Validation of Maximal Heart Rate Prediction Equations based on Sex and Physical Activity Status

International Journal of Exercise Science 8(4): 318-330, 2015. The purpose of the study was to determine if measured maximal heart rate (HRmax) was affected by sex or aerobic training status, and to determine the accuracy of three common clinical age-prediction maximal heart rate regression equations used to predict HRmax: HRmax = 220 – age, HRmax = 226 – age, and HRmax = 208 – (0.7 ∙ age). Fifty-two participants in total, 30 of which were in the active group (15 M, 15 F) and 22 subjects in the sedentary group (9 M, 13 F), within the age range of 18-25 years and with a normal BMI (18.5-24.9 kg∙m-2) underwent a Bruce maximal treadmill exercise protocol. The effect of sex and training status on HRmax was analyzed through a two-way ANOVA, and the effect of sex, aerobic training status, and regression equation on accuracy of the HRmax prediction was assessed with a three-way ANOVA (α=0.05). Overall, males had a higher HRmax than females (198.3 v. 190.4 beats • min-1 , p\u3c.001) and sedentary individuals had higher measured HRmax than active individuals (197.3 v. 191.4 beats • min-1, p=.002). Furthermore, HRmax = 208 – (0.7 ∙ age)(equation 3) calculated the smallest signed and unsigned residuals from the difference between observed HRmax and predicted HRmax values for the significant main effects of equation (3), equation x sex (females x 3), and equation x activity level (active x 3). Therefore, based on our results, we conclude that HRmax = 208 – (0.7 ∙ age) has greater accuracy than the other two equations studied for predicting observed values of HRmax in 18-25 year olds

Dynamic Stability in Gymnasts, Non-balance Athletes, and Active Controls

Sloanhoffer, H.S., McCrory, J.L., FASCM. Division of Exercise Physiology, West Virginia University, Morgantown, WV Gymnastics by nature is a balance sport requiring both static and dynamic stability. To our knowledge, static and dynamic postural stability of gymnasts has not been compared to other types of athletes of the same caliber and active non-athlete controls. Purpose: To investigate whether or not NCAA gymnasts have greater postural stability than NCAA athletes in other sports and non-athletes. Methods: Data were collected on 7 gymnasts (G), 7 non-balance athletes (NBA), and 6 active non-athlete controls (NAC). Following informed consent, subjects were tested on a posturography device to assess center of pressure (COP) movement during static and dynamic conditions. Static balance was measured using the 6-condition Sensory Organization Test (SOT) and dynamic balance (toes-up and toes-down tilt) was measured using the Adaptation Test (ADT). Mediolateral sway (ML sway), anterioposterior sway (AP sway), COP displacement (COPD) and COP velocity (COPV) were determined for the SOT, and initial sway, total sway, and sway velocity were calculated for the ADT. A two factor ANOVA was performed (group x condition) on each of these variables (α=0.05). Tukey post-hoc tests were performed where appropriate (α=0.05). Results: ML sway was significantly less (pConclusion: Based on these data, G and other NBA share similar dynamic stability. Both G and NBA display greater mediolateral stability compared to NAC. Future research should investigate the biomechanics of these athletes when their balance is challenge

The Influence of Arch Type on Injury in Minimally-Shod Runners

Galbreath K.M., Harrison K.D., McCrory J.L., FACSM, West Virginia University, Morgantown, WV Greater than 30% of runners are injured annually. In shod runners, individuals with high arches (pes cavus) are more likely to sustain a bony injury and those with low arches (pes planus) are more likely to sustain a soft tissue injury. However, this relationship has not been established in minimally-shod runners. Purpose: To determine if arch type (pes cavus, pes planus) is related to location and type (bony, soft tissue) in minimally shod runners. Methods: Sixteen experienced minimalist runners participated (age: 27.4±10.1 yrs, hgt: 170.3±25.0 cm, mass: 78.1±18.0 kg, gender: 8M, 8F). Informed consent was obtained. Arch index (AI) was obtained via an inked footprint. Subjects were surveyed about the type and location of pain felt while running. Pain in areas of common running injuries (hip, knee, ankle, lower leg, and foot) was quantified using a validated visual analog scale (VAS). Based on survey data, injuries were classified as soft-tissue or bony. Subjects were considered to be injured if pain on the VAS \u3e3. Left and right side data were pooled together. Feet were classified as being pes cavus (AI \u3c 0.21, n=7 feet), or pes planus (AI\u3e0.26, n = 11 feet). Feet with normal arches (n = 14) were excluded from further analysis. Chi-squared analyses were performed to determine if arch type was related the incidence of soft-tissue or bony pain. Separate chi-squared analyses assessed if arch type was a factor in the location of pain. (α = 0.05). Results. Runners with a pes cavus foot were more likely to report soft-tissue pain than those with a pes planus foot (PC: 85.7%, PP: 40.0%; p=0.040). No differences were found in the likelihood of runners with different arch types to report pain in the hip, knee, ankle, foot, or calf (p \u3e 0.05). Conclusions: The results of this pilot study seem to contradict the results of a study on shod runners. We found minimalist runners with a pes cavus foot more likely to report soft-tissue pain whereas others reported shod runners with a pes cavus foot more likely to sustain a bony injury. Soft tissue pain was reported by our subjects in the Achilles tendon, calf muscle, patellar tendon, peroneal tendon, plantar fascia, and a Morton’s neuroma. The loading mechanics of minimally-shod running need to be further investigated to determine why these runners with pes cavus feet are more likely to experience a soft-tissue injury

Primigravida Foot Anthropometric Effects on Foot, Posterior-Pelvic and Low Back Pain

1Harrison, K.D., 2Thomas K., 1McCrory, J.L., FASCM. 1Division of Exercise Physiology, 2Division of Physical Therapy, West Virginia University, Morgantown, WV Incidence of foot, posterior pelvic and back pain is increased during pregnancy. Furthermore, many women report changes in foot size during pregnancy; however these changes have not been thoroughly investigated. Purpose: To examine the effects of a first pregnancy on foot anthropometry and self-reported foot, posterior pelvic and low back pain. Methods: Eleven pregnant women (age: 28.7±4.2yrs height: 167.1±6.6cm) and 10 nulliparous controls matched to pre-pregnancy weight (age: 22.9±2.4yrs height: 164.8±4.6cm) participated. Following informed consent, foot length and width were assessed with an anthropometer. Arch index (AI) was assessed with an inked footprint obtained via an Aetrex Harris Mat. Arch Height Index (AHI) was measured with an Arch Height Index Measurement System. Rearfoot angle (RA) and pelvic obliquity (PO) were also assessed using digital photogrammetry and ImageJ software. Self-reported pain at the low back, hip and buttocks region, upper leg, knee, lower leg, and foot and ankle were obtained with validated VAS surveys. An ANOVA was used to compare results between groups (pregnant vs. control) and trimester (nested within pregnant group). For this prospective study, α=0.1. Results: Although mass was significantly different between groups and trimesters (Con: 61.5±8.1kg, 1st tri: 64.7±8.7kg, 2nd tri: 71.2±12.0kg, 3rd tri: 77.5±15.2kg; p=0.068), no significant differences were found in any measure of lower extremity alignment or anthropometry. Despite this, there were significant differences between groups in pain at the lower back (Con: 9.2±0.8, 1st tri: 9.0±0.8, 2nd tri: 7.7±1.9, 3rd tri: 7.5±2.1; p=0.081) and hip (Con: 8.9±1.4, 1st tri: 9.1±1.1, 2nd tri: 7.7±1.9, 3rd tri: 7.8±2.0; p=0.099), where 0 indicates worst possible pain and disability, and 10 indicates no pain or disability. Conclusions: Although no overall differences were found in lower extremity alignment, it is possible that individual biomechanical response to pregnancy is variable. Future research should investigate whether back, hip, and foot pain during pregnancy are more common in women who do experience changes in lower extremity alignment vs. those who demonstrate no changes

Thoracopelvic Coordination of Pregnant Women During Gait

1McCrory J.L., FASCM, 2Seay J.F., 3Hamill J., FACSM, 1West Virginia University, Morgantown, WV, 2U.S. Army Research Institute of Environmental Medicine, Natick, MA, 3University of Massachusetts, Amherst, MA, USA Pregnant women experience dramatic alterations to the shape of their bodies, particularly in the torso. These changes contribute to a “waddling” gait later in pregnancy, which has been defined as greater thoracic extension, anterior pelvic tilt, and mediolateral translation of the torso compared to non-pregnant women. These changes could also increase chances of having pregnancy-related back pain, which has been reported by 50% of pregnant women. Other populations with low back pain exhibit changes in the coordination pattern between the thorax (i.e. upper torso) and pelvis during gait. The Purpose of this study was to examine the effect of advancing pregnancy on thoracopelvic coordination during gait. Methods: Data were collected on 29 pregnant participants in their 2nd and 3rd trimesters and on 40 control women. An 8 camera motion capture system (120 Hz) was used to collect 3D angular data of the thorax and pelvis while subjects walked at their freely chosen speed along an 8m laboratory runway. The thorax was modeled with markers placed on the manubrium, xyphoid process, and spinous processes of the C7 and T10 vertebrae. The pelvis was modeled with markers placed bilaterally on the ASIS and PSIS. Coordination between the thorax and pelvis during early stance, midstance, late stance, and swing was calculated via a vector coding technique. A MANOVA was performed to determine if differences existed in the coupling angle between the thorax and pelvis between pregnant women in each trimester and controls (α=0.05). Tukey post-hoc tests were performed when appropriate. Results: The frontal plane coupling angle was greater in late stance during the 3rd trimester (223.3±63.4º) than in the 2nd trimester (198.7±63.4º; p = 0.01) or in controls (198.6±63.2º; p=0.02). No differences were noted in the coupling angles in the sagittal or transverse planes. Conclusion: Pregnant women are said to “waddle.” While previous studies have reported no alterations in the frontal plane angular movement of the thorax and pelvis individually during gait, we found that the frontal plane phase angle is increased in the third trimester, such that the pelvis and trunk had more in-phase coordination in the third trimester compared to controls. This change in coordination mechanics may be related to the high incidence of back pain in pregnant women

Primigravida Foot Anthropometric Effects on Foot, Posterior-Pelvic and Low Back Pain

1Harrison, K.D., 2Thomas K., 1McCrory, J.L., FASCM. 1Division of Exercise Physiology, 2Division of Physical Therapy, West Virginia University, Morgantown, WV Incidence of foot, posterior pelvic and back pain is increased during pregnancy. Furthermore, many women report changes in foot size during pregnancy; however these changes have not been thoroughly investigated. Purpose: To examine the effects of a first pregnancy on foot anthropometry and self-reported foot, posterior pelvic and low back pain. Methods: Eleven pregnant women (age: 28.7±4.2yrs height: 167.1±6.6cm) and 10 nulliparous controls matched to pre-pregnancy weight (age: 22.9±2.4yrs height: 164.8±4.6cm) participated. Following informed consent, foot length and width were assessed with an anthropometer. Arch index (AI) was assessed with an inked footprint obtained via an Aetrex Harris Mat. Arch Height Index (AHI) was measured with an Arch Height Index Measurement System. Rearfoot angle (RA) and pelvic obliquity (PO) were also assessed using digital photogrammetry and ImageJ software. Self-reported pain at the low back, hip and buttocks region, upper leg, knee, lower leg, and foot and ankle were obtained with validated VAS surveys. An ANOVA was used to compare results between groups (pregnant vs. control) and trimester (nested within pregnant group). For this prospective study, α=0.1. Results: Although mass was significantly different between groups and trimesters (Con: 61.5±8.1kg, 1st tri: 64.7±8.7kg, 2nd tri: 71.2±12.0kg, 3rd tri: 77.5±15.2kg; p=0.068), no significant differences were found in any measure of lower extremity alignment or anthropometry. Despite this, there were significant differences between groups in pain at the lower back (Con: 9.2±0.8, 1st tri: 9.0±0.8, 2nd tri: 7.7±1.9, 3rd tri: 7.5±2.1; p=0.081) and hip (Con: 8.9±1.4, 1st tri: 9.1±1.1, 2nd tri: 7.7±1.9, 3rd tri: 7.8±2.0; p=0.099), where 0 indicates worst possible pain and disability, and 10 indicates no pain or disability. Conclusions: Although no overall differences were found in lower extremity alignment, it is possible that individual biomechanical response to pregnancy is variable. Future research should investigate whether back, hip, and foot pain during pregnancy are more common in women who do experience changes in lower extremity alignment vs. those who demonstrate no changes

Life-course socioeconomic factors are associated with markers of epigenetic aging in a population-based study.

Adverse socioeconomic circumstances negatively affect the functioning of biological systems, but the underlying mechanisms remain only partially understood. Here, we explore the associations between life-course socioeconomic factors and four markers of epigenetic aging in a population-based setting. We included 684 participants (52 % women, mean age 52.6 ± 15.5 years) from a population and family-based Swiss study. We used nine life-course socioeconomic indicators as the main exposure variables, and four blood-derived, second generation markers of epigenetic aging as the outcome variables (Levine's DNAmPhenoAge, DunedinPoAm38, GrimAge epigenetic age acceleration (EAA), and the mortality risk score (MS)). First, we investigated the associations between socioeconomic indicators and markers of epigenetic aging via mixed-effect linear regression models, adjusting for age, sex, participant's recruitment center, familial structure (random-effect covariate), seasonality of blood sampling, and technical covariates. Second, we implemented counterfactual mediation analysis to investigate life-course and intermediate mechanisms underlying the socioeconomic gradient in epigenetic aging. Effect-size estimates were assessed using regression coefficients and counterfactual mediation parameters, along with their respective 95 % confidence intervals. Individuals reporting a low father's occupation, adverse financial conditions in childhood, a low income, having financial difficulties, or experiencing unfavorable socioeconomic trajectories were epigenetically older and had a higher mortality risk score than their more advantaged counterparts. Specifically, this corresponded to an average increase of 1.1-1.5 years for Levine's epigenetic age (β and 95 %CI range, β (minimum and maximum): 1.1-1.5 95 %CI[0.0-0.2; 2.3-3.0]), 1.1-1.5 additional years for GrimAge (β: 1.1-1.5 95 %CI[0.2-0.6; 1.9-3.0]), a 1-3 % higher DunedinPoAm38 age acceleration (β: 0.01-0.03 95 %CI[0.00; 0.03-0.04]), and a 10-50 % higher MS score (β: 0.1-0.4 95 %CI[0.0-0.2; 0.3-0.4]) for the aforementioned socioeconomic indicators. By exploring the life-course mechanisms underlying the socioeconomic gradient in epigenetic aging, we found that both childhood and adulthood socioeconomic factors contributed to epigenetic aging, and that detrimental lifestyle factors mediated the relation between socioeconomic circumstances in adulthood and EAA (31-89 % mediated proportion). This study provides emerging evidence for an association between disadvantaged life-course socioeconomic circumstances and detrimental epigenetic aging patterns, supporting the "sensitive-period" life-course model. Counterfactual mediation analyses further indicated that the effect of socioeconomic factors in adulthood operates through detrimental lifestyle factors, whereas associations involving early-life socioeconomic factors were less clear