1.Expert Consensus on the Ethical Requirements for Generative AI-Assisted Academic Writing
You-Quan BU ; Yong-Fu CAO ; Zeng-Yi CHANG ; Hong-Yu CHEN ; Xiao-Wei CHEN ; Yuan-Yuan CHEN ; Zhu-Cheng CHEN ; Rui DENG ; Jie DING ; Zhong-Kai FAN ; Guo-Quan GAO ; Xu GAO ; Lan HU ; Xiao-Qing HU ; Hong-Ti JIA ; Ying KONG ; En-Min LI ; Ling LI ; Yu-Hua LI ; Jun-Rong LIU ; Zhi-Qiang LIU ; Ya-Ping LUO ; Xue-Mei LV ; Yan-Xi PEI ; Xiao-Zhong PENG ; Qi-Qun TANG ; You WAN ; Yong WANG ; Ming-Xu WANG ; Xian WANG ; Guang-Kuan XIE ; Jun XIE ; Xiao-Hua YAN ; Mei YIN ; Zhong-Shan YU ; Chun-Yan ZHOU ; Rui-Fang ZHU
Chinese Journal of Biochemistry and Molecular Biology 2025;41(6):826-832
With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.
2.Study on the association between compound hot extremes and fall death risk in three provinces of southern China
Linlin XIE ; Jiamei ZENG ; Jie WAN ; Zihang TANG ; Ruilin MENG ; Chunliang ZHOU ; Min YU ; Yi LIN ; Weiquan ZENG ; Wenjun MA ; Guanhao HE
Chinese Journal of Epidemiology 2025;46(4):581-586
Objective:To explore the risk fall death associated with compound hot extremes.Methods:This study collected data on fall deaths in Guangdong, Hunan, and Zhejiang Provinces from 2013 to 2018 and matched their exposure to meteorological data. Based on a time-stratified case-crossover design, a conditional logistic regression model embedded with a cross-basis function of the distributed lag nonlinear model was applied to estimate the risk of fall to death due to compound hot extremes.Results:Compared with regular days, compound hot extremes significantly increased the risk of death from falls ( OR=1.19, 95% CI: 1.09-1.30), and women ( OR=1.27, 95% CI: 1.11-1.45) and the elderly age 65 and above ( OR=1.24, 95% CI: 1.12-1.39) were more sensitive to compound hot extremes. The maximum duration of compound hot extremes was 7 days, and the maximum intensity was 6.2 ℃, and the duration and intensity were proportional to the risk of death from falls. The risk of death from falls increased by 12% ( OR=1.12, 95% CI: 1.06-1.18) each day, increasing in duration after linearization. The risk of death from falls increased by 16% ( OR=1.16, 95% CI: 1.10-1.22) for each 1 ℃ increase in linearized intensity. Conclusion:Compound hot extremes increase the risk of death cases from falls.
3.Study on the association between compound hot extremes and fall death risk in three provinces of southern China
Linlin XIE ; Jiamei ZENG ; Jie WAN ; Zihang TANG ; Ruilin MENG ; Chunliang ZHOU ; Min YU ; Yi LIN ; Weiquan ZENG ; Wenjun MA ; Guanhao HE
Chinese Journal of Epidemiology 2025;46(4):581-586
Objective:To explore the risk fall death associated with compound hot extremes.Methods:This study collected data on fall deaths in Guangdong, Hunan, and Zhejiang Provinces from 2013 to 2018 and matched their exposure to meteorological data. Based on a time-stratified case-crossover design, a conditional logistic regression model embedded with a cross-basis function of the distributed lag nonlinear model was applied to estimate the risk of fall to death due to compound hot extremes.Results:Compared with regular days, compound hot extremes significantly increased the risk of death from falls ( OR=1.19, 95% CI: 1.09-1.30), and women ( OR=1.27, 95% CI: 1.11-1.45) and the elderly age 65 and above ( OR=1.24, 95% CI: 1.12-1.39) were more sensitive to compound hot extremes. The maximum duration of compound hot extremes was 7 days, and the maximum intensity was 6.2 ℃, and the duration and intensity were proportional to the risk of death from falls. The risk of death from falls increased by 12% ( OR=1.12, 95% CI: 1.06-1.18) each day, increasing in duration after linearization. The risk of death from falls increased by 16% ( OR=1.16, 95% CI: 1.10-1.22) for each 1 ℃ increase in linearized intensity. Conclusion:Compound hot extremes increase the risk of death cases from falls.
4.Guideline for Adult Weight Management in China
Weiqing WANG ; Qin WAN ; Jianhua MA ; Guang WANG ; Yufan WANG ; Guixia WANG ; Yongquan SHI ; Tingjun YE ; Xiaoguang SHI ; Jian KUANG ; Bo FENG ; Xiuyan FENG ; Guang NING ; Yiming MU ; Hongyu KUANG ; Xiaoping XING ; Chunli PIAO ; Xingbo CHENG ; Zhifeng CHENG ; Yufang BI ; Yan BI ; Wenshan LYU ; Dalong ZHU ; Cuiyan ZHU ; Wei ZHU ; Fei HUA ; Fei XIANG ; Shuang YAN ; Zilin SUN ; Yadong SUN ; Liqin SUN ; Luying SUN ; Li YAN ; Yanbing LI ; Hong LI ; Shu LI ; Ling LI ; Yiming LI ; Chenzhong LI ; Hua YANG ; Jinkui YANG ; Ling YANG ; Ying YANG ; Tao YANG ; Xiao YANG ; Xinhua XIAO ; Dan WU ; Jinsong KUANG ; Lanjie HE ; Wei GU ; Jie SHEN ; Yongfeng SONG ; Qiao ZHANG ; Hong ZHANG ; Yuwei ZHANG ; Junqing ZHANG ; Xianfeng ZHANG ; Miao ZHANG ; Yifei ZHANG ; Yingli LU ; Hong CHEN ; Li CHEN ; Bing CHEN ; Shihong CHEN ; Guiyan CHEN ; Haibing CHEN ; Lei CHEN ; Yanyan CHEN ; Genben CHEN ; Yikun ZHOU ; Xianghai ZHOU ; Qiang ZHOU ; Jiaqiang ZHOU ; Hongting ZHENG ; Zhongyan SHAN ; Jiajun ZHAO ; Dong ZHAO ; Ji HU ; Jiang HU ; Xinguo HOU ; Bimin SHI ; Tianpei HONG ; Mingxia YUAN ; Weibo XIA ; Xuejiang GU ; Yong XU ; Shuguang PANG ; Tianshu GAO ; Zuhua GAO ; Xiaohui GUO ; Hongyi CAO ; Mingfeng CAO ; Xiaopei CAO ; Jing MA ; Bin LU ; Zhen LIANG ; Jun LIANG ; Min LONG ; Yongde PENG ; Jin LU ; Hongyun LU ; Yan LU ; Chunping ZENG ; Binhong WEN ; Xueyong LOU ; Qingbo GUAN ; Lin LIAO ; Xin LIAO ; Ping XIONG ; Yaoming XUE
Chinese Journal of Endocrinology and Metabolism 2025;41(11):891-907
Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.
5.Study on the association between systemic immune-inflammation index and metabolic types and characteristics of obesity in children and adolescents
Jiayi WAN ; Shiyun LUO ; Jie HUANG ; Wanzhen ZHONG ; Guixian TAO ; Chunzi ZENG ; Jiaying GUO ; Weiwei ZHANG ; Jing GU ; Yan LI
Chinese Journal of Preventive Medicine 2025;59(11):1916-1923
Objective:To explore the association between the systemic immune-inflammation index (SII) and obesity metabolic phenotypes, as well as metabolic features in children and adolescents.Methods:A cross-sectional study was conducted using the random cluster sampling method from March 2023 to May 2024. Children and adolescents aged 9-17 years in Guangzhou were surveyed through questionnaires, physical measurements, and blood tests. According to BMI and metabolic status, participants were classified into normal-weight groups [metabolically healthy normal weight (MHNW) and metabolically unhealthy normal weight (MUNW)] and overweight/obese groups [metabolically healthy overweight/obese (MHO/O) and metabolically unhealthy overweight/obese (MUO/O)]. After natural log-transformation of SII values (lnSII), multinomial logistic regression was used to assess the association between SII and obesity metabolic phenotypes, while binary logistic regression was applied to assess the relationship between SII and metabolic phenotypes in the overweight/obese subgroup. Linear regression model and restricted cubic spline (RCS) were employed to examine the relationship between SII and metabolic features among the entire population.Results:A total of 3 749 participants were included. After adjusting for covariates, for every unit increase in lnSII, the risk of MHO/O and MUO/O increased by 93% ( OR=1.93, 95% CI: 1.56-2.40, P<0.001) and 156% ( OR=2.56, 95% CI: 2.02-3.25, P<0.001), respectively. In the overweight/obesity subgroup, for every unit increase in lnSII, the risk of MUO/O increased by 37% ( OR=1.37, 95% CI: 1.01-1.87, P=0.045). Linear regression model and RCS showed that lnSII was positively correlated with systolic blood pressure (SBP) and diastolic blood pressure (DBP) (SBP: β=1.39, 95% CI: 0.67-2.11, P<0.001; DBP: β=1.27, 95% CI: 0.79-1.75, P<0.001). lnSII also had a non-linear relationship with triglyceride ( Pnonlinear=0.032) and high-density lipoprotein cholesterol ( Pnonlinear=0.002). Conclusion:Elevated SII levels are associated with unfavorable obesity metabolic phenotypes, higher blood pressure, and altered lipid profiles in children and adolescents. SII may be a potential driving factor for metabolic heterogeneity in children and adolescents.
6.Role of miR-140-5p/BCL2L1 in apoptosis and autophagy of HFOB1.19 and effect of Bushen Jianpi Huoxue Decoction.
Tong-Ying CHEN ; Sai FU ; Xiao-Yun LI ; Shu-Hua LIU ; Yi-Fu YANG ; Dong-Sheng YANG ; Yun-Jie ZENG ; Yang-Bo LI ; Dan LUO ; Hong-Xing HUANG ; Lei WAN
China Journal of Chinese Materia Medica 2025;50(3):583-589
Osteoporosis(OP) is a senile bone disease characterized by an imbalance between bone remodeling and bone formation. Targeting pathogenesis of kidney deficiency, spleen deficiency, and blood stasis, Bushen Jianpi Huoxue Decoction has a significant effect on the treatment of OP by tonifying kidney, invigorating spleen, and activating blood circulation. MicroRNA(miRNA) and the anti-apoptotic protein B-cell lymphoma-2-like protein 1(BCL2L1) are closely related to bone cell metabolism. Therefore, in this study, the binding of miR-140-5p to BCL2L1 was detected by dual luciferase assay and polymerase chain reaction(PCR). After silencing or overexpressing miR-140-5p, the apoptosis, autophagy, and osteogenic function of human fetal osteoblast cell line 1.19(HFOB1.19) were observed by flow cytometry and Western blot. Bushen Jianpi Huoxue Decoction-containing serum was prepared by intragastric administration of Bushen Jianpi Huoxue Decoction in rats. Different concentrations of Bushen Jianpi Huoxue Decoction-containing serum were used to treat HFOB1.19 with or without miR-140-5p mimic. The expression of osteogenic proteins in each group was observed, and the role of miR-140-5p/BCL2L1 in apoptosis and autophagy of HFOB1.19 was studied, along with the effect of Bushen Jianpi Huoxue Decoction on these processes. As indicated by the dual luciferase assay, miR-140-5p bound to BCL2L1. Flow cytometry and Western blot showed that miR-140-5p promoted apoptosis and inhibited autophagy in HFOB1.19. After intervention with high, medium, and low doses of Bushen Jianpi Huoxue Decoction-medicated serum, compared with the miR-140-5p NC group, the expression of osteocalcin(OCN), osteopontin(OPN), Runt-related transcription factor 2(RUNX2), and transforming growth factor beta 1(TGF-β1) decreased in the miR-140-5p mimic group, while the expression of bone morphogenetic protein 2(BMP2) showed no significant difference under high-dose intervention. Therefore, miR-140-5p/BCL2L1 can promote apoptosis and inhibit autophagy in HFOB1.19. Bushen Jianpi Huoxue Decoction can affect the osteogenic effect of miR-140-5p through BMP2.
MicroRNAs/metabolism*
;
Autophagy/drug effects*
;
Apoptosis/drug effects*
;
Humans
;
Drugs, Chinese Herbal/administration & dosage*
;
Animals
;
Cell Line
;
bcl-X Protein/metabolism*
;
Osteoblasts/metabolism*
;
Rats
;
Osteoporosis/physiopathology*
;
Male
;
Rats, Sprague-Dawley
;
Osteogenesis/drug effects*
7.Tongmai Hypoglycemic Capsule Attenuates Myocardial Oxidative Stress and Fibrosis in the Development of Diabetic Cardiomyopathy in Rats.
Jie-Qiong ZENG ; Hui-Fen ZHOU ; Hai-Xia DU ; Yu-Jia WU ; Qian-Ping MAO ; Jun-Jun YIN ; Hai-Tong WAN ; Jie-Hong YANG
Chinese journal of integrative medicine 2025;31(3):251-260
OBJECTIVE:
To investigate the effect of Tongmai Hypoglycemic Capsule (THC) on myocardium injury in diabetic cardiomyopathy (DCM) rats.
METHODS:
A total of 24 Sprague Dawley rats were fed for 4 weeks with high-fat and high-sugar food and then injected with streptozotocin intraperitoneally for the establishment of the DCM model. In addition, 6 rats with normal diets were used as the control group. After modeling, 24 DCM rats were randomly divided into the model, L-THC, M-THC, and H-THC groups by computer generated random numbers, and 0, 0.16, 0.32, 0.64 g/kg of THC were adopted respectively by gavage, with 6 rats in each group. After 12 weeks of THC administration, echocardiography, histopathological staining, biochemical analysis, and Western blot were used to detect the changes in myocardial structure, oxidative stress (OS), biochemical indexes, protein expressions of myocardial fibrosis, and nuclear factor erythroid 2-related faactor 2 (Nrf2) element, respectively.
RESULTS:
Treatment with THC significantly decreased cardiac markers such as creatine kinase, lactate dehydrogenase, and creatine kinase-MB, etc., (P<0.01); enhanced cardiac function indicators including heart rate, ejection fraction, cardiac output, interventricular septal thickness at diastole, and others (P<0.05 or P<0.01); decreased levels of biochemical indicators such as fasting blood glucose, total cholesterol, triglycerides, low-density lipoprotein cholesterol, aspartate transaminase, (P<0.05 or P<0.01); and decreased the levels of myocardial fibrosis markers α-smooth muscle actin (α-SMA), and collagen I (Col-1) protein (P<0.01), improved myocardial morphology and the status of myocardial interstitial fibrosis. THC significantly reduced malondialdehyde levels in model rats (P<0.01), increased levels of catalase, superoxide dismutase, and glutathione (P<0.01), and significantly increased the expression of Nrf2, NAD(P)H:quinone oxidoreductase 1, heme oxygenase-1, and superoxide dismutase 2 proteins in the left ventricle of rats (P<0.01).
CONCLUSION
THC activates the Nrf2 signaling pathway and plays a protective role in reducing OS injury and cardiac fibrosis in DCM rats.
Animals
;
Diabetic Cardiomyopathies/physiopathology*
;
Oxidative Stress/drug effects*
;
Drugs, Chinese Herbal/therapeutic use*
;
Rats, Sprague-Dawley
;
Myocardium/metabolism*
;
Fibrosis
;
Male
;
Capsules
;
Hypoglycemic Agents/therapeutic use*
;
NF-E2-Related Factor 2/metabolism*
;
Rats
;
Diabetes Mellitus, Experimental/drug therapy*
8.Expert Consensus on the Ethical Requirements for Generative AI-Assisted Academic Writing
You-Quan BU ; Yong-Fu CAO ; Zeng-Yi CHANG ; Hong-Yu CHEN ; Xiao-Wei CHEN ; Yuan-Yuan CHEN ; Zhu-Cheng CHEN ; Rui DENG ; Jie DING ; Zhong-Kai FAN ; Guo-Quan GAO ; Xu GAO ; Lan HU ; Xiao-Qing HU ; Hong-Ti JIA ; Ying KONG ; En-Min LI ; Ling LI ; Yu-Hua LI ; Jun-Rong LIU ; Zhi-Qiang LIU ; Ya-Ping LUO ; Xue-Mei LV ; Yan-Xi PEI ; Xiao-Zhong PENG ; Qi-Qun TANG ; You WAN ; Yong WANG ; Ming-Xu WANG ; Xian WANG ; Guang-Kuan XIE ; Jun XIE ; Xiao-Hua YAN ; Mei YIN ; Zhong-Shan YU ; Chun-Yan ZHOU ; Rui-Fang ZHU
Chinese Journal of Biochemistry and Molecular Biology 2025;41(6):826-832
With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.
9.Guideline for Adult Weight Management in China
Weiqing WANG ; Qin WAN ; Jianhua MA ; Guang WANG ; Yufan WANG ; Guixia WANG ; Yongquan SHI ; Tingjun YE ; Xiaoguang SHI ; Jian KUANG ; Bo FENG ; Xiuyan FENG ; Guang NING ; Yiming MU ; Hongyu KUANG ; Xiaoping XING ; Chunli PIAO ; Xingbo CHENG ; Zhifeng CHENG ; Yufang BI ; Yan BI ; Wenshan LYU ; Dalong ZHU ; Cuiyan ZHU ; Wei ZHU ; Fei HUA ; Fei XIANG ; Shuang YAN ; Zilin SUN ; Yadong SUN ; Liqin SUN ; Luying SUN ; Li YAN ; Yanbing LI ; Hong LI ; Shu LI ; Ling LI ; Yiming LI ; Chenzhong LI ; Hua YANG ; Jinkui YANG ; Ling YANG ; Ying YANG ; Tao YANG ; Xiao YANG ; Xinhua XIAO ; Dan WU ; Jinsong KUANG ; Lanjie HE ; Wei GU ; Jie SHEN ; Yongfeng SONG ; Qiao ZHANG ; Hong ZHANG ; Yuwei ZHANG ; Junqing ZHANG ; Xianfeng ZHANG ; Miao ZHANG ; Yifei ZHANG ; Yingli LU ; Hong CHEN ; Li CHEN ; Bing CHEN ; Shihong CHEN ; Guiyan CHEN ; Haibing CHEN ; Lei CHEN ; Yanyan CHEN ; Genben CHEN ; Yikun ZHOU ; Xianghai ZHOU ; Qiang ZHOU ; Jiaqiang ZHOU ; Hongting ZHENG ; Zhongyan SHAN ; Jiajun ZHAO ; Dong ZHAO ; Ji HU ; Jiang HU ; Xinguo HOU ; Bimin SHI ; Tianpei HONG ; Mingxia YUAN ; Weibo XIA ; Xuejiang GU ; Yong XU ; Shuguang PANG ; Tianshu GAO ; Zuhua GAO ; Xiaohui GUO ; Hongyi CAO ; Mingfeng CAO ; Xiaopei CAO ; Jing MA ; Bin LU ; Zhen LIANG ; Jun LIANG ; Min LONG ; Yongde PENG ; Jin LU ; Hongyun LU ; Yan LU ; Chunping ZENG ; Binhong WEN ; Xueyong LOU ; Qingbo GUAN ; Lin LIAO ; Xin LIAO ; Ping XIONG ; Yaoming XUE
Chinese Journal of Endocrinology and Metabolism 2025;41(11):891-907
Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.
10.Study on the association between systemic immune-inflammation index and metabolic types and characteristics of obesity in children and adolescents
Jiayi WAN ; Shiyun LUO ; Jie HUANG ; Wanzhen ZHONG ; Guixian TAO ; Chunzi ZENG ; Jiaying GUO ; Weiwei ZHANG ; Jing GU ; Yan LI
Chinese Journal of Preventive Medicine 2025;59(11):1916-1923
Objective:To explore the association between the systemic immune-inflammation index (SII) and obesity metabolic phenotypes, as well as metabolic features in children and adolescents.Methods:A cross-sectional study was conducted using the random cluster sampling method from March 2023 to May 2024. Children and adolescents aged 9-17 years in Guangzhou were surveyed through questionnaires, physical measurements, and blood tests. According to BMI and metabolic status, participants were classified into normal-weight groups [metabolically healthy normal weight (MHNW) and metabolically unhealthy normal weight (MUNW)] and overweight/obese groups [metabolically healthy overweight/obese (MHO/O) and metabolically unhealthy overweight/obese (MUO/O)]. After natural log-transformation of SII values (lnSII), multinomial logistic regression was used to assess the association between SII and obesity metabolic phenotypes, while binary logistic regression was applied to assess the relationship between SII and metabolic phenotypes in the overweight/obese subgroup. Linear regression model and restricted cubic spline (RCS) were employed to examine the relationship between SII and metabolic features among the entire population.Results:A total of 3 749 participants were included. After adjusting for covariates, for every unit increase in lnSII, the risk of MHO/O and MUO/O increased by 93% ( OR=1.93, 95% CI: 1.56-2.40, P<0.001) and 156% ( OR=2.56, 95% CI: 2.02-3.25, P<0.001), respectively. In the overweight/obesity subgroup, for every unit increase in lnSII, the risk of MUO/O increased by 37% ( OR=1.37, 95% CI: 1.01-1.87, P=0.045). Linear regression model and RCS showed that lnSII was positively correlated with systolic blood pressure (SBP) and diastolic blood pressure (DBP) (SBP: β=1.39, 95% CI: 0.67-2.11, P<0.001; DBP: β=1.27, 95% CI: 0.79-1.75, P<0.001). lnSII also had a non-linear relationship with triglyceride ( Pnonlinear=0.032) and high-density lipoprotein cholesterol ( Pnonlinear=0.002). Conclusion:Elevated SII levels are associated with unfavorable obesity metabolic phenotypes, higher blood pressure, and altered lipid profiles in children and adolescents. SII may be a potential driving factor for metabolic heterogeneity in children and adolescents.

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