Wednesday, September 10, 2025

 

The Lancet: Chronic disease deaths decline globally, but progress is slowing




The Lancet






Death rates from chronic diseases have fallen in four out of five countries around the world in the last decade - but progress has slowed, suggests an analysis led by researchers at Imperial College London and published in The Lancet.

In recent decades there have been many global and national political pledges and plans to improve prevention and treatment of chronic diseases (also called non-communicable diseases - NCDs), such as cancer, cardiovascular disease, diabetes, kidney disease, liver disease, neurological conditions and others. This includes the UN Sustainable Development Goal of reducing premature mortality from NCDs by one-third by 2030.

This study is believed to be the first global analysis to not only track changes in NCD mortality at the national level but also benchmark progress against historical performance and the regional best-performers.

The analysis suggests deaths from chronic diseases has fallen in nearly 80% of countries in the last decade. However almost two thirds of all countries – including nearly all high-income countries in Europe, north America, Australasia and the Pacific – experienced a slowdown in the rate of decline for mortality in 2010 to 2019 compared to the previous decade. The United States was one of the worst performers among high-income countries, experiencing the smallest decrease in risk over 2010-2019.

Ahead of the upcoming Fourth High-level Meeting of the UN General Assembly [1], authors say these trends show an urgent need for greater investment in tackling chronic diseases and ensuring approaches effectively reach people most in need.

Notes to editors:

[1] https://www.who.int/news-room/events/detail/2025/09/25/default-calendar/fourth-high-level-meeting-of-the-un-general-assembly-on-the-prevention-and-control-of-ncds-and-the-promotion-of-mental-health-and-wellbeing-(hlm4)

 

Family-based intervention programs are insufficient to prevent childhood obesity, major study finds



Study of 17 international trials finds early childhood obesity programs targeting parents alone don’t improve BMI, prompting calls for stronger government action on environmental and structural drivers.




University of Sydney





A landmark study led by the University of Sydney has found no evidence that family-based early obesity prevention programs, such as home visits from health professionals or community parent groups, improve overall body mass index (BMI) in young children.

 

Published in The Lancet, the study was led by Dr Kylie Hunter from the Faculty of Medicine and Health as part of the TOPCHILD collaboration with multiple scientists including those at the University Medical Center Rostock and Flinders University.

 

Early weight is a strong predictor of future weight trajectory, with one in four children in Australia living with overweight or obesity by the time they start school.  

 

"We found that early parent-focused obesity prevention programs did not improve BMI in children,” said Dr Kylie Hunter, lead author and research fellow at the NHMRC Clinical Trials Centre and the Charles Perkins Centre

 

“To shift the dial, we need to stop putting the onus on families alone. Governments, health officials and local authorities must show stronger leadership and commitment to addressing the social and environmental drivers of obesity.” 

 

Assessing the impact of childhood obesity prevention programs

 

The scientists analysed data from 31 international studies evaluating different types of family-based childhood obesity prevention programs commencing during pregnancy up to the age of one. 

 

Of these 31 international studies, the researchers focused on 17 studies, which assessed children’s BMI at the age of two, after the obesity programs had concluded. 

 

The academics found that despite the range of interventions employed there was no meaningful difference in the BMI of children in families who participated in any of the programs compared to those who did not. 

 

The interventions analysed in the study aimed to help parents build healthy habits for their children, focusing on diet, breast-feeding, physical activity, sleep and screen time. They were delivered in a variety of ways including home visits from health professionals and peer educators, community parent groups or via mobile apps.    

 

Recognising the limits of family-based health interventions

 

With a third of children and adolescents worldwide forecast to live with overweight or obesity within the next 25 years, researchers say programs are being undermined by societal factors beyond families’ control, especially those in lower socioeconomic groups. 

 

Dr Hunter said: “It’s hard to make healthy choices when unhealthy options are cheaper, easier, and more heavily advertised. We must address the broader environments where children eat, learn and play – making healthy choices easier for everyone, regardless of where they live."

 

The programs analysed in the study were conducted in countries such as Australia, the UK, Norway, Belarus, Brazil, the US and Sweden and lasted from two days to 39 months. 

 

Structural change key to obesity prevention

 

The researchers emphasised that the programs studied were well-designed and delivered by passionate and skilled professionals, but argued that without wider systemic change, both health professionals and parents were fighting a losing battle. 

 

“The first phase of life is challenging for many families”, said co-author Professor Anna Lene Seidler from the German Center for Child and Adolescent Health at the University Medical Center Rostock in Germany and affiliate at the University of Sydney. 

 

“Parents may feel overwhelmed and lack the time, resources and stability to implement healthy behaviours without broader structural support.” 

 

The researchers warn that focusing solely on parents to make changes may also widen health inequalities.

 

“Families most affected by childhood obesity – often those in lower socioeconomic groups – are also the least likely to access or benefit from these programs, while families in higher socioeconomic areas, who already meet many health recommendations, are more likely to be reached,” said Dr Hunter. 

 

About the TOPCHILD Collaboration 

 

The TOPCHILD Collaboration is a global initiative that unites more than 70 researchers from 47 institutions, contributing original data to create the largest early childhood obesity prevention database to date, encompassing nearly 30,000 children.

 

-ENDS-

The Lancet: Parent-focused programs insufficient to prevent obesity in toddlers, finds meta-analysis; authors call for a re-think of childhood obesity prevention approaches




The Lancet




  • A meta-analysis of 17 trials including over 9,000 toddlers found no evidence that parent-focused early childhood obesity prevention programs have an impact on young children's BMI.

  • Authors say their findings underscore the need to re-think current behavioural approaches to prevent obesity in early childhood and stress the need for broader, coordinated and resourced public health action.

Existing approaches to parent-focused behavioural programs delivered up to 12 months of age which aim to combat childhood obesity are insufficient to improve body mass index (BMI) at approximately two years of age, according to the largest study to date on the topic published in The Lancet.
 

Globally, around 37 million children under five years live with overweight or obesity [1]. Child obesity has major lifelong health impacts. To prevent obesity, many argue it is crucial to intervene early, before overweight or obesity first develop in early childhood. The WHO recommends a life-long approach to reduce the risk of obesity, starting during pregnancy. It advocates for the provision of guidance on healthy diet, sleep and physical activity in early childhood for parents/caregivers [2].

 

Therefore, many governments have made early parent-focused programs – such as community parenting classes, home visits or sharing information via SMS/email/app with a focus on building parent’s skills and knowledge on topics such as nutrition, physical activity, and sleep - a key strategy for obesity prevention.
 
However, there has been limited evidence on the effectiveness of such programs, putting policymakers in a challenging position and resulting in decisions to implement potentially resource-intensive programs despite gaps in the evidence. 

 

Lead author Dr Kylie Hunter, University of Sydney (Australia), says, “Obesity is in large part driven by environmental and socio-economic factors that individuals are unable to change. Parents play a vital role, but our study highlights that they cannot be expected to reduce childhood obesity levels alone.

 

“Broader, coordinated action across society is needed to make healthy choices easier for everyone, regardless of where they live. Alongside support for parents, we need to see coordinated policies which improve affordability of healthy foods, increase access to green spaces, and regulate unhealthy food marketing to tackle childhood obesity."

 
The authors formed a global collaboration (TOPCHILD) of more than 70 researchers across 47 institutions, combining data from 31 trials set across 10 countries. Investigators from all trials worked together and shared their individual participant data resulting in a large dataset of 28,825 participants to examine the impact of obesity prevention programs designed to help parents foster healthy nutrition, sleep and activity patterns in their toddlers. To be included in the meta-analysis, programs needed to commence sometime between pregnancy and 12 months of age and to measure a child weight-related outcome. The authors also disentangled detailed information on the content and delivery of interventions in a complementary piece of research led by Flinders University [3].

 

Of the 31 trials contributing data, there were 17 trials with individual participant data which assessed BMI at approximately two years of age (a total of 9128 participants). These trialled different intervention approaches [3], including for example: 

  • A trial in the UK assessing a program where eight weekly sessions were delivered in children centres to groups of eight to ten parents to target behaviours including food provision and movement. [4]
  • An Australian trial where women with their first child received eight home visits spread over two years with advice on topics including breastfeeding, timing of introducing solids, screen time and physical activity. [5]
  • A trial in the US where primary-care providers set dietary, physical activity or screen time goals with parents, aided by low-literacy booklets, at seven visits from two to 18 months. [6] 

With a high level of certainty, the meta-analysis found that the early childhood obesity prevention programs had no effect on BMI of the children at approximately two years old.
 
Senior author Prof Anna Lene Seidler, University of Rostock (Germany), says, “There are several potential explanations for why current parent-focused programs to prevent obesity in toddlers are not effective. One reason could be that the first year of a child’s life can be overwhelming and stressful for parents, leaving them with limited capacity to fully engage in behavioural changes. Once children enter broader social settings such as early childcare and school, programs which create healthier environments for children directly in these setting may be more effective.

 

“Additionally, the families most affected by childhood obesity – often those in lower socioeconomic groups – are also the least likely to be reached by parent-focused early programs. They often simply do not have the resources or time to attend and adhere to these programs, particularly in the current cost of living crisis. Policy level changes aimed at creating healthier environments for all children are more likely to reach these families.”
 

The authors acknowledge some limitations in their study, including that seven of the 17 trials were rated as high risk of bias due to missing data and/or that data were missing at different rates for participants in the intervention group compared to those in the control group. However, when these studies were excluded from the analysis, the results remained the same.

 

NOTES TO EDITORS
 

This study was funded by the Australian National Health and Medical Research Council. For a full list of researchers and institutions see the paper.

 

Quotes from Authors cannot be found in the text of the Article but have been supplied for the press release. The Comment quote is taken directly from the linked Comment.

The labels have been added to this press release as part of a project run by the Academy of Medical Sciences seeking to improve the communication of evidence. For more information, please see: http://www.sciencemediacentre.org/wp-content/uploads/2018/01/AMS-press-release-labelling-system-GUIDANCE.pdf If you have any questions or feedback, please contact The Lancet press office pressoffice@lancet.com  

 

References: 

[1] https://data.unicef.org/resources/jme-report-2023/?utm_id=JME-2023

[2] https://www.who.int/publications/i/item/9789241510066

[3] Johnson BJ, Chadwick PM, Pryde S, Seidler AL, Hunter KE et al. Behavioural components and delivery features of early childhood obesity prevention interventions: intervention coding of studies in the TOPCHILD Collaboration systematic review. IJBNPA. 2025;22:14.

[4] Bryant M, Collinson M, Burton W, et al. Cluster randomised controlled feasibility study of HENRY: a community-based intervention aimed at reducing obesity rates in preschool children. Pilot and Feasibility Studies 2021; 7(1): 59.  

[5] Wen LM, Baur LA, Simpson JM, Rissel C, Wardle K, Flood VM. Effectiveness of home-based early intervention on children’s BMI at age 2: randomised controlled trial. BMJ 2012; 344:e3732.

[6] Sanders LM, Perrin EM, Yin HS, et al. A health-literacy intervention for early childhood obesity prevention: a cluster-randomized controlled trial. Pediatrics 2021; 147(5).

 

 

 UK

Study sheds light on hurdles faced in transforming NHS healthcare with AI




University College London

Implementing artificial intelligence (AI) into NHS hospitals is far harder than initially anticipated, with complications around governance, contracts, data collection, harmonisation with old IT systems, finding the right AI tools and staff training, finds a major new UK study led by UCL researchers. 

Authors of the study, published in The Lancet  eClinicalMedicine, say the findings should provide timely and useful learning for the UK Government, whose recent 10-year NHS plan identifies digital transformation, including AI, as a key platform to improving the service and patient experience. 

In 2023, NHS England launched a programme to introduce AI to help diagnose chest conditions, including lung cancer, across 66 NHS hospital trusts in England, backed by £21 million in funding. The trusts are grouped into 12 imaging diagnostic networks: these hospital networks mean more patients have access to specialist opinions. Key functions of these AI tools included prioritising critical cases for specialist review and supporting specialists’ decisions by highlighting abnormalities on scans.

Funded by the National Institute for Health and Care Research (NIHR), this research was conducted by a team from UCL, the Nuffield Trust, and the University of Cambridge, analysing how procurement and early deployment of the AI tools went. The study is one of the first studies to analyse real-world implementation of AI in healthcare.

Evidence from previous studies¹, mostly laboratory-based, suggested that AI might benefit diagnostic services by supporting decisions, improving detection accuracy, reducing errors and easing workforce burdens.

In this UCL-led study, the researchers reviewed how the new diagnostic tools were procured and set up through interviews with hospital staff and AI suppliers, identifying any pitfalls but also any factors that helped smooth the process.

They found that setting up the AI tools took longer than anticipated by the programme’s leadership. Contracting took between four and 10 months longer than anticipated and by June 2025, 18 months after contracting was meant to be completed, a third (23 out of 66) of the hospital trusts were not yet using the tools in clinical practice.

Key challenges included engaging clinical staff with already high workloads in the project, embedding the new technology in ageing and varied NHS IT systems across dozens of hospitals and a general lack of understanding, and scepticism, among staff about using AI in healthcare.

The study also identified important factors which helped embed AI including national programme leadership and local imaging networks sharing resources and expertise, high levels of commitment from hospital staff leading implementation, and dedicated project management.

The researchers concluded that while “AI tools may offer valuable support for diagnostic services, they may not address current healthcare service pressures as straightforwardly as policymakers may hope” and are recommending that NHS staff are trained in how AI can be used effectively and safely and that dedicated project management is used to implement schemes like this in the future.

First author Dr Angus Ramsay (UCL Department of Behavioural Science and Health) said: “In July ministers unveiled the Government’s 10-year plan for the NHS, of which a digital transformation is a key platform.

“Our study provides important lessons that should help strengthen future approaches to implementing AI in the NHS.

“We found it took longer to introduce the new AI tools in this programme than those leading the programme had expected.

“A key problem was that clinical staff were already very busy – finding time to go through the selection process was a challenge, as was supporting integration of AI with local IT systems and obtaining local governance approvals.  Services that used dedicated project managers found their support very helpful in implementing changes, but only some services were able to do this.

“Also, a common issue was the novelty of AI, suggesting a need for more guidance and education on AI and its implementation.

“AI tools can offer valuable support for diagnostic services, but they may not address current healthcare service pressures as simply as policymakers may hope.”

The researchers conducted their evaluation between March and September last year, studying 10 of the participating networks and focusing in depth on six NHS trusts. They interviewed network teams, trust staff and AI suppliers, observed planning, governance and training and analysed relevant documents.

Some of the imaging networks and many of the hospital trusts within them were new to procuring and working with AI.

The problems involved in setting up the new tools varied – for example, in some cases those procuring the tools were overwhelmed by a huge amount of very technical information, increasing the likelihood of key details being missed. Consideration should be given to creating a national approved shortlist of potential suppliers to facilitate procurement at local level, the researchers said.

Another problem was initial lack of enthusiasm among some NHS staff for the new technology in this early phase, with some more senior clinical staff raising concerns about the potential impact of AI making decisions without clinical input and on where accountability lay in the event a condition was missed. The researchers found the training offered to staff did not address these issues sufficiently across the wider workforce – hence their call for early and ongoing training on future projects.

In contrast, however, the study team found the process of procurement was supported by advice from the national team and imaging networks learning from each other. The researchers also observed high levels of commitment and collaboration between local hospital teams (including clinicians and IT) working with AI supplier teams to progress implementation within hospitals.

Senior author Professor Naomi Fulop (UCL Department of Behavioural Science and Health) said: “In this project, each hospital selected AI tools for different reasons, such as focusing on X-ray or CT scanning, and purposes, such as to prioritise urgent cases for review or to identify potential symptoms.

“The NHS is made up of hundreds of organisations with different clinical requirements and different IT systems and introducing any diagnostic tools that suit multiple hospitals is highly complex. These findings indicate AI might not be the silver bullet some have hoped for but the lessons from this study will help the NHS implement AI tools more effectively.”

Limitations

While the study has added to the very limited body of evidence on the implementation and use of AI in real-world settings, it focused on procurement and early deployment. The researchers are now studying the use of AI tools following early deployment when they have had a chance to become more embedded. Further, the researchers did not interview patients and carers and are therefore now conducting such interviews to address important gaps in knowledge about patient experiences and perspectives, as well as considerations of equity.

Ends

Notes to editors                                                                                                       

For more information or to speak to the researchers involved, please contact Nick Hodgson, UCL Media Relations. T: +44 (0)7769 240209, E: nick.hodgson@ucl.ac.uk   

Angus I.G. Ramsay, Nadia Crellin, Rachel Lawrence, Holly Walton, Stuti Bagri, Emma Dodsworth, Holly Elphinstone, Fergus Gleeson, Amanda Halliday, Kevin Herbert, Joanne Lloyd, Efthalia Massou, Raj Mehta, Stephen Morris, Pei Li Ng, Tracy O'Regan, Chris Sherlaw-Johnson and Naomi J. Fulop, ‘Procurement and early deployment of artificial intelligence tools for chest diagnostics in NHS services in England: A rapid, mixed method evaluation’ will be published in The Lancet e-Clinical Medicine on Wednesday 10 September 2025, 00:01 UK time and is under a strict embargo until this time.

The DOI will be https://doi.org/10.1016/j.eclinm.2025.103481.

¹ Liu M, Wu J, Wang N, Zhang X, Bai Y, Guo J, et al, The value of artificial intelligence in the diagnosis of lung cancer: A systematic review and meta-analysis; Joy Mathew C, David AM, Joy Mathew CM, Artificial Intelligence and its future potential in lung cancer screening; Chiu HY, Chao HS, Chen YM, Application of Artificial Intelligence in Lung Cancer.; and Lawrence R, Dodsworth E, at al, Artificial intelligence for diagnostics in radiology practice: a rapid systematic scoping review.

In January, the Government announced a shake-up in the use of technology and AI across the NHS and other public services.

About UCL – London’s Global University

UCL is a diverse global community of world-class academics, students, industry links, external partners, and alumni. Our powerful collective of individuals and institutions work together to explore new possibilities.

Since 1826, we have championed independent thought by attracting and nurturing the world's best minds. Our community of more than 50,000 students from 150 countries and over 16,000 staff pursues academic excellence, breaks boundaries and makes a positive impact on real world problems.

The Times and Sunday Times University of the Year 2024, we are consistently ranked among the top 10 universities in the world and are one of only a handful of institutions rated as having the strongest academic reputation and the broadest research impact.

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For almost 200 years, we are proud to have opened higher education to students from a wide range of backgrounds and to change the way we create and share knowledge.

We were the first in England to welcome women to university education and that courageous attitude and disruptive spirit is still alive today. We are UCL.

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About NIHR

The mission of the National Institute for Health and Care Research (NIHR) is to improve the health and wealth of the nation through research. 

We do this by:

  •  funding high quality, timely research that benefits the NHS, public health and social care
  •  investing in world-class expertise, facilities and a skilled delivery workforce to translate discoveries into improved treatments and services
  • partnering with patients, service users, carers and communities, improving the relevance, quality and impact of our research
  • attracting, training and supporting the best researchers to tackle complex health and social care challenges
  • collaborating with other public funders, charities and industry to help shape a cohesive and globally competitive research system funding applied global health research and training to meet the needs of the poorest people in low and middle income countries

NIHR is funded by the Department of Health and Social Care. 

Its work in low and middle income countries is principally funded through UK international development funding from the UK government.