Gestational diabetes mellitus (GDM) affects approximately 5 to 7% of pregnancies and is associated with increased risk for fetal overgrowth, cesarean delivery, birth trauma, and pre-eclampsia. GDM is commonly diagnosed in the US using a two-step screening and confirmatory approach, whereas a one-step approach is commonly used outside the US. Recent guidelines have suggested that the one-step approach should be used to diagnose GDM, although concern that this may increase the prevalence of GDM to approximately 18%--as well as the lack of clinical trials-based evidence regarding the difference in perinatal outcomes--has led to skepticism about adopting the one-step approach. The Comparison of Two Screening Strategies for Gestational Diabetes (GDM2) Trial is a single-center, parallel-arm, comparative effectiveness trial of one-step versus two-step GDM screening strategies on the rate of adverse perinatal outcomes including: large-for-gestational age (LGA) deliveries (primary outcome), small-for-gestational age (SGA), macrosomia, cesarean delivery, fetal growth and body composition, and maternal and neonatal composite outcomes. This paper describes the design and analysis plan of the GDM2 Trial as well as overall challenges in assessing the impact of screening and diagnosis strategy on adverse pregnancy outcomes. We will also assess whether the additional women diagnosed with the onestep approach benefit from treatment as assessed by metabolic profiles at one year postpartum. Ultimately, this study will provide the necessary evidence for establishing universal guidelines for GDM diagnosis and implementation into clinical care.

The purpose of this study was to examine the neighborhood environment and the association with weight change among overweight/obese individuals in the first six months of a 12-month weight loss intervention, EMPOWER, from 2011 to 2015. Measures of the neighborhood environment included neighborhood racial composition, neighborhood income, and neighborhood food retail stores density (e.g., grocery stores). Weight was measured at baseline and 6 months and calculated as the percent weight change from baseline to 6 months. The analytic sample (N = 127) was 91% female and 81% white with a mean age of 51 (± 10.4) years. At 6 months, the mean weight loss was 8.0 kg (± 5.7), which was equivalent to 8.8% (± 6%) of baseline weight. Participants living in neighborhoods in which 25–75% of the residents identified as black had the greatest percentage of weight loss compared to those living in neighborhoods with < 25% or > 75% black residents. No other neighborhood measures were associated with weight loss. Future studies testing individual-level behavioral weight loss interventions need to consider the influence of neighborhood factors, and how neighborhood-level interventions could be enhanced with individual-level interventions that address behaviors and lifestyle changes.

This article summarizes and reviews the cross-discipline literature on violent crime in destination neighborhoods postrelocation in order to build a more comprehensive picture of risk factors for violence, as well as how and why housing policies influence risk of violence. High rates of violent crime continue to be a persistent problem in areas of concentrated poverty and public housing. Modern housing programs such as Moving to Opportunity and Housing Opportunities for People Everywhere are popular interventions for reducing the density of low-income people receiving public housing assistance by relocating residents of distressed housing projects. However, evidence suggests that relocated residents may not experience less violence or improved safety in their new communities.

Abstract. Commercial data sources have been increasingly used to measure and locate community resources. We describe a methodology for combining and comparing the differences in commercial data of the food and alcohol environment. We used commercial data from two commercial databases (InfoUSA and Dun&Bradstreet) for 2003 and 2009 to obtain information on food and alcohol establishments and developed a matching process using computer algorithms and manual review by applying ArcGIS to geocode addresses, standard industrial classification and North American industry classification taxonomy for type of establishment and establishment name. We constructed population and area-based density measures (e.g. grocery stores) and assessed differences across data sources and used ArcGIS to map the densities. The matching process resulted in 8,705 and 7,078 unique establishments for 2003 and 2009, respectively. There were more establishments captured in the combined dataset than relying on one data source alone, and the additional establishments captured ranged from 1,255 to 2,752 in 2009. The correlations for the density measures between the two data sources was highest for alcohol outlets (r = 0.75 and 0.79 for per capita and area, respectively) and lowest for grocery stores/supermarkets (r = 0.32 for both). This process for applying geographical information systems to combine multiple commercial data sources and develop measures of the food and alcohol environment captured more establishments than relying on one data source alone. This replicable methodology was found to be useful for understanding the food and alcohol environment when local or public data are limited.