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Zhang Y, Zhang L, Lv H, Zhang G. Ensemble machine learning prediction of hyperuricemia based on a prospective health checkup population. Front Physiol 2024; 15:1357404. [PMID: 38665596 PMCID: PMC11043598 DOI: 10.3389/fphys.2024.1357404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 03/11/2024] [Indexed: 04/28/2024] Open
Abstract
Objectives: An accurate prediction model for hyperuricemia (HUA) in adults remain unavailable. This study aimed to develop a stacking ensemble prediction model for HUA to identify high-risk groups and explore risk factors. Methods: A prospective health checkup cohort of 40899 subjects was examined and randomly divided into the training and validation sets with the ratio of 7:3. LASSO regression was employed to screen out important features and then the ROSE sampling was used to handle the imbalanced classes. An ensemble model using stacking strategy was constructed based on three individual models, including support vector machine, decision tree C5.0, and eXtreme gradient boosting. Model validations were conducted using the area under the receiver operating characteristic curve (AUC) and the calibration curve, as well as metrics including accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1 score. A model agnostic instance level variable attributions technique (iBreakdown) was used to illustrate the black-box nature of our ensemble model, and to identify contributing risk factors. Results: Fifteen important features were screened out of 23 clinical variables. Our stacking ensemble model with an AUC of 0.854, outperformed the other three models, support vector machine, decision tree C5.0, and eXtreme gradient boosting with AUCs of 0.848, 0.851 and 0.849 respectively. Calibration accuracy as well as other metrics including accuracy, specificity, negative predictive value, and F1 score were also proved our ensemble model's superiority. The contributing risk factors were estimated using six randomly selected subjects, which showed that being female and relatively younger, together with having higher baseline uric acid, body mass index, γ-glutamyl transpeptidase, total protein, triglycerides, creatinine, and fasting blood glucose can increase the risk of HUA. To further validate our model's applicability in the health checkup population, we used another cohort of 8559 subjects that also showed our ensemble prediction model had favorable performances with an AUC of 0.846. Conclusion: In this study, the stacking ensemble prediction model for HUA was developed, and it outperformed three individual models that compose it (support vector machine, decision tree C5.0, and eXtreme gradient boosting). The contributing risk factors were identified with insightful ideas.
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Affiliation(s)
- Yongsheng Zhang
- Health Management Center, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, China
- Institute of Health Management, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, China
- Shandong Engineering Laboratory of Health Management, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, China
| | - Li Zhang
- Department of Pharmacology, Jinan Central Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Haoyue Lv
- Health Management Center, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, China
- Institute of Health Management, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, China
- Shandong Engineering Laboratory of Health Management, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, China
| | - Guang Zhang
- Health Management Center, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, China
- Institute of Health Management, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, China
- Shandong Engineering Laboratory of Health Management, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, China
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Yin T, Chen S, Zhu Y, Kong L, Li Q, Zhang G, He H. Insulin resistance, combined with health-related lifestyles, psychological traits and adverse cardiometabolic profiles, is associated with cardiovascular diseases: findings from the BHMC study. Food Funct 2024; 15:3864-3875. [PMID: 38516900 DOI: 10.1039/d4fo00941j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Abstract
The triglyceride glucose (TyG) index is a reliable marker of insulin resistance; however, its combined impact with modifiable lifestyle risk factors and psychological traits on cardiovascular diseases (CVDs) remains unclear. The aim of this study was to explore the relationship between the TyG index, various behavioral factors, psychological traits, and CVDs. A total of 77 752 adults aged 18 and over from the baseline survey of the Beijing Health Management Cohort study were investigated. Associations of the TyG index, body roundness index (BRI), dietary habits, psychological traits, and sleep habits with CVDs were estimated using multivariable logistic regression models. Compared to the Q1 level, the Q4 level of the TyG index had an odds ratio (OR) and 95% confidence interval (CI) of 2.30 (1.98-2.68) for CVD risk in men and 2.12 (1.81-2.48) in women. Compared to a sleep duration of more than 7 hours, a sleep duration less than 5 hours had a 32% (8%-61%) higher risk in men and 22% (1%-48%) in women. The ORs (95% CIs) for fast eating compared to normal speed were 1.47 (1.23-1.76) in men and 1.17 (1.05-1.29) in women. Compared to individuals with a passive and depressed psychological trait, those who were positive and optimistic had a 47% (36%-56%) decreased risk in men and 43% (31%-53%) in women. In the age-stratified analysis, a higher BRI level showed a sex-differential effect on CVDs, which is potentially related to a lower risk of CVDs in elderly men. A high level of the TyG index combined with unhealthy lifestyle factors indicates a higher risk of CVDs, while maintaining a positive and optimistic psychological trait acts as a protective factor. These findings may be valuable for identifying high-risk populations for CVDs in community settings.
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Affiliation(s)
- Tao Yin
- Department of Technology, Capital Institute of Pediatrics, Beijing, China
| | - Shuo Chen
- Beijing Physical Examination Center, Beijing, China.
| | - Yingying Zhu
- Department of Otolaryngology-Head and Neck Surgery, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China.
| | - Linrun Kong
- Beijing Physical Examination Center, Beijing, China.
| | - Qiang Li
- Beijing Physical Examination Center, Beijing, China.
| | - Guohong Zhang
- Beijing Physical Examination Center, Beijing, China.
| | - Huijing He
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China.
- State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
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Li L, Zhao K, Luo J, Tian J, Zheng F, Lin X, Xie Z, Jiang H, Li Y, Zhao Z, Wu T, Pang J. Piperine Improves Hyperuricemic Nephropathy by Inhibiting URAT1/GLUT9 and the AKT-mTOR Pathway. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024; 72:6565-6574. [PMID: 38498316 DOI: 10.1021/acs.jafc.3c07655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/20/2024]
Abstract
Uncontrolled hyperuricemia often leads to the development of hyperuricemic nephropathy (HN), characterized by excessive inflammation and oxidative stress. Piperine, a cinnamic acid alkaloid, possesses various pharmacological activities, such as antioxidant and anti-inflammatory effects. In this study, we intended to investigate the protective effects of piperine on adenine and potassium oxonate-induced HN mice and a uric-acid-induced injury model in renal tubular epithelial cells (mRTECs). We observed that treatment with piperine for 3 weeks significantly reduced serum uric acid levels and reversed kidney function impairment in mice with HN. Piperine (5 μM) alleviated uric acid-induced damage in mRTECs. Moreover, piperine inhibited transporter expression and dose-dependently inhibited the activity of both transporters. The results revealed that piperine regulated the AKT/mTOR signaling pathway both in vivo and in vitro. Overall, piperine inhibits URAT1/GLUT9 and ameliorates HN by inhibiting the AKT/mTOR pathway, making it a promising candidate for patients with HN.
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Affiliation(s)
- Lu Li
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism & Guangdong Provincial Key Laboratory of New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou 510515, China
| | - Kunlu Zhao
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism & Guangdong Provincial Key Laboratory of New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou 510515, China
| | - Jian Luo
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism & Guangdong Provincial Key Laboratory of New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou 510515, China
| | - Jinhong Tian
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism & Guangdong Provincial Key Laboratory of New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou 510515, China
| | - Fengxin Zheng
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism & Guangdong Provincial Key Laboratory of New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou 510515, China
| | - Xueman Lin
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism & Guangdong Provincial Key Laboratory of New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou 510515, China
| | - Zijun Xie
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism & Guangdong Provincial Key Laboratory of New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou 510515, China
| | - Heyang Jiang
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism & Guangdong Provincial Key Laboratory of New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou 510515, China
| | - Yongmei Li
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism & Guangdong Provincial Key Laboratory of New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou 510515, China
| | - Zean Zhao
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism & Guangdong Provincial Key Laboratory of New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou 510515, China
| | - Ting Wu
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism & Guangdong Provincial Key Laboratory of New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou 510515, China
| | - Jianxin Pang
- NMPA Key Laboratory for Research and Evaluation of Drug Metabolism & Guangdong Provincial Key Laboratory of New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, 1838 Guangzhou Avenue North, Guangzhou 510515, China
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Gao Y, Bi L, Li A, Du M, Song M, Jiang G. Associations of Bisphenols Exposure and Hyperuricemia Based on Human Investigation and Animal Experiments. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:5290-5298. [PMID: 38468128 DOI: 10.1021/acs.est.4c00792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
Hyperuricemia is characterized by elevated blood uric acid (UA) levels, which can lead to certain diseases. Epidemiological studies have explored the association between environmental contaminant exposure and hyperuricemia. However, few studies have investigated the role of chemical exposure in the development of hyperuricemia. Here, we sought to investigate the effects of bisphenol exposure on the occurrence of hyperuricemia. Fifteen bisphenol chemicals (BPs) were detected in human serum and urine samples collected from an area with a high incidence of hyperuricemia in China. Serum UA levels positively correlated with urinary bisphenol S (BPS), urinary bisphenol P (BPP), and serum bisphenol F (BPF). The effects of these three chemicals on UA levels in mice were explored at various exposure concentrations. An increase in serum UA levels was observed in BPS- and BPP-exposed mice. The results showed that BPS exposure increased serum UA levels by damaging the structure of the kidneys, whereas BPP exposure increased serum UA levels by disturbing purine metabolism in the liver. Moreover, BPF did not induce an increase in serum UA levels owing to the inhibition of guanine conversion to UA. In summary, we provide evidence of the mechanisms whereby exposure to three BPs disturbs UA homeostasis. These findings provide new insights into the risks of exposure to bisphenol chemicals.
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Affiliation(s)
- Yue Gao
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Science, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lei Bi
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Science, Beijing 100085, China
| | - Aijing Li
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Science, Beijing 100085, China
| | - Mei Du
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Science, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Maoyong Song
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Science, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Guibin Jiang
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Science, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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Fu Y, Chen YS, Xia DY, Luo XD, Luo HT, Pan J, Ma WQ, Li JZ, Mo QY, Tu Q, Li MM, Zhao Y, Li Y, Huang YT, Chen ZX, Li ZJ, Bernard L, Dione M, Zhang YM, Miao K, Chen JY, Zhu SS, Ren J, Zhou LJ, Jiang XZ, Chen J, Lin ZP, Chen JP, Ye H, Cao QY, Zhu YW, Yang L, Wang X, Wang WC. Lactobacillus rhamnosus GG ameliorates hyperuricemia in a novel model. NPJ Biofilms Microbiomes 2024; 10:25. [PMID: 38509085 PMCID: PMC10954633 DOI: 10.1038/s41522-024-00486-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 02/06/2024] [Indexed: 03/22/2024] Open
Abstract
Hyperuricemia (HUA) is a metabolic syndrome caused by abnormal purine metabolism. Although recent studies have noted a relationship between the gut microbiota and gout, whether the microbiota could ameliorate HUA-associated systemic purine metabolism remains unclear. In this study, we constructed a novel model of HUA in geese and investigated the mechanism by which Lactobacillus rhamnosus GG (LGG) could have beneficial effects on HUA. The administration of antibiotics and fecal microbiota transplantation (FMT) experiments were used in this HUA goose model. The effects of LGG and its metabolites on HUA were evaluated in vivo and in vitro. Heterogeneous expression and gene knockout of LGG revealed the mechanism of LGG. Multi-omics analysis revealed that the Lactobacillus genus is associated with changes in purine metabolism in HUA. This study showed that LGG and its metabolites could alleviate HUA through the gut-liver-kidney axis. Whole-genome analysis, heterogeneous expression, and gene knockout of LGG enzymes ABC-type multidrug transport system (ABCT), inosine-uridine nucleoside N-ribohydrolase (iunH), and xanthine permease (pbuX) demonstrated the function of nucleoside degradation in LGG. Multi-omics and a correlation analysis in HUA patients and this goose model revealed that a serum proline deficiency, as well as changes in Collinsella and Lactobacillus, may be associated with the occurrence of HUA. Our findings demonstrated the potential of a goose model of diet-induced HUA, and LGG and proline could be promising therapies for HUA.
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Affiliation(s)
- Yang Fu
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Yong-Song Chen
- Clinical Research Center, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China
| | - Dai-Yang Xia
- School of Marine Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519082, China
| | - Xiao-Dan Luo
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Hao-Tong Luo
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Jie Pan
- Hunan Shihua Biotech Co. Ltd., Changsha, 410000, China
| | - Wei-Qing Ma
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Jin-Ze Li
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Qian-Yuan Mo
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Qiang Tu
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266237, Shandong, China
| | - Meng-Meng Li
- School of Agricultural Science and Engineering, Liaocheng University, Liaocheng, 252000, China
| | - Yue Zhao
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Yu Li
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Yi-Teng Huang
- Clinical Research Center, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China
| | - Zhi-Xian Chen
- Clinical Research Center, The First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, China
| | - Zhen-Jun Li
- Key Laboratory of Carcinogenesis and Translational Research, Departments of Lymphoma, Radiology and Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing, 100080, China
| | - Lukuyu Bernard
- International Livestock Research Institute, Nairobi, 00100, Kenya
| | - Michel Dione
- International Livestock Research Institute, Nairobi, 00100, Kenya
| | - You-Ming Zhang
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266237, Shandong, China
| | - Kai Miao
- Cancer Center, Faculty of Health Sciences, University of Macau, Macau, SAR, China
| | - Jian-Ying Chen
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Shan-Shan Zhu
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Jie Ren
- Department of Rheumatology and Immunology, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
| | - Ling-Juan Zhou
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Xian-Zhi Jiang
- Microbiome Research Center, Moon (Guangzhou) Biotech Co. Ltd., Guangzhou, 510535, China
| | - Juan Chen
- Microbiome Research Center, Moon (Guangzhou) Biotech Co. Ltd., Guangzhou, 510535, China
| | - Zhen-Ping Lin
- Shantou Baisha Research Institute of Origin Species of Poultry and Stock, Shantou, 515041, China
| | - Jun-Peng Chen
- Shantou Baisha Research Institute of Origin Species of Poultry and Stock, Shantou, 515041, China
| | - Hui Ye
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Qing-Yun Cao
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Yong-Wen Zhu
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Lin Yang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China.
| | - Xue Wang
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266237, Shandong, China.
| | - Wen-Ce Wang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China.
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Di Gioia G, Crispino SP, Maestrini V, Monosilio S, Squeo MR, Lemme E, Segreti A, Serdoz A, Fiore R, Zampaglione D, Pelliccia A. Prevalence of Hyperuricemia and Associated Cardiovascular Risk Factors in Elite Athletes Practicing Different Sporting Disciplines: A Cross-Sectional Study. J Clin Med 2024; 13:560. [PMID: 38256692 PMCID: PMC10816906 DOI: 10.3390/jcm13020560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 12/29/2023] [Accepted: 01/17/2024] [Indexed: 01/24/2024] Open
Abstract
Uricemia has been identified as an independent risk factor for cardiovascular disease. In the general population, hyperuricemia is associated with hypertension, endothelial dysfunction, and other cardiovascular risk (CVR) factors. Our aim was to explore the prevalence of hyperuricemia among Olympic athletes, evaluating the influence of sporting discipline and its correlation with CVR factors. We enrolled 1173 Olympic athletes classified into four disciplines: power, skill, endurance, and mixed. Clinical, anthropometric data, and complete blood test results were collected. Hyperuricemia was present in 4.4% of athletes, 0.3% were hypertensive, 11.7% had high-normal blood pressure values, 0.2% were diabetic, 1.2%. glucose intolerance, 8.2% active smokers, and 3% were obese. Males had a higher prevalence of hyperuricemia (5.3%) than females (3.4%) with no significant differences between different sporting disciplines (male, p = 0.412; female p = 0.561). Males with fat mass >22% presented higher uricemia (5.8 ± 1 vs. 5.3 ± 1 mg/dL, p = 0.010) like hypertensive athletes (6.5 ± 0.3 vs. 5.3 ± 1 mg/dL, p = 0.031), those with high-normal blood pressure (5.13 ± 1 vs. 4.76 ± 1.1 mg/dL, p = 0.0004) and those with glucose intolerance (6 ± 0.8 vs. 5.3 ± 1 mg/dL, p = 0.066). The study provides a comprehensive evaluation of hyperuricemia among Olympic athletes, revealing a modest prevalence, lower than in the general population. However, aggregation of multiple CVR factors could synergistically elevate the risk profile, even in a population assumed to be at low risk. Therefore, uric acid levels should be monitored as part of the CVR assessment in athletes.
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Affiliation(s)
- Giuseppe Di Gioia
- Institute of Sports Medicine and Science, National Italian Olympic Committee, Largo Piero Gabrielli 1, 00197 Rome, Italy; (V.M.); (S.M.); (M.R.S.); (E.L.); (A.S.); (R.F.); (D.Z.); (A.P.)
- Department of Cardiovascular Sciences, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo 200, 00128 Rome, Italy; (S.P.C.); (A.S.)
- Department of Movement, Human and Health Sciences, University of Rome “Foro Italico”, Piazza Lauro De Bosis 15, 00135 Rome, Italy
| | - Simone Pasquale Crispino
- Department of Cardiovascular Sciences, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo 200, 00128 Rome, Italy; (S.P.C.); (A.S.)
| | - Viviana Maestrini
- Institute of Sports Medicine and Science, National Italian Olympic Committee, Largo Piero Gabrielli 1, 00197 Rome, Italy; (V.M.); (S.M.); (M.R.S.); (E.L.); (A.S.); (R.F.); (D.Z.); (A.P.)
- Department of Clinical, Internal, Anesthesiologic and Cardiovascular Sciences, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy
| | - Sara Monosilio
- Institute of Sports Medicine and Science, National Italian Olympic Committee, Largo Piero Gabrielli 1, 00197 Rome, Italy; (V.M.); (S.M.); (M.R.S.); (E.L.); (A.S.); (R.F.); (D.Z.); (A.P.)
- Department of Clinical, Internal, Anesthesiologic and Cardiovascular Sciences, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy
| | - Maria Rosaria Squeo
- Institute of Sports Medicine and Science, National Italian Olympic Committee, Largo Piero Gabrielli 1, 00197 Rome, Italy; (V.M.); (S.M.); (M.R.S.); (E.L.); (A.S.); (R.F.); (D.Z.); (A.P.)
| | - Erika Lemme
- Institute of Sports Medicine and Science, National Italian Olympic Committee, Largo Piero Gabrielli 1, 00197 Rome, Italy; (V.M.); (S.M.); (M.R.S.); (E.L.); (A.S.); (R.F.); (D.Z.); (A.P.)
| | - Andrea Segreti
- Department of Cardiovascular Sciences, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo 200, 00128 Rome, Italy; (S.P.C.); (A.S.)
- Department of Movement, Human and Health Sciences, University of Rome “Foro Italico”, Piazza Lauro De Bosis 15, 00135 Rome, Italy
| | - Andrea Serdoz
- Institute of Sports Medicine and Science, National Italian Olympic Committee, Largo Piero Gabrielli 1, 00197 Rome, Italy; (V.M.); (S.M.); (M.R.S.); (E.L.); (A.S.); (R.F.); (D.Z.); (A.P.)
| | - Roberto Fiore
- Institute of Sports Medicine and Science, National Italian Olympic Committee, Largo Piero Gabrielli 1, 00197 Rome, Italy; (V.M.); (S.M.); (M.R.S.); (E.L.); (A.S.); (R.F.); (D.Z.); (A.P.)
| | - Domenico Zampaglione
- Institute of Sports Medicine and Science, National Italian Olympic Committee, Largo Piero Gabrielli 1, 00197 Rome, Italy; (V.M.); (S.M.); (M.R.S.); (E.L.); (A.S.); (R.F.); (D.Z.); (A.P.)
| | - Antonio Pelliccia
- Institute of Sports Medicine and Science, National Italian Olympic Committee, Largo Piero Gabrielli 1, 00197 Rome, Italy; (V.M.); (S.M.); (M.R.S.); (E.L.); (A.S.); (R.F.); (D.Z.); (A.P.)
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7
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Luo Y, Wu Q, Meng R, Lian F, Jiang C, Hu M, Wang Y, Ma H. Associations of serum uric acid with cardiovascular disease risk factors: a retrospective cohort study in southeastern China. BMJ Open 2023; 13:e073930. [PMID: 37758669 PMCID: PMC10537982 DOI: 10.1136/bmjopen-2023-073930] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 08/18/2023] [Indexed: 09/29/2023] Open
Abstract
OBJECTIVE To evaluate the associations between serum uric acid (SUA) levels and cardiovascular disease (CVD) risk factors, focusing on potential sex-specific differences. DESIGN A retrospective cohort study. SETTING A large community-based survey was conducted every two years from 2010 to 2018 in Hangzhou, Zhejiang Province, outheastern China. PARTICIPANTS 6119 participants aged 40 years and above who underwent at least three times of physical examinations were enrolled. METHODS Participants were categorised into four groups (Q1-Q4) based on baseline SUA quartiles within the normal range, with hyperuricaemia (HUA) as the fifth group. The Q1 was the reference. By stratifying participants by gender, the relationships between SUA levels and systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting blood glucose (FBG) and total cholesterol (TC) were investigated using linear regression models in the generalised estimating equation. Additionally, the associations of elevated SUA levels and HUA with hypertension, hyperglycaemia and dyslipidaemia were correspondingly examined using multivariate logistic regression models. RESULTS After adjusting for confounding variables, we found positive associations between SUA levels and SBP, DBP, FBG and TC in women, and with TC in men (p<0.01). Likewise, elevated SUA quartiles and HUA were linked to increased dyslipidaemia risk in both sexes, and increased hyperglycaemia risk only in women, with HRs (95% CI) of 1.64 (1.05 to 2.55) and 2.37 (1.47 to 3.81) in the Q4 and HUA group, respectively. Women with HUA had higher hypertension risk (HR=1.45, 95% CI 1.21 to 1.73), while no such association was observed in men. Stratified analyses revealed significant associations between elevated SUA levels and CVD risk factors in postmenopausal and non-obese women. CONCLUSIONS Elevated SUA levels increase the risk of dyslipidaemia in both sexes. SUA levels within normal range and HUA are positively associated with hyperglycaemia and hypertension in postmenopausal women, but not in men.
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Affiliation(s)
- Yingxian Luo
- School of Public Health, Hangzhou Normal University, Hangzhou, China
| | - Qiong Wu
- School of Public Health, Hangzhou Normal University, Hangzhou, China
| | - Runtang Meng
- School of Public Health, Hangzhou Normal University, Hangzhou, China
| | - Fuzhi Lian
- School of Public Health, Hangzhou Normal University, Hangzhou, China
| | - Chen Jiang
- School of Public Health, Hangzhou Normal University, Hangzhou, China
| | - Meiyu Hu
- School of Public Health, Hangzhou Normal University, Hangzhou, China
| | - Yaxin Wang
- School of Public Health, Hangzhou Normal University, Hangzhou, China
| | - Haiyan Ma
- School of Public Health, Hangzhou Normal University, Hangzhou, China
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Yin T, Lu Y, Xiong W, Yu C, Yin D, He H. Occupational Risk Factors for Physical and Mental Health in Primary Healthcare Providers: A National Cross-Sectional Survey from 62 Urban Communities in China. J Multidiscip Healthc 2023; 16:751-762. [PMID: 36969734 PMCID: PMC10032140 DOI: 10.2147/jmdh.s401914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Accepted: 03/14/2023] [Indexed: 03/19/2023] Open
Abstract
Purpose To understand the physical and mental health status of primary healthcare providers (PHPs) including physicians, nurses and other staff and the workplace risk factors for depression, anxiety and intention-to-leave. Patients and Methods In December 2021, a national cross-sectional survey was conducted from 62 urban communities in China, and all PHPs were invited to complete a standardized questionnaire. Information on demographic, health-related lifestyle, cardiovascular risk factors and physical health status, occupational stress and intention-to-leave was collected. Depression and anxiety were assessed using the Zung Self-Rating Anxiety/Depression Scale (SAS/SDS). Results A total of 4901 PHPs were included. 67.0% males currently drank alcohol vs 25.3% in females; 36.0% males currently smoked cigarettes vs 1.4% in females. Notably, more than half males were overweight or obese, but this proportion was 24.2% in females. The prevalence of chronic diseases, including hypertension, diabetes, dyslipidemia, non-alcoholic fatty liver disease, gout, and disease clustering were higher in males than in females. The prevalence of depression and anxiety were high, 50% had depression, of whom 15.6% had moderate/severe depression. Over 15% participants had varied levels of anxiety, and approximately 4% had moderate/severe anxiety. PHPs who aged 18-29 (OR: 1.31, 95% CI: 1.05-1.64), were males (OR: 1.34, 95% CI: 1.14-1.57), with lower professional title (comparing with staff with senior title, the ORs of the intermedium, junior and none were 1.83, 2.18 and 2.49, respectively), took charge in nursing (OR: 1.41, 95% CI: 1.20-1.65), with higher perceived stress level (OR: 1.82, 95% CI: 1.41-2.34), and suffering from severe fatigue (OR: 2.55, 95% CI: 1.99-3.27) were more likely to have depression. Likewise, PHPs who were younger, with intermedium professional title, had higher perceived pressure level, and higher fatigue levels were more likely to have anxiety. Conclusion The mental health of PHPs is worrisome, with a high burden of chronic diseases and occupational risk factors. Younger PHPs, nurses, and those with higher levels of work pressure and fatigue are more vulnerable to psychological problems. The high prevalence of intention-to-leave calls for strategies that relieve the workplace stress and enhance the human resource capability.
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Affiliation(s)
- Tao Yin
- Department of Technology, Capital Institute of Pediatrics, Beijing, People’s Republic of China
| | - Yan Lu
- Department of Cardiology, First Affiliated Hospital of Nanjing Medical University, Nanjing, People’s Republic of China
| | - Wei Xiong
- Department of Gynecology Endocrine & Reproductive Center, National Clinical Research Center for Obstetric & Gynecologic Diseases Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Peking Union Medical College/Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Chengdong Yu
- Department of Growth and Development, Capital Institute of Pediatrics, Beijing, People’s Republic of China
| | - Delu Yin
- Department of Child Health Care, Capital Institute of Pediatrics, Beijing, People’s Republic of China
- Delu Yin, Department of Child Health Care, Capital Institute of Pediatrics, 2 Yabao Road, Chaoyang District, Beijing, 100020, People’s Republic of China, Tel +8613810349722, Email
| | - Huijing He
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, People’s Republic of China
- Correspondence: Huijing He, Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, 5 Dongdansantiao, Dongcheng District, Beijing, 100005, People’s Republic of China, Tel +8615010086743, Email
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Zheng Z, Si Z, Wang X, Meng R, Wang H, Zhao Z, Lu H, Wang H, Zheng Y, Hu J, He R, Chen Y, Yang Y, Li X, Xue L, Sun J, Wu J. Risk Prediction for the Development of Hyperuricemia: Model Development Using an Occupational Health Examination Dataset. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:3411. [PMID: 36834107 PMCID: PMC9967697 DOI: 10.3390/ijerph20043411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 02/13/2023] [Accepted: 02/13/2023] [Indexed: 06/18/2023]
Abstract
OBJECTIVE Hyperuricemia has become the second most common metabolic disease in China after diabetes, and the disease burden is not optimistic. METHODS We used the method of retrospective cohort studies, a baseline survey completed from January to September 2017, and a follow-up survey completed from March to September 2019. A group of 2992 steelworkers was used as the study population. Three models of Logistic regression, CNN, and XG Boost were established to predict HUA incidence in steelworkers, respectively. The predictive effects of the three models were evaluated in terms of discrimination, calibration, and clinical applicability. RESULTS The training set results show that the accuracy of the Logistic regression, CNN, and XG Boost models was 84.4, 86.8, and 86.6, sensitivity was 68.4, 72.3, and 81.5, specificity was 82.0, 85.7, and 86.8, the area under the ROC curve was 0.734, 0.724, and 0.806, and Brier score was 0.121, 0.194, and 0.095, respectively. The XG Boost model effect evaluation index was better than the other two models, and similar results were obtained in the validation set. In terms of clinical applicability, the XG Boost model had higher clinical applicability than the Logistic regression and CNN models. CONCLUSION The prediction effect of the XG Boost model was better than the CNN and Logistic regression models and was suitable for the prediction of HUA onset risk in steelworkers.
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Affiliation(s)
- Ziwei Zheng
- Key Laboratory of Coal Mine Health and Safety of Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Zhikang Si
- Key Laboratory of Coal Mine Health and Safety of Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Xuelin Wang
- Key Laboratory of Coal Mine Health and Safety of Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Rui Meng
- Key Laboratory of Coal Mine Health and Safety of Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Hui Wang
- Key Laboratory of Coal Mine Health and Safety of Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Zekun Zhao
- Key Laboratory of Coal Mine Health and Safety of Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Haipeng Lu
- Key Laboratory of Coal Mine Health and Safety of Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Huan Wang
- Key Laboratory of Coal Mine Health and Safety of Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Yizhan Zheng
- Key Laboratory of Coal Mine Health and Safety of Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Jiaqi Hu
- Key Laboratory of Coal Mine Health and Safety of Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Runhui He
- College of Science, North China University of Science and Technology, Tangshan 063210, China
| | - Yuanyu Chen
- Key Laboratory of Coal Mine Health and Safety of Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Yongzhong Yang
- Key Laboratory of Coal Mine Health and Safety of Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Xiaoming Li
- Key Laboratory of Coal Mine Health and Safety of Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Ling Xue
- Key Laboratory of Coal Mine Health and Safety of Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Jian Sun
- School of Public Health, North China University of Science and Technology, Tangshan 063210, China
| | - Jianhui Wu
- Key Laboratory of Coal Mine Health and Safety of Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan 063210, China
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He H, Pan L, Wang D, Liu F, Du J, Pa L, Wang X, Cui Z, Ren X, Wang H, Peng X, Zhao J, Shan G. Fat-to-Muscle Ratio Is Independently Associated with Hyperuricemia and a Reduced Estimated Glomerular Filtration Rate in Chinese Adults: The China National Health Survey. Nutrients 2022; 14:4193. [PMID: 36235845 PMCID: PMC9573307 DOI: 10.3390/nu14194193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 10/04/2022] [Accepted: 10/07/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND The effects of the fat-to-muscle ratio (FMR) on hyperuricemia and a reduction in the estimated glomerular filtration rate (eGFR) are still unclear. METHODS Data from the China National Health Survey were used to explore the associations of the FMR with hyperuricemia and reduced eGFR. The fat mass and muscle mass were measured through bioelectrical impedance analysis. Mediation analysis was used to estimate the mediated effect of hyperuricemia on the association between the FMR and reduced eGFR. RESULTS A total of 31171 participants were included. For hyperuricemia, compared with the Q1 of the FMR, the ORs (95% CI) of Q2, Q3 and Q4 were 1.60 (1.32-1.95), 2.31 (1.91-2.80) and 2.71 (2.15-3.43) in men and 1.91 (1.56-2.34), 2.67 (2.12-3.36) and 4.47 (3.40-5.89) in women. For the reduced eGFR, the ORs (95% CI) of Q2, Q3 and Q4 of the FMR were 1.48 (1.18-1.87), 1.38 (1.05-1.82) and 1.45 (1.04-2.04) in men aged 40-59, but no positive association was found in younger men or in women. Hyperuricemia mediated the association between the FMR and reduced eGFR in men. The OR (95% CI) of the indirect effect was 1.08 (1.05-1.10), accounting for 35.11% of the total effect. CONCLUSIONS The FMR was associated with hyperuricemia and reduced eGFR, and the associations varied based on sex and age. The effect of the FMR on the reduced eGFR was significantly mediated by hyperuricemia in men.
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Affiliation(s)
- Huijing He
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing 100005, China
| | - Li Pan
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing 100005, China
| | - Dingming Wang
- Department of Chronic and Noncommunicable Disease Prevention and Control, Guizhou Provincial Center for Disease Control and Prevention, Guiyang 550004, China
| | - Feng Liu
- Department of Chronic and Noncommunicable Disease Prevention and Control, Shaanxi Provincial Center for Disease Control and Prevention, Xi’an 710054, China
| | - Jianwei Du
- Department of Chronic and Noncommunicable Disease Prevention and Control, Hainan Provincial Center for Disease Control and Prevention, Haikou 570203, China
| | - Lize Pa
- Department of Chronic and Noncommunicable Disease Prevention and Control, Xinjiang Uyghur Autonomous Region Center for Disease Control and Prevention, Urumqi 830001, China
| | - Xianghua Wang
- Institute of Biomedical Engineering, Chinese Academy of Medical Sciences, Tianjin 300192, China
| | - Ze Cui
- Department of Chronic and Noncommunicable Disease Prevention and Control, Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang 050000, China
| | - Xiaolan Ren
- Department of Chronic and Noncommunicable Disease Prevention and Control, Gansu Provincial Center for Disease Control and Prevention, Lanzhou 730000, China
| | - Hailing Wang
- Department of Chronic and Noncommunicable Disease Prevention and Control, Inner Mongolia Autonomous Region Center for Disease Control and Prevention, Baotou 014000, China
| | - Xia Peng
- Department of Chronic and Noncommunicable Disease Prevention and Control, Yunnan Provincial Center for Disease Control and Prevention, Kunming 650022, China
| | - Jingbo Zhao
- School of Public Health, Harbin Medical University, Harbin 150081, China
| | - Guangliang Shan
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing 100005, China
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