J Obes Metab Syndr 2020; 29(2): 160-162
Published online June 30, 2020 https://doi.org/10.7570/jomes20046
Copyright © Korean Society for the Study of Obesity.
Department of Internal Medicine, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea
Correspondence to:
Ji Won Yoon
https://orcid.org/0000-0001-9003-0614
Department of Internal Medicine, Seoul National University Hospital Healthcare System Gangnam Center, 152 Teheran-ro, Gangnam-gu, Seoul 06236, Korea
Tel: +82-2-2112-5677
Fax: +82-2-2112-5794
E-mail: jwyoonmd@gmail.com
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Recently, we reported the association between sarcopenia and nonalcoholic fatty liver disease (NAFLD) in
The mechanism through which age is an effect modifier is not clear, but analyzing the clinical characteristics according to age, as suggested in the letter, would be helpful in estimating the components. Thus, we compared several body compositions and metabolic and inflammatory parameters according to age group.
In all subjects, with or without sarcopenia, waist circumference and visceral adipose tissue area increased while skeletal muscle mass decreased with age (data not shown). Similarly, blood pressure and blood glucose level increased with age. On the other hand, triglycerides, high-density lipoprotein (HDL)-cholesterol, and alanine aminotransferase levels were not significantly different among age groups. Also, high-sensitivity C-reactive protein (hs-CRP) level as an inflammatory marker was not significantly different according to age group (data not shown).
However, in subjects with sarcopenia, younger subjects were more likely to be male and had higher body mass index, waist circumference, and skeletal muscle mass (Table 1). They also showed higher uric acid, triglyceride, and total and low-density lipoprotein (LDL)-cholesterol level and lower HDL-cholesterol level. Again, hs-CRP level showed no difference (Table 1). Male sex, obesity/abdominal obesity, and worse metabolic profiles shown in blood tests can be related to insulin resistance, an important risk factor for NAFLD. Even though sex and visceral adiposity were adjusted in the subgroup analysis of our previous study, the residual effect of insulin resistance might have influenced the association between sarcopenia and NALFD. In our study population, most young subjects with sarcopenia had sarcopenic obesity. Only two people in the tertile 1 (19–49 years) age group were non-obese and sarcopenic. Therefore, we were not able to compare metabolic profiles between young sarcopenic subjects with or without obesity.
A previous study by Srikanthan et al.3 reported that sarcopenia was more strongly associated with insulin resistance in a younger group (<60 years). In that study, not only sarcopenic obesity, but also sarcopenia without obesity was significantly associated with insulin resistance. However, data from Korea National Health and Nutrition Examination Survey 2009–2010 showed no age-related effect modification between sarcopenia and insulin resistance.4 In a study reporting decrease in skeletal muscle mass as an independent risk factor for incident NAFLD, the subjects in a younger age subgroup (<45 years) did not show such an association.5 However, in non-obese subjects, decreased muscle mass over time was a risk factor for NAFLD even in a younger age group.5 As such, findings of the association between sarcopenia and insulin resistance or NALFD vary depending on the study. The discrepancy between study results could be due to differences in study design and population characteristics.
In our study, an increase in insulin resistance at a younger age could be explained in part by obesity/abdominal obesity in this group. Unfortunately, detailed analysis of the association between sarcopenia with or without obesity and NAFLD was difficult to perform using the data. Differences in etiology of sarcopenia, changes in muscle fiber type distribution, and intramyocellular lipid accumulation have been suggested as possible mechanisms of age-related differences in the association between sarcopenia and insulin resistance.3 Further studies are needed to determine whether there is an effect modification by age and whether these factors cause differences in insulin resistance.
The effect of chronic inflammation in the association between sarcopenia and NAFLD did not seem to be major. However, chronic inflammation is regarded as an important mediator of insulin resistance,6 so future studies should evaluate it as a potential factor for mediating the association between sarcopenia and NAFLD. We are grateful for the opportunity to look deeper into our data based on this response letter.
The authors declare no conflict of interest.
Clinical characteristics of subjects with sarcopenia according to age
Variable | T1 (19–49 yr, n= 82) | T2 (50–57 yr, n= 65) | T3 (58–87 yr, n= 168) | Total (n= 315) | |
---|---|---|---|---|---|
Age (yr) | 42.1±4.8*, |
53.0±2.3‡ | 65.9±6.0 | 57.1±11.4 | <0.001 |
Male (n, %) | 69 (84.1) | 48 (73.8) | 113 (67.3) | 230 (73) | 0.018* |
Systolic blood pressure (mmHg) | 123.0±13.1 | 122.2±14.1 | 125.4±14.7 | 124.1±14.2 | 0.228 |
Diastolic blood pressure (mmHg) | 0.8±10.7† | 79.4±10.8 | 76.5±10.6 | 78.2±10.8 | 0.007 |
Waist circumference (cm) | 99.5±9.0*, |
95.3±9.1 | 94.7±8.7 | 96.1±9.0 | <0.001 |
Visceral adipose tissue (cm2) | 171.8±52.5 | 186.3±56.2 | 180.2±60.6 | 179.3±57.7 | 0.322 |
Body mass index (kg/m2) | 29.8±3.9*, |
28.3±3.5‡ | 26.7±3.1 | 27.8±3.6 | <0.001 |
Appendicular skeletal muscle (kg) | 22.8±4.1*, |
20.1±4.9‡ | 18.2±4.5 | 19.8±4.9 | <0.001 |
ASM/body weight (%) | 26.9±2.6† | 26.1±3.4 | 25.9±3.1 | 26.2±3.1 | 0.044 |
Fasting glucose (mg/dL) | 108.0±38.5 | 103.9±20.6 | 106.5±22.8 | 106.3±27.4 | 0.661 |
Total cholesterol (mg/dL) | 05.3±37.0† | 199.8±42.0 | 190.8±35.4 | 196.5±37.7 | 0.013 |
Triglycerides (mg/dL) | 50.0±59.2† | 132.5±67.0 | 116.1±58.7 | 128.6±62.2 | <0.001 |
HDL-cholesterol (mg/dL) | 46.2±7.4† | 47.4±8.8‡ | 50.4±11.0 | 48.7±9.9 | 0.004 |
LDL-cholesterol (mg/dL) | 37.3±34.7† | 130.9±36.0‡ | 120.9±30.7 | 127.4±33.6 | 0.001 |
Alanine aminotransferase (IU/mL) | 45.3±28.5*, |
34.8±20.7 | 31.7±20.4 | 35.9±23.5 | <0.001 |
Uric acid (mg/dL) | 7.1±1.5*, |
6.3±1.4‡ | 5.7±1.6 | 6.2±1.6 | <0.001 |
hs-CRP (mg/dL) | 0.2±0.4 | 0.1±0.2 | 0.2±0.4 | 0.2±0.3 | 0.586 |
Values are presented as mean± standard deviation or number (%). One-way analysis of variance with post-hoc least significant difference for continuous variables. Chi-square test for categorical variable.
*
T1, 1st tertile; T2, 2nd tertile; T3, 3rd tertile; ASM, appendicular skeletal muscle; HDL, high-density lipoprotein; LDL, low-density lipoprotein; hs-CRP, high-sensitivity C-reactive protein.
Online ISSN : 2508-7576Print ISSN : 2508-6235
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