Battalio Samuel L, Barrett Benjamin W, Arnaoudova Ivelina I, Press David J, Hedeker Donald, Pfammatter Angela Fidler, Kershaw Kiarri N, Spring Bonnie
Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
The Center for Health Information Partnerships, Institute of Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
J Behav Med. 2024 Dec;47(6):965-979. doi: 10.1007/s10865-024-00505-2. Epub 2024 Aug 7.
To evaluate whether the neighborhood social and built environment moderates response to a mobile health multiple health behavior change intervention targeting fruit/vegetable intake, sedentary behavior, and physical activity.
Participants were 156 Chicago-residing adults with unhealthy lifestyle behaviors. Using linear mixed models, we evaluated whether access to food facilities (fast food restaurants and grocery stores) and recreational activity spaces (gyms and parks) moderated the difference in behavior change between the active intervention condition relative to control. Using spatial data analysis (cross K functions), we also assessed whether participants who achieved goal levels of behaviors ("responders") were more or less likely than those who did not achieve intervention goals ("non-responders") to reside near fast food restaurants, grocery stores, gyms, or parks.
According to linear mixed models, none of the neighborhood social and built environment factors moderated the difference in behavior change between the active intervention condition and the control condition (Likelihood Ratio (χ²[1] = 0.02-2.33, P-values > 0.05). Cross K functions showed that diet behavior change responders were more likely than non-responders to reside near fast food restaurants, but not grocery stores. The results for activity behavior change were more variable. Sedentary screen time responders were more likely to reside around recreational activity spaces than non-responders. Moderate-vigorous physical activity responders had greater and lesser clustering than non-responders around parks, dependent upon distance from the park to participant residence.
A complex relationship was observed between residential proximity to Chicago facilities and response to multiple health behavior change intervention. Replication across diverse geographic settings and samples is necessary.
评估社区社会和建筑环境是否会调节针对水果/蔬菜摄入量、久坐行为和体育活动的移动健康多健康行为改变干预措施的效果。
研究对象为156名居住在芝加哥且生活方式不健康的成年人。我们使用线性混合模型评估了食品设施（快餐店和杂货店）和娱乐活动空间（健身房和公园）的可达性是否会调节积极干预组与对照组之间行为改变的差异。我们还使用空间数据分析（交叉K函数）评估了达到行为目标水平的参与者（“响应者”) 比未达到干预目标的参与者（“无响应者”）居住在快餐店、杂货店、健身房或公园附近的可能性是更高还是更低。
根据线性混合模型，社区社会和建筑环境因素均未调节积极干预组与对照组之间行为改变的差异（似然比(χ²[1] = 0.02 - 2.33，P值>0.05）。交叉K函数显示，饮食行为改变的响应者比无响应者更有可能居住在快餐店附近，但在杂货店附近则不然。活动行为改变的结果更具可变性。久坐屏幕时间的响应者比无响应者更有可能居住在娱乐活动空间周围。中度至剧烈体育活动的响应者在公园周围的聚集程度比无响应者更高或更低，这取决于公园与参与者住所的距离。
观察到居住在芝加哥设施附近与对多种健康行为改变干预的反应之间存在复杂关系。有必要在不同地理环境和样本中进行重复研究。
