{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T17:04:41Z","timestamp":1786122281211,"version":"build-2736575974"},"reference-count":32,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T00:00:00Z","timestamp":1781481600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T00:00:00Z","timestamp":1781481600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["dom-pubs.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Diabetes Obesity Metabolism"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>To test the hypothesis that continuous glucose monitoring (CGM) metrics are independently associated with cardiovascular risk factor (CVRF) exposure, particularly low\u2010density lipoprotein cholesterol (LDL\u2010C) and blood pressure (BP), in youth with type 1 diabetes (T1D) enrolled in the international SWEET registry.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods<\/jats:title>\n                    <jats:p>This cross\u2010sectional study included youth aged 6\u201318\u2009years with T1D duration \u2265\u20091\u2009year, not receiving antihypertensive or lipid\u2010lowering therapy and with available CGM profiles (\u2265\u200914\u2009days), lipid and BP data between January 2019 and June 2023. Associations between CGM metrics and LDL\u2010C or BP were analysed using multiple linear regression, adjusted for sex and pubertal status (model 1) and additionally for body mass index\u2013SDS (model 2), diabetes duration (model 3) and HbA1c (model 4).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Data from 3328 subjects (median age 14.3\u2009years, T1D duration 5.6\u2009years, 52.2% male) were analysed. Time in range (TIR) and time in tight range (TITR) were inversely associated with BP\u2010SDS and LDL\u2010C, while time above range (TAR), mean glucose, glucose variability (coefficient of variation (CV)) [%] and glycemia risk index showed positive associations (all\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.01). In multivariable regression models 1\u20133, TIR, TITR, TAR and glycemia risk index remained independently associated with LDL\u2010C and systolic BP\u2010SDS (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001), with CV also independently associated with systolic BP\u2010SDS (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001). In model 4 associations with SBP\u2010SDS were attenuated, whereas those with LDL\u2010C remained significant, although with a reversal direction.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Key CGM metrics, particularly TIR and TITR, are independently associated with LDL\u2010C and BP in youth with T1D, highlighting their potential clinical relevance in the assessment of cardiovascular risk profile, alongside HbA1c.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/dom.70979","type":"journal-article","created":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T02:21:41Z","timestamp":1781576501000},"page":"7982-7992","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Association of Time in Range and Time in Tight Range With Cardiovascular Risk Factor Exposure in Youth With Type 1 Diabetes: A Cross\u2010Sectional Analysis on\n                    <scp>LDL<\/scp>\n                    Cholesterol and Blood Pressure Data From the\n                    <scp>SWEET<\/scp>\n                    International Database"],"prefix":"10.1111","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5168-8317","authenticated-orcid":false,"given":"Claudia","family":"Piona","sequence":"first","affiliation":[{"name":"Section of Pediatric Diabetes and Metabolism, Department of Surgery, Dentistry, Pediatrics, and Gynecology University of Verona  Verona Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Agata","family":"Chobot","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Institute of Medical Sciences University of Opole  Opole Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jantje","family":"Weiskorn","sequence":"additional","affiliation":[{"name":"Diabetes Centre for Children and Adolescents, Children's Hospital AUF DER BULT  Hannover Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arun","family":"Shankar","sequence":"additional","affiliation":[{"name":"Jothydev's Diabetes Research Center, JDC Junction, Mudavanmugal  Trivandrum Kerala India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ingrida","family":"Stankute","sequence":"additional","affiliation":[{"name":"Institute of Endocrinology, Medical Academy Lithuanian University of Health Sciences  Kaunas Lithuania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katrin","family":"Nagl","sequence":"additional","affiliation":[{"name":"Department of Pediatric and Adolescent Medicine Medical University of Vienna  Vienna Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marie\u2010Anne","family":"Burckhardt","sequence":"additional","affiliation":[{"name":"Pediatric Endocrinology and Diabetology University Children's Hospital Basel  Basel Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christina","family":"Kanaka\u2010Gantenbein","sequence":"additional","affiliation":[{"name":"Division of Endocrinology, Metabolism and Diabetes, Diabetes Center and Aghia Sophia Children's Hospital Endo\u2010ERN Center for Rare Pediatric Endocrine Disorders, First Department of Pediatrics, Medical School National and Kapodistrian University of Athens, \u201cAghia Sophia\u201d Children's Hospital  Athens Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesco","family":"Gasparini","sequence":"additional","affiliation":[{"name":"Department of Pediatrics Women's and Children's Health, Azienda Ospedaliero\u2010Universitaria Delle Marche, Salesi Hospital  Ancona Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marina","family":"Cavalin","sequence":"additional","affiliation":[{"name":"Centro De Diabetes Curitiba  Curitiba Paran\u00e1 Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eva","family":"Hauser","sequence":"additional","affiliation":[{"name":"Institute of Epidemiology and Medical Biometry Ulm University  Ulm Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3789-6459","authenticated-orcid":false,"given":"Stefanie","family":"Lanzinger","sequence":"additional","affiliation":[{"name":"Institute of Epidemiology and Medical Biometry Ulm University  Ulm Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claudio","family":"Maffeis","sequence":"additional","affiliation":[{"name":"Section of Pediatric Diabetes and Metabolism, Department of Surgery, Dentistry, Pediatrics, and Gynecology University of Verona  Verona Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"SWEET Study 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