Hongzhi Guo

Mr. Hongzhi Guo

Waseda University, Tokyo, Japan
orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
MWMeiqi Wei
Meiqi Wei
DMDeyu Meng
Deyu Meng
HGHongzhi Guo
Hongzhi Guo
HCHe Shi Chun
He Shi Chun
ZTZhibo Tian
Zhibo Tian
ZWZiheng Wang
Ziheng Wang
Background: Sarcopenia is a geriatric syndrome characterized by decreased skeletal muscle mass and function with age. It is well-established that resistance exercise and Yi Jin Jing improve the skeletal muscle mass of older adults with sarcopenia. Accordingly, we designed an exercise program incorporating resistance exercise and Yi Jin Jing to increase skeletal muscle mass and reverse sarcopenia in older adults. Additionally, machine learning simulations were used to predict the sarcopenia status after the intervention. Method: This randomized controlled trial assessed the effects of sarcopenia in older adults. For 24 weeks, 90 older adults with sarcopenia were divided into intervention groups, including the Yi Jin Jing and resistance training group (YR, n = 30), the resistance training group (RT, n = 30), and the control group (CG, n = 30). Computed tomography (CT) scans of the abdomen were used to quantify the skeletal muscle cross-sectional area at the third lumbar vertebra (L3 SMA). Participants’ age, body mass, stature, and BMI characteristics were analyzed by one-way ANOVA and the chi-squared test for categorical data. This study explored the improvement effect of three interventions on participants’ L3 SMA, skeletal muscle density at the third lumbar vertebra (L3 SMD), skeletal muscle interstitial fat area at the third lumbar vertebra region of interest (L3 SMFA), skeletal muscle interstitial fat density at the third lumbar vertebra (L3 SMFD), relative skeletal muscle mass index (RSMI), muscle fat infiltration (MFI), and handgrip strength. Experimental data were analyzed using two-way repeated-measures ANOVA. Eleven machine learning models were trained and tested 100 times to assess the model’s performance in predicting whether sarcopenia could be reversed following the intervention. Results: There was a significant interaction in L3 SMA (p < 0.05), RSMI (p < 0.05), MFI (p < 0.05), and handgrip strength (p < 0.05). After the intervention, participants in the YR and RT groups showed significant improvements in L3 SMA, RSMI, and handgrip strength. Post hoc tests showed that the YR group (p < 0.05) yielded significantly better L3 SMA and RSMI than the RT group (p < 0.05) and CG group (p < 0.05) after the intervention. Compared with other models, the stacking model exhibits the best performance in terms of accuracy (85.7%) and F1 (75.3%). Conclusion: One hybrid exercise program with Yi Jin Jing and resistance exercise training can improve skeletal muscle area among older adults with sarcopenia. Accordingly, it is possible to predict whether sarcopenia can be reversed in older adults based on our stacking model.

DMDeyu Meng
Deyu Meng
HGHongzhi Guo
Hongzhi Guo
SLsiyu Liang
siyu Liang
ZTZhibo Tian
Zhibo Tian
RWRan Wang
Ran Wang
ZWZiheng Wang
Ziheng Wang
Background: Due to the low physical fitness of the frail elderly, current exercise program strategies have a limited impact. Eight-form Tai Chi has a low intensity, but high effectiveness in the elderly. Inspired by it, we designed an exercise program that incorporates eight-form Tai Chi, strength, and endurance exercises, to improve physical fitness and reverse frailty in the elderly. Additionally, for the ease of use in clinical practice, machine learning simulations were used to predict the frailty status after the intervention. Methods: For 24 weeks, 150 frail elderly people completed the experiment, which comprised the eight-form Tai Chi group (TC), the strength and endurance training group (SE), and a comprehensive intervention combining both TC and SE (TCSE). The comparison of the demographic variables used one-way ANOVA for continuous data and the chi-squared test for categorical data. Two-way repeated measures analysis of variance (ANOVA) was performed to determine significant main effects and interaction effects. Eleven machine learning models were used to predict the frailty status of the elderly following the intervention. Results: Two-way repeated measures ANOVA results before the intervention, group effects of ten-meter maximum walking speed (10 m MWS), grip strength (GS), timed up and go test (TUGT), and the six-minute walk test (6 min WT) were not significant. There was a significant interaction effect of group × time in ten-meter maximum walking speed, grip strength, and the six-minute walk test. Post hoc tests showed that after 24 weeks of intervention, subjects in the TCSE group showed the greatest significant improvements in ten-meter maximum walking speed (p < 0.05) and the six-minute walk test (p < 0.05) compared to the TC group and SE group. The improvement in grip strength in the TCSE group (4.29 kg) was slightly less than that in the SE group (5.16 kg). There was neither a significant main effect nor a significant interaction effect for TUGT in subjects. The stacking model outperformed other algorithms. Accuracy and the F1-score were 67.8% and 71.3%, respectively. Conclusion: A hybrid exercise program consisting of eight-form Tai Chi and strength and endurance exercises can more effectively improve physical fitness and reduce frailty among the elderly. It is possible to predict whether an elderly person will reverse frailty following an exercise program based on the stacking model.

QWQiang Wang
Qiang Wang
HGHongzhi Guo
Hongzhi Guo
SCSitong Chen
Sitong Chen
Jiameng MaJiameng Ma
Jiameng Ma
Hyunshik KimHyunshik Kim
Hyunshik Kim
Body fat mass (FM) has advantages over body mass index (BMI) in terms of accuracy of fitness assessment and health monitoring. However, the relationship between FM and fitness in Chinese children has not yet been well studied. This study aimed to investigate the relationship between health-related physical fitness, BMI, and FM, which was estimated using a predictive model among elementary schoolchildren in China. This cross-sectional study included 2677 participants (boys, 53.6%; girls, 46.4%) who underwent anthropometric measurements (height, weight, BMI, and FM) and five health-related fitness tests: 50-m sprint (speed), sit and reach (flexibility), timed rope-skipping (coordination), timed sit-ups (muscular endurance), and 50-m × 8 shuttle run (endurance). In boys, BMI showed a positive correlation with speed (p < 0.001) and endurance (p < 0.006) tests and a negative correlation with flexibility (p < 0.004) and coordination (p < 0.001) tests. In girls, a positive correlation between speed (p < 0.001) and endurance (p < 0.036) tests was observed. Both BMI and FM (estimated using the predictive model) were strongly associated with the health-related physical fitness of elementary schoolchildren. Our findings indicate that health-related physical fitness was similarly affected by FM and BMI. As FM can be quantified, it could therefore be used to develop strategies and intervention programs for the prevention and management of obesity in children.

HGHongzhi Guo
Hongzhi Guo
Jiameng MaJiameng Ma
Jiameng Ma
TCTerence Chua
Terence Chua
LTLee Yong Tay
Lee Yong Tay
Michael ChiaMichael Chia
Michael Chia
Hyunshik KimHyunshik Kim
Hyunshik Kim
The 24-hour movement guidelines (24-h MG) recommend behaviors (physical activity, screen time, sleep) to aid appropriate physical and mental development in early childhood. This research examined parents’ digital media habits (DMH), engagement (DME), and awareness (DMA) among parents in relation to their preschool-aged children’s 24-h MG in Japan and identified and compared the modifiable determinants of adherence to 24-h MG in urban and rural regions. This cross-sectional study included 867 participants and data were obtained from the International Ipreschooler Surveillance Study Among Asians and OtheRs (IISSAAR). The results revealed that adherence to weekend screen time recommendations and weekday sleep duration were higher in the urban region. The parents’ digital media variables that predicted moderate-intensity to vigorous-intensity physical activity among preschool-aged children were parents’ DME and DMA in the urban regions and parents’ DME in the rural regions. The children’s screen time was significantly associated with parents’ DMH, DME, and DMA in the urban regions and with parents’ DMH and DMA in the rural regions (p < 0.005, p < 0.001, respectively). This study confirmed that parents’ DMH, DME, and DMA are strong predictors of adherence to 24-h MG among preschool-aged children living in both rural and urban regions in Japan.

15 November 2024 in JMIR Aging
Verified
Journal Article
Open access
HGHongzhi Guo
Hongzhi Guo
JCJianwei Cao
Jianwei Cao
HCHe Shi Chun
He Shi Chun
MWMeiqi Wei
Meiqi Wei
DMDeyu Meng
Deyu Meng
ZWZiheng Wang
Ziheng Wang
Background: Sarcopenia is characterized by the loss of skeletal muscle mass and muscle function with increasing age. The skeletal muscle mass of older people who endure sarcopenia may be improved via the practice of strength training and tai chi. However, it remains unclear if the hybridization of strength exercise training and traditional Chinese exercise will have a better effect. Objective: We designed a strength training and tai chi exercise hybrid program to improve sarcopenia in older people. Moreover, explainable artificial intelligence was used to predict postintervention sarcopenic status and quantify the feature contribution. Methods: To assess the influence of sarcopenia in the older people group, 93 participated as experimental participants in a 24-week randomized controlled trial and were randomized into 3 intervention groups, namely the tai chi exercise and strength training hybrid group (TCSG; n=33), the strength training group (STG; n=30), and the control group (n=30). Abdominal computed tomography was used to evaluate the skeletal muscle mass at the third lumbar (L3) vertebra. Analysis of demographic characteristics of participants at baseline used 1-way ANOVA and χ2 tests, and repeated-measures ANOVA was used to analyze experimental data. In addition, 10 machine-learning classification models were used to calculate if these participants could reverse the degree of sarcopenia after the intervention. Results: A significant interaction effect was found in skeletal muscle density at the L3 vertebra, skeletal muscle area at the L3 vertebra (L3 SMA), grip strength, muscle fat infiltration, and relative skeletal muscle mass index (all P values were <.05). Grip strength, relative skeletal muscle mass index, and L3 SMA were significantly improved after the intervention for participants in the TCSG and STG (all P values were <.05). After post hoc tests, we found that participants in the TCSG experienced a better effect on L3 SMA than those in the STG and participants in the control group. The LightGBM classification model had the greatest performance in accuracy (88.4%), recall score (74%), and F1-score (76.1%). Conclusions: The skeletal muscle area of older adults with sarcopenia may be improved by a hybrid exercise program composed of strength training and tai chi. In addition, we identified that the LightGBM classification model had the best performance to predict the reversion of sarcopenia.

ZWziyi wang
ziyi wang
DMDeyu Meng
Deyu Meng
HCHe Shi Chun
He Shi Chun
HGHongzhi Guo
Hongzhi Guo
ZTZhibo Tian
Zhibo Tian
ZWZiheng Wang
Ziheng Wang
Background: Frailty is a serious physical disorder affecting the elderly all over the world. However, the frail elderly have low physical fitness, which limits the effectiveness of current exercise programs. Inspired by this, we attempted to integrate Baduanjin and strength and endurance exercises into an exercise program to improve the physical fitness and alleviate frailty among the elderly. Additionally, to achieve the goals of personalized medicine, machine learning simulations were performed to predict post-intervention frailty. Methods: A total of 171 frail elderly individuals completed the experiment, including a Baduanjin group (BDJ), a strength and endurance training group (SE), and a combination of Baduanjin and strength and endurance training group (BDJSE), which lasted for 24 weeks. Physical fitness was evaluated by 10-meter maximum walk speed (10 m MWS), grip strength, the timed up-and-go test (TUGT), and the 6 min walk test (6 min WT). A one-way analysis of variance (ANOVA), chi-square test, and two-way repeated-measures ANOVA were carried out to analyze the experimental data. In addition, nine machine learning models were utilized to predict the frailty status after the intervention. Results: In 10 m MWS and TUGT, there was a significant interactive influence between group and time. When comparing the BDJ group and the SE group, participants in the BDJSE group demonstrated the maximum gains in 10 m MWS and TUGT after 24 weeks of intervention. The stacking model surpassed other algorithms in performance. The accuracy and precision rates were 75.5% and 77.1%, respectively. Conclusion: The hybrid exercise program that combined Baduanjin with strength and endurance training proved more effective at improving fitness and reversing frailty in elderly individuals. Based on the stacking model, it is possible to predict whether an elderly person will exhibit reversed frailty following an exercise program.