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Table 2 Multinomial logistic regression analysis for access to restaurants and grocery stores with home-cooking (n = 5076)

From: Spatial access to restaurants and grocery stores in relation to frequency of home cooking

  

0–3/week

RRR (95% CI)

4 – 5/week

RRR (95% CI)

p value

6 – 7/week

RRR (95% CI)

p value

Model 1

Spatial access to restaurants

T1 (lowest)

1

1

 

1

 

T2

0.73 (0.49 – 1.10)

0.135

0.61 (0.35 – 1.05)

0.076

T3 (highest)

0.61 (0.39 – 0.96)

0.031

0.42 (0.23 – 0.76)

0.004

Model 2

Spatial access to grocery stores

T1 (lowest)

1

1

 

1

 

T2

0.83 (0.58 – 1.20)

0.318

0.62 (0.35 – 1.13)

0.117

T3 (highest)

0.70 (0.47 – 1.08)

0.106

0.55 (0.29 – 1.01)

0.054

Model 3

Spatial access to restaurants

T1 (lowest)

1

1

 

1

 

T2

0.75 (0.50 – 1.13)

0.171

0.63 (0.37 – 1.09)

0.101

T3 (highest)

0.65 (0.38 – 1.12)

0.123

0.42 (0.21 – 0.87)

0.019

Spatial access to grocery stores

T1 (lowest)

1

1

 

1

 

T2

0.90 (0.65 – 1.25)

0.533

0.72 (0.43 – 1.22)

0.229

T3 (highest)

0.90 (0.56 – 1.44)

0.652

0.91 (0.45 – 1.83)

0.783

  1. RRR Relative Risk Ratio, 95%CI 95% confidence intervals; Model 1: model with spatial access to restaurants as independent variable; Model 2: model with spatial access to grocery stores as independent variable; Model 3: model with spatial access to restaurants and spatial access to grocery stores as independent variables; T1, T2 and T3 are tertiles of spatial access, where individuals in T1 have the lowest access and individuals in T3 the highest access; All models were adjusted for age, sex, educational attainment, BMI, household composition, employment status, and urban region; Results in bold are statically significant (p < 0.05)