Supplementary Data from Contextual Correlates of Physical Activity among Older Adults: A Neighborhood Environment-Wide Association Study (NE-WAS)
Year: 2023
Type: supplementary-materials
Abstract: Supplementary Figure 1. Using Shapiro-Wilk Test Statistic to Decide Whether to Log-Transform Predictor Variable. Supplementary Table 1. Measures used in the NE-WAS. Supplementary Figure 2: Manhattan Plots showing the strengths of correlations between individual neighborhood variables and various physical activity outcomes as measured by the Physical Activity Scale for the Elderly (PASE) after controlling for age, sex, race/ethnicity, educational attainment, income, and housing type. Supplementary Figure 3. Manhattan Plots showing the statistical significance of correlations between individual neighborhood variables total Physical Activity Scale for the Elderly (PASE) score at smaller and larger buffer sizes. Supplementary Figure 4. “Volcano plots� relating log p-value to regression coefficient for each variable. Supplementary Table 2. Specific neighborhood measures identified as most predictive for several physical activity outcomes using regression modes in the full cohort. Supplementary Brief Report: LASSO and Random Forest Approaches for NE-WAS. Supplementary Figure 5. Regularization path graph for the LASSO regression on PASE score. Supplementary Figure 6: Example of a decision tree computed using a recursive partitioning algorithm to predict probability of reporting gardening as a function of neighborhood-level and individual-level covariates among subjects in NYCNAMES-II who reported fair or better health. Supplementary Table 3. Specific neighborhood measures identified as most predictive for several physical activity outcomes using Least Absolute Shrinkage and Selection Operator (‘LASSO’). Supplementary Table 4. Specific neighborhood measures identified as most important by the Random Forest algorithm for several physical activity outcomes. Supplementary Table 5. Specific neighborhood measures identified as most predictive for several physical activity outcomes using LASSO on cohort created by selecting a random imputation for each subject.
Language: English
Subfield: Transportation
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
OpenAlex ID: W4362391853