Background: Structured aerobic or resistance training alone seems to be a beneficial tool for improving glucose homeostasis, chronic systemic inflammation, resting cardiovascular function, and mental health in people with obesity and type 2 diabetes mellitus (T2DM). The aim of the present study was to synthesize the available data on the effectiveness of combined aerobic and resistance training (CART) on glycemic control, blood pressure, inflammation, cardiorespiratory fitness (CRF), and quality of life (QoL) in overweight and obese individuals with T2DM.Methods: A database search was carried out in PubMed, Web of Science, Scopus, Science Direct, Cochrane Library, and Google Scholar from inception up to May 2023. The Cochrane risk of bias tool was used to assess eligible studies, and the GRADE method to evaluate the reliability of evidence. A random-effects model was used, and data were analyzed using standardized mean differences and 95% confidence intervals. The study protocol was registered in the International Prospective Register of Systematic Reviews (ID: CRD42022355612).Results: A total of 21,612 studies were retrieved; 20 studies were included, and data were extracted from 1,192 participants (mean age: 57 ± 7 years) who met the eligibility criteria. CART demonstrated significant improvements in body mass index, glycated hemoglobin, systolic and diastolic blood pressure, C-reactive protein, tumor necrosis factor-alpha, interleukin-6, CRF, and QoL compared to ST. These findings highlight the significance of exercise interventions such as CART as essential elements within comprehensive diabetes management strategies, ultimately enhancing overall health outcomes in individuals with T2DM and overweight/obesity.No differences were found in resting heart rate between CART and ST. An uncertain risk of bias and poor quality of evidence were found among the eligible studies.Conclusion: These outcomes show clear evidence considering the positive role of CART in inducing beneficial changes in various cardiometabolic and mental health-related indicators in patients with T2DM and concurrent overweight/obesity. More studies with robust methodological design are warranted to examine the dose-response relationship, training parameters configuration, and mechanisms behind these positive adaptations.

The availability of critical information about training and competition is fundamental on performance. Principal components analysis (PCA) is widely used in sports as a multivariate technique to manage big data from different technological assessments. This systematic review aimed to explore the methods reported and statistical criteria used in team’s sports science and to propose a criteria standard to report PCA in further applications. A systematic electronic search was developed through four electronic databases and a total of 45 studies were included in the review for final analysis. Inclusion criteria: (i) of the studies we looked at, 22.22% performed factorability processes with different retention criteria (r > 0.4–0.7); (ii) 21 studies confirmed sample adequacy using Kaiser-Meyer-Olkim (KMO > 5–8) and 22 reported Bartlett’s sphericity; (iii) factor retention was considered if eigenvalues >1–1.5 (n = 29); (iv) 23 studies reported loading retention (>0.4–0.7); and (v) used VariMax as the rotation method (48.9%). A lack of consistency and serious voids in reporting of essential methodological information was found. Twenty-one items were selected to provide a standard quality criterion to report methods sections when using PCA. These evidence-based criteria will lead to a better understanding and applicability of the results and future study replications.

Since the accelerating development of technology applied to team sports and its subsequent high amount of information available, the need for data mining leads to the use of data reduction techniques such as Principal Component Analysis (PCA). This systematic review aims to identify determinant variables in soccer, basketball and rugby using exploratory factor analysis for, training design, performance analysis and talent identification. Three electronic databases (PubMed, Web of Science, SPORTDiscus) were systematically searched and 34 studies were finally included in the qualitative synthesis. Through PCA, data sets were reduced by 75.07%, and 3.9 ± 2.53 factors were retained that explained 80 ± 0.14% of the total variance. All team sports should be analyzed or trained based on the high level of aerobic capacity combined with adequate levels of power and strength to perform repeated high-intensity actions in a very short time, which differ between team sports. Accelerations and decelerations are mainly significant in soccer, jumps and landings are crucial in basketball, and impacts are primarily identified in rugby. Besides, from these team sports, primary information about different technical/tactical variables was extracted such as (a) soccer: occupied space, ball controls, passes, and shots; (b) basketball: throws, rebounds, and turnovers; or (c) rugby: possession game pace and team formation. Regarding talent identification, both anthropometrics and some physical capacity measures are relevant in soccer and basketball. Although overall, since these variables have been identified in different investigations, further studies should perform PCA on data sets that involve variables from different dimensions (technical, tactical, conditional).

The aims of this study were to: (1) identify the representative external load profile of match‐play in Spanish professional soccer players by principal components analysis (PCA), and (2) analyse the effect of match location (home vs away), match outcome (win vs draw vs loss) and length of the microcycle (5 vs 6 vs 7 vs 8 vs 9 days) on the external load profile. Data were collected during one season consisting of 42 matches in LaLiga 123 and 11 external load variables were selected after the PCA. TD, total distance covered; DIS_0–6: distance from 0 to 6 km/h; DIS_21–24: distance from 21 to 24 km/h; HSRD: high‐speed running distance above 21 km/h; HSRA: total of high‐speed running actions above 21 km/h; V _MAX: maximum speed in km/h; Sprints: total of actions above 24 km/h; ACC: total of accelerations; ACC_G‐avg: average accelerometer G‐force; ACC_MAX: maximum acceleration (m/s2); DEC_MAX: maximum deceleration (m/s²). Match location had an impact on HSRD (p < 0.01; ES = 0.05), DIS_0–6 (p < 0.01; ES = 0.05), and ACC_MAX (p < 0.01; ES = 0.05). Match outcome had a relation to TD (p < 0.01; ES = 0.05), DIS_0–6 (p < 0.01; ES = 0.05) and HSRD (p < 0.01; ES = 0.05). Length of the microcycle had an impact on TD (p < 0.01; ES = 0.05), DIS_0–6 (p < 0.01; ES = 0.11), ACC (p < 0.01; ES = 0.04) and V_MAX (p < 0.01; ES = 0.04). This study provides coaches a selection of variables for match‐play analysis, which could represent two‐thirds of external load profile. Then, professionals should consider that these contextual variables could have an impact on the external load profile.

Despite constituting approximately 50% of the population, women specifically are under-represented in sport and exercise medicine (SEM) and they often experience a negative bias. Our authorship group has recognised this issue based on evidence from recent studies, personal experiences and the experiences of the wider SEM community. We understand that this is a complex issue. Through this editorial, we aim to briefly highlight the issue of insufficient representation of women in SEM, discuss some of the impacts of this inadequate inclusion and other negative aspects experienced and suggest steps that we can all take to address female under-representation to improve the field of SEM