Table 4. Associations of psychosocial and environmental variables with cycling.
| 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) | 0.66 (0.40, 1.08) | 1.05 (0.85, 1.30) | ||
| age | 1.07 (0.92, 1.23) | 1.32 (0.92, 1.88) | ||
| BMI | 0.99 (0.90, 1.08) | |||
| SES (ref: low) | 0.59 (0.31, 1.09) | 0.60 (0.35, 1.02) | ||
| education (ref: vocational) | 0.52 (0.18, 1.49) | 1.10 (0.48, 2.54) | ||
| Psychosocial | ||||
| self-efficacy | 0.27 (0.18, 0.42)*** | 0.42 (0.30, 0.60)*** | 1.48 (1.26, 1.72)*** | |
| social norm | 0.64 (0.50, 0.82)*** | 0.62 (0.51, 0.77)*** | ||
| perceived benefits | 0.90 (0.61, 1.32) | |||
| perceived barriers | 1.63 (0.99, 2.67) | 1.20 (0.79, 1.83) | ||
| Environmental | ||||
| residential density | 1.22 (0.88, 1.69) | 1.24 (0.94, 1.62) | 0.86 (0.76, 0.97)* | |
| land use mix diversity | 1.29 (0.94, 1.78) | |||
| land use mix access | 0.75 (0.39, 1.46) | 0.64 (0.36, 1.13) | ||
| street connectivity | 0.70 (0.39, 1.27) | |||
| walking and cycling facilities | 1.06 (0.82, 1.36) | |||
| safety from crime | 0.77 (0.50, 1.18) | 0.87 (0.60, 1.25) | 0.75 (0.63, 0.89)** | |
| distance | 1.05 (1.02, 1.07)*** | |||
OR = odds ratio; CI = confidence interval;
* p<0.05,
** p<0.01,
*** p<0.001.
a OR of being non-participant in cycling to school;
b OR of being non-participant in cycling 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 cycling to school or to other destinations (logit model). Simultaneously, among participants who did cycle to school or to other destinations, ZINB models evaluate the correlates of weekly minutes cycling to school or to other destinations (negative binomial model). Negative binomial model parameters represent the proportional increase in minutes/week cycling to school or to other destinations with a one-unit increase in the predictor.