Neighborhood social environments, healthy resources, and adult diabetes: Accounting for activity space exposures

This study broadens contextual environments to include adults' activity spaces-inside and outside the residential neighborhood-to examine how contextual exposures shape type 2 diabetes risk. We use novel longitudinal data from the Los Angeles Family and Neighborhood Survey, construct time-weighted exposure measures of adults' social-structural and healthy resource environments, and execute random effects logistic models predicting the probability of being diabetic. Results indicate that residential and activity space exposures are independently associated with adult diabetes, and that residential and activity space healthy resources combine to influence diabetes risk in synergistic ways. Living in more socioeconomically advantaged neighborhoods reduces diabetes risk, particularly when spending time in activity spaces with greater access to recreational facilities. Moreover, healthier activity space environments may compensate for living in neighborhoods devoid of healthy food options to lessen diabetes risk. Adopting an activity space framework can inform multilevel interventions aimed at alleviating type 2 diabetes and other chronic ailments.

Home sweet home? Home physical environment and inflammation in children

The home environment includes important social and physical contexts within which children develop. Poor physical home environments may be a potential source of stress for children through difficult daily experiences. Using a sub-sample from the Los Angeles Family and Neighborhood Survey (N = 425), we consider how the home physical environment affects stress-related immune system dysregulation in children ages 3-18 years. Results indicated that children in poorer quality homes had higher inflammation (measured by C-reactive protein). The associations were particularly strong for younger children. We also found that part of the home physical environment association with CRP worked through increased risk of obesity for children living in low-quality homes. Future research should assess how home physical environments could be improved to reduce stress and improve health outcomes in children.

Empirical Reference Distributions for Networks of Different Size

Network analysis has become an increasingly prevalent research tool across a vast range of scientific fields. Here, we focus on the particular issue of comparing network statistics, i.e. graph-level measures of network structural features, across multiple networks that differ in size. Although "normalized" versions of some network statistics exist, we demonstrate via simulation why direct comparison is often inappropriate. We consider normalizing network statistics relative to a simple fully parameterized reference distribution and demonstrate via simulation how this is an improvement over direct comparison, but still sometimes problematic. We propose a new adjustment method based on a reference distribution constructed as a mixture model of random graphs which reflect the dependence structure exhibited in the observed networks. We show that using simple Bernoulli models as mixture components in this reference distribution can provide adjusted network statistics that are relatively comparable across different network sizes but still describe interesting features of networks, and that this can be accomplished at relatively low computational expense. Finally, we apply this methodology to a collection of ecological networks derived from the Los Angeles Family and Neighborhood Survey activity location data.