Does investing in low-income urban neighborhoods improve sleep?

STUDY OBJECTIVES: Neighborhood disadvantage is associated with poor sleep, which may contribute to and exacerbate racial and socioeconomic health disparities. Most prior work has been cross-sectional and thus it has not been possible to estimate causal effects. METHODS: We leveraged a natural experiment opportunity in two low-income, predominantly African American Pittsburgh, PA neighborhoods, following a randomly selected cohort of households (n = 676) between 2013 and 2016. One of the neighborhoods received substantial public and private investments (housing, commercial) over the study period, while the other socio-demographically similar neighborhood received far fewer investments. Primary analyses used a difference-in-difference analysis based on neighborhood, to examine changes in actigraphy-assessed sleep duration, efficiency, and wakefulness after sleep onset (WASO), and self-reported sleep quality. Secondary analyses examined whether residents' proximity to investments, regardless of neighborhood, was associated with changes in sleep outcomes. RESULTS: Resident sleep worsened over time in both neighborhoods with no significant differences among residents between the two neighborhoods. Secondary analyses, including covariate adjustment and propensity score weighting to improve comparability, indicated that regardless of neighborhood, those who lived in closer proximity to investments (<0.1 mile) were significantly less likely to experience decreases in sleep duration, efficiency, and quality, or increases in WASO, compared to those who lived farther away. CONCLUSIONS: While we did not observe sleep differences among residents between neighborhoods, living closer to a neighborhood investment was associated with better sleep outcomes. Findings have relevance for public health and policy efforts focused on investing in historically disinvested neighborhoods.

Development of a Control-Oriented Model of Social Cognitive Theory for Optimized mHealth Behavioral Interventions.

Mobile health (mHealth) technologies are contributing to the increasing relevance of control engineering principles in understanding and improving health behaviors, such as physical activity. Social Cognitive Theory (SCT), one of the most influential theories of health behavior, has been used as the conceptual basis for behavioral interventions for smoking cessation, weight management, and other health-related outcomes. This paper presents a control-oriented dynamical systems model of SCT based on fluid analogies that can be used in system identification and control design problems relevant to the design and analysis of intensively adaptive interventions. Following model development, a series of simulation scenarios illustrating the basic workings of the model are presented. The model's usefulness is demonstrated in the solution of two important practical problems: 1) semiphysical model estimation from data gathered in a physical activity intervention (the MILES study) and 2) as a means for discerning the range of "ambitious but doable" daily step goals in a closed-loop behavioral intervention aimed at sedentary adults. The model is the basis for ongoing experimental validation efforts, and should encourage additional research in applying control engineering technologies to the social and behavioral sciences.

Neighborhood disadvantage is associated with actigraphy-assessed sleep continuity and short sleep duration.

Study Objectives: Neighborhood disadvantage has been linked to poor sleep. However, the extant research has primarily focused on self-reported assessments of sleep and neighborhood characteristics. The current study examines the association between objective and perceived neighborhood characteristics and actigraphy-assessed sleep duration, efficiency, and wakefulness after sleep onset (WASO) in an urban sample of African American adults. Methods: We examined data from predominantly African American adults (n = 788, mean age 55 years; 77% female) living in two low-income neighborhoods. Perceived neighborhood characteristics included safety, social cohesion, and satisfaction with one's neighborhood as a place to live. Objective neighborhood conditions included walkability, disorder, street lighting, and crime levels. Sleep duration, efficiency, and WASO were measured via 7 days of wrist-worn actigraphy. Analyses estimated each of the sleep outcomes as a function of perceived and objective neighborhood characteristics. Individual-level sociodemographics, body mass index, and psychological distress were included as covariates. Results: Greater perceived safety was associated with higher sleep efficiency and shorter WASO. Greater neighborhood disorder and street lighting were associated with poorer sleep efficiency and longer WASO and greater likelihood of short sleep duration (<7 versus 7-9 hr as referent). Higher levels of crime were associated with poorer sleep efficiency and longer WASO, but these associations were only evident in one of the neighborhoods. Conclusions: Both how residents perceive their neighborhood and their exposure to objectively measured neighborhood disorder, lighting, and crime have implications for sleep continuity. These findings suggest that neighborhood conditions may contribute to disparities in sleep health.