Tomoko Aoyama

Habitual rowing exercise is associated with high physical fitness without affecting arterial stiffness in older men

Abstract The present study elucidated the effects of habitual rowing exercise on arterial stiffness and plasma levels of the vasoconstrictor endothelin-1 and the vasodilator nitric oxide (NO) in older men. Eleven rowers (68.0 ± 1.6 years) and 11 sedentary control older men (64.9 ± 1.1 years) were studied. Peak oxygen uptake (36.0 ± 1.7 vs. 27.7 ±1.9 ml · kg−1 · min−1), leg press power (1346 ± 99 vs. 1077 ± 68 W), and HDL-cholesterol (75 ± 5 vs. 58 ±3 mg · ml−1) were higher and triglyceride (78 ± 9 vs. 120 ± 14 mg · ml−1) was lower in rowers than in control participants (all P < 0.05). Arterial stiffness indices (carotid β-stiffness and cardio-ankle vascular index) and plasma endothelin-1 and NOx (nitrite + nitrate) levels did not differ between the two groups. These results suggest that habitual rowing exercise in older men is associated with high muscle power and aerobic capacity, and favourable blood lipid profile without affecting arterial stiffness or plasma levels of endotheline-1 and NO.

Does Cardiorespiratory Fitness Modify the Association between Birth Weight and Insulin Resistance in Adult Life

Objective Lower birth weight is associated with higher insulin resistance in later life. The aim of this study was to determine whether cardiorespiratory fitness modifies the association of birth weight with insulin resistance in adults. Methods The subjects were 379 Japanese individuals (137 males, 242 females) aged 20–64 years born after 1943. Insulin resistance was assessed using a homeostasis model assessment of insulin resistance (HOMA-IR), which is calculated from fasting blood glucose and insulin levels. Cardiorespiratory fitness (maximal oxygen uptake, VO2max) was assessed by a maximal graded exercise test on a cycle ergometer. Birth weight was reported according to the Maternal and Child Health Handbook records or the subject’s or his/her mother’s memory. Results The multiple linear regression analysis revealed that birth weight was inversely associated with HOMA-IR (β = −0.141, p = 0.003), even after adjustment for gender, age, current body mass index, mean blood pressure, triglycerides, HDL cholesterol, and smoking status. Further adjustments for VO2max made little difference in the relationship between birth weight and HOMA-IR (β = −0.148, p = 0.001), although VO2max (β = −0.376, p<0.001) was a stronger predictor of HOMA-IR than birth weight. Conclusions The results showed that the association of lower birth weight with higher insulin resistance was little modified by cardiorespiratory fitness in adult life. However, cardiorespiratory fitness was found to be a stronger predictor of insulin resistance than was birth weight, suggesting that increasing cardiorespiratory fitness may have a much more important role in preventing insulin resistance than an individual’s low birth weight.

Physical activity group classification algorithm using triaxial acceleration and heart rate.

As described in this paper, a physical activity classification algorithm is proposed for energy expenditure estimation. The proposed algorithm can improve the classification accuracy using both the triaxial acceleration and heart rate. The optimal classification also contributes to improvement of the accuracy of the energy expenditures estimation. The proposed algorithm employs three indices: the heart rate reserve (%HRreserve), the filtered triaxial acceleration, and the ratio of filtered and unfiltered acceleration. The percentage HRreserve is calculated using the heart rate at rest condition and the maximum heart rate, which is calculated using Karvonen Formula. Using these three indices, a decision tree is constructed to classify physical activities into five classes: sedentary, household, moderate (excluding locomotive), locomotive, and vigorous. Evaluation results show that the average classification accuracy for 21 activities is 91%.

Post-exercise ingestion of different amounts of protein affects plasma insulin concentration in humans

Abstract The synergistic stimulating effect of combined intake of carbohydrate and protein on plasma insulin concentration has been reported previously. However, it remains unclear whether the amount of protein ingested after exercise affects the concentrations of plasma insulin and amino acids. This study of trained men compared the effects of post-exercise co-ingestion of carbohydrate plus different amounts of whey protein hydrolysates (WPHs) with carbohydrate alone on (1) blood biochemical parameters of carbohydrate metabolism during the post-exercise phase, and (2) endurance performance. Eight trained men exercised continuously for 70 min. Immediately after exercise and 30, 60, 90, and 120 min later, the participants received supplements containing: (1) 17.5 g carbohydrate, (2) 3.0 g WPHs and 17.5 g carbohydrate (L-WPH), or (3) 8.0 g WPHs and 17.5 g carbohydrate (H-WPH). After a 2-h recovery period, the participants performed an endurance performance test. The concentrations of blood glucose were lower and plasma insulin significantly higher in the H-WPH trial compared with the carbohydrate trial. The concentrations of plasma amino acids were increased in a dose-dependent manner following ingestion of different amounts of WPHs with carbohydrate. Endurance performance was not significantly different between the three trials. Co-ingestion of carbohydrate and H-WPH was more effective than ingestion of carbohydrate alone for stimulating insulin secretion and increasing the availability of plasma amino acids. These results suggest that plasma concentrations of amino acids during the recovery period are determined by the amount of dietary protein ingested, and that it is necessary to increase the concentration of plasma amino acids above a certain level to stimulate insulin secretion.

Association between age at onset of independent walking and objectively measured sedentary behavior is mediated by moderate-to-vigorous physical activity in primary school children

Objective Age at onset of walking has been shown as an early predictor of physical activity in infants and children. However, little is known about whether age at onset of walking may predict sedentary behavior (SB). The aim of the present study was to examine the association between the timing of onset of walking and objectively measured SB, and whether this association is mediated by moderate-to-vigorous physical activity (MVPA) in children. Methods The subjects were 388 elementary school children aged 6–12 years. Current weight and height data were collected. Birth weight and the age in months the child first walked independently were reported based on the parents’ recall. Children’s SB and physical activity were objectively measured using a triaxial accelerometer (Active style Pro HJA-350IT, OMRON). The following summary outcome variables were derived from accelerometer data: Time (min/day) spent in SB (≤1.5 metabolic equivalents [METs]) and MVPA (≥3.0 METs). Results The mean ± SD time (min/day) spent in sedentary was 376 ± 62 and MVPA was 67.6 ± 20.8. Multiple linear regression analyses revealed that a later age at independent walking was associated with increased time spent in SB (β = 0.15, P < 0.001) and decreased time spent in MVPA (β = -0. 18, P < 0.001) after adjusting for gender, birth weight, current age, body weight, schools, and time spent wearing the accelerometer. When MVPA was introduced as a covariate in the model predicting SB, the association between the age at independent walking and time spent in SB was completely attenuated (β = 0.04, P = 0.215), while MVPA was significantly associated with SB (β = -0.61, P < 0.001). Conclusions Our results indicate that infants who walked at a later age spent more time in SB in childhood, and this association is mediated by MVPA. Appropriate interventions which focus on increasing MVPA and thereby reducing SB may be beneficial in infants who demonstrate a later age at onset of independent walking.

Estimating metabolic equivalents for activities in daily life using acceleration and heart rate in wearable devices

BackgroundHerein, an algorithm that can be used in wearable health monitoring devices to estimate metabolic equivalents (METs) based on physical activity intensity data, particularly for certain activities in daily life that make MET estimation difficult.ResultsEnergy expenditure data were obtained from 42 volunteers using indirect calorimetry, triaxial accelerations and heart rates. The proposed algorithm used the percentage of heart rate reserve (%HRR) and the acceleration signal from the wearable device to divide the data into a middle-intensity group and a high-intensity group (HIG). The two groups were defined in terms of estimated METs. Evaluation results revealed that the classification accuracy for both groups was higher than 91%. To further facilitate MET estimation, five multiple-regression models using different features were evaluated via leave-one-out cross-validation. Using this approach, all models showed significant improvements in mean absolute percentage error (MAPE) of METs in the HIG, which included stair ascent, and the maximum reduction in MAPE for HIG was 24% compared to the previous model (HJA-750), which demonstrated a 70.7% improvement ratio. The most suitable model for our purpose that utilized heart rate and filtered synthetic acceleration was selected and its estimation error trend was confirmed.ConclusionFor HIG, the MAPE recalculated by the most suitable model was 10.5%. The improvement ratio was 71.6% as compared to the previous model (HJA-750C). This result was almost identical to that obtained from leave-one-out cross-validation. This proposed algorithm revealed an improvement in estimation accuracy for activities in daily life; in particular, the results included estimated values associated with stair ascent, which has been a difficult activity to evaluate so far.