Body Mass Index Misclassify Obesity in Firefighters

Among firefighters the issue of obesity has gained significant attention due to its correlation with adverse health consequences. The National Fire Protection Association 1582 has endorsed the utilization of the body mass index (BMI) to assess obesity. However, long-standing concerns have emerged regarding BMI\u27s reliability in accurately representing body composition (BC), especially in distinguishing between lean and fat mass. Firefighters\u27 work is physically demanding, which often leads to increased muscle mass, BMI use may misclassify them as obese. This can result in false positives where firefighters are categorized as obese based on BMI even when their BC aligns with non-obese definition by body fat percentage (BF%) and/or waist circumference (WC) measurements. PURPOSE: To examine potential misclassifications of obesity using BMI with equivalent BF% and WC standards. METHODS: BMI, WC, and BF% measurements were employed on 62 male firefighters. BMI classifications followed the World Health Organization (WHO) guidelines, and WC and BF% were assessed based on American College of Sports Medicine (ACSM). Firefighters categorized as non-obese or obese with specific cutoff criteria: BMI ≥ 30 kg/m2, BF% \u3e 25%, and WC \u3e 102 cm. Using the ClinicoPath package in Jamovi 2.4.8, misclassification presence was assessed, with statistical significance set at p \u3c 0.05. The BF% or WC categories served as the golden standard, while BMI-based categories considered the new test. RESULTS: BMI yielded higher rates of obesity at 23%, compared to 10% and 6% recorded by BF% and WC, respectively. Approximately 33% and 50% of BF%- and WC-defined obese participants were misclassified as non-obese using BMI, resulting in false negatives. Conversely, 73.3% and 86.6% of non-obese firefighters defined by BF% and WC were identified as obese using BMI, leading to false positives. BMI exhibited 66.7% sensitivity and 80.4% specificity when compared to BF%, while in contrast to WC, it demonstrated sensitivity of 50% and specificity of 77.6%. CONCLUSION: This inquiry underscores the intricate limitations of BMI as an assessment tool in firefighters. It accentuates the compelling advantages offered by alternative and more precise BC measurement methods, such as BF% and WC, for the accurate identification of obesity among firefighters

Prognostic Validity of Professional Soccer Status by Anthropometrics and Repeated Jump Testing

ABSTRACT Soccer is characterized by intermittent high-intensity actions interspersed with lower intensity ones. Soccer clubs invest time and money to early identify and nurture potential professional players in the premise to maximize the return of their investment. Multidimensional talent identification models are proposed as best practice but are difficult to be implemented in the field. Explosive lower limbs strength assessment by vertical jumping (VJ) is used as a single predictor for future player status. Alternative to VJ, the repeated vertical jump test (RVJ) has been proposed, but its prognostic ability is still unexplored. PURPOSE: To analyze the prognostic validity of the RVJ obtained variables within professional (PRO) and under 19 years old (U19) male soccer players. It was hypothesized that anthropometric and performance related variables modeled on U19 will fail to predict the PRO status. METHODS: Forty-four participants (PRO=24, U19=20), after the end of the preseason, performed 15 RVJ aiming for highest jump (hJUMP) with the minimum possible ground contact time. Group differences examined by t-test, binomial logistic regression (BLR) calculated the likelihood of each individual to be categorized as PRO or U19 and receiver operating characteristic (ROC) for prognostic validity of anthropometric and performance derivative values in predicting PRO status were used at p \u3c0.05. Statistical analyses were performed using the R-based software Jamovi version 2.3.3.0. RESULTS: PRO and U19 significantly differed in body height, mass, body mass index (BMI), hJUMP, average jump height, and relative jump power. The prediction model was significant (x2(2) = 17.12, p \u3c0.001). From the examined variables, only height and BMI were positive predictors of the PRO status (b = 21.66, SE = 8.20, p = 0.008 and b = 0.94, SE = 0.38, p = 0.014, respectively). The model was 73% accurate, 75% specific, and 71% sensitive, with acceptable area under the curve (AUC = 0.82). CONCLUSION: The RVJ test demonstrated acceptable discriminating prognostic validity between PRO and U19 soccer players. Until the applicability of the multidimensional models in predicting future player status is further established, field practitioners may use the simplistic and single dimensional RVJ testing to predict future status among male soccer players

Differences in Reach Scores Between Three Upper Quarter Y-Balance Test Versions in Older Adults

The Upper Quarter Y-Balance Test (UQYBT) is often used to measure shoulder mobility and stability and screen for upper extremities musculoskeletal disorders in the physically active and athletic population. Shoulder injuries are typical among older adults, often decreasing the quality of life. There are no studies investigating the functionality of the UQYBT in older adults. PURPOSE: To examine the functionality of the UQYBT and two variations on the older population, 50 years old and older. METHODS: Eight individuals (2 males and 6 females) participated in this study (56.8±3.9 years, 166.0±10.0 cm, 69.6±13.5 kg). Each participant completed a five-minute warm-up on an arm ergometer followed by an arm length measurement. Participants completed the three UQYBT variations in a randomized order; Standard push-up position (SUQYBT), Modified push-up position (MUQYBT), and Wall push-up position (WUQYBT). In each variation, participants completed three reaches in the medial, inferolateral, and superolateral directions for the right and left hands. Highest score for each reach from the different UQYBT variations and supporting hand were saved to further analysis. Relative reach scores were calculated using the right arm length as reference. Composite scores were calculated by averaging the reach scores of the three directions. Repeated measured ANOVAs were used to compare reach score between the UQYBT variations in the older population. This was followed by post-hoc analysis; alpha level was set to 0.05. RESULTS: Significant main effects were identified in the medial reach (p-value CONCLUSION: Several differences were observed between the three UQYBT variations. When the reach was outside of the participant’s base of support (medial and superolateral reaches) WUQYBT had the highest score followed by MUQYBT and last SUQYBT. During the inferolateral reach, participants were able to get similar reach scores between the different UQYBT variations. Further studies should study the option to use the two UQYBT variations in the older population

Identifying Anger through Gait and Balance Analysis using Machine Learning Models

Anger may have detrimental effects on an individual\u27s flexibility, muscle tension, and cognitive function. Gait and balance data have emerged as promising indicators for accurately identifying anger. However, the use of machine learning (ML) models in developing algorithms to predict anger levels using such data remains limited. PURPOSE: To contribute to the development of algorithms that can be used to identify individuals who are angry based on their gait and balance data. METHODS: The Profile of Mood Survey-Short Form (POMS-SF) was administered to 133 individuals (male = 50) to assess mood state, followed by the modified Clinical Test of Sensory Interaction on Balance (mCTSIB), and a 2-minute walk around a 6m track with participants wearing APDM mobility monitors. Spatiotemporal gait and balance parameters were extracted and used in ML models to classify individuals reporting no anger (NA), mild feelings of anger (MA), or moderate to high feelings of anger (HA). A leave-one-out cross-validation technique was employed in model training, and F1 scores were utilized to assess sensitivity due to imbalanced data. RESULTS: The Gaussian Naive Bayes model achieved the highest accuracy of 87.15% (F1 = 0.87) in distinguishing individuals reporting NA from those reporting HA when utilizing both gait and balance data. The Random Forest Classifiers exhibited the best performance in differentiating between individuals reporting NA and those reporting MA, with an accuracy of 81.20% (F1 = 0.81) when analyzing data from the eyes open, feet on the ground portion of the mCTSIB. In discriminating individuals with MA from those with HA, the Gradient Boosting classifier showed the highest accuracy of 90.24% (F1 = 0.90). CONCLUSION: Being able to accurately identify anger in individuals can inform exercise professionals in tailoring interventions to improve physical performance and reduce injury risk. The present study provides evidence that the use of gait and balance analysis may serve as a viable method for identifying individuals exhibiting anger-related affective states. Despite promising results, further investigations are necessary to refine/optimize the ML algorithms employed in this study; thus, providing a more comprehensive/reliable framework for identifying emotional states via biomechanical measures

Facemask Type Impacts Dyspnea During Maximal Exercise Testing, but Mental Toughness Does Not Mediate

With the increasing use of facemasks during maximal exercise testing, concerns have been raised about their impact on perceptual responses, such as dyspnea and discomfort. Mental toughness (MT) has been proposed as a potential mediator for the relationship between facemasks and perceptual responses. PURPOSE: Examine whether sensational perceptions related to facemasks and maximal exercise testing are mediated by MT. METHODS: The study utilized a randomized crossover design. Five participants completed a maximum Bruce protocol while wearing a surgical (SM), cloth (CM), N95 (N95), or no mask (NM). Perceptual responses were collected at pre-exercise (PRE), Respiratory Exchange Ratio of 1.0 (RER1.0), and immediately post-exercise (IPE), using Feeling Scale (FS) and Dyspnea scale (CR10). We used the IPE time point for maximum FS and CR10 responses. Mental Toughness Index (MTI) was administered at PRE and IPE. ΔMTI change was calculated as PRE-MTI minus IPE-MTI. A mediation analysis using the medmode and jAMM packages on Jamovi vs. 2.3 at p \u3c .005 was performed to assess the mediating role of ΔMTI on the linkage between facemasks and FS or CR10 respectively. We used simple contrasts comparing the NM with each of the remaining facemasks. The large sample z-test of the mediated effect and non-parametric resampling procedure of bootstrapping (percent) with 1000 samples for the calculation of the standard errors of the mediated effect was employed. RESULTS: The indirect effect of ΔMTI on FS was not significant for any of the contrasts. The direct effect of facemasks on FS was not significant. Therefore, there is no mediating effect of ΔMTI on FS. The indirect effect of ΔMTI on CR10 was not significant for any of the contrasts. The direct effect of NM to CM facemask contrasts on CR10 (1.77) was significant (β = .42, z = 2.03, p = .042), indicating only a direct effect and no mediation is present. CONCLUSION: MT does not mediate the relationship between facemasks and dyspnea/discomfort during maximal exercise testing. However, there was a significant direct effect of the type of facemask on the dyspnea score, with the NM to CM contrast being the most impactful. These findings suggest that the type of facemask worn during exercise can have a direct impact on perceived dyspnea, with CMs potentially causing more discomfort than SMs or N95s