{"doi":"10.1123/jmpb.2022-0036","title":"Calibrating Physical Activity and Sedentary Behavior for Hip-Worn Accelerometry in Older Women With Two Epoch Lengths: The Women’s Health Initiative Objective Physical Activity and Cardiovascular Health Calibration Study","abstract":"Purpose : The purpose of this study was to develop 60-s epoch accelerometer intensity cut points for vertical axis count and vector magnitude (VM) output from hip-worn triaxial accelerometers among women 60–91 years old. We also compared these cut points against cut points derived by multiplying 15-s epoch cut points by four. Methods : Two hundred apparently healthy women wore an ActiGraph GT3X+ accelerometer on their hip while performing a variety of laboratory-based activities that were sedentary (watching television and assembling a puzzle), low light (washing/drying dishes), high light (laundry and dust mopping), or moderate-to-vigorous physical activity (400-m walk) intensity. Oxygen uptake was measured using an Oxycon portable calorimeter. Sedentary behavior and physical activity intensity cut points for vertical axis and VM counts were derived for 60-s epochs from receiver operating characteristic and by multiplying the 15-s cut points by four; both were compared with oxygen uptake. Results : The median age was 74.5 years (interquartile range 70–83). The 60-s epoch cut points for vertical counts were 0 sedentary, 1–73 low light, 74–578 high light, and ≥579 moderate-to-vigorous physical activity. The 60-s epoch cut points for VM were 0–88 sedentary, 89–663 low light, 664–1,730 high light, and ≥1,731 moderate-to-vigorous physical activity. For both sets of cut points, the receiver operating characteristic approach yielded more accurate estimates than the multiplication approach. Conclusion : The derived 60-s epoch cut points for vertical counts and VM can be applied to epidemiologic studies to define sedentary behavior and physical activity intensities in older adult populations.","journal":"Journal for the Measurement of Physical Behaviour","year":2023,"id":388223,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8952,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":591896,"name":"Fang Wen","orcid":"0000-0001-5799-4569","position":1,"is_corresponding":false},{"id":320955,"name":"Christopher C. Moore","orcid":"0000-0001-6027-1732","position":2,"is_corresponding":false},{"id":61604,"name":"Michael J. Lamonte","orcid":"0000-0002-6669-5242","position":3,"is_corresponding":false},{"id":20423,"name":"I‐Min Lee","orcid":"0000-0002-1083-6907","position":4,"is_corresponding":false},{"id":302270,"name":"Andrea Z. LaCroix","orcid":"0000-0002-9532-976X","position":5,"is_corresponding":false},{"id":334533,"name":"Chongzhi Di","orcid":"0000-0002-1371-581X","position":6,"is_corresponding":false},{"id":231463,"name":"Kelly R. Evenson","orcid":"0000-0002-3720-5830","position":0,"is_corresponding":true}],"reference_count":26,"raw_metadata":null,"created_at":"2026-07-19T01:18:13.977537Z","pmid":"38037607","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":[]}