Obesity Care

Whole Milk and Childhood Obesity – New Study Challenges Long-Standing Dietary Advice

Key Takeaways:

• Children who consumed whole-fat milk in early childhood showed lower odds of living with obesity in later childhood compared with those consuming reduced-fat options
  
• The study found no evidence that whole milk increases adiposity, challenging decades of low-fat dietary guidance
  
• Researchers suggest milk fat may influence satiety and overall dietary patterns, although mechanisms remain unclear
  
  
  

Rethinking milk fat and childhood health

New research from the University of Toronto suggests that children who consume whole-fat milk during early childhood may have a lower likelihood of living with obesity in middle childhood than those who drink reduced-fat milk.

These findings contribute to a growing body of evidence indicating that lower-fat milk may not provide the protective effect against childhood obesity that has long been assumed. For several decades, dietary guidelines in many countries have promoted low-fat dairy products. For example, Canada’s Dietary Guidelines in 2019 continued to recommend reduced-fat options, reflecting a broader historical focus on reducing dietary fat intake.

Study overview and design

The study, published in the American Journal of Clinical Nutrition, is described as one of the most comprehensive analyses to date examining the relationship between milk consumption and childhood obesity over time.

Researchers, including former postdoctoral fellow Tara Zeitoun and doctoral student Zheng Hao Chen, analysed data from the CHILD Cohort Study. This large, prospective study tracks health data from thousands of children from before birth through to adolescence.

Caregivers reported the type of milk consumed by children, including skim, one per cent, two per cent, and whole-fat milk. Researchers then assessed a range of outcomes at ages five and eight, including:

• Body mass index (BMI)
• Waist-to-height ratio
• Fat mass
• Preclinical and clinical obesity status
  
  
  

Key findings

Milk consumption was common among participants, with over 90 per cent of children consuming milk before the age of five. Among these:

• 24 per cent consumed whole-fat milk
• Approximately half consumed less than one cup per day
  

Despite relatively modest intake, notable differences emerged. Children who consumed whole milk at age five had significantly lower BMI at age eight. They also had 69 per cent lower odds of living with obesity compared with children who consumed skim milk.

In addition, researchers identified a broader pattern in which higher milk fat content was associated with more favourable adiposity profiles.

Expert insight

Kozeta Miliku, a professor of nutritional sciences at the University of Toronto’s Temerty Faculty of Medicine and a researcher at the Joannah and Brian Lawson Centre for Child Nutrition, emphasised the implications of these findings:

“The most important learning from this study is that whole milk was not associated with higher adiposity or obesity risks risk in children, and may even be linked to healthier growth patterns,”

She also highlighted the limitations of focusing narrowly on fat reduction:

“Switching to lower-fat milk has been about cutting fat in the diet, but that may miss the bigger picture,” says Miliku. “When we think about healthy growth, it’s important to consider the overall nutritional context. Removing fat does not automatically make skim milk a healthier choice for children.”

Implications for public health guidance

The findings raise important questions about long-standing public health recommendations. Prior to 2019, Health Canada advised that children transition from whole milk to reduced-fat milk from the age of two. Similarly, the Dietary Guidelines for Americans 2020–2025 supported reduced-fat dairy intake.

However, recent policy developments suggest a shift in thinking. In the United States, the Whole Milk for Healthy Kids Act has allowed full-fat milk to be reintroduced into school lunches, aligning with updated national guidance that is more permissive of full-fat dairy.

Possible biological mechanisms

While the study did not directly investigate underlying mechanisms, the researchers proposed several hypotheses:

• Milk fat may enhance satiety, potentially reducing the consumption of energy-dense, nutrient-poor foods
• It may influence overall energy balance
• It could play a role in metabolic pathways linked to growth and nutritional status
  

These potential explanations highlight the complexity of dietary patterns and suggest that focusing on single nutrients may overlook broader physiological effects.

The need for further research

Miliku noted that additional research is needed to better understand how milk fat may influence obesity risk and whether any protective effects persist into adolescence and adulthood.

With Canada’s 2019 dietary recommendations offering limited specific guidance on milk consumption for children, the study’s findings may help inform future discussions among parents, clinicians, and policymakers.

A broader view of healthy diets

Miliku concluded by reinforcing the importance of overall dietary quality:

“Whole fat milk can be part of a healthy diet and does not on its own increase obesity risk,” she adds. “And it’s important to think about the overall quality of the diet – the fruits and vegetables, whole grains and protein-rich foods they consume.”

Funding and support

The research was funded by the Canadian Institutes of Health Research and the Joannah & Brian Lawson Centre for Child Nutrition at the University of Toronto, supported through a donation by President’s Choice Children’s Charity.

CCH insights:

This interesting new research will hopefully be the trigger for governments and public health bodies to review and amend their outdated advice to choose low-fat dairy options instead of full-fat. The reductionist approach to nutrition, which considers food just in terms of calories and individual nutrients, is an oversimplification which does not help our understanding of the relationship between food and health. If the best food for children early in life is whole milk, why would it be beneficial for them to suddenly switch to low-fat milk at the age of 2?

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Visual Signals, Healthier Choices – Study Shows Colour-Coded Labels Influence Consumer Decisions

Key Takeaways:

• Colour-coded nutrition labels are more effective than traditional tables in guiding healthier food choices
  
• Red warning signals have a stronger behavioural impact than green positive cues, reflecting a “negative bias” in decision-making
  
• Simple visual labelling systems may support public health efforts to address obesity and poor dietary habits
  
  
  

The growing use of colour-coded nutrition labels

Colour coding on food packaging is becoming increasingly common, particularly as policymakers and manufacturers seek ways to guide consumers towards healthier dietary choices. A recent study conducted by researchers from SWPS University, the University of Wisconsin, and the University of Massachusetts suggests that these visual systems are significantly more effective than traditional nutritional tables.

The findings, published in Current Psychology, indicate that the effectiveness of colour-coded labels lies in how the brain processes signals of benefit and risk. Rather than requiring effortful interpretation, colour cues allow for rapid, intuitive judgements about a product’s healthfulness.

Obesity and the need for clearer nutritional guidance

According to the World Health Organization, overweight and obesity are major contributors to the development of chronic diseases. Over the past three decades, the proportion of children and adolescents in the United States who are overweight or at risk has more than tripled, reaching 37% and 34% respectively.

This trend has been driven largely by reduced physical activity and the increased consumption of foods high in fat and sugar. In response, clearer and more accessible nutritional labelling systems are being explored as tools to help people make more informed food choices.

How traffic light labelling works

One widely adopted approach is the traffic light labelling (TLL) system, originally developed in the United Kingdom. This system uses colours to indicate the levels of key nutrients such as calories, fat, saturated fat, sugar, and salt relative to recommended intake levels.

• Green indicates low levels, typically below 15% of the reference intake
  
• Red signals high levels, typically exceeding 25% of the reference intake

By translating numerical data into easily recognisable visual cues, the system allows consumers to assess a product’s nutritional profile at a glance.

“A picture is worth a thousand words”

The study aimed to explore the psychological mechanisms behind how people interpret these colour-coded labels.

“We decided to investigate the psychological mechanisms behind the reading of color-coded product labels. We drew on theories about verbal and visual information processing, as well as the perception of information in positive and negative contexts. We wanted to bridge a gap. Previous studies focused exclusively on consumer purchasing behavior and analyzed the extent to which color-coded labels influenced the choice of healthy food products,” says Professor Andrzej Falkowski, a business psychologist from the Institute of Psychology at SWPS University and the author of the study.

To examine this, researchers recruited 79 participants in the United States via Amazon Mechanical Turk. Participants were asked to evaluate products such as chicken noodle soup, ranch dressing, and peanut butter. These products were presented either with colour-coded nutrient indicators or with traditional text-based information.

Participants rated each product on a scale from 0 to 10, where 0 indicated “harmful” and 10 indicated “healthy”.

Faster processing, more intuitive decisions

The findings confirmed that visual information is easier for people to process than text. Colour cues are interpreted almost instantly by the brain, requiring minimal cognitive effort.

This enables individuals to make quick, instinctive judgements about whether a product is beneficial, even in time-pressured situations such as shopping. In contrast, traditional nutritional tables require more deliberate analysis, which may reduce their practical usefulness in real-world settings.

The power of red and the role of negative bias

One of the most striking findings was the disproportionately strong influence of the colour red. While green highlights positive attributes, red signals high levels of fat or sugar and prompts caution.

“This result also aligns with existing theories suggesting that negative events exert a stronger influence on behavior than positive ones. It is this ‘negative bias’ that makes color systems so effective. Red causes us to pause and reconsider a purchase,” Professor Falkowski emphasizes.

This asymmetry – where negative signals carry more weight than positive ones – was not observed with traditional labelling formats. Without clear visual cues, participants found it more difficult to distinguish between beneficial and harmful aspects of a product.

Improved consistency in consumer judgements

The study also found that colour-coded labels led to more consistent evaluations across participants. Because the visual system clearly differentiates between risks and benefits, individuals were better able to assess products in a uniform way.

By contrast, traditional descriptors such as “low fat” can be ambiguous and open to interpretation, particularly for those with limited nutritional knowledge. Colour coding, based on universally recognised traffic signals, offers a more accessible and intuitive alternative.

Implications for public health and obesity prevention

The researchers suggest that these findings have important implications for public health policy.

“Given the ongoing global challenges of obesity and poor dietary habits, color-coded labeling represents a simple yet impactful strategy for guiding healthier consumer choices,” Falkowski says.

By enhancing the visibility and clarity of nutritional information, colour-coded systems may encourage people to select healthier options. Over time, such behavioural shifts could contribute to improvements in population health.

The authors conclude that leveraging visual attention mechanisms and simplifying complex nutritional data may be a practical and scalable approach to addressing poor dietary habits and the global rise in obesity.

CCH insights:

The results of this study supports the use colour-coded labelling system as it enables quick health-based decision-making, with minimal time or effort required. And it also revealed that we use the system more to avoid unhealthy ‘red’ foods than to actively choose healthy ‘green’ foods. These outcomes emphasise the complex range of factors that contribute to shopping behaviours and decisions about what people eat. And if we want to encourage people to eat healthily, we need to understand these factors better and consider how best to influence them.

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Children with Obesity Face Elevated Long-Term Health Risks Even with Normal Test Results, Study Finds

Key Takeaways:

• Children living with obesity can face significantly higher risks of future disease even when current clinical tests appear normal
  
• By early adulthood, rates of type 2 diabetes, hypertension and abnormal lipids are markedly higher compared with the general population
  
• Effective obesity treatment in childhood is associated with meaningful reductions in long-term health risks
  
  
  

Rethinking “metabolically healthy” obesity in childhood

Children living with obesity who show no immediate signs of metabolic complications may still be at substantial risk of developing serious health conditions later in life. New research from the Karolinska Institutet, published in JAMA Pediatrics, challenges the long-standing notion that some children with obesity can be considered “metabolically healthy” and therefore may not require intervention.

The findings contribute to an ongoing clinical debate about whether normal blood markers, liver function and blood pressure in childhood are sufficient indicators of long-term health.

“There has been a debate about whether children with normal blood and liver values and normal blood pressure might not need treatment for their obesity. Our study shows that this assumption is incorrect,” says Claude Marcus, professor at the Department of Clinical Science, Intervention and Technology at Karolinska Institutet.

Study design and population

The study followed just over 7,200 children aged 7–17 in Sweden who had initiated obesity treatment. Participants were tracked longitudinally up to the age of 30, allowing researchers to assess long-term health outcomes.

Children were grouped into three categories:

• Those with metabolically healthy obesity (MHO)
  
• Those with obesity and impaired cardiometabolic risk markers (MUO)
  
• A control group drawn from the general population
  

This design enabled a direct comparison of long-term disease risk across different metabolic profiles in childhood.

A clearly increased risk of future disease

Despite appearing clinically healthy in childhood, individuals with MHO demonstrated a substantially elevated risk of developing cardiometabolic diseases by early adulthood.

By the age of 30:

• 9 percent of individuals with MHO had developed type 2 diabetes, compared with 17 percent in the MUO group and 0.5 percent in the control group
  
• High blood pressure was observed in 11 percent of the MHO group, 18 percent of the MUO group and 4 percent of the general population
  
• Abnormal blood lipid levels were present in 5 percent of those with MHO and 13 percent of those with MUO, compared with just 1 percent among controls
  

These findings indicate that even in the absence of early warning signs, children living with obesity carry a significantly increased burden of future disease risk.

“Even children with obesity who show no signs of cardiometabolic impact have a clearly increased risk of future diseases. This means that normal blood pressure and the absence of abnormal blood test results are not sufficient protection against future morbidity,” says Emilia Hagman, associate professor at the same department and the study’s corresponding author.

The role of early treatment

All children included in the study received structured support aimed at improving lifestyle habits. Researchers examined whether treatment response during childhood influenced long-term outcomes.

A strong response to treatment was associated with a reduced risk of developing all studied conditions – including type 2 diabetes, hypertension and dyslipidaemia. Notably, this protective effect was observed in both MHO and MUO groups.

This suggests that early intervention has meaningful and lasting clinical benefits, regardless of a child’s initial metabolic profile.

“Our results suggest that all children with obesity need treatment, even if they appear completely healthy upon examination,” says Claude Marcus.

Data sources and funding

The study drew on data from Sweden’s national quality registry BORIS, alongside several national health data registries.

Funding was provided by multiple organisations, including the Center for Innovative Medicine, the Ollie and Elof Ericsson Foundation and the Freemason Foundation for Children’s Welfare.

Several researchers reported receiving compensation from companies unrelated to this work. A full list of potential conflicts of interest is available in the original scientific publication.

Implications for clinical practice

The findings underscore the limitations of relying solely on current metabolic markers when assessing risk in children living with obesity. Even in the absence of immediate clinical abnormalities, long-term risks remain significant.

For clinicians, this supports a more proactive and inclusive approach to obesity management in paediatric populations – one that does not defer intervention based on apparently normal test results, but instead recognises obesity itself as a key driver of future health risk.

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Larger Organs, More Cells – New Study Clarifies How Obesity May Increase Cancer Risk

Key Takeaways: 

• A new study suggests that larger organ size in people living with obesity increases cancer risk due to a higher number of cells
  
• Organ growth appears to be driven largely by an increase in cell number rather than simply larger cells
  
• Findings indicate that organ size may be a more precise predictor of cancer risk than BMI alone
  
  
  

A longstanding question in obesity and cancer

For many years, researchers have recognised a clear association between obesity and an increased risk of cancer, particularly in organs such as the liver, kidneys and pancreas. However, the biological mechanism underpinning this relationship has remained uncertain.

A research team from City of Hope and its Translational Genomics Research Institute, known as TGen, has now provided a clearer explanation. Their findings suggest that the relationship may be explained by a straightforward principle – larger bodies tend to have larger organs, and larger organs contain more cells.

This increase in cell number creates more opportunities for mutations and, consequently, cancer development.

Study design and key findings

The study, presented in Cancer Research, analysed data from 747 adults across a broad spectrum of body mass index (BMI), ranging from underweight at 18.5 kg/m² to severe obesity above 40 kg/m².

Researchers examined the pancreas, kidneys and liver, identifying a consistent pattern: as body weight increased, organ size increased proportionally.

For every 5-point rise in BMI:

• The liver increased in size by 12%
  
• The kidneys increased by 9%
  
• The pancreas increased by 7%
  

These findings demonstrate a measurable and progressive relationship between BMI and organ enlargement.

More cells, not just bigger cells

To better understand how organs grow, the research team analysed kidney tissue from autopsies and biopsy samples from living individuals. This allowed them to distinguish between two biological processes:

• Hypertrophy – where existing cells grow larger
  
• Hyperplasia – where the number of cells increases
  

First author Sophie Pénisson, PhD, explained the importance of this distinction:

“When an organ increases in size, the question is to know whether it’s because the cells in it become bigger or whether there are more of them [that are] the same size,” Pénisson said. “And the first case is we call hypertrophy, with bigger cells, and hyperplasia is when we have more cells.”

The results showed that approximately 60% of kidney growth was due to hyperplasia, meaning an increase in the number of cells, while the remainder was due to hypertrophy.

A simple but powerful explanation for cancer risk

These findings support the idea that a greater number of cells increases the likelihood of cancer simply by increasing the number of opportunities for mutations to occur.

Senior author Cristian Tomasetti, PhD, illustrated this concept with a simple analogy:

“Think of playing the lottery: The more tickets you buy, the greater your chances of winning,” Tomasetti said. “Similarly, the more cells in an organ, the more mutations and the greater the risk of one cell going awry during division and becoming cancerous.”

Importantly, this mechanism does not replace existing explanations such as inflammation or hormonal disruption. Instead, it works alongside them.

Pénisson elaborated on this interaction:

“If more cells is like having more raffle tickets, she said, ‘if on top of that, there is inflammation – it means you play more often. With greater frequency, again, you increase your risk of developing cancer.’”

Rethinking BMI as a predictor of risk

The study also raises important questions about the use of BMI as a measure of cancer risk.

Although BMI is widely used in clinical practice, the researchers observed considerable variation in organ size among individuals with similar BMI values. Some individuals within a “healthy” BMI range had organ sizes typically seen in severe obesity, while others with higher BMI did not.

The authors wrote:

“We…observe substantial interindividual variation in organ size among people with similar BMI: For example, some individuals in the healthy BMI range have organ sizes expected only in severe obesity, and vice versa. This large variability suggests that organ size itself may be a better predictor of cancer risk than BMI, a possibility we believe warrants further investigation.”

They further concluded:

“Taken together, these findings establish organ hyperplasia as a previously unrecognized contributor to obesity-related kidney, liver, and pancreatic cancer risk, complementing known mechanisms including inflammation, hormonal changes, and metabolic dysfunction.”

Pénisson reinforced this point:

“When an organ doubles in size, it is expected to roughly double its risk of developing cancer,” Pénisson said, noting that BMI does not distinguish between fat mass and lean tissue. “Our work suggests that, at least for some organs, their dimensions may predict cancer risk better than BMI.”

Can weight loss reverse the risk?

An important question arising from these findings is whether reducing body weight can reverse organ enlargement and lower cancer risk.

Tomasetti indicated that this is an active area of research:

“It’s actually something we are working on right now,” Tomasetti said. “But yes, preliminary data seem to indicate that essentially, you are reverting back according to the same process” that caused the weight gain.

He also referenced emerging evidence presented at the American Society of Clinical Oncology, suggesting a link between GLP-1 receptor agonists and reduced cancer risk, although further research is needed to confirm this relationship.

Implications for treatment and prevention

Given the global scale of obesity, affecting more than 2 billion people, these findings may have important implications for prevention strategies and treatment approaches.

Tomasetti suggested that therapies such as GLP-1 receptor agonists could play a broader role:

GLP-1 RAs “are something that should be given to people as a treatment option to reduce the cancer risk, among other things,” including heart disease.

While further research is needed, this study provides a clearer mechanistic link between obesity and cancer risk and highlights the potential importance of organ size as a clinical marker.

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Genetic Risk Scores Offer Improved Prediction of Obesity, Type 2 Diabetes and Long-Term Health Outcomes

Key Takeaways: 

• A new polygenic risk score integrates genetic data from over 8.5 million people to better predict obesity and type 2 diabetes risk
  
• The model goes beyond traditional measures such as body mass index by incorporating multiple aspects of metabolic function
  
• Individuals with higher genetic risk were more likely to develop complications and require interventions such as GLP-1 therapy or bariatric surgery
  
  
  

A more comprehensive approach to metabolic risk

Obesity and type 2 diabetes are complex metabolic conditions influenced by a combination of environmental, behavioural and genetic factors. While traditional clinical measures such as body mass index have long been used to assess risk, they do not fully capture the biological complexity underlying these conditions.

In a new study published in Cell Metabolism, researchers from Mass General Brigham have developed an advanced polygenic risk score designed to improve prediction of both obesity and type 2 diabetes, as well as their long-term health consequences. Polygenic risk scores work by aggregating the effects of many genetic variants across the genome, providing an estimate of an individual’s predisposition to developing a given condition.

“Our intention was to not only capture the risk of being diagnosed with obesity or diabetes, but also to better predict health consequences across the life course by integrating many aspects of metabolic function,” said co-first author Min Seo Kim, MD, MSc. “In the future, this genomic approach could complement established clinical risk factors to inform patient care and preventative strategies.”

Building a next-generation polygenic risk score

The research team constructed two distinct metabolic risk scores – one optimised for obesity and another for type 2 diabetes. Unlike conventional models, these scores incorporate genetic signals linked to 20 different traits associated with metabolic health. These include factors such as fat distribution, insulin regulation and glucose control.

To build these models, the investigators drew on genome-wide association studies conducted across some of the largest biobank datasets globally, encompassing more than 8.5 million individuals. This scale allowed the researchers to capture a broad and diverse range of genetic influences.

Importantly, the model moves beyond reliance on body mass index alone, reflecting a growing recognition that metabolic health cannot be fully understood through weight-based measures in isolation.

Predicting disease progression and clinical outcomes

Beyond predicting the likelihood of developing obesity or type 2 diabetes, the new polygenic risk scores demonstrated the ability to forecast downstream health outcomes.

The researchers found that individuals identified as high risk were more likely to go on to develop complications such as cardiovascular disease and stroke. Even among people who were initially healthy, those with a high genetic risk score were approximately twice as likely to require clinical interventions over time.

Specifically, individuals with higher polygenic risk scores were about twice as likely to receive GLP-1 receptor agonist medications or undergo bariatric surgery compared with those with average risk scores, over a median follow-up period of 5.5 years.

These findings suggest that genetic profiling could help identify people at risk earlier in the disease trajectory, potentially enabling more proactive and targeted care.

Improved performance across diverse populations

A notable strength of the study lies in its use of multi-ancestry genetic data. By incorporating genome-wide association studies from a wide range of populations, including African, East Asian, South Asian and Middle Eastern groups, the researchers were able to develop risk scores that performed better across diverse populations than earlier models.

Historically, many genetic prediction tools have been less accurate in non-European populations due to limited representation in genomic datasets. This study represents a step towards addressing that imbalance and improving equity in precision medicine.

Towards more personalised prevention and treatment

The research team emphasises that this work is part of a broader effort to refine understanding of the genetic subtypes of obesity and type 2 diabetes. Improved classification of these conditions could support more precise patient stratification in clinical trials and, ultimately, more tailored interventions in routine care.

“We want clinicians to be able to think about metabolic conditions in terms beyond body mass index, with a focus more broadly on underlying genetic susceptibility,” said co-senior author Akl Fahed, MD, MPH, of the Cardiovascular Research Center at Massachusetts General Hospital and an interventional cardiologist with the Mass General Brigham Heart and Vascular Institute. “Early identification of people who are likely to have a worse trajectory of poor metabolic health, before they even develop these conditions, can help us improve prevention and clinical interventions. That is how we can cure disease, and that is the bold mission that we are after.”

Implications for clinical practice

While further validation and implementation work will be required, the findings highlight the potential role of genomic tools in enhancing current approaches to metabolic disease prevention and management. By complementing existing clinical risk factors, polygenic risk scores could support earlier identification of people at risk and enable more personalised, proactive care pathways.

As healthcare systems increasingly move towards precision medicine, integrating genetic insights with clinical decision-making may become an important step in improving outcomes for people living with obesity and type 2 diabetes.

CCH insights:

This is exciting research, and a big step towards precision obesity prevention, as it gives us an individual risk score for obesity and diabetes for each patient. However, it is only half the story – ideally we’d also like to be able to determine what type of interventions will work best for each individual (in terms of diet, lifestyle and medicine) in order to optimise their chances of good metabolic health and achieving a healthy weight. Hopefully the ability to do this is not too far away.

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Reducing Parental Stress May Help Lower Childhood Obesity Risk, Yale Study Suggests

Key Takeaways: 

• A Yale study suggests that reducing parental stress may play an important role in lowering obesity risk in young children.
  
• Parents who took part in a mindfulness-based stress management programme showed improvements in parenting behaviours and children’s eating habits.
  
• Children whose parents received the stress-focused intervention were less likely to gain excess weight during follow-up compared with those receiving standard nutrition advice alone.
  
  
  

Childhood obesity continues to rise

Childhood obesity has been increasing in recent years and remains a major public health concern. According to the U.S. Centers for Disease Control and Prevention, approximately one in five children and adolescents in the United States met the clinical definition of obesity in 2024.

Efforts to prevent obesity in children have traditionally focused on encouraging healthier diets and increasing levels of physical activity. However, new research from Yale University suggests that another factor may also be important in shaping children’s health outcomes – parental stress.

A research team led by psychologist Rajita Sinha has found evidence that helping parents manage stress more effectively may reduce obesity risk among young children. The findings were published in the journal Pediatrics.

“It’s the third leg of the stool,” said Sinha. “We already knew that stress can be a big contributor in the development of childhood obesity. The surprise was that when parents handled stress better, their parenting improved, and their young child’s obesity risk went down.”

How parent stress may influence children’s health

Previous research has shown that children are more likely to develop obesity if their parents are living with obesity. However, scientists have increasingly suspected that psychological and environmental factors within families may also influence early childhood weight gain.

Parental stress has emerged as one such potential contributor.

Studies suggest that parents experiencing high levels of stress may be more likely to rely on convenient or fast-food options and less nutritious dietary patterns. These habits can influence the types of foods available in the home and shape children’s developing eating behaviours.

Stress can also affect broader family routines. When parents feel overwhelmed, regular meal patterns may become disrupted, healthier foods may be replaced with more convenient alternatives, and positive parenting behaviours may decline. Reduced patience, decreased emotional responsiveness, and less consistent family structure may all affect children’s wellbeing.

Despite these insights, most childhood obesity prevention programmes continue to focus primarily on nutrition education and physical activity promotion.

According to Sinha, these approaches alone often fail to produce long-lasting behavioural change.

Equipping practitioners with the skills to support lasting change – rather than just deliver initial advice – is the focus of professional training such as the College of Contemporary Health’s Behaviour Change short course, which draws on techniques from psychology and behavioural science.

Sinha is the Foundations Fund Professor in Psychiatry and a professor in neuroscience and child study at Yale School of Medicine.

A randomised trial examining stress reduction

To better understand the potential role of parental stress, the research team conducted a 12-week randomised prevention trial involving 114 parents.

Participants represented diverse ethnic and socioeconomic backgrounds and all had children aged between two and five years old who were living with overweight or obesity.

Parents were randomly assigned to one of two groups:

• Parenting Mindfully for Health (PMH) – a stress-focused intervention programme
  
• Standard counselling focusing on nutrition and physical activity
  

The Parenting Mindfully for Health programme combined several elements. Parents were taught mindfulness techniques and behavioural self-regulation strategies designed to help them manage stress more effectively. The programme also included guidance on healthy eating and physical activity for families.

Both groups attended weekly sessions lasting up to two hours over the 12-week study period.

During the programme, researchers measured parental stress levels, parenting behaviours, and children’s weight. Parenting behaviours assessed included warmth, listening, patience, and positive emotional interactions with children.

Researchers also evaluated children’s dietary patterns, including both healthy and unhealthy food consumption.

Children’s weight was measured again three months after the programme ended in order to assess whether any benefits were sustained.

Stress reduction linked to improvements in parenting and eating habits

The results showed clear differences between the two groups.

Parents who participated in the Parenting Mindfully for Health programme experienced significant reductions in stress levels, alongside improvements in parenting behaviours.

Children in these families also showed reductions in unhealthy food intake.

Importantly, during the three-month follow-up period, children in the PMH group did not experience significant weight gain.

In contrast, the comparison group receiving only nutrition and physical activity counselling showed no meaningful improvements in parental stress or parenting behaviours.

Children in this group experienced greater weight gain during the follow-up period and were six times more likely to move into the overweight or obesity risk category.

Researchers also observed differences in the relationships between stress, parenting, and children’s diet.

Among families in the control group, higher parental stress remained associated with weaker parenting behaviours and lower intake of healthy foods among children.

However, this relationship was no longer statistically significant in families who had participated in the stress management intervention.

“The combination of mindfulness with behavioral self-regulation to manage stress, integrated with healthy nutrition and physical activity, seemed to protect the young children from some of the negative effects of stress on weight gain,” Sinha said.

Building on research into stress and chronic disease

The study builds on broader research conducted at the Yale Stress Center, an interdisciplinary consortium established through a 2007 National Institutes of Health Common Fund initiative.

The centre investigates the biological and behavioural effects of stress, including how stress influences health behaviours and contributes to chronic mental and physical illnesses.

Researchers involved in the current study emphasised that childhood obesity remains a pressing health concern.

“Childhood obesity is such a major issue right now, and the results of this study are highly relevant to the current administration’s priority of reducing childhood chronic diseases,” said Sinha. “When people start moving up the weight scale, their risk of obesity-related illnesses, even in children, is increased.”

The findings suggest that addressing parental stress may represent an additional strategy for preventing early childhood obesity.

Longer-term studies are now underway to better understand the sustained effects of the Parenting Mindfully for Health programme. According to Sinha, results from a larger group of families followed for two years are expected in future research.

Research team and funding

The study was co-led by Wendy Silverman, the Alfred A. Professor in the Child Study Center and professor of psychology, and Ania Jastreboff, the Harvey and Kate Cushing Professor of Medicine and professor of pediatrics.

Additional contributors came from several departments at Yale School of Medicine, including pediatrics, neuroscience, and the Yale Child Study Center.

Researchers from the Bethesda Group, the Chicago School of Professional Psychology, the University of New Mexico, and George Mason University also participated in the study.

The research was supported by funding from the U.S. National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK).

CCH insight:

Childhood obesity is rising and is a major public health concern, so research like this, which improves our understanding of the determinants of childhood obesity, are very valuable. We know that stress causes overeating in many adults, and it is not surprising that it can impact their children too. People experiencing high levels of stress are usually time-poor and will find it very challenging to provide a healthy diet and lifestyle for their young children. The intervention described in the study appears to be effective, but the difficulty will be in scaling it up, at an affordable cost, so it can reach tens or hundreds of thousands of families. Developing an online version would be one way to approach this.

Developing an online version would be one way to approach this. For practitioners wanting to build these skills themselves, CCH’s Behaviour Change Skills CPD short courses (three 2-hour modules, fully online, CPD-accredited) teaches evidence-based techniques from psychology and behavioural science to help patients and families change diet, activity and other health behaviours for good.
Explore Behaviour Change Skills →

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Ultra-Processed Food Intake Linked to Higher Risk of Binge Eating in Adults Living with Obesity

Key Takeaways: 

• Higher consumption of ultra-processed foods was associated with increased symptoms of binge eating, bulimia-related behaviours, and emotional or uncontrolled eating in adults living with obesity.
  
• Individuals consuming the greatest proportion of ultra-processed foods had poorer overall diet quality and significantly lower protein intake.
  
• The findings suggest that addressing eating behaviour patterns alongside dietary composition may be important when supporting people living with obesity.
  
  
  

Rising consumption of ultra-processed foods during nutritional transition

A cross-sectional study published in Archives of Endocrinology and Metabolism has explored the relationship between ultra-processed food (UPF) intake and eating behaviour among adults living with obesity in São Paulo, Brazil.

The research was conducted against the backdrop of a broader nutritional transition that has been occurring in many developing countries. Economic development, demographic changes, cultural shifts, and evolving food systems have led to major transformations in dietary patterns.

While these changes have contributed to reductions in malnutrition and infectious diseases, they have also been accompanied by a marked increase in noncommunicable diseases such as obesity. A key driver of this shift has been the growing consumption of highly processed foods that are rich in fat, sugar, and refined ingredients.

Previous research has linked high consumption of ultra-processed foods to a range of adverse health outcomes, including obesity, overweight, type 2 diabetes, metabolic syndrome, cardiovascular and cerebrovascular disease, anxiety, depression, and increased all-cause mortality.

There is also emerging evidence that ultra-processed foods may influence eating behaviour itself. Some studies suggest that these foods may affect neurobiological and endocrine pathways that regulate appetite, potentially encouraging compulsive overeating.

Disordered eating patterns are also known to occur among individuals living with obesity. These patterns can complicate treatment and may reduce the effectiveness of weight management interventions. Understanding how ultra-processed food consumption interacts with eating behaviour is therefore clinically important.

Study design and participant characteristics

To explore this relationship, researchers recruited adults aged 18 to 59 years living with obesity, defined as a body mass index (BMI) of 30 kg/m² or higher. Participants were recruited both through a clinical obesity treatment service and via social media in São Paulo.

Several exclusion criteria were applied to minimise confounding factors. Individuals were excluded if they were pregnant or had diagnosed eating disorders, cardiac disease, renal disease, obesity caused by genetic disorders, or if they were taking antiepileptic medications or corticosteroids. People who smoked, misused alcohol, or were currently receiving pharmacological treatment for weight loss were also excluded.

Dietary intake was assessed using three non-consecutive 24-hour dietary recalls, including one weekend day. Researchers used the multiple-pass method, a structured interview approach designed to improve the accuracy of dietary reporting.

Foods reported in the recalls were categorised using the NOVA classification system, which groups foods according to the degree of industrial processing. Diet quality was assessed using the Diet Quality Index associated with the Digital Food Guide.

Eating behaviour was evaluated using validated self-administered online questionnaires:

• BITE (Bulimic Investigatory Test Edinburgh) – measuring symptoms and severity of bulimia and binge eating
  
• TFEQ-21 (Three-Factor Eating Questionnaire) – assessing cognitive restraint, emotional eating, and uncontrolled eating
  
• DEBQ (Dutch Eating Behaviour Questionnaire) – evaluating external eating, emotional eating, and restrained eating
  

Associations between ultra-processed food intake and eating behaviours were analysed using generalised linear models.

Prevalence of unusual eating behaviours

A total of 77 adults took part in the study. Of these participants, 78 percent were female.

The mean age of the group was 36 years, and the average BMI was 39.14 kg/m², corresponding to class II obesity.

Participants were divided into three groups based on the proportion of calories derived from ultra-processed foods:

• First tertile – less than 24.1 percent of calories from UPFs
  
• Second tertile – 24.1 percent to 35.4 percent
  
• Third tertile – more than 35.4 percent
  

Only around one quarter of participants displayed what researchers classified as normal eating behaviour.

In contrast:

• Approximately 52 percent exhibited unusual eating behaviour
  
• 23.4 percent reported binge eating
  

Symptoms consistent with unusual eating behaviours were observed across all tertiles of ultra-processed food consumption. However, participants in the highest UPF tertile showed significantly higher symptom scores on the BITE questionnaire compared with those in the lowest tertile.

Despite this difference in symptom scores, severity scores did not significantly differ between groups.

Overall, 40.3 percent of participants had clinically significant symptoms, while 13 percent were classified as having severe symptoms.

Eating style patterns associated with UPF intake

The study also examined several different eating style patterns.

Using the DEBQ questionnaire, researchers found that:

• 37.8 percent of participants had elevated external eating scores
  
• 36.5 percent had elevated emotional eating scores
  
• 25.7 percent had elevated restrained eating scores
  

Results from the TFEQ-21 questionnaire revealed:

• 52 percent had higher emotional eating
  
• 29.3 percent demonstrated increased cognitive restraint
  
• 18.7 percent showed higher uncontrolled eating
  

Higher intake of ultra-processed foods was positively associated with several problematic eating behaviours.

These included:

• Binge eating and bulimia-related symptoms measured by BITE
  
• Emotional eating
  
• External eating
  
• Uncontrolled eating
  

Together, these results suggest that people consuming larger amounts of ultra-processed foods were more likely to display eating behaviours characterised by reduced self-regulation and greater responsiveness to emotional or environmental triggers.

Diet quality and macronutrient intake

Across the overall study population, diet quality was classified as intermediate.

Participants in the highest ultra-processed food tertile had significantly lower diet quality scores than those in the lower tertiles.

Clear dietary differences were also observed between groups.

Participants in the lowest tertile consumed a higher proportion of unprocessed or minimally processed foods, whereas those in the highest tertile consumed more ultra-processed foods.

Interestingly, individuals in the first and second tertiles reported greater intake of processed culinary ingredients, such as oils or sugars used in cooking, compared with those in the third tertile.

The average macronutrient distribution across the entire sample was:

• 20 percent protein
  
• 48 percent carbohydrates
  
• 32 percent lipids
  

Participants in the highest UPF tertile had significantly lower protein intake than those in the other groups. Carbohydrate and lipid intake did not differ significantly between tertiles.

Median total daily caloric intake across the sample was 1,661 kcal. However, participants in the highest UPF tertile reported higher caloric intake than those in the second tertile.

Researchers suggested that lower protein intake associated with higher UPF consumption may influence satiety and appetite regulation, potentially contributing to overeating.

Clinical implications and study limitations

Overall, the study found that more than half of adults living with obesity exhibited unusual eating behaviours.

Higher intake of ultra-processed foods was associated with:

• Binge eating
  
• Bulimia-related symptoms
  
• Emotional eating
  
• External eating
  
• Uncontrolled eating
  

In addition, greater consumption of ultra-processed foods was linked to poorer diet quality and reduced protein intake.

These findings suggest that obesity treatment strategies may benefit from incorporating both dietary assessment and evaluation of eating behaviour patterns. Addressing behavioural drivers alongside nutritional composition could potentially improve weight management outcomes.

However, the authors emphasised several important limitations.

Because the study used a cross-sectional design, it cannot establish cause-and-effect relationships. The research was also conducted within a single clinical population in one urban centre, which may limit the generalisability of the findings.

In addition, dietary recalls and questionnaires were self-reported, which may introduce recall bias or social desirability bias. The relatively small sample size and predominantly female participant group may also affect the applicability of the results to broader populations.

Nevertheless, the study highlights the importance of considering ultra-processed food consumption within a wider behavioural and nutritional context when addressing obesity and supporting individuals in weight management.

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Obesity-Related Fat Tissue Signals Identified as a Driver of Age-Related Muscle Loss

Key Takeaways: 

• Researchers have identified a biological mechanism linking obesity-related fat tissue to accelerated muscle loss in older adults.
• Tiny particles released by adipose tissue were shown to directly trigger muscle atrophy in ageing human muscle cells.
• Younger muscle appears biologically protected from these effects, highlighting an age-dependent vulnerability that may inform future therapies.
  
  
  

New insight into sarcopenic obesity

Researchers at the University of Birmingham have identified a previously unrecognised biological pathway through which obesity may contribute to muscle loss in older adults. The findings provide important new insight into sarcopenic obesity, a condition in which excess body fat exists alongside reduced muscle mass and strength.

The study, published in the Journal of Cachexia, Sarcopenia and Muscle and conducted through the National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre (BRC), demonstrates for the first time that signals released from adipose tissue can directly induce muscle wasting in human cells.

Sarcopenic obesity is becoming increasingly common as populations age and is associated with frailty, impaired mobility and poorer overall health outcomes. The condition is estimated to affect approximately 11% of the population.

Fat tissue communication with muscle

The research focused on extracellular vesicles – microscopic particles released by fat tissue that act as biological messengers between organs and tissues.

Investigators discovered that extracellular vesicles derived specifically from obese adipose tissue, rather than lean tissue, caused significant thinning of muscle fibres obtained from older adults. This thinning represents a hallmark feature of muscle atrophy.

The harmful effects were traced to molecular cargo carried within these vesicles, particularly miR-150-5p, a microRNA known to regulate gene expression pathways involved in maintaining muscle structure and function.

These findings suggest that obesity does not simply increase fat mass but fundamentally alters how adipose tissue behaves and communicates with other organs, including skeletal muscle.

Age-dependent vulnerability of muscle

A notable finding of the study was that muscle cells derived from younger adults showed resistance to these obesity-related signals.

When exposed to extracellular vesicles from obese adipose tissue, younger muscle cells did not undergo the same degree of thinning observed in older muscle cells. This indicates that ageing muscle becomes biologically more susceptible to inflammatory and metabolic signals associated with obesity.

Speaking about the findings, first author Dr Joshua Price, Postdoctoral Researcher, explained:

“It isn’t just having more fat tissue that matters. Obesity changes how fat tissue behaves and how it communicates with muscle. Ageing muscle is far more vulnerable to these altered signals, which helps explain why muscle loss accelerates with obesity later in life.”

Identifying a potential therapeutic target

The identification of miR-150-5p as a key molecular driver presents a potential opportunity for therapeutic intervention. Researchers found that inhibiting this microRNA could partially reduce the muscle-wasting effects observed in laboratory models.

Overall, the results suggest a dual biological reality – younger muscle demonstrates protective resilience, while ageing muscle becomes increasingly vulnerable to obesity-related signalling pathways.

Senior author Professor Simon Jones, Professor in Musculoskeletal Ageing at the University of Birmingham and lead for the NIHR Birmingham BRC’s Sarcopenia and Multimorbidity research theme, said:

“Through this research, we’ve identified a key molecular pathway by which obesity can accelerate muscle loss in older adults. Importantly, we found that younger muscle appears resilient to these harmful signals, whereas ageing muscle becomes more vulnerable. This reinforces the importance of maintaining a healthy weight and muscle health as we age.”

He added:

“Our findings also open two potential therapeutic avenues: either blocking or modifying the harmful extracellular vesicles released from obese tissue, or developing strategies to make older muscle more resilient, mimicking the protective effects seen in younger muscle.”

Implications for ageing and obesity care

The study strengthens understanding of how ageing and obesity interact at a cellular level to influence physical decline. Rather than viewing muscle loss solely as a consequence of ageing or inactivity, the findings highlight obesity-related biological signalling as an active contributor.

By demonstrating that altered communication between fat and muscle tissue can directly drive muscle atrophy, the research provides a clearer mechanistic explanation for why people living with obesity may experience accelerated functional decline later in life.

The work was delivered through the NIHR Birmingham Biomedical Research Centre, with Dr Joshua Price serving as a BRC-funded postdoctoral research associate within the Sarcopenia and Multimorbidity research theme.

Together, these findings may support future strategies aimed at preserving muscle health in ageing populations, particularly among people living with obesity, where preventing muscle loss is critical for maintaining independence, mobility and long-term health outcomes.

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Parental Weight Before Pregnancy Linked to Higher Risk of Fatty Liver Disease in Adult Offspring, UK Study Finds

Key Takeaways: 

• Pre-pregnancy overweight or obesity in either parent is associated with a significantly increased risk of metabolic dysfunction associated steatotic liver disease (MASLD) in their children by early adulthood.
  
• When both parents were living with overweight or obesity prior to conception, the likelihood of MASLD in offspring by age 24 was more than three times higher.
  
• Much of this increased risk appears to be mediated by excess weight accumulated during childhood and adolescence.
  
  
  

Rising concern over MASLD across generations

Parental weight status before pregnancy may play an important role in shaping long-term liver and metabolic health in the next generation, according to new research published online in Gut. The findings suggest that overweight and obesity in both mothers and fathers prior to conception are linked to a heightened risk of metabolic dysfunction associated steatotic liver disease (MASLD) in their children as young adults.

MASLD, previously known as non-alcoholic fatty liver disease, is now recognised as the most common chronic liver condition worldwide. Researchers note that the disease affects approximately 15% of children and more than 30% of adults globally. The condition is characterised by excess fat accumulation in the liver alongside cardiometabolic abnormalities and may progress to cirrhosis or liver failure in some individuals.

While earlier studies have primarily focused on maternal obesity, uncertainty has remained regarding the contribution of paternal weight and the role of childhood weight trajectories in determining future disease risk.

Large UK birth cohort provides long-term insight

To investigate these questions, researchers analysed data from 1,933 participants enrolled in the UK Avon Longitudinal Study of Parents and Children (ALSPAC), a long-running population study tracking health outcomes across generations.

The study examined associations between parental body mass index (BMI) before pregnancy and the likelihood that offspring would develop MASLD by the age of 24.

MASLD was defined as the presence of elevated liver fat together with at least one cardiometabolic risk factor, such as raised cholesterol levels or elevated fasting glucose.

Both parents provided information on height, weight, BMI and waist circumference before pregnancy. They also completed detailed questionnaires during pregnancy and following childbirth covering a wide range of potential influencing factors, including:

• Age at delivery
  
• Smoking during early pregnancy
  
• Weekly alcohol consumption prior to pregnancy
  
• Employment status
  
• Educational attainment
  

Mothers additionally reported physical activity levels and whether they had previously been diagnosed with diabetes or hypertension at study enrolment.

Tracking early life and adolescent risk factors

Extensive information was also collected about the children, allowing researchers to examine developmental influences across childhood and adolescence. Recorded factors included:

• Sex
  
• Mode of delivery
  
• Gestational age and birthweight
  
• Antibiotic exposure during the first six months of life
  
• Duration of breastfeeding
  

Participants underwent repeated measurements of BMI and waist circumference between the ages of 7–9, 10–12 and 13–17 years. Lifestyle factors in early adulthood, including alcohol and tobacco use, were also assessed.

One in ten young adults developed MASLD

By age 24, MASLD was identified in 201 participants, representing approximately one in ten individuals in the cohort. The remaining 1,732 participants had normal liver findings.

Those living with MASLD were more likely to be male and to have a higher BMI compared with peers without the condition.

After adjusting for multiple potential confounding factors, both maternal and paternal overweight or obesity before conception were independently associated with increased odds of MASLD in offspring.

Each additional kilogram per square metre of maternal BMI increased the likelihood of MASLD by 10%, while each equivalent increase in paternal BMI was associated with a 9% rise in risk.

Most notably, offspring whose parents were both living with overweight or obesity prior to pregnancy had more than three times the odds of developing MASLD compared with those whose parents had a normal BMI.

Childhood weight plays a central role

Further analysis suggested that much of this association operates through weight gain during childhood and adolescence. Researchers estimated that 67% of the increased risk linked to parental overweight or obesity was explained by cumulative excess BMI between the ages of 7 and 17.

Additional analyses incorporating maternal and offspring sugar intake, as well as genetic susceptibility to MASLD, produced similar results, strengthening confidence in the observed associations.

Observational findings with important limitations

The authors emphasise that the study was observational and therefore cannot establish direct causation. Several limitations were also acknowledged.

Parental weight data prior to pregnancy were self-reported, and information was unavailable regarding parental MASLD status or certain underlying health conditions before and during pregnancy. In addition, physical activity levels of offspring in early adulthood were not captured, which may have influenced outcomes.

Implications for preconception health

Despite these limitations, the researchers conclude that their findings highlight the potential importance of parental metabolic health before conception in shaping long-term outcomes for future generations.

They state that the results “lend support to an early life influence of biparental obesity on offspring metabolic health, suggesting efforts to mitigate excess adiposity of both mothers and fathers before conceiving may confer longitudinal benefits to the metabolic outcomes of their future offspring.“

The study adds to growing evidence that prevention of metabolic disease may need to begin not only in childhood, but even before pregnancy, with both parents playing a meaningful role in influencing lifelong health trajectories.

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New Cochrane Review Finds Intermittent Fasting Offers No Clear Weight Loss Advantage

Key Takeaways:

• A major Cochrane review found intermittent fasting did not lead to clinically meaningful weight loss compared with standard dietary advice or no structured diet.
  
• Evidence on safety and long-term outcomes remains limited due to small trials, inconsistent reporting, and short follow-up periods.
  
• Experts caution against overinterpreting social media claims and emphasise the need for individualised, long-term approaches to weight management.
  
  
  

Intermittent fasting under scrutiny

Intermittent fasting has become one of the most widely promoted dietary strategies for weight loss, often presented as a superior alternative to conventional calorie reduction. However, a new Cochrane review suggests that these claims may not be supported by robust evidence.

According to the review, intermittent fasting does not appear to deliver greater weight loss than standard dietary advice or even no specific diet plan. The findings challenge the widespread perception that structured fasting schedules offer a unique or clinically meaningful advantage for people who are overweight or living with obesity.

Obesity remains a global public health challenge

Obesity continues to represent a major public health concern worldwide and is now among the leading causes of death in high-income countries. Data from the World Health Organization show that global adult obesity rates have more than tripled since 1975. By 2022, an estimated 2.5 billion adults were classified as overweight, including around 890 million adults living with obesity.

Against this backdrop, intermittent fasting has gained substantial attention. Eating patterns such as alternate-day fasting, periodic fasting, and time-restricted feeding are widely promoted across social media platforms, often accompanied by claims of rapid weight loss and metabolic benefits.

What the review examined

To assess whether intermittent fasting truly offers an advantage, researchers analysed 22 randomised clinical trials involving 1,995 adults across North America, Europe, China, Australia, and South America. The studies evaluated a range of fasting approaches, including alternate-day fasting, periodic fasting, and time-restricted feeding. Most trials followed participants for up to one year.

When outcomes were compared with those of traditional dietary advice or no dietary intervention, intermittent fasting did not result in a clinically meaningful difference in weight loss. In practical terms, fasting-based approaches did not outperform more conventional strategies.

Limited evidence on safety and long-term outcomes

The review also highlighted substantial limitations in the available evidence. Reporting of side effects varied widely between studies, and many trials were relatively small. Inconsistent data collection made it difficult to draw firm conclusions about safety or potential long-term effects.

As a result, the overall certainty of the evidence was judged to be limited.

“Intermittent fasting just doesn’t seem to work for overweight or obese adults trying to lose weight,” said Luis Garegnani, lead author of the review from the Universidad Hospital Italiano de Buenos Aires Cochrane Associate Centre.

Social media enthusiasm outpaces the evidence

Garegnani also warned against the level of enthusiasm surrounding intermittent fasting online. “Intermittent fasting may be a reasonable option for some people, but the current evidence doesn’t justify the enthusiasm we see on social media.”

A further concern is the lack of long-term research. Few studies have examined outcomes beyond relatively short trial periods. “Obesity is a chronic condition. Short-term trials make it difficult to guide long-term decision-making for patients and clinicians,” Garegnani added.

Generalisability remains uncertain

Most of the studies included in the review primarily involved white participants living in high-income countries. Given that obesity prevalence is rising rapidly in low and middle-income countries, the findings may not fully reflect outcomes in more diverse global populations.

The authors note that responses to intermittent fasting could vary depending on sex, age, ethnic background, underlying health conditions, or existing eating behaviours and eating disorders.

Implications for clinical practice

Given the current state of evidence, the review’s authors advise caution when recommending intermittent fasting as a weight loss strategy.

“With the current evidence available, it’s hard to make a general recommendation,” said Eva Madrid, senior author from the Cochrane Evidence Synthesis Unit Iberoamerica. “Doctors will need to take a case-by-case approach when advising an overweight adult on losing weight.”

Overall, the findings reinforce the need for personalised, sustainable approaches to weight management rather than reliance on highly promoted dietary trends.

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Big Breakfast Study Shows Protein Reduces Appetite While Fibre Supports Gut Microbiome Health

 Key Takeaways: 

• Within a calorie-restricted big-breakfast eating pattern, a higher-protein breakfast improved satiety, while a higher-fibre breakfast produced more favourable gut microbiota and short-chain fatty acid profiles.
  
• Both dietary approaches led to clinically meaningful short-term weight loss and improvements in metabolic markers, but with distinct physiological effects.
  
• Fibre-rich breakfasts were linked to greater abundance of beneficial butyrate-producing bacteria, whereas protein-rich breakfasts may better support appetite control and dietary adherence.
  
  
  

Background and rationale

A recent study published in the British Journal of Nutrition examined how breakfast composition influences appetite regulation, energy balance and markers of gut microbiota health when consumed as part of a calorie-restricted, big-breakfast weight-loss diet.

There is growing evidence that meal timing, in addition to dietary composition, plays an important role in healthy weight management. Previous research has shown that people who eat earlier in the day tend to lose more weight than those who eat later. Morning calorie intake has also been associated with improved blood glucose control and lower hunger levels compared with evening intake.

Larger breakfasts have been shown to improve appetite control, while late eating patterns have been linked to increased hunger and greater fat storage. Despite public health advice emphasising the importance of breakfast for weight management, relatively little is known about what people typically consume in the morning. Moreover, evidence explaining how meal timing, calorie distribution and macronutrient composition interact to influence appetite remains limited.

Study design and dietary interventions

The researchers used a randomised crossover design to compare two calorie-restricted weight-loss diets with identical big-breakfast calorie distribution but differing macronutrient profiles. The primary outcomes were appetite, energy balance and gut microbiota composition and metabolites, rather than clinical gastrointestinal outcomes.

Healthy adults with overweight or obesity, aged 18–75 years, were recruited. The protocol consisted of:

• a four-day ad libitum diet
  
• a four-day maintenance diet
  
• a 28-day high-fibre weight-loss diet or high-protein weight-loss diet
  

These phases were separated by a washout period, with participants acting as their own controls. Resting metabolic rate was measured by indirect calorimetry during screening.

The maintenance diet provided 15% of energy from protein, 55% from carbohydrate and 30% from fat, and was set at 1.5 times resting metabolic rate to maintain body weight. Both weight-loss diets were set at 100% of resting metabolic rate to induce a calorie deficit.

Participants consumed three meals per day, with 45% of daily calories at breakfast, 20% at lunch and 35% in the evening. Lunch intake was allowed ad libitum within the provided calorie allowance.

• High-fibre weight-loss diet – 50% carbohydrate, 15% protein and 35% fat, incorporating both soluble and insoluble fibre sources such as lentils, fava beans, buckwheat and wheat bran.
  
• High-protein weight-loss diet – 30% protein, 35% carbohydrate and 35% fat, using foods including fish, poultry, eggs, red meat and dairy.
  
  
  

Measurements and outcomes assessed

Body density, waist and hip circumference, resting metabolic rate, total body water and blood pressure were measured. The thermic effect of food was assessed every 30 minutes for four hours after breakfast. Subjective appetite was evaluated using visual analogue scales.

Blood samples collected after an overnight fast were used to assess glucose, lipid profile and insulin as metabolic biomarkers rather than clinical disease outcomes. Insulin and glucose values were used to calculate HOMA-IR, HOMA-β and the insulin-to-glucose ratio. Total body water was measured using deuterium dilution, and faecal samples were collected to analyse gut microbiota composition.

Weight loss, energy expenditure and metabolic markers

Nineteen participants completed the study, including two women. The mean age was 57.4 years and the mean body mass index was 33.3 kg/m², indicating a predominantly male cohort and limiting generalisability to broader populations.

Energy intake did not differ significantly between the two weight-loss diets. Average weight loss was 4.87 kg with the high-fibre diet and 3.87 kg with the high-protein diet. Both diets significantly reduced fat mass and fat-free mass compared with the maintenance diet, although loss of fat-free mass was greater with the high-fibre approach.

Total body water was reduced following the high-fibre diet but not after the high-protein diet. Waist and hip circumferences, as well as waist-to-hip ratio, were significantly reduced with both weight-loss diets compared with the maintenance diet.

The high-protein breakfast maintained postprandial satiety, whereas the high-fibre breakfast was associated with reduced satiety after meals. Resting metabolic rate declined significantly after both weight-loss diets. The thermic effect of food was lower following the high-fibre diet than after the high-protein or maintenance meals.

Both weight-loss diets improved lipid profiles relative to baseline, with no significant difference between the two approaches. Fasting and postprandial glucose levels were reduced by around 10% following the high-fibre diet and by 8–7% following the high-protein diet compared with the maintenance diet. Fasting insulin, HOMA-IR and the insulin-to-glucose ratio were significantly lower after both weight-loss diets.

HOMA-β decreased significantly more after the high-protein diet than after the maintenance diet, with no significant change observed after the high-fibre diet.

Gut microbiota composition and short-chain fatty acids

Total bacterial load in faecal samples did not differ significantly between the two weight-loss diets. However, microbial diversity was lower following the high-protein diet compared with the high-fibre diet.

Distinct differences in microbiota composition were observed between the dietary patterns, although individual variation remained a major determinant of microbiota profiles and diet explained only part of the observed variability.

The high-fibre diet was associated with a greater abundance of butyrate-producing bacteria, including Anaerostipes hadrus, Roseburia faecis and Faecalibacterium prausnitzii. At the genus level, Bifidobacterium, Faecalibacterium and Roseburia were linked to the high-fibre diet, while Streptococcus was associated with the high-protein diet.

Total short-chain fatty acids and key faecal short-chain fatty acids, including acetate, butyrate and propionate, were significantly lower with the high-protein diet compared with the high-fibre diet.

Interpretation and clinical implications

Overall, the findings suggest that within a calorie-restricted big-breakfast eating pattern, breakfast composition meaningfully influences short-term weight loss, metabolic health markers and gut microbiota characteristics.

Both dietary approaches led to significant weight reduction and metabolic improvements. The high-protein breakfast produced greater satiation, which may support long-term adherence in some people. In contrast, the high-fibre breakfast promoted a more favourable gut microbiota profile and higher short-chain fatty acid production, which may be beneficial for long-term gut health, although this was inferred from microbial and metabolic markers rather than direct clinical outcomes.

The authors emphasised that longer-term studies are needed to determine whether these differences are sustained over time and how they translate into long-term health outcomes.

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Obesity Associated With Higher Risk of Severe Infectious Disease, Large Study Finds

Key Takeaways:

• People living with obesity face a substantially higher risk of hospitalisation or death from a wide range of common infections, with risk increasing alongside body weight.
  
• Weight change matters – moving out of obesity is associated with fewer severe infections, while progression into obesity increases risk.
  
• Global estimates suggest that around one in ten infectious disease deaths worldwide may be linked to obesity.
  
  
  

Obesity and severe infection risk across multiple pathogens

A large population-based study has examined the relationship between obesity and the risk of severe infectious diseases, finding that people living with obesity are significantly more likely to be hospitalised or die from common infections. These include influenza, Covid-19, pneumonia, and gastrointestinal and urinary tract infections. For people living with morbid obesity, the risk was approximately three times higher than for people of healthy weight.

“During the pandemic, obesity was widely linked to a higher likelihood of severe Covid-19. We set out to investigate how broadly this link applies across different types of infections and whether any underlying factors contribute to it. Our findings extend beyond any single pathogen, with similar associations observed for bacterial, viral, parasitic and fungal infections,” says one of the article’s lead authors, Solja Nyberg of the University of Helsinki and the Finnish Institute of Occupational Health.

Notably, HIV and tuberculosis were exceptions, with no evidence that obesity increased the risk of severe disease for these infections. The researchers also found that comorbidities, socioeconomic status, and lifestyle factors such as alcohol consumption and physical activity did not explain the increased infection risk associated with obesity.

Weight matters for infection outcomes

Participants were followed for an average of 13–14 years, with body mass index (BMI) measured at baseline. People living with obesity, defined as a BMI of 30 kg/m² or higher, had a 70% greater risk of hospitalisation or death from any infectious disease compared with people of healthy weight, defined as a BMI of 18.5–24.9. The risk increased progressively with higher body weight.

People living with morbid obesity, defined as a BMI of 40 kg/m² or higher, experienced a risk of severe infection three times that of people of healthy weight.

Importantly, changes in body weight over time were also associated with changes in risk. Participants who lost weight and moved from obesity to overweight or healthy weight experienced 20% fewer severe infections compared with those whose obesity persisted. In contrast, weight gain from overweight to obesity was linked to a 30% higher risk of severe infection.

Possible links with immune system dysfunction

“Obesity is a well-known risk factor for diabetes and other chronic diseases. The links now identified indicate that severe infectious diseases should be added to the same list,” says Mika Kivimäki of the University of Helsinki and University College London, who led the study.

“Obesity seems to weaken the immune system’s ability to manage infections, raising the risk of severe disease,” he explains.

Kivimäki also notes that experimental evidence from studies of weight-loss drugs supports a link between obesity and immune function. Reductions in body weight appear to lower the risk of severe infections alongside other health benefits. However, he emphasises that further research is needed to confirm the biological mechanisms underlying these associations.

Obesity and global infectious disease mortality

The researchers analysed data from large Finnish cohorts and the UK Biobank, tracking participants through national health registers. They also incorporated infectious disease mortality data from the Global Burden of Disease study to assess how obesity contributes to infectious disease deaths across countries and regions.

Their analysis suggests that approximately 0.6 million of the 5.4 million infectious disease deaths recorded worldwide in 2023, equivalent to around 11% or one in ten, were associated with obesity.

In the Nordic countries, the estimated proportions of infectious disease deaths linked to obesity were:

• Finland – 19%
  
• Sweden – 13%
  
• Norway – 11%
  
• Denmark – 12%
  

Among high-income countries, the United States recorded the highest proportion in 2023, at 26%.

Importance of vaccination and prevention

The researchers stress that adults living with obesity should ensure their vaccinations are up to date and take up booster doses when offered to groups at higher risk of severe infection.

They also highlight several limitations of the study. As an observational analysis, it cannot establish causality. In addition, participants in the Finnish cohorts and the UK Biobank are not fully representative of the general population, meaning the findings should be generalised with caution.

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