{"doi":"10.1093/sleep/zsaa256","title":"Blunted rest–activity rhythms link to higher body mass index and inflammatory markers in children","abstract":"STUDY OBJECTIVES: Disturbances of rest-activity rhythms are associated with higher body mass index (BMI) in adults. Whether such relationship exists in children is unclear. We aimed to examine cross-sectional associations of rest-activity rhythm characteristics with BMI z-score and obesity-related inflammatory markers in school-age children. METHODS: Participants included 411 healthy children (mean ± SD age 10.1 ± 1.3 years, 50.8% girls) from a Mediterranean area of Spain who wore wrist accelerometers for 7 consecutive days. Metrics of rest-activity rhythm were derived using both parametric and nonparametric approaches. Obesity-related inflammatory markers were measured in saliva (n = 121). RESULTS: In a multivariable-adjusted model, higher BMI z-score is associated with less robust 24-h rest-activity rhythms as represented by lower relative amplitude (-0.16 [95% CI -0.29, -0.02] per SD, p = 0.02). The association between BMI z-score and relative amplitude persisted with additional adjustment for sleep duration, and attenuated after adjustment for daytime activity level. Less robust rest-activity rhythms were related to increased levels of several salivary pro-inflammatory markers, including C-reactive protein, which is inversely associated with relative amplitude (-32.6% [-47.8%, -12.9%] per SD), independently of BMI z-score, sleep duration, and daytime activity level. CONCLUSION: Blunted rest-activity rhythms are associated with higher BMI z-score and salivary pro-inflammatory markers already at an early age. The association with BMI z-score seem to be independent of sleep duration, and those with pro-inflammatory markers further independent of BMI z-score and daytime activity. Novel intervention targets at an early age based on improving the strength of rest-activity rhythms may help to prevent childhood obesity and related inflammation. CLINICAL TRIALS REGISTRATION: NCT02895282.","journal":"SLEEP","year":2020,"id":96839,"datarank":1.7052141596378916,"base_score":3.5553480614894135,"endowment":3.5553480614894135,"self_citation_contribution":0.5333022092234121,"citation_network_contribution":1.1719119504144795,"self_endowment_contribution":0.5333022092234121,"citer_contribution":1.1719119504144795,"corpus_percentile":null,"corpus_rank":null,"citation_count":34,"citer_count":31,"citers_with_citation_signal":27,"citers_with_endowment":27,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8575,"is_data_producer":true,"deposit_databanks":{"ClinicalTrials.gov":["NCT02895282"]},"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":315700,"name":"Nuria Martínez-Lozano","orcid":null,"position":1,"is_corresponding":false},{"id":313403,"name":"Asta Tvarijonaviciute","orcid":"0000-0002-5323-5001","position":2,"is_corresponding":false},{"id":313404,"name":"Rafael Ríos","orcid":"0000-0003-2505-3910","position":3,"is_corresponding":false},{"id":249994,"name":"Frank A. J. L. Scheer","orcid":"0000-0002-2014-7582","position":4,"is_corresponding":false},{"id":249990,"name":"Marta Garaulet","orcid":"0000-0002-4066-3509","position":5,"is_corresponding":false},{"id":249991,"name":"Jingyi Qian","orcid":"0000-0002-8793-9330","position":0,"is_corresponding":true}],"reference_count":64,"raw_metadata":null,"created_at":"2026-07-18T22:35:06.014648Z","pmid":"33249510","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}