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Toshiki Ohta, Izumi Tabata and Yumiko Mochizuki

Edited by Wojtek J. Chodzko-Zajko

The Japanese National Physical Activity and Health Promotion Guidelines were compiled by the Ministry of Health and Welfare of Japan. A broad definition of physical activity was adopted in this report. Objectives of physical activity were (a) maintaining and promoting health, (b) preventing and treating disease, (c) reducing stress, (d) promoting development in childhood, (e) maintaining and improving independence in older people, (f) managing symptoms associated with menopause, and (g) promoting general psychological well-being.

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Toshiki Ohta, Izumi Tabata and Yumiko Mochizuki

Edited by Wojtek J. Chodzko-Zajko

The Japanese National Physical Activity and Health Promotion Guidelines were compiled by the Ministry of Health and Welfare of Japan. A broad definition of physical activity was adopted in this report. Objectives of physical activity were (a) maintaining and promoting health, (b) preventing and treating disease, (c) reducing stress, (d) promoting development in childhood, (e) maintaining and improving independence in older people, (f) managing symptoms associated with menopause, and (g) promoting general psychological well-being.

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Yuko Gando, Haruka Murakami, Ryoko Kawakami, Noriko Tanaka, Kiyoshi Sanada, Izumi Tabata, Mitsuru Higuchi and Motohiko Miyachi

Background:

It is unclear whether light physical activity is beneficially associated with insulin resistance, similar to moderate and/or vigorous physical activity. This cross-sectional study was performed to determine the relationship between the amount of light physical activity, as determined with a triaxial accelerometer, and insulin resistance.

Methods:

A total of 807 healthy men and women participated in this study. Physical activity was measured using a triaxial accelerometer worn for 28 days and summarized as light intensity (1.1–2.9 METs) or moderate to vigorous intensity (≥ 3.0 METs). Insulin resistance was evaluated by HOMA_R (FPG [mg/dL] × IRI [μU/mL]/405).

Results:

The daily time spent in light physical activity was inversely associated with HOMA_R (r = –0.173, P < 0.05). After adjustment for confounders, the association between light physical activity and HOMA_R remained statistically significant (β = –0.119, P < .05). Light physical activity remained significantly associated with HOMA_R following further adjustment for moderate to vigorous intensity activity (β = –0.125, P < .05). Similar results were observed when light physical activity was modeled as quartiles, especially in elderly women.

Conclusions:

These cross-sectional data suggest that light-intensity physical activity is beneficially associated with insulin resistance in elderly Japanese women.

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Zhen-Bo Cao, Taewoong Oh, Nobuyuki Miyatake, Kazuyo Tsushita, Mitsuru Higuchi and Izumi Tabata

Background:

This study aimed to determine the optimal number of steps per day needed to meet the current physical activity guidelines in a large population sample of Japanese adults.

Methods:

An accelerometer-based activity monitor (Kenz Lifecorder) was used to simultaneously measure moderate-to-vigorous intensity physical activity (MVPA) and step counts in 940 Japanese adults (480 women) aged 20 to 69 years. The step count per day equivalents to 2 different physical activity recommendations (23 MET-h/wk and 150 min/wk of MVPA) were derived using linear regression analysis and receiver operating characteristic (ROC) methodology.

Results:

Linear regression analysis showed that daily step counts correlated with weekly PAEE (r = .83) and daily minutes of MVPA (r = .83). Linear regression analysis also showed that 23 MET-h/wk of MVPA is equivalent to 11,160 steps/d, and 150 min/wk of MVPA is equivalent to 7716 steps/d. ROC analysis yielded similar findings: 10,225 steps/d are required to accumulate ≥ 23 MET-h/wk of MVPA and 7857 steps/d are needed to meet the recommendation of ≥ 150 min/wk of MVPA.

Conclusions:

The findings suggest that 10,000 to 11,000 and 7700 to 8000 steps/d represent the optimal thresholds for accumulating ≥ 23 MET-h/wk of MVPA and ≥ 150 min/wk of MVPA, respectively, for Japanese adults.

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Zhen-Bo Cao, Nobuyuki Miyatake, Tomoko Aoyama, Mitsuru Higuchi and Izumi Tabata

Background:

The purpose was to develop new maximal oxygen uptake (VO2max) prediction models using a perceptually regulated 3-minute walk test.

Methods:

VO2max was measured with a maximal incremental cycle test in 283 Japanese adults. A 3-minute walk test was conducted at a self-regulated intensity corresponding to ratings of perceived exertion (RPE) 13.

Results:

A 3-minute walk distance (3MWD) was significantly related to VO2max (r = .60, P < .001). Three prediction models were developed by multiple regression to estimate VO2max using data on gender, age, 3MWD, and either BMI [BMI model, multiple correlation coefficients (R) = .78, standard error of estimate (SEE) = 5.26 ml⋅kg-1⋅min-1], waist circumference (WC model, R = .80, SEE = 5.04 ml⋅kg-1⋅min-1), or body fat percentage (%Fat model, R = .84, SEE = 4.57 ml⋅kg-1⋅min-1), suggesting that the %Fat model is the best model [VO2max = 37.501 + 0.463 × Gender (0 = women, 1 = men) – 0.195 × Age – 0.589 × %Fat + 0.053 × 3MWD]. Cross-validation by using the predicted residual sum of squares (PRESS) procedures demonstrated a high level of cross-validity of all prediction models.

Conclusions:

The new VO2max prediction models are reasonably applicable to estimating VO2max in Japanese adults and represent a quick, low-risk, and convenient means for estimating VO2max in the field.

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Yuki Hikihara, Shigeho Tanaka, Kazunori Ohkawara, Kazuko Ishikawa-Takata and Izumi Tabata

Background:

The current study evaluated the validity of 3 commercially-available accelerometers to assess metabolic equivalent values (METs) during 12 activities.

Methods:

Thirty-three men and thirty-two women were enrolled in this study. The subjects performed 5 nonlocomotive activities and 7 locomotive movements. The Douglas bag method was used to gather expired air. The subjects also wore 3 hip accelerometers, a Lifecorder uniaxial accelerometer (LC), and 2 triaxial accelerometers (ActivTracer, AT; Actimarker, AM).

Results:

For nonlocomotive activities, the LC largely underestimated METs for all activities (20.3%–55.6%) except for desk work. The AT overestimated METs for desk work (11.3%) and hanging clothes (11.7%), but underestimated for vacuuming (2.3%). The AM underestimated METs for all nonlocomotive activities (8.0%–19.4%) except for hanging clothes (overestimated by 16.7%). The AT and AM errors were significant, but much smaller than the LC errors (23.2% for desk work and –22.3 to –55.6% for the other activities). For locomotive movements, the 3 accelerometers significantly underestimated METs for all activities except for climbing down stairs.

Conclusions:

We conclude that there were significant differences for most activities in 3 accelerometers. However, the AT, which uses separate equations for nonlocomotive and locomotive activities, was more accurate for nonlocomotive activities than the LC.