School of Geodesy and Geomatics, Wuhan University, Wuhan, 430079, Hubei, China.
Department of Geography, University of Oregon, Eugene, OR, 97403, USA.
Int J Health Geogr. 2019 Feb 6;18(1):4. doi: 10.1186/s12942-019-0168-x.
Active travel for utilitarian purposes contributes to total physical activity and may help counter the obesity epidemic. However, the evidence linking active travel and individual-level body weight is equivocal. Statistical modeling that accounts for spatial autocorrelation and unmeasured spatial predictors has not yet used to explore whether the health benefits of active travel are shared equally across socioeconomic groups.
Bayesian hierarchical models with spatial random effects were developed using travel survey data from Saskatoon, Canada (N = 4625). Differences in log-transformed body mass index (BMI) were estimated for levels of active travel use (vehicular travel only, mixed vehicular/active travel, and active travel only), household income, and neighbourhood deprivation after controlling for sociodemographic and physical activity variables. The modifying effect of household income on the association between active travel and BMI was also evaluated.
Significant and meaningful decreases in BMI were observed for mixed (β = - 0.02, CrI - 0.036 to - 0.004) and active only (β = - 0.043, CrI - 0.06 to - 0.025) compared to vehicular only travelers. BMI was significantly associated with levels of household income and neighbourhood deprivation. Accounting for the interaction between travel mode and household income, decreases in BMI were observed for active only compared to vehicular only travellers in the highest income category (β = - 0.061, CrI - 0.115 to - 0.007).
Strategies to increase active travel use can support healthy weight loss and maintenance, but the opportunity to benefit from active travel use may be limited by low income. Considerations should be given to how interventions to increase active transportation might exacerbate social inequalities in BMI. Spatial statistical models are needed to account for unmeasured but spatially structured neighbourhood factors.
出于实用目的的积极出行有助于增加总的身体活动量，并可能有助于对抗肥胖流行。然而，将积极出行与个体体重联系起来的证据尚无定论。尚未使用考虑空间自相关和未测量空间预测因子的统计建模来探索积极出行的健康益处是否在社会经济群体中均等共享。
使用来自加拿大萨斯卡通的出行调查数据（N=4625），开发了具有空间随机效应的贝叶斯层次模型。在控制社会人口统计学和身体活动变量后，估计了不同水平的积极出行使用（仅机动车出行、混合机动车/积极出行和仅积极出行）、家庭收入和邻里贫困对对数转换体重指数（BMI）的差异。还评估了家庭收入对积极出行与 BMI 之间关联的调节作用。
与仅机动车出行者相比，混合出行（β=-0.02，CrI -0.036 至 -0.004）和仅积极出行（β=-0.043，CrI -0.06 至 -0.025）的 BMI 显著且有意义地降低。BMI 与家庭收入和邻里贫困水平显著相关。考虑到出行模式和家庭收入之间的相互作用，与仅机动车出行者相比，高收入群体中仅积极出行者的 BMI 下降（β=-0.061，CrI -0.115 至 -0.007）。
增加积极出行使用的策略可以支持健康的体重减轻和维持，但从积极出行使用中获益的机会可能会受到低收入的限制。应该考虑如何增加积极交通干预措施可能会加剧 BMI 方面的社会不平等。需要空间统计模型来解释未测量但具有空间结构的邻里因素。
