The authors of this paper conclude that reducing Ultraprocessed Drink Consumption could lower environmental impact and all-cause mortality risk; however, this was not shown for Ultraprocessed Foods. When categorizing food consumption by their degree of processing, trade-offs are observed for human and planetary health aspects.
Climate change is impacting the health of Western Australians.Temperature increases and air pollution are particularly problematic.Food and water security may be compromised. An urgent response is required.
Background: Few studies have evaluated postnatal depression before and during the Covid-19 pandemic using comparable data across time.
Background: Workplace offensive behaviours, such as violence and bullying, have been linked to psychological symptoms, but their potential impact on suicide risk remains unclear.
This paper explores the assess to antiretroviral therapy and its associated factors among patients accessing treatment at Health centers in Ethiopia.
This research underscores the health rights of firefighters by investigating the potential impact of occupational exposure to PFAS and PAHs on liver function and serum lipids, which could contribute to work-related adverse health outcomes. [occupational exposure]
Food-related illnesses are very common and this study reminds us of the importance of maintaining food hygiene standards to improve human health.
This paper reviews the unique perspective that Indigenous People have on the HIV/AIDS epidemic, and the interactions between Indigenous Identities and HIV. The authors call for a human rights based approach to ending the HIV epidemic among Indigenous Peoples.
This Article supports SDG 3 by analysing peripartum antiviral prophylaxis for hepatitis B in 110 countries, finding that it could be beneficial in averting both neonatal hepatitis B infections and DALYS, and that it might be cost-effective depending on how it is implemented and the associated diagnostic costs.
This Perspective explores the sources of bias in medical machine learning, and how these can contribute to unequal performance, for example for women. The authors discuss methods for mitigating bias, hopefully leading to more equitable use of machine learning in healthcare.
