{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T05:10:34Z","timestamp":1788844234484,"version":"build-2803163510"},"reference-count":62,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T00:00:00Z","timestamp":1788825600000},"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. Med."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>There is emerging evidence that frailty, and its early stage, pre-frailty, are closely linked to metabolic changes, particularly in response to environmental factors such as lifestyle and diet. There is therefore a major interest in exploring these links, particularly with regard to the highly prevalent metabolic syndrome (MetS) and heterogeneity in phenotypes due to the multicriteria nature of both syndromes. In order to structure this heterogeneity, this study aimed to identify and characterize novel sub-phenotypes of MetS and (pre-)frailty co-occurrence in older adults, as well as to examine the associated clinical, psychosocial, and behavioral factors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Data from the Whitehall II cohort (2015\u20132016 wave), including 3,398 participants aged \u226560 years, were used. A data-driven approach was applied using agglomerative hierarchical clustering based on selected clinical parameters defining MetS (harmonized consensus definition) and pre-frailty (Fried phenotype). After deriving and describing the resulting sub-phenotypes (SPs)\n                      <jats:bold>,<\/jats:bold>\n                      their associated factors were examined using a multinomial logistic regression model that simultaneously included a broad set of biological, sociodemographic, lifestyle, and health variables.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Four clinical SPs (intra-sex concordance &amp;gt;87%) emerged from this reclassification, each characterized by distinct patterns of cardiometabolic and functional parameters. The first profile (SP1 31.7%) showed the most favorable cardiometabolic parameters and superior functional performance, although handgrip strength and physical activity levels were slightly lower; it was associated with more favorable socio-demographic, lifestyle, and psychosocial characteristics. A second profile (SP2, 28.7%) displayed cardiometabolic burden, particularly hypertension, with still preserved physical functional characteristics. The two last profiles, SP3 (6.4%) characterized by slow gait, lower physical activity, and exhaustion despite largely preserved metabolic parameters, whereas SP4 (33.2%) showing abdominal obesity, hypertriglyceridemia, hyperglycemia, low HDL-cholesterol, and functional impairments, were associated with older age and male sex. Lower fruit and vegetable intake and poorer physical quality-of-life were associated to SP2 and SP4. Depression and poor mental health markedly increased the likelihood of belonging to SP3.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>By structuring heterogeneity into clinically interpretable sub-phenotypes, these findings provide a framework for multidimensional assessment of complex age-related conditions and generate hypotheses regarding potential combinations of underlying metabolic, functional, and psychosocial mechanisms.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmed.2026.1909752","type":"journal-article","created":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T04:26:22Z","timestamp":1788841582000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Clinical sub-phenotypes of co-occurring metabolic syndrome and pre-frailty and their associated factors in older adults: findings 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