Sunday, December 3, 2023
| 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.
| 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).
| 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).
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.
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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.
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.
