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We applied DDRTree to accelerometry data to identify multidimensional physical activity phenotypes in children and adolescents with obesity and assessed their associations with body composition and cardiometabolic. This cross-sectional study included 91 children and adolescents with obesity (43% girls), aged 6\u201317 years, who wore a thigh-mounted accelerometer for 7 days. Multidimensional accelerometry features were extracted and PA phenotypes identified using DDRTree, an unsupervised reversed graph-embedding method that maps high-dimensional data onto a low-dimensional branching manifold. DDRTree identified 3-PA phenotypes. Anthropometry, metabolic outcomes, and a continuous metabolic syndrome risk score were compared across phenotypes using ANCOVA adjusted for age and sex. DDRTree identified three PA phenotypes: Sedentary (24%), Light Activity (55%), and Higher Activity (21%); only three participants met MVPA recommendations. Compared with the Sedentary Pattern, the Higher Activity Pattern accumulated 122\u00a0min\/day less sedentary time and 16.5\u00a0min\/day more MVPA (\n                    <jats:italic>p<\/jats:italic>\n                    \u2009&lt;\u20090.001) and showed lower fat mass percentage, higher fat-free mass percentage, higher insulin sensitivity (SPISE), and a lower metabolic risk score (\n                    <jats:italic>p<\/jats:italic>\n                    \u2009\u2264\u20090.05).\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:italic>Conclusion<\/jats:italic>\n                    : Multidimensional PA phenotypes derived from accelerometry identify clinically meaningful differences in body composition and metabolic risk beyond MVPA duration, supporting phenotype-based approaches for pediatric obesity risk stratification and intervention design.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:table-wrap>\n                      <jats:table>\n                        <jats:tbody>\n                          <jats:tr>\n                            <jats:td align=\"left\">\n                              <jats:bold>What is Known?<\/jats:bold>\n                              \u2022\n                              <jats:italic>Most children and adolescents with obesity do not meet moderate-to-vigorous physical activity recommendations and are at increased risk of adverse cardiometabolic outcomes.<\/jats:italic>\n                              \u2022\n                              <jats:italic>Physical activity volume alone may not fully capture health-relevant movement behaviour; sedentary accumulation, light activity, activity fragmentation, and transitions between activity states may also be associated with metabolic health.<\/jats:italic>\n                            <\/jats:td>\n                          <\/jats:tr>\n                          <jats:tr>\n                            <jats:td align=\"left\">\n                              <jats:bold>What is New?<\/jats:bold>\n                              \u2022\n                              <jats:italic>Multidimensional analysis of thigh-worn accelerometry data identified three distinct physical activity phenotypes, Sedentary, Light Activity, and Higher Activity, even though only three participants met recommended moderate-to-vigorous physical activity levels.<\/jats:italic>\n                              \u2022\n                              <jats:italic>The Higher Activity phenotype was associated with lower fat mass percentage, higher fat-free mass percentage, greater insulin sensitivity, and a lower metabolic risk score than the Sedentary phenotype, supporting assessment beyond moderate-to-vigorous physical activity duration alone<\/jats:italic>\n                              .\n                            <\/jats:td>\n                          <\/jats:tr>\n                        <\/jats:tbody>\n                      <\/jats:table>\n                    <\/jats:table-wrap>\n                  <\/jats:p>","DOI":"10.1007\/s00431-026-07299-2","type":"journal-article","created":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T07:18:54Z","timestamp":1786000734000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Beyond MVPA minutes: physical activity phenotypes are associated with metabolic profiles in children with obesity"],"prefix":"10.1007","volume":"185","author":[{"given":"Alessandro","family":"Gatti","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3405-9364","authenticated-orcid":false,"given":"Matteo","family":"Vandoni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Caterina","family":"Cavallo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vittoria","family":"Carnevale Pellino Carnevale Pellino","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Virginia","family":"Rossi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna","family":"Odone","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gianvincenzo","family":"Zuccotti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Valeria","family":"Calcaterra","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,8,6]]},"reference":[{"key":"7299_CR1","unstructured":"Obesity and overweight. https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/obesity-and-overweight. 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