Belly Weight Predicts Heart Health Better Than BMI, Study Indicates
Key Takeaways:
- Fat stored around the waist is a stronger predictor of heart disease than body mass index alone.
- People with preclinical obesity face a raised cardiovascular risk despite appearing healthy.
- Researchers estimate early intervention could prevent 45% of new cardiovascular disease cases.
Why waist size matters more than the scales
People living with overweight or obesity can carry a higher risk of heart disease even when they appear to be perfectly healthy, according to new research presented at the International Congress on Obesity in Mexico City (15–17 July). Combining waist-based measurements with body mass index (BMI) to detect this hidden risk and act early could, over the years ahead, prevent hundreds of thousands of people from dying from heart attacks, strokes and other cardiac problems, researchers from the University of Glasgow, Glasgow, UK, said.
“We know that excess weight, particularly around the waist, increases the risk of heart disease,” said lead researcher Estefania Fuentes Avalos. “In 2021, an estimated 1.9 million cardiovascular disease deaths – almost one in 10 heart-related deaths worldwide – were attributed to high body mass index.
“The link between central, or abdominal, obesity and heart disease is especially strong because fat stored around the waist, known as visceral fat, is metabolically active and releases inflammatory substances into the bloodstream. Over time, this chronic inflammatory state can damage blood vessels and accelerate the buildup of arterial plaque, significantly increasing the risk of heart attacks.”
The limits of BMI
BMI, a measure of weight compared with height, is routinely used to assess a person’s weight status, defining whether they have a normal weight, overweight or obesity. However, it does not take into account where fat is stored in the body.
To address this and other shortcomings of BMI, The Lancet Diabetes & Endocrinology Commission recently proposed a different way of assessing obesity status. The Lancet Commission framework uses BMI together with central adiposity markers – waist measurements – to determine whether a person has excess body fat. People with excess body fat are then categorised as having either preclinical obesity or clinical obesity, depending on whether they also have long-term obesity-related conditions such as high blood pressure, joint pain and sleep apnoea.
The new study set out to establish whether this method is better at identifying people at high risk of cardiovascular disease than BMI alone.
“Detecting cardiovascular risk at an early stage is essential, particularly at the preclinical stage of obesity, as it provides a window of opportunity to implement timely, targeted interventions before obesity-related complications such as high blood pressure arise,” Fuentes Avalos said.
“This underpins our focus on risk stratification in this group, with the aim of detecting high-risk individuals who may otherwise be overlooked.”
What the study looked at
Fuentes Avalos examined data on 382,769 adults of white ethnicity in the UK Biobank study (age range 40–69 years, average age 56 years, 53% women).
Under The Lancet Commission framework, 285,190 (74%) of the participants had excess body fat, based on BMI and central adiposity markers. Within this group, 102,237 (26.7%) were classified as having preclinical obesity – excess body fat without long-term obesity-related conditions – and 182,953 (47.8%) as having clinical obesity, meaning excess body fat alongside long-term obesity-related conditions. The remainder had neither excess body fat nor long-term obesity-related conditions; they were classified as not having obesity and served as the reference group.
None of the participants had cardiovascular disease at the start of the study. Hospital and death records provided information about diagnoses of, and deaths from, heart attacks, strokes and other forms of cardiovascular disease over the following 12 years. During this time, there were 41,742 new cases of, and 8,832 deaths from, cardiovascular disease. Studies of this scale underline how much practical assessment skill clinicians need when supporting patients with excess weight – a competency CCH’s Obesity Essentials short course is designed to build.
Clinical obesity carried the sharpest risk
Analysis of the data showed that people with clinical obesity were far more likely to develop, or die from, cardiovascular disease than those without obesity.
Women with clinical obesity developed cardiovascular disease at a rate 2.5-fold higher than women without obesity, and died from it at an almost threefold (2.8-fold) higher rate. Men with clinical obesity developed cardiovascular disease at an almost twofold higher rate (1.9-fold) and had a 2.6-fold higher rate of cardiovascular death than men without obesity.
The hidden risk in preclinical obesity
People with preclinical obesity were also at greater risk, despite having no obesity-related conditions and appearing to be in good health.
Women with preclinical obesity developed cardiovascular disease at a 38% higher rate and died from it at a 46% higher rate than women without obesity. For men, preclinical obesity was associated with an 18% higher rate of developing cardiovascular disease and a 52% higher rate of cardiovascular death.
All of the results were adjusted for socioeconomic status and lifestyle factors, including smoking and alcohol consumption.
More waist markers, more risk
Further analysis showed that the more high-risk central adiposity markers a person had, the more likely they were to develop heart disease. For example, a woman with one high-risk marker – waist circumference, waist-to-hip ratio or waist-to-height ratio – was 17% more likely to develop cardiovascular disease than a woman with no high-risk waist measurements. Having all three high-risk measurements increased the risk by 64%. The study also found that waist measurements were more accurate at predicting cardiovascular disease than BMI.
A window of opportunity
The researchers concluded that people with preclinical obesity are at higher risk of developing, and dying from, cardiovascular disease despite appearing to be healthy.
“Preclinical obesity is a critical window of opportunity to improve heart health. Routinely measuring waist circumference, waist-to-hip ratio and waist-to-height ratio along with BMI would identify high-risk individuals who might be overlooked by assessing BMI alone,” Fuentes Avalos said.
“They could then be offered intensive diet and exercise programs to improve their cardiac and overall health.
“We have calculated that early intervention could prevent 45% of new cases of cardiovascular disease and 41% of cardiovascular disease deaths in similar populations.
“Given that cardiovascular disease remains a leading cause of ill health and death globally, routinely taking waist measurements along with BMI could prevent hundreds of thousands of deaths over a decade alone.”
CCH insight
This is very important work on two levels. Firstly, it not only re-enforces the importance of waist circumference measures as superior indicators of disease risk compared to the traditional BMI measure, but also suggests that calculating three waist circumference markers gives a more accurate indication of CV risk than just one. And secondly, it feeds into the current debate around the terms ‘clinical’ and ‘pre-clinical’ obesity coined by The Lancet Diabetes & Endocrinology Commission. The results indicate that, while people with clinical obesity have a far higher risk of cardiovascular disease or death, those with pre-clinical obesity are still at risk and still therefore warrant intervention. Depending on your perspective, you could argue this supports the Commission’s findings or contradicts them!
Findings like these are only useful in practice if clinicians feel confident assessing excess weight and having sensitive, evidence-based conversations with patients about it. CCH’s Obesity Essentials – an online CPD short course offering 10 CPD hours – equips healthcare professionals with the practical skills to assess and manage patients living with overweight and obesity, from measurement through to compassionate communication.
Explore Obesity Essentials and strengthen your day-to-day weight-management practice.
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How Losing Around 80 Minutes of Sleep a Night Could Drive Weight Gain and Inactivity
Key Takeaways:
- Adults who cut their nightly sleep by about 80 minutes over six weeks gained roughly one pound (around 0.45 kg) on average and became more sedentary, Columbia University researchers found.
- Modest over six weeks, but the team estimates that sustaining this mild sleep loss for a year could cause clinically meaningful weight gain – a pattern affecting around 30% of adults.
- Related work in the same participants linked mild sleep restriction to greater insulin resistance and heart inflammation, pointing to a wider risk of type 2 diabetes and heart disease.
Why modest sleep loss deserves attention
Trimming a little sleep each night may carry more weight for your health than you might realise. Researchers at Columbia University Vagelos College of Physicians and Surgeons found that adults who shortened their nightly sleep by about 80 minutes over a six-week period gained an average of one pound and spent more of their waking hours being inactive.
The findings add to a growing body of evidence suggesting that consistently getting enough sleep may play an important role in preventing weight gain and in lowering the risk of obesity-related disease. Rather than pointing solely to diet and exercise, the results place sleep alongside them as a factor worth taking seriously.
“Our study shows that getting adequate sleep may help reduce the risk of weight gain and obesity-related conditions like heart disease and diabetes,” says Marie-Pierre St-Onge, a professor of nutritional medicine in Columbia’s Department of Medicine and Institute for Human Nutrition and the study leader. “People tend to gain weight over the course of their adulthood, and obesity is a major risk factor for heart disease. But focusing on eating a healthier diet and getting more physical activity to offset weight gain is simplistic and can be difficult to maintain.”
Looking beyond extreme sleep deprivation
Much of the earlier research connecting poor sleep with obesity has centred on severe sleep deprivation, frequently restricting people to as little as four hours of sleep a night. Those studies indicated that extreme sleep loss can heighten appetite and encourage overeating – behaviours that in turn contribute to weight gain.
The difficulty is that such severe restriction is hard for most people to sustain for more than a few days, which limits how far the results can be applied to everyday life. Very few people live with four hours of sleep for weeks at a time, so the relevance of those findings to the wider population has remained uncertain.
“These studies only show us what happens under the most extreme conditions and don’t tell us if mildly sleep-deprived people, like a lot of Americans who get 5 or 6 hours of sleep a night, will gain weight,” St-Onge says.
To reflect real-world habits more closely, the researchers set out to examine the effects of chronic, mild sleep loss – a pattern estimated to affect around 30% of adults.
Six weeks of less sleep led to measurable changes
The study involved 95 adults who typically slept between seven and eight hours each night. During one six-week phase, participants delayed their usual bedtime by 90 minutes, which shortened their nightly sleep. During a separate six-week phase, they kept to their normal sleep schedule, allowing each participant to serve as their own comparison.
Across both phases, participants wore wrist monitors that tracked sleep and physical activity. The researchers also measured body weight, waist circumference, body composition, and fasting levels of several hormones involved in regulating appetite, building a detailed picture of how the body responded to the change.
“While the one-pound weight gain observed with modest sleep curtailment is not overwhelming, it is important to remember this is occurring over just six weeks,” says Faris Zuraikat, assistant professor of nutritional medicine in Columbia’s Department of Medicine and Institute for Human Nutrition and first author of the study. “Our study was designed to mimic sleep patterns that most adults experience chronically. When extrapolated to a full year, we would expect that losing less than an hour and a half of sleep per night could result in clinically meaningful weight gain.”
Less sleep also meant more sitting
Alongside the change in weight, the researchers found that participants became less active during the sleep-restriction phase. On average, sedentary time rose by 17 minutes per day. Among men and postmenopausal women, inactivity climbed by nearly 30 minutes each day.
Notably, this increase in sitting held up even after accounting for the extra waking hours that come with shorter sleep – so the added inactivity was not simply a matter of being awake for longer.
“Even when we accounted for the fact that they were awake longer when sleep was shortened, participants spent more time being inactive than when they got adequate sleep,” Zuraikat says. “This is notable, as people who are more sedentary have elevated risk for chronic diseases.”
Earlier research suggests broader health effects
The same group of participants has featured in several related studies, which together suggest that the consequences of mild sleep loss may extend well beyond weight. In one earlier investigation, women with increased cardiometabolic risk who reduced their sleep by about 80 minutes each night for six weeks developed greater insulin resistance – an important risk factor for type 2 diabetes. The effect was particularly pronounced in postmenopausal women.
A separate study found that men and women with an elevated risk of heart disease developed an influx of inflammatory cells in the heart after undergoing mild sleep restriction, hinting at a possible mechanism linking short sleep to cardiovascular harm.
“Though more research is needed to further understand how sleep restriction leads to weight gain, all of our findings suggest that insufficient sleep increases the risk of obesity-related conditions like type 2 diabetes and heart disease,” St-Onge says.
“Now we need to understand the health effects of improving sleep in those who fail to get adequate sleep on a regular basis.”
About the study
The study, titled “Skimping on Sleep and Its Impact on Body Weight and Composition: A Pooled Analysis of Randomized Trials,” was published on 6 July in Annals of Internal Medicine.
The authors are Faris Zuraikat, Samantha Scaccia, Justin Cochran, Bin Cheng, Keith Diaz, Seth Creasy (University of Colorado), Brooke Aggarwal, Sanja Jelic, and Marie-Pierre St-Onge. The authors report no conflicts of interest.
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Carbohydrate-Rich Diets May Promote Weight Gain Even Without Higher Calorie Intake
Key Takeaways:
- A new mouse study found that carbohydrate-rich foods such as bread, wheat flour, and rice flour promoted weight gain and fat accumulation even when total calorie intake did not significantly increase.
- Researchers observed that the weight gain appeared to be linked more closely to reduced energy expenditure and metabolic changes than to overeating.
- Scientists say future human studies will explore how factors such as whole grains, fibre content, food processing, meal timing, and combinations with protein and fat influence metabolic responses to carbohydrates.
Bread and carbohydrates under renewed scrutiny
Bread has served as a central part of human diets for centuries and remains a staple food in many cultures around the world. Foods such as bread, rice, noodles, and other carbohydrate-rich staples continue to form the foundation of everyday meals for billions of people.
However, as rates of overweight and obesity continue to increase globally, researchers are re-examining how modern dietary patterns may influence body weight and metabolic health. While high-fat diets have traditionally received much of the attention in obesity research, scientists are now taking a closer look at the role carbohydrates may play in weight regulation.
A new study led by researchers at Osaka Metropolitan University suggests that certain carbohydrate-heavy eating patterns may contribute to weight gain in ways that are not solely explained by consuming more calories.
The findings were published in Molecular Nutrition & Food Research.
Obesity research has traditionally focused on fat intake
Obesity is associated with a broad range of chronic conditions and lifestyle-related diseases, including type 2 diabetes, cardiovascular disease, and metabolic dysfunction. Because of this, understanding the drivers of weight gain has become an increasingly important area of scientific research.
Historically, many obesity studies have focused primarily on dietary fat as the main contributor to excess weight gain. This is reflected in the widespread use of high-fat diets in animal research investigating obesity and metabolism.
At the same time, carbohydrate-rich foods remain deeply embedded in daily diets across the world. Despite their prominence, the metabolic effects of staple carbohydrates such as bread, rice, and noodles have not always been explored in the same depth.
Public perceptions around carbohydrates also remain widespread. Beliefs such as “bread makes you gain weight” or “carbohydrates should be restricted” are common, yet researchers say it has remained unclear whether such effects are driven by the foods themselves, overall dietary habits, eating behaviour, or broader metabolic responses.
Researchers investigated how carbohydrate-rich foods affect metabolism
To better understand the relationship between carbohydrates and weight gain, researchers led by Professor Shigenobu Matsumura at Osaka Metropolitan University’s Graduate School of Human Life and Ecology conducted a series of experiments in mice.
The study examined whether mice would preferentially select carbohydrate-rich foods over standard laboratory chow and how those dietary choices would affect body weight, metabolism, and energy expenditure.
The mice were separated into several dietary groups, including:
- Chow
- Chow + Bread
- Chow + Wheat Flour
- Chow + Rice Flour
- High-fat diet (HFD) + Chow
- High-fat diet (HFD) + Wheat Flour
Researchers monitored multiple metabolic indicators throughout the study, including:
- Body weight
- Fat mass
- Energy expenditure
- Blood metabolites
- Liver gene activity
Mice preferred carbohydrate-rich foods
The researchers found that mice consistently showed a strong preference for carbohydrate-rich foods. Animals given access to bread, wheat flour, or rice flour largely abandoned their standard chow diet in favour of these carbohydrate sources.
Importantly, the researchers reported that overall calorie intake did not increase substantially despite this dietary shift. Nevertheless, mice consuming the carbohydrate-rich diets still experienced increases in body weight and fat mass.
Rice flour produced similar effects to wheat flour, suggesting the observed metabolic changes were not specific to wheat itself.
Interestingly, mice in the High-fat diet (HFD) + Wheat flour group gained less weight than those in the High-fat diet (HFD) + Chow group, indicating that the interaction between fat and carbohydrate intake may be more complex than previously assumed.
“These findings suggest that weight gain may not be due to wheat-specific effects, but rather to a strong preference for carbohydrates and the associated metabolic changes,” said Professor Matsumura.
Reduced energy expenditure appeared to play a key role
To investigate why the mice gained weight without substantially increasing calorie intake, the researchers carried out further metabolic analysis using indirect calorimetry and respiratory gas measurements.
The findings suggested that the weight gain was not primarily caused by overeating. Instead, the animals appeared to experience reduced energy expenditure, meaning they were burning fewer calories.
Researchers also identified several metabolic changes in the mice consuming the carbohydrate-rich diets.
Blood analysis showed:
- Increased fatty acid levels
- Reduced levels of essential amino acids
Meanwhile, examination of the liver revealed:
- Greater fat accumulation
- Increased activity of genes involved in fatty acid synthesis
- Increased activity of genes associated with lipid transport
Together, these findings suggest that carbohydrate-heavy dietary patterns may alter how the body processes and stores energy.
Metabolic changes improved when carbohydrates were reduced
The researchers also observed that removing wheat flour from the diet rapidly improved both body weight and several metabolic abnormalities.
According to the authors, this finding suggests that moving away from a highly carbohydrate-focused dietary pattern and towards a more balanced eating pattern may help improve metabolic regulation.
However, the researchers emphasised that additional work is needed to determine how these findings translate to human diets and real-world eating behaviour.
Future studies will explore human dietary patterns
The research team says the next phase of investigation will focus on understanding whether similar metabolic effects occur in people.
“Going forward, we plan to shift our research focus to humans to verify the extent to which the metabolic changes identified in this study apply to actual dietary habits,” stated Professor Matsumura.
“We also intend to investigate how factors such as whole grains, unrefined grains, and foods rich in dietary fiber, as well as their combinations with proteins and fats, food processing methods, and timing of consumption, affect metabolic responses to carbohydrate intake. In the future, we hope this will serve as a scientific foundation for achieving a balance between ‘taste’ and ‘health’ in the fields of nutritional guidance, food education, and food development.”
The researchers noted that future studies examining food quality, fibre content, food combinations, and meal timing may help provide a more nuanced understanding of how carbohydrates influence metabolism and body weight.
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