1.Analysis of human bocavirus characteristics in children with acute respiratory infections in Bengbu City, Anhui province, 2024
Xinyue CHEN ; Yingli QU ; Jin CAO ; Wenyan TIAN ; Guangyu XUE ; Yuting HU ; Qin LUO ; Qinqin SONG ; Haijun DU ; Guoyong MEI ; Zhiqiang XIA ; Juan SONG ; Jun HAN ; Guoyu LU
Chinese Journal of Experimental and Clinical Virology 2025;39(2):214-218
Objective:To determine the epidemiological characteristics of human bocavirus (HBoV) in children with acute respiratory infections (ARI) in Bengbu City, Anhui Province, in 2024.Methods:Nasopharyngeal swab samples were collected from 269 children with ARI in Bengbu City, Anhui Province, in 2024. Seventeen respiratory pathogens were screened using quantitative fluorescence PCR. For HBoV-positive samples, the VP1/VP2 structural gene fragments of HBoV were amplified and sequenced for genetic evolutionary analysis.Results:Among the 269 nasopharyngeal swab samples from children with ARI, the overall detection rate of respiratory pathogens was 48.33% (103/269). The top three pathogens with the highest detection rates were: Influenza A virus (FluA): 10.04% (27/269), Respiratory syncytial virus (RSV): 8.18% (22/269), Human bocavirus (HBoV): 7.43% (20/269). The age distribution of HBoV-infected children showed that the detection rate was highest in the 0-2 years age group (50%, 10/20), followed by the 3-5 years age group (25%, 5/20) and the over 6 years age group (25%, 5/20). However, there was no statistically significant difference in viral detection rates among the age groups. Genetic evolutionary analysis based on VP1/VP2 revealed that all 13 HBoV strains were of the HBoV-1 genotype.Conclusions:HBoV is one of the major pathogens causing ARI in children in Bengbu City, Anhui Province, in 2024, with HBoV-1 being the predominant genotype. Additionally, infants aged 0-2 years are the most susceptible population to HBoV infection.
2.Association of blood selenium exposure with sex hormones among men aged 18-79 years in China
Zheng LI ; Yingli QU ; Yawei LI ; Saisai JI ; Haocan SONG ; Qi SUN ; Miao ZHANG ; Wenli ZHANG ; Jiayi CAI ; Liang DING ; Ying ZHU ; Feng ZHAO ; Zhaojin CAO ; Yuebin LYU ; Lu WANG ; Xiaoming SHI
Chinese Journal of Preventive Medicine 2025;59(10):1632-1639
Objective:To investigate the association between blood selenium levels and sex hormones in Chinese men aged 18-79 years.Methods:Data were derived from the China National Human Biomonitoring survey conducted in 2017-2018, with a final sample size of 5 414 men. General demographic characteristics, behavioral habits, and dietary frequency were collected through questionnaires and physical examinations. Fasting blood samples were collected to measure blood lead, serum testosterone, and estradiol levels. Complex sampling linear regression models were used to analyze the associations between blood selenium levels and testosterone, estradiol, and the testosterone/estradiol ratio, adjusting for confounding factors including age, education level, marital status, smoking status, alcohol consumption, seafood intake, soy product intake, protein supplement intake, BMI, and diabetes status.Results:The mean age of the 5 414 participants was (46.85±27.91) years; 4 774 (91.65%) were of Han ethnicity and 4 505 (86.68%) were married. The median ( Q1, Q3) blood selenium concentration in men was 97.80 (80.64, 116.99) μg/L. After adjusting for confounding factors, the complex sampling linear regression model revealed negative associations between blood selenium levels and both testosterone levels and the testosterone/estradiol ratio, with a significant linear trend ( Ptrend<0.05). Compared with the Q1 group, the β (95% CI) values for testosterone in the Q2, Q3, and Q4 groups were -0.02 (-0.06 to 0.02), -0.03 (-0.08 to 0.01), and -0.06 (-0.09 to -0.02), respectively. Similarly, the β (95% CI) values for the testosterone/estradiol ratio in the Q2, Q3, and Q4 groups were -0.01 (-0.03 to 0.02), -0.01 (-0.04 to 0.04), and -0.03 (-0.06 to -0.01), respectively. Subgroup analysis indicated stronger associations between blood selenium levels and testosterone/estradiol levels in non-smoking and obese men (BMI≥28 kg/m2). Conclusion:Blood selenium levels are negatively associated with testosterone levels and the testosterone/estradiol ratio in Chinese adult males.
3.Association of cadmium internal exposure levels with blood lipid in adults aged 18 to 79 years in China
Haocan SONG ; Saisai JI ; Zheng LI ; Yawei LI ; Feng ZHAO ; Yingli QU ; Yifu LU ; Yingying HAN ; Junxin LIU ; Jiayi CAI ; Tian QIU ; Wenli ZHANG ; Xiao LIN ; Junfang CAI ; Yuebin LYU ; Xiaoming SHI
Chinese Journal of Preventive Medicine 2025;59(8):1254-1263
Objective:To explore the association of blood and urinary cadmium levels with lipid profile levels and dyslipidemia in Chinese adults aged 18 to 79 years.Methods:Based on the China National Human Biomonitoring (CNHBM) program, a cross-sectional survey was conducted from 2017 to 2018 using a multi-stage stratified random sampling method, including a total of 10 713 adults aged 18 to 79 years. Data was obtained through questionnaires, physical examinations, biological sample collection, and laboratory testing. Multiple linear mixed effect model (MLMM) and generalized linear mixed effect model (GLMM) were used to analyze the association of blood and creatinine-corrected urinary cadmium levels with lipid profile levels as well as dyslipidemia among adults.Results:The age of 10 713 participants was (47.23±0.24) years, with 5 372 males accounting for 61.3% of the national population. The weighted mean±standard error (SE) of total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) was (5.21±0.03), (1.86±0.03), (2.96±0.03), and (1.43±0.01) mmol/L, respectively. The prevalence rate of hypercholesterolemia, hypertriglyceridemia, mixed hyperlipidemia, low HDL-C, and high LDL-C was 16.0%, 21.6%, 6.6%, 13.5%, and 10.0%, respectively. MLMM showed that, after adjusting for relevant confounders, log-transformed blood cadmium levels were positively associated with increased levels of TC, TG and LDL-C ( P<0.05). When blood cadmium levels were categorized into quartiles, compared to the lowest exposure group ( Q1), participants in the highest blood cadmium exposure group ( Q4) had increases of 0.19 (95% CI: 0.06, 0.32) mmol/L in TC and 0.25 (95% CI: 0.08, 0.43) mmol/L in TG. GLMM indicated that, after adjusting for confounders, higher blood cadmium exposure levels were associated with increased risks of hypercholesterolemia, hypertriglyceridemia, mixed hyperlipidemia, and high LDL-C ( P<0.05). Further analysis by quartiles showed that, compared to the blood cadmium Q1 exposure group, the OR value (95% CI) for the Q4 group was 1.53 (1.12, 2.08) for hypercholesterolemia, 1.54 (1.09, 2.17) for hypertriglyceridemia, 2.24 (1.47, 3.40) for mixed hyperlipidemia, and 1.49 (1.07, 2.09) for high LDL-C. Conclusion:The cadmium internal exposure levels are associated with blood lipid profile levels as well as the incidence of dyslipidemia in Chinese adults aged 18 to 79.
4.Association of blood selenium exposure with sex hormones among men aged 18-79 years in China
Zheng LI ; Yingli QU ; Yawei LI ; Saisai JI ; Haocan SONG ; Qi SUN ; Miao ZHANG ; Wenli ZHANG ; Jiayi CAI ; Liang DING ; Ying ZHU ; Feng ZHAO ; Zhaojin CAO ; Yuebin LYU ; Lu WANG ; Xiaoming SHI
Chinese Journal of Preventive Medicine 2025;59(10):1632-1639
Objective:To investigate the association between blood selenium levels and sex hormones in Chinese men aged 18-79 years.Methods:Data were derived from the China National Human Biomonitoring survey conducted in 2017-2018, with a final sample size of 5 414 men. General demographic characteristics, behavioral habits, and dietary frequency were collected through questionnaires and physical examinations. Fasting blood samples were collected to measure blood lead, serum testosterone, and estradiol levels. Complex sampling linear regression models were used to analyze the associations between blood selenium levels and testosterone, estradiol, and the testosterone/estradiol ratio, adjusting for confounding factors including age, education level, marital status, smoking status, alcohol consumption, seafood intake, soy product intake, protein supplement intake, BMI, and diabetes status.Results:The mean age of the 5 414 participants was (46.85±27.91) years; 4 774 (91.65%) were of Han ethnicity and 4 505 (86.68%) were married. The median ( Q1, Q3) blood selenium concentration in men was 97.80 (80.64, 116.99) μg/L. After adjusting for confounding factors, the complex sampling linear regression model revealed negative associations between blood selenium levels and both testosterone levels and the testosterone/estradiol ratio, with a significant linear trend ( Ptrend<0.05). Compared with the Q1 group, the β (95% CI) values for testosterone in the Q2, Q3, and Q4 groups were -0.02 (-0.06 to 0.02), -0.03 (-0.08 to 0.01), and -0.06 (-0.09 to -0.02), respectively. Similarly, the β (95% CI) values for the testosterone/estradiol ratio in the Q2, Q3, and Q4 groups were -0.01 (-0.03 to 0.02), -0.01 (-0.04 to 0.04), and -0.03 (-0.06 to -0.01), respectively. Subgroup analysis indicated stronger associations between blood selenium levels and testosterone/estradiol levels in non-smoking and obese men (BMI≥28 kg/m2). Conclusion:Blood selenium levels are negatively associated with testosterone levels and the testosterone/estradiol ratio in Chinese adult males.
5.Association of cadmium internal exposure levels with blood lipid in adults aged 18 to 79 years in China
Haocan SONG ; Saisai JI ; Zheng LI ; Yawei LI ; Feng ZHAO ; Yingli QU ; Yifu LU ; Yingying HAN ; Junxin LIU ; Jiayi CAI ; Tian QIU ; Wenli ZHANG ; Xiao LIN ; Junfang CAI ; Yuebin LYU ; Xiaoming SHI
Chinese Journal of Preventive Medicine 2025;59(8):1254-1263
Objective:To explore the association of blood and urinary cadmium levels with lipid profile levels and dyslipidemia in Chinese adults aged 18 to 79 years.Methods:Based on the China National Human Biomonitoring (CNHBM) program, a cross-sectional survey was conducted from 2017 to 2018 using a multi-stage stratified random sampling method, including a total of 10 713 adults aged 18 to 79 years. Data was obtained through questionnaires, physical examinations, biological sample collection, and laboratory testing. Multiple linear mixed effect model (MLMM) and generalized linear mixed effect model (GLMM) were used to analyze the association of blood and creatinine-corrected urinary cadmium levels with lipid profile levels as well as dyslipidemia among adults.Results:The age of 10 713 participants was (47.23±0.24) years, with 5 372 males accounting for 61.3% of the national population. The weighted mean±standard error (SE) of total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) was (5.21±0.03), (1.86±0.03), (2.96±0.03), and (1.43±0.01) mmol/L, respectively. The prevalence rate of hypercholesterolemia, hypertriglyceridemia, mixed hyperlipidemia, low HDL-C, and high LDL-C was 16.0%, 21.6%, 6.6%, 13.5%, and 10.0%, respectively. MLMM showed that, after adjusting for relevant confounders, log-transformed blood cadmium levels were positively associated with increased levels of TC, TG and LDL-C ( P<0.05). When blood cadmium levels were categorized into quartiles, compared to the lowest exposure group ( Q1), participants in the highest blood cadmium exposure group ( Q4) had increases of 0.19 (95% CI: 0.06, 0.32) mmol/L in TC and 0.25 (95% CI: 0.08, 0.43) mmol/L in TG. GLMM indicated that, after adjusting for confounders, higher blood cadmium exposure levels were associated with increased risks of hypercholesterolemia, hypertriglyceridemia, mixed hyperlipidemia, and high LDL-C ( P<0.05). Further analysis by quartiles showed that, compared to the blood cadmium Q1 exposure group, the OR value (95% CI) for the Q4 group was 1.53 (1.12, 2.08) for hypercholesterolemia, 1.54 (1.09, 2.17) for hypertriglyceridemia, 2.24 (1.47, 3.40) for mixed hyperlipidemia, and 1.49 (1.07, 2.09) for high LDL-C. Conclusion:The cadmium internal exposure levels are associated with blood lipid profile levels as well as the incidence of dyslipidemia in Chinese adults aged 18 to 79.
6.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.
7.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.
8.Analysis of human bocavirus characteristics in children with acute respiratory infections in Bengbu City, Anhui province, 2024
Xinyue CHEN ; Yingli QU ; Jin CAO ; Wenyan TIAN ; Guangyu XUE ; Yuting HU ; Qin LUO ; Qinqin SONG ; Haijun DU ; Guoyong MEI ; Zhiqiang XIA ; Juan SONG ; Jun HAN ; Guoyu LU
Chinese Journal of Experimental and Clinical Virology 2025;39(2):214-218
Objective:To determine the epidemiological characteristics of human bocavirus (HBoV) in children with acute respiratory infections (ARI) in Bengbu City, Anhui Province, in 2024.Methods:Nasopharyngeal swab samples were collected from 269 children with ARI in Bengbu City, Anhui Province, in 2024. Seventeen respiratory pathogens were screened using quantitative fluorescence PCR. For HBoV-positive samples, the VP1/VP2 structural gene fragments of HBoV were amplified and sequenced for genetic evolutionary analysis.Results:Among the 269 nasopharyngeal swab samples from children with ARI, the overall detection rate of respiratory pathogens was 48.33% (103/269). The top three pathogens with the highest detection rates were: Influenza A virus (FluA): 10.04% (27/269), Respiratory syncytial virus (RSV): 8.18% (22/269), Human bocavirus (HBoV): 7.43% (20/269). The age distribution of HBoV-infected children showed that the detection rate was highest in the 0-2 years age group (50%, 10/20), followed by the 3-5 years age group (25%, 5/20) and the over 6 years age group (25%, 5/20). However, there was no statistically significant difference in viral detection rates among the age groups. Genetic evolutionary analysis based on VP1/VP2 revealed that all 13 HBoV strains were of the HBoV-1 genotype.Conclusions:HBoV is one of the major pathogens causing ARI in children in Bengbu City, Anhui Province, in 2024, with HBoV-1 being the predominant genotype. Additionally, infants aged 0-2 years are the most susceptible population to HBoV infection.
9.Identification of novel biomarkers for varicocele using iTRAQ LC-MS/MS technology.
Xianfeng LU ; Na LI ; Lufang LI ; Yongai WU ; Xuefeng LYU ; Yingli CAO ; Jianrong LIU ; Qin QIN
Chinese Medical Journal 2024;137(3):371-372
10.Serum 25-hydroxyvitamin D, genetic susceptibility, and the risk of incident type 2 diabetes: A prospective cohort in East China
Ying SUN ; Haojie ZHANG ; Bin WANG ; Yuying WANG ; Chi CHEN ; Yi CHEN ; Yingli LU ; Ningjian WANG
Chinese Medical Journal 2024;137(8):972-979
Background::The serum vitamin D level varies widely by population, and studies have linked vitamin D levels with the risk of type 2 diabetes mellitus (T2DM). However, the relationship is inconsistent and the impact of vitamin D on T2DM among East Chinese adults is unclear. The study aimed to investigate the association between serum 25-hydroxyvitamin D (25[OH]D) levels and the risk of T2DM and evaluated whether the association is modified by genetic predisposition.Methods::In the Survey on Prevalence in East China for Metabolic Diseases and Risk Factors (SPECT-China) cohort, 1862 participants free of T2DM at baseline were included. A weighted genetic risk score was calculated with 28 variants associated with T2DM. Hierarchical logistic models were used to examine the association of serum 25(OH)D and genetic risk with T2DM.Results::After a 5-year follow-up, 132 cases of T2DM were documented. We observed no significant association between quartiles of serum 25(OH)D and T2DM risk after multivariable adjustment (χ 2 = 0.571, Pfor trend = 0.426). Compared to those in the lowest quartile of 25(OH)D, the odds ratios (ORs) (95% confidence interval [CI]) for participants with increased quartiles were 1.29 (0.74-2.25), 1.35 (0.77-2.36), and 1.27 (0.72-2.24), respectively. We observed a positive association of glycated hemoglobin (HbA1c) with 25(OH)D at baseline (β = 1.752, P = 0.001) and after follow-up (β = 1.385, P = 0.003), and a negative association of ln conversion homeostasis model assessment (HOMA)-β with 25(OH)D at baseline (β = -0.982, P = 0.021). There was no significant interaction between 25(OH)D and diabetes genetic predisposition on the risk of T2DM (χ 2 = 2.710, Pfor interaction = 0.100). The lowest OR (95% CI) of T2DM was among participants with low genetic risk and the highest quartile of 25(OH)D (0.17 [0.05–0.62]). Conclusion::Serum 25(OH)D may be irrelevant to the risk of incident T2DM among East Chinese adults regardless of genetic predisposition.

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