A simple anthropometric estimation formula for healthy female labourers' leg volume.

BACKGROUND: Leg volume (LV) is an important reference in nutrition, physiology in exercise, or clinical diagnosis. Therefore, how to evaluate LV easily and quickly with accuracy is important in these areas. AIM: To develop a simple anthropometric estimation formula with ease of use and good accuracy for leg volume (LV) of female labourers. SUBJECTS: One hundred and thirty female labourers (110 subjects for formula regression procedure and 20 subjects for the comparison phase) were recruited as subjects with no reported leg surgery history, trauma, or deformity. METHODS: A set of 3 D scanners was used to measure the range data of each subject's leg. RESULTS: The resultant LV estimation formula is LV = 0.215 × LL × CTH1.620 with R2 = 0.967, in which LL stands for leg length and CTH for circumference of thigh. Mean error of this LV estimation is 0.10% and much smaller than that of the previous study (25.11% with significant difference). CONCLUSION: An anthropometric estimation formula for female labourers' leg volume was developed in this study. Estimation mean error of this formula is much smaller than the one in the previous study. This formula is easy to use and shows good accuracy in estimating female labourers' leg volume.

Can We Use Grip Strength to Predict Other Types of Hand Exertions? An Example of Manufacturing Industry Workers.

BACKGROUND: There are different types of hand motions in people's daily lives and working environments. However, testing duration increases as the types of hand motions increase to build a normative database. Long testing duration decreases the motivation of study participants. The purpose of this study is to propose models to predict pinch and press strength using grip strength. METHODS: One hundred ninety-eight healthy volunteers were recruited from the manufacturing industries in Central Taiwan. The five types of hand motions were grip, lateral pinch, palmar pinch, thumb press, and ball of thumb press. Stepwise multiple linear regression was used to explore the relationship between force type, gender, height, weight, age, and muscle strength. RESULTS: The prediction models developed according to the variable of the strength of the opposite hand are good for explaining variance (76.9-93.1%). Gender is the key demographic variable in the predicting models. Grip strength is not a good predictor of palmar pinch (adjusted-R2: 0.572-0.609), nor of thumb press and ball of thumb (adjusted-R2: 0.279-0.443). CONCLUSIONS: We recommend measuring the palmar pinch and ball of thumb strength and using them to predict the other two hand motions for convenience and time saving.

Body volume estimation equation for male laborers in Taiwan.

The purpose of this study was to develop a body volume (BV) estimation equation for male laborers in Taiwan with body weight (W) and stature height (H) as initial estimators. A three-dimensional (3D) body scanner and a 3D foot scanner were used to measure the 3D range data of 100 male laborers in this study. Subjects' BV was extracted from the 3D body model, and H and W were used as independent variables in regression analysis. The results show that the final BV estimation equation is BV = 1122.927 × W0.972, with R2 = 0.949. Thirty extra male subjects were scanned to compare this BV estimation equation with those in previous studies. The results show that this BV estimation equation had the smallest absolute mean difference at 1.1458 L and the smallest standard error of the estimate at 2.48% in comparison.

Normative Hand Strength of Healthcare Industry Workers in Central Taiwan.

Objectives: The purpose of this study is to establish the norms of hand grip strength in the healthcare industry in Taiwan and propose models to predict the strength of hand movement by regression with demographic and anthropometric factors. Methods: This is a cross-sectional study with a stratified convenience sample of workers in healthcare service industries in central Taiwan. Three hundred twenty-nine healthy subjects were recruited. Strength of different hand movement were tested three times in both hands and rests were given between tests. Results: Female strength of these hand movement was 59.1% to 73.0% that in males (p < 0.001). In general, the hand strength of male workers in the healthcare industry was less than that of male workers in the manufacturing industry (p < 0.001). In the prediction model, sex and weight played important roles in predicting hand strength. Conclusions: The norms of different types of hand strength was investigated the first time in workers in the healthcare industry in Taiwan. The tasks performed by healthcare personnel vary widely, and this variable should be considered in a future prediction model.

A Pilot Study of Five Types of Maximum Hand Strength among Manufacturing Industry Workers in Taiwan.

Background: The purpose of this study is to collect five types of maximum hand strength among workers in the manufacturing industry in Taiwan. Methods: This study is a cross sectional study with a stratified and convenient sample of workers on the production line in manufacturing industries in Central Taiwan. In total, we recruited 198 healthy subjects to participate in this study. Five types of hand strength were measured in both hands three times with 3 min rests between trials. Results: The strength of females for these five types of hand exertions were 52.0% to 67.6% of the strength of males (p < 0.001). For both genders, there was a main effect for the types of hand strength for the right hand (p < 0.001) and the left hand (p < 0.001). In general, the hand strength in U.S. and EU countries was 1.2 to 1.7 times greater than the strength among the three types of hand exertions in this study. Conclusion: These results can be used to evaluate the musculoskeletal burdens on the upper extremities in the manufacturing industry and could also be used for tool and job design and job modifications.

Foot surface area database and estimation formula.

The purpose of this study is to establish a foot surface area (FSA) database and estimation formula based on 3-D foot scan data. For each gender, 135 subjects stratified in five statures and three body weights were drawn. The foot was measured using a high-resolution 3-D foot scanner, of which the precision and accuracy is within 1%. The FSA was computed by the triangular mesh summation method and five 1-D foot measurements were extracted automatically to be used as candidate estimators for FSA estimation formula. The results of the FSA measurements are tabulated on fifteen strata for the Male, the Female and the Total (the two genders combined). The comparison of these FSA measurements with previous studies shows that previous studies underestimated the FSA approximately 4.06% for the Total (for the Male, 6.93%; for the Female, 0.82%). Regression analyses using these five 1-D foot measurements were performed. The results show that foot-length and ball-girth are effective estimators of FSA for the total (FSA=1.043 x foot-length x ball-girth, R(2)=95.4%). A test on the necessity of gender-specific formula indicated that no gender-specific formula is needed, and the formula for the total is good for both genders.