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Table 4 Conditional autoregressive model summaries for sufficient walking to improve health

From: The contribution of area-level walkability to geographic variation in physical activity: a spatial analysis of 95,837 participants from the 45 and Up Study living in Sydney, Australia

  Model 1 Model 2 Model 3 Model 4 Model 5
Individual-level adjustment No Yes Yes Yes Yes
Parameter estimates (PR, 95% CrI)
Constant 1.00 (0.99-1.02) 1.01 (0.99-1.02) 0.94 (0.90-0.98) 1.03 (1.00-1.08) 0.97 (0.91-1.03)
Walkability
Low 1.00 1.00
Low-medium 1.03 (0.99-1.08) 1.03 (0.98-1.07)
Medium-high 1.07 (1.01-1.13) 1.05 (0.99-1.11)
High 1.20 (1.12-1.29) 1.18 (1.09-1.27)
Socioeconomic disadvantage
High 1.00 1.00
High-medium 0.98 (0.93-1.03) 0.98 (0.94-1.03)
Medium 0.99 (0.94-1.04) 1.00 (0.95-1.05)
Medium-low 0.97 (0.91-1.02) 0.97 (0.92-1.03)
Low 0.92 (0.86-0.98) 0.94 (0.89-1.00)
Model diagnostics
pD 92.37 75.41 62.05 76.81 65.25
DIC 1875.16 1858.87 1855.11 1857.33 1854.39
Fit (1=best, 5=poorest) 5 4 2 3 1
Spatial fraction 0.98 0.97 0.90 0.97 0.93
  1. PR prevalence ratio, CrI credible interval, pD effective parameters, DIC Deviance Information Criterion
  2. Model 1 null model with expected cases proportional to the overall prevalence
  3. Model 2 null model with expected cases adjusted for individual-level factors
  4. Model 3 Model 2 + Sydney Walkability Index
  5. Model 4 Model 2 + Index of Relative Socioeconomic Disadvantage
  6. Model 5 Model 3 + Index of Relative Socioeconomic Disadvantage