Jiaolong Ma

Prof. Jiaolong Ma


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

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

Representative Publications

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18 May 2024 in Biological Trace Element Research
Verified
Journal Article
Closed access
PDF file
PXPanpan Xu
Panpan Xu
HXHengrui Xing
Hengrui Xing
YMYue Ma
Yue Ma
XDXueman Ding
Xueman Ding
TLTingting Li
Tingting Li
QNQiang Niu
Qiang Niu

18 July 2025 in Journal of Environmental Sciences
Verified
Journal Article
Closed access
XDXueman Ding
Xueman Ding
LLLi Liu
Li Liu
ZLZhaochun Liu
Zhaochun Liu
SZShurui Zuo
Shurui Zuo
YHYu Huang
Yu Huang
QNQiang Niu
Qiang Niu

28 August 2026 in BMC Endocrine Disorders
Verified
Journal Article
Open access
PDF file
MXMenghuan Xiao
Menghuan Xiao
ZWZhiyu Wu
Zhiyu Wu
ZLZhaochun Liu
Zhaochun Liu
YTYingjie Tian
Yingjie Tian
YHYu Huang
Yu Huang
JMJiaolong Ma
Jiaolong Ma
To investigate the ratio of uric acid (UA) to high-density lipoprotein cholesterol (HDL-C) (UHR) in early pregnancy and the risk of gestational diabetes me

18 September 2026 in Nutrients
Verified
Journal Article
Open access
PDF file
LZLi Zhang
Li Zhang
LWLu Wang
Lu Wang
CYChun-Jie Yin
Chun-Jie Yin
YDYuqi Duan
Yuqi Duan
JMJiaolong Ma
Jiaolong Ma
HWHaijun Wang
Haijun Wang
Background/Objectives: Few paediatric obesity trials have examined behavioural mediators of intervention effects on detailed body composition outcomes beyond body mass index (BMI). Given the complexity of multiple correlated body composition indicators, this study aimed to employ principal component analysis (PCA) to derive a composite adiposity factor and to apply mediation analysis to identify whether changes in dietary behaviours and physical activity mediated the effects of the DECIDE-Children intervention on body composition. Methods: This study included 1180 children from a 9-month cluster-randomised controlled trial that delivered a multifaceted, digitally assisted intervention targeting children (health education, physical activity reinforcement, and app-based BMI monitoring/feedback) and their environments (school food policies and family engagement). Outcomes were changes in body composition (whole-body and trunk fat mass, fat-free mass, and muscle mass indices measured by bioelectrical impedance analysis). Potential mediators included changes in dietary behaviour, screen time, and moderate-to-vigorous physical activity (MVPA), assessed via validated questionnaires. PCA was used to reduce the dimensionality of body composition variables and to derive a composite adiposity factor (PCA_1), with higher values indicating greater adiposity and lower muscle mass. Mediation was tested using linear mixed-effects models adjusted for age, sex, and region. Results: The intervention significantly reduced adiposity indicators (e.g., whole-body and trunk fat mass percentage decreased by 1.003%, and PCA_1 decreased by 0.942 SD) and concurrently increased fat-free mass percentage and muscle mass percentage at both whole-body and trunk levels. Dietary behaviour significantly mediated the intervention effects on all body composition outcomes (e.g., mediating 16.1% of the effect on PCA_1), whereas physical activity (both screen time and MVPA) showed no mediation. Sensitivity analyses supported the primary findings. Conclusions: The DECIDE-Children intervention improved body composition by reducing adiposity and increasing fat-free and muscle mass percentage, effects primarily mediated by dietary behaviour. These findings highlight dietary behaviour as a key component in paediatric obesity intervention.