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Sports experts on T2D: Boost activity, cut sedentary time
The American College of Sports Medicine (ACSM) has issued new recommendations for exercise/physical activity in people with type 2 diabetes, which update a 2010 joint ACSM/American Diabetes Association position statement.
The guidance has been published in the February issue of Medicine & Science in Sports & Exercise.
“This consensus statement provides a brief summary of the current evidence and extends and updates the prior recommendations,” the authors explain.
In the past decade, there has been a “considerable amount” of research about exercise in people with type 2 diabetes, they add, while the prevalence of diabetes has steadily increased.
The updated recommendations have been “expanded to include physical activity – a broader, more comprehensive definition of human movement than planned exercise – and reducing sedentary time,” the authors note.
“The latest guidelines are applicable to most individuals with diabetes, including youth, with a few exceptions and modifications,” lead author Jill A. Kanaley, PhD, said in a press release from the ACSM.
The key takeaway is that “all individuals [with type 2 diabetes] should engage in regular physical activity, reduce sedentary time, and break up sitting time with frequent activity breaks,” said Dr. Kanaley, a professor in the department of nutrition and exercise physiology, University of Missouri, Columbia.
“Exercise can play an important role in managing type 2 diabetes, and workouts can be modified to fit the abilities of most people,” she stressed.
And those with type 2 diabetes who want to lose weight “should consider workouts of moderately high volume for 4 to 5 days per week,” she added.
Six key tips for physical activity in adults with type 2 diabetes
The consensus statement gives six key tips for physical activity in adults with type 2 diabetes, as follows.
- Regular aerobic exercise improves glycemic management; meta-analyses have reported fewer daily hyperglycemic episodes and reductions in A1c of 0.5%-0.7%.
- High-intensity resistance exercise, when performed safely, is better than low-to-moderate intensity resistance exercise for glucose management and attenuation of insulin levels. Resistance exercise typically results in improvements of 10% to 15% in strength, bone mineral density, blood pressure, lipid profile, skeletal muscle mass, and insulin sensitivity.
- Exercise after meals, such as taking a walk after dinner at one’s own pace, takes advantage of the blood glucose-stabilizing effects of exercise.
- Reduce sedentary time by taking regular breaks for small “doses” of physical activity, which can modestly attenuate postprandial glucose and insulin levels, particularly in individuals with insulin resistance and a higher body mass index.
- To prevent hypoglycemia during or after exercise, people taking insulin or insulin secretagogues should increase carbohydrate intake, or if possible, reduce insulin.
- People who are taking beta blockers should not rely on a heart monitor to measure workout intensity. They could ask a certified exercise professional about using ratings of perceived exertion to track how a workout feels.
Other recommendations
The consensus statement also summarizes precautions that people with complications of type 2 diabetes (such as neuropathy, retinopathy, kidney disease, and hypertension) should take.
Low impact exercises for flexibility can help introduce sedentary people to physical activity, the consensus group writes. Balance exercises can be helpful for older adults.
Weight loss greater than 5% can benefit A1c, blood lipid, and blood pressure levels. Moderate exercise 4 to 5 days a week can reduce visceral fat.
In studies of youth with type 2 diabetes, intensive lifestyle interventions plus metformin were not superior to metformin alone for managing glycemia. Physical activity goals are the same for youth with or without diabetes.
Pregnant women with diabetes should participate in at least 20 to 30 minutes of moderate-intensity exercise most days of the week.
Participating in an exercise program before and after bariatric surgery may enhance surgical outcomes.
Dr. Kanaley has reported receiving a grant from the National Institutes of Health. Disclosures for the other authors are listed in the article.
A version of this article first appeared on Medscape.com.
The American College of Sports Medicine (ACSM) has issued new recommendations for exercise/physical activity in people with type 2 diabetes, which update a 2010 joint ACSM/American Diabetes Association position statement.
The guidance has been published in the February issue of Medicine & Science in Sports & Exercise.
“This consensus statement provides a brief summary of the current evidence and extends and updates the prior recommendations,” the authors explain.
In the past decade, there has been a “considerable amount” of research about exercise in people with type 2 diabetes, they add, while the prevalence of diabetes has steadily increased.
The updated recommendations have been “expanded to include physical activity – a broader, more comprehensive definition of human movement than planned exercise – and reducing sedentary time,” the authors note.
“The latest guidelines are applicable to most individuals with diabetes, including youth, with a few exceptions and modifications,” lead author Jill A. Kanaley, PhD, said in a press release from the ACSM.
The key takeaway is that “all individuals [with type 2 diabetes] should engage in regular physical activity, reduce sedentary time, and break up sitting time with frequent activity breaks,” said Dr. Kanaley, a professor in the department of nutrition and exercise physiology, University of Missouri, Columbia.
“Exercise can play an important role in managing type 2 diabetes, and workouts can be modified to fit the abilities of most people,” she stressed.
And those with type 2 diabetes who want to lose weight “should consider workouts of moderately high volume for 4 to 5 days per week,” she added.
Six key tips for physical activity in adults with type 2 diabetes
The consensus statement gives six key tips for physical activity in adults with type 2 diabetes, as follows.
- Regular aerobic exercise improves glycemic management; meta-analyses have reported fewer daily hyperglycemic episodes and reductions in A1c of 0.5%-0.7%.
- High-intensity resistance exercise, when performed safely, is better than low-to-moderate intensity resistance exercise for glucose management and attenuation of insulin levels. Resistance exercise typically results in improvements of 10% to 15% in strength, bone mineral density, blood pressure, lipid profile, skeletal muscle mass, and insulin sensitivity.
- Exercise after meals, such as taking a walk after dinner at one’s own pace, takes advantage of the blood glucose-stabilizing effects of exercise.
- Reduce sedentary time by taking regular breaks for small “doses” of physical activity, which can modestly attenuate postprandial glucose and insulin levels, particularly in individuals with insulin resistance and a higher body mass index.
- To prevent hypoglycemia during or after exercise, people taking insulin or insulin secretagogues should increase carbohydrate intake, or if possible, reduce insulin.
- People who are taking beta blockers should not rely on a heart monitor to measure workout intensity. They could ask a certified exercise professional about using ratings of perceived exertion to track how a workout feels.
Other recommendations
The consensus statement also summarizes precautions that people with complications of type 2 diabetes (such as neuropathy, retinopathy, kidney disease, and hypertension) should take.
Low impact exercises for flexibility can help introduce sedentary people to physical activity, the consensus group writes. Balance exercises can be helpful for older adults.
Weight loss greater than 5% can benefit A1c, blood lipid, and blood pressure levels. Moderate exercise 4 to 5 days a week can reduce visceral fat.
In studies of youth with type 2 diabetes, intensive lifestyle interventions plus metformin were not superior to metformin alone for managing glycemia. Physical activity goals are the same for youth with or without diabetes.
Pregnant women with diabetes should participate in at least 20 to 30 minutes of moderate-intensity exercise most days of the week.
Participating in an exercise program before and after bariatric surgery may enhance surgical outcomes.
Dr. Kanaley has reported receiving a grant from the National Institutes of Health. Disclosures for the other authors are listed in the article.
A version of this article first appeared on Medscape.com.
The American College of Sports Medicine (ACSM) has issued new recommendations for exercise/physical activity in people with type 2 diabetes, which update a 2010 joint ACSM/American Diabetes Association position statement.
The guidance has been published in the February issue of Medicine & Science in Sports & Exercise.
“This consensus statement provides a brief summary of the current evidence and extends and updates the prior recommendations,” the authors explain.
In the past decade, there has been a “considerable amount” of research about exercise in people with type 2 diabetes, they add, while the prevalence of diabetes has steadily increased.
The updated recommendations have been “expanded to include physical activity – a broader, more comprehensive definition of human movement than planned exercise – and reducing sedentary time,” the authors note.
“The latest guidelines are applicable to most individuals with diabetes, including youth, with a few exceptions and modifications,” lead author Jill A. Kanaley, PhD, said in a press release from the ACSM.
The key takeaway is that “all individuals [with type 2 diabetes] should engage in regular physical activity, reduce sedentary time, and break up sitting time with frequent activity breaks,” said Dr. Kanaley, a professor in the department of nutrition and exercise physiology, University of Missouri, Columbia.
“Exercise can play an important role in managing type 2 diabetes, and workouts can be modified to fit the abilities of most people,” she stressed.
And those with type 2 diabetes who want to lose weight “should consider workouts of moderately high volume for 4 to 5 days per week,” she added.
Six key tips for physical activity in adults with type 2 diabetes
The consensus statement gives six key tips for physical activity in adults with type 2 diabetes, as follows.
- Regular aerobic exercise improves glycemic management; meta-analyses have reported fewer daily hyperglycemic episodes and reductions in A1c of 0.5%-0.7%.
- High-intensity resistance exercise, when performed safely, is better than low-to-moderate intensity resistance exercise for glucose management and attenuation of insulin levels. Resistance exercise typically results in improvements of 10% to 15% in strength, bone mineral density, blood pressure, lipid profile, skeletal muscle mass, and insulin sensitivity.
- Exercise after meals, such as taking a walk after dinner at one’s own pace, takes advantage of the blood glucose-stabilizing effects of exercise.
- Reduce sedentary time by taking regular breaks for small “doses” of physical activity, which can modestly attenuate postprandial glucose and insulin levels, particularly in individuals with insulin resistance and a higher body mass index.
- To prevent hypoglycemia during or after exercise, people taking insulin or insulin secretagogues should increase carbohydrate intake, or if possible, reduce insulin.
- People who are taking beta blockers should not rely on a heart monitor to measure workout intensity. They could ask a certified exercise professional about using ratings of perceived exertion to track how a workout feels.
Other recommendations
The consensus statement also summarizes precautions that people with complications of type 2 diabetes (such as neuropathy, retinopathy, kidney disease, and hypertension) should take.
Low impact exercises for flexibility can help introduce sedentary people to physical activity, the consensus group writes. Balance exercises can be helpful for older adults.
Weight loss greater than 5% can benefit A1c, blood lipid, and blood pressure levels. Moderate exercise 4 to 5 days a week can reduce visceral fat.
In studies of youth with type 2 diabetes, intensive lifestyle interventions plus metformin were not superior to metformin alone for managing glycemia. Physical activity goals are the same for youth with or without diabetes.
Pregnant women with diabetes should participate in at least 20 to 30 minutes of moderate-intensity exercise most days of the week.
Participating in an exercise program before and after bariatric surgery may enhance surgical outcomes.
Dr. Kanaley has reported receiving a grant from the National Institutes of Health. Disclosures for the other authors are listed in the article.
A version of this article first appeared on Medscape.com.
FDA okays 6-month implanted Eversense CGM for diabetes
The U.S. Food and Drug Administration has approved a new second-generation version of the implanted continuous glucose monitoring (CGM) system Eversense (Senseonics) that lasts for 6 months.
The Eversense E3 CGM system doubles the wear time from 3 months with the previous Eversense device approved in the United States in 2018. As before, the new system is approved for adults with diabetes aged 18 years and older.
This means that it will be the longest lasting CGM system available in the United States, with essentially two sensor insertion and removal procedures per year, the company said.
Data from the pivotal PROMISE trial of the 6-month version were presented at the American Diabetes Association Scientific Sessions in 2021, as reported by this news organization.
An older 6-month wear time version (Eversense XL) has been available in Europe since 2017. The new second-generation 6-month system is currently under regulatory review there.
The PROMISE trial included 181 participants with diabetes, about two-thirds with type 1 and one-third with type 2 diabetes, at eight clinical research sites.
“We repeatedly hear from our patients with diabetes that what they desire is a long-lasting sensor that is also highly accurate ... The next generation Eversense E3 System delivers on both,” said PROMISE study principal investigator Satish Garg, MD, professor of medicine and director of the adult diabetes program at the Barbara Davis Center, University of Colorado, Aurora, in a company press release.
The Eversense E3 consists of a fluorescence-based sensor, a transmitter, and a smartphone app that displays glucose values, trends, and alerts. The sensor is inserted subcutaneously into the upper arm by a certified health care professional in a brief office procedure. The transmitter is placed on the skin on top of the sensor. Glucose data are sent to the app automatically every 5 minutes.
The system includes an on-body vibratory alert as well as alerts on the app for high and low blood glucose values. Eversense readings may be used for treatment decisions, but users still must perform fingerstick glucose checks for calibration.
The regulatory review for the Eversense E3 was delayed for a year due to the COVID-19 pandemic. It will be distributed in the United States through a partnership with Ascensia Diabetes Care beginning in the second quarter of 2022, according to a Senseonics statement.
In addition, “the company expects the majority of its expenses for 2022 to be for research and development for ongoing feasibility and pivotal clinical trials for additional products in its product pipeline, including the start of its 365-day pivotal trial.”
Health care providers who want to offer the Eversense CGM System to their patients can sign up here or call 844-SENSE4U (844-736-7348).
Patients interested in getting started on Eversense can sign up here and will be among the first to know when Eversense E3 is commercially available.
A version of this article first appeared on Medscape.com.
The U.S. Food and Drug Administration has approved a new second-generation version of the implanted continuous glucose monitoring (CGM) system Eversense (Senseonics) that lasts for 6 months.
The Eversense E3 CGM system doubles the wear time from 3 months with the previous Eversense device approved in the United States in 2018. As before, the new system is approved for adults with diabetes aged 18 years and older.
This means that it will be the longest lasting CGM system available in the United States, with essentially two sensor insertion and removal procedures per year, the company said.
Data from the pivotal PROMISE trial of the 6-month version were presented at the American Diabetes Association Scientific Sessions in 2021, as reported by this news organization.
An older 6-month wear time version (Eversense XL) has been available in Europe since 2017. The new second-generation 6-month system is currently under regulatory review there.
The PROMISE trial included 181 participants with diabetes, about two-thirds with type 1 and one-third with type 2 diabetes, at eight clinical research sites.
“We repeatedly hear from our patients with diabetes that what they desire is a long-lasting sensor that is also highly accurate ... The next generation Eversense E3 System delivers on both,” said PROMISE study principal investigator Satish Garg, MD, professor of medicine and director of the adult diabetes program at the Barbara Davis Center, University of Colorado, Aurora, in a company press release.
The Eversense E3 consists of a fluorescence-based sensor, a transmitter, and a smartphone app that displays glucose values, trends, and alerts. The sensor is inserted subcutaneously into the upper arm by a certified health care professional in a brief office procedure. The transmitter is placed on the skin on top of the sensor. Glucose data are sent to the app automatically every 5 minutes.
The system includes an on-body vibratory alert as well as alerts on the app for high and low blood glucose values. Eversense readings may be used for treatment decisions, but users still must perform fingerstick glucose checks for calibration.
The regulatory review for the Eversense E3 was delayed for a year due to the COVID-19 pandemic. It will be distributed in the United States through a partnership with Ascensia Diabetes Care beginning in the second quarter of 2022, according to a Senseonics statement.
In addition, “the company expects the majority of its expenses for 2022 to be for research and development for ongoing feasibility and pivotal clinical trials for additional products in its product pipeline, including the start of its 365-day pivotal trial.”
Health care providers who want to offer the Eversense CGM System to their patients can sign up here or call 844-SENSE4U (844-736-7348).
Patients interested in getting started on Eversense can sign up here and will be among the first to know when Eversense E3 is commercially available.
A version of this article first appeared on Medscape.com.
The U.S. Food and Drug Administration has approved a new second-generation version of the implanted continuous glucose monitoring (CGM) system Eversense (Senseonics) that lasts for 6 months.
The Eversense E3 CGM system doubles the wear time from 3 months with the previous Eversense device approved in the United States in 2018. As before, the new system is approved for adults with diabetes aged 18 years and older.
This means that it will be the longest lasting CGM system available in the United States, with essentially two sensor insertion and removal procedures per year, the company said.
Data from the pivotal PROMISE trial of the 6-month version were presented at the American Diabetes Association Scientific Sessions in 2021, as reported by this news organization.
An older 6-month wear time version (Eversense XL) has been available in Europe since 2017. The new second-generation 6-month system is currently under regulatory review there.
The PROMISE trial included 181 participants with diabetes, about two-thirds with type 1 and one-third with type 2 diabetes, at eight clinical research sites.
“We repeatedly hear from our patients with diabetes that what they desire is a long-lasting sensor that is also highly accurate ... The next generation Eversense E3 System delivers on both,” said PROMISE study principal investigator Satish Garg, MD, professor of medicine and director of the adult diabetes program at the Barbara Davis Center, University of Colorado, Aurora, in a company press release.
The Eversense E3 consists of a fluorescence-based sensor, a transmitter, and a smartphone app that displays glucose values, trends, and alerts. The sensor is inserted subcutaneously into the upper arm by a certified health care professional in a brief office procedure. The transmitter is placed on the skin on top of the sensor. Glucose data are sent to the app automatically every 5 minutes.
The system includes an on-body vibratory alert as well as alerts on the app for high and low blood glucose values. Eversense readings may be used for treatment decisions, but users still must perform fingerstick glucose checks for calibration.
The regulatory review for the Eversense E3 was delayed for a year due to the COVID-19 pandemic. It will be distributed in the United States through a partnership with Ascensia Diabetes Care beginning in the second quarter of 2022, according to a Senseonics statement.
In addition, “the company expects the majority of its expenses for 2022 to be for research and development for ongoing feasibility and pivotal clinical trials for additional products in its product pipeline, including the start of its 365-day pivotal trial.”
Health care providers who want to offer the Eversense CGM System to their patients can sign up here or call 844-SENSE4U (844-736-7348).
Patients interested in getting started on Eversense can sign up here and will be among the first to know when Eversense E3 is commercially available.
A version of this article first appeared on Medscape.com.
Do latest SURPASS findings with twincretin in diabetes impress?
, new research shows.
The novel once-weekly injectable agent is nicknamed a twincretin because it combines two different gut-hormone activities. It works both as a glucagonlike peptide-1 (GLP-1) receptor agonist and as an agent that mimics the glucose-dependent insulinotropic polypeptide (GIP).
Findings from the randomized phase 3 SURPASS-5 clinical trial were published online Feb. 8 in JAMA.
This is the latest in a series of SURPASS trials of tirzepatide in individuals with type 2 diabetes for which results have been presented at various conferences, announced by the company, and/or published since late 2020.
SURPASS-5 specifically investigated the effect on glycemic control of adding three different doses of once-weekly subcutaneous tirzepatide compared with placebo in 475 adults who hadn’t achieved target A1c levels using insulin glargine with or without metformin. Statistically significant reductions in A1c were found at 40 weeks for all three doses.
Moreover, authors Dominik Dahl, MD, group practice for internal medicine and diabetology, Hamburg, Germany, and colleagues note that the improvements in the tirzepatide groups “were associated with significantly lower insulin glargine use and significant bodyweight reduction compared with placebo.”
“Despite the differences in glycemic control between the tirzepatide and placebo groups, the rate of clinically significant or severe hypoglycemia was below one event per patient-year in all treatment groups,” they add.
However, concerns about the study protocol and generalizability were raised in an accompanying editorial by Stuart R. Chipkin, MD, of the School of Public Health & Health Sciences, University of Massachusetts Amherst.
“Importantly, the study did not compare tirzepatide with other treatments that could have been used to target the postprandial glycemic pattern of the study population,” he writes.
And ultimately, he says: “Even though the results of this investigation are important for demonstrating the potential clinical benefit of [tirzepatide], and may help to advance the goal of achieving U.S. Food and Drug Administration approval, the study may leave clinicians uncertain about when and how to best use tirzepatide to improve clinical outcomes for patients with type 2 diabetes.”
Significant A1c, weight reductions when added to insulin glargine
The randomized, phase 3 SURPASS-5 trial was conducted at 45 centers in eight countries between August 2019 and January 2021. The 475 adult participants had type 2 diabetes inadequately controlled (baseline A1c, 7.0%-10.5%) with once-daily insulin glargine, with or without metformin. They were randomized to receive once-weekly subcutaneous injections of tirzepatide in doses of 5 mg, 10 mg, or 15 mg, or volume-matched placebo injections over 40 weeks.
The mean changes from baseline in A1c at week 40, the primary study endpoint, were –2.11, –2.40, and –2.34 percentage points for the 5 mg, 10 mg, and 15 mg doses of tirzepatide, respectively (P < .001), versus a nonsignificant change of –0.86 percentage points with placebo. The differences from placebo at week 40 were also significant for the 10-mg and 15-mg doses (both P < .001).
Significantly higher proportions of patients receiving 5 mg, 10 mg, and 15 mg tirzepatide met the A1c target of less than 7% at week 40, compared with placebo (85%-90% vs. 34%; P < .001). Significantly higher proportions of patients in the 10-mg and 15-mg dose groups also achieved A1c less than 5.7% (42% and 50%, respectively, vs. 3%).
Mean fasting glucose was also reduced significantly with all doses of tirzepatide by 58.2 mg/dL, 64.0 mg/dL, and 62.6 mg/dL, respectively, versus 39.2 mg/dL with placebo (all P <0.001 vs. placebo).
At week 40, mean body weight reductions from baseline were 5.4 kg (11.9 lbs), 7.5 kg, and 8.8 kg versus just 1.6 kg with placebo (all P <0.001 vs. placebo).
All three tirzepatide doses were also associated with significant improvements from baseline in total cholesterol, low-density lipoprotein cholesterol, very low-density lipoprotein cholesterol, and triglycerides.
Gastrointestinal adverse events, hypoglycemia seen in minority
The most common treatment-emergent adverse events in the tirzepatide groups versus placebo were gastrointestinal, including diarrhea (12%-21% vs. 10%), nausea (13%-18% vs. 2.5%), vomiting (7%-13% vs. 2.5%), and decreased appetite (7%-14% vs. 1.7%). Most of these adverse events were mild to moderate in intensity and decreased over time in the tirzepatide groups.
There were no deaths in the study. Serious adverse events were reported by 8%-11% in the tirzepatide groups, compared with 8% in the placebo group. Drug discontinuation due to adverse events occurred in 6.0%, 8.4%, and 10.8% of the 5-mg, 10-mg, and 15-mg dose groups, respectively, versus 2.5% in the placebo group.
Rates of hypoglycemia (less than or equal to 70 mg/dL) ranged from 14.2% to 19.3% with tirzepatide versus 12.5% with placebo. There were three episodes of severe hypoglycemia (less than 54 mg/dL), two with 10 mg tirzepatide and one with 15 mg tirzepatide.
Editorial raises questions
In his editorial, Dr. Chipkin writes that the study “demonstrated that use of tirzepatide was associated with significant reductions in A1c and weight in a fairly homogeneous cohort of patients with type 2 diabetes who were receiving insulin glargine with or without metformin.”
“The protocol answered questions about efficacy but left open questions about generalizability and effectiveness in different populations, especially patients with certain complications or comorbid chronic diseases.” He also notes that younger adults and Black patients were not well-represented.
And the study didn’t allow for dividing up the glargine dose or for adding short-acting insulin before meals or any other pre-meal medications and “thus may represent a departure from usual care” in the setting of rising glucose levels.
The authors themselves acknowledge that “the postprandial glucose excursions observed in the placebo group suggest an additional prandial intervention was likely needed in some patients, despite the strict inclusion criteria and the treat-to-target-approach used in the study.”
Dr. Chipkin concludes that “although patients are likely to embrace a medication with weight loss outcomes, the protocol also leaves unanswered questions about reducing insulin and evaluating the comparative risk of adverse effects.”
The study was sponsored by Eli Lilly. Dr. Dahl has reported receiving personal fees from Eli Lilly during the conduct of the study and personal fees from Afimmune, Novo Nordisk, and Novartis outside the submitted work. Dr. Chipkin has reported no relevant financial relationships.
A version of this article first appeared on Medscape.com.
, new research shows.
The novel once-weekly injectable agent is nicknamed a twincretin because it combines two different gut-hormone activities. It works both as a glucagonlike peptide-1 (GLP-1) receptor agonist and as an agent that mimics the glucose-dependent insulinotropic polypeptide (GIP).
Findings from the randomized phase 3 SURPASS-5 clinical trial were published online Feb. 8 in JAMA.
This is the latest in a series of SURPASS trials of tirzepatide in individuals with type 2 diabetes for which results have been presented at various conferences, announced by the company, and/or published since late 2020.
SURPASS-5 specifically investigated the effect on glycemic control of adding three different doses of once-weekly subcutaneous tirzepatide compared with placebo in 475 adults who hadn’t achieved target A1c levels using insulin glargine with or without metformin. Statistically significant reductions in A1c were found at 40 weeks for all three doses.
Moreover, authors Dominik Dahl, MD, group practice for internal medicine and diabetology, Hamburg, Germany, and colleagues note that the improvements in the tirzepatide groups “were associated with significantly lower insulin glargine use and significant bodyweight reduction compared with placebo.”
“Despite the differences in glycemic control between the tirzepatide and placebo groups, the rate of clinically significant or severe hypoglycemia was below one event per patient-year in all treatment groups,” they add.
However, concerns about the study protocol and generalizability were raised in an accompanying editorial by Stuart R. Chipkin, MD, of the School of Public Health & Health Sciences, University of Massachusetts Amherst.
“Importantly, the study did not compare tirzepatide with other treatments that could have been used to target the postprandial glycemic pattern of the study population,” he writes.
And ultimately, he says: “Even though the results of this investigation are important for demonstrating the potential clinical benefit of [tirzepatide], and may help to advance the goal of achieving U.S. Food and Drug Administration approval, the study may leave clinicians uncertain about when and how to best use tirzepatide to improve clinical outcomes for patients with type 2 diabetes.”
Significant A1c, weight reductions when added to insulin glargine
The randomized, phase 3 SURPASS-5 trial was conducted at 45 centers in eight countries between August 2019 and January 2021. The 475 adult participants had type 2 diabetes inadequately controlled (baseline A1c, 7.0%-10.5%) with once-daily insulin glargine, with or without metformin. They were randomized to receive once-weekly subcutaneous injections of tirzepatide in doses of 5 mg, 10 mg, or 15 mg, or volume-matched placebo injections over 40 weeks.
The mean changes from baseline in A1c at week 40, the primary study endpoint, were –2.11, –2.40, and –2.34 percentage points for the 5 mg, 10 mg, and 15 mg doses of tirzepatide, respectively (P < .001), versus a nonsignificant change of –0.86 percentage points with placebo. The differences from placebo at week 40 were also significant for the 10-mg and 15-mg doses (both P < .001).
Significantly higher proportions of patients receiving 5 mg, 10 mg, and 15 mg tirzepatide met the A1c target of less than 7% at week 40, compared with placebo (85%-90% vs. 34%; P < .001). Significantly higher proportions of patients in the 10-mg and 15-mg dose groups also achieved A1c less than 5.7% (42% and 50%, respectively, vs. 3%).
Mean fasting glucose was also reduced significantly with all doses of tirzepatide by 58.2 mg/dL, 64.0 mg/dL, and 62.6 mg/dL, respectively, versus 39.2 mg/dL with placebo (all P <0.001 vs. placebo).
At week 40, mean body weight reductions from baseline were 5.4 kg (11.9 lbs), 7.5 kg, and 8.8 kg versus just 1.6 kg with placebo (all P <0.001 vs. placebo).
All three tirzepatide doses were also associated with significant improvements from baseline in total cholesterol, low-density lipoprotein cholesterol, very low-density lipoprotein cholesterol, and triglycerides.
Gastrointestinal adverse events, hypoglycemia seen in minority
The most common treatment-emergent adverse events in the tirzepatide groups versus placebo were gastrointestinal, including diarrhea (12%-21% vs. 10%), nausea (13%-18% vs. 2.5%), vomiting (7%-13% vs. 2.5%), and decreased appetite (7%-14% vs. 1.7%). Most of these adverse events were mild to moderate in intensity and decreased over time in the tirzepatide groups.
There were no deaths in the study. Serious adverse events were reported by 8%-11% in the tirzepatide groups, compared with 8% in the placebo group. Drug discontinuation due to adverse events occurred in 6.0%, 8.4%, and 10.8% of the 5-mg, 10-mg, and 15-mg dose groups, respectively, versus 2.5% in the placebo group.
Rates of hypoglycemia (less than or equal to 70 mg/dL) ranged from 14.2% to 19.3% with tirzepatide versus 12.5% with placebo. There were three episodes of severe hypoglycemia (less than 54 mg/dL), two with 10 mg tirzepatide and one with 15 mg tirzepatide.
Editorial raises questions
In his editorial, Dr. Chipkin writes that the study “demonstrated that use of tirzepatide was associated with significant reductions in A1c and weight in a fairly homogeneous cohort of patients with type 2 diabetes who were receiving insulin glargine with or without metformin.”
“The protocol answered questions about efficacy but left open questions about generalizability and effectiveness in different populations, especially patients with certain complications or comorbid chronic diseases.” He also notes that younger adults and Black patients were not well-represented.
And the study didn’t allow for dividing up the glargine dose or for adding short-acting insulin before meals or any other pre-meal medications and “thus may represent a departure from usual care” in the setting of rising glucose levels.
The authors themselves acknowledge that “the postprandial glucose excursions observed in the placebo group suggest an additional prandial intervention was likely needed in some patients, despite the strict inclusion criteria and the treat-to-target-approach used in the study.”
Dr. Chipkin concludes that “although patients are likely to embrace a medication with weight loss outcomes, the protocol also leaves unanswered questions about reducing insulin and evaluating the comparative risk of adverse effects.”
The study was sponsored by Eli Lilly. Dr. Dahl has reported receiving personal fees from Eli Lilly during the conduct of the study and personal fees from Afimmune, Novo Nordisk, and Novartis outside the submitted work. Dr. Chipkin has reported no relevant financial relationships.
A version of this article first appeared on Medscape.com.
, new research shows.
The novel once-weekly injectable agent is nicknamed a twincretin because it combines two different gut-hormone activities. It works both as a glucagonlike peptide-1 (GLP-1) receptor agonist and as an agent that mimics the glucose-dependent insulinotropic polypeptide (GIP).
Findings from the randomized phase 3 SURPASS-5 clinical trial were published online Feb. 8 in JAMA.
This is the latest in a series of SURPASS trials of tirzepatide in individuals with type 2 diabetes for which results have been presented at various conferences, announced by the company, and/or published since late 2020.
SURPASS-5 specifically investigated the effect on glycemic control of adding three different doses of once-weekly subcutaneous tirzepatide compared with placebo in 475 adults who hadn’t achieved target A1c levels using insulin glargine with or without metformin. Statistically significant reductions in A1c were found at 40 weeks for all three doses.
Moreover, authors Dominik Dahl, MD, group practice for internal medicine and diabetology, Hamburg, Germany, and colleagues note that the improvements in the tirzepatide groups “were associated with significantly lower insulin glargine use and significant bodyweight reduction compared with placebo.”
“Despite the differences in glycemic control between the tirzepatide and placebo groups, the rate of clinically significant or severe hypoglycemia was below one event per patient-year in all treatment groups,” they add.
However, concerns about the study protocol and generalizability were raised in an accompanying editorial by Stuart R. Chipkin, MD, of the School of Public Health & Health Sciences, University of Massachusetts Amherst.
“Importantly, the study did not compare tirzepatide with other treatments that could have been used to target the postprandial glycemic pattern of the study population,” he writes.
And ultimately, he says: “Even though the results of this investigation are important for demonstrating the potential clinical benefit of [tirzepatide], and may help to advance the goal of achieving U.S. Food and Drug Administration approval, the study may leave clinicians uncertain about when and how to best use tirzepatide to improve clinical outcomes for patients with type 2 diabetes.”
Significant A1c, weight reductions when added to insulin glargine
The randomized, phase 3 SURPASS-5 trial was conducted at 45 centers in eight countries between August 2019 and January 2021. The 475 adult participants had type 2 diabetes inadequately controlled (baseline A1c, 7.0%-10.5%) with once-daily insulin glargine, with or without metformin. They were randomized to receive once-weekly subcutaneous injections of tirzepatide in doses of 5 mg, 10 mg, or 15 mg, or volume-matched placebo injections over 40 weeks.
The mean changes from baseline in A1c at week 40, the primary study endpoint, were –2.11, –2.40, and –2.34 percentage points for the 5 mg, 10 mg, and 15 mg doses of tirzepatide, respectively (P < .001), versus a nonsignificant change of –0.86 percentage points with placebo. The differences from placebo at week 40 were also significant for the 10-mg and 15-mg doses (both P < .001).
Significantly higher proportions of patients receiving 5 mg, 10 mg, and 15 mg tirzepatide met the A1c target of less than 7% at week 40, compared with placebo (85%-90% vs. 34%; P < .001). Significantly higher proportions of patients in the 10-mg and 15-mg dose groups also achieved A1c less than 5.7% (42% and 50%, respectively, vs. 3%).
Mean fasting glucose was also reduced significantly with all doses of tirzepatide by 58.2 mg/dL, 64.0 mg/dL, and 62.6 mg/dL, respectively, versus 39.2 mg/dL with placebo (all P <0.001 vs. placebo).
At week 40, mean body weight reductions from baseline were 5.4 kg (11.9 lbs), 7.5 kg, and 8.8 kg versus just 1.6 kg with placebo (all P <0.001 vs. placebo).
All three tirzepatide doses were also associated with significant improvements from baseline in total cholesterol, low-density lipoprotein cholesterol, very low-density lipoprotein cholesterol, and triglycerides.
Gastrointestinal adverse events, hypoglycemia seen in minority
The most common treatment-emergent adverse events in the tirzepatide groups versus placebo were gastrointestinal, including diarrhea (12%-21% vs. 10%), nausea (13%-18% vs. 2.5%), vomiting (7%-13% vs. 2.5%), and decreased appetite (7%-14% vs. 1.7%). Most of these adverse events were mild to moderate in intensity and decreased over time in the tirzepatide groups.
There were no deaths in the study. Serious adverse events were reported by 8%-11% in the tirzepatide groups, compared with 8% in the placebo group. Drug discontinuation due to adverse events occurred in 6.0%, 8.4%, and 10.8% of the 5-mg, 10-mg, and 15-mg dose groups, respectively, versus 2.5% in the placebo group.
Rates of hypoglycemia (less than or equal to 70 mg/dL) ranged from 14.2% to 19.3% with tirzepatide versus 12.5% with placebo. There were three episodes of severe hypoglycemia (less than 54 mg/dL), two with 10 mg tirzepatide and one with 15 mg tirzepatide.
Editorial raises questions
In his editorial, Dr. Chipkin writes that the study “demonstrated that use of tirzepatide was associated with significant reductions in A1c and weight in a fairly homogeneous cohort of patients with type 2 diabetes who were receiving insulin glargine with or without metformin.”
“The protocol answered questions about efficacy but left open questions about generalizability and effectiveness in different populations, especially patients with certain complications or comorbid chronic diseases.” He also notes that younger adults and Black patients were not well-represented.
And the study didn’t allow for dividing up the glargine dose or for adding short-acting insulin before meals or any other pre-meal medications and “thus may represent a departure from usual care” in the setting of rising glucose levels.
The authors themselves acknowledge that “the postprandial glucose excursions observed in the placebo group suggest an additional prandial intervention was likely needed in some patients, despite the strict inclusion criteria and the treat-to-target-approach used in the study.”
Dr. Chipkin concludes that “although patients are likely to embrace a medication with weight loss outcomes, the protocol also leaves unanswered questions about reducing insulin and evaluating the comparative risk of adverse effects.”
The study was sponsored by Eli Lilly. Dr. Dahl has reported receiving personal fees from Eli Lilly during the conduct of the study and personal fees from Afimmune, Novo Nordisk, and Novartis outside the submitted work. Dr. Chipkin has reported no relevant financial relationships.
A version of this article first appeared on Medscape.com.
Biomarkers predict cardiovascular risk in chronic kidney disease patients
Chronic kidney disease (CKD) patients may be at increased risk for atherosclerotic cardiovascular disease, but no ASCVD risk prediction models are currently in place to inform clinical care and prevention strategies, Joshua Bundy, PhD, of Tulane University, New Orleans, and colleagues wrote in their paper, published in the Journal of the American Society of Nephrology.
To improve the accuracy of ASCVD risk prediction, the researchers developed several models using data from the Chronic Renal Insufficiency Cohort (CRIC) study. This longitudinal cohort study included more than 2,500 adult CKD patients. The participants’ ages ranged from 21-74 years, with the mean age having been 55.8 years, and 52.0% of the cohort was male.
Kidney function was defined using the glomerular filtration rate; the mean estimated glomerular filtration rate (eGFR) of the study participants was 56.0 mL/min per 1.73m2. The primary endpoint for the prediction models was incident ASCVD, defined as a composite of incident fatal or nonfatal stroke or MI.
A total of 252 incident ASCVD events occurred during the first 10 years of follow-up from baseline (1.9 events per 1,000 person-years). Patients with ASCVD events were more likely to be older, Black, and current smokers. They also were more likely than those who did not experience ASCVD events to have less than a college level education, to have a history of diabetes, and to use blood pressure–lowering medications.
“In our study, we created two new prediction tools for patients with CKD: the first is a simple model that includes factors routinely measured by health care providers and the second is an expanded model with additional variables particularly important to patients with CKD, including measures of long-term blood sugar, inflammation, and kidney and heart injury,” he explained. “We found that the new models are better able to classify patients who will or will not have a stroke or heart attack within 10 years, compared with the standard models. The new tools may better assist health care providers and patients with CKD in shared decision-making for prevention of heart disease.”
Results
The area under the curve for a prediction model using coefficients estimated within the CRIC sample was 0.736. This represented an accuracy higher than the American College of Cardiology/American Heart Association Pooled Cohort Equations (PCE), which have shown an AUC of 0.730 (P = .03). The PCE were developed by the ACC and the AHA in 2013 to estimate ASCVD risk in the primary prevention population.
The second CRIC model that was developed using clinically available variables had an AUC of 0.760. However, the third CRIC biomarker-enriched model was even more effective, with an AUC of 0.771 – significantly higher than the clinical model (P = .001).
Model 1 included the ACC/AHA PCE variables with coefficients recalculated in the CRIC study sample. Model 2 (the CRIC Clinical Model) included age, HDL cholesterol, systolic BP, current smoking, urinary albumin-to-creatinine ratio (ACR), hemoglobin A1c, and hemoglobin. Model 3 (the CRIC Enriched Model) included age, total cholesterol, HDL cholesterol, current smoking, urinary ACR, A1c, apolipoprotein B, high-sensitivity C-reactive protein (hsCRP), troponin T, and N-terminal of the prohormone brain natriuretic peptide (NT-proBNP).
Both the clinical and biomarker models improved reclassification of non-ASCVD events, compared with the PCEs (6.6% and 10.0%, respectively).
Several factors not included in prior prediction models were important for atherosclerotic CVD prediction among patients with CKD, the researchers noted. These included variables routinely measured in clinical practice as well as biomarkers: measures of long-term glycemia (A1c), inflammation (hsCRP), kidney injury (urinary ACR), and cardiac injury (troponin T and NT-proBNP).
Patients who had an ASCVD event had higher levels of A1c, systolic and diastolic BP, urinary ACR, troponin T, and NT-proBNP; these patients also had lower levels of HDL cholesterol, eGFR, and hemoglobin, compared with those who did not have an event.
The study findings were limited by several factors including the selection of study participants based on a single assessment of kidney function, who had an above average baseline ASCVD risk, the researchers noted. Other limitations included the inability to include imaging variables in the models, and the overestimated risk in the highest predicted probability groups in the CRIC study.
However, the models significantly improve prediction beyond the ACC/AHA PCE in patients with CKD, they concluded.
Models may inform shared decision-making
The development of new prediction models is important, because cardiovascular disease is the leading cause of death among U.S. adults and preventing CVD is a major public health challenge, lead author Dr. Bundy said in an interview.
“In an effort to prevent CVD, risk prediction equations can help identify patients who are at high risk for developing CVD and who may benefit from initiation or intensification of preventive and/or therapeutic measures. Simultaneously, chronic kidney disease is prevalent and those with CKD are often considered at high risk for CVD,” he said.
“However, common risk prediction tools were developed for the general population and may not work as well in patients with CKD, who may have different risk factors. Improving risk prediction in patients with CKD may help identify those among this growing population who are truly at high risk, as well as identify those who are at low risk and less likely to benefit from invasive procedures,” Dr. Bundy explained.
Glomerular filtration rate was not a strong predictor of atherosclerotic CVD
“One of the surprising findings was that estimated glomerular filtration rate was not a strong predictor and was not included in our final models,” Dr. Bundy said.
“We know that eGFR is a very important measurement in this population, but our results suggest that, at least in our sample, urinary albumin-to-creatinine ratio and cardiac biomarkers like troponin T and NT-proBNP are stronger predictors of atherosclerotic CVD in a population with reduced kidney function,” he said.
“Patient characteristics like age, blood pressure, and cholesterol are used by health care providers to predict whether a person will have a heart attack or stroke. However, most currently available prediction tools were not made for use in patients with CKD, which is a condition that is becoming more common and is likely to be seen by more health care providers in family practice,” said Dr. Bundy. “These people with CKD may have different risk factors for heart disease.”
Models are useful for clinical practice
“We are seeing rising numbers of patients with CKD in the population because of increasing age, rising rates of diabetes, and hypertension,” Noel Deep, MD, said in an interview. “The current practice of medicine does not have CKD-specific prediction models for ASCVD development, and current risks are calculated based on prediction models developed for the general population.”
“Having a prediction model that incorporates criteria/variables associated with CKD improves our ability to accurately identify and address the risk of ASCVD in this particular patient population,” said Dr. Deep, who is a general internist in a multispecialty group practice with Aspirus Antigo (Wisc.) Clinic and the chief medical officer and a staff physician at Aspirus Langlade Hospital, also in Antigo.
“We always knew that CKD does place the individual at higher risk for developing ASCVD, but I was impressed by the significant improvement in the prediction models using CKD specific tools, such as cardiac biomarkers (NT-proBNP), intensity of diabetes control (A1c), tobacco use, urinary albuminuria, in addition to advancing age,” he said. “Many of the laboratory tests listed in this study are commonly available and can be easily incorporated into our evaluation for and management of ASCVD in our patients with CKD.”
“As a practicing primary care physician, I would say that this study emphasizes the importance of identifying and working toward mitigating the associated health risks that our patients with CKD might have coexisting and that significantly contribute to progression of CKD,” said Dr. Deep, who is also assistant clinical professor at the Medical College of Wisconsin, Wausau. “By addressing these risk factors, we can positively impact the health of our patients with CKD and decrease the morbidity and mortality, and health care costs. These predictive models can hopefully help us more accurately identify the risk of ASCVD thereby decreasing unnecessary diagnostic procedures and interventions which carry their own risks and morbidity.”
Looking ahead, “these predictive models should be assessed and validated in large studies in diverse populations and those with different risk factors for ASCVD because CKD can be caused by several different medical conditions each with potential to contribute to ASCVD,” Dr. Deep added.
Limitations and next steps
“Although we externally validated our models in two population-based cohort studies, the individuals in these datasets were selected based on only one assessment of kidney function,” Dr. Bundy noted. “Furthermore, the best practices for implementing risk prediction models in the clinic remain to be determined, especially as new models are developed.
“While our models show promising performance for predicting 10-year risk of atherosclerotic CVD, more clinical trials are needed to test implementation of these models for improving patient care and disease prevention.”
The study was supported by the National Institute of Diabetes and Digestive and Kidney Diseases. Additional support came from the University of Pennsylvania Clinical and Translational Science Award, Johns Hopkins University, the University of Maryland, Clinical and Translational Science Collaborative of Cleveland, the National Center for Advancing Translational Sciences component of the National Institutes of Health and NIH roadmap for Medical Research, Michigan Institute for Clinical and Health Research, University of Illinois at Chicago, Tulane COBRE for Clinical and Translational Research in Cardiometabolic Diseases, Kaiser Permanente, and the University of New Mexico. Lead author Dr. Bundy was supported by the National Institutes of Health/Eunice Kennedy Shriver National Institute of Child Health and Human Development. The researchers had no financial conflicts to disclose. Dr. Deep had no financial conflicts to disclose.
This article was updated on 2/17/2021.
Chronic kidney disease (CKD) patients may be at increased risk for atherosclerotic cardiovascular disease, but no ASCVD risk prediction models are currently in place to inform clinical care and prevention strategies, Joshua Bundy, PhD, of Tulane University, New Orleans, and colleagues wrote in their paper, published in the Journal of the American Society of Nephrology.
To improve the accuracy of ASCVD risk prediction, the researchers developed several models using data from the Chronic Renal Insufficiency Cohort (CRIC) study. This longitudinal cohort study included more than 2,500 adult CKD patients. The participants’ ages ranged from 21-74 years, with the mean age having been 55.8 years, and 52.0% of the cohort was male.
Kidney function was defined using the glomerular filtration rate; the mean estimated glomerular filtration rate (eGFR) of the study participants was 56.0 mL/min per 1.73m2. The primary endpoint for the prediction models was incident ASCVD, defined as a composite of incident fatal or nonfatal stroke or MI.
A total of 252 incident ASCVD events occurred during the first 10 years of follow-up from baseline (1.9 events per 1,000 person-years). Patients with ASCVD events were more likely to be older, Black, and current smokers. They also were more likely than those who did not experience ASCVD events to have less than a college level education, to have a history of diabetes, and to use blood pressure–lowering medications.
“In our study, we created two new prediction tools for patients with CKD: the first is a simple model that includes factors routinely measured by health care providers and the second is an expanded model with additional variables particularly important to patients with CKD, including measures of long-term blood sugar, inflammation, and kidney and heart injury,” he explained. “We found that the new models are better able to classify patients who will or will not have a stroke or heart attack within 10 years, compared with the standard models. The new tools may better assist health care providers and patients with CKD in shared decision-making for prevention of heart disease.”
Results
The area under the curve for a prediction model using coefficients estimated within the CRIC sample was 0.736. This represented an accuracy higher than the American College of Cardiology/American Heart Association Pooled Cohort Equations (PCE), which have shown an AUC of 0.730 (P = .03). The PCE were developed by the ACC and the AHA in 2013 to estimate ASCVD risk in the primary prevention population.
The second CRIC model that was developed using clinically available variables had an AUC of 0.760. However, the third CRIC biomarker-enriched model was even more effective, with an AUC of 0.771 – significantly higher than the clinical model (P = .001).
Model 1 included the ACC/AHA PCE variables with coefficients recalculated in the CRIC study sample. Model 2 (the CRIC Clinical Model) included age, HDL cholesterol, systolic BP, current smoking, urinary albumin-to-creatinine ratio (ACR), hemoglobin A1c, and hemoglobin. Model 3 (the CRIC Enriched Model) included age, total cholesterol, HDL cholesterol, current smoking, urinary ACR, A1c, apolipoprotein B, high-sensitivity C-reactive protein (hsCRP), troponin T, and N-terminal of the prohormone brain natriuretic peptide (NT-proBNP).
Both the clinical and biomarker models improved reclassification of non-ASCVD events, compared with the PCEs (6.6% and 10.0%, respectively).
Several factors not included in prior prediction models were important for atherosclerotic CVD prediction among patients with CKD, the researchers noted. These included variables routinely measured in clinical practice as well as biomarkers: measures of long-term glycemia (A1c), inflammation (hsCRP), kidney injury (urinary ACR), and cardiac injury (troponin T and NT-proBNP).
Patients who had an ASCVD event had higher levels of A1c, systolic and diastolic BP, urinary ACR, troponin T, and NT-proBNP; these patients also had lower levels of HDL cholesterol, eGFR, and hemoglobin, compared with those who did not have an event.
The study findings were limited by several factors including the selection of study participants based on a single assessment of kidney function, who had an above average baseline ASCVD risk, the researchers noted. Other limitations included the inability to include imaging variables in the models, and the overestimated risk in the highest predicted probability groups in the CRIC study.
However, the models significantly improve prediction beyond the ACC/AHA PCE in patients with CKD, they concluded.
Models may inform shared decision-making
The development of new prediction models is important, because cardiovascular disease is the leading cause of death among U.S. adults and preventing CVD is a major public health challenge, lead author Dr. Bundy said in an interview.
“In an effort to prevent CVD, risk prediction equations can help identify patients who are at high risk for developing CVD and who may benefit from initiation or intensification of preventive and/or therapeutic measures. Simultaneously, chronic kidney disease is prevalent and those with CKD are often considered at high risk for CVD,” he said.
“However, common risk prediction tools were developed for the general population and may not work as well in patients with CKD, who may have different risk factors. Improving risk prediction in patients with CKD may help identify those among this growing population who are truly at high risk, as well as identify those who are at low risk and less likely to benefit from invasive procedures,” Dr. Bundy explained.
Glomerular filtration rate was not a strong predictor of atherosclerotic CVD
“One of the surprising findings was that estimated glomerular filtration rate was not a strong predictor and was not included in our final models,” Dr. Bundy said.
“We know that eGFR is a very important measurement in this population, but our results suggest that, at least in our sample, urinary albumin-to-creatinine ratio and cardiac biomarkers like troponin T and NT-proBNP are stronger predictors of atherosclerotic CVD in a population with reduced kidney function,” he said.
“Patient characteristics like age, blood pressure, and cholesterol are used by health care providers to predict whether a person will have a heart attack or stroke. However, most currently available prediction tools were not made for use in patients with CKD, which is a condition that is becoming more common and is likely to be seen by more health care providers in family practice,” said Dr. Bundy. “These people with CKD may have different risk factors for heart disease.”
Models are useful for clinical practice
“We are seeing rising numbers of patients with CKD in the population because of increasing age, rising rates of diabetes, and hypertension,” Noel Deep, MD, said in an interview. “The current practice of medicine does not have CKD-specific prediction models for ASCVD development, and current risks are calculated based on prediction models developed for the general population.”
“Having a prediction model that incorporates criteria/variables associated with CKD improves our ability to accurately identify and address the risk of ASCVD in this particular patient population,” said Dr. Deep, who is a general internist in a multispecialty group practice with Aspirus Antigo (Wisc.) Clinic and the chief medical officer and a staff physician at Aspirus Langlade Hospital, also in Antigo.
“We always knew that CKD does place the individual at higher risk for developing ASCVD, but I was impressed by the significant improvement in the prediction models using CKD specific tools, such as cardiac biomarkers (NT-proBNP), intensity of diabetes control (A1c), tobacco use, urinary albuminuria, in addition to advancing age,” he said. “Many of the laboratory tests listed in this study are commonly available and can be easily incorporated into our evaluation for and management of ASCVD in our patients with CKD.”
“As a practicing primary care physician, I would say that this study emphasizes the importance of identifying and working toward mitigating the associated health risks that our patients with CKD might have coexisting and that significantly contribute to progression of CKD,” said Dr. Deep, who is also assistant clinical professor at the Medical College of Wisconsin, Wausau. “By addressing these risk factors, we can positively impact the health of our patients with CKD and decrease the morbidity and mortality, and health care costs. These predictive models can hopefully help us more accurately identify the risk of ASCVD thereby decreasing unnecessary diagnostic procedures and interventions which carry their own risks and morbidity.”
Looking ahead, “these predictive models should be assessed and validated in large studies in diverse populations and those with different risk factors for ASCVD because CKD can be caused by several different medical conditions each with potential to contribute to ASCVD,” Dr. Deep added.
Limitations and next steps
“Although we externally validated our models in two population-based cohort studies, the individuals in these datasets were selected based on only one assessment of kidney function,” Dr. Bundy noted. “Furthermore, the best practices for implementing risk prediction models in the clinic remain to be determined, especially as new models are developed.
“While our models show promising performance for predicting 10-year risk of atherosclerotic CVD, more clinical trials are needed to test implementation of these models for improving patient care and disease prevention.”
The study was supported by the National Institute of Diabetes and Digestive and Kidney Diseases. Additional support came from the University of Pennsylvania Clinical and Translational Science Award, Johns Hopkins University, the University of Maryland, Clinical and Translational Science Collaborative of Cleveland, the National Center for Advancing Translational Sciences component of the National Institutes of Health and NIH roadmap for Medical Research, Michigan Institute for Clinical and Health Research, University of Illinois at Chicago, Tulane COBRE for Clinical and Translational Research in Cardiometabolic Diseases, Kaiser Permanente, and the University of New Mexico. Lead author Dr. Bundy was supported by the National Institutes of Health/Eunice Kennedy Shriver National Institute of Child Health and Human Development. The researchers had no financial conflicts to disclose. Dr. Deep had no financial conflicts to disclose.
This article was updated on 2/17/2021.
Chronic kidney disease (CKD) patients may be at increased risk for atherosclerotic cardiovascular disease, but no ASCVD risk prediction models are currently in place to inform clinical care and prevention strategies, Joshua Bundy, PhD, of Tulane University, New Orleans, and colleagues wrote in their paper, published in the Journal of the American Society of Nephrology.
To improve the accuracy of ASCVD risk prediction, the researchers developed several models using data from the Chronic Renal Insufficiency Cohort (CRIC) study. This longitudinal cohort study included more than 2,500 adult CKD patients. The participants’ ages ranged from 21-74 years, with the mean age having been 55.8 years, and 52.0% of the cohort was male.
Kidney function was defined using the glomerular filtration rate; the mean estimated glomerular filtration rate (eGFR) of the study participants was 56.0 mL/min per 1.73m2. The primary endpoint for the prediction models was incident ASCVD, defined as a composite of incident fatal or nonfatal stroke or MI.
A total of 252 incident ASCVD events occurred during the first 10 years of follow-up from baseline (1.9 events per 1,000 person-years). Patients with ASCVD events were more likely to be older, Black, and current smokers. They also were more likely than those who did not experience ASCVD events to have less than a college level education, to have a history of diabetes, and to use blood pressure–lowering medications.
“In our study, we created two new prediction tools for patients with CKD: the first is a simple model that includes factors routinely measured by health care providers and the second is an expanded model with additional variables particularly important to patients with CKD, including measures of long-term blood sugar, inflammation, and kidney and heart injury,” he explained. “We found that the new models are better able to classify patients who will or will not have a stroke or heart attack within 10 years, compared with the standard models. The new tools may better assist health care providers and patients with CKD in shared decision-making for prevention of heart disease.”
Results
The area under the curve for a prediction model using coefficients estimated within the CRIC sample was 0.736. This represented an accuracy higher than the American College of Cardiology/American Heart Association Pooled Cohort Equations (PCE), which have shown an AUC of 0.730 (P = .03). The PCE were developed by the ACC and the AHA in 2013 to estimate ASCVD risk in the primary prevention population.
The second CRIC model that was developed using clinically available variables had an AUC of 0.760. However, the third CRIC biomarker-enriched model was even more effective, with an AUC of 0.771 – significantly higher than the clinical model (P = .001).
Model 1 included the ACC/AHA PCE variables with coefficients recalculated in the CRIC study sample. Model 2 (the CRIC Clinical Model) included age, HDL cholesterol, systolic BP, current smoking, urinary albumin-to-creatinine ratio (ACR), hemoglobin A1c, and hemoglobin. Model 3 (the CRIC Enriched Model) included age, total cholesterol, HDL cholesterol, current smoking, urinary ACR, A1c, apolipoprotein B, high-sensitivity C-reactive protein (hsCRP), troponin T, and N-terminal of the prohormone brain natriuretic peptide (NT-proBNP).
Both the clinical and biomarker models improved reclassification of non-ASCVD events, compared with the PCEs (6.6% and 10.0%, respectively).
Several factors not included in prior prediction models were important for atherosclerotic CVD prediction among patients with CKD, the researchers noted. These included variables routinely measured in clinical practice as well as biomarkers: measures of long-term glycemia (A1c), inflammation (hsCRP), kidney injury (urinary ACR), and cardiac injury (troponin T and NT-proBNP).
Patients who had an ASCVD event had higher levels of A1c, systolic and diastolic BP, urinary ACR, troponin T, and NT-proBNP; these patients also had lower levels of HDL cholesterol, eGFR, and hemoglobin, compared with those who did not have an event.
The study findings were limited by several factors including the selection of study participants based on a single assessment of kidney function, who had an above average baseline ASCVD risk, the researchers noted. Other limitations included the inability to include imaging variables in the models, and the overestimated risk in the highest predicted probability groups in the CRIC study.
However, the models significantly improve prediction beyond the ACC/AHA PCE in patients with CKD, they concluded.
Models may inform shared decision-making
The development of new prediction models is important, because cardiovascular disease is the leading cause of death among U.S. adults and preventing CVD is a major public health challenge, lead author Dr. Bundy said in an interview.
“In an effort to prevent CVD, risk prediction equations can help identify patients who are at high risk for developing CVD and who may benefit from initiation or intensification of preventive and/or therapeutic measures. Simultaneously, chronic kidney disease is prevalent and those with CKD are often considered at high risk for CVD,” he said.
“However, common risk prediction tools were developed for the general population and may not work as well in patients with CKD, who may have different risk factors. Improving risk prediction in patients with CKD may help identify those among this growing population who are truly at high risk, as well as identify those who are at low risk and less likely to benefit from invasive procedures,” Dr. Bundy explained.
Glomerular filtration rate was not a strong predictor of atherosclerotic CVD
“One of the surprising findings was that estimated glomerular filtration rate was not a strong predictor and was not included in our final models,” Dr. Bundy said.
“We know that eGFR is a very important measurement in this population, but our results suggest that, at least in our sample, urinary albumin-to-creatinine ratio and cardiac biomarkers like troponin T and NT-proBNP are stronger predictors of atherosclerotic CVD in a population with reduced kidney function,” he said.
“Patient characteristics like age, blood pressure, and cholesterol are used by health care providers to predict whether a person will have a heart attack or stroke. However, most currently available prediction tools were not made for use in patients with CKD, which is a condition that is becoming more common and is likely to be seen by more health care providers in family practice,” said Dr. Bundy. “These people with CKD may have different risk factors for heart disease.”
Models are useful for clinical practice
“We are seeing rising numbers of patients with CKD in the population because of increasing age, rising rates of diabetes, and hypertension,” Noel Deep, MD, said in an interview. “The current practice of medicine does not have CKD-specific prediction models for ASCVD development, and current risks are calculated based on prediction models developed for the general population.”
“Having a prediction model that incorporates criteria/variables associated with CKD improves our ability to accurately identify and address the risk of ASCVD in this particular patient population,” said Dr. Deep, who is a general internist in a multispecialty group practice with Aspirus Antigo (Wisc.) Clinic and the chief medical officer and a staff physician at Aspirus Langlade Hospital, also in Antigo.
“We always knew that CKD does place the individual at higher risk for developing ASCVD, but I was impressed by the significant improvement in the prediction models using CKD specific tools, such as cardiac biomarkers (NT-proBNP), intensity of diabetes control (A1c), tobacco use, urinary albuminuria, in addition to advancing age,” he said. “Many of the laboratory tests listed in this study are commonly available and can be easily incorporated into our evaluation for and management of ASCVD in our patients with CKD.”
“As a practicing primary care physician, I would say that this study emphasizes the importance of identifying and working toward mitigating the associated health risks that our patients with CKD might have coexisting and that significantly contribute to progression of CKD,” said Dr. Deep, who is also assistant clinical professor at the Medical College of Wisconsin, Wausau. “By addressing these risk factors, we can positively impact the health of our patients with CKD and decrease the morbidity and mortality, and health care costs. These predictive models can hopefully help us more accurately identify the risk of ASCVD thereby decreasing unnecessary diagnostic procedures and interventions which carry their own risks and morbidity.”
Looking ahead, “these predictive models should be assessed and validated in large studies in diverse populations and those with different risk factors for ASCVD because CKD can be caused by several different medical conditions each with potential to contribute to ASCVD,” Dr. Deep added.
Limitations and next steps
“Although we externally validated our models in two population-based cohort studies, the individuals in these datasets were selected based on only one assessment of kidney function,” Dr. Bundy noted. “Furthermore, the best practices for implementing risk prediction models in the clinic remain to be determined, especially as new models are developed.
“While our models show promising performance for predicting 10-year risk of atherosclerotic CVD, more clinical trials are needed to test implementation of these models for improving patient care and disease prevention.”
The study was supported by the National Institute of Diabetes and Digestive and Kidney Diseases. Additional support came from the University of Pennsylvania Clinical and Translational Science Award, Johns Hopkins University, the University of Maryland, Clinical and Translational Science Collaborative of Cleveland, the National Center for Advancing Translational Sciences component of the National Institutes of Health and NIH roadmap for Medical Research, Michigan Institute for Clinical and Health Research, University of Illinois at Chicago, Tulane COBRE for Clinical and Translational Research in Cardiometabolic Diseases, Kaiser Permanente, and the University of New Mexico. Lead author Dr. Bundy was supported by the National Institutes of Health/Eunice Kennedy Shriver National Institute of Child Health and Human Development. The researchers had no financial conflicts to disclose. Dr. Deep had no financial conflicts to disclose.
This article was updated on 2/17/2021.
FROM THE JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY
Heavy cannabis use tied to less diabetes in women
Women who used marijuana (cannabis) at least four times in the previous month (heavy users) were less likely to have type 2 diabetes than women who were light users or nonusers, in a nationally representative U.S. observational study.
In contrast, there were no differences in the prevalence of type 2 diabetes in men who were light or heavy cannabis users versus nonusers.
These findings are based on data from the 2013-2018 National Health and Nutrition Examination Survey (NHANES), whereby participants self-reported their cannabis use.
The study by Ayobami S. Ogunsola, MD, MPH, a graduate student at Texas A&M University, College Station, and colleagues was recently published in Cannabis and Cannabinoid Research.
What do the findings mean?
Although overall findings linking cannabis use and diabetes have been inconsistent, the gender differences in the current study are consistent with animal studies and some clinical studies, senior author Ibraheem M. Karaye, MD, MPH, said in an interview.
However, these gender differences need to be confirmed, and “we strongly recommend that more biological or biochemical studies be conducted that could actually tell us the mechanisms,” said Dr. Karaye, an assistant professor in the department of population health, Hofstra University, Hempstead, N.Y.
“It’s indisputable that medical marijuana has some medical benefits,” he added. “Women [who use cannabis] have been shown to lose more weight than men, for example.”
“If women [cannabis users] are less likely to develop diabetes or more likely to express improvement of symptoms of diabetes,” he noted, “this means that hyperglycemic medications that are being prescribed should be watched scrupulously. Otherwise, there is a risk that [women] may overrespond.”
That is, Dr. Karaye continued, women “may be at risk of developing hypoglycemia because the cannabis is acting synergistically with the regular drug that is being used to treat the diabetes.”
U.S. clinicians, especially in states with legalized medical marijuana, need to be aware of the potential synergy.
“One would have to consider the patient as a whole,” he stressed. “For example, a woman that uses medical marijuana may actually respond differently to hyperglycemic medication.”
Conflicting reports explained by sex differences?
Evidence on whether cannabis use is linked with type 2 diabetes is limited and conflicting, the researchers wrote. They hypothesized that these conflicting findings might be explained by sex differences.
To “help inform current diabetes prevention and mitigation efforts,” they investigated sex differences in cannabis use and prevalence of type 2 diabetes in 15,602 men and women in the 2013-2014, 2015-2016, and 2017-2018 NHANES surveys.
Participants were classified as having type 2 diabetes if they had a physician’s diagnosis; a 2-hour plasma glucose of at least 200 mg/dL (in a glucose tolerance test); fasting blood glucose of at least 126 mg/dL; or A1c of at least 6.5%.
About half of respondents were women (52%) and close to half (44%) were age 18-39.
More than a third (38%) had a body mass index (BMI) of at least 30 kg/m2, indicating obesity.
Roughly 1 in 10 had a diagnosis of type 2 diabetes (13.5%) or A1c of at least 6.5% (9.8%).
Close to a fifth smoked cigarettes (16%). Similarly, 14.5% used cannabis at least four times a week, 3.3% used it less often, and the rest did not use it. Half of participants were not physically active (49%).
Just over half had at least a college education (55%).
Heavy cannabis users were more likely to be younger than age 40 (57% of men, 57% of women), college graduates (54% of men, 63% of women), cigarette smokers (79% of men, 83% of women), and physically inactive (39% of men, 49% of women).
Among women, heavy cannabis users were 49% less likely to have type 2 diabetes than nonusers, after adjusting for age, sex, race/ethnicity, educational level, physical activity, tobacco use, alcohol use, marital status, difficulty walking, employment status, income, and BMI (adjusted odds ratio, 0.51; 95% confidence interval, 0.31-0.84).
There were no significant differences between light cannabis users versus nonusers and diabetes prevalence in women, or between light or heavy cannabis users versus nonusers and diabetes prevalence in men.
Limitations, yet biologically plausible
The researchers acknowledged several study limitations.
They do not know how long participants had used marijuana. The men and women may have underreported their cannabis use, especially in states where medical marijuana was not legal, and the NHANES data did not specify whether the cannabis was recreational or medicinal.
The study may have been underpowered to detect a smaller difference in men who used versus did not use marijuana.
And importantly, this was an observational study (a snapshot at one point in time), so it cannot say whether the heavy cannabis use in women caused a decreased likelihood of diabetes.
Nevertheless, the inverse association between cannabis use and presence of type 2 diabetes is biologically plausible, Dr. Ogunsola and colleagues wrote.
The two major cannabis compounds, cannabidiol and delta-9-tetrahydrocannabinol, stimulate CBD1 and CBD2 receptors in the central and peripheral nervous systems, respectively. And “activation of the CBD1 receptor increases insulin secretion, glucagon, and somatostatin, and activates metabolic processes in fat and skeletal muscles – mechanisms that improve glucose disposal,” they explained.
The researchers speculated that the sex differences they found for this association may be caused by differences in sex hormones, or the endocannabinoid system, or fat deposits.
Therefore, “additional studies are needed to investigate the sex-based heterogeneity reported in this study and to elucidate potential mechanisms for the observation,” they concluded.
The study did not receive any funding and the researchers have no relevant financial disclosures.
A version of this article first appeared on Medscape.com.
Women who used marijuana (cannabis) at least four times in the previous month (heavy users) were less likely to have type 2 diabetes than women who were light users or nonusers, in a nationally representative U.S. observational study.
In contrast, there were no differences in the prevalence of type 2 diabetes in men who were light or heavy cannabis users versus nonusers.
These findings are based on data from the 2013-2018 National Health and Nutrition Examination Survey (NHANES), whereby participants self-reported their cannabis use.
The study by Ayobami S. Ogunsola, MD, MPH, a graduate student at Texas A&M University, College Station, and colleagues was recently published in Cannabis and Cannabinoid Research.
What do the findings mean?
Although overall findings linking cannabis use and diabetes have been inconsistent, the gender differences in the current study are consistent with animal studies and some clinical studies, senior author Ibraheem M. Karaye, MD, MPH, said in an interview.
However, these gender differences need to be confirmed, and “we strongly recommend that more biological or biochemical studies be conducted that could actually tell us the mechanisms,” said Dr. Karaye, an assistant professor in the department of population health, Hofstra University, Hempstead, N.Y.
“It’s indisputable that medical marijuana has some medical benefits,” he added. “Women [who use cannabis] have been shown to lose more weight than men, for example.”
“If women [cannabis users] are less likely to develop diabetes or more likely to express improvement of symptoms of diabetes,” he noted, “this means that hyperglycemic medications that are being prescribed should be watched scrupulously. Otherwise, there is a risk that [women] may overrespond.”
That is, Dr. Karaye continued, women “may be at risk of developing hypoglycemia because the cannabis is acting synergistically with the regular drug that is being used to treat the diabetes.”
U.S. clinicians, especially in states with legalized medical marijuana, need to be aware of the potential synergy.
“One would have to consider the patient as a whole,” he stressed. “For example, a woman that uses medical marijuana may actually respond differently to hyperglycemic medication.”
Conflicting reports explained by sex differences?
Evidence on whether cannabis use is linked with type 2 diabetes is limited and conflicting, the researchers wrote. They hypothesized that these conflicting findings might be explained by sex differences.
To “help inform current diabetes prevention and mitigation efforts,” they investigated sex differences in cannabis use and prevalence of type 2 diabetes in 15,602 men and women in the 2013-2014, 2015-2016, and 2017-2018 NHANES surveys.
Participants were classified as having type 2 diabetes if they had a physician’s diagnosis; a 2-hour plasma glucose of at least 200 mg/dL (in a glucose tolerance test); fasting blood glucose of at least 126 mg/dL; or A1c of at least 6.5%.
About half of respondents were women (52%) and close to half (44%) were age 18-39.
More than a third (38%) had a body mass index (BMI) of at least 30 kg/m2, indicating obesity.
Roughly 1 in 10 had a diagnosis of type 2 diabetes (13.5%) or A1c of at least 6.5% (9.8%).
Close to a fifth smoked cigarettes (16%). Similarly, 14.5% used cannabis at least four times a week, 3.3% used it less often, and the rest did not use it. Half of participants were not physically active (49%).
Just over half had at least a college education (55%).
Heavy cannabis users were more likely to be younger than age 40 (57% of men, 57% of women), college graduates (54% of men, 63% of women), cigarette smokers (79% of men, 83% of women), and physically inactive (39% of men, 49% of women).
Among women, heavy cannabis users were 49% less likely to have type 2 diabetes than nonusers, after adjusting for age, sex, race/ethnicity, educational level, physical activity, tobacco use, alcohol use, marital status, difficulty walking, employment status, income, and BMI (adjusted odds ratio, 0.51; 95% confidence interval, 0.31-0.84).
There were no significant differences between light cannabis users versus nonusers and diabetes prevalence in women, or between light or heavy cannabis users versus nonusers and diabetes prevalence in men.
Limitations, yet biologically plausible
The researchers acknowledged several study limitations.
They do not know how long participants had used marijuana. The men and women may have underreported their cannabis use, especially in states where medical marijuana was not legal, and the NHANES data did not specify whether the cannabis was recreational or medicinal.
The study may have been underpowered to detect a smaller difference in men who used versus did not use marijuana.
And importantly, this was an observational study (a snapshot at one point in time), so it cannot say whether the heavy cannabis use in women caused a decreased likelihood of diabetes.
Nevertheless, the inverse association between cannabis use and presence of type 2 diabetes is biologically plausible, Dr. Ogunsola and colleagues wrote.
The two major cannabis compounds, cannabidiol and delta-9-tetrahydrocannabinol, stimulate CBD1 and CBD2 receptors in the central and peripheral nervous systems, respectively. And “activation of the CBD1 receptor increases insulin secretion, glucagon, and somatostatin, and activates metabolic processes in fat and skeletal muscles – mechanisms that improve glucose disposal,” they explained.
The researchers speculated that the sex differences they found for this association may be caused by differences in sex hormones, or the endocannabinoid system, or fat deposits.
Therefore, “additional studies are needed to investigate the sex-based heterogeneity reported in this study and to elucidate potential mechanisms for the observation,” they concluded.
The study did not receive any funding and the researchers have no relevant financial disclosures.
A version of this article first appeared on Medscape.com.
Women who used marijuana (cannabis) at least four times in the previous month (heavy users) were less likely to have type 2 diabetes than women who were light users or nonusers, in a nationally representative U.S. observational study.
In contrast, there were no differences in the prevalence of type 2 diabetes in men who were light or heavy cannabis users versus nonusers.
These findings are based on data from the 2013-2018 National Health and Nutrition Examination Survey (NHANES), whereby participants self-reported their cannabis use.
The study by Ayobami S. Ogunsola, MD, MPH, a graduate student at Texas A&M University, College Station, and colleagues was recently published in Cannabis and Cannabinoid Research.
What do the findings mean?
Although overall findings linking cannabis use and diabetes have been inconsistent, the gender differences in the current study are consistent with animal studies and some clinical studies, senior author Ibraheem M. Karaye, MD, MPH, said in an interview.
However, these gender differences need to be confirmed, and “we strongly recommend that more biological or biochemical studies be conducted that could actually tell us the mechanisms,” said Dr. Karaye, an assistant professor in the department of population health, Hofstra University, Hempstead, N.Y.
“It’s indisputable that medical marijuana has some medical benefits,” he added. “Women [who use cannabis] have been shown to lose more weight than men, for example.”
“If women [cannabis users] are less likely to develop diabetes or more likely to express improvement of symptoms of diabetes,” he noted, “this means that hyperglycemic medications that are being prescribed should be watched scrupulously. Otherwise, there is a risk that [women] may overrespond.”
That is, Dr. Karaye continued, women “may be at risk of developing hypoglycemia because the cannabis is acting synergistically with the regular drug that is being used to treat the diabetes.”
U.S. clinicians, especially in states with legalized medical marijuana, need to be aware of the potential synergy.
“One would have to consider the patient as a whole,” he stressed. “For example, a woman that uses medical marijuana may actually respond differently to hyperglycemic medication.”
Conflicting reports explained by sex differences?
Evidence on whether cannabis use is linked with type 2 diabetes is limited and conflicting, the researchers wrote. They hypothesized that these conflicting findings might be explained by sex differences.
To “help inform current diabetes prevention and mitigation efforts,” they investigated sex differences in cannabis use and prevalence of type 2 diabetes in 15,602 men and women in the 2013-2014, 2015-2016, and 2017-2018 NHANES surveys.
Participants were classified as having type 2 diabetes if they had a physician’s diagnosis; a 2-hour plasma glucose of at least 200 mg/dL (in a glucose tolerance test); fasting blood glucose of at least 126 mg/dL; or A1c of at least 6.5%.
About half of respondents were women (52%) and close to half (44%) were age 18-39.
More than a third (38%) had a body mass index (BMI) of at least 30 kg/m2, indicating obesity.
Roughly 1 in 10 had a diagnosis of type 2 diabetes (13.5%) or A1c of at least 6.5% (9.8%).
Close to a fifth smoked cigarettes (16%). Similarly, 14.5% used cannabis at least four times a week, 3.3% used it less often, and the rest did not use it. Half of participants were not physically active (49%).
Just over half had at least a college education (55%).
Heavy cannabis users were more likely to be younger than age 40 (57% of men, 57% of women), college graduates (54% of men, 63% of women), cigarette smokers (79% of men, 83% of women), and physically inactive (39% of men, 49% of women).
Among women, heavy cannabis users were 49% less likely to have type 2 diabetes than nonusers, after adjusting for age, sex, race/ethnicity, educational level, physical activity, tobacco use, alcohol use, marital status, difficulty walking, employment status, income, and BMI (adjusted odds ratio, 0.51; 95% confidence interval, 0.31-0.84).
There were no significant differences between light cannabis users versus nonusers and diabetes prevalence in women, or between light or heavy cannabis users versus nonusers and diabetes prevalence in men.
Limitations, yet biologically plausible
The researchers acknowledged several study limitations.
They do not know how long participants had used marijuana. The men and women may have underreported their cannabis use, especially in states where medical marijuana was not legal, and the NHANES data did not specify whether the cannabis was recreational or medicinal.
The study may have been underpowered to detect a smaller difference in men who used versus did not use marijuana.
And importantly, this was an observational study (a snapshot at one point in time), so it cannot say whether the heavy cannabis use in women caused a decreased likelihood of diabetes.
Nevertheless, the inverse association between cannabis use and presence of type 2 diabetes is biologically plausible, Dr. Ogunsola and colleagues wrote.
The two major cannabis compounds, cannabidiol and delta-9-tetrahydrocannabinol, stimulate CBD1 and CBD2 receptors in the central and peripheral nervous systems, respectively. And “activation of the CBD1 receptor increases insulin secretion, glucagon, and somatostatin, and activates metabolic processes in fat and skeletal muscles – mechanisms that improve glucose disposal,” they explained.
The researchers speculated that the sex differences they found for this association may be caused by differences in sex hormones, or the endocannabinoid system, or fat deposits.
Therefore, “additional studies are needed to investigate the sex-based heterogeneity reported in this study and to elucidate potential mechanisms for the observation,” they concluded.
The study did not receive any funding and the researchers have no relevant financial disclosures.
A version of this article first appeared on Medscape.com.
FROM CANNABIS AND CANNABINOID RESEARCH
Limited benefits of early gestational diabetes screening
Screening pregnant women with obesity for gestational diabetes before 20 weeks of pregnancy did not lead to any improved maternal or neonatal outcomes compared with doing routine screening between 24 and 28 weeks, according to research presented Feb. 4 at the Pregnancy Meeting sponsored by the Society for Maternal-Fetal Medicine.
“There is increasing evidence that early screening does not reduce the risk of adverse perinatal outcomes,” Jennifer Thompson, MD, associate professor of ob.gyn. at Vanderbilt University, Nashville, Tenn., said in an interview. “The increasing number of studies that have demonstrated no benefit in reducing adverse perinatal outcomes leads to consideration to revise recommendations for early screening.”
However, she did note that early screening may be helpful in identifying patients with undiagnosed preexisting diabetes.
Michael Richley, MD, a maternal-fetal medicine fellow at the University of California, Los Angeles, said catching those previously undiagnosed cases is one of the goals of earlier screening with the expectation that earlier management will lead to better outcomes.
“If a patient then obtains the diagnosis of type 2 diabetes, introducing nutritional counseling and possible medical management early can lead to better outcomes,” said Dr. Richley, who attended the presentation but was not involved in the research. ”While catching undiagnosed type 2 diabetes is not common, it is becoming increasingly common lately.”
Obesity is a known risk factor for impaired glucose metabolism and for gestational diabetes, explained presenter Christopher A. Enakpene, MD, an ob.gyn. from Midland, Tex., who completed the study while completing his maternal-fetal medicine fellowship at the University of Illinois in Chicago. Dr. Enakpene reminded attendees that the American College of Obstetricians and Gynecologists (ACOG) currently recommends early screening for gestational diabetes in patients with certain risk factors, including obesity, a history of first-degree relatives with diabetes, or a history of gestational diabetes, impaired glucose tolerance, poor pregnancy outcomes, fetal demise, congenital abnormalities, or birth of an infant large for gestational age.
The researchers screened 7,126 patients for enrollment in the study from March 2017 through February 2019 and identified 600 who met the criteria: An adult with a singleton pregnancy and body mass index (BMI) of at least 30 kg/m2. Patients were excluded if they had preexisting diabetes, elevated blood glucose or impaired glucose tolerance, a history of gestational diabetes, any chromosomal anomalies or abnormalities in the pregnancy, or were past 20 weeks of pregnancy.
The prospective randomized controlled trial was open label and included 296 patients who were randomly assigned to early screening with a 1-hour glucose challenge test (GCT) and hemoglobin A1c before 20 weeks, followed by a 3-hour oral glucose tolerance test if the GCT result was between 140 and 200 mg/dL with an HbA1c of less than 6.5%. The other 304 patients were screened with a 1-hour GCT between 24 and 28 weeks but also had an HbA1c test before 20 weeks.
The primary outcome was macrosomia, defined as a birth weight at least 4,000 g, with various maternal and neonatal secondary outcomes. The only significant difference between the groups at baseline was a higher proportion of Hispanic participants in the early screening group (22.4%) compared to the routine screening group (13.7%).
The groups had no significant differences in birth weight or macrosomia, which occurred in 2.8% of the early screening group and 3.4% of the routine screening group (P = .7). There were no significant differences in gestational age at delivery, preeclampsia, polyhydramnios, shoulder dystocia, cesarean delivery, or NICU admission. However, the rate of gestational diabetes was significantly higher in the early screening group (22.5%) than in the routine screening group (15.7%; P < .05). In addition, more participants with gestational diabetes in the early screening group used insulin (34.4%) compared with those in the routine screening group (15.6%; P < .05).
Dr. Enakpene noted several reasons that the perinatal outcomes may have been similar between the groups, such as the increased rate of gestational diabetes requiring treatment in the early screening group or a higher proportion of participants using insulin in the early screening group.
“Hence, the similarity in adverse perinatal outcomes between the groups despite a higher proportion of gestational diabetes in the early group might be due to more utilization of insulin,” Dr. Enakpene said.
Dr. Richley was not surprised by the findings and hypothesized that the reason for not seeing a difference in outcomes might relate to using a 20-week cutoff for testing when type 2 diabetes would be evident at any stage of pregnancy.
“It would be interesting to have a study look at diabetes testing exclusively in the first trimester for high-risk patients that looks at neonatal outcomes and see if that would show a difference between the two groups,” Dr. Richley said.
Dr. Thompson was similarly interested in whether 20 weeks was an early enough time for early screening.
”I would also like to know the differences in management between the two groups and if the knowledge of early diagnosis impacted their management, such as timing of medication start, amount of medication required, and how that differed from the standard group,” Dr. Thompson said. ”Since patients with a hemoglobin A1c > 6.5% or glucose tolerance test > 200 [mg/dL] were excluded, I’m interested in the number of patients that were excluded since they likely have undiagnosed preexisting diabetes, which are the patients that may benefit most from early screening.”
Dr. Richley pointed out that the potential clinical implications of the study are limited right now.
“While their secondary outcomes of neonatal hypoglycemia, method of delivery, and other common obstetrical measures were not different, we cannot draw conclusions from this as the study was not powered to evaluate these findings,” Dr. Richley said. “I do still see a role in early screening for patients with risk factors but favor doing so at the first prenatal visit, whenever that is, as opposed to as late as mid-second trimester, though this is often when a patient’s first interaction with a health care system will be within their pregnancy.”
Dr. Enakpene, Dr. Thompson, and Dr. Richley reported no disclosures. External funding for the study was not noted.
Screening pregnant women with obesity for gestational diabetes before 20 weeks of pregnancy did not lead to any improved maternal or neonatal outcomes compared with doing routine screening between 24 and 28 weeks, according to research presented Feb. 4 at the Pregnancy Meeting sponsored by the Society for Maternal-Fetal Medicine.
“There is increasing evidence that early screening does not reduce the risk of adverse perinatal outcomes,” Jennifer Thompson, MD, associate professor of ob.gyn. at Vanderbilt University, Nashville, Tenn., said in an interview. “The increasing number of studies that have demonstrated no benefit in reducing adverse perinatal outcomes leads to consideration to revise recommendations for early screening.”
However, she did note that early screening may be helpful in identifying patients with undiagnosed preexisting diabetes.
Michael Richley, MD, a maternal-fetal medicine fellow at the University of California, Los Angeles, said catching those previously undiagnosed cases is one of the goals of earlier screening with the expectation that earlier management will lead to better outcomes.
“If a patient then obtains the diagnosis of type 2 diabetes, introducing nutritional counseling and possible medical management early can lead to better outcomes,” said Dr. Richley, who attended the presentation but was not involved in the research. ”While catching undiagnosed type 2 diabetes is not common, it is becoming increasingly common lately.”
Obesity is a known risk factor for impaired glucose metabolism and for gestational diabetes, explained presenter Christopher A. Enakpene, MD, an ob.gyn. from Midland, Tex., who completed the study while completing his maternal-fetal medicine fellowship at the University of Illinois in Chicago. Dr. Enakpene reminded attendees that the American College of Obstetricians and Gynecologists (ACOG) currently recommends early screening for gestational diabetes in patients with certain risk factors, including obesity, a history of first-degree relatives with diabetes, or a history of gestational diabetes, impaired glucose tolerance, poor pregnancy outcomes, fetal demise, congenital abnormalities, or birth of an infant large for gestational age.
The researchers screened 7,126 patients for enrollment in the study from March 2017 through February 2019 and identified 600 who met the criteria: An adult with a singleton pregnancy and body mass index (BMI) of at least 30 kg/m2. Patients were excluded if they had preexisting diabetes, elevated blood glucose or impaired glucose tolerance, a history of gestational diabetes, any chromosomal anomalies or abnormalities in the pregnancy, or were past 20 weeks of pregnancy.
The prospective randomized controlled trial was open label and included 296 patients who were randomly assigned to early screening with a 1-hour glucose challenge test (GCT) and hemoglobin A1c before 20 weeks, followed by a 3-hour oral glucose tolerance test if the GCT result was between 140 and 200 mg/dL with an HbA1c of less than 6.5%. The other 304 patients were screened with a 1-hour GCT between 24 and 28 weeks but also had an HbA1c test before 20 weeks.
The primary outcome was macrosomia, defined as a birth weight at least 4,000 g, with various maternal and neonatal secondary outcomes. The only significant difference between the groups at baseline was a higher proportion of Hispanic participants in the early screening group (22.4%) compared to the routine screening group (13.7%).
The groups had no significant differences in birth weight or macrosomia, which occurred in 2.8% of the early screening group and 3.4% of the routine screening group (P = .7). There were no significant differences in gestational age at delivery, preeclampsia, polyhydramnios, shoulder dystocia, cesarean delivery, or NICU admission. However, the rate of gestational diabetes was significantly higher in the early screening group (22.5%) than in the routine screening group (15.7%; P < .05). In addition, more participants with gestational diabetes in the early screening group used insulin (34.4%) compared with those in the routine screening group (15.6%; P < .05).
Dr. Enakpene noted several reasons that the perinatal outcomes may have been similar between the groups, such as the increased rate of gestational diabetes requiring treatment in the early screening group or a higher proportion of participants using insulin in the early screening group.
“Hence, the similarity in adverse perinatal outcomes between the groups despite a higher proportion of gestational diabetes in the early group might be due to more utilization of insulin,” Dr. Enakpene said.
Dr. Richley was not surprised by the findings and hypothesized that the reason for not seeing a difference in outcomes might relate to using a 20-week cutoff for testing when type 2 diabetes would be evident at any stage of pregnancy.
“It would be interesting to have a study look at diabetes testing exclusively in the first trimester for high-risk patients that looks at neonatal outcomes and see if that would show a difference between the two groups,” Dr. Richley said.
Dr. Thompson was similarly interested in whether 20 weeks was an early enough time for early screening.
”I would also like to know the differences in management between the two groups and if the knowledge of early diagnosis impacted their management, such as timing of medication start, amount of medication required, and how that differed from the standard group,” Dr. Thompson said. ”Since patients with a hemoglobin A1c > 6.5% or glucose tolerance test > 200 [mg/dL] were excluded, I’m interested in the number of patients that were excluded since they likely have undiagnosed preexisting diabetes, which are the patients that may benefit most from early screening.”
Dr. Richley pointed out that the potential clinical implications of the study are limited right now.
“While their secondary outcomes of neonatal hypoglycemia, method of delivery, and other common obstetrical measures were not different, we cannot draw conclusions from this as the study was not powered to evaluate these findings,” Dr. Richley said. “I do still see a role in early screening for patients with risk factors but favor doing so at the first prenatal visit, whenever that is, as opposed to as late as mid-second trimester, though this is often when a patient’s first interaction with a health care system will be within their pregnancy.”
Dr. Enakpene, Dr. Thompson, and Dr. Richley reported no disclosures. External funding for the study was not noted.
Screening pregnant women with obesity for gestational diabetes before 20 weeks of pregnancy did not lead to any improved maternal or neonatal outcomes compared with doing routine screening between 24 and 28 weeks, according to research presented Feb. 4 at the Pregnancy Meeting sponsored by the Society for Maternal-Fetal Medicine.
“There is increasing evidence that early screening does not reduce the risk of adverse perinatal outcomes,” Jennifer Thompson, MD, associate professor of ob.gyn. at Vanderbilt University, Nashville, Tenn., said in an interview. “The increasing number of studies that have demonstrated no benefit in reducing adverse perinatal outcomes leads to consideration to revise recommendations for early screening.”
However, she did note that early screening may be helpful in identifying patients with undiagnosed preexisting diabetes.
Michael Richley, MD, a maternal-fetal medicine fellow at the University of California, Los Angeles, said catching those previously undiagnosed cases is one of the goals of earlier screening with the expectation that earlier management will lead to better outcomes.
“If a patient then obtains the diagnosis of type 2 diabetes, introducing nutritional counseling and possible medical management early can lead to better outcomes,” said Dr. Richley, who attended the presentation but was not involved in the research. ”While catching undiagnosed type 2 diabetes is not common, it is becoming increasingly common lately.”
Obesity is a known risk factor for impaired glucose metabolism and for gestational diabetes, explained presenter Christopher A. Enakpene, MD, an ob.gyn. from Midland, Tex., who completed the study while completing his maternal-fetal medicine fellowship at the University of Illinois in Chicago. Dr. Enakpene reminded attendees that the American College of Obstetricians and Gynecologists (ACOG) currently recommends early screening for gestational diabetes in patients with certain risk factors, including obesity, a history of first-degree relatives with diabetes, or a history of gestational diabetes, impaired glucose tolerance, poor pregnancy outcomes, fetal demise, congenital abnormalities, or birth of an infant large for gestational age.
The researchers screened 7,126 patients for enrollment in the study from March 2017 through February 2019 and identified 600 who met the criteria: An adult with a singleton pregnancy and body mass index (BMI) of at least 30 kg/m2. Patients were excluded if they had preexisting diabetes, elevated blood glucose or impaired glucose tolerance, a history of gestational diabetes, any chromosomal anomalies or abnormalities in the pregnancy, or were past 20 weeks of pregnancy.
The prospective randomized controlled trial was open label and included 296 patients who were randomly assigned to early screening with a 1-hour glucose challenge test (GCT) and hemoglobin A1c before 20 weeks, followed by a 3-hour oral glucose tolerance test if the GCT result was between 140 and 200 mg/dL with an HbA1c of less than 6.5%. The other 304 patients were screened with a 1-hour GCT between 24 and 28 weeks but also had an HbA1c test before 20 weeks.
The primary outcome was macrosomia, defined as a birth weight at least 4,000 g, with various maternal and neonatal secondary outcomes. The only significant difference between the groups at baseline was a higher proportion of Hispanic participants in the early screening group (22.4%) compared to the routine screening group (13.7%).
The groups had no significant differences in birth weight or macrosomia, which occurred in 2.8% of the early screening group and 3.4% of the routine screening group (P = .7). There were no significant differences in gestational age at delivery, preeclampsia, polyhydramnios, shoulder dystocia, cesarean delivery, or NICU admission. However, the rate of gestational diabetes was significantly higher in the early screening group (22.5%) than in the routine screening group (15.7%; P < .05). In addition, more participants with gestational diabetes in the early screening group used insulin (34.4%) compared with those in the routine screening group (15.6%; P < .05).
Dr. Enakpene noted several reasons that the perinatal outcomes may have been similar between the groups, such as the increased rate of gestational diabetes requiring treatment in the early screening group or a higher proportion of participants using insulin in the early screening group.
“Hence, the similarity in adverse perinatal outcomes between the groups despite a higher proportion of gestational diabetes in the early group might be due to more utilization of insulin,” Dr. Enakpene said.
Dr. Richley was not surprised by the findings and hypothesized that the reason for not seeing a difference in outcomes might relate to using a 20-week cutoff for testing when type 2 diabetes would be evident at any stage of pregnancy.
“It would be interesting to have a study look at diabetes testing exclusively in the first trimester for high-risk patients that looks at neonatal outcomes and see if that would show a difference between the two groups,” Dr. Richley said.
Dr. Thompson was similarly interested in whether 20 weeks was an early enough time for early screening.
”I would also like to know the differences in management between the two groups and if the knowledge of early diagnosis impacted their management, such as timing of medication start, amount of medication required, and how that differed from the standard group,” Dr. Thompson said. ”Since patients with a hemoglobin A1c > 6.5% or glucose tolerance test > 200 [mg/dL] were excluded, I’m interested in the number of patients that were excluded since they likely have undiagnosed preexisting diabetes, which are the patients that may benefit most from early screening.”
Dr. Richley pointed out that the potential clinical implications of the study are limited right now.
“While their secondary outcomes of neonatal hypoglycemia, method of delivery, and other common obstetrical measures were not different, we cannot draw conclusions from this as the study was not powered to evaluate these findings,” Dr. Richley said. “I do still see a role in early screening for patients with risk factors but favor doing so at the first prenatal visit, whenever that is, as opposed to as late as mid-second trimester, though this is often when a patient’s first interaction with a health care system will be within their pregnancy.”
Dr. Enakpene, Dr. Thompson, and Dr. Richley reported no disclosures. External funding for the study was not noted.
FROM THE PREGNANCY MEETING
Eating dinner late ups diabetes risk; melatonin involved
which increase the risk of type 2 diabetes.
And people who are carriers of the G allele of the MTNR1B gene have greater impairment in glucose tolerance after eating a late dinner.
“In natural late eaters [in Spain], we simulated early and late dinner timing by administering a glucose drink and compared effects on blood sugar control over 2 hours,” said senior author Richa Saxena, PhD, a principal investigator at the Center for Genomic Medicine at Massachusetts General Hospital, Boston.
The study also compared outcomes in carriers and noncarriers of the G allele variant of the melatonin receptor gene, Dr. Saxena pointed out in a press release from the hospital.
“We found that late eating disturbed blood sugar control in the whole group,” added lead author Marta Garaulet, PhD.
“This impaired glucose control was predominantly seen in genetic risk variant carriers, representing about half of the cohort,” said Dr. Garaulet, professor of physiology and nutrition, University of Murcia (Spain).
The study results “may be important in the effort toward prevention of type 2 diabetes,” according to co–senior author Frank A.J.L. Scheer, PhD.
“Our findings are applicable to about a third of the population in the industrialized world who consume food close to bedtime, as well as other populations who eat at night, including shift workers, or those experiencing jet lag or night-eating disorders, as well as those who routinely use melatonin supplements close to food intake,” said Dr. Scheer, director of the medical chronobiology program at Brigham and Women’s Hospital, Boston.
The results suggest people should not eat within 2 hours of bedtime, said the researchers.
“Notably, our study does not include patients with diabetes, so additional studies are needed to examine the impact of food timing and its link with melatonin and receptor variation in patients with diabetes,” Dr. Scheer said.
The findings, from the MTNR1B SNP*Food Timing Interaction on Glucose Control (ONTIME-MT) randomized crossover study, were recently published in Diabetes Care.
Melatonin plays a key role in glucose metabolism
Melatonin, a hormone primarily released at night that helps control the sleep-wake cycle, typically rises around 2 hours before bedtime, the researchers explained.
The discovery of MTNR1B as a type 2 diabetes–associated gene “suggests that, beyond sleep and circadian regulation, melatonin plays a key role in glucose metabolism,” they noted. However, whether melatonin improves or impairs glucose control is controversial, and the effect of MTNR1B genotypes on glucose control is not clear.
“We decided to test if late eating that usually occurs with elevated melatonin levels results in disturbed blood sugar control,” Dr. Saxena explained.
To investigate this, researchers enrolled 845 adults in Spain who were 18-70 years old and did not have diabetes. Participants were a mean age of 38 years and 71% were women. They had a mean body mass index of 25.7 kg/m2 and 18% had obesity.
On average, they typically ate dinner at 21:38 (9:38 p.m.) and went to bed at 24:32 (12:32 a.m.).
DNA analysis from participants’ blood samples determined that 50% had the CC genotype of the MTNR1B gene, 40% had the CG genotype, and 10% had the GG genotype.
Each participant underwent two oral glucose tolerance tests. They fasted for 8 hours and then had a 2-hour 75-g oral glucose tolerance test either 1 hour before bedtime (simulating a late dinner) or 4 hours before bedtime (simulating an early dinner). Then they repeated the test at the opposite dinner time on another night.
The average serum melatonin values were 3.5-fold higher after the late dinner than after the early dinner, resulting in 6.7% lower insulin area under the curve and 8.3% higher glucose AUC.
Genotype differences in glucose tolerance were attributed to reductions in beta-cell function.
“Our results confirm that late eating acutely impairs glucose tolerance through a defect in insulin secretion,” the researchers reiterated.
ONTIME-MT was funded by the National Institutes of Health; the Spanish Government of Investigation, Development, and Innovation; and the Seneca Foundation. The researchers reported no relevant financial disclosures.
A version of this article first appeared on Medscape.com.
which increase the risk of type 2 diabetes.
And people who are carriers of the G allele of the MTNR1B gene have greater impairment in glucose tolerance after eating a late dinner.
“In natural late eaters [in Spain], we simulated early and late dinner timing by administering a glucose drink and compared effects on blood sugar control over 2 hours,” said senior author Richa Saxena, PhD, a principal investigator at the Center for Genomic Medicine at Massachusetts General Hospital, Boston.
The study also compared outcomes in carriers and noncarriers of the G allele variant of the melatonin receptor gene, Dr. Saxena pointed out in a press release from the hospital.
“We found that late eating disturbed blood sugar control in the whole group,” added lead author Marta Garaulet, PhD.
“This impaired glucose control was predominantly seen in genetic risk variant carriers, representing about half of the cohort,” said Dr. Garaulet, professor of physiology and nutrition, University of Murcia (Spain).
The study results “may be important in the effort toward prevention of type 2 diabetes,” according to co–senior author Frank A.J.L. Scheer, PhD.
“Our findings are applicable to about a third of the population in the industrialized world who consume food close to bedtime, as well as other populations who eat at night, including shift workers, or those experiencing jet lag or night-eating disorders, as well as those who routinely use melatonin supplements close to food intake,” said Dr. Scheer, director of the medical chronobiology program at Brigham and Women’s Hospital, Boston.
The results suggest people should not eat within 2 hours of bedtime, said the researchers.
“Notably, our study does not include patients with diabetes, so additional studies are needed to examine the impact of food timing and its link with melatonin and receptor variation in patients with diabetes,” Dr. Scheer said.
The findings, from the MTNR1B SNP*Food Timing Interaction on Glucose Control (ONTIME-MT) randomized crossover study, were recently published in Diabetes Care.
Melatonin plays a key role in glucose metabolism
Melatonin, a hormone primarily released at night that helps control the sleep-wake cycle, typically rises around 2 hours before bedtime, the researchers explained.
The discovery of MTNR1B as a type 2 diabetes–associated gene “suggests that, beyond sleep and circadian regulation, melatonin plays a key role in glucose metabolism,” they noted. However, whether melatonin improves or impairs glucose control is controversial, and the effect of MTNR1B genotypes on glucose control is not clear.
“We decided to test if late eating that usually occurs with elevated melatonin levels results in disturbed blood sugar control,” Dr. Saxena explained.
To investigate this, researchers enrolled 845 adults in Spain who were 18-70 years old and did not have diabetes. Participants were a mean age of 38 years and 71% were women. They had a mean body mass index of 25.7 kg/m2 and 18% had obesity.
On average, they typically ate dinner at 21:38 (9:38 p.m.) and went to bed at 24:32 (12:32 a.m.).
DNA analysis from participants’ blood samples determined that 50% had the CC genotype of the MTNR1B gene, 40% had the CG genotype, and 10% had the GG genotype.
Each participant underwent two oral glucose tolerance tests. They fasted for 8 hours and then had a 2-hour 75-g oral glucose tolerance test either 1 hour before bedtime (simulating a late dinner) or 4 hours before bedtime (simulating an early dinner). Then they repeated the test at the opposite dinner time on another night.
The average serum melatonin values were 3.5-fold higher after the late dinner than after the early dinner, resulting in 6.7% lower insulin area under the curve and 8.3% higher glucose AUC.
Genotype differences in glucose tolerance were attributed to reductions in beta-cell function.
“Our results confirm that late eating acutely impairs glucose tolerance through a defect in insulin secretion,” the researchers reiterated.
ONTIME-MT was funded by the National Institutes of Health; the Spanish Government of Investigation, Development, and Innovation; and the Seneca Foundation. The researchers reported no relevant financial disclosures.
A version of this article first appeared on Medscape.com.
which increase the risk of type 2 diabetes.
And people who are carriers of the G allele of the MTNR1B gene have greater impairment in glucose tolerance after eating a late dinner.
“In natural late eaters [in Spain], we simulated early and late dinner timing by administering a glucose drink and compared effects on blood sugar control over 2 hours,” said senior author Richa Saxena, PhD, a principal investigator at the Center for Genomic Medicine at Massachusetts General Hospital, Boston.
The study also compared outcomes in carriers and noncarriers of the G allele variant of the melatonin receptor gene, Dr. Saxena pointed out in a press release from the hospital.
“We found that late eating disturbed blood sugar control in the whole group,” added lead author Marta Garaulet, PhD.
“This impaired glucose control was predominantly seen in genetic risk variant carriers, representing about half of the cohort,” said Dr. Garaulet, professor of physiology and nutrition, University of Murcia (Spain).
The study results “may be important in the effort toward prevention of type 2 diabetes,” according to co–senior author Frank A.J.L. Scheer, PhD.
“Our findings are applicable to about a third of the population in the industrialized world who consume food close to bedtime, as well as other populations who eat at night, including shift workers, or those experiencing jet lag or night-eating disorders, as well as those who routinely use melatonin supplements close to food intake,” said Dr. Scheer, director of the medical chronobiology program at Brigham and Women’s Hospital, Boston.
The results suggest people should not eat within 2 hours of bedtime, said the researchers.
“Notably, our study does not include patients with diabetes, so additional studies are needed to examine the impact of food timing and its link with melatonin and receptor variation in patients with diabetes,” Dr. Scheer said.
The findings, from the MTNR1B SNP*Food Timing Interaction on Glucose Control (ONTIME-MT) randomized crossover study, were recently published in Diabetes Care.
Melatonin plays a key role in glucose metabolism
Melatonin, a hormone primarily released at night that helps control the sleep-wake cycle, typically rises around 2 hours before bedtime, the researchers explained.
The discovery of MTNR1B as a type 2 diabetes–associated gene “suggests that, beyond sleep and circadian regulation, melatonin plays a key role in glucose metabolism,” they noted. However, whether melatonin improves or impairs glucose control is controversial, and the effect of MTNR1B genotypes on glucose control is not clear.
“We decided to test if late eating that usually occurs with elevated melatonin levels results in disturbed blood sugar control,” Dr. Saxena explained.
To investigate this, researchers enrolled 845 adults in Spain who were 18-70 years old and did not have diabetes. Participants were a mean age of 38 years and 71% were women. They had a mean body mass index of 25.7 kg/m2 and 18% had obesity.
On average, they typically ate dinner at 21:38 (9:38 p.m.) and went to bed at 24:32 (12:32 a.m.).
DNA analysis from participants’ blood samples determined that 50% had the CC genotype of the MTNR1B gene, 40% had the CG genotype, and 10% had the GG genotype.
Each participant underwent two oral glucose tolerance tests. They fasted for 8 hours and then had a 2-hour 75-g oral glucose tolerance test either 1 hour before bedtime (simulating a late dinner) or 4 hours before bedtime (simulating an early dinner). Then they repeated the test at the opposite dinner time on another night.
The average serum melatonin values were 3.5-fold higher after the late dinner than after the early dinner, resulting in 6.7% lower insulin area under the curve and 8.3% higher glucose AUC.
Genotype differences in glucose tolerance were attributed to reductions in beta-cell function.
“Our results confirm that late eating acutely impairs glucose tolerance through a defect in insulin secretion,” the researchers reiterated.
ONTIME-MT was funded by the National Institutes of Health; the Spanish Government of Investigation, Development, and Innovation; and the Seneca Foundation. The researchers reported no relevant financial disclosures.
A version of this article first appeared on Medscape.com.
FROM DIABETES CARE
Does using A1c to diagnose diabetes miss some patients?
The introduction of hemoglobin A1c as an option for diagnosing type 2 diabetes over a decade ago may have resulted in underdiagnosis, new research indicates.
In 2011, the World Health Organization advised that A1c measurement, with a cutoff value of 6.5%, could be used to diagnose diabetes. The American Diabetes Association had issued similar guidance in 2010.
Prior to that time, the less-convenient 2-hour oral glucose tolerance test (OGTT) and fasting blood glucose (FBG) were the only recommended tests. While WHO made no recommendations for interpreting values below 6.5%, the ADA designated 5.7%-6.4% as prediabetes.
The new study, published online in The Lancet Regional Health–Europe, showed that the incidence of type 2 diabetes in Denmark had been increasing prior to the 2012 adoption of A1c as a diagnostic option but declined thereafter. And all-cause mortality among people with type 2 diabetes, which had been dropping, began to increase after that time.
“Our findings suggest that fewer patients have been diagnosed with [type 2 diabetes] since A1c testing was introduced as a convenient diagnostic option. We may thus be missing a group with borderline increased A1c values that is still at high metabolic and cardiovascular risk,” Jakob S. Knudsen, MD, of the department of clinical epidemiology, Aarhus (Denmark) University Hospital, and colleagues wrote.
Therefore, Dr. Knudsen said in an interview, clinicians should “consider testing with FBG or OGTT when presented with borderline A1c values.”
The reason for the increase in mortality after incident type 2 diabetes diagnosis, he said, “is that the patients who would have reduced the average mortality are no longer diagnosed...This does not reflect that we are treating already diagnosed patients any worse, rather some patients are not diagnosed.”
But M. Sue Kirkman, MD, emeritus professor of medicine at the University of North Carolina at Chapel Hill, who was part of the writing group for the 2010 ADA guidelines, isn’t convinced.
“This is an interesting paper, but it is a bit hard to believe that a change in WHO recommendations would have such a large and almost immediate impact on incidence and mortality. It seems likely that ... factors [other] than just the changes in recommendations for the diagnostic test account for these findings,” she said.
Dr. Kirkman pointed to new data just out from the Centers for Disease Control and Prevention on Jan. 26 that don›t show evidence of a higher proportion of people in the United States who have undiagnosed diabetes, “which would be expected if more cases were being ‘missed’ by A1c.”
She added that the CDC incidence data “show a continuing steady rate of decline in incidence that began in 2008, before any organizations recommended using A1c to screen for or diagnose diabetes.” Moreover, “there is evidence that type 2 diabetes incidence has fallen or plateaued in many countries since 2006, well before the WHO recommendation, with most of the studies from developed countries.”
But Dr. Knudsen also cited other data, including a study that showed a drop or stabilization in diagnosed diabetes incidence in high-income countries since 2010.
“That study concluded that the reasons for the declines in the incidence of diagnosed diabetes warrant further investigation with appropriate data sources, which was a main objective of our study,” wrote Dr. Knudsen and coauthors.
Dr. Knudsen said in an interview: “We are not the first to make the point that this sudden change is related to A1c introduction...but we are the first to have the data to clearly show that is the case.”
Diabetes incidence dropped but mortality rose after 2010
The population-based longitudinal study used four Danish medical databases and included 415,553 patients treated for type 2 diabetes for the first time from 1995-2018 and 2,060,279 matched comparators not treated for diabetes.
From 1995 until the 2012 introduction of A1c as a diagnostic option, the annual standardized incidence rates of type 2 diabetes more than doubled, from 193 per 100,000 population to 396 per 100,000 population, at a rate of 4.1% per year.
But from 2011 to 2018, the annual standardized incidence rate declined by 36%, to 253 per 100,000 population, a 5.7% annualized decrease.
The increase prior to 2011 occurred in both men and women and in all age groups, while the subsequent decline was seen primarily in the older age groups. The all-cause mortality risk within the first year after diabetes diagnosis was higher than subsequent 1-year mortality risks and not different between men and women.
From the periods 1995-1997 to 2010-2012, the adjusted mortality rate among those with type 2 diabetes decreased by 44%, from 72 deaths per 1000 person-years to 40 deaths per 1000 person-years (adjusted mortality rate ratio, 0.55). After that low level in 2010-2012, mortality increased by 27% to 48 per 1000 person-years (adjusted mortality rate ratio 0.69, compared with 1995-1997).
The reversed mortality trend after 2010-2012 was caused almost entirely by the increase in the first year after diabetes diagnosis, Dr. Knudsen and colleagues noted.
According to Dr. Kirkman, “A1c is strongly predictive of complications and mortality. That plus its ease of use and the fact that more people may be screened mean it’s still a good option. But for any of these tests, people who are slightly below the cut-point should not be considered normal or low risk.”
Indeed, Dr. Knudsen and colleagues said, “these findings may have implications for clinical practice and suggest that a more multifactorial view of metabolic risk is needed.”
Dr. Knudsen and Dr. Kirkman have reported no relevant financial relationships.
A version of this article first appeared on Medscape.com.
The introduction of hemoglobin A1c as an option for diagnosing type 2 diabetes over a decade ago may have resulted in underdiagnosis, new research indicates.
In 2011, the World Health Organization advised that A1c measurement, with a cutoff value of 6.5%, could be used to diagnose diabetes. The American Diabetes Association had issued similar guidance in 2010.
Prior to that time, the less-convenient 2-hour oral glucose tolerance test (OGTT) and fasting blood glucose (FBG) were the only recommended tests. While WHO made no recommendations for interpreting values below 6.5%, the ADA designated 5.7%-6.4% as prediabetes.
The new study, published online in The Lancet Regional Health–Europe, showed that the incidence of type 2 diabetes in Denmark had been increasing prior to the 2012 adoption of A1c as a diagnostic option but declined thereafter. And all-cause mortality among people with type 2 diabetes, which had been dropping, began to increase after that time.
“Our findings suggest that fewer patients have been diagnosed with [type 2 diabetes] since A1c testing was introduced as a convenient diagnostic option. We may thus be missing a group with borderline increased A1c values that is still at high metabolic and cardiovascular risk,” Jakob S. Knudsen, MD, of the department of clinical epidemiology, Aarhus (Denmark) University Hospital, and colleagues wrote.
Therefore, Dr. Knudsen said in an interview, clinicians should “consider testing with FBG or OGTT when presented with borderline A1c values.”
The reason for the increase in mortality after incident type 2 diabetes diagnosis, he said, “is that the patients who would have reduced the average mortality are no longer diagnosed...This does not reflect that we are treating already diagnosed patients any worse, rather some patients are not diagnosed.”
But M. Sue Kirkman, MD, emeritus professor of medicine at the University of North Carolina at Chapel Hill, who was part of the writing group for the 2010 ADA guidelines, isn’t convinced.
“This is an interesting paper, but it is a bit hard to believe that a change in WHO recommendations would have such a large and almost immediate impact on incidence and mortality. It seems likely that ... factors [other] than just the changes in recommendations for the diagnostic test account for these findings,” she said.
Dr. Kirkman pointed to new data just out from the Centers for Disease Control and Prevention on Jan. 26 that don›t show evidence of a higher proportion of people in the United States who have undiagnosed diabetes, “which would be expected if more cases were being ‘missed’ by A1c.”
She added that the CDC incidence data “show a continuing steady rate of decline in incidence that began in 2008, before any organizations recommended using A1c to screen for or diagnose diabetes.” Moreover, “there is evidence that type 2 diabetes incidence has fallen or plateaued in many countries since 2006, well before the WHO recommendation, with most of the studies from developed countries.”
But Dr. Knudsen also cited other data, including a study that showed a drop or stabilization in diagnosed diabetes incidence in high-income countries since 2010.
“That study concluded that the reasons for the declines in the incidence of diagnosed diabetes warrant further investigation with appropriate data sources, which was a main objective of our study,” wrote Dr. Knudsen and coauthors.
Dr. Knudsen said in an interview: “We are not the first to make the point that this sudden change is related to A1c introduction...but we are the first to have the data to clearly show that is the case.”
Diabetes incidence dropped but mortality rose after 2010
The population-based longitudinal study used four Danish medical databases and included 415,553 patients treated for type 2 diabetes for the first time from 1995-2018 and 2,060,279 matched comparators not treated for diabetes.
From 1995 until the 2012 introduction of A1c as a diagnostic option, the annual standardized incidence rates of type 2 diabetes more than doubled, from 193 per 100,000 population to 396 per 100,000 population, at a rate of 4.1% per year.
But from 2011 to 2018, the annual standardized incidence rate declined by 36%, to 253 per 100,000 population, a 5.7% annualized decrease.
The increase prior to 2011 occurred in both men and women and in all age groups, while the subsequent decline was seen primarily in the older age groups. The all-cause mortality risk within the first year after diabetes diagnosis was higher than subsequent 1-year mortality risks and not different between men and women.
From the periods 1995-1997 to 2010-2012, the adjusted mortality rate among those with type 2 diabetes decreased by 44%, from 72 deaths per 1000 person-years to 40 deaths per 1000 person-years (adjusted mortality rate ratio, 0.55). After that low level in 2010-2012, mortality increased by 27% to 48 per 1000 person-years (adjusted mortality rate ratio 0.69, compared with 1995-1997).
The reversed mortality trend after 2010-2012 was caused almost entirely by the increase in the first year after diabetes diagnosis, Dr. Knudsen and colleagues noted.
According to Dr. Kirkman, “A1c is strongly predictive of complications and mortality. That plus its ease of use and the fact that more people may be screened mean it’s still a good option. But for any of these tests, people who are slightly below the cut-point should not be considered normal or low risk.”
Indeed, Dr. Knudsen and colleagues said, “these findings may have implications for clinical practice and suggest that a more multifactorial view of metabolic risk is needed.”
Dr. Knudsen and Dr. Kirkman have reported no relevant financial relationships.
A version of this article first appeared on Medscape.com.
The introduction of hemoglobin A1c as an option for diagnosing type 2 diabetes over a decade ago may have resulted in underdiagnosis, new research indicates.
In 2011, the World Health Organization advised that A1c measurement, with a cutoff value of 6.5%, could be used to diagnose diabetes. The American Diabetes Association had issued similar guidance in 2010.
Prior to that time, the less-convenient 2-hour oral glucose tolerance test (OGTT) and fasting blood glucose (FBG) were the only recommended tests. While WHO made no recommendations for interpreting values below 6.5%, the ADA designated 5.7%-6.4% as prediabetes.
The new study, published online in The Lancet Regional Health–Europe, showed that the incidence of type 2 diabetes in Denmark had been increasing prior to the 2012 adoption of A1c as a diagnostic option but declined thereafter. And all-cause mortality among people with type 2 diabetes, which had been dropping, began to increase after that time.
“Our findings suggest that fewer patients have been diagnosed with [type 2 diabetes] since A1c testing was introduced as a convenient diagnostic option. We may thus be missing a group with borderline increased A1c values that is still at high metabolic and cardiovascular risk,” Jakob S. Knudsen, MD, of the department of clinical epidemiology, Aarhus (Denmark) University Hospital, and colleagues wrote.
Therefore, Dr. Knudsen said in an interview, clinicians should “consider testing with FBG or OGTT when presented with borderline A1c values.”
The reason for the increase in mortality after incident type 2 diabetes diagnosis, he said, “is that the patients who would have reduced the average mortality are no longer diagnosed...This does not reflect that we are treating already diagnosed patients any worse, rather some patients are not diagnosed.”
But M. Sue Kirkman, MD, emeritus professor of medicine at the University of North Carolina at Chapel Hill, who was part of the writing group for the 2010 ADA guidelines, isn’t convinced.
“This is an interesting paper, but it is a bit hard to believe that a change in WHO recommendations would have such a large and almost immediate impact on incidence and mortality. It seems likely that ... factors [other] than just the changes in recommendations for the diagnostic test account for these findings,” she said.
Dr. Kirkman pointed to new data just out from the Centers for Disease Control and Prevention on Jan. 26 that don›t show evidence of a higher proportion of people in the United States who have undiagnosed diabetes, “which would be expected if more cases were being ‘missed’ by A1c.”
She added that the CDC incidence data “show a continuing steady rate of decline in incidence that began in 2008, before any organizations recommended using A1c to screen for or diagnose diabetes.” Moreover, “there is evidence that type 2 diabetes incidence has fallen or plateaued in many countries since 2006, well before the WHO recommendation, with most of the studies from developed countries.”
But Dr. Knudsen also cited other data, including a study that showed a drop or stabilization in diagnosed diabetes incidence in high-income countries since 2010.
“That study concluded that the reasons for the declines in the incidence of diagnosed diabetes warrant further investigation with appropriate data sources, which was a main objective of our study,” wrote Dr. Knudsen and coauthors.
Dr. Knudsen said in an interview: “We are not the first to make the point that this sudden change is related to A1c introduction...but we are the first to have the data to clearly show that is the case.”
Diabetes incidence dropped but mortality rose after 2010
The population-based longitudinal study used four Danish medical databases and included 415,553 patients treated for type 2 diabetes for the first time from 1995-2018 and 2,060,279 matched comparators not treated for diabetes.
From 1995 until the 2012 introduction of A1c as a diagnostic option, the annual standardized incidence rates of type 2 diabetes more than doubled, from 193 per 100,000 population to 396 per 100,000 population, at a rate of 4.1% per year.
But from 2011 to 2018, the annual standardized incidence rate declined by 36%, to 253 per 100,000 population, a 5.7% annualized decrease.
The increase prior to 2011 occurred in both men and women and in all age groups, while the subsequent decline was seen primarily in the older age groups. The all-cause mortality risk within the first year after diabetes diagnosis was higher than subsequent 1-year mortality risks and not different between men and women.
From the periods 1995-1997 to 2010-2012, the adjusted mortality rate among those with type 2 diabetes decreased by 44%, from 72 deaths per 1000 person-years to 40 deaths per 1000 person-years (adjusted mortality rate ratio, 0.55). After that low level in 2010-2012, mortality increased by 27% to 48 per 1000 person-years (adjusted mortality rate ratio 0.69, compared with 1995-1997).
The reversed mortality trend after 2010-2012 was caused almost entirely by the increase in the first year after diabetes diagnosis, Dr. Knudsen and colleagues noted.
According to Dr. Kirkman, “A1c is strongly predictive of complications and mortality. That plus its ease of use and the fact that more people may be screened mean it’s still a good option. But for any of these tests, people who are slightly below the cut-point should not be considered normal or low risk.”
Indeed, Dr. Knudsen and colleagues said, “these findings may have implications for clinical practice and suggest that a more multifactorial view of metabolic risk is needed.”
Dr. Knudsen and Dr. Kirkman have reported no relevant financial relationships.
A version of this article first appeared on Medscape.com.
FROM THE LANCET REGIONAL HEALTH–EUROPE
Anxiety in men tied to risk factors for CVD, diabetes
Among healthy middle-aged men, those who were more anxious were more likely to develop high levels of multiple biomarkers of cardiometabolic risk over a 40-year follow-up in a new study.
“By middle adulthood, higher anxiety levels are associated with stable differences” in biomarkers of risk for coronary artery disease (CAD), stroke, and type 2 diabetes, which “are maintained into older ages,” the researchers wrote.
Anxious individuals “may experience deteriorations in cardiometabolic health earlier in life and remain on a stable trajectory of heightened risk into older ages,” they concluded.
The study, led by Lewina Lee, PhD, was published online Jan. 24, 2022, in the Journal of the American Heart Association.
“Men who had higher levels of anxiety at the beginning of the study had consistently higher biological risk for cardiometabolic disease than less anxious men from midlife into old age,” Dr. Lee, assistant professor of psychiatry, Boston University, summarized in an email.
Clinicians may not screen for heart disease and diabetes, and/or only discuss lifestyle modifications when patients are older or have the first signs of disease, she added.
However, the study findings “suggest that worries and anxiety are associated with preclinical pathophysiological processes that tend to culminate in cardiometabolic disease” and show “the importance of screening for mental health difficulties, such as worries and anxiety, in men as early as in their 30s and 40s,” she stressed.
Since most of the men were White (97%) and veterans (94%), “it would be important for future studies to evaluate if these associations exist among women, people from diverse racial and ethnic groups, and in more socioeconomically varying samples, and to consider how anxiety may relate to the development of cardiometabolic risk in much younger individuals than those in our study,” Dr. Lee said in a press release from the American Heart Association.
“This study adds to the growing body of research that link psychological health to cardiovascular risk,” Glenn N. Levine, MD, who was not involved with this research, told this news organization in an email.
“We know that factors such as depression and stress can increase cardiac risk; this study further supports that anxiety can as well,” added Dr. Levine, chief of cardiology, Michael E. DeBakey Veterans Affairs Medical Center, Houston.
“Everyone experiences some anxiety in their life,” he added. However, “if a provider senses that a patient’s anxiety is far beyond the ‘normal’ that we all have from time to time, and it is seemingly adversely impacting both their psychological and physical health, it would be reasonable to suggest to the patient that it might be useful to speak with a mental health professional, and if the patient is receptive, to then make a formal consultation or referral,” said Dr. Levine, who was writing group chair of a recent AHA Scientific Statement on mind-heart-body connection.
Neuroticism and worry
Several studies have linked anxiety to a greater risk of cardiometabolic disease onset, Dr. Lee and colleagues wrote, but it is unclear if anxious individuals have a steadily worsening risk as they age, or if they have a higher risk in middle age, which stays the same in older age.
To investigate this, they analyzed data from 1561 men who were seen at the VA Boston outpatient clinic and did not have CAD, type 2 diabetes, stroke, or cancer when they enrolled in the Normative Aging Study.
The men had a mean age of 53 years (range, 33-84) in 1975 and were followed until 2015 or until dropout from the study or death.
At baseline, the study participants filled in the Eysenck Personality Inventory, which assesses neuroticism, and also responded to a scale indicating how much they worry about 20 issues (excluding health).
“Neuroticism,” the researchers explained, “is a tendency to perceive experiences as threatening, feel that challenges are uncontrollable, and experience frequent and disproportionately intense negative emotions,” such as fear, anxiety, sadness, and anger, “across many situations.”
“Worry refers to attempts to solve a problem where future outcome is uncertain and potentially positive or negative,” Dr. Lee noted. Although worry can be healthy and lead to constructive solutions, “it may be unhealthy, especially when it becomes uncontrollable and interferes with day-to-day functioning.”
Of note, in 1980, the American Psychiatric Association removed the term neurosis from its diagnostic manual. What was previously called neurosis is included as part of generalized anxiety disorder; GAD also encompasses excessive worry.
Cardiometabolic risk from midlife to old age
The men in the current study had on-site physical examinations every 3-5 years.
The researchers calculated the men’s cardiometabolic risk score (from 0 to 7) by assigning 1 point each for the following: systolic blood pressure greater than 130 mm Hg, diastolic blood pressure greater than 85 mm Hg, total cholesterol of at least 240 mg/dL, triglycerides of at least 150 mg/dL, body mass index of at least 30 kg/m2, glucose of at least 100 mg/dL, and erythrocyte sedimentation rate of at least 14 mm/hour.
Alternatively, patients were assigned a point each for taking medication that could affect these markers (except for body mass index).
Overall, on average, at baseline, the men had a cardiometabolic risk score of 2.9. From age 33-65, this score increased to 3.8, and then it did not increase as much later on.
That is, the cardiometabolic risk score increased by 0.8 per decade until age 65, followed by a slower increase of 0.5 per decade.
At all ages, men with higher levels of neuroticism or worry had a higher cardiometabolic risk score
Each additional standard deviation of neuroticism was associated with a 13% increased risk of having six or more of the seven cardiometabolic risk markers during follow-up, after adjusting for age, demographics, and family history of CAD, but the relationship was attenuated after also adjusting for health behaviors (for example, smoking, alcohol consumption, physical activity, and past-year physician visit at baseline).
Similarly, each additional standard deviation of worry was associated with a 10% increased risk of having six or more of the seven cardiometabolic risk markers during follow-up after the same adjustments, and was also no longer significantly different after the same further adjustments.
The research was supported by grants from the National Institutes of Health and a Senior Research Career Scientist Award from the Office of Research and Development, Department of Veterans Affairs. The Normative Aging Study is a research component of the Massachusetts Veterans Epidemiology Research and Information Center and is supported by the VA Cooperative Studies Program/Epidemiological Research Centers. The study authors and Dr. Levine disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.
Among healthy middle-aged men, those who were more anxious were more likely to develop high levels of multiple biomarkers of cardiometabolic risk over a 40-year follow-up in a new study.
“By middle adulthood, higher anxiety levels are associated with stable differences” in biomarkers of risk for coronary artery disease (CAD), stroke, and type 2 diabetes, which “are maintained into older ages,” the researchers wrote.
Anxious individuals “may experience deteriorations in cardiometabolic health earlier in life and remain on a stable trajectory of heightened risk into older ages,” they concluded.
The study, led by Lewina Lee, PhD, was published online Jan. 24, 2022, in the Journal of the American Heart Association.
“Men who had higher levels of anxiety at the beginning of the study had consistently higher biological risk for cardiometabolic disease than less anxious men from midlife into old age,” Dr. Lee, assistant professor of psychiatry, Boston University, summarized in an email.
Clinicians may not screen for heart disease and diabetes, and/or only discuss lifestyle modifications when patients are older or have the first signs of disease, she added.
However, the study findings “suggest that worries and anxiety are associated with preclinical pathophysiological processes that tend to culminate in cardiometabolic disease” and show “the importance of screening for mental health difficulties, such as worries and anxiety, in men as early as in their 30s and 40s,” she stressed.
Since most of the men were White (97%) and veterans (94%), “it would be important for future studies to evaluate if these associations exist among women, people from diverse racial and ethnic groups, and in more socioeconomically varying samples, and to consider how anxiety may relate to the development of cardiometabolic risk in much younger individuals than those in our study,” Dr. Lee said in a press release from the American Heart Association.
“This study adds to the growing body of research that link psychological health to cardiovascular risk,” Glenn N. Levine, MD, who was not involved with this research, told this news organization in an email.
“We know that factors such as depression and stress can increase cardiac risk; this study further supports that anxiety can as well,” added Dr. Levine, chief of cardiology, Michael E. DeBakey Veterans Affairs Medical Center, Houston.
“Everyone experiences some anxiety in their life,” he added. However, “if a provider senses that a patient’s anxiety is far beyond the ‘normal’ that we all have from time to time, and it is seemingly adversely impacting both their psychological and physical health, it would be reasonable to suggest to the patient that it might be useful to speak with a mental health professional, and if the patient is receptive, to then make a formal consultation or referral,” said Dr. Levine, who was writing group chair of a recent AHA Scientific Statement on mind-heart-body connection.
Neuroticism and worry
Several studies have linked anxiety to a greater risk of cardiometabolic disease onset, Dr. Lee and colleagues wrote, but it is unclear if anxious individuals have a steadily worsening risk as they age, or if they have a higher risk in middle age, which stays the same in older age.
To investigate this, they analyzed data from 1561 men who were seen at the VA Boston outpatient clinic and did not have CAD, type 2 diabetes, stroke, or cancer when they enrolled in the Normative Aging Study.
The men had a mean age of 53 years (range, 33-84) in 1975 and were followed until 2015 or until dropout from the study or death.
At baseline, the study participants filled in the Eysenck Personality Inventory, which assesses neuroticism, and also responded to a scale indicating how much they worry about 20 issues (excluding health).
“Neuroticism,” the researchers explained, “is a tendency to perceive experiences as threatening, feel that challenges are uncontrollable, and experience frequent and disproportionately intense negative emotions,” such as fear, anxiety, sadness, and anger, “across many situations.”
“Worry refers to attempts to solve a problem where future outcome is uncertain and potentially positive or negative,” Dr. Lee noted. Although worry can be healthy and lead to constructive solutions, “it may be unhealthy, especially when it becomes uncontrollable and interferes with day-to-day functioning.”
Of note, in 1980, the American Psychiatric Association removed the term neurosis from its diagnostic manual. What was previously called neurosis is included as part of generalized anxiety disorder; GAD also encompasses excessive worry.
Cardiometabolic risk from midlife to old age
The men in the current study had on-site physical examinations every 3-5 years.
The researchers calculated the men’s cardiometabolic risk score (from 0 to 7) by assigning 1 point each for the following: systolic blood pressure greater than 130 mm Hg, diastolic blood pressure greater than 85 mm Hg, total cholesterol of at least 240 mg/dL, triglycerides of at least 150 mg/dL, body mass index of at least 30 kg/m2, glucose of at least 100 mg/dL, and erythrocyte sedimentation rate of at least 14 mm/hour.
Alternatively, patients were assigned a point each for taking medication that could affect these markers (except for body mass index).
Overall, on average, at baseline, the men had a cardiometabolic risk score of 2.9. From age 33-65, this score increased to 3.8, and then it did not increase as much later on.
That is, the cardiometabolic risk score increased by 0.8 per decade until age 65, followed by a slower increase of 0.5 per decade.
At all ages, men with higher levels of neuroticism or worry had a higher cardiometabolic risk score
Each additional standard deviation of neuroticism was associated with a 13% increased risk of having six or more of the seven cardiometabolic risk markers during follow-up, after adjusting for age, demographics, and family history of CAD, but the relationship was attenuated after also adjusting for health behaviors (for example, smoking, alcohol consumption, physical activity, and past-year physician visit at baseline).
Similarly, each additional standard deviation of worry was associated with a 10% increased risk of having six or more of the seven cardiometabolic risk markers during follow-up after the same adjustments, and was also no longer significantly different after the same further adjustments.
The research was supported by grants from the National Institutes of Health and a Senior Research Career Scientist Award from the Office of Research and Development, Department of Veterans Affairs. The Normative Aging Study is a research component of the Massachusetts Veterans Epidemiology Research and Information Center and is supported by the VA Cooperative Studies Program/Epidemiological Research Centers. The study authors and Dr. Levine disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.
Among healthy middle-aged men, those who were more anxious were more likely to develop high levels of multiple biomarkers of cardiometabolic risk over a 40-year follow-up in a new study.
“By middle adulthood, higher anxiety levels are associated with stable differences” in biomarkers of risk for coronary artery disease (CAD), stroke, and type 2 diabetes, which “are maintained into older ages,” the researchers wrote.
Anxious individuals “may experience deteriorations in cardiometabolic health earlier in life and remain on a stable trajectory of heightened risk into older ages,” they concluded.
The study, led by Lewina Lee, PhD, was published online Jan. 24, 2022, in the Journal of the American Heart Association.
“Men who had higher levels of anxiety at the beginning of the study had consistently higher biological risk for cardiometabolic disease than less anxious men from midlife into old age,” Dr. Lee, assistant professor of psychiatry, Boston University, summarized in an email.
Clinicians may not screen for heart disease and diabetes, and/or only discuss lifestyle modifications when patients are older or have the first signs of disease, she added.
However, the study findings “suggest that worries and anxiety are associated with preclinical pathophysiological processes that tend to culminate in cardiometabolic disease” and show “the importance of screening for mental health difficulties, such as worries and anxiety, in men as early as in their 30s and 40s,” she stressed.
Since most of the men were White (97%) and veterans (94%), “it would be important for future studies to evaluate if these associations exist among women, people from diverse racial and ethnic groups, and in more socioeconomically varying samples, and to consider how anxiety may relate to the development of cardiometabolic risk in much younger individuals than those in our study,” Dr. Lee said in a press release from the American Heart Association.
“This study adds to the growing body of research that link psychological health to cardiovascular risk,” Glenn N. Levine, MD, who was not involved with this research, told this news organization in an email.
“We know that factors such as depression and stress can increase cardiac risk; this study further supports that anxiety can as well,” added Dr. Levine, chief of cardiology, Michael E. DeBakey Veterans Affairs Medical Center, Houston.
“Everyone experiences some anxiety in their life,” he added. However, “if a provider senses that a patient’s anxiety is far beyond the ‘normal’ that we all have from time to time, and it is seemingly adversely impacting both their psychological and physical health, it would be reasonable to suggest to the patient that it might be useful to speak with a mental health professional, and if the patient is receptive, to then make a formal consultation or referral,” said Dr. Levine, who was writing group chair of a recent AHA Scientific Statement on mind-heart-body connection.
Neuroticism and worry
Several studies have linked anxiety to a greater risk of cardiometabolic disease onset, Dr. Lee and colleagues wrote, but it is unclear if anxious individuals have a steadily worsening risk as they age, or if they have a higher risk in middle age, which stays the same in older age.
To investigate this, they analyzed data from 1561 men who were seen at the VA Boston outpatient clinic and did not have CAD, type 2 diabetes, stroke, or cancer when they enrolled in the Normative Aging Study.
The men had a mean age of 53 years (range, 33-84) in 1975 and were followed until 2015 or until dropout from the study or death.
At baseline, the study participants filled in the Eysenck Personality Inventory, which assesses neuroticism, and also responded to a scale indicating how much they worry about 20 issues (excluding health).
“Neuroticism,” the researchers explained, “is a tendency to perceive experiences as threatening, feel that challenges are uncontrollable, and experience frequent and disproportionately intense negative emotions,” such as fear, anxiety, sadness, and anger, “across many situations.”
“Worry refers to attempts to solve a problem where future outcome is uncertain and potentially positive or negative,” Dr. Lee noted. Although worry can be healthy and lead to constructive solutions, “it may be unhealthy, especially when it becomes uncontrollable and interferes with day-to-day functioning.”
Of note, in 1980, the American Psychiatric Association removed the term neurosis from its diagnostic manual. What was previously called neurosis is included as part of generalized anxiety disorder; GAD also encompasses excessive worry.
Cardiometabolic risk from midlife to old age
The men in the current study had on-site physical examinations every 3-5 years.
The researchers calculated the men’s cardiometabolic risk score (from 0 to 7) by assigning 1 point each for the following: systolic blood pressure greater than 130 mm Hg, diastolic blood pressure greater than 85 mm Hg, total cholesterol of at least 240 mg/dL, triglycerides of at least 150 mg/dL, body mass index of at least 30 kg/m2, glucose of at least 100 mg/dL, and erythrocyte sedimentation rate of at least 14 mm/hour.
Alternatively, patients were assigned a point each for taking medication that could affect these markers (except for body mass index).
Overall, on average, at baseline, the men had a cardiometabolic risk score of 2.9. From age 33-65, this score increased to 3.8, and then it did not increase as much later on.
That is, the cardiometabolic risk score increased by 0.8 per decade until age 65, followed by a slower increase of 0.5 per decade.
At all ages, men with higher levels of neuroticism or worry had a higher cardiometabolic risk score
Each additional standard deviation of neuroticism was associated with a 13% increased risk of having six or more of the seven cardiometabolic risk markers during follow-up, after adjusting for age, demographics, and family history of CAD, but the relationship was attenuated after also adjusting for health behaviors (for example, smoking, alcohol consumption, physical activity, and past-year physician visit at baseline).
Similarly, each additional standard deviation of worry was associated with a 10% increased risk of having six or more of the seven cardiometabolic risk markers during follow-up after the same adjustments, and was also no longer significantly different after the same further adjustments.
The research was supported by grants from the National Institutes of Health and a Senior Research Career Scientist Award from the Office of Research and Development, Department of Veterans Affairs. The Normative Aging Study is a research component of the Massachusetts Veterans Epidemiology Research and Information Center and is supported by the VA Cooperative Studies Program/Epidemiological Research Centers. The study authors and Dr. Levine disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.
FROM THE JOURNAL OF THE AMERICAN HEART ASSOCIATION
AHA annual stats update highlights heart-brain connection
in its annual statistical update on heart disease and stroke.
“For several years now, the AHA and the scientific community have increasingly recognized the connections between cardiovascular health and brain health, so it was time for us to cement this into its own chapter, which we highlight as the brain health chapter,” Connie W. Tsao, MD, MPH, chair of the statistical update writing group, with Harvard Medical School, Boston, said in an AHA podcast.
“The global rate of brain disease is quickly outpacing heart disease,” Mitchell S. V. Elkind, MD, immediate past president of the AHA, added in a news release.
“The rate of deaths from Alzheimer’s disease and other dementias rose more than twice as much in the past decade compared to the rate of deaths from heart disease, and that is something we must address,” said Dr. Elkind, with Columbia University Vagelos College of Physicians and Surgeons in New York.
“It’s becoming more evident that reducing vascular disease risk factors can make a real difference in helping people live longer, healthier lives, free of heart disease and brain disease,” Dr. Elkind added.
The AHA’s Heart Disease and Stroke Statistics – 2022 Update was published online January 26 in Circulation).
The report highlights some of the research connecting heart and brain health, including the following:
- A meta-analysis of 139 studies showed that people with midlife hypertension were five times more likely to experience impairment on global cognition and about twice as likely to experience reduced executive function, dementia, and Alzheimer’s disease.
- A meta-analysis of four longitudinal studies found that the risk for dementia associated with heart failure was increased nearly twofold.
- In the large prospective Atherosclerosis Risk in Communities (ARIC) Neurocognitive Study, atrial fibrillation was associated with greater cognitive decline and dementia over 20 years.
- A meta-analysis of 10 prospective studies (including 24,801 participants) showed that coronary heart disease (CHD) was associated with a 40% increased risk of poor cognitive outcomes, including dementia, cognitive impairment, or cognitive decline.
“This new chapter on brain health was a critical one to add,” Dr. Tsao said in the news release.
“The data we’ve collected brings to light the strong correlations between heart health and brain health and makes it an easy story to tell -- what’s good for the heart is good for the brain,” Dr. Tsao added.
Along with the new chapter on brain health, the 2022 statistical update provides the latest statistics and heart disease and stroke. Among the highlights:
- Cardiovascular disease (CVD) remains the leading cause of death worldwide. In the United States in 2019, CVD, listed as the underlying cause of death, accounted for 874,613 deaths, about 2,396 deaths each day. On average, someone dies of CVD every 36 seconds.
- CVD claims more lives each year in the United States than all forms of cancer and chronic lower respiratory disease combined.
- In 2019, CHD was the leading cause (41.3%) of deaths attributable to CVD, followed by other CVD (17.3%), stroke (17.2%), hypertension (11.7%), heart failure (9.9%), and diseases of the arteries (2.8%).
- In 2019, stroke accounted for roughly 1 in every 19 deaths in the United States. On average, someone in the United States has a stroke every 40 seconds and someone dies of stroke every 3 minutes 30 seconds. When considered separately from other CVD, stroke ranks number five among all causes of death in the United States.
While the annual statistics update aims to be a contemporary update of annual heart disease and stroke statistics over the past year, it also examines trends over time, Dr. Tsao explains in the podcast.
“One noteworthy point is that we saw a decline in the rate of cardiovascular mortality over the past three decades or so until about 2010. But over the past decade now, we’re also seeing a rise in these numbers,” she said.
This could be due to rising rates of obesity, diabetes, and poor hypertension control, as well as other lifestyle behaviors, Tsao said.
Key risk factor data
Each year, the statistical update gauges the cardiovascular health of Americans by tracking seven key health factors and behaviors that increase risk for heart disease and stroke. Below is a snapshot of the latest risk factor data.
Smoking
In 2019, smoking was the leading risk factor for years of life lost to premature death and the third leading risk factor for years of life lived with disability or injury.
According to the 2020 surgeon general’s report on smoking cessation, more than 480,000 Americans die as a result of cigarette smoking, and more than 41,000 die of secondhand smoke exposure each year (roughly 1 in 5 deaths annually).
One in 7 adults are current smokers, 1 in 6 female adults are current smokers, and 1 in 5 high school students use e-cigarettes.
Physical inactivity
In 2018, 25.4% of U.S. adults did not engage in leisure-time physical activity, and only 24.0% met the 2018 Physical Activity Guidelines for Americans for both aerobic and muscle strengthening.
Among U.S. high school students in 2019, only 44.1% were physically active for 60 minutes or more on at least 5 days of the week.
Nutrition
While there is some evidence that Americans are improving their diet, fewer than 10% of U.S. adults met guidelines for whole grain, whole fruit, and nonstarchy vegetable consumption each day in 2017–2018.
Overweight/obesity
The prevalence of obesity among adults increased from 1999–2000 through 2017–2018 from 30.5% to 42.4%. Overall prevalence of obesity and severe obesity in U.S. youth 2 to 19 years of age increased from 13.9% to 19.3% and 2.6% to 6.1% between 1999–2000 and 2017–2018.
Cholesterol
Close to 94 million (38.1%) U.S. adults have total cholesterol of 200 mg/dL or higher, according to 2015–2018 data; about 28.0 million (11.5%) have total cholesterol of 240 mg/dL or higher; and 27.8% have high levels of low-density lipoprotein cholesterol (130 mg/dL or higher).
Diabetes
In 2019, 87,647 U.S. deaths were attributed to diabetes; data show that 9.8 million U.S. adults have undiagnosed diabetes, 28.2 million have diagnosed diabetes, and 113.6 million have prediabetes.
Hypertension
A total of 121.5 million (47.3%) U.S. adults have hypertension, based on 2015–2018 data. In 2019, 102,072 U.S. deaths were primarily attributable to hypertension.
This statistical update was prepared by a volunteer writing group on behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee. Disclosures for the writing committee are listed with the original article.
A version of this article first appeared on Medscape.com.
in its annual statistical update on heart disease and stroke.
“For several years now, the AHA and the scientific community have increasingly recognized the connections between cardiovascular health and brain health, so it was time for us to cement this into its own chapter, which we highlight as the brain health chapter,” Connie W. Tsao, MD, MPH, chair of the statistical update writing group, with Harvard Medical School, Boston, said in an AHA podcast.
“The global rate of brain disease is quickly outpacing heart disease,” Mitchell S. V. Elkind, MD, immediate past president of the AHA, added in a news release.
“The rate of deaths from Alzheimer’s disease and other dementias rose more than twice as much in the past decade compared to the rate of deaths from heart disease, and that is something we must address,” said Dr. Elkind, with Columbia University Vagelos College of Physicians and Surgeons in New York.
“It’s becoming more evident that reducing vascular disease risk factors can make a real difference in helping people live longer, healthier lives, free of heart disease and brain disease,” Dr. Elkind added.
The AHA’s Heart Disease and Stroke Statistics – 2022 Update was published online January 26 in Circulation).
The report highlights some of the research connecting heart and brain health, including the following:
- A meta-analysis of 139 studies showed that people with midlife hypertension were five times more likely to experience impairment on global cognition and about twice as likely to experience reduced executive function, dementia, and Alzheimer’s disease.
- A meta-analysis of four longitudinal studies found that the risk for dementia associated with heart failure was increased nearly twofold.
- In the large prospective Atherosclerosis Risk in Communities (ARIC) Neurocognitive Study, atrial fibrillation was associated with greater cognitive decline and dementia over 20 years.
- A meta-analysis of 10 prospective studies (including 24,801 participants) showed that coronary heart disease (CHD) was associated with a 40% increased risk of poor cognitive outcomes, including dementia, cognitive impairment, or cognitive decline.
“This new chapter on brain health was a critical one to add,” Dr. Tsao said in the news release.
“The data we’ve collected brings to light the strong correlations between heart health and brain health and makes it an easy story to tell -- what’s good for the heart is good for the brain,” Dr. Tsao added.
Along with the new chapter on brain health, the 2022 statistical update provides the latest statistics and heart disease and stroke. Among the highlights:
- Cardiovascular disease (CVD) remains the leading cause of death worldwide. In the United States in 2019, CVD, listed as the underlying cause of death, accounted for 874,613 deaths, about 2,396 deaths each day. On average, someone dies of CVD every 36 seconds.
- CVD claims more lives each year in the United States than all forms of cancer and chronic lower respiratory disease combined.
- In 2019, CHD was the leading cause (41.3%) of deaths attributable to CVD, followed by other CVD (17.3%), stroke (17.2%), hypertension (11.7%), heart failure (9.9%), and diseases of the arteries (2.8%).
- In 2019, stroke accounted for roughly 1 in every 19 deaths in the United States. On average, someone in the United States has a stroke every 40 seconds and someone dies of stroke every 3 minutes 30 seconds. When considered separately from other CVD, stroke ranks number five among all causes of death in the United States.
While the annual statistics update aims to be a contemporary update of annual heart disease and stroke statistics over the past year, it also examines trends over time, Dr. Tsao explains in the podcast.
“One noteworthy point is that we saw a decline in the rate of cardiovascular mortality over the past three decades or so until about 2010. But over the past decade now, we’re also seeing a rise in these numbers,” she said.
This could be due to rising rates of obesity, diabetes, and poor hypertension control, as well as other lifestyle behaviors, Tsao said.
Key risk factor data
Each year, the statistical update gauges the cardiovascular health of Americans by tracking seven key health factors and behaviors that increase risk for heart disease and stroke. Below is a snapshot of the latest risk factor data.
Smoking
In 2019, smoking was the leading risk factor for years of life lost to premature death and the third leading risk factor for years of life lived with disability or injury.
According to the 2020 surgeon general’s report on smoking cessation, more than 480,000 Americans die as a result of cigarette smoking, and more than 41,000 die of secondhand smoke exposure each year (roughly 1 in 5 deaths annually).
One in 7 adults are current smokers, 1 in 6 female adults are current smokers, and 1 in 5 high school students use e-cigarettes.
Physical inactivity
In 2018, 25.4% of U.S. adults did not engage in leisure-time physical activity, and only 24.0% met the 2018 Physical Activity Guidelines for Americans for both aerobic and muscle strengthening.
Among U.S. high school students in 2019, only 44.1% were physically active for 60 minutes or more on at least 5 days of the week.
Nutrition
While there is some evidence that Americans are improving their diet, fewer than 10% of U.S. adults met guidelines for whole grain, whole fruit, and nonstarchy vegetable consumption each day in 2017–2018.
Overweight/obesity
The prevalence of obesity among adults increased from 1999–2000 through 2017–2018 from 30.5% to 42.4%. Overall prevalence of obesity and severe obesity in U.S. youth 2 to 19 years of age increased from 13.9% to 19.3% and 2.6% to 6.1% between 1999–2000 and 2017–2018.
Cholesterol
Close to 94 million (38.1%) U.S. adults have total cholesterol of 200 mg/dL or higher, according to 2015–2018 data; about 28.0 million (11.5%) have total cholesterol of 240 mg/dL or higher; and 27.8% have high levels of low-density lipoprotein cholesterol (130 mg/dL or higher).
Diabetes
In 2019, 87,647 U.S. deaths were attributed to diabetes; data show that 9.8 million U.S. adults have undiagnosed diabetes, 28.2 million have diagnosed diabetes, and 113.6 million have prediabetes.
Hypertension
A total of 121.5 million (47.3%) U.S. adults have hypertension, based on 2015–2018 data. In 2019, 102,072 U.S. deaths were primarily attributable to hypertension.
This statistical update was prepared by a volunteer writing group on behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee. Disclosures for the writing committee are listed with the original article.
A version of this article first appeared on Medscape.com.
in its annual statistical update on heart disease and stroke.
“For several years now, the AHA and the scientific community have increasingly recognized the connections between cardiovascular health and brain health, so it was time for us to cement this into its own chapter, which we highlight as the brain health chapter,” Connie W. Tsao, MD, MPH, chair of the statistical update writing group, with Harvard Medical School, Boston, said in an AHA podcast.
“The global rate of brain disease is quickly outpacing heart disease,” Mitchell S. V. Elkind, MD, immediate past president of the AHA, added in a news release.
“The rate of deaths from Alzheimer’s disease and other dementias rose more than twice as much in the past decade compared to the rate of deaths from heart disease, and that is something we must address,” said Dr. Elkind, with Columbia University Vagelos College of Physicians and Surgeons in New York.
“It’s becoming more evident that reducing vascular disease risk factors can make a real difference in helping people live longer, healthier lives, free of heart disease and brain disease,” Dr. Elkind added.
The AHA’s Heart Disease and Stroke Statistics – 2022 Update was published online January 26 in Circulation).
The report highlights some of the research connecting heart and brain health, including the following:
- A meta-analysis of 139 studies showed that people with midlife hypertension were five times more likely to experience impairment on global cognition and about twice as likely to experience reduced executive function, dementia, and Alzheimer’s disease.
- A meta-analysis of four longitudinal studies found that the risk for dementia associated with heart failure was increased nearly twofold.
- In the large prospective Atherosclerosis Risk in Communities (ARIC) Neurocognitive Study, atrial fibrillation was associated with greater cognitive decline and dementia over 20 years.
- A meta-analysis of 10 prospective studies (including 24,801 participants) showed that coronary heart disease (CHD) was associated with a 40% increased risk of poor cognitive outcomes, including dementia, cognitive impairment, or cognitive decline.
“This new chapter on brain health was a critical one to add,” Dr. Tsao said in the news release.
“The data we’ve collected brings to light the strong correlations between heart health and brain health and makes it an easy story to tell -- what’s good for the heart is good for the brain,” Dr. Tsao added.
Along with the new chapter on brain health, the 2022 statistical update provides the latest statistics and heart disease and stroke. Among the highlights:
- Cardiovascular disease (CVD) remains the leading cause of death worldwide. In the United States in 2019, CVD, listed as the underlying cause of death, accounted for 874,613 deaths, about 2,396 deaths each day. On average, someone dies of CVD every 36 seconds.
- CVD claims more lives each year in the United States than all forms of cancer and chronic lower respiratory disease combined.
- In 2019, CHD was the leading cause (41.3%) of deaths attributable to CVD, followed by other CVD (17.3%), stroke (17.2%), hypertension (11.7%), heart failure (9.9%), and diseases of the arteries (2.8%).
- In 2019, stroke accounted for roughly 1 in every 19 deaths in the United States. On average, someone in the United States has a stroke every 40 seconds and someone dies of stroke every 3 minutes 30 seconds. When considered separately from other CVD, stroke ranks number five among all causes of death in the United States.
While the annual statistics update aims to be a contemporary update of annual heart disease and stroke statistics over the past year, it also examines trends over time, Dr. Tsao explains in the podcast.
“One noteworthy point is that we saw a decline in the rate of cardiovascular mortality over the past three decades or so until about 2010. But over the past decade now, we’re also seeing a rise in these numbers,” she said.
This could be due to rising rates of obesity, diabetes, and poor hypertension control, as well as other lifestyle behaviors, Tsao said.
Key risk factor data
Each year, the statistical update gauges the cardiovascular health of Americans by tracking seven key health factors and behaviors that increase risk for heart disease and stroke. Below is a snapshot of the latest risk factor data.
Smoking
In 2019, smoking was the leading risk factor for years of life lost to premature death and the third leading risk factor for years of life lived with disability or injury.
According to the 2020 surgeon general’s report on smoking cessation, more than 480,000 Americans die as a result of cigarette smoking, and more than 41,000 die of secondhand smoke exposure each year (roughly 1 in 5 deaths annually).
One in 7 adults are current smokers, 1 in 6 female adults are current smokers, and 1 in 5 high school students use e-cigarettes.
Physical inactivity
In 2018, 25.4% of U.S. adults did not engage in leisure-time physical activity, and only 24.0% met the 2018 Physical Activity Guidelines for Americans for both aerobic and muscle strengthening.
Among U.S. high school students in 2019, only 44.1% were physically active for 60 minutes or more on at least 5 days of the week.
Nutrition
While there is some evidence that Americans are improving their diet, fewer than 10% of U.S. adults met guidelines for whole grain, whole fruit, and nonstarchy vegetable consumption each day in 2017–2018.
Overweight/obesity
The prevalence of obesity among adults increased from 1999–2000 through 2017–2018 from 30.5% to 42.4%. Overall prevalence of obesity and severe obesity in U.S. youth 2 to 19 years of age increased from 13.9% to 19.3% and 2.6% to 6.1% between 1999–2000 and 2017–2018.
Cholesterol
Close to 94 million (38.1%) U.S. adults have total cholesterol of 200 mg/dL or higher, according to 2015–2018 data; about 28.0 million (11.5%) have total cholesterol of 240 mg/dL or higher; and 27.8% have high levels of low-density lipoprotein cholesterol (130 mg/dL or higher).
Diabetes
In 2019, 87,647 U.S. deaths were attributed to diabetes; data show that 9.8 million U.S. adults have undiagnosed diabetes, 28.2 million have diagnosed diabetes, and 113.6 million have prediabetes.
Hypertension
A total of 121.5 million (47.3%) U.S. adults have hypertension, based on 2015–2018 data. In 2019, 102,072 U.S. deaths were primarily attributable to hypertension.
This statistical update was prepared by a volunteer writing group on behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee. Disclosures for the writing committee are listed with the original article.
A version of this article first appeared on Medscape.com.