Introduction Food systems can shape dietary behaviour and obesity outcomes in complex ways. Qualitative systems mapping using causal loop diagrams (CLDs) can depict how people understand the complex dynamics, inter-relationships and feedback characteristic of food systems in ways that can support policy planning and action. To date, there has been no attempt to review this literature. The objectives of this review are to scope the extent and nature of studies using qualitative systems mapping to facilitate the development of CLDs by stakeholders to understand food environments, including settings and populations represented, key findings and the methodological processes employed. It also seeks to identify gaps in knowledge and implications for policy and practice. Methods and analysis This protocol describes a scoping review guided by the Joanna Briggs Institute manual, the framework by Khalil and colleagues and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist reporting guidelines. A search strategy was iteratively developed with two academic librarians and the research team. This strategy will be used to search six databases, including Ovid MEDLINE, Embase, EmCare, Web of Science, Scopus and ProQuest Central. Identified citations will be screened by two independent reviewers; first, by title and abstract, and then full-text articles to identify papers eligible for inclusion. The reference lists of included studies and relevant systematic reviews will be searched to identify other papers eligible for inclusion. Two reviewers will extract information from all included studies and summarise the findings descriptively and numerically. Ethics and dissemination The scoping review will provide an overview of how CLDs developed by stakeholders have been elicited to understand food environments, diet and obesity, the insights gained and how the CLDs have been used. It will also highlight gaps in knowledge and implications for policy and practice. The review will be disseminated through publication in an academic journal and conference presentations.
Place-based initiatives attempt to reduce persistent health inequities through multisectoral, cross-system collaborations incorporating multiple interventions targeted at varying levels from individuals to systems. Evaluations of these initiatives may be thought of as part of the community change process itself with a focus on real-time learning and accountability. We described the design, implementation, challenges, and initial results of an evaluation of the West Philly Promise Neighborhood, which is a comprehensive, child-focused place-based initiative in Philadelphia, Pennsylvania. Priorities for the evaluation were to build processes for and a culture of ongoing data collection, monitoring, and communication, with a focus on transparency, accountability, and data democratization; establish systems to collect data at multiple levels, with a focus on multiple uses of the data and future sustainability; and adhere to grant requirements on data collection and reporting. Data collection activities included the compilation of neighborhood-level indicators; the implementation of a program-tracking system; administrative data linkage; and neighborhood, school, and organizational surveys. Baseline results pointed to existing strengths in the neighborhood, such as the overwhelming majority of caregivers reporting that they read to their young children (86.9%), while other indicators showed areas of need for additional supports and were programmatic focuses for the initiative (e.g., about one-quarter of young children were not engaged in an early childhood education setting). Results were communicated in multiple formats. Challenges included aligning timelines, the measurement of relationship-building and other process-focused outcomes, data and technology limitations, and administrative and legal barriers. Evaluation approaches and funding models that acknowledge the importance of capacity-building processes and allow the development and measurement of population-level outcomes in a realistic timeframe are critical for measuring the success of place-based approaches.
Objective This study aimed to assess associations between neighborhood typologies classified across multiple neighborhood domains and cardiometabolic pregnancy outcomes and determine variation in effectiveness of a mindfulness‐based stress‐reduction intervention on outcomes across neighborhood types. Methods Neighborhoods of participants in the Maternal Adiposity Metabolism and Stress (MAMAS) intervention ( n = 208) were classified across dimensions of socioeconomic, food, safety, and service/resource environments using latent class analysis. The study estimated associations between neighborhood type and three cardiometabolic pregnancy outcomes—glucose tolerance (GT) during pregnancy, excessive gestational weight gain, and 6‐month postpartum weight retention (PPWR)—using marginal regression models. Interaction between neighborhood type and intervention was assessed. Results Five neighborhood types differing across socioeconomic, food, and resource environments were identified. Compared with poor, well‐resourced neighborhoods, middle‐income neighborhoods with low resources had higher risk of impaired GT (relative risk [RR]: 4.1; 95% confidence Interval [CI]: 1.1, 15.5), and wealthy, well‐resourced neighborhoods had higher PPWR (beta: 3.9 kg; 95% CI: 0.3, 7.5). Intervention effectiveness varied across neighborhood type with wealthy, well‐resourced and poor, moderately resourced neighborhoods showing improvements in GT scores. PPWR was higher in intervention compared with control groups within wealthy, well‐resourced neighborhoods. Conclusions Consideration of multidimensional neighborhood typologies revealed important nuances in intervention effectiveness on cardiometabolic pregnancy outcomes.
Background: Weight gained during childbearing has significant implications for maternal and child health. Both too much and too little weight gained during pregnancy can result in adverse outcomes. Recommendations for ideal gestational weight gain (GWG) have been developed by the Institute of Medicine, but achieving these standards remains a challenge. Better understanding of the wider context in which women experience pregnancy may aid in the development of novel interventions to improve trends in healthy GWG. Neighborhoods define one such dimension of women’s wider context that is emerging as a promising factor in this area of research. However, limited work has considered long-term exposure to neighborhood environments or the role of women’s perceptions of their neighborhood environments in relation to either inadequate or excessive GWG.Methods: This dissertation explores the associations between long- and short-term exposure to neighborhood social and socioeconomic context and GWG using data from the 1979 National Longitudinal Survey of Youth. It additionally investigates associations between objective and perceived measures of neighborhood social context in relation to GWG. The first paper investigates associations between long-term, cumulative neighborhood socioeconomic deprivation and GWG. The second paper investigates associations between objectively measured and perceptions of point-in-time neighborhood social environment and GWG. Objective neighborhood social environment is measured using neighborhood socioeconomic deprivation. Perceived neighborhood social environment is assessed from women’s self-report of problems within their neighborhood environment. The final paper in this dissertation conducts a systematic review of the literature to characterize the reporting error associated with use of self-reported, pregnancy-related weight in efforts to move the field toward developing bias correction techniques to address methodological limitations of this measure. While not directly related to understanding neighborhoods and GWG, this issue is relevant to future studies in this area that rely on self-reported weight.Conclusion: The papers included in this dissertation illustrate the importance of considering both long-term and short-term measures of neighborhood social context in order to fully understand how neighborhood environments impact inadequate and excessive GWG. In particular, long-term measures of exposure to neighborhood environments should be more fully considered in order to better understand how neighborhoods can support healthy GWG. Interventions based on this improved knowledge of the environment in which women experience weight gain during pregnancy may improve GWG outcomes and health trajectories of both mother and child. Future studies in this area may also benefit from more rigorous study of variation of reporting error in self-reported pregnancy-related weight by maternal characteristics, which will aid in the development of bias correction techniques for these widely used measures.
Racialized economic segregation, a key metric that simultaneously accounts for spatial, social and income polarization in communities, has been linked to adverse health outcomes, including morbidity and mortality. Due to the spatial nature of this metric, the association between health outcomes and racialized economic segregation could also change with space. Most studies assessing the relationship between racialized economic segregation and health outcomes have always treated racialized economic segregation as a fixed effect and ignored the spatial nature of it. This paper proposes a two–stage Bayesian statistical framework that provides a broad, flexible approach to studying the spatially varying association between premature mortality and racialized economic segregation while accounting for neighborhood–level latent health factors across US counties. The two–stage framework reduces the dimensionality of spatially correlated data and highlights the importance of accounting for spatial autocorrelation in racialized economic segregation measures, in health equity focused settings.
To model the hypothetical impact of preventing excessive gestational weight gain on midlife obesity and compare the estimated reduction with the US Healthy People 2020 goal of a 10% reduction of obesity prevalence in adults.
Mortgage discrimination refers to the systematic withholding of home mortgages from minoritized groups. In recent years, there has been an increase in empirical research investigating associations of historical and contemporary mortgage discrimination on contemporary outcomes. Investigators have used a variety of measurement methods and approaches, which may have implications for results and interpretation.
