The vast majority of patients with chronic respiratory disease live in low- and middle-income countries (LMICs). Paradoxically, relevant interventions often fail to be effective particularly in these settings, as LMICs lack solid evidence on how to implement interventions successfully. Therefore, we aimed to identify factors critical to the implementation of lung health interventions in LMICs, and weight their level of evidence.This systematic review followed Cochrane methodology and PRISMA reporting standards. We searched eight databases without date- or language restrictions in July 2019, and included all relevant original, peer-reviewed articles. Two researchers independently selected articles, critically appraised them (using CASP/MetaQAT), extracted data, coded factors (following CFIR), and assigned levels of confidence in the factors (via GRADE-CERQual). We meta-synthesised levels of evidence of the factors based on their frequency and the assigned level of confidence. (PROSPERO:CRD42018088687)We included 37 articles out of 9111 screened. Studies were performed across the globe in a broad range of settings. Factors identified with a high level of evidence were 1) Understanding needs of local users, 2) ensuring Compatibility of interventions with local contexts (cultures, infrastructures), 3) identifying influential stakeholders and applying Engagement strategies, 4) ensuring adequate Access to knowledge and information, and 5) addressing Resource Availability. All implementation factors and their level of evidence were synthesised in an implementation tool.To conclude, this study identified implementation factors for lung health interventions in LMICs, weighted their level of evidence, and integrated the results into an implementation tool for practice. Policymakers, non-governmental organisations, practitioners, and researchers may use this FRESH AIR Implementation tool to develop evidence-based implementation strategies for related interventions. This could increase interventions’ implementation success, thereby optimising the use of already-scarce resources and improving health outcomes.

BackgroundKnowledge creation forms an integral part of the knowledge-to-action framework aimed at bridging the gap between research and evidence-informed decision making. Although principles of science communication, data visualisation and user-centred design largely impact the effectiveness of communication, their role in knowledge creation is still limited. Hence, this article aims to provide researchers a systematic approach on how knowledge creation can be put into practice.MethodsA systematic two-phased approach towards knowledge creation was formulated and executed. First, during a preparation phase the purpose and audience of the knowledge were defined. Subsequently, a developmental phase facilitated how the content is ‘said’ (language) and communicated (channel). This developmental phase proceeded via two pathways: a translational cycle and design cycle, during which core translational and design components were incorporated. The entire approach was demonstrated by a case study.ResultsThe case study demonstrated how the phases in this systematic approach can be operationalised. It furthermore illustrated how created knowledge can be delivered.ConclusionThe proposed approach offers researchers a systematic, practical and easy-to-implement tool to facilitate effective knowledge creation towards decision-makers in healthcare. Through the integration of core components of knowledge creation evidence-informed decision making will ultimately be optimized.

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BackgroundElevated concentrations of liver enzymes have been associated with an increased risk of developing type 2 diabetes mellitus. However, it remains unclear to which specific aspects of diurnal glucose metabolism these associate most. We aimed to investigate the associations between liver enzyme concentrations and 24 h-glucose trajectories in individuals without diabetes mellitus from three independent cohorts.MethodsThis cross-sectional study included 436 participants without diabetes mellitus from the Active and Healthy Aging Study, the Switchbox Study, and the Growing Old Together Study. Fasting blood samples were drawn to measure gamma-glutamyltransferase (GGT), alanine transaminase, and aspartate transaminase. Measures of glycemia (e.g., nocturnal and diurnal mean glucose levels) and glycemic variability (e.g., mean amplitude of glucose excursions) were derived from continuous glucose monitoring. Analyses were performed separately for the three cohorts; derived estimates were additionally meta-analyzed.ResultsAfter meta-analyses of the three cohorts, elevated liver enzyme concentrations, and specifically elevated GGT concentrations, were associated with higher glycemia. More specific, participants in the highest GGT tertile (GGT ≥37.9 U/L) had a 0.39 mmol/L (95% confidence interval: 0.23, 0.56) higher mean nocturnal glucose (3:00 to 6:00 a.m.) and a 0.23 mmol/L (0.10, 0.36) higher diurnal glucose (6:00 to 0:00 a.m.) than participants in the lowest GGT tertile (GGT <21.23 U/L). However, elevated liver enzyme concentrations were not associated with a higher glycemic variability.ConclusionThough elevated liver enzyme concentrations did not associate with higher glycemic variability in participants without diabetes mellitus, specifically, elevated GGT concentrations associated with higher glycemia.