From May 2016 to August 2017, we conducted a cross-sectional study on individuals undergoing routine health follow-up at the First Affiliated Hospital of Wenzhou Medical University. We included participants aged ≥18 years who underwent serum lipid profile assay and bioelectrical impedance analysis (BIA) during the study period. We excluded individuals aged <18 years; those taking anti-dyslipidemic medications; and those with a history of stroke, malignant tumor, chronic kidney disease, liver disease, or thyroid disease.
The study was approved by the hospital’s Institutional Review Board (IRB). Given its cross-sectional nature, the need for participant informed consent was waived by the IRB as confidentiality was assured. The study was conducted in in accordance with the principles of the Declaration of Helsinki.
With the use of predesigned questionnaires, we collected the following patient data: mode of life and comorbidities, as well as the results of BIA, blood analysis, and biochemical and anthropometric measurements.
Smoking and alcohol consumption: Alcohol consumptions > 70 g and 140 g per week for women and men, respectively, were considered as heavy drinking. Smoking status was divided into the following 3 categories: current smoker (has been smoking for at least 6 months, or abandoned smoking <2 years ago), past smoker (stopped smoking at least 2 years ago), and non-smoker (never smoked).
Comorbidities included diabetes mellitus (DM), hypertension (HTN), and hyperuricemia. DM was define as random plasma glucose (PG), fasting plasma glucose (FPG), or 2-h PG 200 mg/dL, 126 mg/dL, or 200 mg/dL, respectively (18). Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured for all participants in the morning during medical examination. HTN was defined as SBP ≥140 mmHg or DBP ≥90 mmHg (19). Hyperuricemia was defined as serum uric acid (UA) levels >6 mg/dL and >7.0 mg/dL in females and males, respectively (20). Additionally, we obtained comorbidity and drug histories from self-reports.
BIA (InBody770; InBody Japan Inc., Tokyo, Japan) was used to monitor patient appendicular skeletal muscle mass (ASM, in kg). Thereafter, skeletal muscle mass index (SMI, kg/m2) was computed using the formula, SMI = ASM (kg)/ height2 (m2). Moreover, according to the AWGS 2019 Consensus (1), sarcopenia was diagnosed in males and females with SMI <7.0 kg/m2 and <5.7 kg/m2, respectively. Participants with body mass index (BMI) >25 kg/m2 were considered to be overweight.
The following blood parameters were measured on the morning of the day when the medical examination was performed: TG, HDL-C, low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), glycated hemoglobin (HbA1c), FPG, albumin, UA, hemoglobin (Hb), white blood cell count (WBC), and platelet count (PLT).
Continuous and categorical variables were presented as medians (ranges) and frequencies (percentages), respectively. We used receiver operating characteristic (ROC) curves to assess the diagnostic accuracy of lipid profile for sarcopenia. The optimal indicator was selected based on the area under the curve (AUC) and Youden index. Participants were grouped, according to the selected indicator, in the high and low groups. Differences in continuous and categorical variables were compared with the Mann-Whitney and χ2 tests, respectively. Univariate and multivariate logistic regression models were used to evaluate the effects of the different factors on the risk of sarcopenia occurrence; moreover, TG, HDL-C, and TG/HDL-C ratio were used as separate logistic regression models. We performed backward stepwise selection using the Akaike information criterion (AIC) to identify variables for multivariate logistic regression models. Interaction terms were added to the multivariate logistic regression analysis in order to get rid of confounding factors. In addition, individuals were stratified by quartiles, and the χ2 test was used to compare the different sarcopenia occurrence rates.
Statistical analyses were performed using R version 3.6.1 (https://www.r-project.org/). All analyses were two-sided, and a P value <0.05 was considered statistically significant.