{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T08:35:32Z","timestamp":1792053332192,"version":"4.4.0"},"reference-count":71,"publisher":"American Medical Association (AMA)","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"<jats:sec id=\"ab-zoi250401-4\"><jats:title>Importance<\/jats:title><jats:p>Identifying atypical body mass index (BMI) trajectories in children and understanding associated, modifiable early-life factors may help prevent childhood obesity.<\/jats:p><\/jats:sec><jats:sec id=\"ab-zoi250401-5\"><jats:title>Objective<\/jats:title><jats:p>To characterize multiphase BMI trajectories in children and identify associated modifiable early-life factors.<\/jats:p><\/jats:sec><jats:sec id=\"ab-zoi250401-6\"><jats:title>Design, Setting, and Participants<\/jats:title><jats:p>This cohort study included longitudinal data obtained from January 1997 to June 2024, from the Environmental influences on Child Health Outcomes (ECHO) cohort, which included children aged 1 to 9 years with 4 or more weight and height assessments. Analyses were conducted from January to June 2024.<\/jats:p><\/jats:sec><jats:sec id=\"ab-zoi250401-7\"><jats:title>Exposures<\/jats:title><jats:p>Prenatal exposure to substances and stress (smoking, alcohol, depression, anxiety), maternal characteristics (prepregnancy BMI, gestational weight gain), child characteristics (preterm birth, birth weight, breastfeeding), and demographic covariates.<\/jats:p><\/jats:sec><jats:sec id=\"ab-zoi250401-8\"><jats:title>Main Outcomes and Measures<\/jats:title><jats:p>BMI (calculated as weight in kilograms divided by length in meters squared for children aged 1 and 2 years and as weight in kilograms divided by height in meters squared for children older than 2 years) obtained using medical records, staff measurements, caregiver reports, or remote study measures. The analysis was conducted using a multiphase latent growth mixture model.<\/jats:p><\/jats:sec><jats:sec id=\"ab-zoi250401-9\"><jats:title>Results<\/jats:title><jats:p>This study included 9483 children (4925 boys [51.9%]). Two distinct 2-phase BMI patterns were identified: typical and atypical. The typical group (n\u2009=\u20098477 [89.4%]) showed linear decreases in BMI (<jats:italic>b<\/jats:italic><jats:sub>2<\/jats:sub>, \u22120.23 [95% CI, \u22120.24 to \u22120.22]), with the lowest BMI at age 6 years (95% CI, 5.94-6.11), followed by linear increases from 6 to 9 years (slope difference [<jats:italic>b<\/jats:italic><jats:sub>4<\/jats:sub> \u2212 <jats:italic>b<\/jats:italic><jats:sub>2<\/jats:sub>], 0.81 [95% CI, 0.76-0.86];  mean BMI at 9 years: 17.33). The atypical group (n\u2009=\u20091006 [10.6%]) showed a stable BMI from ages 1 to 3.5 years (<jats:italic>b<\/jats:italic><jats:sub>6<\/jats:sub>, 0.06 [95% CI, \u22120.04 to 0.15]), followed by rapid linear increases from ages 3.5 to 9 years (slope difference [<jats:italic>b<\/jats:italic><jats:sub>8<\/jats:sub> \u2212 <jats:italic>b<\/jats:italic><jats:sub>6<\/jats:sub>], 1.44 [95% CI, 1.34-1.55]). At age 9 years, this group reached a mean BMI (26.2) that exceeded the 99th percentile. Prenatal smoking, high prepregnancy BMI, high gestational weight gain, and high birth weight were key risk factors for the atypical trajectory.<\/jats:p><\/jats:sec><jats:sec id=\"ab-zoi250401-10\"><jats:title>Conclusions and Relevance<\/jats:title><jats:p>In this cohort study of children in the ECHO cohort, analyses identified children on the path to obesity as early as age 3.5 years. Modifiable factors could be targeted for early prevention and intervention programs aimed at reducing childhood obesity.<\/jats:p><\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2025.11835","type":"journal-article","created":{"date-parts":[[2025,5,22]],"date-time":"2025-05-22T15:31:18Z","timestamp":1747927878000},"page":"e2511835","source":"Crossref","is-referenced-by-count":24,"title":["Early-Life Factors and Body Mass Index Trajectories Among Children in the ECHO Cohort"],"prefix":"10.1001","volume":"8","author":[{"given":"Chang","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Psychology, Washington State University, Pullman"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sy-Miin","family":"Chow","sequence":"additional","affiliation":[{"name":"Department of Human Development and Family Studies, The Pennsylvania State University, University Park"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Izzuddin M.","family":"Aris","sequence":"additional","affiliation":[{"name":"Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dana","family":"Dabelea","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora"},{"name":"Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora"},{"name":"Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jenae M.","family":"Neiderhiser","sequence":"additional","affiliation":[{"name":"Department of Psychology, The Pennsylvania State University, University Park"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leslie D.","family":"Leve","sequence":"additional","affiliation":[{"name":"College of Education, University of Oregon, Eugene"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Clancy","family":"Blair","sequence":"additional","affiliation":[{"name":"Department of Applied Psychology, New York University, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Diane J.","family":"Catellier","sequence":"additional","affiliation":[{"name":"RTI International, Research Triangle Park, North Carolina"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lance","family":"Couzens","sequence":"additional","affiliation":[{"name":"RTI International, Research Triangle Park, North Carolina"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph M.","family":"Braun","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Brown University, Providence, Rhode Island"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Assiamira","family":"Ferrara","sequence":"additional","affiliation":[{"name":"Kaiser Permanente Northern California Division of Research, Oakland"},{"name":"Upstream Prevention of Adiposity and Diabetes Mellitus (UPSTREAM) Center, Kaiser Permanente Northern California Division of Research, Oakland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Judy L.","family":"Aschner","sequence":"additional","affiliation":[{"name":"Center for Discovery and Innovation, Department of Pediatrics, Hackensack Meridian School of Medicine, Nutley, New Jersey"},{"name":"Department of Pediatrics, Albert Einstein College of Medicine, Bronx, New York"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sean C. 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