“…The SenseWear Armband was positioned on the right arm, over the triceps muscle halfway between the acromion and the olecranon processes, as suggested by the manufacturer, at least two hours before the test. Previous studies have confirmed the validity and reproducibility of the SenseWear Armband measures of energy expenditure [11, 20–22]. …”
Section: Methodsmentioning
confidence: 63%
“…Further, walking also provides older persons with extensive benefits in terms of morbidity and mortality by controlling cardiovascular risk factors, by limiting the progressive loss of muscle mass and strength, by maintaining joint flexibility and bone resistance, and by stimulating more complex functions, such as balance and coordination, that are critical to prevent falls [9]. Unluckily, people walk progressively less with advancing age, even in the absence of clear-cut chronic functional impairments [8] and the habitual speed of walking also declines as a compensatory action aimed at offsetting the decline in walking metabolic efficiency [10, 11] and in cardiopulmonary capacity [12], both occurring with advancing age.…”
Background. Although walking has been extensively investigated in its biomechanical and physiological aspects, little is known on whether lower limb length and body proportions affect the energy cost of overground walking in older persons. Methods. We enrolled 50 men and 12 women aged 65 years and over, mean 69.1 ± SD 5.4, who at the end of their cardiac rehabilitation program performed the six-minute walk test while wearing a portable device for direct calorimetry and who walked a distance comparable to that of nondisabled community-dwelling older persons. Results. In the multivariable regression model (F = 12.75, P < 0.001, adjusted R2 = 0.278) the energy cost of overground walking, expressed as the net energy expenditure, in kg−1 sec−1, needed to provide own body mass with 1 joule kinetic energy, was inversely related to lower limb length and directly related to lower limb length to height ratio (β ± SE(β) = −3.72∗10−3 ± 0.74∗10−3, P < 0.001, and 6.61∗10−3 ± 2.14∗10−3, P = 0.003, resp.). Ancillary analyses also showed that, altogether, 1 cm increase in lower limb length reduced the energy cost of overground walking by 2.57% (95%CI 2.35–2.79). Conclusions. Lower limb length and body proportions actually affect the energy cost of overground walking in older persons.
“…The SenseWear Armband was positioned on the right arm, over the triceps muscle halfway between the acromion and the olecranon processes, as suggested by the manufacturer, at least two hours before the test. Previous studies have confirmed the validity and reproducibility of the SenseWear Armband measures of energy expenditure [11, 20–22]. …”
Section: Methodsmentioning
confidence: 63%
“…Further, walking also provides older persons with extensive benefits in terms of morbidity and mortality by controlling cardiovascular risk factors, by limiting the progressive loss of muscle mass and strength, by maintaining joint flexibility and bone resistance, and by stimulating more complex functions, such as balance and coordination, that are critical to prevent falls [9]. Unluckily, people walk progressively less with advancing age, even in the absence of clear-cut chronic functional impairments [8] and the habitual speed of walking also declines as a compensatory action aimed at offsetting the decline in walking metabolic efficiency [10, 11] and in cardiopulmonary capacity [12], both occurring with advancing age.…”
Background. Although walking has been extensively investigated in its biomechanical and physiological aspects, little is known on whether lower limb length and body proportions affect the energy cost of overground walking in older persons. Methods. We enrolled 50 men and 12 women aged 65 years and over, mean 69.1 ± SD 5.4, who at the end of their cardiac rehabilitation program performed the six-minute walk test while wearing a portable device for direct calorimetry and who walked a distance comparable to that of nondisabled community-dwelling older persons. Results. In the multivariable regression model (F = 12.75, P < 0.001, adjusted R2 = 0.278) the energy cost of overground walking, expressed as the net energy expenditure, in kg−1 sec−1, needed to provide own body mass with 1 joule kinetic energy, was inversely related to lower limb length and directly related to lower limb length to height ratio (β ± SE(β) = −3.72∗10−3 ± 0.74∗10−3, P < 0.001, and 6.61∗10−3 ± 2.14∗10−3, P = 0.003, resp.). Ancillary analyses also showed that, altogether, 1 cm increase in lower limb length reduced the energy cost of overground walking by 2.57% (95%CI 2.35–2.79). Conclusions. Lower limb length and body proportions actually affect the energy cost of overground walking in older persons.
“…Since older persons consume more metabolic energy than younger persons when walking it is a recommended type of physical activity that should be included in rehabilitation plans. [21] That almost half the respondents 65 years and older had reduces their physical activity after the AMI indicates that they were not aware of the significance of physical activity, and that they might think that this activity might be dangerous. Many adults, and particularly older women, lack ingrained exercise behaviour as a part of routine self-care.…”
Citation for the original published paper (version of record):Løvlien, M., Mundal, L., Hall-Lord, M-L. (2015) Physical activity in women after an acute myocardial infarction.. ABSTRACT Background: Physical activity is recognized as being important in reducing mortality after an acute myocardial infarction. The study aimed to describe younger and older women's leisure time physical activity after an acute myocardial infarction, their motivations and barriers for engaging in physical activity and to assess aspects associated with referral and attendance in cardiac rehabilitation programmes. Methods: Women diagnosed with an acute myocardial infarction were consecutively recruited and answered a questionnaire 2-3 months after hospital discharge.
Journal of Nursing Education andResults: The majority of the respondents (86%) were physically active after their acute myocardial infarction and 34% were physically active ≥ 4 days a week for ≥ 30 minutes. Respondents ≥ 66 years were less likely than respondents < 66 years to report moderate physical activity (39% vs. 58%, p = .03) and more likely to report low physical activity (27% vs. 8%, p < .01). No differences were found between these age groups reporting high physical activity (34% vs. 34%). Respondents ≥ 66 years were also less likely than younger respondents to maintain or increase their physical activity after the acute event (59% vs. 76%, p < .01), to be informed about the significance of physical activity while in hospital (61% vs. 80%, p = .01), to be referred to a cardiac rehabilitation programme (49% vs. 75%, p ≤ .01) and to attend such a programme (30% vs. 65%, p < .01). Conclusions: Women's age was associated with physical activity as well as their possibilities regarding cardiac rehabilitation after an acute myocardial infarction.
Objective Optimal metabolically healthy status is important to prevent various chronic diseases. This study investigated the association between lifelog-derived physical activity and metabolically healthy status. Methods This cross-sectional study included 51 Korean adults aged 30–40 years with no history of chronic diseases. Physical activity data were obtained by the International Physical Activity Questionnaire-Short Form (IPAQ-SF). Lifelog-derived physical activity was defined by step counts and walking speed for 1 week, as recorded by the Samsung Health application on both the Samsung Galaxy Fit2 and mobile phones. Participants without metabolic syndrome components were categorized as the metabolically healthy group ( n = 31) and the remaining participants as the metabolically unhealthy group ( n = 20). Prevalence ratios and 95% confidence intervals were estimated using Poisson regression models. The predictive ability of each physical activity measure was evaluated according to the area under the curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) values. Results Among the physical activity measures, lifelog-derived walking speed was significantly inversely associated with prevalent metabolically unhealthy status. The lifelog component model including walking speed, age, and sex had the highest AUC value for metabolically unhealthy status. Adding lifelog-derived step counts to the IPAQ-SF-derived metabolic equivalent (MET) model (including age, sex, and IPAQ-SF-METs) yielded 37% and 13% increases in the NRI and IDI values, respectively. Incorporating walking speed into the IPAQ-SF-derived MET model improved metabolically unhealthy status prediction by 42% and 21% in the NRI and IDI analyses, respectively. Conclusions Slow walking speed derived from the lifelog was associated with a higher prevalence of metabolically unhealthy status. Lifelog-derived physical activity information may aid in identifying individuals with metabolic abnormalities.
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