{"doi":"10.1161/jaha.118.009754","title":"Assessing Baseline and Temporal Changes in Cardiometabolic Risk Using Metabolic Syndrome Severity and Common Risk Scores","abstract":"\n Background\n \n Type 2 diabetes mellitus (T2\n DM\n ) is considered a cardiovascular disease (\n CVD\n ) risk equivalent, thereby linking assessment of cardiometabolic risk with that of\n CVD\n risk over time. Our goal was to determine how commonly used\n CVD\n risk scores and metabolic syndrome (MetS) severity performed in predicting T2\n DM\n with and without ultimate\n CVD\n .\n \n \n \n Methods and Results\n \n We assessed data from 8273 participants of the ARIC (Atherosclerosis Risk in Communities) Study, using the pooled cohort atherosclerotic\n CVD\n risk score, the Framingham Risk Score, and a MetS severity\n Z\n score to assess their association with future risk for\n CVD\n alone, T2\n DM\n alone, or both over 20 years of follow‐up. Baseline levels of all scores were significantly associated with isolated incident T2\n DM\n (odds ratios [\n OR\n s] for each 1‐\n SD\n increase: atherosclerotic\n CVD\n =1.7, Framingham risk score=1.7, MetS\n Z\n score=5.1). All 3 baseline scores were also significantly associated with isolated incident\n CVD\n (atherosclerotic\n CVD OR\n =2.4, Framingham risk score\n OR\n =2.3, MetS\n Z\n ‐score\n OR\n =1.8), with the 2\n CVD\n scores remaining significant independent of MetS severity. MetS severity was strongly associated with future T2\n DM\n leading to\n CVD\n (MetS\n Z\n ‐score\n OR\n =7.0, atherosclerotic\n CVD OR\n =3.9, Framingham risk score\n OR\n =3.5). Furthermore, changes in MetS severity were independently associated with future T2\n DM\n ‐\n CVD\n progression.\n \n \n \n Conclusions\n \n CVD\n risk scores are associated with risk for future isolated T2\n DM\n in addition to isolated\n CVD\n . However, MetS severity (both baseline and changes over time) was more strongly associated with T2\n DM\n , including T2\n DM\n ultimately leading to\n CVD\n . Following MetS severity within patients over time may identify those at greatest risk of combined cardiometabolic disease.\n \n ","journal":"Journal of the American Heart Association","year":2018,"id":634220,"datarank":0.5416376868966337,"base_score":3.6109179126442243,"endowment":3.6109179126442243,"self_citation_contribution":0.5416376868966337,"citation_network_contribution":0.0,"self_endowment_contribution":0.5416376868966337,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":36,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":363711,"name":"Stephanie L. Filipp","orcid":"0009-0009-9901-566X","position":1,"is_corresponding":false},{"id":502305,"name":"Thomas A. Pearson","orcid":null,"position":2,"is_corresponding":false},{"id":426461,"name":"Mark D. DeBoer","orcid":"0000-0003-1462-591X","position":3,"is_corresponding":false},{"id":363710,"name":"Matthew J. Gurka","orcid":"0000-0002-3371-4582","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Assessing Baseline and Temporal Changes in Cardiometabolic Risk Using Metabolic Syndrome Severity and Common Risk Scores","abstract":"\n Background\n \n Type 2 diabetes mellitus (T2\n DM\n ) is considered a cardiovascular disease (\n CVD\n ) risk equivalent, thereby linking assessment of cardiometabolic risk with that of\n CVD\n risk over time. Our goal was to determine how commonly used\n CVD\n risk scores and metabolic syndrome (MetS) severity performed in predicting T2\n DM\n with and without ultimate\n CVD\n .\n \n \n \n Methods and Results\n \n We assessed data from 8273 participants of the ARIC (Atherosclerosis Risk in Communities) Study, using the pooled cohort atherosclerotic\n CVD\n risk score, the Framingham Risk Score, and a MetS severity\n Z\n score to assess their association with future risk for\n CVD\n alone, T2\n DM\n alone, or both over 20 years of follow‐up. Baseline levels of all scores were significantly associated with isolated incident T2\n DM\n (odds ratios [\n OR\n s] for each 1‐\n SD\n increase: atherosclerotic\n CVD\n =1.7, Framingham risk score=1.7, MetS\n Z\n score=5.1). All 3 baseline scores were also significantly associated with isolated incident\n CVD\n (atherosclerotic\n CVD OR\n =2.4, Framingham risk score\n OR\n =2.3, MetS\n Z\n ‐score\n OR\n =1.8), with the 2\n CVD\n scores remaining significant independent of MetS severity. MetS severity was strongly associated with future T2\n DM\n leading to\n CVD\n (MetS\n Z\n ‐score\n OR\n =7.0, atherosclerotic\n CVD OR\n =3.9, Framingham risk score\n OR\n =3.5). Furthermore, changes in MetS severity were independently associated with future T2\n DM\n ‐\n CVD\n progression.\n \n \n \n Conclusions\n \n CVD\n risk scores are associated with risk for future isolated T2\n DM\n in addition to isolated\n CVD\n . However, MetS severity (both baseline and changes over time) was more strongly associated with T2\n DM\n , including T2\n DM\n ultimately leading to\n CVD\n . Following MetS severity within patients over time may identify those at greatest risk of combined cardiometabolic disease.\n \n ","is_dataset_classified":null,"base_score":3.6109179126442243,"endowment":3.6109179126442243,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"30369320","pmcid":"PMC6201393","openalex_id":"https://openalex.org/W2891168675","authors":[],"funders":[{"funder_name":"NHLBI NIH HHS","grant_id":"R01 HL120960","title":null},{"funder_name":"NIGMS NIH HHS","grant_id":"U54 GM104942","title":null},{"funder_name":"NHLBI NIH HHS","grant_id":"HHSN268201100012C","title":null},{"funder_name":"National Institutes of Health","grant_id":"5R01HL120960-02","title":"An Ethnicity-Specific MetS Severity Score to Assess Risk: The Jackson Heart Study"},{"funder_name":"National Institutes of Health","grant_id":"3U54GM104942-05S3","title":"Developing novel strategies to increase COVID-19 testing among underserved and vulnerable populations in West Virginia through community and state partnerships"},{"funder_name":"National Institutes of Health","grant_id":"2U54GM104942-02","title":"West Virginia Clinical and Translational Science Institute: Improving Health through Partnerships and Transformative Research"}],"total_grants":6,"fwci":1.8011,"citation_percentile":0.86222568,"influential_citations":0,"citation_trend":[{"year":2018,"count":2},{"year":2019,"count":3},{"year":2020,"count":3},{"year":2021,"count":4},{"year":2022,"count":6},{"year":2023,"count":4},{"year":2024,"count":4},{"year":2025,"count":4},{"year":2026,"count":6}],"oa_status":"gold","license":"cc-by-nc-nd","oa_locations":[{"url":"https://www.ahajournals.org/doi/pdf/10.1161/JAHA.118.009754","host_type":"journal"},{"url":"https://www.ahajournals.org/doi/pdf/10.1161/JAHA.118.009754","host_type":"publisher"},{"url":"https://www.ahajournals.org/doi/full/10.1161/JAHA.118.009754","host_type":"publisher"},{"url":"https://doi.org/10.1161/jaha.118.009754","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/30369320","host_type":"repository"},{"url":"https://doaj.org/article/cbb8ac2607de4955942ddcc27c0934eb","host_type":"repository"},{"url":"http://europepmc.org/pmc/articles/PMC6201393","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6201393","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC6201393","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC6201393?pdf=render","host_type":"Europe_PMC"},{"url":"http://dx.doi.org/10.1161/JAHA.118.009754","host_type":""},{"url":"https://dx.doi.org/10.1161/jaha.118.009754","host_type":""}],"fields_of_study":["Diabetes, Cardiovascular Risks, and Lipoproteins","Cardiovascular Function and Risk Factors","Liver Disease Diagnosis and Treatment","03 medical and health sciences","0302 clinical medicine"],"mesh_terms":["Blood Glucose","Blood Pressure","Cardiovascular Diseases","Diabetes Mellitus, Type 2","Female","Humans","Cholesterol, HDL","Cholesterol, LDL","Male","Middle Aged","Severity of Illness Index","Triglycerides","Cohort Studies","Odds Ratio","Risk Assessment","Metabolic Syndrome","Waist Circumference"],"keywords":["Medicine","Framingham Risk Score","Internal medicine","Metabolic syndrome","Atherosclerosis Risk in Communities","Diabetes mellitus","Cohort","Odds ratio","Risk assessment","Disease","Obesity","Endocrinology","Prediction","Type 2 diabetes mellitus","Cardiovascular disease","Blood Glucose","Male","Blood Pressure","Severity of Illness Index","Cohort Studies","Diseases of the circulatory (Cardiovascular) system","Humans","Triglycerides","Original Research","Cholesterol, HDL","Cholesterol, LDL","Middle Aged","Diabetes Mellitus, Type 2","Cardiovascular Diseases","RC666-701","Female","Waist Circumference"],"sdg_mappings":[{"sdg_number":3,"sdg_label":"3. 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