{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:26:19Z","timestamp":1760239579258,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2020,11,30]],"date-time":"2020-11-30T00:00:00Z","timestamp":1606694400000},"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>A screening model for estimating undiagnosed diabetes mellitus (UDM) is important for early medical care. There is minimal research and a serious lack of screening models for people with a family history of diabetes (FHD), especially one which incorporates gender characteristics. Therefore, the primary objective of our study was to develop a screening model for estimating UDM among people with FHD and enable its validation. We used data from the Korean National Health and Nutrition Examination Survey (KNHANES). KNAHNES (2010\u20132016) was used as a developmental cohort (n = 5939) and was then evaluated in a validation cohort (n = 1047) KNHANES (2017). We developed the screening model for UDM in male (SMM), female (SMF), and male and female combined (SMP) with FHD using backward stepwise logistic regression analysis. The SMM and SMF showed an appropriate performance (area under curve (AUC) = 76.2% and 77.9%) compared with SMP (AUC = 72.9%) in the validation cohort. Consequently, simple screening models were developed and validated, for the estimation of UDM among patients in the FHD group, which is expected to reduce the burden on the national health care system.<\/jats:p>","DOI":"10.3390\/ijerph17238903","type":"journal-article","created":{"date-parts":[[2020,11,30]],"date-time":"2020-11-30T10:26:12Z","timestamp":1606731972000},"page":"8903","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Screening Model for Estimating Undiagnosed Diabetes among People with a Family History of Diabetes Mellitus: A KNHANES-Based Study"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1492-6635","authenticated-orcid":false,"given":"Kwang Sun","family":"Ryu","sequence":"first","affiliation":[{"name":"Cancer Big Data Center, National Cancer Center, Goyang-si 10408, Gyeonggi-do, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0234-1872","authenticated-orcid":false,"given":"Ha Ye Jin","family":"Kang","sequence":"additional","affiliation":[{"name":"Cancer Big Data Center, National Cancer Center, Goyang-si 10408, Gyeonggi-do, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sang Won","family":"Lee","sequence":"additional","affiliation":[{"name":"Cancer Big Data Center, National Cancer Center, Goyang-si 10408, Gyeonggi-do, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hyun Woo","family":"Park","sequence":"additional","affiliation":[{"name":"Healthcare AI Team, National Cancer Center, Goyang-si 10408, Gyeonggi-do, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1816-2959","authenticated-orcid":false,"given":"Na Young","family":"You","sequence":"additional","affiliation":[{"name":"Cancer Big Data Center, National Cancer Center, Goyang-si 10408, Gyeonggi-do, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jae Ho","family":"Kim","sequence":"additional","affiliation":[{"name":"Cancer Big Data Center, National Cancer Center, Goyang-si 10408, Gyeonggi-do, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7129-2133","authenticated-orcid":false,"given":"Yul","family":"Hwangbo","sequence":"additional","affiliation":[{"name":"Healthcare AI Team, National Cancer Center, Goyang-si 10408, Gyeonggi-do, Korea"},{"name":"Division of Endocrinology, Department of Internal Medicine, National Cancer Center, Goyang-si 10408, Gyeonggi-do, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5336-3874","authenticated-orcid":false,"given":"Kui Son","family":"Choi","sequence":"additional","affiliation":[{"name":"Cancer Big Data Center, National Cancer Center, Goyang-si 10408, Gyeonggi-do, Korea"},{"name":"Graduate School of Cancer Science and Policy, National Cancer Center, Goyang-si 10408, Gyeonggi-do, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0537-8355","authenticated-orcid":false,"given":"Hyo Soung","family":"Cha","sequence":"additional","affiliation":[{"name":"Cancer Big Data Center, National Cancer Center, Goyang-si 10408, Gyeonggi-do, Korea"},{"name":"Healthcare AI Team, National Cancer Center, Goyang-si 10408, Gyeonggi-do, Korea"},{"name":"Graduate School of Cancer Science and Policy, National Cancer Center, Goyang-si 10408, Gyeonggi-do, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,30]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2020, January 05). Global Report on Diabetes. Available online: https:\/\/apps.who.int\/iris\/handle\/10665\/204871."},{"key":"ref_2","unstructured":"World Health Organization (2020, April 05). Classification of Diabetes Mellitus. Available online: https:\/\/apps.who.int\/iris\/handle\/10665\/325182."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1111\/pedi.12613","article-title":"Screening, staging, and naming of presymptomatic type 1 diabetes","volume":"19","author":"Becker","year":"2018","journal-title":"Pediatr. Diabetes"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"183","DOI":"10.3904\/kjim.2009.24.3.183","article-title":"Early detection of asymptomatic coronary artery disease in patients with type 2 diabetes mellitus","volume":"24","author":"Yoo","year":"2009","journal-title":"Korean J. Intern. Med."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"17016","DOI":"10.1038\/nrdp.2017.16","article-title":"Type 1 diabetes mellitus","volume":"3","author":"Katsarou","year":"2017","journal-title":"Nat. Rev. Dis. Primers"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"180","DOI":"10.3904\/kjim.2009.24.3.180","article-title":"Early Detection of Asymptomatic Coronary Artery Disease in Patients with Type 2 Diabetes Mellitus","volume":"24","author":"Youn","year":"2009","journal-title":"Korean J. Intern. Med."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"783","DOI":"10.1038\/hr.2015.72","article-title":"Hypertension is an independent risk factor for type 2 diabetes: The Korean genome and epidemiology study","volume":"38","author":"Kim","year":"2015","journal-title":"Hypertens. Res."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"42685","DOI":"10.1038\/srep42685","article-title":"Development and evaluation of a risk score for type 2 diabetes mellitus among middle-aged Chinese rural population based on the RuralDiab Study","volume":"7","author":"Zhou","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Ryu, K.S., Lee, S.W., Batbaatar, E., Lee, J.W., Choi, K.S., and Cha, H.S. (2020). A deep learning model for estimation of patients with undiagnosed diabetes. Appl. Sci., 10.","DOI":"10.3390\/app10010421"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"727","DOI":"10.2337\/diacare.27.3.727","article-title":"A Danish diabetes risk score for targeted screening: The Inter99 Study","volume":"27","author":"Glumer","year":"2004","journal-title":"Diabetes Care"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1723","DOI":"10.2337\/dc11-2347","article-title":"A simple screening score for diabetes for the Korean population: Development, validation, and comparison with other scores","volume":"35","author":"Lee","year":"2012","journal-title":"Diabetes Care"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Katulanda, P., Hill, N.R., Stratton, I., Sheriff, R., De Silva, S.D.N., and Matthews, D.R. (2016). Development and validation of a diabetes risk score for screening undiagnosed diabetes in Sri Lanka (SLDRISK). BMC Endocr. Disord., 16.","DOI":"10.1186\/s12902-016-0124-8"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1040","DOI":"10.2337\/dc07-1150","article-title":"Diabetes risk calculator: A simple tool for detecting undiagnosed diabetes and pre-diabetes","volume":"31","author":"Heikes","year":"2008","journal-title":"Diabetes Care"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1872","DOI":"10.2337\/dc05-2141","article-title":"A risk score for predicting incident diabetes in the Thai population","volume":"29","author":"Aekplakorn","year":"2006","journal-title":"Diabetes Care"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Nanri, A., Nakagawa, T., Kuwahara, K., Yamamoto, S., Honda, T., Okazaki, H., Uehara, A., Yamamoto, M., Miyamoto, T., and Kochi, T. (2015). Development of Risk Score for Predicting 3-Year Incidence of Type 2Diabetes: Japan Epidemiology Collaboration on Occupational Health Study. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0142779"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1111\/j.1464-5491.2010.02943.x","article-title":"A simple Chinese risk score for undiagnosed diabetes","volume":"27","author":"Gao","year":"2010","journal-title":"Diabetic Med."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"213","DOI":"10.2337\/diacare.22.2.213","article-title":"Performance of a predictive model to identify undiagnosed diabetes in a health care setting","volume":"22","author":"Baan","year":"1999","journal-title":"Diabetes Care"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1079","DOI":"10.1093\/aje\/kwq026","article-title":"Improvements in ability to detect undiagnosed diabetes by using information on family history among adults in the United States","volume":"171","author":"Yang","year":"2010","journal-title":"Am. J. Epidemiol."},{"key":"ref_19","unstructured":"(2020, November 01). The Seventh Korea National Health and Nutrition Examination Survey (KNHANES V-II) 2017, Korea Centers for Disease Control and Prevention. Available online: https:\/\/knhanes.cdc.go.kr."},{"key":"ref_20","unstructured":"World Health Organization (2020, October 18). Regional Office for the Western Pacific. The Asia-Pacific Perspective: Redefining Obesity and its Treatment. Sydney: Health Communications Australia., Available online: https:\/\/apps.who.int\/iris\/handle\/10665\/206936."},{"key":"ref_21","unstructured":"International Diabetes Federation (2020, October 18). IDF Diabetes Atlas, 6th Edition. Available online: https:\/\/www.idf.org\/e-library\/epidemiology-research\/diabetes-atlas\/19-atlas-6th-edition.html."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2228","DOI":"10.1161\/CIRCULATIONAHA.118.037885","article-title":"Age at Diagnosis of Type 2 Diabetes Mellitus and Associations with Cardiovascular and Mortality Risks: Findings from the Swedish National Diabetes Registry","volume":"139","author":"Sattar","year":"2019","journal-title":"Circulation"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1093\/epirev\/mxm008","article-title":"Comparison of body mass index, waist circumference and waist\/hip ratio in predicting incident diabetes: A meta-analysis","volume":"29","author":"Vazquez","year":"2007","journal-title":"Epidemiol. Rev."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Siren, R., Eriksson, J.G., and Vanhanen, H. (2012). Waist circumference a good indicator of future risk for type 2 diabetes and cardiovascular disease. BMC Public Health, 12.","DOI":"10.1186\/1471-2458-12-631"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3105","DOI":"10.2337\/dc07-0945","article-title":"Does Waist Circumference Predict Diabetes and Cardiovascular Disease beyond Commonly Evaluated Cardiometabolic Risk Factors?","volume":"30","author":"Janiszewski","year":"2007","journal-title":"Diabetes Care"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Steiner, J.L., Crowell, K.T., and Lang, C.H. (2016). Impact of alcohol on glycemic control and insulin action. Biomolecules, 5.","DOI":"10.3390\/biom5042223"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2123","DOI":"10.2337\/dc09-0227","article-title":"Alcohol as a Risk Factor for Type 2 Diabetes: A Systematic Review and Meta-Analysis","volume":"32","author":"Baliunas","year":"2009","journal-title":"Diabetes Care"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1001\/jama.282.3.279","article-title":"Should Patients with Diabetes Drink to Their Health?","volume":"282","author":"Criqui","year":"1999","journal-title":"JAMA"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"719","DOI":"10.2337\/diacare.28.3.719","article-title":"Moderate alcohol consumption lowers the risk of type 2 diabetes: A meta-analysis of prospective observational studies","volume":"28","author":"Koppes","year":"2005","journal-title":"Diabetes Care"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"29","DOI":"10.14423\/SMJ.0000000000000214","article-title":"Relation between BMI and diabetes mellitus and its complications among US older adults","volume":"108","author":"Gray","year":"2015","journal-title":"South Med. J."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1097\/00006254-200203000-00018","article-title":"Willett WC. Diet, lifestyle, and the risk of type 2 diabetes mellitus in women","volume":"57","author":"Hu","year":"2002","journal-title":"Obstet. Gynecol. Surv."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1093\/oxfordjournals.aje.a009256","article-title":"Weight change and diabetes incidence: Findings from a national cohort of US adults","volume":"146","author":"Ford","year":"1997","journal-title":"Am. J. Epidemiol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2806","DOI":"10.2337\/diacare.27.12.2806","article-title":"Trends in the Prevalence and Ratio of Diagnosed to Undiagnosed Diabetes According to Obesity Levels in the U.S","volume":"27","author":"Gregg","year":"2004","journal-title":"Diabetes Care"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1038\/s41440-018-0034-4","article-title":"Hypertension with diabetes mellitus: Physiology and pathology","volume":"41","author":"Ohishi","year":"2018","journal-title":"Hypertens. Res."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"710","DOI":"10.1038\/hr.2017.21","article-title":"Association between changes in systolic blood pressure and incident diabetes in a community-based cohort study in Korea","volume":"40","author":"Lee","year":"2017","journal-title":"Hypertens. Res."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1081\/CEH-200031945","article-title":"Diabetes and hypertension: Pathogenesis, prevention and treatment","volume":"26","author":"Landsberg","year":"2004","journal-title":"Clin. Exp. Hypertens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1889","DOI":"10.2337\/dc08-0405","article-title":"Association between raised blood pressure and dysglycemia in Hong Kong Chinese","volume":"31","author":"Cheung","year":"2008","journal-title":"Diabetes Care"},{"key":"ref_38","first-page":"542","article-title":"Is insulin an independent risk factor for hypertension?","volume":"26","author":"Balkau","year":"1997","journal-title":"The Paris Prospective Study. Int. J. Epidemiol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1862","DOI":"10.1210\/jcem.84.6.5724","article-title":"Hypertension in women","volume":"84","author":"August","year":"1999","journal-title":"J. Clin. Endocrinol. Metab."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1161\/01.HYP.25.3.305","article-title":"Prevalence of hypertension in the US adult population: Results of the Third National Health and Nutrition Examination Survey, 1988\u20131991","volume":"25","author":"Burt","year":"1995","journal-title":"Hypertension"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Sandberg, K., and Ji, H. (2012). Sex differences in primary hypertension. Biol. Sex Differ., 3.","DOI":"10.1186\/2042-6410-3-7"}],"container-title":["International Journal of Environmental Research and Public Health"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1660-4601\/17\/23\/8903\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:39:41Z","timestamp":1760179181000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1660-4601\/17\/23\/8903"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,30]]},"references-count":41,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2020,12]]}},"alternative-id":["ijerph17238903"],"URL":"https:\/\/doi.org\/10.3390\/ijerph17238903","relation":{},"ISSN":["1660-4601"],"issn-type":[{"type":"electronic","value":"1660-4601"}],"subject":[],"published":{"date-parts":[[2020,11,30]]}}}