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The current study tested whether poorer cardiometabolic health is associated with brain structure and microstructure development in 10\u201317\u2010year\u2010old youth. Using the Adolescent Brain Cognitive Development Study, we analysed data from 3527 participants with 4433 observations across three waves (single wave:\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u20092745; two waves:\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u2009658 participants; three waves:\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u2009124 participants). We related anthropometric (body\u2010mass index, waist circumference), cardiovascular (systolic and diastolic blood pressure, resting heart rate) and metabolic (haemoglobin A1c, high\u2010density lipoprotein cholesterol) indices to global cortical thickness and surface area, and to white matter fractional anisotropy and mean diffusivity. Bayesian multilevel models were fitted to estimate main and time\u2010interaction effects, and sensitivity analyses tested within\u2010person change, prospective prediction to the next wave, and replaced chronological age with puberty status. Higher resting heart rate was associated with higher mean diffusivity, an association that strengthened over time. Higher waist circumference was associated with larger surface area. Other cardiometabolic measures favoured the null, and sensitivity analyses provided little evidence that wave\u2010to\u2010wave changes in cardiometabolic health tracked contemporaneous brain change or predicted subsequent brain structure. Across late childhood and adolescence, brain architecture appears largely insensitive to short\u2010term variation in cardiometabolic risk indices.\n                  <\/jats:p>","DOI":"10.1002\/hbm.70575","type":"journal-article","created":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T10:34:33Z","timestamp":1780482873000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Cardiometabolic Risk and Structural Brain Development in a Large Community\u2010Based US Cohort"],"prefix":"10.1002","volume":"47","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0974-9304","authenticated-orcid":false,"given":"Dani","family":"Beck","sequence":"first","affiliation":[{"name":"PROMENTA Research Center, Department of Psychology University of Oslo  Oslo Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lars T.","family":"Westlye","sequence":"additional","affiliation":[{"name":"Department of Psychology University of Oslo  Oslo Norway"},{"name":"Center for Precision Psychiatry, Division of Mental Health and Addiction Oslo University Hospital  Oslo Norway"},{"name":"KG Jebsen Centre for Neurodevelopmental Disorders University of Oslo  Oslo Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian K.","family":"Tamnes","sequence":"additional","affiliation":[{"name":"PROMENTA Research Center, Department of Psychology University of Oslo  Oslo Norway"},{"name":"Division of Mental Health and Substance Abuse Diakonhjemmet Hospital  Oslo Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,6,3]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1111\/ijpo.12985"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.5888\/pcd16.180528"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.3109\/00207454.2013.817408"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.2337\/dc25-S002"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.2337\/dci18-0052"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.dcn.2018.04.003"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2022.102949"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.25680"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.26685"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.dcn.2023.101261"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2020.117129"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v080.i01"},{"key":"e_1_2_11_14_1","doi-asserted-by":"publisher","DOI":"10.32614\/RJ-2018-017"},{"key":"e_1_2_11_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11682-019-00036-4"},{"key":"e_1_2_11_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.dcn.2018.03.001"},{"key":"e_1_2_11_17_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2014.00584"},{"key":"e_1_2_11_18_1","doi-asserted-by":"publisher","DOI":"10.1006\/nimg.1998.0395"},{"key":"e_1_2_11_19_1","doi-asserted-by":"publisher","DOI":"10.1111\/ijpo.12149"},{"key":"e_1_2_11_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.mhpa.2024.100611"},{"key":"e_1_2_11_21_1","doi-asserted-by":"publisher","DOI":"10.1161\/HYPERTENSIONAHA.123.21672"},{"key":"e_1_2_11_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0896-6273(02)00569-X"},{"key":"e_1_2_11_23_1","doi-asserted-by":"publisher","DOI":"10.1542\/peds.2017-1904"},{"key":"e_1_2_11_24_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2025.9855"},{"key":"e_1_2_11_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cjca.2020.06.023"},{"key":"e_1_2_11_26_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0033291719001545"},{"key":"e_1_2_11_27_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.20619"},{"key":"e_1_2_11_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2019.116091"},{"key":"e_1_2_11_29_1","volume-title":"Prevalence of Obesity Among Adults and Youth: United States, 2015\u20132016","author":"Hales C. 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