Table 4.
Variables | Mean | Model 1a | Model 2b |
---|---|---|---|
b (SE) | b (SE) | ||
How much do you trust in the people of your neighborhood? | |||
Nothing at all or very little, moderately | 44.5 | Ref | Ref |
Quite a lot, very much | 46.2 | −0.03 (0.81) | −0.04 (0.81) |
How much can you rely in your neighbors to help in various ways if someone is destructive to a nearby place such as a park? | |||
Nothing at all or very little, moderately | 44.3 | Ref | Ref |
Quite a lot, very much | 46.5 | +0.76 (0.72) | +0.77 (0.72) |
How much do the people in your neighborhood share the same values? | |||
Nothing at all or very little, moderately | 44.5 | Ref | Ref |
Quite a lot, very much | 46.7 | +1.29* (0.70) | +1.29* (0.70) |
How much would the people in your neighborhood try to take to advantage of you if they got a chance? | |||
Quite a lot, very much | 45.8 | Ref | Ref |
Nothing at all or very little, moderately | 48.1 | +2.88*** (1.02) | +2.89*** (1.02) |
Neighborhood SES | |||
Low | 43.2 | Ref | Ref |
Middle-low and middle-high | 45.2 | +1.77*** (0.49) | +2.56*** (0.86) |
Interactions terms | |||
Trust in neighbors (Quite a lot, very much) *SES (Middle-low and middle-high upper) | +0.96(0.77) | ||
Rely in your neighbors (Quite a lot, very much) *SES (Middle-low and middle-high) | −0.77(0.63) | ||
Neighbors share the same values (Quite a lot, very much) *SES (Middle-low and middle-high) | +1.12* (0.56) | ||
Neighbors would take advantage of you if they could (Nothing at all or very little, moderately) *SES (Middle-low and middle-high) | −0.81 (0.77) |
Model adjusted by age, gender, years of residence in the neighborhood, living arrangements, neighborhood SES, educational attainment; walking from your house, how far do the members of your family live and social capital variables,
Model adjusted by age, gender, years of residence in the neighborhood, living arrangements, neighborhood SES, educational attainment; walking from your house, how far do the members of your family live; social capital variables and interaction terms.
Variance components. Tau: empty model (2.1822; p<0.001), model 1 (0.2126; p=0.376), model 2 (0.1186; p=0.422). ICC: empty model (0.0214), model 1 (0.0023), model 2 (0.0013).
p ≤ 0.1;
p ≤ .05;
p ≤ .01