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Updated: Jun 10, 2025

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments
Published on: August 8, 2019
Associations between neighborhood factors and insomnia and their spatial clustering in Philadelphia, Pennsylvania
Foster Osei Baah1, Augustine Cassis Obeng Boateng2, Janeese A Brownlow3
1Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, Georgia, USA.
Background:
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.
Methods:
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.
Results:
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.
Conclusion:
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.
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