[헬스앤라이프 송보미 기자] 심혈관질환 원인 중 하나인 근육감소지표가 처음으로 나왔다. 체질량 지수 30미만 경우 근육량 대비 복부지방량을, 고도비만인 경우 키로 보정한 근육의 절대량이 심혈관질환 위험을 나타내는 지표다.
기존에는 근육 감소를 나타내는 지표로 일정하게 쓰이는 기준이 없고, 개개인의 성별·연령·키·체중에 따라 정상 근육량의 기준이 다르다는 점에서 특정 한 가지 지표로 심혈관질환의 위험도를 정의하기는 어려웠다. 이번 연구 결과는 향후 정상체중군에 속하지만 대사학적으로는 비만인 위험군을 평가하는 지표로 활용가치가 있을 전망이다.
19일 분당서울대병원에 따르면 가정의학과 김주영 교수 연구팀은 근육 감소를 나타내는 여러 지표 중 한국인에게 발생하는 심혈관질환의 위험 요인을 가장 잘 반영하는 지표를 찾기 위한 연구를 수행했다.
연구팀은 지난 2008년부터 2011년까지 한국인 1만7870명을 대상으로 사지 근육량을 ▲키 ▲체중 ▲체질량 지수 ▲체지방을 보정한 지표 ▲근육량과 복부지방의 비율 등 총 5가지 지표로 나눠 비교했다.
그 결과 근육 자체의 양이 줄어들 때보다는 근육량에 비해 지방이 과다하게 축적돼 있을 때 심혈관질환의 위험도와 상관관계가 확인됐다.
반면 체질량 지수가 30 이상으로 고도비만인 경우에는 ‘키로 보정한 근육의 절대량’ 지표가 심혈관질환의 위험도를 가장 잘 반영하는 것으로 나타났다.
김주영 교수는 “허리둘레와 같이 일반적으로 알려진 비만도의 기준만으로 심혈관질환을 평가하면 저체중이나 정상체중에 있는 사람에게 발생하는 심혈관질환의 위험을 간과하기 쉽다.일례로 아시아인은 서양인에 비해 비교적 낮은 체질량지수를 보임에도 심혈관질환 위험도는 높은 편”이라고 설명했다.
아래는 논문 원본 일부 발췌본. (Downloaded from Scientific Reports)
Comparisons of different indices of low muscle mass in relationship with cardiometabolic disorder
Ju Young Kim, Sohee Oh, Hwa Yeon Park, Ji Hye Jun, Hwa Jung Kim
This study aimed to evaluate the most valid index among various indices of low muscle mass in assessing cardiometabolic risks in a Korean population. Appendicular lean mass index (ALMI, kg/m2), fat mass index (FMI, kg/m2), FMI-adjusted ALMI (ALMfmi), ratio of ALM to weight index (ALMwt), ratio of ALM to body mass index (ALMbmi) and ratio of ALM to truncal fat index (ALMtrunkfat) were measured by dual energy X-ray absorptiometry in 17,870 participants from 2008 to 2011. We adopted all the aforementioned indices of low muscle mass expressed as sex- and age-specific standard deviation scores (Z-scores). Low muscle mass for age was defined as Z-score <−1. The prevalence of low muscle mass was approximately 16% across all indices. Low muscle mass defined by ALMI had low muscle mass and low fat mass, and ALMfmi had low muscle mass at the same FMI. However, low muscle mass defined by ALMwt, ALMbmi and ALMtrunkfat had similar muscle mass with high FMI. The receiver operating characteristic curve in metabolic syndrome showed that the ALMtrunkfat was 0.74 in male and 0.69 in female, indicating that ALMtrunkfat was the best discrimination index for metabolic syndrome. This study showed that ALMtrunkfat could be a useful indicator for screening cardiometabolic risk factors, particularly in normal or overweight Asian population.
The characteristics of the participants of the Korea National Health and Nutrition Examination Surveys (KNHANES) are summarised in Table 1. The prevalence of metabolic syndrome among KNHANES population was 22% in male and 19% in female.
Comparison of body composition between low muscle mass for age and control groups among different indices
Table 2 shows the characteristics between decreased muscle mass and normal muscle mass groups according to the five different definitions of muscle mass depletion. Since we adopted the definition of relative low muscle mass (Z score less than −1 SD) across age and sex, the prevalence of low muscle mass was approximately 16% among different indices. The difference in the average BMI was the highest in appendicular lean mass index (ALMI) criteria (20.5 in the low muscle mass group vs 24.2 in the control group) and the lowest in ratio of appendicular lean mass to body mass index (ALMbmi) criteria (25.5 in the low muscle mass group vs 23.2 in the control group).
When low muscle mass was classified by ratio of appendicular lean mass index adjusted for fat mass index (ALMIfmi), the ALMI was decreased in the low muscle mass group (the difference was −1.50 in male, −1.06 in female) given the same FMI between the groups. If the low muscle mass was classified by ratio of appendicular lean mass to weight (ALMwt) or ALMbmi criteria, the difference in ALMI was −0.30 in male and −0.33 in female, whereas the difference in FMI was more prominent (2.03 to 2.68 in male, 2.40 to 2.97 in female). The biggest difference was noted when low muscle mass was classified by ratio of ALM to truncal fat index (ALMtrunkfat) criteria; the difference in ALMI was −0.04 in male and 0.02 in female, whereas that in FMI was 3.06 in male and 3.46 in female.
Association of different indices of low muscle mass with cardiometabolic risk factors
Each index of low muscle mass adjusted for age, sex and BMI was strongly associated with waist circumference or triglyceride (TG) in both male and female. However, the relationship with other cardiometabolic components was different among each index as shown in Table 3. The ALMI or ALMIfmi was not associated with SBP and weakly associated with high-density lipoprotein (HDL) in male and weakly associated with HDL or TG in female. In general, the ALMtrunkfat was the only index strongly associated with each cardiometabolic component and inversely associated with homeostasis model assessment of insulin resistance (HOMA-IR) (β = −0.38 in male, β = −0.25 in female, p < 0.001) in both sexes.
Table 3 Age-, sex- and body mass index-adjusted linear and logistic models evaluating associations between several indices of low muscle mass with cardiometabolic components.
When analysed with multivariable logistic model, each index was strongly associated with metabolic syndrome in male, but again the ALMtrunkfat was the only index associated with metabolic syndrome in female (odds ratio = 1.45, 95% confidence interval [CI]: 1.25, 1.67).
Comparison of receiver operating characteristic curves in metabolic syndrome among different indices of low muscle mass
The receiver operating characteristic (ROC) curves of different indices of low muscle mass in predicting metabolic syndrome are shown in Fig. 2 in male and Fig. 3 in female. The area under the receiver operating characteristics (AUCs) of ALMI, ALMIfmi, ALMbmi and ALMwt showed moderately good discrimination for metabolic syndrome. The AUCs of ALMtrunkfat were 0.74 (95% CI: 0.73, 0.75) in male and 0.69 (95% CI: 0.68, 0.70) in female, indicating that ALMtrunkfat was the best discrimination index for metabolic syndrome.
The ROC contrast estimation showed that when compared with ALMI, the ALMwt (difference 0.051, 95% CI: 0.029, 0.073) and ALMtrunkfat(difference 0.091, 95% CI: 0.071, 0.110) were better index for metabolic syndrome in male. In female, the same estimation revealed that ALMIfmi(difference −0.065, 95% CI: −0.071, −0.060) and ALMwt (difference −0.061, 95% CI: −0.081, −0.060) were not better than ALMI index, but ALMtrunkfat performed better (difference 0.040, 95% CI: 0.022, 0.059) than ALMI.
Table 4 shows the different AUCs of ALMtrunkfat in various age, BMI and sex groups. When a person’s BMI is normal weight (BMI< 23) or overweight (BMI between 23 and 25), the ALMtrunkfat index performed significantly better in predicting metabolic syndrome. However, when a person’s BMI is more than 30, the ALMIfmi index in male or the ALMI index in female modestly worked, but performed better than the ALMtrunkfat index in predicting metabolic syndrome. Based on maximised Youden’s index, cut-off values of 2.60 in male (sensitivity 76.2% and specificity 62.1%) and 1.44 in female (sensitivity 76.6% and specificity 67.0%), which were the optimal cut-off values of the ALMtrunkfat index in predicting metabolic syndrome, were obtained20.
Table 4 Best ROC models of decreased muscle mass index in metabolic syndrome across sex, age and body mass groups.
※ 출처 Scientific Reports
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