Weight management during teenage pregnancy: Issues to consider when developing appropriate support

Teenage pregnancy is more prevalent in areas of high obesity, compared to areas where obesity levels are low. Risks associated with maternal obesity in pregnant teenagers include pre-eclampsia and caesarean delivery. To reduce these risks, pregnant teenagers need to be supported to gain a healthy weight in pregnancy. This includes encouraging these women to eat healthily through providing appropriate information including online or smartphone apps in conjunction with face-to-face support. These young women also need encouragement to be physically active. This support must be tailored to the teenage population considering their specific barriers and facilitators to behaviour change. Midwives with the aid of a multidisciplinary team play a key role in encouraging these healthy behaviours

Mapping out a One Health model of antimicrobial resistance in the context of the Swedish food system: A literature scan

Background: Antimicrobial resistance (AMR) causes worsening health, environmental, and financial burdens. Modeling complex issues such as AMR is important, however, how well such models and data cover the broader One Health system is unknown. Our study aimed to identify models of AMR across the One Health system (objective 1), and data to parameterize such models (objective 2) to inform a future model of the AMR in the Swedish One Health system. Methods: Based on an expert-derived qualitative description of the system, an extensive literature scan was performed to identify models and data from peer-reviewed and grey literature sources. Models and data were extracted, categorized in an Excel database, and visually represented on the existing qualitative model to illustrate coverage. Results: Articles described 106 models in various parts of the One Health system; 54 were AMR specific. Few multi-level, multi-sector models, and models within the animal and environmental sectors, were identified. We identified 414 articles containing data to parameterize the models. Data gaps included the environment and broad, ill-defined, or abstract ideas (e.g., human behaviour). Conclusions: No models addressed the entire system, and many data gaps were found. Existing models could be integrated into a mixed-methods model in the interim.</p

Is scientific evidence enough? Using expert opinion to fill gaps in data in antimicrobial resistance research

Background Antimicrobial Resistance (AMR) is a global problem with large health and economic consequences. Current gaps in quantitative data are a major limitation for creating models intended to simulate the drivers of AMR. As an intermediate step, expert knowledge and opinion could be utilized to fill gaps in knowledge for areas of the system where quantitative data does not yet exist or are hard to quantify. Therefore, the objective of this study was to identify quantifiable data about the current state of the factors that drive AMR and the strengths and directions of relationships between the factors from statements made by a group of experts from the One Health system that drives AMR development and transmission in a European context. Methods This study builds upon previous work that developed a causal loop diagram of AMR using input from two workshops conducted in 2019 in Sweden with experts within the European food system context. A secondary analysis of the workshop transcripts was conducted to identify semi-quantitative data to parameterize drivers in a model of AMR. Main findings Participants spoke about AMR by combining their personal experiences with professional expertise within their fields. The analysis of participants’ statements provided semi-quantitative data that can help inform a future of AMR emergence and transmission based on a causal loop diagram of AMR in a Swedish One Health system context. Conclusion Using transcripts of a workshop including participants with diverse expertise across the system that drives AMR, we gained invaluable insight into the past, current, and potential future states of the major drivers of AMR, particularly where quantitative data are lacking.</p

Is scientific evidence enough? Using expert opinion to fill gaps in data in antimicrobial resistance research

Background Antimicrobial Resistance (AMR) is a global problem with large health and economic consequences. Current gaps in quantitative data are a major limitation for creating models intended to simulate the drivers of AMR. As an intermediate step, expert knowledge and opinion could be utilized to fill gaps in knowledge for areas of the system where quantitative data does not yet exist or are hard to quantify. Therefore, the objective of this study was to identify quantifiable data about the current state of the factors that drive AMR and the strengths and directions of relationships between the factors from statements made by a group of experts from the One Health system that drives AMR development and transmission in a European context. Methods This study builds upon previous work that developed a causal loop diagram of AMR using input from two workshops conducted in 2019 in Sweden with experts within the European food system context. A secondary analysis of the workshop transcripts was conducted to identify semi-quantitative data to parameterize drivers in a model of AMR. Main findings Participants spoke about AMR by combining their personal experiences with professional expertise within their fields. The analysis of participants’ statements provided semi-quantitative data that can help inform a future of AMR emergence and transmission based on a causal loop diagram of AMR in a Swedish One Health system context. Conclusion Using transcripts of a workshop including participants with diverse expertise across the system that drives AMR, we gained invaluable insight into the past, current, and potential future states of the major drivers of AMR, particularly where quantitative data are lacking

Using a fuzzy cognitive map to assess interventions to reduce antimicrobial resistance in a Swedish One Health system context under potential climate change conditions

Abstract Introduction: Antimicrobial resistance (AMR) is a growing One Health crisis that can be impacted by other challenges of sustainable development, such as climate change, but few interventions have been assessed with a systems-wide lens. The objectives of this study were to use a previously defined fuzzy cognitive map (FCM) of the Swedish One Health system to: 1) identify areas in the system to target interventions; and 2) test the potential ability and viability of interventions to reduce AMR under a changing climate. Methods: The FCM, based on participatory modelling workshops and literature scan, was used to assess the sustainability of eight interventions under potential climate change conditions. Network metrics were calculated to describe the system structure and identify highly impactful nodes. Results: The network metrics identified high-leverage nodes including alternative productions systems and good farming practices. None of the scenarios evaluated were able to adequately reduce AMR within the system. Conclusions: Overall, fuzzy cognitive mapping provides an innovative way to analyse the AMR system, identify high-leverage interventions, and examine potential impact of interventions using a broader systems lens.</p