Normalized Hand Grip and Back Muscle Strength as Risk Factors for Incident Type 2 Diabetes Mellitus: 16 Years of Follow-Up in a Population-Based Cohort Study.

PURPOSE: Muscle strength is associated with type 2 diabetes mellitus (T2DM). However, it is controversial whether muscle strength and normalized muscle strength is a risk factor for T2DM. Moreover, the relationship of back muscle strength (BMS) and incident T2DM has not been reported. In this study, we investigated the relationship between HGS, BMS, normalized HGS and BMS, and incident T2DM. METHODS: A total of 2699 non-diabetes subjects aged 40-69 years (1313 women and 1386 men) in the Korean Genome and Epidemiology Study (KoGES) Ansan cohort were followed for 16 years. At the baseline and biennial follow-up visits, fasting glucose, postprandial 2-h glucose, clinical examinations, HGS, and BMS were measured by trained interviewers and examiners. HGS and BMS were measured at baseline. The relationships between incident T2DM, HGS, BMS, and normalized HGS and BMS were estimated using Cox proportional hazard regression models after adjusting for the confounding factors. RESULTS: HGS and BMS were not associated with incident T2DM in multivariate analysis. However, the hazard ratio (HR) per one standard deviation (SD) increase in the body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR)-normalized HGS, and BMS was associated with a lower risk for incident T2DM in both women and men after adjusting for the confounding factors (HR = 0.842-0.880-fold for women, p ≤ 0.015; HR = 0.887-0.903-fold for men, p ≤ 0.024). In the sub-analysis of menopause status, the HR per one SD increase in BMI, weight2/3, WC, and WHR-normalized HGS was associated with a lower risk for incident T2DM in both pre- and post-menopausal women after adjusting for the confounding factors (HR = 0.860-0.820-fold for premenopausal, P ≤ 0.006; HR = 0.900-0.867-fold for postmenopausal, p ≤ 0.024). Additionally, we confirmed that the quartile group with higher muscle strength was associated with a lower risk for incident T2DM. CONCLUSION: The present study suggested that normalized HGS and BMS were associated with a lower risk for the future development of T2DM. Moreover, weak muscle strength in premenopausal women may be the cause of T2DM. Further research is needed to determine whether efforts to improve muscle strength, such as exercise can reduce the risk of T2DM.

The Anthropometric Correlates for the Physiological Demand of Strength and Flexibility: A study in Young Indian Field Hockey Players.

INTRODUCTION: Optimal strength and flexibility are essential for performance enhancement and injury prevention in hockey, and anthropometry is known to influence these parameters. AIM: To find anthropometric correlates for strength and flexibility score in young Indian field hockey players. MATERIALS AND METHODS: Thirteen female and 19 male subjects volunteered for the study. Selected anthropometric variables: lengths, breadths, girths and body composition; strength and sit and reach score were measured for each subject. RESULTS: Males were taller, leaner and stronger with longer upper limbs and broader chests. With few exceptions, taller, heavier and leaner players with longer trunks and limbs, broader chest and hip, and bulkier arms and lower limbs had stronger grip, back, upper and lower limbs. Heavier and taller players with longer trunk and more percentage of body fat were more flexible. Also, the stronger players had more percentage body fat and body mass index, which might be due to the strong positive correlation of percentage body fat and body mass index with fat free mass. CONCLUSION: Anthropometric variables, especially heights, breadths and body composition, show significant correlation with strength and flexibility, and hence may serve as monitoring tool and for talent identification.

Reliability and validity of a custom-made instrument including a hand-held dynamometer for measuring trunk muscle strength.

BACKGROUND: Measuring isometric strength is necessary in many areas of health and sport. However, trunk muscles have some particular characteristics that make them difficult to evaluate with simple, inexpensive instruments. OBJECTIVE: To evaluate the reliability and validity of an instrument constructed with a hand-held dynamometer and a metallic structure (HHD+S) for measuring maximum isometric voluntary trunk muscle strength. METHODS: Maximum isometric voluntary trunk muscle strength (extension, flexion and lateral flexion) was measured in 20 healthy individuals using the custom-made instrument (HHD+S) and the gold standard Back-Check (BC). RESULTS: The results showed that the two instruments had high and similar intra-subject reliability. The validity of the HHD+S was demonstrated by the high Pearson coefficient correlation between the two instruments (r ⩾ 0.78). CONCLUSIONS: Given the good trial reliability and the close correlation between the two instruments, we believe that the use of a hand-held dynamometer together with the custom-made metallic structure (HHD+S) allows an evaluation of the maximum isometric voluntary trunk muscle strength to be made, that is very similar in quality, accuracy and reliability to the BC.

The relationship between health-related fitness and quality of life in postmenopausal women from Southern Taiwan.

BACKGROUND: Health-related fitness has been reported to be associated with improved quality of life (QoL) in the elderly. Health-related fitness is comprised of several dimensions that could be enhanced by specific training regimens. It has remained unclear how various dimensions of health-related fitness interact with QoL in postmenopausal women. OBJECTIVE: The purpose of the current study was to investigate the relationship between the dimensions of health-related fitness and QoL in elderly women. METHODS: A cohort of 408 postmenopausal women in a rural area of Taiwan was prospectively collected. Dimensions of health-related fitness, consisting of muscular strength, balance, cardiorespiratory endurance, flexibility, muscle endurance, and agility, were assessed. QoL was determined using the Short Form Health Survey (SF-36). Differences between age groups (stratified by decades) were calculated using a one-way analysis of variance (ANOVA) and multiple comparisons using a Scheffé test. A Spearman's correlation analysis was performed to examine differences between QoL and each dimension of fitness. Multiple linear regression with forced-entry procedure was performed to evaluate the effects of health-related fitness. A P-value of <0.05 was considered statistically significant. RESULTS: Age-related decreases in health-related fitness were shown for sit-ups, back strength, grip strength, side steps, trunk extension, and agility (P<0.05). An age-related decrease in QoL, specifically in physical functioning, role limitation due to physical problems, and physical component score, was also demonstrated (P<0.05). Multiple linear regression analyses demonstrated that back strength significantly contributed to the physical component of QoL (adjusted beta of 0.268 [P<0.05]). CONCLUSION: Back strength was positively correlated with the physical component of QoL among the examined dimensions of health-related fitness. Health-related fitness, as well as the physical component of QoL, declined with increasing age.

Stability Ball Training on Lower Back Strength has Greater Effect in Untrained Female Compared to Male.

The purpose of this study was to evaluate the effectiveness of short-term stability ball (SB) training on males and females by comparing the strength changes produced in the core muscles. Forty-two previously untrained subjects, mean age = 23.62 ± 2.89 years were matched by their maximum strength (back strength: male = 190-200 kg, female = 45-50 kg and abdominal strength: male = 110-120 kg, female = 35-40 kg 1RM) and randomly placed in either one of these 3 groups; unstable SB group (n = 14), stable floor group (n = 14) and control group (n = 14) who did no exercise. SB training showed greatest improvement (p < 0.001) in back and abdominal strength (25.79 % and 29.51 % respectively), compared with the gain in floor training (FT) back and abdominal strength (10.28 % and 8.47 % respectively). Untrained female subjects achieved a higher percentage of improvement in strength compared to males in both back and abdominal muscles, and this is most evident in the SB training group. It is apparent that performing core training exercises on unstable surfaces stressed the musculature, possibly activating the neuro-adaptive mechanisms that led to the early phase gains in strength.

ANALYSIS ON BACK STRENGTH ON GROWING STATE / 体力科学

1) Children's data (10-18 years old) of back strength, height, grip strength and running long jump from data book of Japan Education Ministry (1964-1981) were analyzed. Back strength was mainly studied and was compared with other data (grip strength etc.) . The groups with high average values for back strength at 10-14 years old did not necessarily show high values for back strength at 17 years old, or vice versa. Values for back strength at 10-14 years old were not significantly correlated with those at 17 years old.<BR>2) Using the data from data book mentioned above, tension of deep back muscle (FMUS) was calculated based on kinetic models (FMUS. I, II, III) . Calculated FMUS values were 3-5 times larger than measured back strength values at each age.<BR>3) Relative change of back strength and FMUS in 1964-1981 were compared. All values for back strength were lower than those for FMUS except in 1967. During the late 1960th and the 1970th, average back strength values gradully decreased, but the decrease of FMUS was less obvious than that of back strength.<BR>4) Based on the data of 422 children (7-12 years old, male and femele), values of diaphragm area were approximated with some assumptions, and then FMUS values were calculated. FMUS values calculated by approximate diaphragm area were significantly larger than those calculated by constant diaphragm area (465 cm2) .<BR>The figure for getting FMUS values easily was offered to avoid troublesome calculation. This consists of two graphs, and one can read FMUS values with reasonable precision. Parameters needed for getting FMUS values are sexuality, height, body weight and back strength.