Osei Baah Foster, Boateng Augustine Cassis Obeng, Brownlow Janeese A, So Christine J, Miller Katherine E, Gehrman Philip, Riegel Barbara
Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, Georgia, USA.
University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA.
Sleep Health. 2024 Oct 17. doi: 10.1016/j.sleh.2024.09.003.
Neighborhood-level adverse social determinants may be a risk factor for sleep health disparities. We examined the associations between neighborhood factors and insomnia and explored their spatial clustering in the city of Philadelphia, Pennsylvania.
We conducted a cross-sectional analysis of data from Philadelphia residents who participated in online screening for insomnia-related research. Participants self-reported sex, age, body mass index, anxiety, post-traumatic stress disorder, depression, and insomnia symptoms. The sample was stratified as "No Insomnia" (≤7) and "Insomnia" (>7) based on the Insomnia Severity Index (range: 0-28). Neighborhood and participant data were merged using geospatial techniques. Multiple regression models and geospatial analysis were used to identify neighborhood variables that are associated with insomnia and their spatial distribution.
The sample (N = 350) was predominantly female (53%), middle-aged (40.8 ± 13.8), overweight (body mass index=26.1 ± 5.54), and 53.7% had insomnia. The insomnia group had significantly higher depression scores (14.6 ± 5.5), a large percentage had anxiety (64.4%) and post-traumatic stress disorder symptoms (31.9%), and largely resided in high crime (p < .001) and highly deprived neighborhoods (p = .034). Within the insomnia group, a 1-point increase in the number of spiritual centers in the neighborhood was associated with lower insomnia symptoms (b=-1.02, p = .002), while a 1-point increase in depression scores (b=0.44, p < .001) and residence in a highly deprived neighborhood (b=1.49, p = .021) was associated with greater insomnia.
Disparities exist in the neighborhood determinants of insomnia and their spatial distribution in Philadelphia. Interventions targeting the spatial distribution of adverse social determinants may improve insomnia disparities.
社区层面的不良社会决定因素可能是睡眠健康差异的一个风险因素。我们研究了社区因素与失眠之间的关联,并探讨了它们在宾夕法尼亚州费城的空间聚集情况。
我们对参与失眠相关研究在线筛查的费城居民数据进行了横断面分析。参与者自我报告了性别、年龄、体重指数、焦虑、创伤后应激障碍、抑郁和失眠症状。根据失眠严重程度指数(范围:0 - 28),将样本分为“无失眠”(≤7)和“失眠”(>7)两类。使用地理空间技术将社区和参与者数据进行合并。采用多元回归模型和地理空间分析来确定与失眠相关的社区变量及其空间分布。
样本(N = 350)主要为女性(53%),中年(40.8 ± 13.8),超重(体重指数 = 26.1 ± 5.54),53.7%有失眠症状。失眠组的抑郁得分显著更高(14.6 ± 5.5),很大比例的人有焦虑(64.4%)和创伤后应激障碍症状(31.9%),并且主要居住在高犯罪率(p <.001)和高度贫困的社区(p =.034)。在失眠组中,社区内精神中心数量每增加1分与较低的失眠症状相关(b = -1.02,p =.002),而抑郁得分每增加1分(b = 0.44,p <.001)以及居住在高度贫困社区(b = 1.49,p =.021)与更严重的失眠相关。
费城失眠的社区决定因素及其空间分布存在差异。针对不良社会决定因素空间分布的干预措施可能会改善失眠差异。