Association Between Physical Activity and Risk of Depression: A Systematic Review and Meta-analysis.

Importance: Depression is the leading cause of mental health-related disease burden and may be reduced by physical activity, but the dose-response relationship between activity and depression is uncertain. Objective: To systematically review and meta-analyze the dose-response association between physical activity and incident depression from published prospective studies of adults. Data Sources: PubMed, SCOPUS, Web of Science, PsycINFO, and the reference lists of systematic reviews retrieved by a systematic search up to December 11, 2020, with no language limits. The date of the search was November 12, 2020. Study Selection: We included prospective cohort studies reporting physical activity at 3 or more exposure levels and risk estimates for depression with 3000 or more adults and 3 years or longer of follow-up. Data Extraction and Synthesis: Data extraction was completed independently by 2 extractors and cross-checked for errors. A 2-stage random-effects dose-response meta-analysis was used to synthesize data. Study-specific associations were estimated using generalized least-squares regression and the pooled association was estimated by combining the study-specific coefficients using restricted maximum likelihood. Main Outcomes and Measures: The outcome of interest was depression, including (1) presence of major depressive disorder indicated by self-report of physician diagnosis, registry data, or diagnostic interviews and (2) elevated depressive symptoms established using validated cutoffs for a depressive screening instrument. Results: Fifteen studies comprising 191 130 participants and 2 110 588 person-years were included. An inverse curvilinear dose-response association between physical activity and depression was observed, with steeper association gradients at lower activity volumes; heterogeneity was large and significant (I2 = 74%; P < .001). Relative to adults not reporting any activity, those accumulating half the recommended volume of physical activity (4.4 marginal metabolic equivalent task hours per week [mMET-h/wk]) had 18% (95% CI, 13%-23%) lower risk of depression. Adults accumulating the recommended volume of 8.8 mMET hours per week had 25% (95% CI, 18%-32%) lower risk with diminishing potential benefits and higher uncertainty observed beyond that exposure level. There were diminishing additional potential benefits and greater uncertainty at higher volumes of physical activity. Based on an estimate of exposure prevalences among included cohorts, if less active adults had achieved the current physical activity recommendations, 11.5% (95% CI, 7.7%-15.4%) of depression cases could have been prevented. Conclusions and Relevance: This systematic review and meta-analysis of associations between physical activity and depression suggests significant mental health benefits from being physically active, even at levels below the public health recommendations. Health practitioners should therefore encourage any increase in physical activity to improve mental health.

Digital health: a neglected part of health curricula?

With growing government investment and a thriving consumer market, digital technologies are rapidly transforming our means of healthcare delivery. These innovations offer increased diagnostic accuracy, greater accessibility and reduced costs compared with conventional equivalents. Despite these benefits, implementing digital health poses challenges. Recent surveys of healthcare professionals (HCPs) have revealed marked inequities in digital literacy across the healthcare service, hampering the use of these new technologies in clinical practice. Furthermore, a lack of appropriate training in the associated ethical considerations risks HCPs running into difficulty when it comes to patient rights. In light of this, and with a clear need for dedicated digital health education, we argue that our focus should turn to the foundation setting of any healthcare profession: the undergraduate curriculum.

A Systematic Review of Animal Models of NAFLD Finds High-Fat, High-Fructose Diets Most Closely Resemble Human NAFLD.

BACKGROUND AND AIMS: Animal models of human disease are a key component of translational hepatology research, yet there is no consensus on which model is optimal for NAFLD. APPROACH AND RESULTS: We generated a database of 3,920 rodent models of NAFLD. Study designs were highly heterogeneous, and therefore, few models had been cited more than once. Analysis of genetic models supported the current evidence for the role of adipose dysfunction and suggested a role for innate immunity in the progression of NAFLD. We identified that high-fat, high-fructose diets most closely recapitulate the human phenotype of NAFLD. There was substantial variability in the nomenclature of animal models: a consensus on terminology of specialist diets is needed. More broadly, this analysis demonstrates the variability in preclinical study design, which has wider implications for the reproducibility of in vivo experiments both in the field of hepatology and beyond. CONCLUSIONS: This systematic analysis provides a framework for phenotypic assessment of NAFLD models and highlights the need for increased standardization and replication.

Social media in undergraduate medical education: A systematic review.

INTRODUCTION: There are over 3.81 billion worldwide active social media (SoMe) users. SoMe are ubiquitous in medical education, with roles across undergraduate programmes, including professionalism, blended learning, well being and mentoring. Previous systematic reviews took place before recent explosions in SoMe popularity and revealed a paucity of high-quality empirical studies assessing its effectiveness in medical education. This review aimed to synthesise evidence regarding SoMe interventions in undergraduate medical education, to identify features associated with positive and negative outcomes. METHODS: Authors searched 31 key terms through seven databases, in addition to references, citation and hand searching, between 16 June and 16 July 2020. Studies describing SoMe interventions and research on exposure to existing SoMe were included. Title, abstract and full paper screening were undertaken independently by two reviewers. Included papers were assessed for methodological quality using the Medical Education Research Study Quality Instrument (MERSQI) and/or the Standards for Reporting Qualitative Research (SRQR) instrument. Extracted data were synthesised using narrative synthesis. RESULTS: 112 studies from 26 countries met inclusion criteria. Methodological quality of included studies had not significantly improved since 2013. Engagement and satisfaction with SoMe platforms in medical education are described. Students felt SoMe flattened hierarchies and improved communication with educators. SoMe use was associated with improvement in objective knowledge assessment scores and self-reported clinical and professional performance, however evidence for long term knowledge retention was limited. SoMe use was occasionally linked to adverse impacts upon mental and physical health. Professionalism was heavily investigated and considered important, though generally negative correlations between SoMe use and medical professionalism may exist. CONCLUSIONS: Social media is enjoyable for students who may improve short term knowledge retention and can aid communication between learners and educators. However, higher-quality study is required to identify longer-term impact upon knowledge and skills, provide clarification on professionalism standards and protect against harms.

Weight loss, insulin resistance, and study design confound results in a meta-analysis of animal models of fatty liver.

The classical drug development pipeline necessitates studies using animal models of human disease to gauge future efficacy in humans, however there is a low conversion rate from success in animals to humans. Non-alcoholic fatty liver disease (NAFLD) is a complex chronic disease without any established therapies and a major field of animal research. We performed a meta-analysis with meta-regression of 603 interventional rodent studies (10,364 animals) in NAFLD to assess which variables influenced treatment response. Weight loss and alleviation of insulin resistance were consistently associated with improvement in NAFLD. Multiple drug classes that do not affect weight in humans caused weight loss in animals. Other study design variables, such as age of animals and dietary composition, influenced the magnitude of treatment effect. Publication bias may have increased effect estimates by 37-79%. These findings help to explain the challenge of reproducibility and translation within the field of metabolism.

Obesity and diabetes are increasingly common diseases that can lead to other complications such as fatty liver disease. Fatty liver disease affects one in five people and is caused by a built-up of fat in the liver, which can result in scarring of the liver tissue and other serious complications. There is currently no cure for fatty liver disease. Drugs that have been effective in treating the condition in mice, lack efficacy in humans. To better understand why this is the case, Hunter, de Gracia Hahn, Duret, Im et al. conducted a review of over 5,000 published studies, analysing over 600 experiments. Hunter et al. asked which drugs improved fatty liver in mice the most and if they had the same effect in humans. They also tested whether the age of the mice affected the outcome of the experiments. The analyses revealed that the drugs that work best in mice are different to the ones that show some effect in humans. In mice, many of the drugs reduced their weight or lowered their blood sugar levels, which also improved the fatty liver condition. Moreover, drugs appeared to be less effective the older the mice were. However, most of these drugs do not cause weight loss or lower blood sugar levels in humans, suggesting that factors other than the intended action of these drug could affect the outcome of a mouse study. These findings will help shape future research into obesity, diabetes and fatty liver disease using mice. They highlight that results obtained from studies with mice so far do not predict if a drug will work in humans to treat fatty liver disease. Moreover, weight loss seems to be the most important factor linked to how efficiently a drug treats fatty liver disease.