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This study investigates the connection between antimicrobial resistance (AMR) and climate change across diverse global regions. The study focuses on Mexico, Southeast Asia, and Canada. By analyzing how regional climatic conditions such as temperature, humidity, and seasonal weather patterns influence AMR dynamics, the research can address the critical question of how to tackle AMR. Based on the global escalation of AMR and its profound implications for public health, our study is vital in highlighting the necessity for integrated climate change mitigation strategies within AMR management. The findings emphasize the urgency of surveillance, targeted research, and enforcing strict antimicrobial stewardship to counteract the rising threat of AMR, thereby informing more effective global health responses and policy-making in an era of significant environmental change.

Purpose: To discuss the utility of and value of the use of logic models for program evaluation of community-based programs and more specifically, the integration of logic models and factor analysis to develop and revise a survey as part of an effective evaluation plan. Principal results: Diverse stakeholders with varying outlooks used a logic model as a framework to reach agreement on a plan for a state-wide evaluation. This evaluation plan utilized a survey of sixth grade students, administered before and after exposure to a year-long abstinence education program. Components of the logic model were linked to specific survey questions. Exploratory factor analysis was then used to assess whether and how the questions in the survey fit with the constructs of the model; confirmatory factor analysis was used to test the hypothesis that the factors identified in the exploratory analysis were consistently represented in the survey. Major conclusions: A logic model is a tool that engages stakeholders to link evaluation instruments more closely to specific program objectives. Thus, stakeholders can more closely assess the extent to which project outcomes have been achieved. In addition, use of factor analysis in the evaluation process can help the stakeholders better understand whether evaluation instruments such as a survey adequately assess program effectiveness. Lastly, a logic model process can help to achieve consensus among diverse stakeholders, by allowing them to focus on objectives that are concrete, measurable, and mutually acceptable. (Contains 2 figures and 5 tables.)

INNOVATION Food insecurity is consistently associated with negative health outcomes, (1) and health systems are increasingly interested in addressing the social determinants of health, including food access, within the clinical [...]

Abstract Background Individual and community health are adversely impacted by disparities in health outcomes among disadvantaged and vulnerable populations. Understanding the underlying causes for variations in health outcomes is an essential step towards developing effective interventions to ameliorate inequalities and subsequently improve overall community health. Working at the neighborhood scale, this study examines multiple social determinates that can cause health disparities including low neighborhood wealth, weak social networks, inadequate public infrastructure, the presence of hazardous materials in or near a neighborhood, and the lack of access to primary care services. The goal of this research is to develop innovative and replicable strategies to improve community health in disadvantaged communities such as newly arrived Hispanic immigrants. Methods/design This project is taking place within a primary care practice-based research network (PBRN) using key principles of community-based participatory research (CBPR). Associations between social determinants and rates of hospitalizations, emergency department (ED) use, and ED use for primary care treatable or preventable conditions are being examined. Geospatial models are in development using both hospital and community level data to identify local areas where interventions to improve disparities would have the greatest impact. The developed associations between social determinants and health outcomes as well as the geospatial models will be validated using community surveys and qualitative methods. A rapidly growing and underserved Hispanic immigrant population will be the target of an intervention informed by the research process to impact utilization of primary care services and designed, deployed, and evaluated using the geospatial tools and qualitative research findings. The purpose of this intervention will be to reduce health disparities by improving access to, and utilization of, primary care and preventative services. Discussion The results of this study will demonstrate the importance of several novel approaches to ameliorating health disparities, including the use of CBPR, the effectiveness of community-based interventions to influence health outcomes by leveraging social networks, and the importance of primary care access in ameliorating health disparities.

Abstract Background The Charlotte-Mecklenburg region has one of the fastest growing Hispanic communities in the country. This population has experienced disparities in health outcomes and diminished ability to access healthcare services. This city is home to an established practice-based research network (PBRN) that includes community representatives, health services researchers, and primary care providers. The aims of this project are: to use key principles of community-based participatory research (CBPR) within a practice-based research network (PBRN) to identify a single disease or condition that negatively affects the Charlotte Hispanic community; to develop a community-based intervention that positively impacts the chosen condition and improves overall community health; and to disseminate findings to all stakeholders. Methods/design This project is designed as CBPR. The CBPR process creates new social networks and connections between participants that can potentially alter patterns of healthcare utilization and other health-related behaviors. The first step is the development of equitable partnerships between community representatives, providers, and researchers. This process is central to the CBPR process and will occur at three levels -- community members trained as researchers and outreach workers, a community advisory board (CAB), and a community forum. Qualitative data on health issues facing the community -- and possible solutions -- will be collected at all three levels through focus groups, key informant interviews and surveys. The CAB will meet monthly to guide the project and oversee data collection, data analysis, participant recruitment, implementation of the community forum, and intervention deployment. The selection of the health condition and framework for the intervention will occur at the level of a community-wide forum. Outcomes of the study will be measured using indicators developed by the participants as well as geospatial modeling. On completion, this study will: determine the feasibility of the CBPR process to design interventions; demonstrate the feasibility of geographic models to monitor CBPR-derived interventions; and further establish mechanisms for implementation of the CBPR framework within a PBRN.