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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