You are leaving Medscape Education
Cancel Continue
Log in to save activities Your saved activities will show here so that you can easily access them whenever you're ready. Log in here CME & Education Log in to keep track of your credits.
 

Table 1.  

Characteristic Sarcopenia Status (N = 337)
Robusta (n = 109) Probable Sarcopeniab (n = 112) Sarcopeniac (n = 116) P Valued
Baseline (1990–1993)
Age, mean (SD), y 54.0 (5.7) 55.6 (6.4) 59.9 (5.8) <.001
<12 Years of education, n (%) 25 (22.9) 37 (33.0) 43 (37.1) .02
Birthplace, n (%)
Middle East 32 (29.4) 33 (29.5) 39 (33.6) .02e
Europe 47 (43.1) 46 (41.1) 55 (47.4)  
Israel 30 (27.5) 33 (29.5) 22 (19.0)  
Smoking, n (%)
Currently 5 (4.6) 10 (8.9) 9 (7.8) .61
Former 75 (68.8) 67 (59.8) 73 (62.9)
Never 29 (26.6) 35 (31.2) 34 (29.3)
Previous myocardial infarction, n (%) 87 (79.8) 92 (82.1) 87 (75.0) .40
Diabetes, n (%) 10 (9.2) 9 (8.0) 13 (11.2) .71
Chronic kidney disease,f n (%) 26 (23.9) 24 (21.6) 39 (33.6) .09
Insulin resistance,g n (%) 25 (23.6) 32 (30.5) 23 (20.9) .25
Angina class,h n (%)
≥2 14 (12.8) 14 (12.5) 18 (15.5) .03e
<2 95 (87.2) 98 (87.5) 98 (84.5)
Previous hypertension, n (%) 22 (20.2) 31 (27.7) 41 (35.3) .04
Any physical activity, n (%) 83 (78.3) 80 (72.1) 82 (71.3) .44
Blood glucose ≥100 mg/dL, n (%) 34 (31.2) 33 (29.7) 51 (44.0) .04
Body mass index, n (%)
18.5 to <25.0 kg/m2 57 (52.3) 34 (30.4) 30 (25.9) <.001
25.0–29.9 kg/m2 48 (44.0) 66 (58.9) 67 (57.8)
≥30.0 kg/m2 4 (3.7) 12 (10.7) 19 (16.4)
Height, mean (SD), m 1.7 (0.6) 1.7 (0.7) 1.7 (0.6) <.001
Blood pressure, mean (SD), mm Hg
Systolic 126 (15) 129 (15) 133 (17) <.001
Diastolic 80 (9) 80 (8) 81 (8) .66
Cholesterol, mean (SD), mg/dL
Total 215 (16) 214 (19) 213 (19) .58
Low-density lipoprotein 150 (16) 149 (17) 150 (18) .91
High-density lipoprotein 34 (5) 35 (5) 35 (5) .35
Triglycerides, median (IQR), mg/dLi 141 (121–184) 135 (108–190) 133 (98–174) .08
C-reactive protein, median (IQR), mg/dLi 2.2 (1.1–4.5) 2.1 (1.3–4.0) 2.4 (1.5–4.9) .23
Time 1 (2004–2009)
Age, mean (SD), y 68.8 (5.4) 70.7 (6.4) 75.3 (5.8) <.001
Common carotid intima-media thickness, mean (SD), mm 0.93 (0.2) 0.97 (0.2) 0.10 (0.2) .04
Impaired cerebrovascular reactivity, n (%) 41 (39.4) 33 (32.7) 56 (51.4) .02
Bilateral carotid plaque, n (%) 49 (45.4) 51 (47.2) 69 (61.6) .03
Global cognitive score,j mean (SD) 98.8 (8.9) 96.8 (10.0) 95.2 (8.9) .02
Geriatric Depression Scale,k score ≥5, n (%) 9 (8.3) 17 (15.2) 26 (22.8) <.001
Time 2 (2011–2013)
Age, mean (SD), y 74.2 (5.5) 76.0 (6.4) 80.4 (5.7) <.001

Table 1. Baseline Characteristics of Participants in the Bezafibrate Infarction Prevention Neurocognitive Study, by Sarcopenia Status at Time 2, Israel, 2011–2013

Abbreviation: IQR, interquartile range.

a No evidence of sarcopenia.

b Defined as low muscle strength or low muscle mass according to European Working Group on Sarcopenia in Older People[2].

c Defined as low muscle strength and low muscle mass and/or low physical performance according to European Working Group on Sarcopenia in Older People[2].

d P value determined by analysis of variance or Kruskal–Wallis test for continuous variables and χ2 test for categorical variables, unless otherwise indicated; P < .05 considered significant.

e P for trend determined by χ2 test; P < .05 considered significant.

f Defined as estimated glomerular filtration rate <60 mL/min/m2.

g Defined as homeostatic model assessment of insulin resistance in the top quartile (≥1.60).

h Classfication according to Canadian Cardiovascular Society angina classification[17]; the larger the value, the greater the severity.

i Median (IQR) presented because of nonnormal distribution of data.

j Global cognitive score scaled to an IQ-style scale with mean of 100 and SD of 15. Patients completed the NeuroTrax computerized cognitive test (NeuroTrax Corporation). A description of this test is available elsewhere [23].

k Geriatric Depression Scale[22] from 0 to 15; score of ≥5 indicates clinically significant depressive symptoms.

Table 2.  

Model Probable Sarcopenia Sarcopenia
OR (95% CI) P Value OR (95% CI) P Value
Model 1b
BMI ≥25 2.95 (1.64–5.29) <.001 4.94 (2.57–9.48) <.001
BMI <25 1 [Reference] 1 [Reference]
Model 2c
BMI ≥25 2.88 (1.54–5.36) .001 5.04 (2.51–10.15) <.001
BMI <25 1 [Reference] 1 [Reference]
Model 3d
BMI ≥25 3.27 (1.68–6.36) <.001 5.31 (2.50–11.27) <.001
BMI <25 1 [Reference] 1 [Reference]
Model 4e
BMI ≥25 2.72 (1.81–4.09) <.001 4.52 (2.89–7.05) <.001
BMI <25 1 [Reference] 1 [Reference]
Model 5f
BMI ≥25 3.76 (1.84–7.68) <.001 7.78 (3.24–18.69) <.001
BMI <25 1 [Reference] 1 [Reference]

Table 2. Multinomial Logistic Regression for Association Between BMI Groups (≥25.0 vs <25.0) at Baseline (1990–1993) and Sarcopenia Status at Time 2 (2011–2013) Among a Sample of Men (n = 337) Participating in Bezafibrate Infarction Prevention Neurocognitive Study, Israela

Abbreviations: BMI, body mass index; OR, odds ratio.

a In all comparisons, reference outcome value is robust, defined as no evidence of sarcopenia. The category BMI <25 excludes underweight (BMI <18.5).

b Model 1 = age, education (≥12 y vs <12 y), and birthplace (Europe, Middle East vs Israel).

c Model 2 = Model 1 + systolic blood pressure (continuous), physical activity, diabetes, insulin resistance (top quartile vs others), C-reactive protein, high-density lipoprotein cholesterol, and triglycerides (continuous).

d Model 3 = Model 2 + impaired cerebrovascular reactivity vs normal, carotid intima-media thickness, global cognitive score, and geriatric depression score ≥5 at time 1 (2004–2009).

e Model 4 = Model 3 applying inverse probability weights.

f Model 5 = Model 3 after excluding 53 participants with stroke and dementia at time 2 (2011–2013).

Table 3.  

Model Probable Sarcopenia Sarcopenia
OR (95% CI) P Value OR (95% CI) P Value
Model 1b 1.24 (1.11–1.39) <.001 1.34 (1.19–1.51) <.001
Model 2c 1.28 (1.12–1.45) <.001 1.39 (1.21–1.59) <.001
Model 3d 1.33 (1.16–1.53) <.001 1.38 (1.19–1.59) <.001
Model 4e 1.28 (1.18–1.39) <.001 1.34 (1.23–1.45) <.001
Model 5f 1.33 (1.15–1.54) <.001 1.42 (1.21–1.66) <.001

Table 3. Multinomial Logistic Regression for Association Between BMI (as a Continuous Variable) and Sarcopenia Status Among a Sample of Men (n = 337) Participating in Bezafibrate Infarction Prevention Neurocognitive Study, Israel, 2011–2013a

Abbreviations: BMI, body mass index; OR, odds ratio.

a In all comparisons, reference outcome value is robust, defined as no evidence of sarcopenia.

b Model 1 = age, education (≥12 y vs <12 y), birthplace (Europe, Middle East vs Israel).

c Model 2 = Model 1 + systolic blood pressure (continuous), physical activity, diabetes, insulin resistance (top quartile vs others), C-reactive protein, high-density lipoprotein cholesterol, and triglycerides (continuous).

d Model 3 = Model 2 + impaired cerebrovascular reactivity vs normal, carotid intima-media thickness, global cognitive score, and geriatric despression score ≥5 at time 1 (2004–2009).

e Model 4 = Model 3 applying inverse probability weights.

f Model 5 = Model 3 after excluding 53 participants with stroke and dementia at time 2 (2011–2013).

CME / ABIM MOC

Overweight, Obesity, and Late-Life Sarcopenia Among Men With Cardiovascular Disease, Israel

  • Authors: Miri Lutski, PhD; Galit Weinstein, PhD; David Tanne, MD; Uri Goldbourt, PhD
  • CME / ABIM MOC Released: 12/24/2020
  • THIS ACTIVITY HAS EXPIRED FOR CREDIT
  • Valid for credit through: 12/24/2021, 11:59 PM EST
Start Activity


Target Audience and Goal Statement

This activity is intended for cardiologists, internists, bariatricians, endocrinologists, family practitioners, and other clinicians caring for patients with cardiovascular disease (CVD) who may be at increased risk for sarcopenia because of obesity.

The goal of this activity is to describe the association among overweight, obesity, and late-life sarcopenia among community-dwelling elderly men with CVD, according to multinomial logistic analysis of data from 337 men (mean age at baseline, 56.7±6.5 years) who previously participated in the Bezafibrate Infarction Prevention trial and who underwent a neurovascular evaluation 15 years after baseline and a sarcopenia evaluation 19.9 years after baseline.

Upon completion of this activity, participants will be able to:

  • Describe the prevalence of sarcopenia and associated factors among community-dwelling elderly men with CVD
  • Assess increased risk for sarcopenia as a function of body mass index among community-dwelling elderly men with CVD
  • Identify clinical and public health implications of the association among overweight, obesity, and late-life sarcopenia among community-dwelling elderly men with CVD


Disclosures

As an organization accredited by the ACCME, Medscape, LLC requires everyone who is in a position to control the content of an education activity to disclose all relevant financial relationships with any commercial interest. The ACCME defines "relevant financial relationships" as financial relationships in any amount, occurring within the past 12 months, including financial relationships of a spouse or life partner, that could create a conflict of interest.

Medscape, LLC encourages Authors to identify investigational products or off-label uses of products regulated by the US Food and Drug Administration, at first mention and where appropriate in the content.


Faculty

  • Miri Lutski, PhD

    The Israel Center for Disease Control
    Israel Ministry of Health
    Tel Aviv, Israel

    Disclosures

    Disclosure: Miri Lutski, PhD, has disclosed no relevant financial relationships.

  • Galit Weinstein, PhD

    School of Public Health
    Faculty of Social Welfare and Health Sciences
    University of Haifa
    Haifa, Israel

    Disclosures

    Disclosure: Galit Weinstein, PhD, has disclosed no relevant financial relationships.

  • David Tanne, MD

    Department of Neurology
    Sackler Faculty of Medicine
    Tel Aviv University
    Tel Aviv, Israel
    Stroke and Cognition Institute
    Rambam Health Care Campus
    Haifa, Israel

    Disclosures

    Disclosure: David Tanne, MD, has disclosed no relevant financial relationships.

  • Uri Goldbourt, PhD

    Department of Epidemiology and Preventive Medicine
    School of Public Health
    Sackler Faculty of Medicine
    Tel Aviv University
    Tel Aviv, Israel

    Disclosures

    Disclosure: Uri Goldbourt, PhD, has disclosed no relevant financial relationships.

CME Author

  • Laurie Barclay, MD

    Freelance writer and reviewer
    Medscape, LLC

    Disclosures

    Disclosure: Laurie Barclay, MD, has disclosed no relevant financial relationships.

Editor

  • Ellen Taratus

    Editor
    Preventing Chronic Disease

    Disclosures

    Disclosure: Ellen Taratus has disclosed no relevant financial relationships.

CME/Content Reviewer

  • Stephanie Corder, ND, RN, CHCP

    Associate Director
    Accreditation and Compliance
    Medscape, LLC

    Disclosures

    Disclosure: Stephanie Corder, ND, RN, CHCP, has disclosed no relevant financial relationships.

CE Reviewer

  • Esther Nyarko, PharmD

    Associate Director, Accreditation and Compliance
    Medscape, LLC

    Disclosures

    Disclosure: Esther Nyarko, PharmD, has disclosed no relevant financial relationships.

Medscape, LLC staff have disclosed that they have no relevant financial relationships.


Accreditation Statements

Medscape

Interprofessional Continuing Education

In support of improving patient care, this activity has been planned and implemented by Medscape, LLC and Preventing Chronic Disease. Medscape, LLC is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team.

    For Physicians

  • Medscape, LLC designates this Journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit(s)™ . Physicians should claim only the credit commensurate with the extent of their participation in the activity.

    Successful completion of this CME activity, which includes participation in the evaluation component, enables the participant to earn up to 1.0 MOC points in the American Board of Internal Medicine's (ABIM) Maintenance of Certification (MOC) program. Participants will earn MOC points equivalent to the amount of CME credits claimed for the activity. It is the CME activity provider's responsibility to submit participant completion information to ACCME for the purpose of granting ABIM MOC credit.

    Contact This Provider

For questions regarding the content of this activity, contact the accredited provider for this CME/CE activity noted above. For technical assistance, contact [email protected]


Instructions for Participation and Credit

There are no fees for participating in or receiving credit for this online educational activity. For information on applicability and acceptance of continuing education credit for this activity, please consult your professional licensing board.

This activity is designed to be completed within the time designated on the title page; physicians should claim only those credits that reflect the time actually spent in the activity. To successfully earn credit, participants must complete the activity online during the valid credit period that is noted on the title page. To receive AMA PRA Category 1 Credit™, you must receive a minimum score of 70% on the post-test.

Follow these steps to earn CME/CE credit*:

  1. Read about the target audience, learning objectives, and author disclosures.
  2. Study the educational content online or print it out.
  3. Online, choose the best answer to each test question. To receive a certificate, you must receive a passing score as designated at the top of the test. We encourage you to complete the Activity Evaluation to provide feedback for future programming.

You may now view or print the certificate from your CME/CE Tracker. You may print the certificate, but you cannot alter it. Credits will be tallied in your CME/CE Tracker and archived for 6 years; at any point within this time period, you can print out the tally as well as the certificates from the CME/CE Tracker.

*The credit that you receive is based on your user profile.

CME / ABIM MOC

Overweight, Obesity, and Late-Life Sarcopenia Among Men With Cardiovascular Disease, Israel

Authors: Miri Lutski, PhD; Galit Weinstein, PhD; David Tanne, MD; Uri Goldbourt, PhDFaculty and Disclosures
THIS ACTIVITY HAS EXPIRED FOR CREDIT

CME / ABIM MOC Released: 12/24/2020

Valid for credit through: 12/24/2021, 11:59 PM EST

processing....

Abstract & Introduction

Abstract

Introduction
Little is known about the association between obesity and sarcopenia — age-related loss of muscle mass and function — among patients with cardiovascular disease. We investigated the association between overweight, obesity, and sarcopenia among community-dwelling men in Israel with cardiovascular disease.

Methods
A subset of 337 men (mean age at baseline 56.7 [SD, 6.5]) who previously (1990–1997) participated in the Bezafibrate Infarction Prevention trial underwent a neurovascular evaluation as part of the Bezafibrate Infarction Prevention Neurocognitive Study 15.0 (SD, 3.0) years after baseline and a sarcopenia evaluation 19.9 (SD, 1.0) years after baseline. We applied a multinomial logistic model to estimate odds ratios and 95% CIs for 3 categories of sarcopenia: no evidence of sarcopenia (ie, robust), probable sarcopenia, and sarcopenia.

Results
We found sarcopenia among 54.3% of participants with obesity (body mass index [BMI, in kg/m2 ] ≥30.0), 37.0% of participants who were overweight (25.0 ≤ BMI ≤29.9), and 24.8% of participants with normal weight (BMI 18.5 to 24.9). In a comparison of BMI ≥25.0 and BMI <25.0, adjusting for covariates, the odds ratio of having probable sarcopenia was 3.27 (95% CI, 1.68–6.36) and having sarcopenia was 5.31 (95% CI, 2.50–11.27).

Conclusion
We found a positive association between obesity and late-life sarcopenia and suggest that obesity might be an important modifiable risk factor related to sarcopenia among men with cardiovascular disease.

Introduction

Sarcopenia, from the Greek “poverty of flesh,” is a highly prevalent geriatric syndrome first described by Rosenberg in 1989 as the age-related loss of muscle mass and function.[1] Accumulating evidence suggests that sarcopenia is associated with adverse health outcomes such as frailty, falls, disability, admission to nursing homes, and mortality.[2] Several underlying mechanisms are linked with the development of sarcopenia, including impaired neuromuscular function, hormonal changes, increased inflammation, changes in body-fat distribution, poor nutritional status, and various chronic conditions, yet not all have been fully elucidated.[3] The most studied approach in modifying risk factors for sarcopenia is resistance exercise. Numerous treatments of sarcopenia, including protein supplementation and pharmacological interventions, have limited value.[4]

Obesity-mediated factors may aggravate sarcopenia in older people and maximize its effects on physical disability, morbidity, and mortality.[5,6] Several studies investigated the association of obesity with sarcopenia[7–10]. Findings on the association between overweight and sarcopenia are controversial.[7] The prevalence of cardiovascular disease (CVD) in middle and old age is increasing, partly as a result of increases in the prevalence of obesity.[11,12] Furthermore, CVD might accelerate the development of sarcopenia, and both have been strongly tied to chronic low-grade inflammation, insulin resistance, and obesity.[13] However, little is known about the association between obesity and sarcopenia in patients with CVD. The aim of this study was to describe the association between overweight, obesity, and late-life sarcopenia among community-dwelling men aged 64 or older with CVD.