Table 5. Associations of psychosocial and environmental variables with public transport.
| School | Other destinations | |||
|---|---|---|---|---|
| Logit model: OR of being non-participanta (95% CI) | Negative binomial model: min/week (95% CI) | Logit model: OR of being non-participantb (95% CI) | Negative binomial model: min/week (95% CI) | |
| Socio-demographic | ||||
| gender (ref: female) | 1.27 (0.95, 1.68) | |||
| age | 0.81 (0.57, 1.14) | |||
| BMI | 1.04 (1.01, 1.08)** | |||
| SES (ref: low) | 1.47 (0.87, 2.48) | 0.74 (0.55, 1.00)* | ||
| education (ref: vocational) | 1.68 (0.92, 3.09) | 2.16 (1.00, 4.64)* | 0.72 (0.51, 1.01) | |
| Psychosocial | ||||
| social norm | 0.58 (0.45, 0.75)*** | 1.08 (0.98, 1.20) | 0.66 (0.51, 0.86)** | 1.04 (0.91, 1.18) |
| social modelling | ||||
| partner | 1.02 (0.88, 1.18) | 0.94 (0.86, 1.02) | ||
| parents | 1.07 (0.95, 1.21) | |||
| brothers/sisters | 0.86 (0.75, 0.99)* | 1.08 (0.99, 1.18) | ||
| friends | 0.76 (0.62, 0.93)** | 0.76 (0.62, 0.94)* | ||
| social support | 0.61 (0.42, 0.87)** | 0.60 (0.42, 0.87)** | ||
| Environmental | ||||
| land use mix access | 2.31 (1.40, 3.81)** | 2.15 (1.33, 3.45)** | ||
| street connectivity | 1.62 (0.97, 2.70) | |||
| safety from traffic | 1.01 (0.76, 1.34) | |||
| safety from crime | 0.97 (0.83, 1.12) | |||
| facilities at school | 1.75 (1.07, 2.86)* | |||
| distance | 0.93 (0.90, 0.96)*** | 1.04 (1.03, 1.05)*** | ||
OR = odds ratio; CI = confidence interval;
* p<0.05,
** p<0.01,
*** p<0.001.
a OR of being non-participant in public transport to school;
b OR of being non-participant in public transport to other destinations
Socio-demographic variables, psychosocial variables, and environmental variables for which at least a trend towards a significant relationship (p<0.10) was observed in the first step were included in this final model.
ZINB models evaluate the correlates of the odds of non-participation in public transport to school or to other destinations (logit model). Simultaneously, among participants who did use public transport to go to school or to other destinations, ZINB models evaluate the correlates of weekly minutes public transport to school or to other destinations (negative binomial model). Negative binomial model parameters represent the proportional increase in minutes/week public transport to school or to other destinations with a one-unit increase in the predictor.