<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Xue M</submitter><funding>Project supported by the National Natural Science Foundation of China</funding><pagination>11600</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC7360758</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>10(1)</volume><pubmed_abstract>Our study is major to establish and validate a simple type||diabetes mellitus (T2DM) screening model for identifying high-risk individuals among Chinese adults. A total of 643,439 subjects who participated in the national health examination had been enrolled in this cross-sectional study. After excluding subjects with missing data or previous medical history, 345,718 adults was included in the final analysis. We used the least absolute shrinkage and selection operator models to optimize feature selection, and used multivariable logistic regression analysis to build a predicting model. The results showed that the major risk factors of T2DM were age, gender, no drinking or drinking/time > 25 g, no exercise, smoking, waist-to-height ratio, heart rate, systolic blood pressure, fatty liver and </pubmed_abstract><journal>Scientific reports</journal><pubmed_title>A nomogram model for screening the risk of diabetes in a large-scale Chinese population: an observational study from 345,718 participants.</pubmed_title><pmcid>PMC7360758</pmcid><funding_grant_id>81960608</funding_grant_id><pubmed_authors>Feng Z</pubmed_authors><pubmed_authors>Wang S</pubmed_authors><pubmed_authors>Zhang M</pubmed_authors><pubmed_authors>Xue M</pubmed_authors><pubmed_authors>Su Y</pubmed_authors><pubmed_authors>Yao H</pubmed_authors><pubmed_authors>Wang K</pubmed_authors></additional><is_claimable>false</is_claimable><name>A nomogram model for screening the risk of diabetes in a large-scale Chinese population: an observational study from 345,718 participants.</name><description>Our study is major to establish and validate a simple type||diabetes mellitus (T2DM) screening model for identifying high-risk individuals among Chinese adults. A total of 643,439 subjects who participated in the national health examination had been enrolled in this cross-sectional study. After excluding subjects with missing data or previous medical history, 345,718 adults was included in the final analysis. We used the least absolute shrinkage and selection operator models to optimize feature selection, and used multivariable logistic regression analysis to build a predicting model. The results showed that the major risk factors of T2DM were age, gender, no drinking or drinking/time > 25 g, no exercise, smoking, waist-to-height ratio, heart rate, systolic blood pressure, fatty liver and </description><dates><release>2020-01-01T00:00:00Z</release><publication>2020 Jul</publication><modification>2025-04-29T10:48:37.965Z</modification><creation>2024-11-21T00:39:09.543Z</creation></dates><accession>S-EPMC7360758</accession><cross_references><pubmed>32665620</pubmed><doi>10.1038/s41598-020-68383-7</doi></cross_references></HashMap>