Race-based assumptions in biomedical journal articles.
This Comment supports SDGs 3 and 10 by discussing the UK's reliance on digital technologies during the COVID-19 pandemic. Although a digital-first policy aims to reduce health inequalities, challenges such as low usage of the internet and low uptake of digital COVID-19 technologies among older, minority ethnic groups, could mean that the strategy instead reinforces the unequal effects of COVID-19.
Digital health, including the use of mobile health apps, telemedicine, and data analytics to improve health systems, has surged during the COVID-19 pandemic. The social and economic fallout from COVID-19 has further exacerbated gender inequities, through increased domestic violence against women, soaring unemployment rates in women, and increased unpaid familial care taken up by women—all factors that can worsen women's health. Digital health can bolster gender equity through increased access to health care, empowerment of one's own health data, and reduced burden of unpaid care work.
This Viewpoint describes a feminist intersectionality framework to tackle digital health's gender inequities and provide recommendations for future research.
Background: Criteria for low-dose CT scan lung cancer screening vary across guidelines. Knowledge of the eligible pool across demographic groups can enable policy and programmatic decision-making, particularly for disproportionately affected populations. Research Question: What are the eligibility rates for low-dose CT scan screening according to sex and race or ethnicity and how do these rates relate to corresponding lung cancer incidence rates?
This study supports SDG 3 and 10 by highlighting an overrepresentation of Black children and adolescents in involuntary psychiatric hospitalisations, which may establish potentially lifelong negative mental health treatment trajectories and contribute to cycles of health inequality that persist in later life.
This article supports SGDs 3 and 10 by identifying ethnicity-specific body-mass index cutoffs for obesity based on type 2 diabetes risk-equivalence to the cutoff in White populations. The findings suggest ethnicity-specific body-mass index cutoffs are needed to optimise prevention and management of type 2 diabetes.
This Comment describes how systematic biases in data linkage misestimate health needs for ethnic minorities and further entrench existing disadvantages.
If we can’t see race and ethnicity in research, how will we see racial inequality?
This Article supprts SDGs 3 and 10 by assessing the performance of four severity scoring systems used for case-mix determination and benchmarking in intensive care units to identify possible ethnicity-based bias. The study found systemic differences in calibration across ethnicities.
