Visceral fat and cardiorespiratory fitness with prevalence of pre-diabetes/diabetes mellitus among middle-aged and elderly Japanese people: WASEDA'S Health Study

Polygenic Risk Score, Cardiorespiratory Fitness, and Cardiometabolic Risk Factors: WASEDA'S Health Study

PURPOSE

This study estimated an individual's genetic liability to cardiometabolic risk factors by polygenic risk score (PRS) construction and examined whether high cardiorespiratory fitness (CRF) modifies the association between PRS and cardiometabolic risk factors.

METHODS

This cross-sectional study enrolled 1296 Japanese adults aged ≥40 yr. The PRS for each cardiometabolic trait (blood lipids, glucose, hypertension, and obesity) was calculated using the LDpred2 and clumping and thresholding methods. Participants were divided into low-, intermediate-, and high-PRS groups according to PRS tertiles for each trait. CRF was quantified as peak oxygen uptake (V̇O 2peak ) per kilogram body weight. Participants were divided into low-, intermediate-, and high-CRF groups according to the tertile V̇O 2peak value.

RESULTS

Linear regression analysis revealed a significant interaction between PRS for triglyceride (PRS TG ) and CRF groups on serum TG levels regardless of the PRS calculation method, and the association between PRS TG and TG levels was attenuated in the high-CRF group. Logistic regression analysis revealed a significant sub-additive interaction between LDpred2 PRS TG and CRF on the prevalence of high TG, indicating that high CRF attenuated the genetic predisposition to high TG. Furthermore, a significant sub-additive interaction between PRS for body mass index and CRF on obesity was detected regardless of the PRS calculation method. These significant interaction effects on high TG and obesity were diminished in the sensitivity analysis using V̇O 2peak per kilogram fat-free mass as the CRF index. Effects of PRSs for other cardiometabolic traits were not significantly attenuated in the high-CRF group regardless of PRS calculation methods.

CONCLUSIONS

The findings of the present study suggest that individuals with high CRF overcome the genetic predisposition to high TG levels and obesity.

Healthy Japanese dietary pattern is associated with slower biological aging in older men: WASEDA'S health study

Aging is the greatest risk factor for numerous diseases and mortality, and establishing geroprotective interventions targeting aging is required. Previous studies have suggested that healthy dietary patterns, such as the Mediterranean diet, are associated with delayed biological aging; however, these associations depend on nationality and sex. Therefore, this study aimed to investigate the relationship between dietary patterns identified through principal component analysis and biological aging in older men of Japan, one of the countries with the longest life expectancies. Principal component analysis identified two dietary patterns: a healthy Japanese dietary pattern and a Western-style dietary pattern. Eight epigenetic clocks, some of the most accurate aging biomarkers, were identified using DNA methylation data from whole-blood samples. Correlation analyses revealed that healthy Japanese dietary patterns were significantly negatively or positively correlated with multiple epigenetic age accelerations (AgeAccel), including AgeAccelGrim, FitAgeAccel, and age-adjusted DNAm-based telomere length (DNAmTLAdjAge). Conversely, the Western-style dietary pattern was observed not to correlate significantly with any of the examined AgeAccels or age-adjusted values. After adjusting for covariates, the healthy Japanese dietary pattern remained significantly positively correlated with DNAmTLAdjAge. Regression analysis showed that healthy Japanese dietary pattern contributed less to epigenetic age acceleration than smoking status. These findings suggest that a Western-style dietary pattern may not be associated with biological aging, whereas a healthy Japanese dietary pattern is associated with delayed biological aging in older Japanese men. Our findings provide evidence that healthy dietary patterns may have mild beneficial effects on delayed biological aging in older Japanese men.

Cardiorespiratory fitness and metabolic risk in Chinese population: evidence from a prospective cohort study

BACKGROUND

Studies on the association between estimated cardiorespiratory fitness (CRF) and changes in metabolic risk in the Chinese population are limited. This study aims to examine the associations between CRF and changes in metabolic risk.

SUBJECTS AND METHODS

We included 4,862 and 2,700 participants recruited from 28 provinces in the China Health and Retirement Longitudinal Study (CHARLS) in the baseline (Wave 1) and follow-up (Wave 4) analyses, respectively. CRF was calculated using sex-specific longitudinal non-exercise equations. Metabolic indicators included systolic blood pressure (SBP), diastolic blood pressure (DBP), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and fasting plasma glucose (FPG) levels. The metabolic score was calculated as the number of changes in the above metabolic indicators above the 75th percentile of the distribution of changes (equal to or below the 25th percentile for HDL-C).

RESULTS

In the baseline analysis, CRF was negatively associated with SBP, DBP, TG, and FPG, and positively correlated with HDL-C after adjusting for age, smoking status, and drinking status (all P < 0.0001) in both males and females. In the follow-up analysis, higher baseline CRF was significantly related to a decrease in SBP, DBP, TG, FPG, and metabolic score (all P < 0.0005), and increased HDL-C (P < 0.0001) after further adjustment for corresponding baseline metabolic indicators. The associations remained significant after stratification by sex, except for the changes in HDL-C levels in females. Furthermore, improved CRF was associated with favorable changes in DBP, TG, HDL-C, FPG, and metabolic scores in all populations and males. Significant associations between changes in CRF and DBP, TG, and FPG levels were found in females.

CONCLUSION

Higher baseline CRF and improved CRF were associated with favorable changes in metabolic indicators.

Associations between cardiorespiratory fitness and lifestyle-related factors with DNA methylation-based ageing clocks in older men: WASEDA'S Health Study

DNA methylation-based age estimators (DNAm ageing clocks) are currently one of the most promising biomarkers for predicting biological age. However, the relationships between cardiorespiratory fitness (CRF), measured directly by expiratory gas analysis, and DNAm ageing clocks are largely unknown. We investigated the relationships between CRF and the age-adjusted value from the residuals of the regression of DNAm ageing clock to chronological age (DNAmAgeAcceleration: DNAmAgeAccel) and attempted to determine the relative contribution of CRF to DNAmAgeAccel in the presence of other lifestyle factors. DNA samples from 144 Japanese men aged 65-72 years were used to appraise first- (i.e., DNAmHorvath and DNAmHannum) and second- (i.e., DNAmPhenoAge, DNAmGrimAge, and DNAmFitAge) generation DNAm ageing clocks. Various surveys and measurements were conducted, including physical fitness, body composition, blood biochemical parameters, nutrient intake, smoking, alcohol consumption, disease status, sleep status, and chronotype. Both oxygen uptake at ventilatory threshold (VO2 /kg at VT) and peak oxygen uptake (VO2 /kg at Peak) showed a significant negative correlation with GrimAgeAccel, even after adjustments for chronological age and smoking and drinking status. Notably, VO2 /kg at VT and VO2 /kg at Peak above the reference value were also associated with delayed GrimAgeAccel. Multiple regression analysis showed that calf circumference, serum triglyceride, carbohydrate intake, and smoking status, rather than CRF, contributed more to GrimAgeAccel and FitAgeAccel. In conclusion, although the contribution of CRF to GrimAgeAccel and FitAgeAccel is relatively low compared to lifestyle-related factors such as smoking, the results suggest that the maintenance of CRF is associated with delayed biological ageing in older men.

Comparison of bioelectrical body and visceral fat indices and anthropometric measures in relation to type 2 diabetes by sex among Chinese adults, a cross-sectional study

Objectives

We aim to compare the efficacies of the bioelectrical indices (percentage of body fat, PBF; visceral fat area, VFA) with the conventional anthropometric measures (body mass index, BMI; waist-hip ratio, WHR) for predicting type 2 diabetes (T2D) risk by sex and to determine the sex-specific optimal adiposity indices to predict the T2D risk.

Design

Cross-sectional design.

Setting

Tianjin First Central Hospital and Tianjin Union Medical Center, Tianjin, China.

Participants

A total of 9,332 adults (41.35% men) undergoing physical examination.

Primary and secondary outcome measures

T2D was defined using the WHO's criteria: fasting blood glucose (FBG) ≥7.0 mmol/L and/or previous diagnosis of T2D. Height, weight, waist, hip, PBF, VFA, and fasting plasma glucose were measured.

Results

All studied adiposity indices were associated with T2D among both males and females, and the observed associations differed by sex. The standardized aORs of BMI, WHR, PBF and VFA for T2D were 1.60 (95% CI 1.42-1.81), 1.43 (95% CI 1.25-1.64), 1.42 (95% CI 1.23-1.62) and 1.53 (95% CI 1.35-1.75) for females, and 1.47 (95% CI 1.31-1.66), 1.40 (95% CI 1.25-1.58), 1.54 (95% CI 1.36-1.74) and 1.47 (95% CI 1.31-1.65) for males, respectively. The AUCs of VFA, WHR and BMI were 0.743, 0.742 and 0.717 in women, respectively, whereas none of the indices had AUC larger than 0.70 in men. The AUCs were not significantly different between VFA and WHR, while both demonstrate larger AUCs than BMI and PBF in females (all p < 0.05). The optimal cutoff values of VFA, WHR, and BMI for T2D in women were 103.55 cm2, 0.905, and 24.15 kg/m2, respectively.

Conclusion

Although BMI, WHR, and PBF and VFA as measured by bioelectrical impedance analysis (BIA) were all positively associated with T2D, their efficacy for predicting the risk of T2D differed by sex. VFA, WHR and BMI could be used as biomarkers to predict T2D risk in women, however none of the study indicators demonstrated favorable efficacy of predicting T2D risk in men.

Development and validation of a simple anthropometric equation to predict appendicular skeletal muscle mass

BACKGROUND & AIMS

A limited number of studies have developed simple anthropometric equations that can be implemented for predicting muscle mass in the local community. Several studies have suggested calf circumference as a simple and accurate surrogate maker for muscle mass. We aimed to develop and cross-validate a simple anthropometric equation, which incorporates calf circumference, to predict appendicular skeletal muscle mass (ASM) using dual-energy X-ray absorptiometry (DXA). Furthermore, we conducted a comparative validity assessment of our equation with bioelectrical impedance analysis (BIA) and two previously reported equations using similar variables.

METHODS

ASM measurements were recorded for 1262 participants (837 men, 425 women) aged 40 years or older. Participants were randomly divided into the development or validation group. Stepwise multiple linear regression was applied to develop the DXA-measured ASM prediction equation. Parameters including age, sex, height, weight, waist circumference, and calf circumference were incorporated as predictor variables. Total error was calculated as the square root of the sum of the square of the difference between DXA-measured and predicted ASMs divided by the total number of individuals.

RESULTS

The most optimal ASM prediction equation developed was: ASM (kg) = 2.955 × sex (men = 1, women = 0) + 0.255 × weight (kg) - 0.130 × waist circumference (cm) + 0.308 × calf circumference (cm) + 0.081 × height (cm) - 11.897 (adjusted R² = 0.94, standard error of the estimate = 1.2 kg). Our equation had smaller total error and higher intraclass correlation coefficient (ICC) values than those for BIA and two previously reported equations, for both men and women (men, total error = 1.2 kg, ICC = 0.91; women, total error = 1.1 kg, ICC = 0.80). The correlation between DXA-measured ASM and predicted ASM by the present equation was not significantly different from the correlation between DXA-measured ASM and BIA-measured ASM.

CONCLUSIONS

The equation developed in this study can predict ASM more accurately as compared to equations where calf circumference is used as the sole variable and previously reported equations; it holds potential as a reliable and an effective substitute for estimating ASM.

Determinants of Resting Oxidative Stress in Middle-Aged and Elderly Men and Women: WASEDA'S Health Study

Previous studies have not investigated the determinants of resting oxidative stress, including physical fitness, as it relates to redox regulation. The present study therefore was aimed at identifying lifestyle and biological factors that determine resting oxidative stress, including objectively measured physical fitness. In 873 middle-aged and elderly men and women, age and anthropometric parameters, lifestyle-related parameters, medication and supplementation status, physical fitness, biochemical parameters, and nutritional intake status, as well as three plasma oxidative stress markers: protein carbonyl (PC), F₂-isoprostane (F₂-IsoP), and thiobarbituric acid reactive substances (TBARS), were surveyed and measured. The determinants of PC, F₂-IsoP, and TBARS in all participants were investigated using stepwise multiple regression analysis. In PC, age (β = −0.11, P = 0.002), leg extension power (β = −0.12, P = 0.008), BMI (β = 0.12, P = 0.004), and HDL-C (β = 0.08, P = 0.040) were included in the regression model (adjusted R² = 0.018). In the F₂-IsoP, smoking status (β = 0.07, P = 0.060), BMI (β = 0.07, P = 0.054), and HbA1c (β = −0.06, P = 0.089) were included in the regression model (adjusted R² = 0.006). In TBARS, glucose (β = 0.18, P < 0.001), CRF (β = 0.16, P < 0.001), age (β = 0.15, P < 0.001), TG (β = 0.11, P = 0.001), antioxidant supplementation (β = 0.10, P = 0.002), and HbA1c (β = −0.13, P = 0.004) were included in the regression model (adjusted R² = 0.071). In conclusion, the present study showed that age, anthropometric index, lifestyle-related parameters, medication and supplementation status, objectively measured physical fitness, biochemical parameters, and nutritional intake status explain less than 10% of oxidative stress at rest.