 to 3. The non-CI participants had a more heterogeneous and nonlinear trajectory of navigating at different speeds.
Heatmapping and visualization also showed that CI participants walked fast in the neighbourhoods (more red) with a regular daily route. Studies have also shown that familiarity with the environment can have an impact on DGS and the extent of travel (Lu et al., 2018; Van Cauwenberg et al., 2012), especially for persons with dementia (Margot-Cattin et al., 2021). Individuals who are familiar with their surroundings tend to navigate more confidently and efficiently, which can influence their walking speed.