Abstract
Background and Aim: Studies of greenness and health often rely on buffer-based residential measures which miss potential exposure occurring outside the home environment. We compared greenness measures obtained from traditional residence-based buffers and novel smartphone mobility-based estimates. Methods: We used data from the US-based Nurses’ Health Study 3 mHealth study, which followed 348 participants who completed four 7-day sampling periods to capture seasonal variability across the year. We used Landsat Normalized Difference Vegetation Index (NDVI) data (30mx30m resolution) for both traditional and mobility-based greenness measures. We assessed two annual average residence-based estimates: 270m and 1230m. Mobility-based greenness exposure was calculated as seasonal NDVI values at GPS points captured every 10 minutes averaged across all four seasonal sampling periods. We compared measures using descriptive statistics, Bland Altman tests, and Generalized Additive Models. Results: Mean NDVI values from traditional residential buffers (270m=0.40, SD =0.12, 1230m=0.40, SD=0.12) were higher than those obtained using mobility derived NDVI (mean = 0.32, SD=0.11). The Bland Altman agreement bias was larger by 8.0% (95% CI: 7.0%, 9.0%) using the 270m residential measure and 7.3% (95% CI: 6.0%, 8.0% ) using the 1230m residential measures compared to mobility derived NDVI. Spearman’s rank correlations comparing the mobility and residential NDVI were 0.57 and 0.55 for the 270m and 1230m buffer respectively. The two residential buffers had a Spearman’s rank correlation of 0.88. Lastly, for each 10% increase in both 270m and 1230m NDVI, was associated with 0.06 increase in mobility based NDVI (95% CI: 0.05, 0.07). Conclusions: Results from our study indicate traditional residential estimates of greenness are higher than mobility derived metrics. These findings contribute to discussions surrounding the choice of an optimal spatial scale for greenness exposure. Keywords: Wearables, Mobility, Greenspace, Exposure Validation
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