{"doi":"10.3389/fpubh.2025.1653392","title":"Commentary: Impact of resistance training intensity on body composition and nutritional intake among college women with overweight and obesity: a cluster randomized controlled trial","abstract":"Cluster randomized controlled trials (cRCTs) are multilevel experimental designs in which groups of participants are randomly assigned to a condition (e.g., an exercise intervention) such that all individuals nested in a naturally occurring group (i.e., cluster) receive the same treatment (1)(2)(3). This design is often utilized when individual randomization is not feasible for various reasons (e.g., concerns about contamination of study conditions, logistical difficulties). There are several factors to consider when selecting this design (1,4,5); one of the most important is the number of clusters per experimental arm (6,7). At a minimum, at least two clusters must be randomized to each condition (1), just as more than one participant must be assigned to a condition during traditional individually randomized RCTs. Many investigators experience resource constraints (e.g., funding), leading to fewer clusters. However, resources may be wasted if spent on severely underpowered studies, and regardless of the number of resources, results from cRCTs assigning <2 clusters per condition are uninterpretable as randomized experiments because cluster membership is perfectly confounded with treatment assignment. The optimal number of clusters depends on many factors, including intra-class correlation coefficients, effect sizes, and analysis method (7,8). Based on our interest in cRCTs (9,10), we read the Wang et al.investigation (11). We commend this research team for coordinating a twelve-week exercise intervention. An investigation of this size requires high effort and dedication. However, we have identified a fundamental flaw in the experimental design, including the statistical approach, which invalidates the corresponding interpretations.Wang et al. (11) aimed to examine the effects of three different resistance training loads versus a control on body composition and nutritional intake in a sample of women who were overweight or had obesity. The twelve-week resistance programs were designed to be completed using loads defined as the following: a) Low-intensity (LI): 45-50% one-repetition maximum (1RM), b) Moderate-intensity (MI): 60-65% 1RM, and c) High-intensity (HI): 75-80% 1RM. The manuscript (11) defined four campuses in Yichen, Jiangxi, China, which were used to complete this trial, with each campus representing a single cluster: LI was completed at the \"new campus\" of Early Childhood Teachers College, while MI was completed at the \"new campus\" and HI was completed at the \"old campus\" of Yichun College. The control group (CG) was conducted at the Early Childhood Teachers College Gaoan campus. Therefore, the participants were not randomly assigned to a particular campus or group, but instead, each naturally occurring group (i.e., cluster) was assigned a resistance training protocol. To illustrate, Table 1 was created with the data in the manuscript and the data provided in the Supplementary material, specifically with the change in percent (%) body fat. We thank the authors for their transparency and for making their raw data publicly accessible. Our intent with Table 1 is to clearly show that one cannot separate whether the differences in mean responses are due to the treatment (e.g., high vs. low loads) or the unique characteristics of the clusters (i.e., campuses) themselves. Said differently, there is no withincluster variation in treatment assignment; group (treatment) is perfectly collinear with cluster. (11).The reported values were generated using a generalized estimating equation (GEE) approach (11) that relies on asymptotic properties, and this can be problematic with a small number of clusters because GEE requires a large sample to calculate accurate standard errors (i.e., sandwich estimator biased downward; underestimates true variability of parameter estimates) (12). Even if a correction is applied to rectify issues with the number of clusters, there is no suitable method to analyze one cluster per condition (13). Th","journal":"Frontiers in Public Health","year":2025,"id":576324,"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":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9613,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":684836,"name":"Sarah E. Deemer","orcid":"0000-0002-4758-6796","position":1,"is_corresponding":false},{"id":303967,"name":"Gian Luca Di Tanna","orcid":"0000-0002-5470-3567","position":2,"is_corresponding":false},{"id":503008,"name":"Sherri Pals","orcid":"0000-0002-0003-6236","position":3,"is_corresponding":false},{"id":71623,"name":"Kevin R. Fontaine","orcid":"0000-0002-2807-6440","position":4,"is_corresponding":false},{"id":71621,"name":"David B. Allison","orcid":"0000-0003-3566-9399","position":5,"is_corresponding":false},{"id":931810,"name":"Joshua L. Keller","orcid":"0000-0003-0756-9358","position":0,"is_corresponding":true}],"reference_count":15,"raw_metadata":null,"created_at":"2026-07-19T02:57:56.636458Z","pmid":"41089857","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":[]}