<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>10</volume><submitter>Yang D</submitter><pubmed_abstract>&lt;h4>Background&lt;/h4>Anthropometric indexes offer a practical approach to identifying metabolic syndrome (MetS) and its components. However, there is a scarcity of research on anthropometric indexes tailored to predict MetS in populations from resource-limited regions.&lt;h4>Objective&lt;/h4>This study aimed to examine the association between 8 easy-to-collect anthropometric indexes and MetS, and determine the most appropriate indexes to identify the presence of MetS for adults in resource-limited areas.&lt;h4>Methods&lt;/h4>A total of 10,520 participants aged 18-85 years from Ningxia Hui Autonomous Region, China, were included in this cross-sectional study. Participants were recruited through a stratified sampling approach from January 1, 2020, to December 31, 2021. MetS was defined using the Internati</pubmed_abstract><journal>JMIR public health and surveillance</journal><pagination>e57799</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11622702</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Utility of Anthropometric Indexes for Detecting Metabolic Syndrome in Resource-Limited Regions of Northwestern China: Cross-Sectional Study.</pubmed_title><pmcid>PMC11622702</pmcid><pubmed_authors>Liu Y</pubmed_authors><pubmed_authors>Ma L</pubmed_authors><pubmed_authors>Shi C</pubmed_authors><pubmed_authors>Yang D</pubmed_authors><pubmed_authors>Cheng Y</pubmed_authors><pubmed_authors>Shi H</pubmed_authors></additional><is_claimable>false</is_claimable><name>Utility of Anthropometric Indexes for Detecting Metabolic Syndrome in Resource-Limited Regions of Northwestern China: Cross-Sectional Study.</name><description>&lt;h4>Background&lt;/h4>Anthropometric indexes offer a practical approach to identifying metabolic syndrome (MetS) and its components. However, there is a scarcity of research on anthropometric indexes tailored to predict MetS in populations from resource-limited regions.&lt;h4>Objective&lt;/h4>This study aimed to examine the association between 8 easy-to-collect anthropometric indexes and MetS, and determine the most appropriate indexes to identify the presence of MetS for adults in resource-limited areas.&lt;h4>Methods&lt;/h4>A total of 10,520 participants aged 18-85 years from Ningxia Hui Autonomous Region, China, were included in this cross-sectional study. Participants were recruited through a stratified sampling approach from January 1, 2020, to December 31, 2021. MetS was defined using the Internati</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Nov</publication><modification>2026-03-13T10:27:23.776Z</modification><creation>2025-04-21T21:48:45.083Z</creation></dates><accession>S-EPMC11622702</accession><cross_references><pubmed>39611790</pubmed><doi>10.2196/57799</doi></cross_references></HashMap>