Emily Rose Ashby, Maëliss Cynthia Chloé Lemoine, Guro F Giskeødegård, Trine Moholdt
{"title":"Maternal cardiorespiratory fitness is associated with metabolic hormone concentrations in human milk.","authors":"Emily Rose Ashby, Maëliss Cynthia Chloé Lemoine, Guro F Giskeødegård, Trine Moholdt","doi":"10.1038/s44437-026-00010-5","DOIUrl":"https://doi.org/10.1038/s44437-026-00010-5","url":null,"abstract":"<p><p>The composition of human milk reflects maternal cardiometabolic health, of which cardiorespiratory fitness is a key determinant. Yet, the influence of maternal fitness on milk-borne hormones remains largely unexplored. In this cross-sectional study, we measured peak oxygen uptake during a maximal exercise test in 149 lactating participants and quantified human milk adiponectin and insulin concentrations using enzyme-linked immunosorbent assays. Higher maternal cardiorespiratory fitness was associated with lower concentrations of milk adiponectin after adjustment for body composition and weeks since delivery (<i>β</i> -0.02, 95% CI -0.04 to -0.001). Milk insulin concentrations were inversely associated with fitness after adjustment for body mass index (<i>β</i> -0.02, 95% CI -0.04 to -0.001). This work identifies maternal cardiorespiratory fitness as a previously unrecognised factor associated with human milk hormone concentrations, providing a potential pathway linking maternal physiology with early-life metabolic development.</p>","PeriodicalId":524192,"journal":{"name":"Npj exercise medicine and health","volume":"1 1","pages":"8"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13623634/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149123871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A framework for estimating cardiorespiratory fitness from diverse exercise tests.","authors":"Tomas I Gonzales, Nick Wareham, Soren Brage","doi":"10.1038/s44437-026-00004-3","DOIUrl":"10.1038/s44437-026-00004-3","url":null,"abstract":"<p><p>Comparing cardiorespiratory fitness across populations is hindered by unstandardised exercise testing and canonical estimation methods that assume steady-state exercise while applying group-level metabolic equations. We developed a framework that standardises maximal oxygen consumption (V̇O<sub>2</sub>max) estimation by harmonising dynamic heart rate modelling with individual calibration of the metabolic cost of mechanical work, conditioned on characteristics like body size. We evaluated the framework using submaximal and maximal tests (treadmill walking and running, cycle ergometer, stepping, overground walking) from 911 adults. Agreement between framework estimates and directly measured V̇O<sub>2</sub>max was strong (mean bias: 1.5 ml O<sub>2</sub>∙min<sup>-1</sup>·kg<sup>-1</sup>, Pearson's <i>r</i> = 0.80) and remained robust when excluding body size (<i>r</i> = 0.76). We then applied the framework and canonical methods to 11,307 UK Fenland Study adults to evaluate associations between estimated V̇O<sub>2</sub>max and cardiometabolic risk. Compared to canonical estimates, framework-estimated V̇O<sub>2</sub>max had stronger associations with a combined cardiometabolic risk profile (blood glucose, fasting insulin, high-density lipoprotein cholesterol) in base (ΔAIC: 3483) and body-size adjusted (ΔAIC: 256) models. The framework standardises fitness estimation across diverse tests, yielding a reliable and comparable biomarker of cardiometabolic health.</p>","PeriodicalId":524192,"journal":{"name":"Npj exercise medicine and health","volume":"1 1","pages":"4"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13561033/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148932492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}