This study supports SDG 3 and 10 by reporting that Māori and Pacific people with type 2 diabetes have consistently poorer health outcomes than European patients, indicating the need for specific policies and interventions to better manage type 2 diabetes in these subpopulations.
This Lancet Global Health Commission advances addresses SDG 3 directly, and SDGs 1, 2, 4, 5, 8 and 10 indirectly, by comprehensively demonstrating how improving eye health by treating and preventing vision impairment and vision loss can not only advance SDG 3—improving health and wellbeing for all—but also contribute to poverty reduction, zero hunger, quality education, gender equality, and decent work and economic growth. The findings of this report frame eye health as a development issue and highlight that, with a growing ageing population globally, urgent and concerted action is needed to meet unmet eye health needs globally, including incorporating equitable eye care into countries’ universal health coverage plans.
Recent pay and hiring discrimination allegations have resulted in high-dollar settlements for Google and a hospitality management company. Developments discussed in this news article cover topics related to SDG 5 (gender equality) and SDG 10 (reduced inequalities).
This book chapter advances SDG #3 and #10 by providing therapeutic strategies that can be employed in clinical trials for AD in DS will be discussed as well as their underlying scientific rationale.
This book chapter advances SDG #3 and #10 by providing a brief history of PET imaging and the radiotracers that have had a significant impact for measuring the three signature AD-related neuropathologies related to AD and provides an overview of the research utilizing PET imaging in the DS population
This book chapter advances SDG #3 and #10 by discussing the advantages of performing genetic studies in people with DS, and then discussing the role of reported genes that are known to be associated with AD risk in adults with DS or in the general population. It also discusses how future longitudinal multiomic and imaging study can enhance our understanding of the biology of AD.
Elsevier,
Alzheimer’s Disease: Understanding Biomarkers, Big Data, and Therapy, Volume , 1 January 2021
This book chapter advances SDG #3 and #10 by discussing the operational aspects of deep learning solutions for Alzheimer’s disease, including the review of the advantages and limitations of using deep learning, and future directions on the applications of deep learning to Alzheimer’s disease.
This book chapter advances SDG #3 and #10 by systematically appraises the concepts and promising benefits of AI technology within healthcare for AD risk prediction across communities, and its possible concerns to be tackled prior to large-scale implementation.
Elsevier,
Alzheimer’s Disease: Understanding Biomarkers, Big Data, and Therapy, Volume , 1 January 2021
This book chapter advances SDG #3 and #10 by providing evidence that behavioral treatments are more effective than most pharmacological therapies at managing depression in Alzheimer’s disease.
This book chapter advances SDG #3 and #10 by stressing that a population health approach and a focus on promoting equity in health and access to care are critical to reducing the risk of AD and other dementias.
