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The United Nation’s sustainable development goals (SDGs) are interconnected and indivisible and need to be addressed in a systematic and holistic way. However, a lack of stakeholder perspective, fragmented responses, and a dearth of integration across sectors have long been perceived as the SDGs’ main pitfalls. In recent years, scholars are calling to address these issues by adopting a systems engineering perspective, as this approach espouses a stakeholder-focused position, embraces a holistic and dynamic mindset, and provides a variety of technical and managerial toolkits, which can help to untangle the complexity and interactions inherent in global sustainability. Nevertheless, little has been done to map the existing literature, comprehensively review, and synthesize research evidence in this field. Therefore, this paper aims to conduct a scoping study that analyzes the extant evidence to uncover the contributions of systems engineering in advancing the SDGs. A three-phase methodology integrating natural language processing and systematic literature review is used to investigate this space. We conclude that systems engineering has been an active catalyst promoting the SDGs, and that systems engineering has the potential to support more transdisciplinary research to achieve long-term transformational and sustainable change across sectors and disciplines.

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PurposeThe purpose of the Irish dual-energy X-ray absorptiometry (DXA) Health Informatics Prediction (HIP) for Osteoporosis Project is to create a large retrospective cohort of adults in Ireland to examine the validity of DXA diagnostic classification, risk assessment tools and management strategies for osteoporosis and osteoporotic fractures for our population.ParticipantsThe cohort includes 36 590 men and women aged 4–104 years who had a DXA scan between January 2000 and November 2018 at one of 3 centres in the West of Ireland.Findings to date36 590 patients had at least 1 DXA scan, 6868 (18.77%) had 2 scans and 3823 (10.45%) had 3 or more scans. There are 364 unique medical disorders, 186 unique medications and 46 DXA variables identified and available for analysis. The cohort includes 10 349 (28.3%) individuals who underwent a screening DXA scan without a clear fracture risk factor (other than age), and 9947 (27.2%) with prevalent fractures at 1 of 44 skeletal sites.Future plansThe Irish DXA HIP Project plans to assess current diagnostic classification and risk prediction algorithms for osteoporosis and fractures, identify the risk predictors for osteoporosis and develop novel, accurate and personalised risk prediction tools, by using the large multicentre longitudinal follow-up cohort. Furthermore, the dataset may be used to assess, and possibly support, multimorbidity management due to the large number of variables collected in this project.

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