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Biomedical subjects

N P Craig

Publications and source records attributed to N P Craig.

14 recordsLinked to original sources
PubMed2001

Characteristics of track cycling.

Track cycling events range from a 200 m flying sprint (lasting 10 to 11 seconds) to the 50 km points race (lasting approximately 1 hour). Unlike road cycling competitions where most racing is undertaken at submaximal power outputs, the shorter track events require the cyclist to tax maximally both the aerobic and anaerobic (oxygen independent) metabolic pathways. Elite track cyclists possess key physical and physiological attributes which are matched to the specific requirements of their events: these cyclists must have the appropriate genetic predisposition which is then maximised through effective training interventions. With advances in technology it is now possible to accurately measure both power supply and demand variables under competitive conditions. This information provides better resolution of factors that are important for training programme design and skill development.

Anaerobic Threshold↗
PubMed2000

The bioenergetics of World Class Cycling.

Professional cycle racing is one of the most demanding of all sports combining extremes of exercise duration, intensity and frequency. Riders are required to perform on a variety of surfaces (track, road, cross-country, mountain), terrains (level, uphill and downhill) and race situations (criterions, sprints, time trials, mass-start road races) in events ranging in duration from 10 s to 3 wk stage races covering 200 m to 4,000 km. Furthermore, professional road cyclists typically have approximately 100 race d/yr. Because of the diversity of cycle races, there are vastly different physiological demands associated with the various events. Until recently there was little information on the demands of professional cycling during training or competition. However, with the advent of reliable, valid bicycle crank dynanometers, it is now possible to quantify real-time power output, cadence and speed during a variety of track and road cycling races. This article provides novel data on the physiological demands of professional and world-class amateur cyclists and characterises some of the physiological attributes necessary for success in cycling at the élite level.

Australia↗
PubMed1999

Effect of pedal cadence on the accumulated oxygen deficit, maximal aerobic power and blood lactate transition thresholds of high-performance junior endurance cyclists.

In this study we investigated the effect of pedal cadence on the cycling economy, accumulated oxygen deficit (AOD), maximal oxygen consumption (VO2max) and blood lactate transition thresholds of ten high-performance junior endurance cyclists [mean (SD): 17.4 (0.4) years; 183.8 (3.5) cm, 71.56 (3.75) kg]. Cycling economy was measured on three ergometers with the specific cadence requirements of: 90-100 rpm for the road dual chain ring (RDCR90-100 rpm) ergometer, 120-130 rpm for the track dual chain ring (TDCR120-130 rpm) ergometer, and 90-130 rpm for the track single chain ring (TSCR90-130 rpm) ergometer. AODs were then estimated using the regression of oxygen consumption (VO2) on power output for each of these ergometers, in conjunction with the data from a 2-min supramaximal paced effort on the TSCR90-130 rpm ergometer. A regression of VO2 on power output for each ergometer resulted in significant differences (P<0.001) between the slopes and intercepts that produced a lower AOD for the RDCR90-100 rpm [2.79 (0.43) l] compared with those for the TDCR120-130 rpm [4.11 (0.78) l] and TSCR90-130 rpm [4.06 (0.84) l]. While there were no statistically significant VO2max differences (P = 0.153) between the three treatments [RDCR90-100 rpm: 5.31 (0.24) l x min(-1); TDCR120-130 rpm; 5.33 (0.25) 1 x min(-1); TSCR90-130 rpm: 5.44 (0.27) l x min(-1)], all pairwise comparisons of the power output at which VO2max occurred were significantly different (P<0.001). Statistically significant differences were identified between the RDCR90-100 rpm and TDCR120-130 rpm tests for power output (P = 0.003) and blood lactate (P = 0.003) at the lactate threshold (Thla-), and for power output (P = 0.005) at the individual anaerobic threshold (Thiat). Our findings emphasise that pedal cadence specificity is essential when assessing the cycling economy, AOD and blood lactate transition thresholds of high-performance junior endurance cyclists.

Adolescent↗
PubMed1999

The evolution of Australian football.

Australian football has undergone considerable change over the past century. This evolution seems to have accelerated more recently since the introduction and major influence of the media, increased professionalism and the start of a national competition. In this study we have attempted to quantify the evolution in game 'style' by measuring events during elite football games (from video analysis) and gathering physical information on players involved at the highest level. These data are important to gain insight into the game demands so that player preparation may be enhanced and when predicting the nature of the game in the future. Understanding the patterns of play within the game may also be useful when assessing the possible impact of rule changes, for example, increasing the number of interchange players on the potential for injury. Four games were selected, one from each of the past 4 decades to determine the rate at which specific, measurable events occurred in the games. Height and mass data on players were also obtained from official records of registered players in the VFL/AFL competitions. The results indicate the 'speed' of the game has approximately doubled in the period 1961-1997. The proportion of the total game which involves 'play' time has been reduced significantly while breaks in play are more frequent and longer. Despite this pattern, however, the average game tempo has increased along with player height and mass and we present a case which suggests these are likely determinants of the increased incidence of player injuries and lost match time.

Athletic Injuries↗
PubMed1995

Exercise stimulus increases ventilation from maximal to supramaximal intensity.

This study investigated the influence of an exercise stimulus on pulmonary ventilation (VE) during severe levels of exercise in a group of ten athletes. The altered ventilation was assessed in relation to its effect on blood gas status, in particular to the incidence and severity of exercise induced hypoxaemia. Direct measurements of arterial blood were made at rest and during the last 15 s of two intense periods of cycling; once at an intensity found to elicit maximal oxygen uptake (VO2max; MAX) and once at an intensity established to require 115% of VO2max (SMAX). Oxygen uptake (VO2) and ventilatory markers were continually recorded during the exercise and respiratory flow-volume loops were measured at rest and during the final 30 s of each minute for both exercise intensities. When compared to MAX exercise, the subjects had higher ventilation and partial pressure of arterial oxygen (PaO2) during the SMAX intensity. Regression analysis for both conditions indicated the levels of PaO2 and oxygen saturation of arterial blood (SaO2) were positively correlated with relative levels of ventilation during exercise. It was apparent that mechanical constraints to ventilate further were not present during the MAX test since the subjects were able to elevate VE during SMAX and attenuate the level of hypoxaemia. This was also confirmed by analysis of the flow volume recordings. These data support the conclusions firstly, that overwhelming mechanical constraints on VE were not present during the MAX exercise, secondly, the subjects exhibiting the most severe hypoxaemia had no consistent relationship with any measure of expiratory flow limitation, and thirdly, ventilatory patterns during intense exercise are strong predictors of blood gas status.

Adolescent↗
PubMed1995

Influence of test duration and event specificity on maximal accumulated oxygen deficit of high performance track cyclists.

This study examined the relationship between the time required to fully utilise the maximal accumulated oxygen deficit (MAOD) and event specificity of track cyclists. Twelve track endurance and 6 sprint high performance track cyclists performed four treatments of 70 s, 120 s, 300 s and 115% VO2max of maximal cycling on an air-braked ergometer. Peak blood lactate was measured immediately after each test with VO2 kinetics being assessed during the 115% VO2max time to exhaustion test. When the two cycling groups were combined there was no significant difference in the MAOD when assessed under the four different exercise durations. However, when the groups were analysed separately the following results were apparent: (1) the sprint cyclists achieved a significantly greater MAOD (66.9 +/- 2.2 ml.kg-1) compared to the track endurance cyclists (57.6 +/- 6.7 ml.kg-1) when a 70 s test duration was employed (2) even though the track endurance cyclists achieved their greatest MAOD during the 300 s test protocol (62.1 +/- 11.0 ml.kg-1), it was not significantly different to the MAOD's measured during the three other test durations and (3) the sprint cyclists recorded their greatest MAOD during the 70 s supramaximal test protocol (66.9 +/- 2.2 ml.kg-1). This was not significantly different to the 120 s test MAOD, but it was significantly higher than the MAOD values recorded during the 115% VO2max and 300 s test durations. There was no significant difference between the two groups in the peak post-exercise blood lactate concentrations for any of the tests and only the 70 s test produced a significant correlation between peak blood lactate and the MAOD. The VO2 kinetics (VO2 t1/2) of the sprinters was significantly slower than that of the track endurance cyclists (26.3 +/- 2.3 vs 23.9 +/- 2.8 s.). The findings of this study demonstrate that sprint cyclists can fully express their anaerobic capacity within an event specific 70 s all-out test and that these cyclists progressively decrease their anaerobic capacity during a 120 s, 115% VO2max (mean time = 210 s) or 300 s test, despite giving all-out efforts. Conversely, track endurance cyclists achieve their highest mean score during an event specific 300 s test and their lowest during a 70 s test. These findings have important implications when testing high performance cyclists for determination of MAOD, with the implication that it is necessary to assess MAOD under exercise conditions (i.e., duration, pacing) specific to the cyclist's chosen event.

Adolescent↗
PubMed1993

Aerobic and anaerobic indices contributing to track endurance cycling performance.

A group of 18 male high performance track endurance and sprint cyclists were assessed to provide a descriptive training season specific physiological profile, to examine the relationship between selected physiological and anthropometric variables and cycling performance in a 4000-m individual pursuit (IP4000) and to propose a functional model for predicting success in the IP4000. Anthropometric characteristics, absolute and relative measurements of maximal oxygen uptake (VO2max), blood lactate transition thresholds (Thla- and Th(an),i), VO2 kinetics, cycling economy and maximal accumulated oxygen deficit (MAOD) were assessed, with cyclists also performing a IP4000 under competition conditions. Peak post-competition blood lactate concentrations and acid-base values were measured. Although all corresponding indices of Thla- and Th(an),i occurred at significantly different intensities there were high intercorrelations between them (0.51-0.85). There was no significant difference in MAOD when assessed using a 2 or 5 min protocol (61.4 vs 60.2 ml.kg-1, respectively). The highest significant correlations were found among IP4000 and the following: VO2max (ml.kg-2/3.min-1; r = -0.79), power output at lactate threshold (Wthla) (W; r = -0.86), half time of VO2 response whilst cycling at 115% VO2max (s; r = 0.48) and MAOD when assessed using the 5 min protocol (ml.kg-1; r = -0.50). A stepwise multiple regression yielded the following equation, which had an r of 0.86 and a standard error of estimate of 5.7 s: IP4000 (s) = 462.9 - 0.366 x (Wthla) - 0.306 x (MAOD) - 0.438 x (VO2max) where Wthla is in W, MAOD is in ml.kg-1 and VO2max is in ml.kg-1 x min-1.(ABSTRACT TRUNCATED AT 250 WORDS)

Acid-Base Equilibrium↗
PubMed1993

Mathematical model of cycling performance.

A model of cycling performance is presented. The model is based on equating two expressions for the total amount of work performed. One expression is deduced from biomechanical principles deriving energy requirements from total resistance. The other models the energy available from aerobic and anaerobic energy systems, including the effect of oxygen uptake kinetics at the onset of exercise. The equation can then be solved for any of the variables. Empirically derived field and laboratory data were used to assess the accuracy of the model. Model estimates of 4,000-m individual pursuit performance times showed a correlation of 0.803 (P < or = 0.0001) with times measured in 18 high-performance track cyclists, with a mean difference (predicted--measured) of 4.6 s (1.3% of mean performance time). The model enables estimates of the performance impact of alterations in physiological, biomechanical, anthropometric, and environmental parameters.

Aerobiosis↗
PubMed1992

Accuracy of pulse oximetry during exercise stress testing.

Pulse oximetry is used extensively during exercise stress-testing in the clinical and sports medicine settings. There are few validation studies to assess the appropriateness of using pulse oximetry under conditions of potentially compromised peripheral blood flow. To study the accuracy of pulse oximetry during severe exercise stress, 10 athletes undertook 3 bouts of exhaustive exercise; once at an intensity requiring VO2max (max), once at 115% of VO2max (Smax), and once at Smax while FIO2 was increased to 0.30. The results indicate relatively large underestimations occur when pulse oximetry is used to estimate %SaO2 during exercise, when compared to the criterion samples of gas analysis in arterial blood. These differences were exacerbated as the exercise intensity increased from a mean(+/- SE) difference of 2.9 +/- 0.7 %SaO2 at max to 4.6 +/- 0.7 %SaO2 at Smax. Breathing a higher FIO2 reversed the hypoxemia that occurred during the normoxic exercise, however, pulse oximetry measurements failed to detect this alteration in %SaO2. Estimates of oxygen saturation during severe exercise using pulse oximetry should be viewed with caution, as potentially large errors may occur.

Adolescent↗
PubMed1991

The Drinkwater-Ross anthropometric fractionation of body mass: comparison with measured body mass and densitometrically estimated fat and fat-free masses.

The Drinkwater-Ross anthropometric fractionation of body mass (mass = sigma skeletal, residual, fat and muscle masses), lean body mass (LBM = sigma skeletal, residual and muscle masses) and fat mass (FM) were compared with the measured body mass, together with the densitometrically estimated fat-free mass (FFM) and fat mass (FM), of 205 male (mean +/- S.D.: 74.66 +/- 10.55 kg; 10.1 +/- 3.7% BF by densitometry) and 177 female (mean +/- S.D.: 59.14 +/- 8.85 kg; 18.5 +/- 5.1% BF by densitometry) South Australian State representatives in a variety of sports. Most absolute differences (d) between the measured body masses and those resultant from the sum of the four fractionated masses (male: d = 2.15 kg or 2.9%; female: d = 1.27 kg or 2.2%) were within what one would expect from random day-to-day variation. However, this was not so for the comparisons between the fractionated LBM (male: d = 2.54 kg or 3.8%; female: d = 2.45 kg or 5.2%) and FM scores (male: d = 1.67 kg or 30.0%; female: d = 2.40 kg or 20.0%) and their densitometric counterparts. These differences are probably related to a combination of the densitometric and fractionation assumptions.

Adipose Tissue↗
PubMed1989

Specificity of test duration when assessing the anaerobic lactacid capacity of high-performance track cyclists.

The specificity of three maximal cycling sprint tests as a measure of anaerobic lactacid capacity was determined in nine highly trained male cyclists when they performed 10-, 30-, 40-, and 60-s tests on a modified Repco wind-braked cycle ergometer. Peak power (PP), percent power loss (% PO), total work done (TW), and peak blood lactate (PHLa) were determined for each test. The cyclists also performed a 1000-m time trial under competition conditions during which 200-m split times, total time (TT), and peak post-competition blood lactate (TTPHLa) were recorded. While there was no statistically significant difference between the peak blood lactate of the 30-, 40-, and 60-s tests, peak blood lactate achieved after the 1000-m time trial was significantly greater than those after the cycle ergometer tests. Although there were high intercorrelations (0.88-0.99) between the anaerobic power and capacity indices of the laboratory tests, only the PP and TW achieved during the 60-s test correlated significantly (P less than 0.05) with TT. The data suggest that when assessing the anaerobic power and capacity of elite 1000-m time trial cyclists, a cycle ergometer test duration of at least 60 s should be employed.

Adult↗
PubMed1987

The relative body fat and anthropometric prediction of body density of South Australian females aged 17-35 years.

One hundred and thirty-five females were tested in order to: produce some normative percentage body fat (% BF) data on an Australian sample which represented a cross-section of physical activity patterns, cross-validate existing multiple regression equations which predict body density (BD) from anthropometric measurements, and if necessary develop population specific equations. Measurements were taken of 10 girths, 3 widths and 7 skinfolds. Body density was measured by underwater weighing with the residual volume (RV) being determined by helium dilution. The Siri equation was then used to convert BD to % BF. The % BF scores had an overall mean of 23.4 (range 10.8-49.2). The very active group (n = 45) had a significantly lower (p less than 0.05) relative body fat (X = 20.6% BF) than either the active (n = 45; 23.5% BF) or sedentary groups (n = 45; 26.2% BF). Previously published equations were found to have limited applicability to Australian subjects. A stepwise multiple regression was therefore used to develop the following equation (R = 0.893): BD(g X cm-3) = 1.16957-0.06447 (log10 sigma triceps, subscapular, supraspinale, front thigh, abdominal and calf skinfolds in mm)-0.00081 (gluteal girth in cm) + 0.0017 (forearm girth in cm) + 0.00606 (biepicondylar humerus breadth in cm). Only those predictors which resulted in a statistically significant increase in r (p less than or equal to 0.05) were included. The standard error of estimate of 0.00568 g X cm-3 was equivalent to 2.6% BF at the mean.

Adipose Tissue↗
PubMed1987

Relative body fat and anthropometric prediction of body density of male athletes.

Two hundred and seven male members of South Australian representative squads in 18 sports (mean +/- s = 24.2 +/- 4.7 years) were tested in order to provide descriptive data on relative body fat (% BF), develop a population specific equation and cross-validate existing equations. Measurements were taken of 10 circumferences, 2 diameters and 8 skinfolds; body density (BD) was measured by underwater weighing with the residual volume (RV) being determined by He dilution. The overall mean BD was 1.0761 g X cm-3 (s = 0.0085 g X cm-3; range = 1.0465-1.0968 g X cm-3) which corresponded to 10.0% BF according to Siri (s = 3.7%; range = 1.3-23.0%). The games players (n = 129) registered an overall mean of 10.3% BF (s = 3.7%; range = 2.2-23.0%). There were significant differences (p less than 0.05) for % BF between the lacrosse players (mean = 12.3%) an both the Australian Rules footballers (mean = 8.0%) and track and field athletes (mean = 8.7%). A stepwise multiple regression on 185 subjects yielded the following equation, which had an R of 0.787: BD = 1.078865-0.000419 (sigma abdominal, medial calf, front thigh and juxta-nipple skinfolds in mm) +0.000948 (neck circumference in cm) -0.000266 (age in decimal years) -0.000564 (ankle circumference in cm). Only those predictors which resulted in a significantly increased correlation (p less than or equal to 0.05) were included. The standard error of estimate of 0.00537 g X cm-3 was equivalent to 2.3% BF at the mean. This equation was satisfactorily cross-validated against the BD of a separate sample (n = 22) from the same population. However, cross-validation of 11 previously published equations indicated that they have limited applicability to State representative sportsmen.

Adipose Tissue↗