Association between the Thigh Muscle and Insulin Resistance According to Body Mass Index in Middle-Aged Korean Adults

Associations of muscle mass, strength, and quality with diabetes and the mediating role of inflammation in two National surveys from China and the United states

AIMS

The evidence for joint and independent associations of low muscle mass and low muscle strength with diabetes is limited and mixed. The study aimed to determine the associations of muscle parameters (muscle mass, strength, quality, and sarcopenia) and sarcopenia obesity with diabetes, and the previously unstudied mediating effect of inflammation.

MATERIALS AND METHODS

A total of 13,420 adults from the 2023 China National Health Survey (CNHS) and 5380 adults from the 2011-2014 National Health and Nutrition Examination Survey (NHANES) were included in this study. Muscle mass was determined using bioelectrical impedance analysis (BIA) in the CNHS, and whole-body dual X-ray absorptiometry (DXA) in the NHANES. Muscle strength was assessed using digital hand dynamometer. Multivariate logistic regression models were used to evaluate the associations of muscle parameters and sarcopenia obesity with diabetes. Inflammatory status was assessed using blood cell counts and two systemic inflammation indices (platelet-to-lymphocyte ratio (PLR) and system inflammation response index (SIRI)). Mediation analysis was conducted to examine inflammation's role in these associations.

RESULTS

Low muscle mass and strength were independently related to diabetes. Low muscle quality was associated with elevated diabetes risk. Sarcopenia has a stronger association with diabetes compared to low muscle strength alone or mass alone (CNHS, odds ratio (OR) = 1.93, 95 % confidence interval (CI):1.64-2.27; NHANES, OR = 3.80, 95 %CI:2.58-5.58). Participants with sarcopenia obesity exhibit a higher risk of diabetes than those with obesity or sarcopenia alone (CNHS, OR = 2.21, 95 %CI:1.72-2.84; NHANES, OR = 6.06, 95 %CI:3.64-10.08). Associations between muscle parameters and diabetes were partially mediated by inflammation (mediation proportion: 1.99 %-36.64 %, P < 0.05).

CONCLUSION

Low muscle mass and muscle strength are independently or jointly associated with diabetes, and inflammation might be a potential mechanism underlying this association. Furthermore, the synergistic effects of sarcopenia and obesity could significantly increase diabetes risk.

Risk of sleep apnea associated with higher blood pressure among Chinese and Korean Americans

OBJECTIVE

This study examines associations between sleep apnea risk and hypertension in a sample of immigrant Chinese and Korean Americans.

DESIGN

The dataset included Chinese and Korean patients ages 50-75 recruited from primary care physicians' offices from April 2018 to June 2020 in the Baltimore-Washington DC Metropolitan Area (n = 394). Hypertension risk was determined using a combination of blood pressure measurements, self-reported diagnosis of hypertension by a medical professional, and/or self-reported use of antihypertensive medications. Linear regression models examined the associations between sleep apnea risk and blood pressure (systolic blood pressure [SBP] and diastolic blood pressure [DBP]). Poisson regression models examined associations sleep apnea risk and hypertension. Models controlled for body mass index (BMI), demographic, and socioeconomic risk factors. We further examined models for potential effect modification by age, gender, Asian subgroup, and obesity, as well as effect modification of daytime sleepiness on the association between snoring and hypertension risk.

RESULTS

High risk of sleep apnea appeared to be associated positively with SBP (β = 6.77, 95% CI: 0.00-13.53), but not with DBP. The association was positive for hypertension, but it was not statistically significant (PR = 1.11, 95% CI: 0.87-1.41). We did not find effect modification of the associations between sleep apnea and hypertension risk, but we did find that daytime sleepiness moderated the effect of snoring on SBP. Snoring was associated with higher SBP, primarily in the presence of daytime sleepiness, such that predicted SBP was 133.27 mmHg (95% CI: 126.52, 140.02) for someone with both snoring and daytime sleepiness, compared to 123.37 mmHg (95% CI: 120.40, 126.34) for someone neither snoring nor daytime sleepiness.

CONCLUSION

Chinese and Korean immigrants living in the U.S. who are at high risk of sleep apnea have higher SBP on average, even after accounting for sociodemographic characteristics and BMI.

CLINICAL TRAIL REGISTRATION

: NCT03481296, date of registration: 3/29/2018.

Establishing reference values for percentage of appendicular skeletal muscle mass and their association with metabolic syndrome in Korean adolescents

PURPOSE

The association between appendicular skeletal muscle mass (ASM) and cardiometabolic risk has been emphasized. We estimated reference values of the percentage of ASM (PASM) and investigated their association with metabolic syndrome (MS) in Korean adolescents.

METHODS

Data from the Korea National Health and Nutrition Examination Survey performed between 2009 and 2011 were used. Tables and graphs of reference PASM were generated using 1,522 subjects, 807 of whom were boys aged 10 to 18. The relationship between PASM and each component of MS in adolescents was further analyzed in 1,174 subjects, 613 of whom were boys. Moreover, the pediatric simple MS score (PsiMS), the homeostasis model assessment of insulin resistance (HOMA-IR), and the triglyceride-glucose (TyG) index were analyzed. Multivariate linear and logistic regressions adjusting for age, sex, household income, and daily energy intake were performed.

RESULTS

In boys, PASM increased with age; the trend was different in girls, in whom PASM declined with age. PsiMS, HOMA-IR, and TyG index showed inverse associations with PASM (PsiMS, β=-0.105, P<0.001; HOMA-IR, β=-0.104, P<0.001; and TyG index, β=-0.013, P<0.001). PASM z-score was negatively associated with obesity (adjusted odds ratio [aOR], 0.22; 95% CI, 0.17-0.30), abdominal obesity (aOR, 0.27; 95% CI, 0.20-0.36), hypertension (aOR, 0.65; 95% CI, 0.52-0.80), and elevated triglycerides (aOR, 0.67; 95% CI, 0.56-0.79).

CONCLUSION

The probability of acquiring MS and insulin resistance decreased as PASM values increased. The reference range may offer clinicians information to aid in the effective management of patients. We urge clinicians to monitor body composition using standard reference databases.

Prospective External Validation of an Algorithm Predicting Hourly Basal Insulin Infusion Rates from Characteristics of Patients with Type 1 Diabetes Treated with Insulin Pumps

BACKGROUND

We previously published an algorithm predicting 24 h basal insulin infusion profiles in insulin pump-treated subjects with type 1 diabetes profiles from six subject characteristics. This algorithm was to be externally validated in an independent environment and patient population.

METHODS

Thirty-two patients with pump-treated type diabetes were switched to their individually algorithm-derived basal insulin infusion profile, and the appropriateness of fasting glycemic control was scrutinized by means of a supervised 24 h fast. Primary endpoint was appropriate fasting glycemic control according to pre-defined criteria in at least 80% of the cohort.

RESULTS

In 24 out of 32 patients switching to the algorithm-derived basal insulin infusion rate and undergoing a 24-h fasting period, appropriate glycemic control was achieved (=75%, lower than the pre-defined threshold of 80%), two patients discontinued the fast due to hyperglycemia, and six finished the fasting period, however, with inappropriate fasting glycemic control (entirely due to hyperglycemic episodes). There were no obvious differences in baseline characteristics between those with appropriate vs. inappropriate fasting glycemic control on the basal insulin infusion rate provided by the algorithm.

CONCLUSION

In conclusion, when testing fasting glycemic control with an algorithm-derived individual basal insulin infusion profile during a 24 h fasting period in a cohort unrelated in terms of the hospital environment and catchment area, the success rate was lower than a pre-defined threshold for concluding utility of this algorithm. Therefore, applying this algorithm in order to initiate or optimize basal insulin infusion profiles in type 1 diabetes cannot be generally recommended.

Sex-specific equations to estimate body composition: Derivation and validation of diagnostic prediction models using UK Biobank

BACKGROUND & AIMS

Body mass index and waist circumference are simple measures of obesity. However, they do not distinguish between visceral and subcutaneous fat, or muscle, potentially leading to biased relationships between individual body composition parameters and adverse health outcomes. The purpose of this study was to develop and validate prediction models for volumetric adipose and muscle.

METHODS

Based on cross-sectional data of 18,457, 18,260, and 17,052 White adults from the UK Biobank, we developed sex-specific equations to estimate visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (ASAT), and total thigh fat-free muscle (FFM) volumes, respectively. Volumetric magnetic resonance imaging served as the reference. We used the least absolute shrinkage and selection operator and the extreme gradient boosting methods separately to fit three sequential models, the inputs of which included demographics and anthropometrics and, in some, bioelectrical impedance analysis parameters. We applied comprehensive metrics to assess model performance in the temporal validation set.

RESULTS

The equations that included more predictors generally performed better. Accuracy of the equations was moderate for VAT (percentage of estimates that differed <30% from the measured values, 70 to 78 in males, 64 to 69 in females) and good for ASAT (85 to 91 in males, 90 to 95 in females) and FFM (99 to 100 in both sexes). All the equations appeared precise (interquartile range of the difference, 0.89 to 1.76 L for VAT, 1.16 to 1.61 L for ASAT, 0.81 to 1.39 L for FFM). Bias of all the equations was negligible (-0.17 to 0.05 L for VAT, -0.10 to 0.12 L for ASAT, -0.07 to 0.09 L for FFM). The equations achieved superior cardiometabolic correlations compared with body mass index and waist circumference.

CONCLUSIONS

The developed equations to estimate VAT, ASAT, and FFM volumes achieved moderate to good performance. They may be cost-effective tools to revisit the implications of diverse body components.

Non-Alcoholic Fatty Liver Disease with Sarcopenia and Carotid Plaque Progression Risk in Patients with Type 2 Diabetes Mellitus

BACKGROUND

We aimed to evaluate whether non-alcoholic fatty liver disease (NAFLD) with or without sarcopenia is associated with progression of carotid atherosclerosis in patients with type 2 diabetes mellitus (T2DM).

METHODS

We investigated 852 T2DM patients who underwent abdominal ultrasonography, bioelectrical impedance analysis, and carotid artery ultrasonography at baseline and repeated carotid ultrasonography after 6 to 8 years. NAFLD was confirmed by abdominal ultrasonography, and sarcopenia was defined as a sex-specific skeletal muscle mass index (SMI) value <2 standard deviations below the mean for healthy young adults. SMI was calculated by dividing the sum of appendicular skeletal mass by body weight. We investigated the association between NAFLD with or without sarcopenia and the progression of carotid atherosclerosis.

RESULTS

Of the 852 patients, 333 (39.1%) were classified as NAFLD without sarcopenia, 66 (7.7%) were classified as sarcopenia without NAFLD, and 123 (14.4%) had NAFLD with sarcopenia at baseline. After 6 to 8 years, patients with both NAFLD and sarcopenia had a higher risk of atherosclerosis progression (adjusted odds ratio, 2.20; P<0.009) than controls without NAFLD and sarcopenia. When a subgroup analysis was performed on only patients with NAFLD, female sex, absence of central obesity, and non-obesity were significant factors related to increased risk of plaque progression risk in sarcopenic patients.

CONCLUSION

NAFLD with sarcopenia was significantly associated with the progression of carotid atherosclerosis in T2DM patients.

Gender Differences in Relation to Body Composition, Insulin Resistance, and Islet Beta Cell Function in Newly Diagnosed Diabetic or Pre-Diabetic Patients

OBJECTIVE

To assess the correlation between body components with insulin resistance (IR) and islet beta cell function in patients with newly diagnosed type 2 diabetes mellitus (T2DM) or pre-diabetes mellitus (pre-DM) and to explore whether this correlation differs in males and females.

METHODS

111 newly diagnosed diabetic or pre-diabetic patients were recruited in this cross-sectional study. 75g oral glucose tolerance test was used to determine the diagnosis of DM or pre-DM. Homeostasis model assessment of insulin resistance (HOMA-IR) and glucose disposition index (DI₃₀) was calculated to assess IR and islet beta cell function, respectively. Whole-body and regional lean mass (LM) and fat mass (FM) were obtained by dual-energy X-ray absorptiometry (DEXA). Partial correlation and multiple linear regression analyses were used to determine the associations between body composition, IR, and islet beta cell function.

RESULTS

More body fat and appendicular fat was observed in female patients than in male, though with similar BMI. Legs fat % was negatively correlated with HOMA-IR, whereas legs lean % was positively associated with HOMA-IR in females (r = -0.673, p = 0.017; r =0.664, p = 0.018, respectively). The regression analysis showed that legs LM was positively correlated with HOMA-IR in females. However, in male patients, android FM was positively correlated with HOMA-IR (r = 0.462, p = 0.007), and trunk LM was negatively associated with DI₃₀ (r = -0.458, p = 0.007). Nevertheless, no significant correlation was observed between body composition and islet beta cell function in female patients.

CONCLUSION

Android FM was positively correlated with IR only in male patients but not in females. Besides, relative legs fat and LM were independently associated with IR in female patients but not in males. Further studies are needed to explore the underlying mechanism.

Evaluating Triglyceride and Glucose Index as a Simple and Easy-to-Calculate Marker for All-Cause and Cardiovascular Mortality

OBJECTIVE

The triglyceride and glucose (TyG) index is a useful marker of insulin resistance and is a predictor of several metabolic diseases. The aim of this study was to evaluate the association between the TyG index and all-cause or cardiovascular mortality using a large population-based cohort study database.

METHODS

A total of 255,508 subjects in the Kangbuk Samsung Health Study cohort were enrolled. Cox proportional hazards models were used to analyze the risk of mortality.

RESULTS

During a median 5.7-year follow-up, the cumulative all-cause and cardiovascular mortality was 0.47% and 0.07%. There was a nonlinear relationship between the TyG index and death, and moving from moderate to high, the TyG index levels were associated with an increase in the risk of death. The hazard ratio (HR) for all-cause and cardiovascular mortality of the TyG index was 1.21 [95% confidence interval (CI) 1.14-1.28] and 1.45 (95% CI 1.26-1.66) in the unadjusted model, respectively. After adjustment for covariates, the association between the TyG index and all-cause and cardiovascular mortality was attenuated. In the multivariable-adjusted model, the TyG index was associated with an elevated risk of all-cause mortality in women (HR 1.13, 95% CI 1.02-1.26) and a decreased risk in men (HR 0.92, 95% CI 0.85-0.99). The association between cardiovascular mortality and the TyG index was not statistically significant among either men or women in the multivariable-adjusted model.

CONCLUSIONS

The TyG index in a young, relatively healthy, population is associated with an elevated risk of all-cause and cardiovascular mortality. This association between the TyG index and all-cause mortality persists in women after multivariable adjustment.

Association between Lower-to-Upper Ratio of Appendicular Skeletal Muscle and Metabolic Syndrome

(1) Background: Metabolic syndrome (MetS) is a cluster-based disorder comprising several pre-disease or pre-clinical statuses for diabetes, hypertension, dyslipidemia, cardiovascular risk, and mortality. Appendicular skeletal muscle (ASM), or lean mass, is considered the main site of insulin-mediated glucose utilization. Therefore, we aimed to reveal the association between lower appendicular skeletal muscle mass to upper appendicular skeletal muscle mass ratio (LUR) and risk for MetS. (2) Methods: We analyzed the 2008–2011 Korean National Health Examination and Nutrition Survey (KNHANES) data. Quintiles of lower ASM to upper ASM ratio (LUR) were categorized as follows: Q1: ≤2.65, Q2: 2.66–2.80, Q3: 2.81–2.94, Q4: 2.95–3.11, and Q5: ≥3.12 in men and Q1: ≤3.00, Q2: 3.01–3.18, Q3: 3.19–3.36, Q4: 3.37–3.60, and Q5: ≥3.61 in women. Multivariate logistic regression models were used after setting MetS and the LUR quintiles as the independent and dependent variables and adjusting for covariates. (3) Result: In men, MetS in accordance with the LUR quintiles exhibits a reverse J-curve. All groups from Q2 to Q5 had a lower odds ratio (OR) (95% CI) for MetS compared to the Q1 group. The lowest OR (95% CI) of 0.85 (0.80–0.91) was observed in Q4. However, in women, the figure shows a sine curve. Compared to the Q1 group, the Q2 and Q3 groups had a higher OR, while the Q4 and Q5 groups presented a lower OR. Among them, the OR (95% CI) in the Q4 group was lowest, at 0.83 (0.76–0.91). (4) Conclusions: While total appendicular skeletal muscle mass is important to prevent MetS, it is necessary to maintain an optimal ratio of muscle mass between the upper and lower appendicular skeletal muscle mass.