Effects of 14 days of bed rest and following physical training on metabolic cost, mechanical work, and efficiency during walking in older and young healthy males
Abstract:In this study, we investigated: i) the effects of bed rest and a subsequent physical training program on metabolic cost (Cw), mechanical work and efficiency during walking in older and young men; ii) the mechanisms underlying the higher Cw observed in older than young men.Twenty-three healthy male subjects (N = 16 older adults, age 59.6±3.4 years; N = 7 young, age: 23.1±2.9 years) participated in this study. The subjects underwent 14 days of bed rest followed by two weeks of physical training (6 sessions). Cw,… Show more
“…Each of the circles is a mean GCoW value or a mean NCoW value from a selected study. The dashed straight lines (black and red) show the mean metabolic cost of a particular age-group for both GCoW and NCoW 40–56 .Figure 3Overview of the results of the meta-analysis using a random effects model on the differences in Gross Metabolic Cost of Walking between YA and OA . A positive Mean Difference ( MD ) means that OA have higher GCoW than YA .…”
Section: Resultsmentioning
confidence: 99%
“…Each of the circles is a mean GCoW value or a mean NCoW value from a selected study. The dashed straight lines (black and red) show the mean metabolic cost of a particular age-group for both GCoW and NCoW 40–56 .…”
The Metabolic Cost of Walking (
MCoW
) is an important variable of daily life that has been studied extensively. Several studies suggest that
MCoW
is higher in Older Adults (
OA
) than in Young Adults (
YA
). However, it is difficult to compare values across studies due to differences in the way
MCoW
was expressed, the units in which it was reported and the walking speed at which it was measured. To provide an overview of
MCoW
in
OA
and
YA
and to investigate the quantitative effect of age on
MCoW
, we have conducted a literature review and performed two meta-analyses. We extracted data on
MCoW
in healthy
YA
(18–41 years old) and healthy
OA
(≥59 years old) and calculated, if not already reported, the Gross (
GCoW
) and Net
MCoW
(
NCoW
) in J/kg/m. If studies reported
MCoW
measured at multiple speeds, we selected those values for
YA
and
OA
at which
MCoW
was minimal. All studies directly comparing
YA
and
OA
were selected for meta-analyses. From all studies reviewed, the average
GCoW
in
YA
was 3.4 ± 0.4 J/kg/m and 3.8 ± 0.4 J/kg/m in
OA
(~12% more in
OA
), and the average
NCoW
in
YA
was 2.4 ± 0.4 J/kg/m and 2.8 ± 0.5 J/kg/m in
OA
(~17% more in
OA
). Our meta-analyses indicated a statistically significant elevation of both
GCoW
and
NCoW
(p < 0.001) for
OA
. In terms of
GCoW
,
OA
expended about 0.3 J/kg/m more metabolic energy than
YA
and about 0.4 J/kg/m more metabolic energy than
YA
in terms of
NCoW
. Our study showed a statistically significant elevation in
MCoW
of
OA
over
YA
. However, from the literature it is unclear if this elevation is directly caused by age or due to an interaction between age and methodology. We recommend further research comparing
MCoW
in healthy
OA
and
YA
during “natural” over-ground walking and treadmill walking, after sufficient familiarization time.
“…Each of the circles is a mean GCoW value or a mean NCoW value from a selected study. The dashed straight lines (black and red) show the mean metabolic cost of a particular age-group for both GCoW and NCoW 40–56 .Figure 3Overview of the results of the meta-analysis using a random effects model on the differences in Gross Metabolic Cost of Walking between YA and OA . A positive Mean Difference ( MD ) means that OA have higher GCoW than YA .…”
Section: Resultsmentioning
confidence: 99%
“…Each of the circles is a mean GCoW value or a mean NCoW value from a selected study. The dashed straight lines (black and red) show the mean metabolic cost of a particular age-group for both GCoW and NCoW 40–56 .…”
The Metabolic Cost of Walking (
MCoW
) is an important variable of daily life that has been studied extensively. Several studies suggest that
MCoW
is higher in Older Adults (
OA
) than in Young Adults (
YA
). However, it is difficult to compare values across studies due to differences in the way
MCoW
was expressed, the units in which it was reported and the walking speed at which it was measured. To provide an overview of
MCoW
in
OA
and
YA
and to investigate the quantitative effect of age on
MCoW
, we have conducted a literature review and performed two meta-analyses. We extracted data on
MCoW
in healthy
YA
(18–41 years old) and healthy
OA
(≥59 years old) and calculated, if not already reported, the Gross (
GCoW
) and Net
MCoW
(
NCoW
) in J/kg/m. If studies reported
MCoW
measured at multiple speeds, we selected those values for
YA
and
OA
at which
MCoW
was minimal. All studies directly comparing
YA
and
OA
were selected for meta-analyses. From all studies reviewed, the average
GCoW
in
YA
was 3.4 ± 0.4 J/kg/m and 3.8 ± 0.4 J/kg/m in
OA
(~12% more in
OA
), and the average
NCoW
in
YA
was 2.4 ± 0.4 J/kg/m and 2.8 ± 0.5 J/kg/m in
OA
(~17% more in
OA
). Our meta-analyses indicated a statistically significant elevation of both
GCoW
and
NCoW
(p < 0.001) for
OA
. In terms of
GCoW
,
OA
expended about 0.3 J/kg/m more metabolic energy than
YA
and about 0.4 J/kg/m more metabolic energy than
YA
in terms of
NCoW
. Our study showed a statistically significant elevation in
MCoW
of
OA
over
YA
. However, from the literature it is unclear if this elevation is directly caused by age or due to an interaction between age and methodology. We recommend further research comparing
MCoW
in healthy
OA
and
YA
during “natural” over-ground walking and treadmill walking, after sufficient familiarization time.
“…Greater decrements, however, are observed in rapid muscle force capacity in older individuals, who also appear to have an impaired capability to fully recover following injuries [ 57 , 58 ]. A possible reason could be a higher co-contraction time of the antagonist lower limb muscles, a lower efficiency, and an uneven transmission of the forces within the fascicle compared to younger players [ 59 , 60 ]. In addition, the passing rate of the NHST in the current study was significantly lower among injured compared to non-injured players.…”
Hamstring injuries remain the most common injury type across many professional sports. Despite a variety of intervention strategies, its incidence in soccer players playing in the UEFA Champions League has increased by 4% per year over the last decade. Test batteries trying to identify potential risk factors have produced inconclusive results. The purpose of the current study was to prospectively record hamstring injuries, to investigate the incidence and characteristics of the injuries, and to identify possible risk factors in elite male soccer players, playing in the Kosovo national premier league. A total of 143 soccer players from 11 teams in Kosovo were recruited. To identify possible prevalent musculoskeletal or medical conditions a widespread health and fitness assessment was performed including isokinetic strength testing, Nordic hamstring strength test, functional tests, and a comprehensive anamnesis surveying previous hamstring injuries. On average 27.9% of the players sustained at least one hamstring injury with three players suffering bilateral strains with the re-injury rate being 23%. Injured players were significantly older and heavier and had a higher body mass index compared to non-injured ones (p < 0.05). There was a lower passing rate in the Nordic hamstring strength test and a higher injury incidence among the previously injured players compared to non-injured ones (p < 0.05). Except for hamstring/quadriceps ratio and relative torque at 60°/sec (p < 0.05) for dominant and non-dominant leg, there were no other significant differences in isokinetic strength regardless of the angular velocity. No differences were observed for functional tests between cohorts. Regression analysis revealed that age, Nordic hamstring strength test, previous injury history, and isokinetic concentric torque at 240°/sec could determine hamstring injuries by 25.9%, with no other significant predicting risk factors. The battery of laboratory and field-based tests performed during preseason to determine performance related skills showed limited diagnostic conclusiveness, making it difficult to detect players at risk for future hamstring injuries.
“…To meet the requirements of their club and sponsors, athletes often neglect certain phases of the training cycle. Reasons may vary and may include shorter resting periods, lack of awareness, or stress stemming, among other factors, from competition [4].…”
Introduction: Despite the positive aspects of taking up physical activity, sport, in general, is inseparably associated with injuries, as well as straining or overloading of the musculoskeletal system. The aim of this study was to determine the functional state and injuries among young athletes practicing crosscountry skiing. Material and methods: A total of 65 individuals participated in the study. The test group consisted of 33 individuals practicing crosscountry skiing, while the control group consisted of 32 persons not involved in this sport. The study was divided into two stages. The first stage consisted of a survey in which participants completed a personal questionnaire and were asked to answer 17 questions. Next, the Funtional Movement Screen (FMS) test was carried out in both groups using a specialty devised assessment form. Results: The assessment of the risk of injury in both groups was similar, no statistically significant differences were found in this respect (p = 0.992). No statistically relevant relation was between the number of injuries sustained and the training experience of individuals in the test group (p = 0.056). There was no statistically significant relationship between the number of sustained injuries and the training experience of individuals included in the test group (p = 0.056), although this relationship was close to the threshold of statistical significance. Conclusions: Crosscountry skiing training had no significant effect on musculoskeletal injuries. The FMS test result did not correlate with previously sustained injuries. Individuals who adopted preventive training schemes were less likely to sustain injuries.
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