{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T11:10:12Z","timestamp":1788952212441,"version":"build-2803163510"},"reference-count":31,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T00:00:00Z","timestamp":1788912000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>While early growth and current weight individually affect cardiometabolic health, their combined effects are poorly understood. This study examines the integrated impact of birth weight and current weight status on the clustering of cardiometabolic risk factors (CMRFs) in children and adolescents.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This study analyzed data from 15,910 children and adolescents aged 6 to 18 years from a multistage cross-sectional survey. Participants were categorized into six combined exposure groups based on birth weight (normal\/low\/high) and current weight status (non-overweight\/overweight\/obese). Multivariable logistic regression models assessed the associations of these categories with CMRF clustering (defined as the presence of 2 or more of the following: elevated blood pressure, impaired fasting glucose, elevated triglycerides, and low high-density lipoprotein cholesterol). Additive interaction was evaluated using the relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI). Statistical mediation analysis decomposed the association of birth weight with CMRF clustering into indirect (current BMI) and direct pathways.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Of 15,910 participants, 6.30% had CMRF clustering. In fully adjusted models, compared with the normal birth weight\/non-overweight group, the low birth weight\/overweight-obese group had the highest odds of CMRF clustering (OR\u00a0=\u00a06.11, 95% CI: 3.32 to 10.53,\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0&amp;lt;\u00a00.001). No statistically significant additive interaction was observed between low birth weight and current overweight\/obesity (RERI\u00a0=\u00a01.57,\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0=\u00a00.193; AP\u00a0=\u00a00.26,\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0=\u00a00.127; SI\u00a0=\u00a01.44,\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0=\u00a00.158). Mediation analysis revealed a competitive mediation pattern: birth weight had a significant positive indirect effect on CMRF clustering through current BMI (\n                      <jats:italic>\u03b2<\/jats:italic>\n                      \u00a0=\u00a00.0091,\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0&amp;lt;\u00a00.001) and a significant negative direct effect (\n                      <jats:italic>\u03b2<\/jats:italic>\n                      = \u22120.0144,\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0=\u00a00.002), while the total effect was not statistically significant (\n                      <jats:italic>\u03b2<\/jats:italic>\n                      = \u22120.0052,\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0=\u00a00.326).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Although the combination of LBW and current overweight\/obesity conferred the greatest risk for CMRF clustering, this was driven primarily by current weight status rather than a synergistic effect. However, LBW remained independently associated with metabolic risk after BMI adjustment, indicating distinct pathophysiological pathways. Thus, preventing excessive weight gain in low birth weight children is critical for reducing cardiometabolic risk.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fendo.2026.1917806","type":"journal-article","created":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T10:16:36Z","timestamp":1788948996000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Combined association of birth weight and current overweight\/obesity with cardiometabolic risk factor clustering in Chinese children and adolescents: a cross-sectional study"],"prefix":"10.3389","volume":"17","author":[{"given":"Gang","family":"Tian","sequence":"first","affiliation":[{"name":"Henan Province Hypertension Precision Prevention and Control Engineering Research Center, Henan Provincial People\u2019s Hospital, Zhengzhou University People\u2019s Hospital","place":["Zhengzhou, Henan, 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Province Hypertension Precision Prevention and Control Engineering Research Center, Henan Provincial People\u2019s Hospital, Zhengzhou University People\u2019s Hospital","place":["Zhengzhou, Henan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yajing","family":"Guo","sequence":"additional","affiliation":[{"name":"College of Public Health, Zhengzhou University","place":["Zhengzhou, Henan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengwei","family":"Wang","sequence":"additional","affiliation":[{"name":"Henan Provincial Center for Disease Control and Prevention","place":["Zhengzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Gao","sequence":"additional","affiliation":[{"name":"Henan Provincial Center for Disease Control and Prevention","place":["Zhengzhou, 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China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhicheng","family":"Han","sequence":"additional","affiliation":[{"name":"Henan Province Hypertension Precision Prevention and Control Engineering Research Center, Henan Provincial People\u2019s Hospital, Zhengzhou University People\u2019s Hospital","place":["Zhengzhou, Henan, China"]},{"name":"Henan Engineering Technology Research Center for Prevention and Treatment of Panvascular Diseases, Henan Provincial People\u2019s Hospital, Zhengzhou University People\u2019s Hospital","place":["Zhengzhou, Henan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jialiang","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Henan Provincial People\u2019s Hospital, Zhengzhou University People\u2019s Hospital","place":["Zhengzhou, Henan, 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