Insights Into Relationships Between Body Mass, Composition and Bone: Findings in Elite Rugby Players

Hind, Karen; Gannon, Lisa; Brightmore, A W; Beck, Belinda R.

doi:10.1016/j.jocd.2014.11.002

Cited by 16 publications

(19 citation statements)

References 24 publications

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“…In another study, nearly 50% of men and women classified as obese using densitometric methods were determined to be of normal BMI (33). Athletes who build high levels of muscle (lean body) mass often possess BMI levels above 30 and would be inappropriately classified as obese (34). However, when they retire, many will increase their body fat levels substantially, while maintaining their high BMI.…”

Section: Problems With Bmi As a Measure Of Obesitymentioning

confidence: 99%

Overfat and Underfat: New Terms and Definitions Long Overdue

Maffetone¹,

Rivera-Dominguez²,

Laursen

2017

Front. Public Health

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For the first time in human history, the number of obese people worldwide now exceeds those who are underweight. However, it is possible that there is an even more serious problem—an overfat pandemic comprised of people who exhibit metabolic health impairments associated with excess fat mass relative to lean body mass. Many overfat individuals, however, are not necessarily classified clinically as overweight or obese, despite the common use of body mass index as the clinical classifier of obesity and overweight. The well-documented obesity epidemic may merely be the tip of the overfat iceberg. The counterpart to the overfat condition is the underfat state, also a common and dangerous health circumstance associated with chronic illness and starvation. Currently (and paradoxically), high rates of obesity and overweight development coexist with undernutrition in developing countries. Studies in cognitive linguistics suggest that accurate, useful, and unintimidating terminology regarding abnormal body fat conditions could help increase a person’s awareness of their situation, helping the process of implementing prevention and simple remedies. Our contention is that promoting the terms “overfat” and “underfat” to describe body composition states to the point where they enter into common usage may help in creating substantive improvements in world health.

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Section: Problems With Bmi As a Measure Of Obesitymentioning

confidence: 99%

Overfat and Underfat: New Terms and Definitions Long Overdue

Maffetone¹,

Rivera-Dominguez²,

Laursen

2017

Front. Public Health

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“…Of all fields, sports science and medicine has witnessed a considerable rise in the number of published research studies utilising DXA for the assessment of total and regional body composition. These studies have included the body composition profiling of competitive athletes [3,4], and in relation to bone density [5][6][7] and nutritional status [8,9]. Serial DXA measurements are increasingly being used to explore the effects of training and diet on athlete body composition changes [10][11][12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Interpretation of Dual-Energy X-Ray Absorptiometry-Derived Body Composition Change in Athletes: A Review and Recommendations for Best Practice

Hind

Slater

Oldroyd

et al. 2018

Journal of Clinical Densitometry

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Dual-energy X-ray absorptiometry (DXA) is a medical imaging device which has become the method of choice for the measurement of body composition in athletes. The objectives of this review were to evaluate published longitudinal DXA body composition studies in athletic populations for interpretation of "meaningful" change, and to propose a best practice measurement protocol. An online search of PubMed and CINAHL via EBSCO Host and Web of Science enabled the identification of studies published until November 2016. Those that met the inclusion criteria were reviewed independently by 2 authors according to their methodological quality and interpretation of body composition change. Twenty-five studies published between 1996 and November 2016 were reviewed (male athletes: 13, female athletes: 3, mixed: 9) and sample sizes ranged from n = 1 to 212. The same number of eligible studies was published between 2013 and 2016, as over the 16 yr prior (between 1996 and 2012). Seven did not include precision error, and fewer than half provided athlete-specific precision error. There were shortfalls in the sample sizes on which precision estimates were based and inconsistencies in the level of pre-scan standardization, with some reporting full standardization protocols and others reporting only single (e.g., overnight fast) or no control measures. There is a need for standardized practice and reporting in athletic populations for the longitudinal measurement of body composition using DXA. Based on this review and those of others, plus the official position of the International Society for Clinical Densitometry, our recommendations and protocol are proposed as a guide to support best practice.

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“…The high proportion of patients classified as overweight-obese (68.8%) by the BMI method in the present study is a reflection of the sports commonly played by our patient population, in particularly rugby and Australian rules football where larger body frames are advantageous with high contact play. 21 Post-hoc analysis of the IKDC scores revealed that Cluster 4, the subgroup with the highest overall health and knee function scores, reported the ability to perform a higher level of activity without experiencing instability, at a higher than expected rate compared with Cluster 1. These findings highlight the need to clearly establish the reasons why patients decide to undergo ACL reconstruction.…”

Section: Discussionmentioning

confidence: 88%

Baseline Analysis of Patients Presenting for Surgical Review of Anterior Cruciate Ligament Rupture Reveals Heterogeneity in Patient-Reported Outcome Measures

Ting

Scholes²,

Zbrojkiewicz

et al. 2020

J Knee Surg

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AbstractDespite the establishment of successful surgical techniques and rehabilitation protocols for anterior cruciate ligament (ACL) reconstruction, published return to sport rates are less than satisfactory. This has led orthopaedic surgeons and researchers to develop more robust patient selection methods, and investigate prognostic patient characteristics. No previous studies have integrated baseline characteristics and responses to patient-reported outcome measures (PROMs) of patients with ACL rupture presenting for surgical review. Patients electing to undergo ACL reconstruction under the care of a single orthopaedic surgeon at a metropolitan public hospital were enrolled in a clinical quality registry. Patients completed Veterans RAND 12-item Health Survey (VR-12) Physical Component Summary and Mental Component Summary scores, Tegner activity scale, and International Knee Documentation Committee (IKDC) questionnaires at presentation. Total scores were extracted from the electronic registry, and a machine learning approach (k-means) was used to identify subgroups based on similarity of questionnaire responses. The average scores in each cluster were compared using analysis of variance (ANOVA; Kruskal–Wallis) and nominal logistic regression was performed to determine relationships between cluster membership and patient age, gender, body mass index (BMI), and injury-to-examination delay. A sample of 107 patients with primary ACL rupture were extracted, with 97 (91%) available for analysis with complete datasets. Four clusters were identified with distinct patterns of PROMs responses. These ranged from lowest (Cluster 1) to highest scores for VR-12 and IKDC (Cluster 4). In particular, Cluster 4 returned median scores within 6 points of the patient acceptable symptom state for the IKDC score for ACL reconstruction (70.1, interquartile range: 59–78). Significant (p < 0.05) differences in PROMs between clusters were observed using ANOVA, with variance explained ranging from 40 to 69%. However, cluster membership was not significantly associated with patient age, gender, BMI, or injury-to-examination delay. Patients electing to undergo ACL reconstruction do not conform to a homogenous group but represent a spectrum of knee function, general physical and mental health, and preinjury activity levels, which may not lend itself to uniform treatment and rehabilitation protocols. The factors driving these distinct responses to PROMs remain unknown but are unrelated to common demographic variables.

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Insights Into Relationships Between Body Mass, Composition and Bone: Findings in Elite Rugby Players

Cited by 16 publications

References 24 publications

Overfat and Underfat: New Terms and Definitions Long Overdue

Overfat and Underfat: New Terms and Definitions Long Overdue

Interpretation of Dual-Energy X-Ray Absorptiometry-Derived Body Composition Change in Athletes: A Review and Recommendations for Best Practice

Baseline Analysis of Patients Presenting for Surgical Review of Anterior Cruciate Ligament Rupture Reveals Heterogeneity in Patient-Reported Outcome Measures

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