{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,5]],"date-time":"2026-09-05T03:10:02Z","timestamp":1788577802891,"version":"build-2803163510"},"reference-count":38,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,2,15]],"date-time":"2023-02-15T00:00:00Z","timestamp":1676419200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/ijerph20043411","type":"journal-article","created":{"date-parts":[[2023,2,15]],"date-time":"2023-02-15T05:12:26Z","timestamp":1676437946000},"page":"3411","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Risk Prediction for the Development of Hyperuricemia: Model Development Using an Occupational Health Examination Dataset"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1762-3285","authenticated-orcid":false,"given":"Ziwei","family":"Zheng","sequence":"first","affiliation":[{"name":"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"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhikang","family":"Si","sequence":"additional","affiliation":[{"name":"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"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuelin","family":"Wang","sequence":"additional","affiliation":[{"name":"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"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui","family":"Meng","sequence":"additional","affiliation":[{"name":"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"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Wang","sequence":"additional","affiliation":[{"name":"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"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zekun","family":"Zhao","sequence":"additional","affiliation":[{"name":"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"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haipeng","family":"Lu","sequence":"additional","affiliation":[{"name":"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"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huan","family":"Wang","sequence":"additional","affiliation":[{"name":"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"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yizhan","family":"Zheng","sequence":"additional","affiliation":[{"name":"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"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaqi","family":"Hu","sequence":"additional","affiliation":[{"name":"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"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Runhui","family":"He","sequence":"additional","affiliation":[{"name":"College of Science, North China University of Science and Technology, Tangshan 063210, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanyu","family":"Chen","sequence":"additional","affiliation":[{"name":"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"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongzhong","family":"Yang","sequence":"additional","affiliation":[{"name":"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"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoming","family":"Li","sequence":"additional","affiliation":[{"name":"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"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ling","family":"Xue","sequence":"additional","affiliation":[{"name":"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"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Public Health, North China University of Science and Technology, Tangshan 063210, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8440-1404","authenticated-orcid":false,"given":"Jianhui","family":"Wu","sequence":"additional","affiliation":[{"name":"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"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,15]]},"reference":[{"key":"ref_1","first-page":"547","article-title":"Evaluation of methodological quality and reporting quality of domestic clinical guidelines for hyperuricemia","volume":"47","author":"Wang","year":"2022","journal-title":"China J. Chin. Mater. Med."},{"key":"ref_2","first-page":"762820","article-title":"Prevalence of Hyperuricemia and Gout in China\u2019s mainland from 2000 to 2014: A Systematic Review and Meta-Analysis","volume":"2015","author":"Rui","year":"2015","journal-title":"BioMed Res. Int."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1874652","DOI":"10.1080\/16549716.2021.1874652","article-title":"Demographic, regional and temporal trends of hyperuricemia epidemics in mainland China from 2000 to 2019: A systematic review and meta-analysis","volume":"14","author":"Li","year":"2021","journal-title":"Glob Health Action"},{"key":"ref_4","first-page":"4","article-title":"Prediction model of random forest for the risk of hyperuricemia in a Chinese basic health checkup test","volume":"41","author":"Yuhan","year":"2021","journal-title":"Biosci. Rep."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1916","DOI":"10.1002\/art.41404","article-title":"Prevalence, Incidence, and Years Lived with Disability Due to Gout and Its Attributable Risk Factors for 195 Countries and Territories 1990-2017: A Systematic Analysis of the Global Burden of Disease Study 2017","volume":"72","author":"Safiri","year":"2020","journal-title":"Arthritis Rheumatol"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1136\/heartjnl-2013-304084","article-title":"The prevalence and risk factors of acute cardiovascular events in China: Findings from China Chronic Disease Risk Factor Surveillance 2010","volume":"99","author":"Wang","year":"2013","journal-title":"Heart"},{"key":"ref_7","first-page":"1123","article-title":"Dose-response relationship between shift work and hyperuricemia","volume":"22","author":"Zhang","year":"2018","journal-title":"Chin. J. Dis. Control. Prev."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.jdent.2018.07.015","article-title":"Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm","volume":"77","author":"Lee","year":"2018","journal-title":"J. Dent."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2376391","DOI":"10.1155\/2021\/2376391","article-title":"Efficient Prediction of Missed Clinical Appointment Using Machine Learning","volume":"2021","author":"Qureshi","year":"2021","journal-title":"Comput. Math Methods Med."},{"key":"ref_10","first-page":"894","article-title":"Analysis of influencing factors and disease awareness of asymptomatic hyperuricemia in young and middle-aged physical examination population in Daqing City","volume":"7","author":"Liu","year":"2021","journal-title":"Chin. Evid. -Based Nurs."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1038\/s41584-020-0441-1","article-title":"Global epidemiology of gout: Prevalence, incidence, treatment patterns and risk factors","volume":"16","author":"Mats","year":"2020","journal-title":"Nat. Rev. Rheumatol."},{"key":"ref_12","unstructured":"(2017). Nephrologist Branch of Chinese Medical Doctor Association: Practice Guidelines for the Diagnosis and Treatment of Hyperuricemia in Renal Disease in China (2017 Edition). Natl. Med. J. China, 97, 1927\u20131936."},{"key":"ref_13","unstructured":"(2019). 2018 revised edition of the Chinese Guidelines for the Prevention and Treatment of Hypertension. Prev. Treat. Cardiovasc. Cerebrovasc. Dis., 19, 1\u201344."},{"key":"ref_14","unstructured":"(2021). Diabetes Branch of Chinese Medical Association: Guidelines for the prevention and treatment of type 2 diabetes in China (2020 edition). Int. J. Endocrinol. Metab., 41, 482\u2013548."},{"key":"ref_15","unstructured":"Zhang, S. (2019). Association of shift and rhythm-related gene polymorphisms in steelworkers with HUA. [Postgraduate Thesis, . North China University of Science and Technology]."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Chen, Y., Yang, Y., and Zheng, Z. (2022). Influence of occupational exposure on hyperuricemia in steelworkers: A nested case-control study. BMC Public Health, 22.","DOI":"10.1186\/s12889-022-13935-x"},{"key":"ref_17","first-page":"7","article-title":"Guidelines for the prevention and treatment of dyslipidemia in adults in China (2016 revised edition)","volume":"11","author":"Zhu","year":"2017","journal-title":"Chinses J. Health Manag."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"9402","DOI":"10.12659\/MSM.920900","article-title":"Validity and Reliability of the International Physical Activity Questionnaire in Chinese Hemodialysis Patients: A Multicenter Study in China","volume":"25","author":"Lou","year":"2019","journal-title":"Med. Sci. Monit."},{"key":"ref_19","first-page":"1197","article-title":"A study on the association between nursing staff\u2019s job adaptation and occupational stress","volume":"54","author":"Sun","year":"2020","journal-title":"Chin. J. Prev. Med."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"e12891","DOI":"10.1111\/jsr.12891","article-title":"A thorough psychometric comparison between Athens Insomnia Scale and Insomnia Severity Index among patients with advanced cancer","volume":"29","author":"Lin","year":"2020","journal-title":"J. Sleep Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"m441","DOI":"10.1136\/bmj.m441","article-title":"Calculating the sample size required for developing a clinical prediction model","volume":"368","author":"Riley","year":"2020","journal-title":"Bmj"},{"key":"ref_22","first-page":"655","article-title":"A 5-year risk prediction model for hyperuricemia in 35~74-year-old health examination population in Taiwan","volume":"14","author":"Yang","year":"2013","journal-title":"China Prev. Med."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"936717","DOI":"10.3389\/fpubh.2022.936717","article-title":"Prevalence of hyperuricemia and the population attributable fraction of modifiable risk factors: Evidence from a general population cohort in China","volume":"10","author":"He","year":"2022","journal-title":"Front. Public Health"},{"key":"ref_24","first-page":"58","article-title":"Establishment and validation of clinical prediction model for recurrence after unilateral chronic subdural hematoma drilling and drainage","volume":"18","author":"Zhuo","year":"2021","journal-title":"J. Clin. Neurosurg."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3628","DOI":"10.1093\/rheumatology\/keaa822","article-title":"Effects of bariatric surgery on serum uric acid in people with obesity with or without hyperuricaemia and gout: A retrospective analysis","volume":"60","author":"Lu","year":"2021","journal-title":"Rheumatology"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1759","DOI":"10.1111\/obr.12940","article-title":"Impact of bariatric surgery on serum uric acid levels and the incidence of gout-A meta-analysis","volume":"20","author":"Yeo","year":"2019","journal-title":"Obes. Rev."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1508","DOI":"10.1007\/s11695-021-05852-6","article-title":"Prevalence and Clinical Predictors of Hyperuricemia in Chinese Bariatric Surgery Patients","volume":"32","author":"Qu","year":"2022","journal-title":"Obes. Surg."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1097\/BOR.0000000000000779","article-title":"The role of diet in hyperuricemia and gout","volume":"33","author":"Yokose","year":"2021","journal-title":"Curr. Opin. Rheumatol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1002\/art.41067","article-title":"Population Impact Attributable to Modifiable Risk Factors for Hyperuricemia","volume":"72","author":"Choi","year":"2020","journal-title":"Arthritis Rheumatol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"j1794","DOI":"10.1136\/bmj.j1794","article-title":"The Dietary Approaches to Stop Hypertension (DASH) diet, Western diet, and risk of gout in men: Prospective cohort study","volume":"357","author":"Rai","year":"2017","journal-title":"Bmj"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1002\/acr.24150","article-title":"Adherence to the Dietary Approaches to Stop Hypertension Diet and Hyperuricemia: A Cross-Sectional Study","volume":"73","author":"Gao","year":"2021","journal-title":"Arthritis Care Res."},{"key":"ref_32","first-page":"845","article-title":"Effects of smoking and aerobic exercise on markers related to metabolic syndrome in male college students","volume":"41","author":"Xiao","year":"2020","journal-title":"Chin. J. Sch. Health"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"989","DOI":"10.1016\/j.numecd.2011.01.003","article-title":"Alcohol intake and the risk of hyperuricaemia: A 6-year prospective study in Japanese men","volume":"22","author":"Nakamura","year":"2012","journal-title":"Nutr. Metab. Cardiovasc. Dis."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2121","DOI":"10.2169\/internalmedicine.50.5506","article-title":"Influence of physical activity intensity and aerobic fitness on the anthropometric index and serum uric acid concentration in people with obesity","volume":"50","author":"Nishida","year":"2011","journal-title":"Intern. Med."},{"key":"ref_35","first-page":"390","article-title":"Research status and prospect of exercise in the prevention and treatment of hyperuricemia","volume":"22","author":"Jiang","year":"2021","journal-title":"China Prev. Med."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1007\/s12020-022-03215-4","article-title":"Predicting risk of obesity and meal planning to reduce the obese in adulthood using artificial intelligence","volume":"78","author":"Kaur","year":"2022","journal-title":"Endocrine"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"107180","DOI":"10.1016\/j.cmpb.2022.107180","article-title":"Harnessing machine learning models for non-invasive pre-diabetes screening in children and adolescents","volume":"226","author":"Kushwaha","year":"2022","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"106451","DOI":"10.1016\/j.cmpb.2021.106451","article-title":"Information fusion and multi-classifier system for miner fatigue recognition in plateau environments based on electrocardiography and electromyography signals","volume":"211","author":"Chen","year":"2021","journal-title":"Comput. Methods Programs Biomed."}],"container-title":["International Journal of Environmental Research and Public Health"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1660-4601\/20\/4\/3411\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:36:28Z","timestamp":1760121388000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1660-4601\/20\/4\/3411"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,15]]},"references-count":38,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["ijerph20043411"],"URL":"https:\/\/doi.org\/10.3390\/ijerph20043411","relation":{},"ISSN":["1660-4601"],"issn-type":[{"value":"1660-4601","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,15]]}}}