Estimating the cost of sports injuries: A scoping review.

OBJECTIVES: Provide an overview of the methods used to estimate the cost of sports-related injury published to date, and to highlight considerations and opportunities for future research. DESIGN: Scoping review. METHODS: Scopus, MEDLINE and CINHAL were searched from 1st January 2000 to 1st January 2023. Studies were screened by two independent reviewers and were eligible if they reported on a cost analysis or cost estimation of sports related injury. RESULTS: Thirty-one studies fulfilled the inclusion criteria. Twenty-seven studies (87 %) were published since 2014. The type of costs included direct healthcare costs (12 studies), indirect costs (10 studies) and a combination of both (9 studies). Twenty-one studies (68 %) used a bottom-up costing approach to measure costs of sports injury and estimated direct costs from the service rates or fee schedules of health systems, hospital, insurance companies or national insurance boards. A top-down approach was used in seven studies (23 %) to estimate the indirect salary cost of time-loss injuries using data from publicly available resources. Ten studies were from the cost perspective of a sporting organisation (32 %). There was a lack of explicit reporting of the costing method used and the perspective of those bearing the costs. CONCLUSIONS: Estimating the cost of sports injuries is an emerging area of research, with publications increasing in recent years. However, there remains a lack of methodological guidance to inform or appraise these studies. The expansion of established cost of illness checklists with sport injury explanations to guide future cost of sports injury studies is recommended.

A decline in planned, but not spontaneous, preterm birth rates in a large Australian tertiary maternity centre during COVID-19 mitigation measures.

BACKGROUND: Reports from around the world suggest that rates of preterm birth decreased during COVID-19 lockdown measures. AIMS: To compare the prevalence of preterm birth and stillbirth rates during COVID-19 restriction measures with infants born at the same maternity centre during the same weeks in 2013-2019. MATERIALS AND METHODS: Deidentified data were extracted from the Mater Mothers' healthcare records database. This is a supra-regional tertiary perinatal centre. Logistic regressions were used to examine singleton live preterm birth rates during the beginning of COVID-19 restrictions (16 March-17 April; 'early'; 6955 births) and during the strictest part of COVID-19 restrictions (30 March-1 May; 'late'; 6953 births), according to gestational age subgroups and birth onset (planned or spontaneous). We adjusted for multiple covariates, including maternal age, body mass index, ethnicity, parity, socioeconomic status, maternal asthma, diabetes mellitus and/or hypertensive disorder. Singleton stillbirth rates were also examined between 16 March-1 May. RESULTS: Planned moderate/late preterm births declined by more than half during early COVID-19 restrictions compared with the previous seven years (29 vs an average of 64 per 1000 births; adjusted odds ratio 0.39, 95% CI 0.22-0.71). There was no effect on extremely or very preterm infants, spontaneous preterm births, or stillbirth rates. Rolling averages from January to June revealed a two-week non-significant spike in spontaneous preterm births from late April to early May, 2020. CONCLUSIONS: Together with evidence from other nations, the pandemic provides a unique opportunity to identify causal and preventative factors for preterm birth.

Adherence to Dietary and Physical Activity Guidelines in Australian Undergraduate Biomedical Students and Associations with Body Composition and Metabolic Health: A Cross-Sectional Study.

There is a paucity of data on whether Australian university students are meeting specific nutrient guidelines, and the relationship between diet and physical activity patterns with body composition and metabolic health. In this study, biomedical students from The University of Queensland were recruited (150 males and 211 females, 19-25 years), and nutritional intake (ASA24-Australia) and physical activity levels (Active Australia Survey) quantified. Body composition (height, waist circumference, body mass, BMI, and percentage body fat; BOD POD) and metabolic health (oral glucose tolerance test) were also measured. Median daily energy intake was 6760 kJ in females and 10,338 kJ in males, with more than 30% of total energy coming from energy-dense, nutrient-poor foods. Only 1 in 10 students met fruit or vegetable recommendations, with less than one third meeting recommendations for fibre, calcium, and potassium. Intakes of calcium and iron were particularly low among female students, with only 16% and 6% of students meeting the recommended dietary intake (RDI), respectively. The majority of males and almost half of all females exceeded the suggested dietary target (SDT) for sodium. Sufficient physical activity (≥150 min over ≥5 sessions per week) was met by more than 80% of students. Body composition and blood glucose concentrations were largely normal but an early sign of insulin resistance (HOMA-IR > 2.0), measured in a subset of students, was present in 21% of males and 17% of females. Modest reductions in blood glucose levels and percentage body fat were associated with increasing vigorous activity. Low intakes of fibre, calcium, and potassium could be corrected by increasing fruit, vegetable, and dairy intake, and, among females, health promotion messages focusing on iron-rich foods should be prioritised. While these nutrient deficiencies did not translate into immediate metabolic heath concerns, dietary behaviours can track into adulthood and have lasting effects on overall health.

The Impact of Isolation Measures Due to COVID-19 on Energy Intake and Physical Activity Levels in Australian University Students.

The coronavirus disease 2019 (COVID-19) pandemic resulted in physical isolation measures in many parts of the world. In Australia, nationwide restrictions included staying at home, unless seeking medical care, providing care, purchasing food, undertaking exercise, or attending work in an essential service. All undergraduate university classes transitioned to online, mostly home-based learning. We, therefore, examined the effect of isolation measures during the early phase of the COVID-19 pandemic in Australia (March/April) on diet (24-h recall) and physical activity (Active Australia Survey) patterns in third-year biomedical students. Findings were compared with students enrolled in the same course in the previous two years. In females, but not males, energy intake was ~20% greater during the pandemic, and snacking frequency and energy density of consumed snacks also increased compared with 2018 and 2019. Physical activity was impacted for both sexes during the pandemic with ~30% fewer students achieving "sufficient" levels of activity, defined by at least 150 min over at least five sessions, compared with the previous two years. In a follow-up study six to eight weeks later (14-18% response rate), during gradual easing of nationwide restrictions albeit continued gym closures and online learning, higher energy intake in females and reduced physical activity levels in both sexes persisted. These data demonstrate the health impacts of isolation measures, with the potential to affect long-term diet and activity behaviours.

Reliability of a portable fixed frame dynamometry system used to test lower limb strength in elite Australian Football League players.

OBJECTIVES: Deficits in strength of lower limb musculature have been associated with increased injury risk in a variety of athletic populations. As medical and performance staff seek to better understand the association between hip and knee strength measures and injury risk, measurement tools with high reliability and utility are required to profile and manage athletes effectively. The purpose of this study was to investigate the test-retest reliability of a portable fixed frame dynamometry system used to assess hip and knee strength of an elite Australian Football League team. DESIGN: Case series. METHODS: Maximum voluntary isometric strength of the hip abductors, hip adductors and knee flexors of 41 elite male Australian Football League footballers (mean age=23.7±4.1 years, height=189.2±7.0cm, weight=88.6±8.4kg) were tested during preseason training. Tests were performed one week apart on the same training day of a standard preseason week. RESULTS: Test-retest reliability was very high for left hip adduction (ICC 0.958), right hip adduction (ICC 0.955), left hip abduction (ICC 0.957), right hip abduction (ICC 0.945), left knee flexion (ICC 0.927) and right knee flexion (ICC 0.923). Furthermore, standard errors of measurement in per cent (SEM%) ranged from 3.21 to 5.03%, and minimal detectable change (MDC) from 3.93 to 6.65kg for the different hip and thigh strength measures, making it possible to determine small changes in strength at the individual level. CONCLUSIONS: This study demonstrated very high reliability when testing maximal voluntary isometric hip and knee strength using a portable fixed dynamometry system (KangaTech) in an elite male Australian Football League setting.

Self-Reported Wellness Profiles of Professional Australian Football Players During the Competition Phase of the Season.

Gallo, TF, Cormack, SJ, Gabbett, TJ, and Lorenzen, CH. Self-reported wellness profiles of professional Australian football players during the competition phase of the season. J Strength Cond Res 31(2): 495-502, 2017-With the prevalence of customized self-report measures in high-performance sport, and the incomplete understanding of athletes' perceived wellness in response to matches and training load, the objective of this study was to explore weekly wellness profiles within the context of the competitive season of professional Australian football. Internal match load, measured through the session-rating of perceived exertion method, match-to-match microcycle, stage of the season, and training load were included in multivariate linear models to determine their effect on weekly wellness profile (n = 1,835). There was a lower weekly training load on a 6-day microcycle compared with a 7-day and 8-day microcycle. Match load had no significant impact on weekly wellness profile, while there was an interaction between microcycle and days postmatch. There was a likely moderately lower wellness Z-score 1 day postmatch for an 8-day microcycle (mean; 95% confidence interval: -1.79; -2.02 to -1.56) compared with a 6-day (-1.19; -1.30 to -1.08) and 7-day (-1.22; -1.34 to -1.09) cycle (d; 95% confidence interval: -0.82; -1.3 to -0.36, -0.78; -1.3 to -0.28, respectively). The second half of the season saw a possibly small reduction in overall wellness Z-score than the first half of the season (0.22; 0.12-0.32). Finally, training load had no effect on wellness Z-score when controlled for days postmatch, microcycle, and stage of the season. These results provide information on the status of players in response to matches and fixed conditions. Knowing when wellness Z-score returns to baseline relative to the length of the microcycle may lead practitioners to prescribe the heaviest load of the week accordingly. Furthermore, wellness "red flags" should be made relative to the microcycles and stage of the season to determine an athlete's status relative to their typical weekly profile.

Pre-training perceived wellness impacts training output in Australian football players.

The impact of perceived wellness on a range of external load parameters, rating of perceived exertion (RPE) and external load:RPE ratios, was explored during skill-based training in Australian footballers. Fifteen training sessions involving 36 participants were analysed. Each morning before any physical training, players completed a customised perceived wellness questionnaire (sleep quality, fatigue, stress, mood and muscle soreness). Microtechnology devices provided external load (average speed, high-speed running distance, player load and player load slow). Players provided RPE using the modified Borg category-ratio 10 RPE scale. Mixed-effect linear models revealed significant effects of wellness Z-score on player load and player load slow. Effects are reported with 95% confidence limits. A wellness Z-score of -1 corresponded to a -4.9 ± 3.1 and -8.6 ± 3.9% reduction in player load and player load slow, respectively, compared to those without reduced wellness. Small significant effects were also seen in the average speed:RPE and player load slow:RPE models. A wellness Z-score of -1 corresponded to a 0.43 ± 0.38 m·min(-1) and -0.02 ± 0.01 au·min(-1) change in the average speed:RPE and player load slow:RPE ratios, respectively. Magnitude-based analysis revealed that the practical size of the effect of a pre-training perceived wellness Z-score of -1 would have on player load slow was likely negative. The results of this study suggests that monitoring pre-training perceived wellness may provide coaches with information about the intensity of output that can be expected from individual players during a training session.

Characteristics impacting on session rating of perceived exertion training load in Australian footballers.

The relationship between external training load and session rating of perceived exertion (s-RPE) training load and the impact that playing experience, playing position and 2-km time-trial performance had on s-RPE training load were explored. From 39 Australian Football players, 6.9 ± 4.6 training sessions were analysed, resulting in 270 samples. Microtechnology devices provided external training load (distance, average speed, high-speed running distance, player load (PL) and player loadslow (PLslow)). The external training load measures had moderate to very large associations (r, 95% CI) with s-RPE training load, average speed (0.45, 0.35-0.54), high-speed running distance (0.51, 0.42-0.59), PLslow (0.80, 0.75-0.84), PL (0.86, 0.83-0.89) and distance (0.88, 0.85-0.90). Differences were described using effect sizes (d ±95% CL). When controlling for external training load, the 4- to 5-year players had higher s-RPE training load than the 0- to 1- (0.44 ± 0.33) and 2- to 3-year players (0.51 ± 0.30), ruckmen had moderately higher s-RPE training load than midfielders (0.82 ± 0.58), and there was a 0.2% increase in s-RPE training load per 1 s increase in time-trial (95% CI: 0.07-0.34). Experience, position and time-trial performance impacted the relationship between external training load and s-RPE training load. This suggests that a given external training load may result in different internal responses between athletes, potentially leaving individuals at risk of overtraining or failing to elicit positive adaptation. It is therefore vital that coaches and trainers give consideration to these mediators of s-RPE training load.