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IntroductionFood 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 analysisThis 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 disseminationThe 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.

IntroductionPublic policymakers are increasingly engaged in participatory model building processes, such as group model building. Understanding the impacts of policymaker participation in these processes on policymakers is important given that their decisions often have significant influence on the dynamics of complex systems that affect health. Little is known about the extent to which the impacts of participatory model building on public policymakers have been evaluated or the methods and measures used to evaluate these impacts.Methods and analysisA scoping review protocol was developed with the objectives of: (1) scoping studies that have evaluated the impacts of facilitated participatory model building processes on public policymakers who participated in these processes; and (2) describing methods and measures used to evaluate impacts and the main findings of these evaluations. The Joanna Briggs Institute’s Population, Concept, Context framework was used to formulate the article identification process. Seven electronic databases—MEDLINE (Ovid), ProQuest Health and Medical, Scopus, Web of Science, Embase (Ovid), CINAHL Complete and PsycInfo—will be searched. Identified articles will be screened according to inclusion and exclusion criteria and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist for scoping reviews will be used and reported. A data extraction tool will collect information across three domains: study characteristics, methods and measures, and findings. The review will be conducted using Covidence, a systematic review data management platform.Ethics and disseminationThe scoping review produced will generate an overview of how public policymaker engagement in participatory model building processes has been evaluated. Findings will be disseminated through peer-reviewed publications and to communities of practice that convene policymakers in participatory model building processes. This review will not require ethics approval because it is not human subject research.

Pre-pregnancy body mass index (BMI) varies by race/ethnicity and modifies the association between gestational weight gain (GWG) and adverse pregnancy outcomes, which disproportionately affect racial/ethnic minorities. Yet studies investigating whether racial/ethnic disparities in GWG vary by pre-pregnancy BMI are inconsistent, and none studied nationally representative populations. Using categorical measures of GWG adequacy based on Institute of Medicine recommendations, we investigated whether associations between race/ethnicity and GWG adequacy were modified by pre-pregnancy BMI [underweight (<18.5 kg/m 2 ), normal weight (18.5–24.9 kg/m 2 ), overweight (25.0–29.9 kg/m 2 ), or obese (≥30.0 kg/m 2 )] among all births to Black, Hispanic, and White mothers in the 1979 USA National Longitudinal Survey of Youth cohort (n = 6,849 pregnancies; range 1–10). We used generalized estimating equations, adjusted for marital status, parity, smoking during pregnancy, gestational age, and multiple measures of socioeconomic position. Effect measure modification between race/ethnicity and pre-pregnancy BMI was significant for inadequate GWG (Wald test p value = 0.08). Normal weight Black [risk ratio (RR) 1.34, 95 % confidence interval (CI) 1.18, 1.52] and Hispanic women (RR 1.33, 95 % CI 1.15, 1.54) and underweight Black women (RR 1.38, 95 % CI 1.07, 1.79) experienced an increased risk of inadequate GWG compared to Whites. Differences in risk of inadequate GWG between minority women, compared to White women, were not significant among overweight and obese women. Effect measure modification between race/ethnicity and pre-pregnancy BMI was not significant for excessive GWG. The magnitude of racial/ethnic disparities in inadequate GWG appears to vary by pre-pregnancy weight class, which should be considered when designing interventions to close racial/ethnic gaps in healthy GWG.

Historical, institutional racism within the housing market may have impacted present-day disparities in heat vulnerability. We quantified associations between historically redlined areas with present-day property and housing characteristics that may enhance heat vulnerability in Philadelphia, PA. We used color-coded Home Owners Loan Corporation (HOLC) maps and tax assessment data to randomly select 100 present-day (2018–2019) residential properties in each HOLC grade area (A = Best; B, C, and D = Most hazardous; N = 400 total). We conducted virtual inventories of the properties using aerial and streetview imagery for land cover and housing characteristics (dark roof color, flat roof shape, low or no mature tree canopy, no recently planted street trees) that may enhance heat vulnerability. We used modified Poisson regression models to estimate associations of HOLC grades with the property characteristics, unadjusted and adjusted for historical and contemporary measures of the neighborhood sociodemographic environment. Compared to grade A areas, higher proportions of properties in grade B, C, and D areas had dark roofs, low/no mature tree canopy, and no street trees. Adjusting for historical sociodemographics attenuated associations, with only associations with low or no tree canopy remaining elevated. Adjusting for present-day concentrated racial and socioeconomic deprivation did not substantially impact overall findings. In Philadelphia, PA, HOLC maps serve as spatial representations of present-day housing and land cover heat vulnerability characteristics. Further analyses incorporating longitudinal data on urban redevelopment, reinvestment, and neighborhood change are needed to more fully represent complex relationships among historical racism, residential segregation, and heat vulnerability.

The purpose of this study was to use participatory systems thinking to develop a dynamic conceptual framework of racial/ethnic and other intersecting disparities (e.g., income) in food access and diet in Philadelphia and to identify policy levers to address these disparities. We conducted three group model building workshops, each consisting of a series of scripted activities. Key artifacts or outputs included qualitative system maps, or causal loop diagrams, identifying the variables, relationships, and feedback loops that drive diet disparities in Philadelphia, Pennsylvania. We used semi-structured methods informed by inductive thematic analysis and network measures to synthesize findings into a single causal loop diagram. There were twenty-nine participants with differing vantages and expertise in Philadelphia’s food system, broadly representing the policy, community, and research domains. In the synthesis model, participants identified 14 reinforcing feedback loops and one balancing feedback loop that drive diet and food access disparities in Philadelphia. The most highly connected variables were upstream factors, including those related to racism (e.g., residential segregation) and community power (e.g., community land control). Consistent with existing frameworks, addressing disparities will require a focus on upstream social determinants. However, existing frameworks should be adapted to emphasize and disrupt the interdependent, reinforcing feedback loops that maintain and exacerbate disparities in fundamental social causes. Our findings suggest that promising policies include those that empower minoritized communities, address socioeconomic inequities, improve community land control, and increase access to affordable, healthy, and culturally meaningful foods.

The purpose of this study was to use participatory systems thinking to develop a dynamic conceptual framework of racial/ethnic and other intersecting disparities (e.g., income) in food access and diet in Philadelphia and to identify policy levers to address these disparities. We conducted three group model building workshops, each consisting of a series of scripted activities. Key artifacts or outputs included qualitative system maps, or causal loop diagrams, identifying the variables, relationships, and feedback loops that drive diet disparities in Philadelphia, Pennsylvania. We used semi-structured methods informed by inductive thematic analysis and network measures to synthesize findings into a single causal loop diagram. There were twenty-nine participants with differing vantages and expertise in Philadelphia’s food system, broadly representing the policy, community, and research domains. In the synthesis model, participants identified 14 reinforcing feedback loops and one balancing feedback loop that drive diet and food access disparities in Philadelphia. The most highly connected variables were upstream factors, including those related to racism (e.g., residential segregation) and community power (e.g., community land control). Consistent with existing frameworks, addressing disparities will require a focus on upstream social determinants. However, existing frameworks should be adapted to emphasize and disrupt the interdependent, reinforcing feedback loops that maintain and exacerbate disparities in fundamental social causes. Our findings suggest that promising policies include those that empower minoritized communities, address socioeconomic inequities, improve community land control, and increase access to affordable, healthy, and culturally meaningful foods.

Small, geographically limited studies report that people with intellectual and developmental disabilities (IDD) have increased risk for serious pregnancy-related and birth-related challenges, including preeclampsia, preterm birth, and increased anxiety and depression, than their peers. United States-based population-level data among people with IDD are lacking. To identify perinatal and postpartum outcomes among a national, longitudinal sample of people with IDD enrolled in public health insurance, compare subgroups of people with IDD, and compare outcomes among people with IDD with those of peers without IDD. This retrospective cohort study used national Medicaid claims from January 1, 2008, to December 31, 2019, for 55 440 birthing people with IDD and a random sample of 438 557 birthing people without IDD. Medicaid funds almost half of all births and is the largest behavioral health insurer in the US, covering a robust array of services for people with IDD. Statistical analysis was performed from July 2023 to June 2024. People who had a documented birth in Medicaid during the study years. Perinatal outcomes were compared across groups using univariate and multivariate logistic regression. The probability of postpartum anxiety and depression was estimated using Kaplan-Meier and Cox proportional hazards regression. The study sample included 55 440 birthing people with IDD (including 41 854 with intellectual disabilities [ID] and 13 586 with autism; mean [SD] age at first delivery, 24.9 [6.7] years) and a random sample of 438 557 birthing people without IDD (mean [SD] age at first delivery, 26.4 [6.3] years). People with IDD were younger at first observed delivery, had a lower prevalence of live births (66.6% vs 76.7%), and higher rates of obstetric conditions (gestational diabetes, 10.3% vs 9.9%; gestational hypertension, 8.7% vs 6.1%; preeclampsia, 6.1% vs 4.4%) and co-occurring physical conditions (heart failure, 1.4% vs 0.4%; hyperlipidemia, 5.3% vs 1.7%; ischemic heart disease, 1.5% vs 0.4%; obesity, 16.3% vs 7.4%) and mental health conditions (anxiety disorders, 27.9% vs 6.5%; depressive disorders, 32.1% vs 7.5%; posttraumatic stress disorder, 9.5% vs 1.2%) than people without IDD. The probability of postpartum anxiety (adjusted hazard ratio [AHR], 3.2 [95% CI, 2.9-3.4]) and postpartum depression (AHR, 2.4 [95% CI, 2.3-2.6]) was significantly higher among autistic people compared with people with ID only and people without IDD. In this retrospective cohort study, people with IDD had a younger mean age at first delivery, had lower prevalence of live births, and had poor obstetric, mental health, and medical outcomes compared with people without IDD, pointing toward a need for clinician training and timely delivery of maternal health care. Results highlight needed reproductive health education, increasing clinician knowledge, and expanding Medicaid to ensure access to care for people with IDD.

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.

BackgroundChildren belonging to the same birth cohort (i.e., born in the same year) experience shared exposure to a common obesity-related milieu during the critical early years of development—e.g., secular beliefs and feeding practices, adverse chemical exposures, food access and nutrition assistance policies—that set the stage for a shared trajectory of obesity as they mature. Fundamental cause theory suggests that inequitable distribution of recent efforts to stem the rise in child obesity may exacerbate cohort-based disparities over time.MethodsData were from electronic health records spanning 2007–2016 linked to birth records for children ages 2–19 years. We used hierarchical age-period-cohort models to investigate cohort effects on disparities in obesity related to maternal education. We hypothesized that maternal education-based disparities in prevalence of obesity would be larger among more recent birth cohorts.ResultsSex-stratified models adjusted for race/ethnicity showed substantial obesity disparities by maternal education that were evident even at young ages: prevalence among children with maternal education < high school compared to maternal college degree was approximately three times as high among girls and twice as high among boys. For maternal education < high school, disparities compared to maternal college degree were higher in more recent birth cohorts. Among girls, this disparity cohort effect was evident at younger ages (at age 4, the disparity increased by 4 [0.1–8] percentage points per 5 birth years), while among boys it was larger at older ages (at age 16, the disparity increased by 7 [1–14] percentage points per 5 birth years).ConclusionsThere may be widening maternal education-based disparities in child obesity by birth cohort at some ages.

Objectives. 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. Methods. We analyzed 3917 women with 1 to 3 pregnancies in the prospective US National Longitudinal Survey of Youth, from 1979 to 2012. We compared the estimated obesity prevalence between 2 scenarios: gestational weight gain as reported and under the scenario of a hypothetical intervention that all women with excessive gestational weight gain instead gained as recommended by the Institute of Medicine (2009). Results. A hypothetical intervention was associated with a significantly reduced estimated prevalence of obesity for first (3.3 percentage points; 95% confidence interval [CI] = 1.0, 5.6) and second (3.0 percentage points; 95% CI = 0.7, 5.2) births, and twice as high in Black as in White mothers, but not significant in Hispanics. The population attributable fraction was 10.7% (95% CI = 3.3%, 18.1%) in first and 9.3% (95% CI = 2.2%, 16.5%) in second births. Conclusions. Development of effective weight-management interventions for childbearing women could lead to meaningful reductions in long-term obesity.