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A 2013 systematic review and Delphi consensus study identified 12 modifiable risk and protective factors for dementia, which were subsequently merged into the "LIfestyle for BRAin health" (LIBRA) score. We systematically evaluated whether LIBRA requires revision based on new evidence. To identify modifiable risk and protective factors suitable for dementia risk reduction, we combined an umbrella review of systematic reviews and meta‐analyses with a two‐round Delphi consensus study. The review of 608 unique primary studies and opinions of 18 experts prioritized six modifiable factors: hearing impairment, social contact, sleep, life course inequalities, atrial fibrillation, and psychological stress. Based on expert ranking, hearing impairment, social contact, and sleep were considered the most suitable candidates for inclusion in updated dementia risk scores. As such, the current study shows that dementia risk scores need systematic updates based on emerging evidence. Future studies will validate the updated LIBRA score in different cohorts. Highlights: An umbrella review was combined with opinions of 18 dementia experts.Various candidate targets for dementia risk reduction were identified.Experts prioritized hearing impairment, social contact, and sleep.Re‐assessment of dementia risk scores is encouraged.Future work should evaluate the predictive validity of updated risk scores. [ABSTRACT FROM AUTHOR]

The article discusses the urgent need for global action to address the environmental crisis and protect health. The editors of health journals worldwide are calling for measures to limit global temperature increases, halt the destruction of nature, and mitigate the harmful effects on health. The risks of temperature increases above 1.5°C are well-established, with adverse impacts on mortality, mental health, pregnancy, and vulnerable populations. The destruction of nature also threatens food security and increases the risk of pandemics. The article emphasizes the need for equitable and fundamental changes to societies, as well as global coordination and cooperation. Wealthy nations must take the lead in reducing emissions, supporting low- and middle-income countries, and providing funding for mitigation and adaptation efforts. The article concludes by urging governments and leaders to take immediate action to create a sustainable, fairer, and healthier world. [Extracted from the article]

The authors offer observation on efforts to tackle the global environmental crisis as global temperature increases. Topics discussed include reason the promise by many countries to protect at least 30 percent of the world's land and oceans by 2030 are not enough, how wealthy nations can contribute to tackling the environmental crisis, and global threat to global public health.

Background: Count scores, disease clustering, and pairwise associations between diseases remain ubiquitous in multimorbidity research despite two major shortcomings: they yield no insight into plausible mechanisms underlying multimorbidity, and they ignore higher-order interactions such as effect modification. Objectives: We argue that two components are currently missing but vital to develop novel multimorbidity metrics. Firstly, networks should be constructed which consists simultaneously of signs, symptoms, and diseases, since only then could they yield insight into plausible shared biological mechanisms underlying diseases. Secondly, learning pairwise associations is insufficient to fully characterize the correlations in a system. That is, synergistic (e.g., cooperative or antagonistic) effects are widespread in complex systems, where two or more elements combined give a larger or smaller effect than the sum of their individual effects. It can even occur that pairs of symptoms have no pairwise associations whatsoever, but in combination have a significant association. Therefore, higherorder interactions should be included in networks used to study multimorbidity, resulting in so-called hypergraphs. Methods: We illustrate our argument using a synthetic Bayesian Network model of symptoms, signs and diseases, composed of pairwise and higher-order interactions. We simulate network interventions on both individual and population levels and compare the ground-truth outcomes with the predictions from pairwise associations. Conclusion: We find that, when judged purely from the pairwise associations, interventions can have unexpected "side-effects" or the most opportune intervention could be missed. The hypergraph uncovers links missed in pairwise networks, giving a more complete overview of sign and disease associations. [ABSTRACT FROM AUTHOR]

Introduction: In Alzheimer's disease (AD), cognitive decline is driven by various interlinking causal factors. Systems thinking could help elucidate this multicausality and identify opportune intervention targets. Methods: We developed a system dynamics model (SDM) of sporadic AD with 33 factors and 148 causal links calibrated with empirical data from two studies. We tested the SDM's validity by ranking intervention outcomes on 15 modifiable risk factors to two sets of 44 and 9 validation statements based on meta‐analyses of observational data and randomized controlled trials, respectively. Results: The SDM answered 77% and 78% of the validation statements correctly. Sleep quality and depressive symptoms yielded the largest effects on cognitive decline with which they were connected through strong reinforcing feedback loops, including via phosphorylated tau burden. Discussion: SDMs can be constructed and validated to simulate interventions and gain insight into the relative contribution of mechanistic pathways. [ABSTRACT FROM AUTHOR]

Introduction: Care integration in primary elderly care is suboptimal. Validated instruments are needed to enable the implementation of integrated primary care. We aimed to assess construct validity of the Rainbow Model of Integrated Care measurement tool (RMIC-MT) for healthcare professionals working in an integrated primary elderly care setting in the Netherlands. Methods: In a cross-sectional study, the RMIC-MT, a 36-item questionnaire covering all domains of the Rainbow Model of Integrated Care (RMIC), was sent out to local networks of primary elderly care professionals. Confirmatory factor analysis with maximum likelihood estimation was used for the validation of the factor structure the RMIC-MT. Model fit was assessed by the chi-square test and fit indices. Results: The RMIC-MT was completed by 323 professionals, primarily general practitioners, community nurses, practice nurses, and case managers. Confirmatory factor analysis and corresponding fit indices showed moderate to good fit, thereby confirming a nine factor model with a total of 36 items. Conclusions: The RMIC-MT is promising for the primary elderly care setting in the Netherlands. It can be used for evaluating integrated care initiatives in a primary care setting, thereby contributing to implementation of integrated primary elderly care. [ABSTRACT FROM AUTHOR]

Call for emergency action to limit global temperature increases, restore biodiversity, and protect health: Wealthy nations must do much more, much faster† The UN General Assembly in September 2021 will bring countries together at a critical time for marshalling collective action to tackle the global environmental crisis. Google Scholar Crossref Search ADS PubMed WorldCat 23 Paremoer L, Nandi S, Serag H, Baum F. Covid-19 pandemic and the social determinants of health. Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC 15 Anderson K, Peters G. The trouble with negative emissions. [Extracted from the article]

The article presents the discussion on limiting global temperature increase and restoring biodiversity and protecting health . Topics include health already being harmed by global temperature increase and the destruction of the natural world, a state of affairs health professionals; and disproportionately on the most vulnerable breeding more conflict, food insecurity, forced displacement, and zoonotic disease.

Clinical reasoning and research in modern geriatrics often prioritises the disease concept. This is understandable as it has brought impressive advances in medicine (e.g. antibiotics, vaccines, successful cancer treatment and many effective surgeries). However, so far the disease framework has not succeeded in getting us to root causes of many age-related chronic diseases (e.g. Alzheimer's disease, diabetes, osteoarthritis). Moreover, in aging and disease constructs alone fail to explain the variability in illness presentations. Therefore, we propose to apply the underused illness concept in a new way by reconsidering the importance of common symptoms in the form of a dynamic network of symptoms as a complementary framework. We show that concepts and methods of complex system thinking now enable to fruitfully monitor and analyse the multiple interactions between symptoms in such in networks, offering new routes for prognosis and treatment. Moreover, close attention to the symptoms that bother older persons may also improve weighing the therapeutic objectives of well-being and survival and aligning treatment targets with the patients' priorities. [ABSTRACT FROM AUTHOR]