Ethnic inequalities in stroke explained by differences in stroke risk factors - Medical Xpress

IntroductionPrecision medicine is an innovative approach to healthcare that tailors disease prevention and treatment to individual variability in genes, environment, and lifestyle [1]. This rejects the “one size fits all” notion and seeks to develop tailored approaches for more effective treatment. Integral to this are advances in genomic technology that enables early disease detection and personalised treatments, such as using genotype information to determine the serious side-effects of carbamazepine and improving cancer outcomes through genomic profiling [2, 3]. However, there are concerns that advances in precision medicine, in particular genomics, are exacerbating health inequalities, particularly among certain ethnic groups. These groups often have limited access to precision medicine services and are underrepresented in research [4, 5]. Addressing these health inequalities is crucial to ensure that advancements in precision medicine benefit everyone. Although the 10-year strategy “Genome UK: the future of healthcare” is a radical vision of genomic medicine in the UK health service, but it does not directly consider how to tackle health inequalities.

EARLY-LIFE clinical characteristics could help identify infants at increased risk of developing atopic dermatitis (AD), according to findings from a prospective cohort study involving 671 children. Researchers developed two prediction models using demographic and clinical information collected during early infancy. Both demonstrated moderate predictive performance, highlighting the potential for early risk assessment to support preventive counselling and monitoring during the first 2 years of life.

Shared family factors, such as genes and upbringing, are likely to explain a large part of the link between high screen use and mental health problems in young people. This is according to a new study from Karolinska Institutet published in Nature Human Behaviour. "Our results suggest that the association may in some cases have been overestimated because it has not been possible to fully account for shared family factors," says Tong Gong, research specialist at the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, and the study's corresponding author alongside Lu Yi, senior researcher at the same department.