Measuring progress and projecting attainment on the basis of past trends of the health-related Sustainable Development Goals in 188 countries: an analysis from the Global Burden of Disease Study 2016

The UN’s Sustainable Development Goals (SDGs) are grounded in the global ambition of “leaving no one behind”. Understanding today’s gains and gaps for the health-related SDGs is essential for decision makers as they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990–2016 for 188 countries, and then on the basis of these past trends, we projected indicators to 2030

Defining an ageing-related pathology, disease or syndrome: International Consensus Statement

Around the world, individuals are living longer, but an increased average lifespan does not always equate to an increased health span. With advancing age, the increased prevalence of ageing-related diseases can have a significant impact on health status, functional capacity and quality of life. It is therefore vital to develop comprehensive classification and staging systems for ageing-related pathologies, diseases and syndromes. This will allow societies to better identify, quantify, understand and meet the healthcare, workforce, well-being and socioeconomic needs of ageing populations, whilst supporting the development and utilisation of interventions to prevent or to slow, halt or reverse the progression of ageing-related pathologies. The foundation for developing such classification and staging systems is to define the scope of what constitutes an ageing-related pathology, disease or syndrome. To this end, a consensus meeting was hosted by the International Consortium to Classify Ageing-Related Pathologies (ICCARP), on February 19, 2024, in Cardiff, UK, and was attended by 150 recognised experts. Discussions and voting were centred on provisional criteria that had been distributed prior to the meeting. The participants debated and voted on these. Each criterion required a consensus agreement of ≥ 70% for approval. The accepted criteria for an ageing-related pathology, disease or syndrome were (1) develops and/or progresses with increasing chronological age; (2) should be associated with, or contribute to, functional decline or an increased susceptibility to functional decline and (3) evidenced by studies in humans. Criteria for an ageing-related pathology, disease or syndrome have been agreed by an international consortium of subject experts. These criteria will now be used by the ICCARP for the classification and ultimately staging of ageing-related pathologies, diseases and syndromes

Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

This online publication has been corrected. The corrected version first appeared at thelancet.com on September 28, 2023BACKGROUND : Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. METHODS : Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively. FINDINGS : In 2021, there were 529 million (95% uncertainty interval [UI] 500–564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8–6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7–9·9]) and, at the regional level, in Oceania (12·3% [11·5–13·0]). Nationally, Qatar had the world’s highest age-specific prevalence of diabetes, at 76·1% (73·1–79·5) in individuals aged 75–79 years. Total diabetes prevalence—especially among older adults—primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1–96·8) of diabetes cases and 95·4% (94·9–95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5–71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5–30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22–1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1–17·6) in north Africa and the Middle East and 11·3% (10·8–11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%. INTERPRETATION : Diabetes remains a substantial public health issue. Type 2 diabetes, which makes up the bulk of diabetes cases, is largely preventable and, in some cases, potentially reversible if identified and managed early in the disease course. However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. Preventing and controlling type 2 diabetes remains an ongoing challenge. It is essential to better understand disparities in risk factor profiles and diabetes burden across populations, to inform strategies to successfully control diabetes risk factors within the context of multiple and complex drivers.Bill & Melinda Gates Foundation.http://www.thelancet.comam2024School of Health Systems and Public Health (SHSPH)SDG-03:Good heatlh and well-bein

قياس أثر بعض المتغيرات الاقتصادية الكلية على التنمية المستدامة في ماليزيا للمدة (2004-2020)

يهدف البحث إلى التعرف على العلاقة بين بعض المتغيرات الاقتصادية الكلية والتنمية المستدامة، من أجل معرفة تأثير تلك المتغيرات الاقتصادية الكلية المتمثلة بـ (الناتج المحلي الاجمالي، البطالة، الادخار، اجمالي تكوين راس المال الثابت) بوصفها متغيرات مستقلة، والتنمية المستدامة بوصفها متغير تابع، إذ تمثل التنمية المستدامة عنصراً مهماٌ من خلال مؤشر متوسط نصيب الفرد في ماليزيا، ومن خلال الاعتماد على الأسلوب الوصفي والتحليلي والقياسي في سبيل تحقيق هدف الدراسة، تم استخدام مدة زمنية ممتدة (2004-2020) باستخـدام النمـوذج القياسـي عبـر برنامـج (E-view) لقياس العلاقة التوازنية بين المتغيرات الاقتصادية الكلية والتنمية المستدامة، وتبين أن المتغيرات مستقرة عند الفرق الأول وهذا ينطبق على استخدام نموذج ARDL، وتم تحديد كل من التأثير الايجابي والسلبي، وتبين وجود أثر سلبي وايجابي بين متغيرات الدراسة، وظهرت النتائج أن ارتفاع الناتج المحلي الاجمالي بمقدار وحدة واحدة يؤدي إلى ارتفاع متوسط نصيب الفرد بمقدار 32.7% حيث إن هذا الأثر كان معنوياً باحتمالية تبلغ (0.0499) وهي أقل من 5% وبالتالي فأن هذه العلاقة معنوية، أما البطالة إن ارتفاع معدل البطالة بمقدار وحدة واحدة لا يؤثر على متوسط نصيب الفرد، وذلك لأن هذا الاحتمالية كانت غير معنوية حيث بلغت (0.6496) وهي أكبر من 5% وبالتالي فأن هذه العلاقة غير معنوية. وتوصي الدراسة أن تعمل ماليزيا على تحسين مسار معدل البطالة وجعلها في الحدود الطبيعية لأن البطالة المنخفضة تنعكس إيجابا على متوسط دخل الفرد، إلى جانب تنمية وتطوير المتغيرات الاقتصادية الكلية وزيادة مساهمتها في الناتج المحلي الإجمالي

Why MASLD lags behind MAFLD: A critical analysis of diagnostic criteria evolution in metabolic dysfunction-associated liver diseases

Emerging in the 1800s under the label fat in the liver and later gaining prominence in the 1980 as non-alcoholic fatty liver disease (NAFLD), the disease predominantly attributed to metabolic dysfunction presents a formidable health issue marked by substantial morbidity and mortality. It was 2020 when a change of one letter NAFLD to metabolic dysfunction-associated fatty liver disease MAFLD linked with the change in the definition and diagnostic criteria began a new controversy around the globe. Metabolic dysfunction-associated fatty liver disease (MAFLD) criteria represent a substantial departure from previous diagnostic measures of NAFLD, and provide the first set of positive criteria for diagnosis of the disease in adults and children that emphasise the key attribute of metabolic dysfunction in the pathogenesis, and acknowledges that the disease is a continuum across the life span. In 2023, an adapted version of the diagnostic criteria of MAFLD was proposed to define a slightly modified term; metabolic dysfunction-associated steatotic liver disease (MASLD). The MASLD criteria did not provide any conceptual advantage, and emerging evidence suggests that it actually performs worse than the MAFLD criteria. This raises the intriguing question of why MASLD was unable to take advantage of being second? In this review, we will explore the possible reasons for this unique case and highlight the current evidence supporting the use of MAFLD instead of MASLD in defining metabolic dysfunction-associated fatty liver diseases

Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico, evaluation, but few have yet demonstrated real benefit to patient care. Early stage clinical evaluation is important to assess an AI system’s actual clinical performance at small scale, ensure its safety, evaluate the human factors surrounding its use, and pave the way to further large scale trials. However, the reporting of these early studies remains inadequate. The present statement provides a multistakeholder, consensus-based reporting guideline for the Developmental and Exploratory Clinical Investigations of DEcision support systems driven by Artificial Intelligence (DECIDE-AI). We conducted a two round, modified Delphi process to collect and analyse expert opinion on the reporting of early clinical evaluation of AI systems. Experts were recruited from 20 predefined stakeholder categories. The final composition and wording of the guideline was determined at a virtual consensus meeting. The checklist and the Explanation & Elaboration (E&E) sections were refined based on feedback from a qualitative evaluation process. 123 experts participated in the first round of Delphi, 138 in the second, 16 in the consensus meeting, and 16 in the qualitative evaluation. The DECIDE-AI reporting guideline comprises 17 AI specific reporting items (made of 28 subitems) and 10 generic reporting items, with an E&E paragraph provided for each. Through consultation and consensus with a range of stakeholders, we have developed a guideline comprising key items that should be reported in early stage clinical studies of AI-based decision support systems in healthcare. By providing an actionable checklist of minimal reporting items, the DECIDE-AI guideline will facilitate the appraisal of these studies and replicability of their findings