Lamb Karen E, Thornton Lukar E, Olstad Dana Lee, Cerin Ester, Ball Kylie
School of Exercise and Nutrition Sciences, Deakin University, Institute for Physical Activity and Nutrition (IPAN), Geelong, Victoria, Australia.
Australian Catholic University, Institute for Health and Ageing, Melbourne, Victoria, Australia.
BMJ Open. 2017 Oct 16;7(10):e016594. doi: 10.1136/bmjopen-2017-016594.
The residential neighbourhood fast-food environment has the potential to lead to increased levels of obesity by providing opportunities for residents to consume energy-dense products. This longitudinal study aimed to examine whether change in body mass index (BMI) differed dependent on major chain fast-food outlet availability among women residing in disadvantaged neighbourhoods.
Eighty disadvantaged neighbourhoods in Victoria, Australia.
Sample of 882 women aged 18-46 years at baseline (wave I: 2007/2008) who remained at the same residential location at all three waves (wave II: 2010/2011; wave III: 2012/2013) of the Resilience for Eating and Activity Despite Inequality study.
BMI based on self-reported height and weight at each wave.
There was no evidence of an interaction between time and the number of major chain fast-food outlets within 2 (p=0.88), 3 (p=0.66) or 5 km (p=0.24) in the multilevel models of BMI. Furthermore, there was no evidence of an interaction between time and change in availability at any distance and BMI.
Change in BMI was not found to differ by residential major chain fast-food outlet availability among Victorian women residing in disadvantaged neighbourhoods. It may be that exposure to fast-food outlets around other locations regularly visited influence change in BMI. Future research needs to consider what environments are the key sources for accessing and consuming fast food and how these relate to BMI and obesity risk.
居民区的快餐环境可能会使居民有机会食用高能量密度产品,从而导致肥胖率上升。这项纵向研究旨在探讨居住在弱势社区的女性中,体重指数(BMI)的变化是否因主要连锁快餐店的分布情况而有所不同。
澳大利亚维多利亚州的80个弱势社区。
从“不平等环境下饮食与活动适应力”研究中选取了882名18 - 46岁的女性作为样本,她们在基线期(第一波:2007/2008年)、所有三个阶段(第二波:2010/2011年;第三波:2012/2013年)都居住在同一地点。
根据每次随访时自我报告的身高和体重计算得出的BMI。
在BMI的多水平模型中,没有证据表明时间与距离2公里(p = 0.88)、3公里(p = 0.66)或5公里(p = 0.24)范围内主要连锁快餐店的数量之间存在交互作用。此外,也没有证据表明时间与任何距离的快餐店分布变化和BMI之间存在交互作用。
在居住于维多利亚州弱势社区的女性中,未发现BMI的变化因居民区主要连锁快餐店的分布情况而有所不同。可能是经常前往的其他地点周围的快餐店暴露情况会影响BMI的变化。未来的研究需要考虑哪些环境是获取和消费快餐的关键来源,以及这些环境与BMI和肥胖风险之间的关系。