Skip to main content

The divergence of minimum unit pricing policy across the UK

A paper published in the Journal of the Royal Society of Medicine discusses the implementation of a minimum unit pricing policy across the UK. Above recommended levels of intake, alcohol use is associated with harm including hypertension, haemorrhagic stroke, liver disease, mental health disorders and cancers, as well as accidents, injuries and assaults. The 2015 UK Global Burden of Disease study indicates that 2.9% of disability-adjusted life years and 1.9% of mortality are attributable to alcohol use, and the 2013 Health Survey for England found that 23% of men and 16% of women in England drink at levels associated with risk to health. Despite the ongoing discussion about minimum unit pricing policy across the UK, and although it is difficult to predict what it would take for the Westminster Government to revert to a minimum unit pricing policy, any minimum unit pricing policy that does come to be implemented in Scotland or England and Wales will only be implemented because the relevant evidence exists.

Read the full article in the Journal of the Royal Society of Medicine.

Comments

Popular posts from this blog

What is the difference between primordial prevention and primary prevention?

Primordial prevention and primary prevention are both crucial strategies for promoting health, but they operate at different levels. Primordial prevention aims to address the root causes of health problems and improve the wider determinants of health. It focuses on preventing the emergence of risk factors in the first place by tackling the underlying social, economic, and environmental determinants of health. This involves broad, population-wide interventions such as: Policies that promote healthy food choices: Think about initiatives like taxing sugary drinks to discourage unhealthy consumption, or providing subsidies for fruits and vegetables to make them more accessible. Urban planning that prioritises well-being: This could include creating walkable neighborhoods with safe cycling routes, ensuring access to green spaces for recreation and relaxation, and designing communities that foster social connections. Social programs that address inequality: Initiatives aimed at reducing pov...

UK Covid-19 Inquiry - The Importance of a Strong Primary Healthcare System

In my witness statement for Module 10 of the UK Covid-19 Inquiry, I discuss the pandemic's impact through from the perspectives of  primary care and public health, drawing on my extensive experience as a senior academic at Imperial College London and as a practising GP and NHS Public Health Specialist.  I emphasise that the pandemic disproportionately affected people who were clinically vulnerable, the disabled, ethnic minority communities and those living in deprived areas. The pandemic highlighted how structural inequalities, multigenerational housing, and employment in high-risk frontline roles exacerbated health disparities.  My statement also critiques the weakening of public health infrastructure - particularly for the control of infectious diseases - and the lack of integrated health data systems to identify at-risk groups such as the clinically vulnerable. I also advocated for a more robust preventive healthcare model that prioritises community-based primary care ...

Relevance Over Recall: Rethinking How AI Uses Clinical Data

Our article in the Journal of the Royal Society of Medicine argues that safe and effective AI in healthcare must incorporate mechanisms that emulate human judgement - down-weighting old, inaccurate or superseded information and prioritising what is recent, clinically relevant and reaffirmed - so that AI supports, rather than disrupts, high-quality patient care.  Clinicians constantly revise, reinterpret and filter past information so that only what is relevant, accurate and timely shapes present-day management decisions; medical records function as dynamic “working tools” rather than fixed archives. By contrast, many AI systems lack this capacity for selective forgetting and often treat all historical data as equally meaningful.  This can lead to outdated or low-confidence diagnoses being repeatedly resurfaced, persistent labels influencing clinical expectations, and irrelevant, long-resolved events cluttering summaries and decision-support outputs. Such indiscriminate recall...