Obesity

TOPLINE:

Endoscopic sleeve gastroplasty (ESG) is more cost-effective, and achieves and sustains greater weight loss, than semaglutide over a 5-year period in patients with class II obesity.

METHODOLOGY:

• Researchers used a Markov cohort model to assess the cost-effectiveness of semaglutide vs ESG over 5 years in people with class II obesity (body mass index [BMI], 35-39.9), with the model costs based on the US healthcare system.
• A 45-year-old patient with a BMI of 37 was included as the base case in this study.
• The model simulated hypothetical patients with class II obesity who received ESG, semaglutide, or no treatment (reference group with zero treatment costs).
• The model derived clinical data for the first year from two randomized clinical trials, STEP 1 (semaglutide) and MERIT (ESG); for the following years, data were derived from published studies and publicly available data sources.
• Study outcomes were total costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratio (ICER).

TAKEAWAY:

• ESG led to better weight loss outcomes (BMI, 31.7 vs 33.0) and added 0.06 more QALYs relative to semaglutide in the modelled patients over the 5-year time horizon; about 20% of the patients receiving semaglutide dropped out owing to medication intolerance or other reasons.
• The semaglutide treatment was $33,583 more expensive than the ESG treatment over the 5-year period.
• ESG became more cost-effective than semaglutide at 2 years and remained so over a 5-year time horizon, with an ICER of — $595,532 per QALY for the base case.
• The annual price of semaglutide would need to be reduced from $13,618 to $3591 to achieve nondominance compared with ESG.

IN PRACTICE:

“The strategic choice of cost saving yet effective treatment such as ESG compared with semaglutide for specific patient groups could help alleviate the potential budget strain expected from the use of semaglutide,” the authors wrote.

SOURCE:

Muhammad Haseeb, MD, MSc, Division of Gastroenterology, Hepatology and Endoscopy, Brigham and Women’s Hospital, Boston, led this study, which was published online on April 12, 2024, in JAMA Network Open.

LIMITATIONS:

The study did not look at benefits associated with improvements in comorbidities from either treatment strategy, and the model used did not account for any microlevel follow-up costs such as routine clinic visits. The authors acknowledged that semaglutide’s prices may fall in the future when more anti-obesity drugs get approved.

DISCLOSURES:

This study was supported in part by the National Institutes of Health. Some authors declared receiving personal fees, royalty payments, and/or grants and having other ties with several sources.

A version of this article appeared on Medscape.com.

TOPLINE:

Endoscopic sleeve gastroplasty (ESG) is more cost-effective, and achieves and sustains greater weight loss, than semaglutide over a 5-year period in patients with class II obesity.

METHODOLOGY:

• Researchers used a Markov cohort model to assess the cost-effectiveness of semaglutide vs ESG over 5 years in people with class II obesity (body mass index [BMI], 35-39.9), with the model costs based on the US healthcare system.
• A 45-year-old patient with a BMI of 37 was included as the base case in this study.
• The model simulated hypothetical patients with class II obesity who received ESG, semaglutide, or no treatment (reference group with zero treatment costs).
• The model derived clinical data for the first year from two randomized clinical trials, STEP 1 (semaglutide) and MERIT (ESG); for the following years, data were derived from published studies and publicly available data sources.
• Study outcomes were total costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratio (ICER).

TAKEAWAY:

• ESG led to better weight loss outcomes (BMI, 31.7 vs 33.0) and added 0.06 more QALYs relative to semaglutide in the modelled patients over the 5-year time horizon; about 20% of the patients receiving semaglutide dropped out owing to medication intolerance or other reasons.
• The semaglutide treatment was $33,583 more expensive than the ESG treatment over the 5-year period.
• ESG became more cost-effective than semaglutide at 2 years and remained so over a 5-year time horizon, with an ICER of — $595,532 per QALY for the base case.
• The annual price of semaglutide would need to be reduced from $13,618 to $3591 to achieve nondominance compared with ESG.

IN PRACTICE:

“The strategic choice of cost saving yet effective treatment such as ESG compared with semaglutide for specific patient groups could help alleviate the potential budget strain expected from the use of semaglutide,” the authors wrote.

SOURCE:

Muhammad Haseeb, MD, MSc, Division of Gastroenterology, Hepatology and Endoscopy, Brigham and Women’s Hospital, Boston, led this study, which was published online on April 12, 2024, in JAMA Network Open.

LIMITATIONS:

The study did not look at benefits associated with improvements in comorbidities from either treatment strategy, and the model used did not account for any microlevel follow-up costs such as routine clinic visits. The authors acknowledged that semaglutide’s prices may fall in the future when more anti-obesity drugs get approved.

DISCLOSURES:

This study was supported in part by the National Institutes of Health. Some authors declared receiving personal fees, royalty payments, and/or grants and having other ties with several sources.

A version of this article appeared on Medscape.com.

TOPLINE:

Endoscopic sleeve gastroplasty (ESG) is more cost-effective, and achieves and sustains greater weight loss, than semaglutide over a 5-year period in patients with class II obesity.

METHODOLOGY:

• Researchers used a Markov cohort model to assess the cost-effectiveness of semaglutide vs ESG over 5 years in people with class II obesity (body mass index [BMI], 35-39.9), with the model costs based on the US healthcare system.
• A 45-year-old patient with a BMI of 37 was included as the base case in this study.
• The model simulated hypothetical patients with class II obesity who received ESG, semaglutide, or no treatment (reference group with zero treatment costs).
• The model derived clinical data for the first year from two randomized clinical trials, STEP 1 (semaglutide) and MERIT (ESG); for the following years, data were derived from published studies and publicly available data sources.
• Study outcomes were total costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratio (ICER).

TAKEAWAY:

• ESG led to better weight loss outcomes (BMI, 31.7 vs 33.0) and added 0.06 more QALYs relative to semaglutide in the modelled patients over the 5-year time horizon; about 20% of the patients receiving semaglutide dropped out owing to medication intolerance or other reasons.
• The semaglutide treatment was $33,583 more expensive than the ESG treatment over the 5-year period.
• ESG became more cost-effective than semaglutide at 2 years and remained so over a 5-year time horizon, with an ICER of — $595,532 per QALY for the base case.
• The annual price of semaglutide would need to be reduced from $13,618 to $3591 to achieve nondominance compared with ESG.

IN PRACTICE:

“The strategic choice of cost saving yet effective treatment such as ESG compared with semaglutide for specific patient groups could help alleviate the potential budget strain expected from the use of semaglutide,” the authors wrote.

SOURCE:

Muhammad Haseeb, MD, MSc, Division of Gastroenterology, Hepatology and Endoscopy, Brigham and Women’s Hospital, Boston, led this study, which was published online on April 12, 2024, in JAMA Network Open.

LIMITATIONS:

The study did not look at benefits associated with improvements in comorbidities from either treatment strategy, and the model used did not account for any microlevel follow-up costs such as routine clinic visits. The authors acknowledged that semaglutide’s prices may fall in the future when more anti-obesity drugs get approved.

DISCLOSURES:

This study was supported in part by the National Institutes of Health. Some authors declared receiving personal fees, royalty payments, and/or grants and having other ties with several sources.

A version of this article appeared on Medscape.com.

TOPLINE:

No significant association was found between the use of glucagon-like peptide 1 receptor agonists (GLP-1 RAs) and thyroid cancer over nearly 4 years.

METHODOLOGY:

• A cohort study using data from nationwide registers in Denmark, Norway, and Sweden between 2007 and 2021 included 145,410 patients who initiated GLP-1 RAs and 291,667 propensity score-matched patients initiating dipeptidyl peptidase 4 (DPP4) inhibitors as active comparators.
• Additional analysis included 111,744 who initiated GLP-1 RAs and 148,179 patients initiating sodium-glucose cotransporter 2 (SGLT2) inhibitors.
• Overall, mean follow-up time was 3.9 years, with 25% followed for more than 6 years.

TAKEAWAY:

• The most common individual GLP-1 RAs were liraglutide (57.3%) and semaglutide (32.9%).
• During follow-up, there were 76 incident thyroid cancer cases among GLP-1 RA users and 184 cases in DPP4 inhibitor users, giving incidence rates per 10,000 of 1.33 and 1.46, respectively, a nonsignificant difference (hazard ratio [HR], 0.93; 95% CI, 0.66-1.31).
• Papillary thyroid cancer was the most common thyroid cancer subtype, followed by follicular and medullary, with no significant increases in risk with GLP-1 RAs by cancer type, although the numbers were small.
• In the SGLT2 inhibitor comparison, there was also no significantly increased thyroid cancer risk for GLP-1 RAs (HR, 1.16; 95% CI, 0.65-2.05).

IN PRACTICE:

“Given the upper limit of the confidence interval, the findings are incompatible with more than a 31% increased relative risk of thyroid cancer. In absolute terms, this translates to no more than 0.36 excess cases per 10 000 person-years, a figure that should be interpreted against the background incidence of 1.46 per 10,000 person-years among the comparator group in the study populations.”

SOURCE:

This study was conducted by Björn Pasternak, MD, PhD, of the Karolinska Institutet, Stockholm, and colleagues. It was published online on April 10, 2024, in The BMJ.

LIMITATIONS:

Relatively short follow-up for cancer risk. Risk by individual GLP-1 RA not analyzed. Small event numbers. Observational, with potential for residual confounding and time-release bias.

DISCLOSURES:

The study was supported by grants from the Swedish Cancer Society and the Swedish Research Council. Dr. Pasternak was supported by a consolidator investigator grant from Karolinska Institutet. Some of the coauthors had industry disclosures.

A version of this article appeared on Medscape.com.

TOPLINE:

No significant association was found between the use of glucagon-like peptide 1 receptor agonists (GLP-1 RAs) and thyroid cancer over nearly 4 years.

METHODOLOGY:

• A cohort study using data from nationwide registers in Denmark, Norway, and Sweden between 2007 and 2021 included 145,410 patients who initiated GLP-1 RAs and 291,667 propensity score-matched patients initiating dipeptidyl peptidase 4 (DPP4) inhibitors as active comparators.
• Additional analysis included 111,744 who initiated GLP-1 RAs and 148,179 patients initiating sodium-glucose cotransporter 2 (SGLT2) inhibitors.
• Overall, mean follow-up time was 3.9 years, with 25% followed for more than 6 years.

TAKEAWAY:

• The most common individual GLP-1 RAs were liraglutide (57.3%) and semaglutide (32.9%).
• During follow-up, there were 76 incident thyroid cancer cases among GLP-1 RA users and 184 cases in DPP4 inhibitor users, giving incidence rates per 10,000 of 1.33 and 1.46, respectively, a nonsignificant difference (hazard ratio [HR], 0.93; 95% CI, 0.66-1.31).
• Papillary thyroid cancer was the most common thyroid cancer subtype, followed by follicular and medullary, with no significant increases in risk with GLP-1 RAs by cancer type, although the numbers were small.
• In the SGLT2 inhibitor comparison, there was also no significantly increased thyroid cancer risk for GLP-1 RAs (HR, 1.16; 95% CI, 0.65-2.05).

IN PRACTICE:

“Given the upper limit of the confidence interval, the findings are incompatible with more than a 31% increased relative risk of thyroid cancer. In absolute terms, this translates to no more than 0.36 excess cases per 10 000 person-years, a figure that should be interpreted against the background incidence of 1.46 per 10,000 person-years among the comparator group in the study populations.”

SOURCE:

This study was conducted by Björn Pasternak, MD, PhD, of the Karolinska Institutet, Stockholm, and colleagues. It was published online on April 10, 2024, in The BMJ.

LIMITATIONS:

Relatively short follow-up for cancer risk. Risk by individual GLP-1 RA not analyzed. Small event numbers. Observational, with potential for residual confounding and time-release bias.

DISCLOSURES:

The study was supported by grants from the Swedish Cancer Society and the Swedish Research Council. Dr. Pasternak was supported by a consolidator investigator grant from Karolinska Institutet. Some of the coauthors had industry disclosures.

A version of this article appeared on Medscape.com.

TOPLINE:

No significant association was found between the use of glucagon-like peptide 1 receptor agonists (GLP-1 RAs) and thyroid cancer over nearly 4 years.

METHODOLOGY:

• A cohort study using data from nationwide registers in Denmark, Norway, and Sweden between 2007 and 2021 included 145,410 patients who initiated GLP-1 RAs and 291,667 propensity score-matched patients initiating dipeptidyl peptidase 4 (DPP4) inhibitors as active comparators.
• Additional analysis included 111,744 who initiated GLP-1 RAs and 148,179 patients initiating sodium-glucose cotransporter 2 (SGLT2) inhibitors.
• Overall, mean follow-up time was 3.9 years, with 25% followed for more than 6 years.

TAKEAWAY:

• The most common individual GLP-1 RAs were liraglutide (57.3%) and semaglutide (32.9%).
• During follow-up, there were 76 incident thyroid cancer cases among GLP-1 RA users and 184 cases in DPP4 inhibitor users, giving incidence rates per 10,000 of 1.33 and 1.46, respectively, a nonsignificant difference (hazard ratio [HR], 0.93; 95% CI, 0.66-1.31).
• Papillary thyroid cancer was the most common thyroid cancer subtype, followed by follicular and medullary, with no significant increases in risk with GLP-1 RAs by cancer type, although the numbers were small.
• In the SGLT2 inhibitor comparison, there was also no significantly increased thyroid cancer risk for GLP-1 RAs (HR, 1.16; 95% CI, 0.65-2.05).

IN PRACTICE:

“Given the upper limit of the confidence interval, the findings are incompatible with more than a 31% increased relative risk of thyroid cancer. In absolute terms, this translates to no more than 0.36 excess cases per 10 000 person-years, a figure that should be interpreted against the background incidence of 1.46 per 10,000 person-years among the comparator group in the study populations.”

SOURCE:

This study was conducted by Björn Pasternak, MD, PhD, of the Karolinska Institutet, Stockholm, and colleagues. It was published online on April 10, 2024, in The BMJ.

LIMITATIONS:

Relatively short follow-up for cancer risk. Risk by individual GLP-1 RA not analyzed. Small event numbers. Observational, with potential for residual confounding and time-release bias.

DISCLOSURES:

The study was supported by grants from the Swedish Cancer Society and the Swedish Research Council. Dr. Pasternak was supported by a consolidator investigator grant from Karolinska Institutet. Some of the coauthors had industry disclosures.

A version of this article appeared on Medscape.com.

You are what you eat, as the adage goes. But a growing body of evidence indicates that it’s not just what and how much you eat that influence your health. How fast and when you eat also play a role.

Research now indicates that these two factors may affect the risk for gastrointestinal problems, obesity, and type 2 diabetes (T2D). Because meal timing and speed of consumption are modifiable, they present new opportunities to change patient behavior to help prevent and perhaps address these conditions.

Not So Fast

Most people are well acquainted with the short-term gastrointestinal effects of eating too quickly, which include indigestion, gas, bloating, and nausea. But regularly eating too fast can cause long-term consequences.

Obtaining a sense of fullness is key to staving off overeating and excess caloric intake. However, it takes approximately 20 minutes for the stomach to alert the brain to feelings of fullness. Eat too quickly and the fullness signaling might not set in until you’ve consumed more calories than intended. Research links this habit to excess body weight.

The practice also can lead to gastrointestinal diseases over the long term because overeating causes food to remain in the stomach longer, thus prolonging the time that the gastric mucosa is exposed to gastric acids.

A study of 10,893 adults in Korea reported that those with the fastest eating speed (< 5 min/meal) had a 1.7 times greater likelihood of endoscopic erosive gastritis than those with the slowest times (≥ 15 min/meal). Faster eating also was linked to increased risk for functional dyspepsia in a study involving 89 young-adult female military cadets in Korea with relatively controlled eating patterns.

On the extreme end of the spectrum, researchers who performed an assessment of a competitive speed eater speculated that the observed physiological accommodation required for the role (expanding the stomach to form a large flaccid sac) makes speed eaters vulnerable to morbid obesity, gastroparesis, intractable nausea and vomiting, and the need for gastrectomy.

The risk for metabolic changes and eventual development of T2D also appear to be linked to how quickly food is consumed.

Two clinical studies conducted in Japan — a cohort study of 2050 male factory workers and a nationwide study with 197,825 participants — identified a significant association between faster eating and T2D and insulin resistance. A case-control study involving 234 patients with new onset T2D and 468 controls from Lithuania linked faster eating to a greater than twofold risk for T2D. And a Chinese cross-sectional study of 7972 adults indicated that faster eating significantly increased the risk for metabolic syndrome, elevated blood pressure, and central obesity in adults.

Various hypotheses have been proposed to explain why fast eating may upset metabolic processes, including a delayed sense of fullness contributing to spiking postprandial glucose levels, lack of time for mastication causing higher glucose concentrations, and the triggering of specific cytokines (eg, interleukin-1 beta and interleukin-6) that lead to insulin resistance. It is also possible that the association is the result of people who eat quickly having relatively higher body weights, which translates to a higher risk for T2D.

However, there’s an opportunity in the association of rapid meal consumption with gastrointestinal and metabolic diseases, as people can slow the speed at which they eat so they feel full before they overeat.

A 2019 study in which 21 participants were instructed to eat a 600-kcal meal at a “normal” or “slow” pace (6 minutes or 24 minutes) found that the latter group reported feeling fuller while consuming fewer calories.

This approach may not work for all patients, however. There’s evidence to suggest that tactics to slow down eating may not limit the energy intake of those who are already overweight or obese.

Patients with obesity may physiologically differ in their processing of food, according to Michael Camilleri, MD, consultant in the Division of Gastroenterology and Hepatology at Mayo Clinic in Rochester, Minnesota.

“We have demonstrated that about 20%-25% of people with obesity actually have rapid gastric emptying,” he told this news organization. “As a result, they don’t feel full after they eat a meal and that might impact the total volume of food that they eat before they really feel full.”

The Ideal Time to Eat

It’s not only the speed at which individuals eat that may influence outcomes but when they take their meals. Research indicates that eating earlier in the day to align meals with the body’s circadian rhythms in metabolism offers health benefits.

“The focus would be to eat a meal that syncs during those daytime hours,” Collin Popp, PhD, MS, RD, a research scientist at the NYU Grossman School of Medicine in New York, told this news organization. “I typically suggest patients have their largest meal in the morning, whether that’s a large or medium-sized breakfast, or a big lunch.”

A recent cross-sectional study of 2050 participants found that having the largest meal at lunch protected against obesity (odds ratio [OR], 0.71), whereas having it at dinner increased the risk for obesity (OR, 1.67) and led to higher body mass index.

Consuming the majority of calories in meals earlier in the day may have metabolic health benefits, as well.

A 2015 randomized controlled trial involving 18 adults with obesity and T2D found that eating a high-energy breakfast and a low-energy dinner leads to reduced hyperglycemia throughout the day compared with eating a low-energy breakfast and a high-energy dinner.

Time-restricted eating (TRE), a form of intermittent fasting, also can improve metabolic health depending on the time of day.

A 2023 meta-analysis found that TRE was more effective at reducing fasting glucose levels in participants who were overweight and obese if done earlier rather than later in the day. Similarly, a 2022 study involving 82 healthy patients without diabetes or obesity found that early TRE was more effective than mid-day TRE at improving insulin sensitivity and that it improved fasting glucose and reduced total body mass and adiposity, while mid-day TRE did not.

A study that analyzed the effects of TRE in eight adult men with overweight and prediabetes found “better insulin resistance when the window of food consumption was earlier in the day,» noted endocrinologist Beverly Tchang, MD, an assistant professor of clinical medicine at Weill Cornell Medicine with a focus on obesity medication.

Patients May Benefit From Behavioral Interventions

Patients potentially negatively affected by eating too quickly or at late hours may benefit from adopting behavioral interventions to address these tendencies. To determine if a patient is a candidate for such interventions, Dr. Popp recommends starting with a simple conversation.

“When I first meet patients, I always ask them to describe to me a typical day for how they eat — when they’re eating, what they’re eating, the food quality, who are they with — to see if there’s social aspects to it. Then try and make the recommendations based on that,” said Dr. Popp, whose work focuses on biobehavioral interventions for the treatment and prevention of obesity, T2D, and other cardiometabolic outcomes.

Dr. Tchang said she encourages her patients to be mindful of hunger and fullness cues.

“Eat if you’re hungry; don’t force yourself to eat if you’re not hungry,” she said. “If you’re not sure whether you’re hungry or not, speak to a doctor because this points to an abnormality in your appetite-regulation system, which can be helped with GLP-1 [glucagon-like peptide 1] receptor agonists.”

Adjusting what patients eat can help them improve their meal timing.

“For example, we know that a high-fiber diet or a diet that has a large amount of fat in it tends to empty from the stomach slower,” Dr. Camilleri said. “That might give a sensation of fullness that lasts longer and that might prevent, for instance, the ingestion of the next meal.”

Those trying to eat more slowly are advised to seek out foods that are hard in texture and minimally processed.

A study involving 50 patients with healthy weights found that hard foods are consumed more slowly than soft foods and that energy intake is lowest with hard, minimally processed foods. Combining hard-textured foods with explicit instructions to reduce eating speed has also been shown to be an effective strategy. For those inclined to seek out technology-based solution, evidence suggests that a self-monitoring wearable device can slow the eating rate.

Although the evidence is mounting that the timing and duration of meals have an impact on certain chronic diseases, clinicians should remember that these two factors are far from the most important contributors, Dr. Popp said.

“We also have to consider total caloric intake, food quality, sleep, alcohol use, smoking, and physical activity,” he said. “Meal timing should be considered as under the umbrella of health that is important for a lot of folks.”

A version of this article appeared on Medscape.com.

You are what you eat, as the adage goes. But a growing body of evidence indicates that it’s not just what and how much you eat that influence your health. How fast and when you eat also play a role.

Research now indicates that these two factors may affect the risk for gastrointestinal problems, obesity, and type 2 diabetes (T2D). Because meal timing and speed of consumption are modifiable, they present new opportunities to change patient behavior to help prevent and perhaps address these conditions.

Not So Fast

Most people are well acquainted with the short-term gastrointestinal effects of eating too quickly, which include indigestion, gas, bloating, and nausea. But regularly eating too fast can cause long-term consequences.

Obtaining a sense of fullness is key to staving off overeating and excess caloric intake. However, it takes approximately 20 minutes for the stomach to alert the brain to feelings of fullness. Eat too quickly and the fullness signaling might not set in until you’ve consumed more calories than intended. Research links this habit to excess body weight.

The practice also can lead to gastrointestinal diseases over the long term because overeating causes food to remain in the stomach longer, thus prolonging the time that the gastric mucosa is exposed to gastric acids.

A study of 10,893 adults in Korea reported that those with the fastest eating speed (< 5 min/meal) had a 1.7 times greater likelihood of endoscopic erosive gastritis than those with the slowest times (≥ 15 min/meal). Faster eating also was linked to increased risk for functional dyspepsia in a study involving 89 young-adult female military cadets in Korea with relatively controlled eating patterns.

On the extreme end of the spectrum, researchers who performed an assessment of a competitive speed eater speculated that the observed physiological accommodation required for the role (expanding the stomach to form a large flaccid sac) makes speed eaters vulnerable to morbid obesity, gastroparesis, intractable nausea and vomiting, and the need for gastrectomy.

The risk for metabolic changes and eventual development of T2D also appear to be linked to how quickly food is consumed.

Two clinical studies conducted in Japan — a cohort study of 2050 male factory workers and a nationwide study with 197,825 participants — identified a significant association between faster eating and T2D and insulin resistance. A case-control study involving 234 patients with new onset T2D and 468 controls from Lithuania linked faster eating to a greater than twofold risk for T2D. And a Chinese cross-sectional study of 7972 adults indicated that faster eating significantly increased the risk for metabolic syndrome, elevated blood pressure, and central obesity in adults.

Various hypotheses have been proposed to explain why fast eating may upset metabolic processes, including a delayed sense of fullness contributing to spiking postprandial glucose levels, lack of time for mastication causing higher glucose concentrations, and the triggering of specific cytokines (eg, interleukin-1 beta and interleukin-6) that lead to insulin resistance. It is also possible that the association is the result of people who eat quickly having relatively higher body weights, which translates to a higher risk for T2D.

However, there’s an opportunity in the association of rapid meal consumption with gastrointestinal and metabolic diseases, as people can slow the speed at which they eat so they feel full before they overeat.

A 2019 study in which 21 participants were instructed to eat a 600-kcal meal at a “normal” or “slow” pace (6 minutes or 24 minutes) found that the latter group reported feeling fuller while consuming fewer calories.

This approach may not work for all patients, however. There’s evidence to suggest that tactics to slow down eating may not limit the energy intake of those who are already overweight or obese.

Patients with obesity may physiologically differ in their processing of food, according to Michael Camilleri, MD, consultant in the Division of Gastroenterology and Hepatology at Mayo Clinic in Rochester, Minnesota.

“We have demonstrated that about 20%-25% of people with obesity actually have rapid gastric emptying,” he told this news organization. “As a result, they don’t feel full after they eat a meal and that might impact the total volume of food that they eat before they really feel full.”

The Ideal Time to Eat

It’s not only the speed at which individuals eat that may influence outcomes but when they take their meals. Research indicates that eating earlier in the day to align meals with the body’s circadian rhythms in metabolism offers health benefits.

“The focus would be to eat a meal that syncs during those daytime hours,” Collin Popp, PhD, MS, RD, a research scientist at the NYU Grossman School of Medicine in New York, told this news organization. “I typically suggest patients have their largest meal in the morning, whether that’s a large or medium-sized breakfast, or a big lunch.”

A recent cross-sectional study of 2050 participants found that having the largest meal at lunch protected against obesity (odds ratio [OR], 0.71), whereas having it at dinner increased the risk for obesity (OR, 1.67) and led to higher body mass index.

Consuming the majority of calories in meals earlier in the day may have metabolic health benefits, as well.

A 2015 randomized controlled trial involving 18 adults with obesity and T2D found that eating a high-energy breakfast and a low-energy dinner leads to reduced hyperglycemia throughout the day compared with eating a low-energy breakfast and a high-energy dinner.

Time-restricted eating (TRE), a form of intermittent fasting, also can improve metabolic health depending on the time of day.

A 2023 meta-analysis found that TRE was more effective at reducing fasting glucose levels in participants who were overweight and obese if done earlier rather than later in the day. Similarly, a 2022 study involving 82 healthy patients without diabetes or obesity found that early TRE was more effective than mid-day TRE at improving insulin sensitivity and that it improved fasting glucose and reduced total body mass and adiposity, while mid-day TRE did not.

A study that analyzed the effects of TRE in eight adult men with overweight and prediabetes found “better insulin resistance when the window of food consumption was earlier in the day,» noted endocrinologist Beverly Tchang, MD, an assistant professor of clinical medicine at Weill Cornell Medicine with a focus on obesity medication.

Patients May Benefit From Behavioral Interventions

Patients potentially negatively affected by eating too quickly or at late hours may benefit from adopting behavioral interventions to address these tendencies. To determine if a patient is a candidate for such interventions, Dr. Popp recommends starting with a simple conversation.

“When I first meet patients, I always ask them to describe to me a typical day for how they eat — when they’re eating, what they’re eating, the food quality, who are they with — to see if there’s social aspects to it. Then try and make the recommendations based on that,” said Dr. Popp, whose work focuses on biobehavioral interventions for the treatment and prevention of obesity, T2D, and other cardiometabolic outcomes.

Dr. Tchang said she encourages her patients to be mindful of hunger and fullness cues.

“Eat if you’re hungry; don’t force yourself to eat if you’re not hungry,” she said. “If you’re not sure whether you’re hungry or not, speak to a doctor because this points to an abnormality in your appetite-regulation system, which can be helped with GLP-1 [glucagon-like peptide 1] receptor agonists.”

Adjusting what patients eat can help them improve their meal timing.

“For example, we know that a high-fiber diet or a diet that has a large amount of fat in it tends to empty from the stomach slower,” Dr. Camilleri said. “That might give a sensation of fullness that lasts longer and that might prevent, for instance, the ingestion of the next meal.”

Those trying to eat more slowly are advised to seek out foods that are hard in texture and minimally processed.

A study involving 50 patients with healthy weights found that hard foods are consumed more slowly than soft foods and that energy intake is lowest with hard, minimally processed foods. Combining hard-textured foods with explicit instructions to reduce eating speed has also been shown to be an effective strategy. For those inclined to seek out technology-based solution, evidence suggests that a self-monitoring wearable device can slow the eating rate.

Although the evidence is mounting that the timing and duration of meals have an impact on certain chronic diseases, clinicians should remember that these two factors are far from the most important contributors, Dr. Popp said.

“We also have to consider total caloric intake, food quality, sleep, alcohol use, smoking, and physical activity,” he said. “Meal timing should be considered as under the umbrella of health that is important for a lot of folks.”

A version of this article appeared on Medscape.com.

You are what you eat, as the adage goes. But a growing body of evidence indicates that it’s not just what and how much you eat that influence your health. How fast and when you eat also play a role.

Research now indicates that these two factors may affect the risk for gastrointestinal problems, obesity, and type 2 diabetes (T2D). Because meal timing and speed of consumption are modifiable, they present new opportunities to change patient behavior to help prevent and perhaps address these conditions.

Not So Fast

Most people are well acquainted with the short-term gastrointestinal effects of eating too quickly, which include indigestion, gas, bloating, and nausea. But regularly eating too fast can cause long-term consequences.

Obtaining a sense of fullness is key to staving off overeating and excess caloric intake. However, it takes approximately 20 minutes for the stomach to alert the brain to feelings of fullness. Eat too quickly and the fullness signaling might not set in until you’ve consumed more calories than intended. Research links this habit to excess body weight.

The practice also can lead to gastrointestinal diseases over the long term because overeating causes food to remain in the stomach longer, thus prolonging the time that the gastric mucosa is exposed to gastric acids.

A study of 10,893 adults in Korea reported that those with the fastest eating speed (< 5 min/meal) had a 1.7 times greater likelihood of endoscopic erosive gastritis than those with the slowest times (≥ 15 min/meal). Faster eating also was linked to increased risk for functional dyspepsia in a study involving 89 young-adult female military cadets in Korea with relatively controlled eating patterns.

On the extreme end of the spectrum, researchers who performed an assessment of a competitive speed eater speculated that the observed physiological accommodation required for the role (expanding the stomach to form a large flaccid sac) makes speed eaters vulnerable to morbid obesity, gastroparesis, intractable nausea and vomiting, and the need for gastrectomy.

The risk for metabolic changes and eventual development of T2D also appear to be linked to how quickly food is consumed.

Two clinical studies conducted in Japan — a cohort study of 2050 male factory workers and a nationwide study with 197,825 participants — identified a significant association between faster eating and T2D and insulin resistance. A case-control study involving 234 patients with new onset T2D and 468 controls from Lithuania linked faster eating to a greater than twofold risk for T2D. And a Chinese cross-sectional study of 7972 adults indicated that faster eating significantly increased the risk for metabolic syndrome, elevated blood pressure, and central obesity in adults.

Various hypotheses have been proposed to explain why fast eating may upset metabolic processes, including a delayed sense of fullness contributing to spiking postprandial glucose levels, lack of time for mastication causing higher glucose concentrations, and the triggering of specific cytokines (eg, interleukin-1 beta and interleukin-6) that lead to insulin resistance. It is also possible that the association is the result of people who eat quickly having relatively higher body weights, which translates to a higher risk for T2D.

However, there’s an opportunity in the association of rapid meal consumption with gastrointestinal and metabolic diseases, as people can slow the speed at which they eat so they feel full before they overeat.

A 2019 study in which 21 participants were instructed to eat a 600-kcal meal at a “normal” or “slow” pace (6 minutes or 24 minutes) found that the latter group reported feeling fuller while consuming fewer calories.

This approach may not work for all patients, however. There’s evidence to suggest that tactics to slow down eating may not limit the energy intake of those who are already overweight or obese.

Patients with obesity may physiologically differ in their processing of food, according to Michael Camilleri, MD, consultant in the Division of Gastroenterology and Hepatology at Mayo Clinic in Rochester, Minnesota.

“We have demonstrated that about 20%-25% of people with obesity actually have rapid gastric emptying,” he told this news organization. “As a result, they don’t feel full after they eat a meal and that might impact the total volume of food that they eat before they really feel full.”

The Ideal Time to Eat

It’s not only the speed at which individuals eat that may influence outcomes but when they take their meals. Research indicates that eating earlier in the day to align meals with the body’s circadian rhythms in metabolism offers health benefits.

“The focus would be to eat a meal that syncs during those daytime hours,” Collin Popp, PhD, MS, RD, a research scientist at the NYU Grossman School of Medicine in New York, told this news organization. “I typically suggest patients have their largest meal in the morning, whether that’s a large or medium-sized breakfast, or a big lunch.”

A recent cross-sectional study of 2050 participants found that having the largest meal at lunch protected against obesity (odds ratio [OR], 0.71), whereas having it at dinner increased the risk for obesity (OR, 1.67) and led to higher body mass index.

Consuming the majority of calories in meals earlier in the day may have metabolic health benefits, as well.

A 2015 randomized controlled trial involving 18 adults with obesity and T2D found that eating a high-energy breakfast and a low-energy dinner leads to reduced hyperglycemia throughout the day compared with eating a low-energy breakfast and a high-energy dinner.

Time-restricted eating (TRE), a form of intermittent fasting, also can improve metabolic health depending on the time of day.

A 2023 meta-analysis found that TRE was more effective at reducing fasting glucose levels in participants who were overweight and obese if done earlier rather than later in the day. Similarly, a 2022 study involving 82 healthy patients without diabetes or obesity found that early TRE was more effective than mid-day TRE at improving insulin sensitivity and that it improved fasting glucose and reduced total body mass and adiposity, while mid-day TRE did not.

A study that analyzed the effects of TRE in eight adult men with overweight and prediabetes found “better insulin resistance when the window of food consumption was earlier in the day,» noted endocrinologist Beverly Tchang, MD, an assistant professor of clinical medicine at Weill Cornell Medicine with a focus on obesity medication.

Patients May Benefit From Behavioral Interventions

Patients potentially negatively affected by eating too quickly or at late hours may benefit from adopting behavioral interventions to address these tendencies. To determine if a patient is a candidate for such interventions, Dr. Popp recommends starting with a simple conversation.

“When I first meet patients, I always ask them to describe to me a typical day for how they eat — when they’re eating, what they’re eating, the food quality, who are they with — to see if there’s social aspects to it. Then try and make the recommendations based on that,” said Dr. Popp, whose work focuses on biobehavioral interventions for the treatment and prevention of obesity, T2D, and other cardiometabolic outcomes.

Dr. Tchang said she encourages her patients to be mindful of hunger and fullness cues.

“Eat if you’re hungry; don’t force yourself to eat if you’re not hungry,” she said. “If you’re not sure whether you’re hungry or not, speak to a doctor because this points to an abnormality in your appetite-regulation system, which can be helped with GLP-1 [glucagon-like peptide 1] receptor agonists.”

Adjusting what patients eat can help them improve their meal timing.

“For example, we know that a high-fiber diet or a diet that has a large amount of fat in it tends to empty from the stomach slower,” Dr. Camilleri said. “That might give a sensation of fullness that lasts longer and that might prevent, for instance, the ingestion of the next meal.”

Those trying to eat more slowly are advised to seek out foods that are hard in texture and minimally processed.

A study involving 50 patients with healthy weights found that hard foods are consumed more slowly than soft foods and that energy intake is lowest with hard, minimally processed foods. Combining hard-textured foods with explicit instructions to reduce eating speed has also been shown to be an effective strategy. For those inclined to seek out technology-based solution, evidence suggests that a self-monitoring wearable device can slow the eating rate.

Although the evidence is mounting that the timing and duration of meals have an impact on certain chronic diseases, clinicians should remember that these two factors are far from the most important contributors, Dr. Popp said.

“We also have to consider total caloric intake, food quality, sleep, alcohol use, smoking, and physical activity,” he said. “Meal timing should be considered as under the umbrella of health that is important for a lot of folks.”

A version of this article appeared on Medscape.com.

TOPLINE:

In people with type 2 diabetes (T2D), higher levels of arm and trunk fat are associated with an increased risk for cardiovascular disease (CVD) and mortality, while higher levels of leg fat are associated with a reduced risk for these conditions.

METHODOLOGY:

• People with T2D have a twofold to fourfold higher risk for CVD and mortality, and evidence shows obesity management helps delay complications and premature death, but an elevated body mass index (BMI) may be insufficient to measure obesity.
• In the “obesity paradox,” people with elevated BMI may have a lower CVD risk than people of normal weight.
• Researchers prospectively investigated how regional body fat accumulation was associated with CVD risk in 21,472 people with T2D (mean age, 58.9 years; 60.7% men; BMI about 29-33) from the UK Biobank (2006-2010), followed up for a median of 7.7 years.
• The regional body fat distribution in arms, trunk, and legs was assessed using bioelectrical impedance analysis.
• The primary outcomes were the incidence of CVD, all-cause mortality, and CVD mortality.

TAKEAWAY:

• Participants in the highest quartile of arm fat percentage (multivariate-adjusted hazard ratio [HR], 1.63; 95% CI, 1.29-2.05) and trunk fat percentage (HR, 1.27; 95% CI, 1.06-1.52) were at a higher risk for CVD than those in the lowest quartile.
• However, participants in the highest quartile of leg fat percentage had a lower risk for CVD than those in the lowest quartile (HR, 0.72; 95% CI, 0.58-0.90).
• A nonlinear relationship was observed between higher leg fat percentage and lower CVD risk and between higher trunk fat percentage and higher CVD risk, whereas a linear relationship was noted between higher arm fat percentage and higher CVD risk.
• The patterns of association were similar for both all-cause mortality and CVD mortality. Overall patterns were similar for men and women.

IN PRACTICE:

“Our findings add to the understanding of body fat distribution in patients with T2D, which highlights the importance of considering both the amount and the location of body fat when assessing CVD and mortality risk among patients with T2D,” wrote the authors.

SOURCE:

The study led by Zixin Qiu, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, was published online in The Journal of Clinical Endocrinology & Metabolism.

LIMITATIONS:

As body fat was measured only once at the beginning of the study, its changing association over time could not be assessed. Moreover, the findings were primarily based on predominantly White UK adults, potentially restricting their generalizability to other population groups. Furthermore, diabetes was diagnosed using self-reported medical history, medication, and hemoglobin A1c levels, implying that some cases may have gone undetected at baseline. 

DISCLOSURES:

This study was funded by grants from the National Natural Science Foundation of China, Hubei Province Science Fund for Distinguished Young Scholars, and Fundamental Research Funds for the Central Universities. The authors declared no conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

In people with type 2 diabetes (T2D), higher levels of arm and trunk fat are associated with an increased risk for cardiovascular disease (CVD) and mortality, while higher levels of leg fat are associated with a reduced risk for these conditions.

METHODOLOGY:

• People with T2D have a twofold to fourfold higher risk for CVD and mortality, and evidence shows obesity management helps delay complications and premature death, but an elevated body mass index (BMI) may be insufficient to measure obesity.
• In the “obesity paradox,” people with elevated BMI may have a lower CVD risk than people of normal weight.
• Researchers prospectively investigated how regional body fat accumulation was associated with CVD risk in 21,472 people with T2D (mean age, 58.9 years; 60.7% men; BMI about 29-33) from the UK Biobank (2006-2010), followed up for a median of 7.7 years.
• The regional body fat distribution in arms, trunk, and legs was assessed using bioelectrical impedance analysis.
• The primary outcomes were the incidence of CVD, all-cause mortality, and CVD mortality.

TAKEAWAY:

• Participants in the highest quartile of arm fat percentage (multivariate-adjusted hazard ratio [HR], 1.63; 95% CI, 1.29-2.05) and trunk fat percentage (HR, 1.27; 95% CI, 1.06-1.52) were at a higher risk for CVD than those in the lowest quartile.
• However, participants in the highest quartile of leg fat percentage had a lower risk for CVD than those in the lowest quartile (HR, 0.72; 95% CI, 0.58-0.90).
• A nonlinear relationship was observed between higher leg fat percentage and lower CVD risk and between higher trunk fat percentage and higher CVD risk, whereas a linear relationship was noted between higher arm fat percentage and higher CVD risk.
• The patterns of association were similar for both all-cause mortality and CVD mortality. Overall patterns were similar for men and women.

IN PRACTICE:

“Our findings add to the understanding of body fat distribution in patients with T2D, which highlights the importance of considering both the amount and the location of body fat when assessing CVD and mortality risk among patients with T2D,” wrote the authors.

SOURCE:

The study led by Zixin Qiu, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, was published online in The Journal of Clinical Endocrinology & Metabolism.

LIMITATIONS:

As body fat was measured only once at the beginning of the study, its changing association over time could not be assessed. Moreover, the findings were primarily based on predominantly White UK adults, potentially restricting their generalizability to other population groups. Furthermore, diabetes was diagnosed using self-reported medical history, medication, and hemoglobin A1c levels, implying that some cases may have gone undetected at baseline. 

DISCLOSURES:

This study was funded by grants from the National Natural Science Foundation of China, Hubei Province Science Fund for Distinguished Young Scholars, and Fundamental Research Funds for the Central Universities. The authors declared no conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

In people with type 2 diabetes (T2D), higher levels of arm and trunk fat are associated with an increased risk for cardiovascular disease (CVD) and mortality, while higher levels of leg fat are associated with a reduced risk for these conditions.

METHODOLOGY:

• People with T2D have a twofold to fourfold higher risk for CVD and mortality, and evidence shows obesity management helps delay complications and premature death, but an elevated body mass index (BMI) may be insufficient to measure obesity.
• In the “obesity paradox,” people with elevated BMI may have a lower CVD risk than people of normal weight.
• Researchers prospectively investigated how regional body fat accumulation was associated with CVD risk in 21,472 people with T2D (mean age, 58.9 years; 60.7% men; BMI about 29-33) from the UK Biobank (2006-2010), followed up for a median of 7.7 years.
• The regional body fat distribution in arms, trunk, and legs was assessed using bioelectrical impedance analysis.
• The primary outcomes were the incidence of CVD, all-cause mortality, and CVD mortality.

TAKEAWAY:

• Participants in the highest quartile of arm fat percentage (multivariate-adjusted hazard ratio [HR], 1.63; 95% CI, 1.29-2.05) and trunk fat percentage (HR, 1.27; 95% CI, 1.06-1.52) were at a higher risk for CVD than those in the lowest quartile.
• However, participants in the highest quartile of leg fat percentage had a lower risk for CVD than those in the lowest quartile (HR, 0.72; 95% CI, 0.58-0.90).
• A nonlinear relationship was observed between higher leg fat percentage and lower CVD risk and between higher trunk fat percentage and higher CVD risk, whereas a linear relationship was noted between higher arm fat percentage and higher CVD risk.
• The patterns of association were similar for both all-cause mortality and CVD mortality. Overall patterns were similar for men and women.

IN PRACTICE:

“Our findings add to the understanding of body fat distribution in patients with T2D, which highlights the importance of considering both the amount and the location of body fat when assessing CVD and mortality risk among patients with T2D,” wrote the authors.

SOURCE:

The study led by Zixin Qiu, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, was published online in The Journal of Clinical Endocrinology & Metabolism.

LIMITATIONS:

As body fat was measured only once at the beginning of the study, its changing association over time could not be assessed. Moreover, the findings were primarily based on predominantly White UK adults, potentially restricting their generalizability to other population groups. Furthermore, diabetes was diagnosed using self-reported medical history, medication, and hemoglobin A1c levels, implying that some cases may have gone undetected at baseline. 

DISCLOSURES:

This study was funded by grants from the National Natural Science Foundation of China, Hubei Province Science Fund for Distinguished Young Scholars, and Fundamental Research Funds for the Central Universities. The authors declared no conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

Higher consumption of ultraprocessed food (UPF) is associated with an increased risk of developing irritable bowel syndrome (IBS), with a significant dose-response relationship.

METHODOLOGY:

• The simultaneous rise in UPF consumption and IBS in recent years is concerning, but there is a lack of epidemiologic evidence regarding the link between UPF consumption and the risk of developing IBS.
• This study included 178,711 participants without IBS, inflammatory bowel disease, celiac disease, or cancer (mean age, 55.8 years; 53.1% women) from the UK Biobank who had completed a 24-hour diet recall questionnaire over five cycles.
• The researchers used the NOVA system to categorize food into four groups, ranging from unprocessed or minimally processed food to UPF. They calculated consumption of food in each group on the basis of portion sizes and UPF consumption as a percentage of total diet intake (as grams per day) using data from participants who completed at least two dietary cycles.
• The primary outcome was incident IBS.

TAKEAWAY:

• Over a median of 11.3 years of follow-up, 2690 incident IBS cases were reported.
• The mean UPF consumption was 21% of the total diet.
• For every 10% increase in UPF consumption, the risk for IBS also increased by 8%.
• The individuals in the highest quartile of UPF consumption had about a 20% higher risk for IBS than those in the lowest quartile.

IN PRACTICE:

“Our findings suggest that avoiding or lowering UPF consumption could be considered as a potential strategy to help reduce the increasing burden of IBS,” the authors wrote.

SOURCE:

The study, led by Shanshan Wu, PhD, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Disease, Beijing, China, was published online in Clinical Gastroenterology and Hepatology.

LIMITATIONS:

Questionnaire-based data could introduce misclassification and recall bias. Lifestyle factors (eg, smoking) or nutritional factors (eg, total intake of protein, fat, and carbohydrates) that may confound the association were not considered. The observational study design has inherent bias.

DISCLOSURES:

This study was supported by grants from the Beijing Nova Program, National Key Research and Development Program of China, and Beijing Science and Technology Project. The authors declared no conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

Higher consumption of ultraprocessed food (UPF) is associated with an increased risk of developing irritable bowel syndrome (IBS), with a significant dose-response relationship.

METHODOLOGY:

• The simultaneous rise in UPF consumption and IBS in recent years is concerning, but there is a lack of epidemiologic evidence regarding the link between UPF consumption and the risk of developing IBS.
• This study included 178,711 participants without IBS, inflammatory bowel disease, celiac disease, or cancer (mean age, 55.8 years; 53.1% women) from the UK Biobank who had completed a 24-hour diet recall questionnaire over five cycles.
• The researchers used the NOVA system to categorize food into four groups, ranging from unprocessed or minimally processed food to UPF. They calculated consumption of food in each group on the basis of portion sizes and UPF consumption as a percentage of total diet intake (as grams per day) using data from participants who completed at least two dietary cycles.
• The primary outcome was incident IBS.

TAKEAWAY:

• Over a median of 11.3 years of follow-up, 2690 incident IBS cases were reported.
• The mean UPF consumption was 21% of the total diet.
• For every 10% increase in UPF consumption, the risk for IBS also increased by 8%.
• The individuals in the highest quartile of UPF consumption had about a 20% higher risk for IBS than those in the lowest quartile.

IN PRACTICE:

“Our findings suggest that avoiding or lowering UPF consumption could be considered as a potential strategy to help reduce the increasing burden of IBS,” the authors wrote.

SOURCE:

The study, led by Shanshan Wu, PhD, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Disease, Beijing, China, was published online in Clinical Gastroenterology and Hepatology.

LIMITATIONS:

Questionnaire-based data could introduce misclassification and recall bias. Lifestyle factors (eg, smoking) or nutritional factors (eg, total intake of protein, fat, and carbohydrates) that may confound the association were not considered. The observational study design has inherent bias.

DISCLOSURES:

This study was supported by grants from the Beijing Nova Program, National Key Research and Development Program of China, and Beijing Science and Technology Project. The authors declared no conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

Higher consumption of ultraprocessed food (UPF) is associated with an increased risk of developing irritable bowel syndrome (IBS), with a significant dose-response relationship.

METHODOLOGY:

• The simultaneous rise in UPF consumption and IBS in recent years is concerning, but there is a lack of epidemiologic evidence regarding the link between UPF consumption and the risk of developing IBS.
• This study included 178,711 participants without IBS, inflammatory bowel disease, celiac disease, or cancer (mean age, 55.8 years; 53.1% women) from the UK Biobank who had completed a 24-hour diet recall questionnaire over five cycles.
• The researchers used the NOVA system to categorize food into four groups, ranging from unprocessed or minimally processed food to UPF. They calculated consumption of food in each group on the basis of portion sizes and UPF consumption as a percentage of total diet intake (as grams per day) using data from participants who completed at least two dietary cycles.
• The primary outcome was incident IBS.

TAKEAWAY:

• Over a median of 11.3 years of follow-up, 2690 incident IBS cases were reported.
• The mean UPF consumption was 21% of the total diet.
• For every 10% increase in UPF consumption, the risk for IBS also increased by 8%.
• The individuals in the highest quartile of UPF consumption had about a 20% higher risk for IBS than those in the lowest quartile.

IN PRACTICE:

“Our findings suggest that avoiding or lowering UPF consumption could be considered as a potential strategy to help reduce the increasing burden of IBS,” the authors wrote.

SOURCE:

The study, led by Shanshan Wu, PhD, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Disease, Beijing, China, was published online in Clinical Gastroenterology and Hepatology.

LIMITATIONS:

Questionnaire-based data could introduce misclassification and recall bias. Lifestyle factors (eg, smoking) or nutritional factors (eg, total intake of protein, fat, and carbohydrates) that may confound the association were not considered. The observational study design has inherent bias.

DISCLOSURES:

This study was supported by grants from the Beijing Nova Program, National Key Research and Development Program of China, and Beijing Science and Technology Project. The authors declared no conflicts of interest.

A version of this article appeared on Medscape.com.

Gut bacteria predictive of body mass index (BMI), waist circumference, and fat mass are different in men and women, and therefore, interventions to prevent obesity may need to be different, as well, new research suggested.

Metagenomic analyses of fecal samples and metabolomic analyses of serum samples from 361 volunteers in Spain showed that an imbalance in specific bacterial strains likely play an important role in the onset and development of obesity, and that there are “considerable differences” between the sexes, said lead study author Paula Aranaz, MD, Centre for Nutrition Research, at the University of Navarra, Pamplona, Spain.

“We are still far from knowing the magnitude of the effect that the microbiota [bacteria, viruses, fungi, and protozoa] has on our metabolic health and, therefore, on the greater or lesser risk of suffering from obesity,” Dr. Aranaz told this news organization.

“However,” she said, “what does seem clear is that the microorganisms of our intestine perform a crucial role in the way we metabolize nutrients and, therefore, influence the compounds and molecules that circulate through our body, affecting different organs and tissues, and our general metabolic health.”

The study will be presented at the European Congress on Obesity (ECO) 2024, to be held in Venice, Italy, from May 12 to 15. The abstract is now available online.

Variation in Bacteria Species, Abundance

The researchers examined the fecal metabolome of 361 adult volunteers (median age, 44; 70%, women) from the Spanish Obekit randomized trial, which investigated the relationship between genetic variants and how participants responded to a low-calorie diet.

A total of 65 participants were normal weight, 110 with overweight, and 186 with obesity. They were matched for sex and age and classified according to an obesity (OB) index as LOW or HIGH.

LOW included those with a BMI ≤ 30 kg/m², fat mass percentage ≤ 25% (women) or ≤ 32% (men), and waist circumference ≤ 88 cm (women) or ≤ 102 cm (men). HIGH included those with a BMI > 30 kg/m², fat mass > 25% (women) or > 32% (men), and waist circumference > 88 cm (women) or > 102 cm (men).

Genetic profiling to identify the different types, composition, diversity, and relative abundance of bacteria in the stool samples showed that those with a HIGH OB index had significantly lower levels of Christensenella minuta, a bacterium linked to leanness and health.

In men, a greater abundance of Parabacteroides helcogenes and Campylobacter canadensis species was associated with higher BMI, fat mass, and waist circumference.

By contrast, in women, a greater abundance of Prevotella micans, P brevis, and P sacharolitica was predictive of higher BMI, fat mass, and waist circumference.

Untargeted metabolomic analyses revealed variation in the abundance of certain metabolites in participants with a HIGH OB index — notably, higher levels of phospholipids (implicated in the development of metabolic disease and modulators of insulin sensitivity) and sphingolipids, which play a role in the development of diabetes and the emergence of vascular complications.

“We can reduce the risk of metabolic diseases by modulating the gut microbiome through nutritional and lifestyle factors, including dietary patterns, foods, exercise, probiotics, and postbiotics,” Dr. Aranaz said. Which modifications can and should be made “depend on many factors, including the host genetics, endocrine system, sex, and age.”

The researchers currently are working to try to relate the identified metabolites to the bacterial species that could be producing them and to characterize the biological effect that these species and their metabolites exert on the organism, Dr. Aranaz added.

Ultimately, she said, “we would like to [design] a microbiota/metabolomic test that can be used in clinical practice to identify human enterotypes and to personalize the dietary strategies to minimize the health risks related to gut dysbiosis.”

No funding was reported. Dr. Aranaz declared no conflicts of interest.

A version of this article appeared on Medscape.com .

Gut bacteria predictive of body mass index (BMI), waist circumference, and fat mass are different in men and women, and therefore, interventions to prevent obesity may need to be different, as well, new research suggested.

Metagenomic analyses of fecal samples and metabolomic analyses of serum samples from 361 volunteers in Spain showed that an imbalance in specific bacterial strains likely play an important role in the onset and development of obesity, and that there are “considerable differences” between the sexes, said lead study author Paula Aranaz, MD, Centre for Nutrition Research, at the University of Navarra, Pamplona, Spain.

“We are still far from knowing the magnitude of the effect that the microbiota [bacteria, viruses, fungi, and protozoa] has on our metabolic health and, therefore, on the greater or lesser risk of suffering from obesity,” Dr. Aranaz told this news organization.

“However,” she said, “what does seem clear is that the microorganisms of our intestine perform a crucial role in the way we metabolize nutrients and, therefore, influence the compounds and molecules that circulate through our body, affecting different organs and tissues, and our general metabolic health.”

The study will be presented at the European Congress on Obesity (ECO) 2024, to be held in Venice, Italy, from May 12 to 15. The abstract is now available online.

Variation in Bacteria Species, Abundance

The researchers examined the fecal metabolome of 361 adult volunteers (median age, 44; 70%, women) from the Spanish Obekit randomized trial, which investigated the relationship between genetic variants and how participants responded to a low-calorie diet.

A total of 65 participants were normal weight, 110 with overweight, and 186 with obesity. They were matched for sex and age and classified according to an obesity (OB) index as LOW or HIGH.

LOW included those with a BMI ≤ 30 kg/m², fat mass percentage ≤ 25% (women) or ≤ 32% (men), and waist circumference ≤ 88 cm (women) or ≤ 102 cm (men). HIGH included those with a BMI > 30 kg/m², fat mass > 25% (women) or > 32% (men), and waist circumference > 88 cm (women) or > 102 cm (men).

Genetic profiling to identify the different types, composition, diversity, and relative abundance of bacteria in the stool samples showed that those with a HIGH OB index had significantly lower levels of Christensenella minuta, a bacterium linked to leanness and health.

In men, a greater abundance of Parabacteroides helcogenes and Campylobacter canadensis species was associated with higher BMI, fat mass, and waist circumference.

By contrast, in women, a greater abundance of Prevotella micans, P brevis, and P sacharolitica was predictive of higher BMI, fat mass, and waist circumference.

Untargeted metabolomic analyses revealed variation in the abundance of certain metabolites in participants with a HIGH OB index — notably, higher levels of phospholipids (implicated in the development of metabolic disease and modulators of insulin sensitivity) and sphingolipids, which play a role in the development of diabetes and the emergence of vascular complications.

“We can reduce the risk of metabolic diseases by modulating the gut microbiome through nutritional and lifestyle factors, including dietary patterns, foods, exercise, probiotics, and postbiotics,” Dr. Aranaz said. Which modifications can and should be made “depend on many factors, including the host genetics, endocrine system, sex, and age.”

The researchers currently are working to try to relate the identified metabolites to the bacterial species that could be producing them and to characterize the biological effect that these species and their metabolites exert on the organism, Dr. Aranaz added.

Ultimately, she said, “we would like to [design] a microbiota/metabolomic test that can be used in clinical practice to identify human enterotypes and to personalize the dietary strategies to minimize the health risks related to gut dysbiosis.”

No funding was reported. Dr. Aranaz declared no conflicts of interest.

A version of this article appeared on Medscape.com .

Gut bacteria predictive of body mass index (BMI), waist circumference, and fat mass are different in men and women, and therefore, interventions to prevent obesity may need to be different, as well, new research suggested.

Metagenomic analyses of fecal samples and metabolomic analyses of serum samples from 361 volunteers in Spain showed that an imbalance in specific bacterial strains likely play an important role in the onset and development of obesity, and that there are “considerable differences” between the sexes, said lead study author Paula Aranaz, MD, Centre for Nutrition Research, at the University of Navarra, Pamplona, Spain.

“We are still far from knowing the magnitude of the effect that the microbiota [bacteria, viruses, fungi, and protozoa] has on our metabolic health and, therefore, on the greater or lesser risk of suffering from obesity,” Dr. Aranaz told this news organization.

“However,” she said, “what does seem clear is that the microorganisms of our intestine perform a crucial role in the way we metabolize nutrients and, therefore, influence the compounds and molecules that circulate through our body, affecting different organs and tissues, and our general metabolic health.”

The study will be presented at the European Congress on Obesity (ECO) 2024, to be held in Venice, Italy, from May 12 to 15. The abstract is now available online.

Variation in Bacteria Species, Abundance

The researchers examined the fecal metabolome of 361 adult volunteers (median age, 44; 70%, women) from the Spanish Obekit randomized trial, which investigated the relationship between genetic variants and how participants responded to a low-calorie diet.

A total of 65 participants were normal weight, 110 with overweight, and 186 with obesity. They were matched for sex and age and classified according to an obesity (OB) index as LOW or HIGH.

LOW included those with a BMI ≤ 30 kg/m², fat mass percentage ≤ 25% (women) or ≤ 32% (men), and waist circumference ≤ 88 cm (women) or ≤ 102 cm (men). HIGH included those with a BMI > 30 kg/m², fat mass > 25% (women) or > 32% (men), and waist circumference > 88 cm (women) or > 102 cm (men).

Genetic profiling to identify the different types, composition, diversity, and relative abundance of bacteria in the stool samples showed that those with a HIGH OB index had significantly lower levels of Christensenella minuta, a bacterium linked to leanness and health.

In men, a greater abundance of Parabacteroides helcogenes and Campylobacter canadensis species was associated with higher BMI, fat mass, and waist circumference.

By contrast, in women, a greater abundance of Prevotella micans, P brevis, and P sacharolitica was predictive of higher BMI, fat mass, and waist circumference.

Untargeted metabolomic analyses revealed variation in the abundance of certain metabolites in participants with a HIGH OB index — notably, higher levels of phospholipids (implicated in the development of metabolic disease and modulators of insulin sensitivity) and sphingolipids, which play a role in the development of diabetes and the emergence of vascular complications.

“We can reduce the risk of metabolic diseases by modulating the gut microbiome through nutritional and lifestyle factors, including dietary patterns, foods, exercise, probiotics, and postbiotics,” Dr. Aranaz said. Which modifications can and should be made “depend on many factors, including the host genetics, endocrine system, sex, and age.”

The researchers currently are working to try to relate the identified metabolites to the bacterial species that could be producing them and to characterize the biological effect that these species and their metabolites exert on the organism, Dr. Aranaz added.

Ultimately, she said, “we would like to [design] a microbiota/metabolomic test that can be used in clinical practice to identify human enterotypes and to personalize the dietary strategies to minimize the health risks related to gut dysbiosis.”

No funding was reported. Dr. Aranaz declared no conflicts of interest.

A version of this article appeared on Medscape.com .

TOPLINE:

Adults with excess weight or obesity tend to experience higher levels of pain intensity than those with a normal weight, highlighting the importance of addressing obesity as part of pain management strategies.

METHODOLOGY:

• Obesity may cause pathophysiological changes, such as increased load on joints and systemic inflammation, potentially affecting the sensation of pain. Recent studies suggest that obesity may change pain perception and worsen existing painful conditions.
• To examine the association between overweight or obesity and self-perceived pain intensities, researchers conducted a meta-analysis of 22 studies that included 31,210 adults older than 18 years and from diverse international cohorts.
• The participants were categorized by body mass index (BMI) as being normal weight (18.5-24.9), overweight (25.0-29.9), and obese (≥ 30). A BMI ≥ 25 was considered excess weight.
• Pain intensity was assessed by self-report using the Visual Analog Scale, Numerical Rating Scale, and Numerical Pain Rating Scale, with the lowest value indicating “no pain” and the highest value representing “pain as bad as it could be.”
• Researchers compared pain intensity between these patient BMI groups: Normal weight vs overweight plus obesity, normal weight vs overweight, normal weight vs obesity, and overweight vs obesity.

TAKEAWAY:

• Compared with people with normal weight, people with excess weight (overweight or obesity; standardized mean difference [SMD], −0.15; P = .0052) or with obesity (SMD, −0.22; P = .0008) reported higher pain intensities, with a small effect size.
• The comparison of self-report pain in people who had normal weight and overweight did not show any statistically significant difference.

IN PRACTICE:

“These findings encourage the treatment of obesity and the control of body mass index (weight loss) as key complementary interventions for pain management,” wrote the authors.

SOURCE:

This study was led by Miguel M. Garcia, Department of Basic Health Sciences, Universidad Rey Juan Carlos, Unidad Asociada de I+D+i al Instituto de Química Médica CSIC-URJC, Alcorcón, Spain. It was published online in Frontiers in Endocrinology.

LIMITATIONS:

The analysis did not include individuals who were underweight, potentially overlooking the associations between physical pain and malnutrition. BMI may misclassify individuals with high muscularity, as it doesn’t accurately reflect adiposity and cannot distinguish between two people with similar BMIs and different body compositions. Furthermore, the study did not consider gender-based differences while evaluating pain outcomes.

DISCLOSURES:

The study received no specific funding from any funding agency in the public, commercial, or not-for-profit sectors. The authors declared no conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

Adults with excess weight or obesity tend to experience higher levels of pain intensity than those with a normal weight, highlighting the importance of addressing obesity as part of pain management strategies.

METHODOLOGY:

• Obesity may cause pathophysiological changes, such as increased load on joints and systemic inflammation, potentially affecting the sensation of pain. Recent studies suggest that obesity may change pain perception and worsen existing painful conditions.
• To examine the association between overweight or obesity and self-perceived pain intensities, researchers conducted a meta-analysis of 22 studies that included 31,210 adults older than 18 years and from diverse international cohorts.
• The participants were categorized by body mass index (BMI) as being normal weight (18.5-24.9), overweight (25.0-29.9), and obese (≥ 30). A BMI ≥ 25 was considered excess weight.
• Pain intensity was assessed by self-report using the Visual Analog Scale, Numerical Rating Scale, and Numerical Pain Rating Scale, with the lowest value indicating “no pain” and the highest value representing “pain as bad as it could be.”
• Researchers compared pain intensity between these patient BMI groups: Normal weight vs overweight plus obesity, normal weight vs overweight, normal weight vs obesity, and overweight vs obesity.

TAKEAWAY:

• Compared with people with normal weight, people with excess weight (overweight or obesity; standardized mean difference [SMD], −0.15; P = .0052) or with obesity (SMD, −0.22; P = .0008) reported higher pain intensities, with a small effect size.
• The comparison of self-report pain in people who had normal weight and overweight did not show any statistically significant difference.

IN PRACTICE:

“These findings encourage the treatment of obesity and the control of body mass index (weight loss) as key complementary interventions for pain management,” wrote the authors.

SOURCE:

This study was led by Miguel M. Garcia, Department of Basic Health Sciences, Universidad Rey Juan Carlos, Unidad Asociada de I+D+i al Instituto de Química Médica CSIC-URJC, Alcorcón, Spain. It was published online in Frontiers in Endocrinology.

LIMITATIONS:

The analysis did not include individuals who were underweight, potentially overlooking the associations between physical pain and malnutrition. BMI may misclassify individuals with high muscularity, as it doesn’t accurately reflect adiposity and cannot distinguish between two people with similar BMIs and different body compositions. Furthermore, the study did not consider gender-based differences while evaluating pain outcomes.

DISCLOSURES:

The study received no specific funding from any funding agency in the public, commercial, or not-for-profit sectors. The authors declared no conflicts of interest.

A version of this article appeared on Medscape.com.

TOPLINE:

Adults with excess weight or obesity tend to experience higher levels of pain intensity than those with a normal weight, highlighting the importance of addressing obesity as part of pain management strategies.

METHODOLOGY:

• Obesity may cause pathophysiological changes, such as increased load on joints and systemic inflammation, potentially affecting the sensation of pain. Recent studies suggest that obesity may change pain perception and worsen existing painful conditions.
• To examine the association between overweight or obesity and self-perceived pain intensities, researchers conducted a meta-analysis of 22 studies that included 31,210 adults older than 18 years and from diverse international cohorts.
• The participants were categorized by body mass index (BMI) as being normal weight (18.5-24.9), overweight (25.0-29.9), and obese (≥ 30). A BMI ≥ 25 was considered excess weight.
• Pain intensity was assessed by self-report using the Visual Analog Scale, Numerical Rating Scale, and Numerical Pain Rating Scale, with the lowest value indicating “no pain” and the highest value representing “pain as bad as it could be.”
• Researchers compared pain intensity between these patient BMI groups: Normal weight vs overweight plus obesity, normal weight vs overweight, normal weight vs obesity, and overweight vs obesity.

TAKEAWAY:

• Compared with people with normal weight, people with excess weight (overweight or obesity; standardized mean difference [SMD], −0.15; P = .0052) or with obesity (SMD, −0.22; P = .0008) reported higher pain intensities, with a small effect size.
• The comparison of self-report pain in people who had normal weight and overweight did not show any statistically significant difference.

IN PRACTICE:

“These findings encourage the treatment of obesity and the control of body mass index (weight loss) as key complementary interventions for pain management,” wrote the authors.

SOURCE:

This study was led by Miguel M. Garcia, Department of Basic Health Sciences, Universidad Rey Juan Carlos, Unidad Asociada de I+D+i al Instituto de Química Médica CSIC-URJC, Alcorcón, Spain. It was published online in Frontiers in Endocrinology.

LIMITATIONS:

The analysis did not include individuals who were underweight, potentially overlooking the associations between physical pain and malnutrition. BMI may misclassify individuals with high muscularity, as it doesn’t accurately reflect adiposity and cannot distinguish between two people with similar BMIs and different body compositions. Furthermore, the study did not consider gender-based differences while evaluating pain outcomes.

DISCLOSURES:

The study received no specific funding from any funding agency in the public, commercial, or not-for-profit sectors. The authors declared no conflicts of interest.

A version of this article appeared on Medscape.com.

As seen in red on the radiogram, the patient's heart is grossly enlarged, indicating cardiomegaly. Cardiomegaly often is first diagnosed on chest imaging, with diagnosis based on a cardiothoracic ratio of < 0.5. It is not a disease but rather a manifestation of an underlying cause. Patients may have few or no cardiomegaly-related symptoms or have symptoms typical of cardiac dysfunction, like this patient's dyspnea and edema. Conditions that impair normal circulation and that are associated with cardiomegaly development include hypertension, obesity, heart valve disorders, thyroid dysfunction, and anemia. In this patient, cardiomegaly probably has been triggered by uncontrolled hypertension and ongoing obesity. This patient's bloodwork also indicates prediabetes and incipient type 2 diabetes (T2D) (the diagnostic criteria for which are A1c ≥ 6.5% and fasting plasma glucose ≥ 126 mg/dL).

As many as 42% of adults in the United States meet criteria for obesity and are at risk for obesity-related conditions, including cardiomegaly. Guidelines for management of patients with obesity have been published by The Obesity Society and the American Association of Clinical Endocrinologists, and management of obesity is a necessary part of comprehensive care of patients with T2D  as well. For most patients, a BMI ≥ 30 diagnoses obesity; this patient has class 1 obesity, based on a BMI of 30 to 34.9. The patient also has complications of obesity, including stage 2 hypertension and prediabetes. As such, lifestyle management plus medical therapy is the recommended approach to weight loss, with a goal of losing 5% to 10% or more of baseline body weight.

The Obesity Society states that all patients with obesity should be offered effective, evidence-based interventions. Medical management of obesity includes use of pharmacologic interventions with proven benefit in weight loss, such as glucagon-like peptide-1 receptor agonists (GLP-1 RAs; eg, semaglutide) or dual gastric inhibitory polypeptide (GIP)/GLP-1 RAs (eg, tirzepatide). Semaglutide and tirzepatide are likely to have cardiovascular benefits for patients with obesity as well. Other medications approved for management of obesity include liraglutide, orlistat, phentermine HCl (with or without topiramate), and naltrexone plus bupropion. The American Diabetes Association (ADA) recommendations for management of obesity in patients with T2D give preference to semaglutide 2.4 mg/wk and tirzepatide at weekly doses of 5, 10, or 15 mg, depending on patient factors. 

As important for this patient is to get control of hypertension. Studies have shown that lowering blood pressure improves left ventricular hypertrophy, a common source of cardiomegaly. Hypertension guidelines from the American College of Cardiology/American Heart Association recommend a blood pressure goal < 130/80 mm Hg for most adults, which is consistent with the current recommendation from the ADA. Management of hypertension should first incorporate a low-sodium, healthy diet (such as the Dietary Approaches to Stop Hypertension [DASH] diet), physical activity, and weight loss; however, many patients (especially with stage 2 hypertension) require pharmacologic therapy as well. Single-pill combination therapies of drugs from different classes (eg, angiotensin-converting enzyme inhibitor plus calcium channel blocker) are preferred for patients with stage 2 hypertension to improve efficacy and enhance adherence.

Romesh K. Khardori, MD, PhD, Professor, Department of Internal Medicine, Division of Diabetes, Endocrine, and Metabolic Disorders, Eastern Virginia Medical School; EVMS Medical Group, Norfolk, Virginia.

Romesh K. Khardori, MD, PhD, has disclosed no relevant financial relationships.

Image Quizzes are fictional or fictionalized clinical scenarios intended to provide evidence-based educational takeaways.

As seen in red on the radiogram, the patient's heart is grossly enlarged, indicating cardiomegaly. Cardiomegaly often is first diagnosed on chest imaging, with diagnosis based on a cardiothoracic ratio of < 0.5. It is not a disease but rather a manifestation of an underlying cause. Patients may have few or no cardiomegaly-related symptoms or have symptoms typical of cardiac dysfunction, like this patient's dyspnea and edema. Conditions that impair normal circulation and that are associated with cardiomegaly development include hypertension, obesity, heart valve disorders, thyroid dysfunction, and anemia. In this patient, cardiomegaly probably has been triggered by uncontrolled hypertension and ongoing obesity. This patient's bloodwork also indicates prediabetes and incipient type 2 diabetes (T2D) (the diagnostic criteria for which are A1c ≥ 6.5% and fasting plasma glucose ≥ 126 mg/dL).

As many as 42% of adults in the United States meet criteria for obesity and are at risk for obesity-related conditions, including cardiomegaly. Guidelines for management of patients with obesity have been published by The Obesity Society and the American Association of Clinical Endocrinologists, and management of obesity is a necessary part of comprehensive care of patients with T2D  as well. For most patients, a BMI ≥ 30 diagnoses obesity; this patient has class 1 obesity, based on a BMI of 30 to 34.9. The patient also has complications of obesity, including stage 2 hypertension and prediabetes. As such, lifestyle management plus medical therapy is the recommended approach to weight loss, with a goal of losing 5% to 10% or more of baseline body weight.

The Obesity Society states that all patients with obesity should be offered effective, evidence-based interventions. Medical management of obesity includes use of pharmacologic interventions with proven benefit in weight loss, such as glucagon-like peptide-1 receptor agonists (GLP-1 RAs; eg, semaglutide) or dual gastric inhibitory polypeptide (GIP)/GLP-1 RAs (eg, tirzepatide). Semaglutide and tirzepatide are likely to have cardiovascular benefits for patients with obesity as well. Other medications approved for management of obesity include liraglutide, orlistat, phentermine HCl (with or without topiramate), and naltrexone plus bupropion. The American Diabetes Association (ADA) recommendations for management of obesity in patients with T2D give preference to semaglutide 2.4 mg/wk and tirzepatide at weekly doses of 5, 10, or 15 mg, depending on patient factors. 

As important for this patient is to get control of hypertension. Studies have shown that lowering blood pressure improves left ventricular hypertrophy, a common source of cardiomegaly. Hypertension guidelines from the American College of Cardiology/American Heart Association recommend a blood pressure goal < 130/80 mm Hg for most adults, which is consistent with the current recommendation from the ADA. Management of hypertension should first incorporate a low-sodium, healthy diet (such as the Dietary Approaches to Stop Hypertension [DASH] diet), physical activity, and weight loss; however, many patients (especially with stage 2 hypertension) require pharmacologic therapy as well. Single-pill combination therapies of drugs from different classes (eg, angiotensin-converting enzyme inhibitor plus calcium channel blocker) are preferred for patients with stage 2 hypertension to improve efficacy and enhance adherence.

Romesh K. Khardori, MD, PhD, Professor, Department of Internal Medicine, Division of Diabetes, Endocrine, and Metabolic Disorders, Eastern Virginia Medical School; EVMS Medical Group, Norfolk, Virginia.

Romesh K. Khardori, MD, PhD, has disclosed no relevant financial relationships.

Image Quizzes are fictional or fictionalized clinical scenarios intended to provide evidence-based educational takeaways.

As seen in red on the radiogram, the patient's heart is grossly enlarged, indicating cardiomegaly. Cardiomegaly often is first diagnosed on chest imaging, with diagnosis based on a cardiothoracic ratio of < 0.5. It is not a disease but rather a manifestation of an underlying cause. Patients may have few or no cardiomegaly-related symptoms or have symptoms typical of cardiac dysfunction, like this patient's dyspnea and edema. Conditions that impair normal circulation and that are associated with cardiomegaly development include hypertension, obesity, heart valve disorders, thyroid dysfunction, and anemia. In this patient, cardiomegaly probably has been triggered by uncontrolled hypertension and ongoing obesity. This patient's bloodwork also indicates prediabetes and incipient type 2 diabetes (T2D) (the diagnostic criteria for which are A1c ≥ 6.5% and fasting plasma glucose ≥ 126 mg/dL).

As many as 42% of adults in the United States meet criteria for obesity and are at risk for obesity-related conditions, including cardiomegaly. Guidelines for management of patients with obesity have been published by The Obesity Society and the American Association of Clinical Endocrinologists, and management of obesity is a necessary part of comprehensive care of patients with T2D  as well. For most patients, a BMI ≥ 30 diagnoses obesity; this patient has class 1 obesity, based on a BMI of 30 to 34.9. The patient also has complications of obesity, including stage 2 hypertension and prediabetes. As such, lifestyle management plus medical therapy is the recommended approach to weight loss, with a goal of losing 5% to 10% or more of baseline body weight.

The Obesity Society states that all patients with obesity should be offered effective, evidence-based interventions. Medical management of obesity includes use of pharmacologic interventions with proven benefit in weight loss, such as glucagon-like peptide-1 receptor agonists (GLP-1 RAs; eg, semaglutide) or dual gastric inhibitory polypeptide (GIP)/GLP-1 RAs (eg, tirzepatide). Semaglutide and tirzepatide are likely to have cardiovascular benefits for patients with obesity as well. Other medications approved for management of obesity include liraglutide, orlistat, phentermine HCl (with or without topiramate), and naltrexone plus bupropion. The American Diabetes Association (ADA) recommendations for management of obesity in patients with T2D give preference to semaglutide 2.4 mg/wk and tirzepatide at weekly doses of 5, 10, or 15 mg, depending on patient factors. 

As important for this patient is to get control of hypertension. Studies have shown that lowering blood pressure improves left ventricular hypertrophy, a common source of cardiomegaly. Hypertension guidelines from the American College of Cardiology/American Heart Association recommend a blood pressure goal < 130/80 mm Hg for most adults, which is consistent with the current recommendation from the ADA. Management of hypertension should first incorporate a low-sodium, healthy diet (such as the Dietary Approaches to Stop Hypertension [DASH] diet), physical activity, and weight loss; however, many patients (especially with stage 2 hypertension) require pharmacologic therapy as well. Single-pill combination therapies of drugs from different classes (eg, angiotensin-converting enzyme inhibitor plus calcium channel blocker) are preferred for patients with stage 2 hypertension to improve efficacy and enhance adherence.

Romesh K. Khardori, MD, PhD, Professor, Department of Internal Medicine, Division of Diabetes, Endocrine, and Metabolic Disorders, Eastern Virginia Medical School; EVMS Medical Group, Norfolk, Virginia.

Romesh K. Khardori, MD, PhD, has disclosed no relevant financial relationships.

Image Quizzes are fictional or fictionalized clinical scenarios intended to provide evidence-based educational takeaways.

Among adults with type 2 diabetes (T2D) older than 65 years, a body mass index (BMI) in the moderate overweight category (26-28) appears to offer better protection from cardiovascular death than does a BMI in the “normal” range, new data suggested.

On the other hand, the study findings also suggest that the “normal” range of 23-25 is optimal for middle-aged adults with T2D.

The findings reflect a previously demonstrated phenomenon called the “obesity paradox,” in which older people with overweight may have better outcomes than leaner people due to factors such as bone loss, frailty, and nutritional deficits, study lead author Shaoyong Xu, of Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, China, told this news organization.

“In this era of population growth and aging, the question arises as to whether obesity or overweight can be beneficial in improving survival rates for older individuals with diabetes. This topic holds significant relevance due to the potential implications it has on weight management strategies for older adults. If overweight does not pose an increased risk of cardiovascular mortality, it may suggest that older individuals are not necessarily required to strive for weight loss to achieve so-called normal values.”

Moreover, Dr. Xu added, “inappropriate weight loss and being underweight could potentially elevate the risk of cardiovascular events, myocardial infarction, cerebral infarction, and all-cause mortality.”

Thus, he said, “while there are general guidelines recommending a BMI below 25, our findings suggest that personalized BMI targets may be more beneficial, particularly for different age groups and individuals with specific health conditions.”

Asked to comment, Ian J. Neeland, MD, director of cardiovascular prevention, University Hospitals Harrington Heart & Vascular Institute, Case Western Reserve University, Cleveland, Ohio, pointed out that older people who are underweight or in lower weight categories may be more likely to smoke or have undiagnosed cancer, or that “their BMI is not so much reflective of fat mass as of low muscle mass, or sarcopenia, and that is definitely a risk factor for adverse outcomes and risks. ... And those who have slightly higher BMIs may be maintaining muscle mass, even though they’re older, and therefore they have less risk.”

However, Dr. Neeland disagreed with the authors’ conclusions regarding “optimal” BMI. “Just because you have different risk categories based on BMI doesn’t mean that’s ‘optimal’ BMI. The way I would interpret this paper is that there’s an association of mildly overweight with better outcomes in adults who are over 65 with type 2 diabetes. We need to try to understand the mechanisms underlying that observation.”

Dr. Neeland advised that for an older person with T2D who has low muscle mass and frailty, “I wouldn’t recommend necessarily targeted weight loss in that person. But I would potentially recommend weight loss in addition to resistance training, muscle building, and endurance training, and therefore reducing fat mass. The goal would be not so much weight loss but reduction of body fat and maintaining and improving muscle health.”
 

U-Shaped Relationship Found Between Age, BMI, and Cardiovascular Disease (CVD) Risk

The data come from the UK Biobank, a population-based prospective cohort study of adults in the United Kingdom. A total of 22,874 participants with baseline T2D were included in the current study. Baseline surveys were conducted between 2006 and 2010, and follow-up was a median of 12.52 years. During that time, 891 people died of CVD.

Hazard ratios were adjusted for baseline variables including age, sex, smoking history, alcohol consumption, level of physical exercise, and history of CVDs.

Compared with people with BMI a < 25 in the group who were aged 65 years or younger, those with a BMI of 25.0-29.9 had a 13% higher risk for cardiovascular death. However, among those older than 65 years, a BMI between 25.0 and 29.9 was associated with an 18% lower risk.

A U-shaped relationship was found between BMI and the risk for cardiovascular death, with an optimal BMI cutoff of 24.0 in the under-65 group and a 27.0 cutoff in the older group. Ranges of 23.0-25.0 in the under-65 group and 26.0-28 in the older group were associated with the lowest cardiovascular risk.

In contrast, there was a linear relationship between both waist circumference and waist-to-height ratio and the risk for cardiovascular death, making those more direct measures of adiposity, Dr. Xu told this news organization.

“For clinicians, our data underscores the importance of considering age when assessing BMI targets for cardiovascular health. Personalized treatment plans that account for age-specific BMI cutoffs and other risk factors may enhance patient outcomes and reduce CVD mortality,” Dr. Xu said.

However, he added, “while these findings suggest an optimal BMI range, it is crucial to acknowledge that these cutoff points may vary based on gender, race, and other factors. Our future studies will validate these findings in different populations and attempt to explain the mechanism by which the optimal nodal values exist in people with diabetes at different ages.”

Dr. Neeland cautioned, “I think more work needs to be done in terms of not just identifying the risk differences but understanding why and how to better risk stratify individuals and do personalized medicine. I think that’s important, but you have to have good data to support the strategies you’re going to use. These data are observational, and they’re a good start, but they wouldn’t directly impact practice at this point.”

The data will be presented at the European Congress on Obesity taking place May 12-15 in Venice, Italy.

The authors declared no competing interests. Study funding came from several sources, including the Young Talents Project of Hubei Provincial Health Commission, China, Hubei Provincial Natural Science Foundation of China, the Science and Technology Research Key Project of the Education Department of Hubei Province China, and the Sanuo Diabetes Charity Foundation, China, and the Xiangyang Science and Technology Plan Project, China. Dr. Neeland is a speaker and/or consultant for Boehringer Ingelheim, Novo Nordisk, Bayer, and Eli Lilly and Company.
 

A version of this article appeared on Medscape.com.

Among adults with type 2 diabetes (T2D) older than 65 years, a body mass index (BMI) in the moderate overweight category (26-28) appears to offer better protection from cardiovascular death than does a BMI in the “normal” range, new data suggested.

On the other hand, the study findings also suggest that the “normal” range of 23-25 is optimal for middle-aged adults with T2D.

The findings reflect a previously demonstrated phenomenon called the “obesity paradox,” in which older people with overweight may have better outcomes than leaner people due to factors such as bone loss, frailty, and nutritional deficits, study lead author Shaoyong Xu, of Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, China, told this news organization.

“In this era of population growth and aging, the question arises as to whether obesity or overweight can be beneficial in improving survival rates for older individuals with diabetes. This topic holds significant relevance due to the potential implications it has on weight management strategies for older adults. If overweight does not pose an increased risk of cardiovascular mortality, it may suggest that older individuals are not necessarily required to strive for weight loss to achieve so-called normal values.”

Moreover, Dr. Xu added, “inappropriate weight loss and being underweight could potentially elevate the risk of cardiovascular events, myocardial infarction, cerebral infarction, and all-cause mortality.”

Thus, he said, “while there are general guidelines recommending a BMI below 25, our findings suggest that personalized BMI targets may be more beneficial, particularly for different age groups and individuals with specific health conditions.”

Asked to comment, Ian J. Neeland, MD, director of cardiovascular prevention, University Hospitals Harrington Heart & Vascular Institute, Case Western Reserve University, Cleveland, Ohio, pointed out that older people who are underweight or in lower weight categories may be more likely to smoke or have undiagnosed cancer, or that “their BMI is not so much reflective of fat mass as of low muscle mass, or sarcopenia, and that is definitely a risk factor for adverse outcomes and risks. ... And those who have slightly higher BMIs may be maintaining muscle mass, even though they’re older, and therefore they have less risk.”

However, Dr. Neeland disagreed with the authors’ conclusions regarding “optimal” BMI. “Just because you have different risk categories based on BMI doesn’t mean that’s ‘optimal’ BMI. The way I would interpret this paper is that there’s an association of mildly overweight with better outcomes in adults who are over 65 with type 2 diabetes. We need to try to understand the mechanisms underlying that observation.”

Dr. Neeland advised that for an older person with T2D who has low muscle mass and frailty, “I wouldn’t recommend necessarily targeted weight loss in that person. But I would potentially recommend weight loss in addition to resistance training, muscle building, and endurance training, and therefore reducing fat mass. The goal would be not so much weight loss but reduction of body fat and maintaining and improving muscle health.”
 

U-Shaped Relationship Found Between Age, BMI, and Cardiovascular Disease (CVD) Risk

The data come from the UK Biobank, a population-based prospective cohort study of adults in the United Kingdom. A total of 22,874 participants with baseline T2D were included in the current study. Baseline surveys were conducted between 2006 and 2010, and follow-up was a median of 12.52 years. During that time, 891 people died of CVD.

Hazard ratios were adjusted for baseline variables including age, sex, smoking history, alcohol consumption, level of physical exercise, and history of CVDs.

Compared with people with BMI a < 25 in the group who were aged 65 years or younger, those with a BMI of 25.0-29.9 had a 13% higher risk for cardiovascular death. However, among those older than 65 years, a BMI between 25.0 and 29.9 was associated with an 18% lower risk.

A U-shaped relationship was found between BMI and the risk for cardiovascular death, with an optimal BMI cutoff of 24.0 in the under-65 group and a 27.0 cutoff in the older group. Ranges of 23.0-25.0 in the under-65 group and 26.0-28 in the older group were associated with the lowest cardiovascular risk.

In contrast, there was a linear relationship between both waist circumference and waist-to-height ratio and the risk for cardiovascular death, making those more direct measures of adiposity, Dr. Xu told this news organization.

“For clinicians, our data underscores the importance of considering age when assessing BMI targets for cardiovascular health. Personalized treatment plans that account for age-specific BMI cutoffs and other risk factors may enhance patient outcomes and reduce CVD mortality,” Dr. Xu said.

However, he added, “while these findings suggest an optimal BMI range, it is crucial to acknowledge that these cutoff points may vary based on gender, race, and other factors. Our future studies will validate these findings in different populations and attempt to explain the mechanism by which the optimal nodal values exist in people with diabetes at different ages.”

Dr. Neeland cautioned, “I think more work needs to be done in terms of not just identifying the risk differences but understanding why and how to better risk stratify individuals and do personalized medicine. I think that’s important, but you have to have good data to support the strategies you’re going to use. These data are observational, and they’re a good start, but they wouldn’t directly impact practice at this point.”

The data will be presented at the European Congress on Obesity taking place May 12-15 in Venice, Italy.

The authors declared no competing interests. Study funding came from several sources, including the Young Talents Project of Hubei Provincial Health Commission, China, Hubei Provincial Natural Science Foundation of China, the Science and Technology Research Key Project of the Education Department of Hubei Province China, and the Sanuo Diabetes Charity Foundation, China, and the Xiangyang Science and Technology Plan Project, China. Dr. Neeland is a speaker and/or consultant for Boehringer Ingelheim, Novo Nordisk, Bayer, and Eli Lilly and Company.
 

A version of this article appeared on Medscape.com.

Among adults with type 2 diabetes (T2D) older than 65 years, a body mass index (BMI) in the moderate overweight category (26-28) appears to offer better protection from cardiovascular death than does a BMI in the “normal” range, new data suggested.

On the other hand, the study findings also suggest that the “normal” range of 23-25 is optimal for middle-aged adults with T2D.

The findings reflect a previously demonstrated phenomenon called the “obesity paradox,” in which older people with overweight may have better outcomes than leaner people due to factors such as bone loss, frailty, and nutritional deficits, study lead author Shaoyong Xu, of Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, China, told this news organization.

“In this era of population growth and aging, the question arises as to whether obesity or overweight can be beneficial in improving survival rates for older individuals with diabetes. This topic holds significant relevance due to the potential implications it has on weight management strategies for older adults. If overweight does not pose an increased risk of cardiovascular mortality, it may suggest that older individuals are not necessarily required to strive for weight loss to achieve so-called normal values.”

Moreover, Dr. Xu added, “inappropriate weight loss and being underweight could potentially elevate the risk of cardiovascular events, myocardial infarction, cerebral infarction, and all-cause mortality.”

Thus, he said, “while there are general guidelines recommending a BMI below 25, our findings suggest that personalized BMI targets may be more beneficial, particularly for different age groups and individuals with specific health conditions.”

Asked to comment, Ian J. Neeland, MD, director of cardiovascular prevention, University Hospitals Harrington Heart & Vascular Institute, Case Western Reserve University, Cleveland, Ohio, pointed out that older people who are underweight or in lower weight categories may be more likely to smoke or have undiagnosed cancer, or that “their BMI is not so much reflective of fat mass as of low muscle mass, or sarcopenia, and that is definitely a risk factor for adverse outcomes and risks. ... And those who have slightly higher BMIs may be maintaining muscle mass, even though they’re older, and therefore they have less risk.”

However, Dr. Neeland disagreed with the authors’ conclusions regarding “optimal” BMI. “Just because you have different risk categories based on BMI doesn’t mean that’s ‘optimal’ BMI. The way I would interpret this paper is that there’s an association of mildly overweight with better outcomes in adults who are over 65 with type 2 diabetes. We need to try to understand the mechanisms underlying that observation.”

Dr. Neeland advised that for an older person with T2D who has low muscle mass and frailty, “I wouldn’t recommend necessarily targeted weight loss in that person. But I would potentially recommend weight loss in addition to resistance training, muscle building, and endurance training, and therefore reducing fat mass. The goal would be not so much weight loss but reduction of body fat and maintaining and improving muscle health.”
 

U-Shaped Relationship Found Between Age, BMI, and Cardiovascular Disease (CVD) Risk

The data come from the UK Biobank, a population-based prospective cohort study of adults in the United Kingdom. A total of 22,874 participants with baseline T2D were included in the current study. Baseline surveys were conducted between 2006 and 2010, and follow-up was a median of 12.52 years. During that time, 891 people died of CVD.

Hazard ratios were adjusted for baseline variables including age, sex, smoking history, alcohol consumption, level of physical exercise, and history of CVDs.

Compared with people with BMI a < 25 in the group who were aged 65 years or younger, those with a BMI of 25.0-29.9 had a 13% higher risk for cardiovascular death. However, among those older than 65 years, a BMI between 25.0 and 29.9 was associated with an 18% lower risk.

A U-shaped relationship was found between BMI and the risk for cardiovascular death, with an optimal BMI cutoff of 24.0 in the under-65 group and a 27.0 cutoff in the older group. Ranges of 23.0-25.0 in the under-65 group and 26.0-28 in the older group were associated with the lowest cardiovascular risk.

In contrast, there was a linear relationship between both waist circumference and waist-to-height ratio and the risk for cardiovascular death, making those more direct measures of adiposity, Dr. Xu told this news organization.

“For clinicians, our data underscores the importance of considering age when assessing BMI targets for cardiovascular health. Personalized treatment plans that account for age-specific BMI cutoffs and other risk factors may enhance patient outcomes and reduce CVD mortality,” Dr. Xu said.

However, he added, “while these findings suggest an optimal BMI range, it is crucial to acknowledge that these cutoff points may vary based on gender, race, and other factors. Our future studies will validate these findings in different populations and attempt to explain the mechanism by which the optimal nodal values exist in people with diabetes at different ages.”

Dr. Neeland cautioned, “I think more work needs to be done in terms of not just identifying the risk differences but understanding why and how to better risk stratify individuals and do personalized medicine. I think that’s important, but you have to have good data to support the strategies you’re going to use. These data are observational, and they’re a good start, but they wouldn’t directly impact practice at this point.”

The data will be presented at the European Congress on Obesity taking place May 12-15 in Venice, Italy.

The authors declared no competing interests. Study funding came from several sources, including the Young Talents Project of Hubei Provincial Health Commission, China, Hubei Provincial Natural Science Foundation of China, the Science and Technology Research Key Project of the Education Department of Hubei Province China, and the Sanuo Diabetes Charity Foundation, China, and the Xiangyang Science and Technology Plan Project, China. Dr. Neeland is a speaker and/or consultant for Boehringer Ingelheim, Novo Nordisk, Bayer, and Eli Lilly and Company.
 

A version of this article appeared on Medscape.com.