178 סאמיז מחכים לך

אונו

הפחתת שומן נקודתית - מציאות או אגדה?

    הורדת אחוז שומן באזור מסוים בגוף הוא רעיון שקוסם להרבה מתאמנים, אבל האם הוא אפשרי?

    • אונו

      מה הקשר בין הרגלי תזונה לאיכות השינה?

      המסקנות של מחקר מקיף בנושא השפעת צריכת חלבונים, פחמימות ושומנים על איכות השינה

      02:38
    • אונו

      האם מתיחות עלולות לפגוע בעלייה במסת השריר?

      עושים מתיחות לפני אימון? יתכן שאתם פוגעים ברמת הביצועים של השריר.

      02:40
    • אונו

      האם למתיחות בין סטים יש השפעה על מסת השריר?

      האם למתיחות בין סטים במהלך אימוני כוח באמת פוגעות בכוח המרבי של השריר, כמו שנהוג לחשוב?

      03:11
    • Newsweek

      מחקר: מהו התזמון האידיאלי לאימון?

      We don't need to tell you that exercise is healthy, but there is some evidence that the benefits vary depending on the time of day you hit the gym. For example, you may burn more fat after a morning workout, according to one study. But is there actually a right time to focus on fitness? In 2011, researchers from Appalachian State University found the perfect time for exercise: 7 a.m. The team noticed that people who scheduled their gym time at this hour lowered their blood pressure by about 10 percent, which remained consistently lower throughout the day. These early risers also had a 25-percent decrease in their blood pressure at night. Plus, they slept for longer periods of time compared to those who exercised at various times. The researchers noted that there were few sleep or blood pressure benefits when people exercised at 7 p.m. or 1 p.m. It seems that morning workouts can also help people hoping to drop a few pounds. Those who worked out with an empty stomach burned up to 20 percent more fat, according to health site Greatist. Another study indicated that moderate exercise for 45 minutes in the morning reduced appetite, the site reports. However, numerous studies have shown that exercising itself can reduce appetite. Research from 2016 revealed that rigorous exercise curbed appetite for the whole day, reports Shape. Scientists found that physical activity decreases ghrelin, a hormone that causes appetite, while increasing peptide YY, a hormone that actually suppresses appetite. In other words, the weight-loss benefits of exercise could come from multiple directions. According to one British study, people who go to the gym at night are able to exercise more intensely and for longer periods of time, according to an article in Self. The researchers found that people who wake up later reach their peak performance 11 hours after getting out of bed, and early risers experience their apex six hours after waking up. Sprint drills at the top of the Waseley hills. . . . #running #sprint #hiit #cardio #hill #picturesque #winter #runner #athlete @usaprouk @bejuststrong @myproteinuk #run #cold #sun #training The magazine reports that strength training might be best done at night because we have higher levels of testosterone, which helps build muscle. Additionally, our muscular function also peaks at night, making it easier to tone up. Of course just getting yourself to the gym is an accomplishment, whether it's on a cold, dark morning, or after a long day at the office. So the right time to work out really comes down to the time that works best for you.

      מה הקשר בין תזמון האימון לבין יעילות שריפת השומנים במהלכו?

      02:39
    • JMMT

      השפעת טיפול בקור על התאוששות אחרי משחק

      כל מי שחטף מכה רצינית במשחק או אימון, בטח כבר קיבל עצות לגבי הטיפול: "פשוט...
      02:17
    • PubMed Central (PMC)

      איך מקלים על כאב ראש ממקור צווארי?

      Studies on the effect of a low intensity coordination exercise on the elderly with limited mobility are sparse. This prospective study attempted to compare the effectiveness of a customized coordination exercise and a strength exercise in improving the cognitive functioning and physical mobility on the elderly. Participants from two centers for the elderly were allocated to practice either an 8-week coordination training (CT) program or an 8-week towel exercise (TE) program. The Chinese Mini-Mental State Examination and Chinese Dementia Rating Scale (CDRS) were used to measure cognitive functioning of participants, and Timed Up-and-Go test for physical mobility. These assessments were administered before and after the program. Paired t-tests showed that the CDRS scores of the CT group improved significantly from 114.8 at pre-test to 119.3 after training (P = 0.045). The CDRS scores of the TE group also improved from 114.9 at pre-test to 116.9 after training. Findings from this prospective study demonstrated that low-intensity level mind-body exercise could be beneficial to the cognitive functioning of older adults. The benefits of physical exercise on cognitive function in the elderly have been demonstrated in many studies. Several large-scale longitudinal studies showed that older people who have a high level of physical activity, have a significantly lower risk of developing Alzheimer’s disease and cognitive impairment.1–7 The results of a meta-analysis of 18 studies investigating the effectiveness of aerobic exercise concluded that fitness training could enhance the cognitive functioning of the elderly.8 This study also showed that a short duration, moderate-level training program could create an optimal effect on cognitive functions in the elderly. Another meta-analysis investigating the change of duration and intensity of physical activity conducted by van Gelder et al found that elderly people who participated in physical exercise for an average of 30 minutes per day or more could postpone their cognitive decline.9 However, studies on the benefits of physical training have focused closely on aerobic exercise such as walking, and strength exercise, such as weight lifting.4,6,7,10–12 These aerobic and strength exercises require the participants to be highly mobile. The elderly with low mobility, or who are hospitalized, might have difficulty enjoying the full benefit of the exercise because of their limited locomotive ability. Therefore exercise with reduced locomotion requirement, could provide the benefits of aerobic exercise to the elderly with restricted mobility. Recently, there has been growing research interest in the therapeutic effects of mind–body exercise.13,14 Tai Chi Chuan, commonly known as Tai Chi, is a typical example of mind–body exercise; it is characterized by slow motion and emphasizes the conscious control of body movements, ie, it requires less locomotive mobility and is deemed appropriate for most elderly people.15 Research has shown that the cognitive functions of the elderly could be well preserved with the aid of such mind–body exercise, in a way similar to typical physical exercise.3 Exercises with lower requirements of locomotive ability, such as coordination training (CT) and towel exercise (TE), are needed for the elderly with poor mobility. Both CT and TE require low locomotive ability, and thus are suitable for most elderly. The literature review showed that CT and TE may also be beneficial for the cognitive functioning of the elderly. The purpose of this study was to compare the effectiveness of CT and TE on the cognitive functioning and physical mobility of the elderly, with the aim of developing an exercise with a low mobility requirement, to benefit the cognitive functioning of the elderly. We hypothesized that the elderly in the CT group would show significant improvement in the cognitive measures compared with the elderly in the TE group. Forty elderly (three male, 37 female) with normal cognition were recruited from two elderly centers of the Hong Kong Lutheran Social Service, aged 66–90 (mean = 79.0, SD = 5.8). Targeted participants were asked to take the Chinese version of Mini-Mental State Examination (CMMSE) as one of the screening criteria, and those who scored ≥ 18 were eligible for this study.16 Other than that, there was no other inclusion or exclusion criterion in recruitment. The ethics approval of this study was obtained from the Survey and Behavioural Research Ethics Committee of the Chinese University of Hong Kong. Participants confirmed their agreement to participate in this study by signing informed consent before the exercise began. A physiotherapist from the Jockey Club Centre for Positive Ageing (JCCPA, see http://www.jccpa.org.hk) developed an 8-week exercise program, called Coordination Training (CT), which is a simplified version of Tai Chi. It focuses on the coordination and conscious control of the body. It was easy for the elderly to learn, and required a relatively low level of mobility to practice. The eleven movements included coordination of fingers, hands, eyes, and legs. A brief description of the eleven movements is set out in Table 1 . The elements of Movement 4 are tabulated in Table 2 and graphically represented in Figure 1 as an example. Movement 4 helped to train participants’ coordination of upper limbs, and was intended to imitate the movements of Tai Chi. Graphical illustrations of Movement 4 of the coordination training. (A) Straighten two arms and point both index fingers to the front. (B) Touch the left or right ear with corresponding index finger, while the other hand remains straight. (C) Switch and practice ten cycles (left and right) with 1 second rest (easy) or without rest (medium and hard) between each cycle. The training protocol of TE was developed by the Leisure and Cultural Services Department, the Government of the Hong Kong Special Administrative Region in 2005.17 Similar to Movement 4 in CT, TE was a type of stretching exercise mainly to train upper limb and bilateral arm movements, but utilize a towel as a tool. It was strongly promoted by the government because it was easy for elderly people with various locomotive abilities to master.18 TE benefited the elderly by improving circulation and helping to control weight, and aimed to reduce the chance of falling.19 For the sake of convenience of participation and better monitoring of participants’ progress, those in one center were allocated to practice CT, and those in another center were allocated to practice TE. TE was chosen to compare with CT because these exercies were similar in a number of ways. Both exercises required subjects to follow instructions, and to coordinate upper limb and bilateral arm movements. Yet TE did not require such fine motor coordination as CT. CT and TE were conducted for 8 consecutive weeks, with one 40-minute session per week. Both groups had a 10-minute warm-up period at the beginning and a 10-minute cool-down period at the end of the session to prevent injury. The remaining 20 minutes would be taken up with the actual CT or TE exercise. Both exercise groups were conducted by qualified instructors trained by the physiotherapist, mentioned above. For CT, there were three levels of difficulty: easy, medium, and difficult (see Table 2 ). The level of difficulty was increased mainly by reducing the rest time (demanding higher concentration as well as physical strength of participants), and by closing the eyes when performing the actions (demanding higher psychomotor balance of participants). In this study, when the participants self-reported being able to handle the movement comfortably, which was confirmed by the trainer, they were required to practice the movement at an advanced difficulty level in order to avoid the ceiling effect.19 Assessment tools including Chinese Mini-Mental State Examination (CMMSE), Chinese Dementia Rating Scale (CDRS), and Timed Up-and-Go test (TUG) were administered to participants in both groups before and after the training sessions by trained occupational therapists and clinical psychologists. CMMSE and CDRS were used to assess participants’ cognitive functioning. General cognitive status was assessed using the CMMSE, which was translated and validated by Chiu et al in the Hong Kong Chinese population.20 The full mark was 30. The Cronbach’s alpha was 0.86. The test had excellent clinical utilities in screening general cognitive decline. CDRS measured the level of cognitive functioning of the participants. It examined five different aspects of cognitive ability, namely, attention, initiation-perseveration, construction, conceptualization, and memory. The maximum score of the unadjusted scale was 144, with the Cronbach’s alpha of 0.89. Good psychometric properties were observed in both the original DRS and the Chinese version.21,22 TUG was a good instrument to measure the general physical mobility of participants, and thus was administrated in this study to measure the effects of relevant exercises.23 The longer time spent to finish TUG (slower), the poorer the performance of participants, and vice versa. SPSS software v 15 (IBM Corp, Somers, NY) was used for data analyses. Independent sample t-tests were conducted to compare the pre-test scores (obtained in pre-test period) between CT and TE groups. Paired sample t-tests were performed to compare the post-test scores (obtained in the ninth week, after the 8-week exercise period) with the pre-test scores in each group. Analysis of covariance (ANCOVA) was used to compare the scores of CMMSE, CDRS, and TUG of the two groups after the training program, using participants’ age and the pre-test scores as covariates. Statistical significant difference was set at P < 0.05. Forty people (three males, 37 females) aged 66 to 90 years (mean = 79.0, SD = 5.8) were recruited. The average ages of the elderly in the CT and TE groups were 77.7 ± 6.0 and 80.3 ± 5.5, respectively. Baseline characteristics are tabulated in Table 3 . No significant difference was found in demographic features or cognitive and physical functioning test scores between the two groups. Comparisons of participants’ pre-test (baseline) and post-test cognitive functioning by CMMSE amd CDRS scores and physical mobility by TUG scores are shown in Table 4 . Paired t-tests showed that the CDRS scores of the CT group had improved significantly from 114.8 ± 15.5 at pre-test to 119.3 ± 18.0 at post-test (CDRS t(17) = −2.25, P = 0.045). The CDRS scores of the TE group improved slightly from 114.9 ± 14.8 at pre-test to 116.9 ± 12.5 at post-test. No significant change was found in CMMSE (t(18) = −0.931, P = 0.368), and TUG (t(17) = −0.334, P = 0.747) in CT group, as well as CMMSE (t(19) = 0.665, P = 0.516), CDRS (t(19) = −0.891, P = 0.384) and TUG (t(19) = −1.908, P = 0.086) in the TE group. Means and standard deviations and the changes in CMMSE, CDRS, and TUG scores between pre-test (baseline) and post-test (eighth week) in CT and TE groups Abbreviations: CMMSE, Chinese Mini-Mental State Examination; CDRS, Chinese Dementia Rating Scale; TUG, Timed Up-and-Go test; CT, coordination training group; TE, towel exercise group; SD, standard deviation. Different ANCOVA (between-subject factor: group [CT, TE] and covariates: age and the pre-test scores) models show the following findings. For CMMSE, the covariate age (F(1,28) = 0.17, P = 0.690, ηp2 = 0.003) and the exercise groups (F(1,28) = 3.41, P = 0.570, ηp2 = 0.139) were not significantly related to the CMMSE post-test scores. Only the covariate pre-test scores of CMMSE were significantly related to the post-test scores (F(1,28) = 16.32, P < 0.001, ηp2 = 0.428). For CDRS, exercise groups were not significantly related to the CDRS post-test scores (F(1,28) = 0.02, P = 0.904, ηp2 = 0.001). Only the covariate age (F(1,28) = 9.14, P = 0.005, ηp2 = 0.462) and the covariate pre-test scores of CDRS (F(1,28) = 59.12, P < 0.001, ηp2 = 0.738) were significantly related to the CDRS post-test scores. For TUG, the covariate age (F(1,26) = 0.01, P = 0.940, ηp2 = <0.001) and the exercise groups (F(1,26) = 0.11, P = 0.740, ηp2 = 0.005) were not significantly related to the TUG post-test scores. Only the covariate pre-test scores of TUG were significantly related to the TUG post test scores (F(1,26) = 83.50, P < 0.001, ηp2 = 0.791). The above findings served to compare the effectiveness of the two exercise programs, coordination training (CT) and towel exercise (TE), in improving cognitive functioning and physical mobility in the elderly. The results showed that CT group participants had significant improvements in global cognition after the 8-week exercise program. CT group gained significant improvement in CDRS scores after the exercise training, while the TE group participants did not. The lack of significant group difference in the changes in CDRS might be caused by the small sample size. Further investigation of the effectiveness of CT is recommended following this prospective study, through a large-scale clinical trial with appropriate numbers of samples in each group to detect the group differences. For the physical mobility measure, TE tended to improve mobility while CT did not. This pattern was probably expected, because CT was designed to improve cognition, not mobility. There was also no significant difference between CT and TE after controlling for age. The insignificant difference in physical mobility measure might suggest that CT, which required less in mobility, had a similar effect to TE, a common physical exercise, on the cognitive and physical functioning of the elderly population. The elderly with low mobility might benefit from physical exercise by practicing CT. Further investigation is needed to confirm this observation. Mind–body exercise can improve cognitive functions and other health indicators, although the role of physical exercise in modulating cognitive decline is complex. The improvements can be described through (1) psychosocial indicators and (2) physiological responses. Practicing regular physical exercise was found to be associated with better cognitive test performance and decreased arousal.3,24 A moderate exercise program followed twice a week significantly slowed, by one-third, the progressive deterioration in ability to perform activities of daily living in people with Alzheimer’s disease living in nursing homes.25 Mind–body exercises produce effects similar to those of regular cardiovascular exercises, suggesting an alternative model of exercise for the elderly, who are less able to exercise vigorously, to lower the risk of sport-related injuries and cardiac hazards.15 Elderly people with the habit of regular physical exercise have been shown to be associated with socialization and environmental enrichment, which may also help attenuate the rate of cognitive decline.3 Tai Chi, a well-known mind–body exercise, employs cognitive tools of both visualization and focused internal awareness to strengthen, relax, and integrate the body and mind.26 Tai Chi can also improve locomotion balance in seniors.27,28 A study evaluating a Tai Chi program called “Taiji (Tai Chi) Buddies Program” found that the program encouraged social participation and supported partner involvement, which may have a positive influence on exercise persistence and the health and well-being of the support partner.28 A 12-week Tai Chi exercise program has been found adequate to reduce perceived stress and improve mood state, as well as increase perceived social support.29 The findings of this research showed that CT exercise, a simplified form of Tai Chi developed in this study specifically for the elderly with low activity, shares similar advantages, improving cognitive functions. Studies reviewing the physiological responses to mind–body exercise explain this phenomenon further. Mind–body exercise enhances cardiovascular function, muscle strength, body balance, and physical function; these improvements have a positive correlation with reduced stress, anxiety, and depression, resulting in an improved quality of life.24,30,31 A study utilizing electroencephalogram (EEG) recorded an increased cordance value at left hemisphere (a sign of enhanced cerebral perfusion) in a patient with chronic epilepsy after practicing Dejian mind–body intervention (one of the components being mind–body exercise).32 The changes in brain activities reflected by EEG underlie the observed improvements in cognitive functions.32 In addition, practicing mind-body exercise, which exerts similar effects to aerobic exercise, helps to increase volume in both gray and white matters primarily located in prefrontal and temporal cortices – brain areas which are involved in age-related deterioration, as observed by MRI images.33 As demonstrated by animal models, exercise-induced up-active pathways are associated with enhancement of several neurotransmitter systems afferent to the hippocampus, including the norepinephrine, serotonin, acetylcholine, and γ-aminobutyric acid systems, which are important to hippocampal function.34 These changes in brain activities and functioning demonstrate that regular, moderate physical exercise has beneficial effects on brain health. The findings of this study are consistent with previous reports that have shown that subjects practicing regular physical exercise are associated with better cognitive test performance, and there is a positive correlation between cardiovascular and mind–body exercise and cognitive function among the Chinese elderly.3,15 These exercises, however, might not be effective for the elderly suffering from moderate and severe dementia, who are likely to be immobile or even bed-bound. The “coordination training” exercise applied in this study, which requires a lesser level of physical movement, sheds light on improving cognitive functions for dementia patients who may find difficulty undertaking regular physical exercise because they are physically less active or less mobile. Additional, large-scale randomized control studies are recommended to elaborate on the efficacy of mind–body exercise on cognitive functioning. The limitations of the study include the small sample size, and the absence of a control group (without any exercise). Participants in this study self-reported a habit of performing regular physical activities, and thus they are likely to be more health conscious with a lower cardiovascular burden.3 This prospective study attempted to provide evidence for the potential benefits of a customized coordination training exercise to improve the cognitive functioning of the elderly. The findings demonstrate that low physical level exercise similar to Tai Chi for example is beneficial for cognitive function and helps maintain the physical mobility of the elderly. The findings also give insight into developing further exercise regimes, which are more suitable for elderly people with a limited level of physical fitness or who are hospitalized. Additional research is encouraged to further confirm the effectiveness of the coordination training exercise. Changes in Chinese Dementia Rating Scale (CDRS) scores before and after the coordination training program (CT) or towel exercise program (TE) in respective groups. National Center for Biotechnology Information, U.S. National Library of Medicine 8600 Rockville Pike , Bethesda MD , 20894 USA

      סובלים מכאב ראש ממקור צווארי? כך תקלו עליו

      03:13
    • Hindawi

      הוכחה מדעית: כך משפיעה נעילת נעלי אפוס על כאבי ברכיים

      1Department of Orthopedic Surgery, Assaf Harofeh Medical Center, Zerifin, Israel 2Biorobotics and Biomechanics Lab, Faculty of Mechanical Engineering, Technion-Israel Institute of Technology, Haifa, Israel Copyright © 2013 Yaron Bar-Ziv et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Several biomechanics treatments for knee osteoarthritis (OA) have emerged with the goal of reducing pain and improving function. Through this, researchers have hoped to achieve a transition from the pathological gait patterns to coordinated motor responses. The purpose of the study was to determine the long-term effects of a therapy using a biomechanical device in patients with knee OA. Patients with knee OA were enrolled to active and control groups. The biomechanical device used in therapy (AposTherapy) was individually calibrated to each patient in the active group. Patients in the control group received standard treatment. Outcomes were the Western Ontario and McMaster Osteoarthritis Index (WOMAC), Aggregated Locomotor Function (ALF), Short Form 36 (SF-36), and Knee Society Score assessments. The active and control groups were similar at the baseline (group difference in all scores ). The active group showed a larger improvement over time between groups in all three WOMAC categories ( , 21.7, and 18.1 for pain, stiffness, and function; all ), SF-36 Physical Scale ( ; ), Knee Society Knee Score ( ; ), and Knee Society Function Score ( ; ). At the two-year endpoint, the active group showed significantly better results (all ). The groups showed a difference of 4.9, 5.6, and 4.7 for the WOMAC pain, stiffness, and function scores, respectively, 10.8 s in ALF score, 30.5 in SF-36 Physical Scale, 16.9 in SF-36 Mental Scale, 17.8 in Knee Society Knee Score, and 25.2 in Knee Society Function Score. The biomechanical therapy examined was shown to significantly reduce pain and improve function and quality of life of patients with knee OA over the long term. Knee osteoarthritis (OA) is one of the leading causes of disability in the elderly [1]. Currently, there is no cure for knee OA, and therefore, the primary goal of treatment is to reduce pain and improve function [2]. In recent years, there has been growing evidence on the importance of biomechanical factors in knee OA. Several biomechanical treatments for knee OA have emerged with the goal of reducing pain and improving function. These treatments aim to unload the diseased articular surface by using wedged insoles, foot orthoses, or valgus braces [3–5]. Other treatments have instead aimed to modify neuromuscular patterns, with a specific goal of improving gait patterns. The knee adduction moment (KAM) is an important parameter of gait that has been examined in recent years. A varus alignment of the femur and tibia compresses the medial compartment of the knee [6]. KAM results from the medially directed vector of the ground reaction force (GRF) relative to the knee during the stance phase of gait, which creates greater compressive loads on the medial compartment relative to the lateral compartment [7, 8]. Patients with knee OA have a higher KAM relative to the normal population, which is believed to drive the rapid progression of the disease [9, 10]. By improving gait patterns, such as KAM, researchers have hoped to achieve a transition from the pathological gait patterns that characterize knee OA gait to coordinated motor responses [11]. This would require patients to undergo a process of motor learning. In order to meet the requirements for motor learning, these methods must incorporate challenges for the motor system in a graded and controlled fashion, with multiple repetitions within a functional context [12]. For example, a study by Barrios et al. [13] was able to improve gait patterns and reduce KAM in individuals with valgus knees through repetitive training on a treadmill [13]. In addition, research has also shown that motor learning can be accomplished under perturbation in closed kinematic chain movement in which the whole limb, rather than just a single joint, is regarded as a kinetic functional unit [11]. One biomechanical therapy (AposTherapy) that has received attention in recent years is thought to both unload the diseased articular surface as well as improve neuromuscular control. This therapy utilizes a unique biomechanical system (Apos system, Figure 1) that consists of two convex-shaped rubber elements attached to each of the patient’s feet. One element is located under the hindfoot region, and one is located under the forefoot region of each foot. The elements are attached to the patient’s foot on mounting rails embedded within the sole of a foot-worn device. The mounting rails enable flexible positioning of each element under each region. The elements are calibrated to the individual patient according to the pathology and motion characteristics. Several studies by Haim et al. have examined the mechanism of the AposTherapy device and have shown that modifying the position of the biomechanical elements will precisely shift the center of pressure (COP) of each foot to a new location during gait [14, 15]. The COP can be shifted such that there are less external moments acting on the diseased articular surface. In addition, the convex shape of the elements puts the subject in a state of perturbation [16]. By having the subject walk with device everyday, the therapy is thereby thought to induce motor learning towards the desired neuromuscular gait pattern. Other studies have examined the effects of therapy on gait patterns and have shown that, over time, the therapy can be used to improve gait patterns, including KAM, in healthy individuals and in patients with knee OA [15, 17, 18]. Additional studies have shown that the biomechanical therapy is also able to modify the activation of lower limb muscles in healthy individuals and patients with knee OA as measured by electromyography [19, 20]. This signifies that the lower limb musculature of the subjects also adapts in a unique way to training. In a previous controlled study [21], we examined the ability of this therapy to improve clinical symptoms of patients with knee OA after 8 weeks of therapy. Our results showed a significant improvement over time in pain, function, and quality of life in the active group compared to the control group after 8 weeks of therapy. The former study was limited by the short-term follow-up period. The purpose of the present study was to examine the effect of this biomechanical therapy on the level of pain, function, and quality of life in patients with knee OA over the course of 2 years. The protocol was approved by the Institutional Helsinki Committee Registry of Assaf Harofeh Medical Center (Helsinki registration number 44/05 and NIH clinical trial registration number NCT00457132). All patients gave written informed consent prior to entering the study. Patients were recruited from the Department of Orthopedics of Assaf Harofeh Medical Center, Zerifin, Israel. Inclusion criteria were (1) symptomatic bilateral knee OA of the medial knee compartment for at least six months; (2) qualification of OA of the knee according to the American College of Rheumatology clinical criteria for OA of the knee, which include knee pain with at least 3 of the following: age > 50 years, stiffness < 30 minutes, crepitus, bony tenderness, bony enlargement, no palpable warmth [22]; (3) radiographically assessed OA of the knee according to the Kellgren & Lawrence (K&L) scale [23]. The K&L scale grades the knee according to one of four grades of severity, with I being the least severe and IV being the most severe OA. Only patients of grade II or above were included in the study. All patients had a varus knee alignment. Exclusion criteria were acute septic arthritis, inflammatory arthritis, patients with a history of increased tendency to fall, patients with a history of knee buckling, lack of physical or mental ability to perform or comply with the treatment procedure, diabetes mellitus, patients with a history of pathological osteoporotic fractures, symptomatic degenerative arthritis in lower limbs joints other than the knees (spine, hip, and ankle), severe back pain, and a history of lower limb orthopedic surgery other than knee arthroscopy. Patients were recruited to the study by the senior orthopedic surgeon (N.H.) according to the inclusion and exclusion criteria. Patients in the active group received the biomechanical therapy, whereas patients in the control group received the same shoe, but without the biomechanical elements (walking on flat shoes like any other shoe). The active group was asked to return for a follow-up exam at six months, one year, and two years. The control group was only asked to return at two years for a followup. Some patients were lost to followup in both groups, and three patients did not arrive for the six-month follow-up in the active group (Figure 2). The biomechanical therapy used for the present study is designed to combine COP manipulation in the foot with perturbation during walking. The therapy combines a biomechanical system with a specific treatment methodology (AposTherapy, Apos-Medical and Sports Technologies Ltd. Herzliya, Israel; Figure 2). The system consists of two convex-shaped biomechanical elements attached to each of the patient’s feet (i.e., 4 elements total). One is located under the hindfoot region, and one is located under the forefoot region of each foot. The elements are attached to the patient’s foot on mounting rails embedded within the sole of a shoe. The mounting rails enable flexible positioning of each element under each region. The device can be calibrated to the individual patient according to the pathology and motion characteristics. Specifically in the case of medial compartment knee OA, the element under the hindfoot is shifted laterally from the baseline position. This shifts the COP in the foot laterally, thereby reducing the magnitude of the KAM acting on the knee joint [14, 24]. The element under the forefoot is shifted medially from the baseline. Both elements are moved until the patient reports minimal pain during walking. In addition, the convex nature of the elements puts the patient under constant perturbation. The device is calibrated by a physical therapist certified in the AposTherapy methodology. In the second phase of the therapy, the patient walks with the device for a prescribed amount of time, allowing for the biomechanical perturbations to be applied throughout all phases of gait in repetition. Perturbation is achieved through the controlled instability created when walking on two convex-shaped elements. At the start of the study, the biomechanical device was calibrated to all patients in the active group. The device was recalibrated, as necessary, at each followup and between followups. Once the device was calibrated, the patient was sent home with the device and was requested to train with the device by walking with it during his daily routine for a specified amount of time each day. The patient was told to begin with ten minutes of indoor walking each day and gradually build up to thirty minutes of daily outdoor walking by three months. Compliance to the therapy was maintained with a log as well as with follow-up phone calls. Individuals allocated to the control and research group were allowed to consume other treatment modalities as they saw necessary to treat their knee. Patients were monitored for any invasive treatments applied during this period. Furthermore, patients were instructed not to participate in other studies. The patients in the control group received the same walking shoe, but without the biomechanical elements. The patients were told to begin with ten minutes of indoor walking each day and gradually build up to thirty minutes of daily outdoor walking by three months. Compliance to the therapy was maintained with a log as well as with follow-up phone calls. Patients returned at two years for reevaluation. Individuals in the control group were allowed to undergo any other medical or physical therapy, as well as use pain medication, as they saw necessary to treat their knee. The primary outcomes of the study included the Western Ontario and McMaster Osteoarthritis Index (WOMAC) [25] and the Aggregated Locomotor Function (ALF) test [26]. The WOMAC contains 24 visual analogue scale (VAS) questions and is divided into three categories of pain, stiffness, and function. These scales are scored from 0 cm to 10 cm, with 0 = no symptoms and 10 = worst symptoms. Since the study population was made up of patients with bilateral knee OA, patients were requested to score the WOMAC for their most painful knee. The ALF score is a sum of the mean time (seconds) taken to complete three locomotor tasks while barefoot: walking eight meters, ascending and descending seven stairs, and transferring from a sitting to standing position. Each task was carried out separately with a break in between. The sum score was added up for all tasks. The secondary outcomes included the Short Form 36 (SF-36) health survey [27] and the Knee Society Score (KSS) [28]. The SF-36 is divided into eight categories: physical functioning, role limitation due to physical health, role limitation due to emotional health, energy/fatigue, emotional well-being, social functioning, pain, and general health. The physical component summary (PCS) and mental component summary (MCS) are summary scales of the eight categories. These scales are scored from 0–100, with higher scores indicating better states of health and quality of life. The KSS is measured by the clinician and is divided into a knee score (KSS-K) and function score (KSS-F). The KSS-K evaluates the function of the knee alone, while the KSS-F evaluated the function of the knee during physical activity. The analysis was performed using SPSS software version 19.0 (SPSS, Chicago). Data were presented by frequencies and percentages for categorical variables and by means and standard deviations for continuous variables. Mean differences between the groups were presented with 95% confidence intervals (CIs). The criterion for significance (alpha) was set at 0.050, and the test was two tailed. With the proposed sample size of 38 pairs of cases, the study had a power exceeding 99.9% to yield a statistically significant result. This computation assumed that the population from which the sample would be drawn would have a mean difference of 3.0 with a standard deviation of 2.0. The observed value was tested against a theoretical value (constant) of 0.00. With the same assumption, a sample size of 9 pairs of cases would have had power of 97.5% to yield a statistically significant result. Kolmogorov-Smirnov tests of the study outcome distribution showed that all the results were normally distributed. An independent -test (two tailed) was used to compare the patient characteristics of age at the baseline, as well as all the outcome measures at the baseline and after two years. The patient characteristics of sex and Kellgren and Lawrence radiographic knee OA (K&L) score between groups were compared at the baseline using a chi-square test. Changes within the groups and differences between the groups in all outcomes over time (time by treatment interaction) were measured using a repeated measures analysis of variance (ANOVA) test. The significant level was set to 0.05. A total of 56 patients (15 males, 41 females, age 65.1 (SD 7.9) years) were enrolled to the study. The active group was comprised of 40 patients (10 males, 30 females, age 64.1 (SD 7.5) years), and the control group was comprised of 16 patients (5 males, 11 females, age 67.4 (SD 8.6) years). At the two-year endpoint, 38 patients and 9 patients remained in each group, respectively (Figure 1). At the baseline, the groups were comparable in patient characteristics (Table 1), primary outcomes (Table 2), and secondary outcomes (Table 3). A significant difference was found between the active and control groups in all three WOMAC categories (pain, stiffness, and function) at the two-year endpoint (all ; Table 2). There was also a significant difference in improvement over time between groups in all three categories ( for interaction =16.8, 21.7 and 18.1 for pain, stiffness, and function, resp.; all ). Figures 3(a) and 3(b) show the time by treatment interaction for WOMAC pain and WOMAC function, respectively. An analysis for the active group over time showed that the improvement in all three categories was maintained throughout the study (Figure 4(a)). The improvements in pain and function in the WOMAC questionnaires qualified as a clinical response to treatment according to the Outcome Measures in Rheumatology Clinical Trials (OMERACT)-Osteoarthritis Research Society International (OARSI) set of responder criteria. These are an improvement in either pain or function of at least fifty percent with a decrease of 2.0 cm on a VAS or an improvement in both pain and function of at least twenty percent with a decrease of 1.0 cm on a VAS [29]. The results of pain and function in the WOMAC questionnaires in the present study meet both these clinical improvement criteria since the changes in pain and function were greater than 50% and greater than 2.0 cm on the VAS. A significant difference between the active and control groups was also found in ALF score at the two-year endpoint ( ; Table 2). The two groups did not differ significantly in their improvement over time ( for interaction =0.67; ; Figure 3(c)). The analysis of the active group over time showed that the improvement in ALF score in the active group was maintained throughout the study (Figure 4(b)). At the two-year endpoint, a significant difference was found between groups in all categories of the SF-36 except for the category of emotional well-being. This is reflected in the two summary indices of the SF-36: the SF-36 PCS and SF-36 MCS ( , , resp.; Table 3). There was a significant difference in improvement over time between groups in the SF-36 PCS ( for interaction =5.8; ; Figure 3(c)) but not in the SF-36 MCS ( for interaction =0.032; ). At the two-year endpoint, a significant difference was found between groups in the KSS-K and the KSS-F ( , , resp.; Table 3). The two groups also differed significantly in their improvement over time in the KSS-K ( for interaction =4.3; ) and the KSS-F ( for interaction =6.5; ; Figure 3(d)). The analysis of the active group over time showed that the improvement in both outcomes was maintained for the rest of the study period. Patients treated with the biomechanical therapy showed greater improvements at the study endpoint in all the study outcomes, as well as greater improvement over time in most of the study outcomes. Interestingly, the results of the ALF test showed that the groups did not show a significant difference in improvement over time. This suggests that the control group may have improved in function over the two years, but not to the extent of the active group. The changes in function in the control group may be due to other therapies that this group used during the study period. Since the control group was not examined as often as the active group, another explanation may be that the control group did not improve in function, but rather that the study was not strong enough at finding the difference in improvement over time between groups. The groups also differed in the number of total knee replacements (TKRs) performed after two years in each group. One patient from the active group required a TKR during the study period (2.6%), while 5 patients (31%) of the control group required a TKR during the two-year study period. The TKR was documented through our follow-up phone calls to the patients over time. The procedures were performed at various medical centers throughout the country where the individual was referred to surgery. The type of prosthetic was not documented for the purposes of the present study. The previous study showed that the improvements in the active group were still rising at the eight-week endpoint. The results of the present study at six months were only slightly higher than the results after eight weeks that were seen in the previous study. From six months to the end of the study, the improvements remained stable. This suggests that the majority of improvements with the biomechanical therapy are achieved within the first eight weeks of therapy. Furthermore, these improvements remain stable as long as treatment is maintained. The present study also supports the results of a previous study by Elbaz et al. [17] that also evaluated this biomechanical therapy. Their study showed that patients with knee OA treated with the therapy reported improvements in pain, function and quality of life as demonstrated by self-evaluation questionnaires [17]. Their study, however, evaluated patients over only twelve weeks of therapy and did not incorporate a control group. Researchers have presented several theories explaining how this therapy may reduce pain and improve function in patients with OA of the knee. Several studies by Haim et al. showed that the device used in this therapy can unload the diseased articular surface of the joint with knee OA and thereby reduce pain. This was witnessed in the current study in that immediately after calibration patients reported diminished pain or no pain while using the biomechanical device. By reducing pain, the therapy gives the patients the ability to train without pain. Over time the therapy may allow the patient to regain strength, function, and lower pain levels. The therapy may also reduce pain and improve function by educating the neuromuscular system of these patients to walk in a less pathological manner [17]. Motor learning in the human body is a complicated task and must be incorporated in a graded and controlled fashion, with multiple repetitions within a functional context [12]. Fitzgerald et al. [11] showed that this could be accomplished through perturbation during repetitive actions [11]. The therapy used in the present study uses COP manipulation to realign the limb towards a normal biomechanical alignment while minimizing any preexisting pain. By combining the changes in alignment with perturbation and repetition over time, the therapy may educate the neuromuscular system to acquire the ability to walk in the new alignment, which in turn allows the patient to walk in the new gait pattern even when the biomechanical device is removed. As a therapy, the biomechanical intervention also showed high compliance over the course of two years. This may be due to the fact that the actual therapy was very easy to apply to patients. The patients also reported ease in using the device since they only had to wear the device while walking in their regular environment or while carrying out simple chores. There were several limitations to the present study. Firstly, in contrast to our previous study, the present study was unblended, and the two groups were not randomized. Nevertheless, the two groups were equal at the baseline in terms of patient characteristics and clinical outcomes. Secondly, due to the study logistics, the control group could only be asked to arrive for a follow-up exam at two year without evaluations before then. This limits our knowledge of how this group faired over time. There are several ways in which the study could have been improved. The study could have attempted to discontinue treatment with the device to see if the improvements are maintained without therapy. This addition to the study could allow researchers to determine if and when the therapy can be terminated. This may test whether the patients acquired a new action that they will maintain on their own or whether the patients need continuous training to maintain their new gait patterns. The present study could also benefits from spatiotemporal, kinetic, and kinematic gait analyses of the patients over time when the treatment device is removed. This could help determine which, if any, changes in gait the body’s motor learning system is able to acquire from therapy. The present study shows that patients with knee OA treated with AposTherapy over time demonstrate a significant reduction in pain and a significant improvement in function and quality of life. These improvements peak after eight weeks of therapy and remain stable for two years as long as treatment is maintained. The authors thank Gilad Fruchter PT for assistance in applying the therapy to all the patients and Nira Koren-Morag, Ph.D., for statistical assistance. This study was not funded in any way.

      מחקר ישראלי מגלה את ההשפעה של נעלי אפוס על כאבי מפרקים כרוניים

      02:58
    • PubMed Central (PMC)

      מחקר מקיף: מה בריא יותר בטווח הארוך - ריצה או הליכה?

      To test whether equivalent energy expenditure by moderate-intensity (e.g., walking) and vigorous-intensity exercise (e.g., running) provides equivalent health benefits. We used the National Runners’ (n=33,060) and Walkers’ (n=15,945) Health Study cohorts to examine the effect of differences in exercise mode and thereby exercise intensity on coronary heart disease (CHD) risk factors. Baseline expenditure (METhr/d) was compared to self-reported, physician-diagnosed incident hypertension, hypercholesterolemia, diabetes and CHD during 6.2 years follow-up. Running significantly decreased the risks for incident hypertension by 4.2% (P<10-7), hypercholesterolemia by 4.3% (P<10-14), diabetes by 12.1% (P<10-5), and CHD by 4.5% per METh/d run (P=0.05). The corresponding reductions for walking were 7.2% (P<10-6), 7.0% (P<10-8), 12.3% (P<10-4), and 9.3% (P=0.01). Relative to <1.8 METh/d, the risk reductions for 1.8 to 3.6, 3.6 to 5.4, 5.4 to 7.2, and ≥ 7.2 METh/d were: 1) 10.1%, 17.7%, 25.1% and 34.9% from running and 14.0%, 23.8%, 21.8% and 38.3% from walking for hypercholesterolemia; 2) 19.7%, 19.4%, 26.8% and 39.8% from running and 14.7%, 19.1%, 23.6% and 13.3% from walking for hypertension; 3) 43.5%, 44.1%, 47.7% and 68.2% from running and 34.1%, 44.2%, and 23.6% from walking for diabetes (too few cases for diabetes for walking >5.4 METh/d). The risk reductions were not significantly greater for running than walking for diabetes (P=0.94) or CHD (P=0.26), and only marginally greater for walking than running for hypertension (P=0.06) and hypercholesterolemia (P=0.04). Equivalent energy expenditures by moderate (walking) and vigorous (running) exercise produced similar risk reductions for hypertension, hypercholesterolemia, diabetes, and CHD, but there is limited statistical power to evaluate CHD conclusively. Adjustment for BMI attenuated more of the risk reduction for the runners’ than walkers’ hypertension, hypercholesterolemia, and diabetes, Current physical activity guidelines postulate that different activities can be combined to achieve a minimum recommended dose, including activities of different intensities [1-7]. Activities that expend 3- to 6-fold the energy expenditure of sitting at rest (3 to 6 metabolic equivalents or METs, 1 MET=3.5 ml O2•kg-1•min-1) are defined as moderate, those that expend more as vigorous, and less as light intensity [1]. Walking is generally performed at moderate intensity [8] and is specifically recommended by the Centers for Disease Control [1], the American Heart Association [2], the American College of Sports Medicine [1], and others [6,7], but whether equivalent doses of moderate and vigorous physical activity yield the same long-term health benefits remains unresolved [9]. The current analyses examined whether equivalent energy expenditure by moderate and vigorous exercise produce similar reductions in coronary heart disease (CHD) risk factors. To this end, we examined the associations of incident hypertension, hypercholesterolemia (high cholesterol), and type 2 diabetes mellitis to reported exercise in two cohorts, the National Runners’ Health Study II and the National Walkers’ Health Study. Walking and running provide an ideal test of the health benefits of moderate-intensity versus vigorous-intensity exercise because they involve the same muscle groups. In addition, the National Runners’ and Walkers’ Health Studies assess running and walking energy expenditure from weekly distance run or walked, which appears to be a better metric than the traditional time-based measurements used by other studies [10-12]. The National Runners’ Health Study II and the National Walkers’ Health Study were started in 1998 and 1999, respectively, to examine the relationships between various amounts and intensity of physical activity in a large national cohort of 63,308 runners and 42,140 walkers. The original cohorts were partially resurveyed in 2006 to establish a population of approximately 50,000 runners and walkers for a proposed clinical trial, rather than a prospective follow-up study per se. These represented approximately a third of the original walker (33.2%), and one-half of the original runner surveyed (51.7%). The difference in recruitment rates was due to the greater effort made to recruit runners (two mailings) than walkers (one mailing). Compared to non-responders, those that responded were slightly more likely to be female, younger, slightly less educated, weighed slightly more, were less likely to report taking medications for blood pressure, hypertension, or diabetes at baseline, but reported approximately the same number of km/day run if a runner or walked if a walker as reported on their baseline questionnaire [35]. Participants completed baseline and follow-up questionnaires on height, current and past weight, diet, current and past cigarette use, and history of diseases. Intakes of meat and fruit were based on the questions “During an average week, how many servings of beef, lamb, or pork do you eat”, and “...pieces of fruit do you eat”. Alcohol intake was estimated from the corresponding questions for 4-oz (112 mL) glasses of wine, 12-oz (336 mL) bottles of beer, and mixed drinks and liqueurs. Alcohol was computed as 10.8 g/4-oz glass of wine, 13.2 g/12-oz bottle of beer, and 15.1 g/mixed drink. Education was solicited by requesting the participant provide “years of education (examples: HS=12; BS or BA = 16; MS or MA = 18; PhD or MD = 20).” Height and weight were determined by asking the participant, “What is your current height (in inches, without shoes)?” and, “What is your current weight (pre-pregnancy weight if pregnant)?” BMI was calculated as weight in kilograms divided by the square of height in meters. Elsewhere, we have reported the strong correlations between self-reported and clinically measured heights (r=0.96) and weights (r=0.96) [11]. The study protocol was reviewed by the University of California Berkeley committee for the protection of human subjects, and all subjects provided a signed statement of informed consent. Walking and running were reported in miles per week. In addition, the questionnaires asked how many hours per week on average did respondents spend running, walking, swimming, cycling, and doing other exercises which they described in detail. They were also asked for their usual pace (minutes per mile) during walking and running. Time based calculations of METhr/d of vigorous, moderate, and light exercise were summed as the product of average daily hours spent on each activity and the activity's estimated energy expenditure [8]. The distance-based calculation of METhr/d walked converted distance into duration (i.e., distance/mph) and calculated the product of the average hours walked per day and the MET value for the reported pace. Running MET values were calculated as 1.02 MET•h per km [11]. Time-based calculation of METhr/d run was computed by converting the hours run into distance (i.e., hours*kmph). New onset or ”incident” hypertension, hypercholesterolemia, diabetes, and CHD (myocardial infarction, coronary artery bypass graphs (CABG), percutaneous coronary intervention, and angina pectoris) were defined as physician diagnosis or starting medications for these conditions since the baseline questionnaire. Self-reported hypertension and hypercholesterolemia have been demonstrated as consistent by repeated surveys and reliable as confirmed by medical records [13] and have been used by the Nurses’ Health Study [14] and other major cohort studies [15]. Statistical analyses were performed using JMP (SAS institute, Cary NC, version 5.1) and Stata (StataCorp LP, College Station TX, version 11). Cox proportional hazard analyses were used to estimate the hazard rate per METhr/d of running, walking, and other vigorous, moderate, and light intensity exercise. There were 15,945 walkers (21.0% males), and 33,060 runners (51.4% males) eligible for analysis (Table 1 ). Baseline hypertension, hypercholesterolemia and diabetes excluded 3,271 walkers and 1,841 runners, 2,638 walkers and 2,148 runners, 716 walkers and 249 runners from the analyses of incident hypertension, hypercholesterolemia and diabetes, respectively. Energy expended by running in the runners was more than twice that reported for walking by walkers. The majority of the other exercise reported by runners and walkers was vigorous. The runners had 38% lower risk for incident hypertension, 36% lower risk for hypercholesterolemia, and 71% lower risk for diabetes mellitis than walkers (Table 2 ). These differences were independent of the reported exercise energy expenditure, but were substantially reduced by adjustment for BMI, i.e., to 14%, 18%, and 41% lower risk for hypertension, hypercholesterolemia, and diabetes, respectively (Table 3 ). Hazard ratios (95% confidence intervals) from Cox proportional hazard analyses of self-reported incident hypertension, hypercholesterolemia, diabetes and CHD. Analyses of runners and walkers combined adjusted for baseline age (age, age2), sex, and race (self identified African-American, Hispanic, Asian, Native American), education, smoking, and intakes of red meat, fruit, and alcohol. Analyses of hypertension, hypercholesterolemia, and diabetes also included adjustment for preexisting CHD at baseline. Significance levels for individual coefficients are coded: Covariates for adjustment included baseline age (age, age2), sex, and race (self identified African-American, Hispanic, Asian, Native American), education, smoking, and intakes of red meat, fruit, and alcohol. Analyses of hypertension, hypercholesterolemia, and diabetes also included adjustment for preexisting CHD at baseline. Significance levels for individual coefficients are coded Equivalent energy spent running and walking was associated with comparable risk reductions for hypertension, hypercholesterolemia, and diabetes mellitis (Figure 1 ). Moreover, there were incremental reductions in risk at 2, 3, and 4-times the dose of exercise recommended by the American Heart Association and the American College of Sports Medicine [2]. Table 2 shows that greater METhr/d run or walked was associated with significantly lower risks, respectively, for incident hypertension (P<10-7 and P<10-6), hypercholesterolemia (P<10-14 and P<10-8), and diabetes (P<10-5 and P<10-4). The risk reductions per METhr/d were not significantly greater for running than walking for hypertension (running vs. walking, P=0.06), hypercholesterolemia (P=0.04, significantly greater for walking not running), or diabetes mellitis (P=0.94). The equivalent benefits per METhr/d run and METhr/d walked persisted even after adjustment for BMI for hypertension (running vs. walking: P=0.54) and hypercholesterolemia (P=0.56), but not for diabetes (running > walking, P=0.01, Table 3 ). Reduction in the risks for hypertension, hypercholesterolemia, and diabetes vs. baseline METhr/d energy expended by walking or running. Energy expenditure (X-axis) is categorized in terms of the upper limit of the minimum recommended physical activity levels (750 METmin/wk=1.8 METhr/d [2]), e.g., 1 to 2-fold higher activity covers from 1.8 to 3.6 METhr/d, etc. The average energy expended by runners and walkers within each interval were 314 and 371 METmin/wk for <1-fold of the recommended levels (<1.8 METhr/d), respectively, 1208 and 1108 METmin/wk for 1 to 2-fold (1.8 to 3.6 METhr/d), respectively, 1927 and 1845 METmin/wk for 2- to 3-fold (3.6 to 5.4 METhr/d), respectively, 2684 and 2587 METmin/wk for 3- to 4-fold (5.4 to 7.2 METhr/d), respectively, and 4197 and 3436 METmin/wk for ≥4-fold (≥7.2 METhr/d). Analyses performed separately in runners and walkers, adjusted for age, sex, race, smoking, prior CHD, and intakes of red meat, fruit, and alcohol. Incident diabetes in walkers excluded for 3- to 4-fold and ≥4-fold due to the small number of cases. Error bars represent 95% confidence intervals. Significant levels relative to the least active runners and walkers coded: * P<0.05; † P<0.01, ‡ P<0.001, and § P<0.0001. Higher levels of nonrunning vigorous exercises were also associated with lower risks of hypertension (P=0.003) and hypercholesterolemia (P=0.0008), but not diabetes (P=0.16). The METhr/d reductions in risk were significantly less for nonrunning vigorous exercise than for running for hypertension: (running - other vigorous exercise: P=0.006), hypercholesterolemia (P<10-4) and diabetes (P=0.0006). Other moderate exercise was not significantly related to hypertension (P=0.72), hypercholesterolemia (P=0.79), or diabetes mellitis (P=0.72), and its risk reduction was significantly less than that of walking (walking-other moderate exercise, hypertension: P=0.0002; hypercholesterolemia: P<10-5; and diabetes: P=0.03). Whereas METhr/d for walking and running were calculated from distance and intensity, METhr/d for other exercises were calculated from time (duration) and intensity. In part, the weak effects of other exercise may be due to its method of estimation rather than the activities themselves. To show that time-based energy estimation underestimates the association of exercise with incident hypertension, hypercholesterolemia, and diabetes, the analyses of Table 2 were repeated for METhr/d run as calculated from reported time and intensity (not displayed), rather than distance (Table 2 ). This shows that the reductions in risk per METhr/d run were much less for the time-based than the distance-based calculations (52% less for hypertension, 29% less for hypercholesterolemia, and 63% less for diabetes mellitis, analyses not displayed). When the time-based METhr/d run and distance-based METhr/d run were included together in the same survival model so that their coefficient could be compared directly, the distance based estimates remained significant (hazard ratio, hypertension: HR=0.961, P=0.0001; hypercholesterolemia: HR=0.963, P=10-6; and diabetes: HR=0.876, P=0.0002), whereas the time-based estimates were not (hypertension: HR=0.997, P=0.68; hypercholesterolemia: HR=0.994, P=0.25; and diabetes: HR=1.003, P=0.88), and in every case the risk reduction for the distance-based estimate was significantly greater than that of the time-based estimate (hypertension: P=0.01; hypercholesterolemia: P=0.007; and diabetes: P=0.008). Thus, time-based estimates of exercise energy expenditure appear to substantially underestimate the reductions in hypertension, hypercholesterolemia, and diabetes risk. When METhr/d of strengthening and non-strengthening exercises replaced other exercise in the analyses of Table 2 , the effects of strengthening exercises and nonstrengthening exercise did not differ significantly from each other for incident hypertension (P=0.08), hypercholesterolemia (P=0.21), or diabetes (P=0.13). Specifically, the per METh/d effect of strengthening exercise was modestly significant for hypercholesterolemia (HR=0.973, 95%CI: 0.949 to 0.998, P=0.03) and diabetes (HR=0.902, 95%CI: 0.802 to 0.999, P=0.05), but not hypertension (HR=1.011, 95%CI: 0.982 to 1.040, P=0.49). Non-strengthening other exercise was significantly associated with hypertension (HR=0.983, 95%CI: 0.973 to 0.993, P=0.0007) and hypercholesterolemia risk (HR=0.990, 95%CI: 0.983 to 0.998, P=0.01), but not diabetes risk (HR=0.984, 95%CI: 0.957 to 1.009, P=0.21). Within both walkers and runners, faster pace (per m/s) was associated with lower risks of hypertension (runners: HR=0.609, 95%CI: 0.553 to 0.671, P<10-15; walkers: HR=0.758, 95%CI: 0.639 to 0.899, P=0.002), hypercholesterolemia (runners: HR= 0.667, 95%CI: 0.619 to 0.720, P<10-15; walkers: HR=0.823, 95%CI: 0.720 to 0.942, P=0.005), and diabetes (runners: HR= 0.433, 95%CI: 0.334 to 0.574, P<10-7; walkers: HR=0.427, 95%CI: 0.331 to 0.573, P<10-9), which were, for the most part, independent of exercise dose, but largely accounted for by BMI. There were no significant interactions between energy expended (METhr/d) and intensity (m/s) to suggest that the same energy expended at a faster pace produced a greater reduction in the risk of hypertension (significance of interaction, runners: P=0.13; walkers: P=0.33), hypercholesterolemia (runners: P=0.24; walkers: P=0.51) or diabetes (runners: P=0.98; walkers: P=0.71). The limited number of incident cases (530) provides limited statistical power for testing whether running and walking were associated with equivalent reductions in CHD risk. Nevertheless, the results were at least consistent with their equivalent effects per METhr/d. There were 706 walkers (442 males, 264 females) and 370 runners (337 males, 33 females) excluded for pre-existing CHD, leaving 189 de novo myocardial infarctions (102 walkers, 87 runners), 122 CABGs (68 walkers, 54 runners), 185 angioplasties (93 walkers, 92 runners), and 34 angina cases (19 walkers, 15 runners). The runners, as a group, had 52% lower CHD risk than the walkers (P<10-5, Table 2 ), which was diminished somewhat by adjustment for BMI (P=0.002, Table 3 ). Table 2 shows that both METhr/d run and METhr/d walked were associated with significantly lower CHD risk (P=0.05 and P=0.01, respectively), which did not differ from each other (P=0.26). The hazard ratios of Figure 2 are consistent with equivalent CHD risk reductions for walking and running. Reduction in CHD risks per METhr/d energy expended by walking or running. Error bars represent 95% confidence intervals. Significant levels relative to the least active runners and walkers coded: * P<0.05; † P<0.01, ‡ P<0.001, and § P<0.0001. Different recruitment rates between the runners (51.7%) and walkers (33.2%) did not affect the analyses. Repeating the analyses using only the first 33.2% of the runners recruited (to match the 33.2% recruitment rate in the walkers) produced results entirely consistent with the complete sample, namely: 1) there were significant declines per METh/d run in risk for hypertension (4.2% lower per METh/d run, 95%CI: 2.4% to 6.0% lower, P<10-5), hypercholesterolemia (3.8% lower per METh/d run, 95%CI: 2.5% to 5.2% lower, P<10-7), and diabetes (11.4% lower per METh/d run, 95%CI: 4.4% to 16.1% lower, P=0.001) whose differences from those of the walkers differed little from the complete sample (P=0.08, P=0.02, and P=0.60, respectively), 2) adjustment for BMI did not eliminate the decline in risk for hypertension (2.4% lower per METh/d run, 95%CI: 0.6% to 4.3% lower, P=0.01), hypercholesterolemia (2.8% lower per METh/d run, 95%CI: 1.4% to 4.1% lower, P=0.0001), and diabetes (6.9% lower per METh/d run, 95%CI: 0.6% to 12.8% lower, P=0.03), and 3) declines in CHD risk that were consistent with the complete sample (HR: 0.057, 95% CI: 0.906 to 1.008 per METh/d run, P=0.10). These results from these very large, prospective, cohorts suggest that equivalent doses of running (a vigorous exercise) and walking (a moderate exercise) are associated with equivalent reductions in the risks for new onset hypertension, hypercholesterolemia, and diabetes. These results also show continued reduction in risk for new onset hypertension, hypercholesterolemia and diabetes when the exercise-dose exceeds 450 to 750 MET minutes per week (1.1 to 1.8 METh/d), the amount of exertion currently recommended by the American Heart Association and the American College of Sports Medicine for health (Figure 1 ). Furthermore, it does not appear to matter whether these exercise doses are achieved by running or by walking. The equivalence of walking, the most commonly performed exercise, [16] and running has not to our knowledge been previously demonstrated prospectively in a large sample, nor has the dose-response relationship between walking and these endpoints been assessed prospectively over such a broad activity range. The additional health benefits of exceeding currently recommended exercise levels are consistent with cross-sectional data in runners and walkers [17,18]. The runners’ results showing increased benefit with increased running energy expenditure also provide confirmation in a new independent sample of a progressively beneficial dose-response relationship for this activity [19]. Activity in the present study was self-selected both with respect to the intensity, running vs walking, and the total exercise dose. The average exercise dose measured as estimated caloric expenditure was more than twice as great for those who chose running over those who chose walking. Specifically, there were substantially more walkers whose walking was at or below the guideline levels than runners whose running was at or below the guidelines (48.1% vs. 12.2%), and substantially fewer walkers than runners whose walking or running exceeded the guideline levels by 2-fold (15.4% vs. 61.1%), three fold (4.5% vs. 40.1%), and four fold (1.1% vs. 17.9%). This is likely due to the fact that runners can expend more calories in a given period of time. Our results suggest that this caloric expenditure is the key issue to reducing CHD risk factors and possibly CHD events. Clinical trials are required to settle the role of exercise intensity on CHD risk, but clinical trials are necessarily restricted by sample size and duration. Available clinical trials on the influence of exercise intensity on new onset blood pressure, cholesterol, and blood glucose control or insulin sensitivity have yielded mixed results. Both moderate and vigorous-intensity training improve blood pressure with approximately equal effects [20], albeit greater benefits have been ascribed to both moderate [21] and vigorous intensity [9]. The ability of exercise to lower total and low-density lipoprotein cholesterol is not widely accepted [20,22,23] irrespective of intensity and some maintain that any reduction in LDL is due to plasma volume expansion [24]. Our results suggest that exercise does affect LDL levels and that this effect increases with increasing exercise doses, consistent with the suggestion that LDL concentrations are more responsive to the exercise quantity than intensity [25]. Both moderate and vigorous exercise have been associated with lower risk of type 2 diabetes [20]; however, studies of blood glucose control tend to achieve significant improvement for vigorous more than moderate physical activity [9]. The benefits of walking, in particular, in lowering type 2 diabetes risk are well-documented [26]. Prospective epidemiologic studies tend to show a greater CHD-risk reduction for vigorous than moderate intensity exercise [20]; however, vigorous physical activity is more accurately reported than moderate-intensity exercise [27], which could contribute to its stronger relationship to CHD, hypertension, hypercholesterolemia, and diabetes when studied prospectively in epidemiologic cohorts [20]. This may be less of an issue for the analyses presented here, which compares two specific activities, running and walking, quantified by distance rather than duration. The superiority of vigorous over moderate exercise in some studies may simply reflect the fact that more calories can be expended per minute of activity with vigorous exercise. Consequently, when exercise is compared by time spent in activity, vigorous exercise appears more beneficial. This last point we believe to be of particular significance. In this paper we have shown that the effects of exercise on incident hypertension, hypercholesterolemia, and diabetes are at least two-fold greater when exercise energy expenditure calculated from distance than when exercise is measured by time. Similar results have been shown for using distance to assess energy expenditure cross-sectionally for body weight, hypertension, hypercholesterolemia, and diabetes [10-12] Presumably, deficiencies in time-based estimates of exercise energy expenditure apply to nonrunning and nonwalking activities as well, which may contribute to the significant differences between running and other vigorous exercise, and walking vs. other moderate exercise (Table 2 ). The superiority of the distance-based vs. time-based estimation of exercise energy expenditure has other important implications. If runners and walkers substantially overestimate exercise duration for a sustained activity, it is reasonable to assume even greater bias for unsustained activities by more-sedentary populations. Most epidemiological studies estimate exercise dose by time and intensity [20], which our analyses would suggest substantially underestimates the true health benefits of physical activity. Moreover, all public health recommendations prescribe physical activity by duration [1-7,20], and if people overestimate exercise by time, then implementing time-based recommendations may be problematic. The subsample included in this report is a sample of convenience, since it was recruited to obtain approximately 50,000 subjects to determine their interest in a possible internet-based intervention, and therefore represent only a portion of the original National Runners’ Health Study II and the National Walkers’ Health Study participants. It is unlikely, however, that the biological interaction of between exercise and hypertension, hypercholesterolemia, and diabetes is different between the current and less selected populations. We cannot exclude the possibility that subjects who exercise have lower innate risks for hypertension, hypercholesterolemia, diabetes, or CHD. We have shown that men with higher high-density lipoprotein cholesterol at baseline (a CHD protective factor [22]) run longer distances when randomized to exercise training [28,29], and others have shown that selective breeding for fitness in rats produces substantial inherited differences in CHD risk factors even in the absence of training [30]. Diet and other variables that could have affected our results were not collected. We doubt the possibility that lower rates of new onset hypertension, hypercholesterolemia, and diabetes with greater exercise levels was due to less medical care contact in the more active men because more vigorously active participants in the Health Professional Study had more frequent medical check-ups than less active men [31] and there was no difference in the frequency of routine medical check-ups by activity level in the Nurses Health Study [32]. Our results probably provide among the best available answers to the important public health question as to what intensity of exercise is required to reduce CHD risk. Our results suggest similar benefit for similar energy expenditures. These results should be used to encourage physical activity in general regardless of its intensity. However, those who choose running achieved over twice the exercise doses as those that choose walking, and given the strong dose-response relationship higher exercise doses and lower risk factors, promoting more vigorous exercise is likely to produce greater health benefits. Dr. Williams was responsible for the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, and approval of the manuscript. Dr. Thompson was responsible for preparation, review, and approval of the manuscript. Dr. Williams had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. This research was supported by grant HL094717 from the National Heart, Lung, and Blood Institute and was conducted at the Ernest Orlando Lawrence Berkeley National Laboratory (Department of Energy DE-AC03-76SF00098 to the University of California). National Center for Biotechnology Information, U.S. National Library of Medicine 8600 Rockville Pike , Bethesda MD , 20894 USA

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