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INTRODUÇÃO: O pico de fluxo expiratório (PFE) é comumente usado para monitorar a progressão de doenças respiratórias, pois fornece boas informações sobre o estado das vias aéreas. Uma boa quantidade de pesquisas está sendo feita em todo o mundo para estabelecer uma equação de previsão local. A força-tarefa conjunta da Sociedade Torácica Americana e da Sociedade Respiratória Europeia promoveu pesquisas a esse respeito. Na Índia, os dados derivados da população caucasiana ainda são usados para o PFE. OBJETIVO: Estudar a relação dos parâmetros do PFE e os dados antropométricos como idade, altura, peso, índice de massa corporal (IMC), área de superfície corporal (ASC) e estabelecer uma equação de regressão para jovens adultos indianos. MÉTODOS: PFE foi feito em 1000 sujeitos de 15-25 anos da região metropolitana de Mumbai. O coeficiente de correlação de Pearson foi usado para entender a relação dos parâmetros antropométricos e PFE. A análise de regressão multivariada foi feita para estabelecer uma equação de predição. (Alfa 5%) RESULTADOS: Idade e todos os parâmetros antropométricos foram correlacionados com PFE. O pico de fluxo expiratório médio da população masculina foi de 515 ml / seg, enquanto a feminina foi de 399 ml / seg. Para o PFE, a maior correlação foi observada com a ASC seguida de altura, peso e idade, enquanto o IMC apresentou o menor coeficiente de correlação. TPFE teve a melhor significância com a idade, ASC, altura e IMC. Teve menos significado com o peso. No sexo feminino, a TPFE teve a melhor significância com altura, peso, IMC e idade. CONCLUSÃO: Existem diferenças de gênero na TPFE. Portanto, equações específicas de gênero são necessárias para a estimativa da TPFE
INTRODUCTION: Peak expiratory flow rate (PEFR) is commonly used to monitor the progression of respiratory diseases as it gives good information about the status of airways. A good amount of research is going across the world to establish a local prediction equation. The joint task force of the American thoracic society and European Respiratory Society has promoted research in this regard. In India, data derived from the Caucasian population are still used for PEFR. OBJECTIVE: To verify the relationship between PEF levels and the variables age, sex, anthropometric and body surface area, and establish the regression equation for young Indian adults. METHODS: A cross-sectional observational study was conducted in 15-25 years aged 1000 subjects from the Metropolitan region of Mumbai. Pearson's correlation coefficient was used to understand the relation of anthropometric parameters and PEFR. Multivariate regression analysis was done for establishing a prediction equation (Alpha 5%). RESULTS: Age and all anthropometric parameters were correlated with PEFR. The mean PEFR of the male population was 515 ml/sec, whereas, for females, it was 399 ml/sec, for PEFR highest correlation was observed with BSA (.696) followed by weight (.667), height (.630), age (.504) whereas BMI shown lowest correlation coefficient (.445). PEFR had the best significance with age, BSA, Height, and BMI. It had less significance with weight. In females, PEFR had the best significance with Height, weight, BMI, and Age. CONCLUSION: Gender-wise differences exist in PEFR. Hence gender-specific equations are needed for the estimation of PEFR.
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Peak Expiratory Flow Rate , Asthma , Young AdultABSTRACT
Objective Drug-resistant tuberculosis (TB) may be resistant to one or multiple anti-TB drugs.We used generalized estimation equations to analysis the risk factors of drug-resistant TB and provide information for the establishment of a warning model for these non-independent data.Methods The drug susceptibility test and questionnaire survey were performed in sputum positive TB patients from 30 anti TB drug-resistance surveillance sites in Zhejiang province.The generalized estimation model was established by the GENMOD module of SAS,with resistance to 13 kinds of anti-TB drugs as dependent variables and possible influencing factors,such as age,having insurance,HBV infection status,and history of anti-TB drug intake,as independent variables.Results In this study,the probability of drug resistance at baseline level was 20.26％.Age,insurance,whether being co-infected with HBV,and treatment history or treatment withdrawal were statistically significantly correlated with anti-TB drug resistance.The prediction equation was established according to the influence degree of the factors mentioned above on drug resistance.Conclusion The generalized estimation equations can effectively and robustly analyze the correlated binary outcomes,and thus provide more comprehensive information for drug resistance risk factor evaluation and warning model establishment.
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Objective Drug-resistant tuberculosis (TB) may be resistant to one or multiple anti-TB drugs.We used generalized estimation equations to analysis the risk factors of drug-resistant TB and provide information for the establishment of a warning model for these non-independent data.Methods The drug susceptibility test and questionnaire survey were performed in sputum positive TB patients from 30 anti TB drug-resistance surveillance sites in Zhejiang province.The generalized estimation model was established by the GENMOD module of SAS,with resistance to 13 kinds of anti-TB drugs as dependent variables and possible influencing factors,such as age,having insurance,HBV infection status,and history of anti-TB drug intake,as independent variables.Results In this study,the probability of drug resistance at baseline level was 20.26％.Age,insurance,whether being co-infected with HBV,and treatment history or treatment withdrawal were statistically significantly correlated with anti-TB drug resistance.The prediction equation was established according to the influence degree of the factors mentioned above on drug resistance.Conclusion The generalized estimation equations can effectively and robustly analyze the correlated binary outcomes,and thus provide more comprehensive information for drug resistance risk factor evaluation and warning model establishment.
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BACKGROUND: Little information is available on the validity of anthropometry or impedance-based equations for prediction of total body water (TBW) in African children. This study was designed to validate and develop equations to predict total body water in Cameroonian children. METHODS: TBW was measured by deuterium dilution in 102 children between 24 and 60 months of age and compared with the ones predicted by 5 anthropometric and 7 BIA equations. Multiple linear regression analysis was used to develop prediction equations for TBW from anthropometric parameters. RESULTS: Unacceptable discrepancies in the estimates of TBW at individual level were noted with all the equations tested. The following new anthropometry and BIA equations for the estimation of TBW were respectively developed: TBW = 6.488 + 0.434 × sex−0.039 × age + 0.670 × weight−0.081 × MUAC (cm)−0.372 × BMI (adjustedR2= 0.71,RMSE = 3.6), and TBW =−6.206 + 0.0037 × height2/Z−0.041 × age + 0.265 × weight + 0.1214 × height (adjustedR2=0.68, RMSE = 1.4). The cross-validation procedures revealed that the predicted values of TBW compared with measured values are accurate at a group level. CONCLUSION: The current published anthropometric and BIA equations are invalid for the estimation of TBW in Cameroonian preschool children. The newly developed anthropometry or BIA prediction equations are valid for use in Cameroonian children aged 2460 months
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Humans , Male , Female , Child, Preschool , Anthropometry/methods , Body Water/chemistry , Deuterium/analysis , Deuterium/pharmacokinetics , Electric ImpedanceABSTRACT
<p>Although it is common to assess visceral adipose tissue (VAT) by CT and MRI with a single slice at the umbilicus or the fourth and fifth lumbar vertebrae (L4-L5), recent studies reported that this single-slice method for determining an individual’s VAT may be inaccurate. Therefore, VAT accumulation should be based on total volume and determined with multiple slices rather than by cross-sectional area. However, obtaining multiple slices is burdensome for both subjects and analysts and lacks versatility despite its accuracy. The purpose of this study was to develop a new equation model for predicting VAT volume while maintaining the measurement accuracy of the multiple-slice method. We analyzed data from 214 Japanese male adults (48.5±9.3 years) and developed multiple, stepwise, linear regressions with VAT volume as a dependent variable and age, BMI, waist circumference and VAT areas (the standard L4-L5 measurement site 0 cm, +5 cm, +10 cm) as independent variables. From these results, we determined the best prediction equation for VAT volume as follows: VAT volume = (30.4×BMI) + (17.9×VAT area at L4-L5+10 cm) – 501.5. The model explained 93.1% of VAT variance and the predicted VAT volume significantly correlated with the measured VAT volume (r=0.97). This study developed a new VAT assessment method with a high level of accuracy. The method is significantly less burdensome in measurement and analysis than the multiple-slice method. Researchers can use this equation when they require an accurate evaluation of VAT accumulation. However, they should bear in mind that this equation was derived from data acquired from middle-aged, overweight and obese male subjects.</p>
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Objective To evaluate the accuracy of prediction equations in calculating energy expenditure in elderly patients with type 2 diabetes mellitus (T2DM).Methods In 75 elderly T2DM patients hospitalized in our hospital between August 2014 and August 2015,the resting energy expenditure (REE)measured with indirect calorimetry was compared with those calculated with six different prediction equations.Statistical analysis was performed with paired t-test,the percentage of individual coincidence,and BlandAltman method.Results The measured REE of the patients was (1 513.2 ± 240.6) kcal/d.There were statistically significant differences between the measured REE and the values predicted with Harris-Benedict,Owen,Mifflin,and Liu equations (all P ＜ 0.05),while no statistically significant differences were observed between the measured REE and the values predicted with FAO/WHO/UNU and Schofield equations (both P ＞0.05).FAO/WHO/UNU equation showed the smallest average difference from the measured value (-18.9 kcal/d),but the 95％ consistency limit (-363.3 kcal/d,325.5 kcal/d) was still beyond the acceptable clinical range.Conclusion The accuracy of prediction equations in estimating REE in elderly patients with T2DM may be dissatisfactory.
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OBJECTIVE: The primary aim of the study was to generate new prediction equations for the estimation of maxillary and mandibular canine and premolar widths based on mandibular incisors and first permanent molar widths. METHODS: A total of 2,340 calculations (768 based on the sum of mandibular incisor and first permanent molar widths, and 1,572 based on the maxillary and mandibular canine and premolar widths) were performed, and a digital stereomicroscope was used to derive the the digital models and measurements. Mesiodistal widths of maxillary and mandibular teeth were measured via scanned digital models. RESULTS: There was a strong positive correlation between the estimation of maxillary (r = 0.85994, r2 = 0.7395) and mandibular (r = 0.8708, r2 = 0.7582) canine and premolar widths. The intraclass correlation coefficients were statistically significant, and the coefficients were in the strong correlation range, with an average of 0.9. Linear regression analysis was used to establish prediction equations. Prediction equations were developed to estimate maxillary arches based on Y = 15.746 + 0.602 × sum of mandibular incisors and mandibular first permanent molar widths (sum of mandibular incisors [SMI] + molars), Y = 18.224 + 0.540 × (SMI + molars), and Y = 16.186 + 0.586 × (SMI + molars) for both genders, and to estimate mandibular arches the parameters used were Y = 16.391 + 0.564 × (SMI + molars), Y = 14.444 + 0.609 × (SMI + molars), and Y = 19.915 + 0.481 × (SMI + molars). CONCLUSIONS: These formulas will be helpful for orthodontic diagnosis and clinical treatment planning during the mixed dentition stage.
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Bicuspid , Dentition, Mixed , Diagnosis , Incisor , Linear Models , Molar , ToothABSTRACT
Background: PEF is a reasonably good measure of ventilatory function. It varies with various anthropometric parameters, geographical location of the subjects as well as various disease processes. Objective: To assess the relationship between PEF and certain selected anthropometric parameters and to devise prediction equation based upon these parameters. Materials and Methods: Three hundred healthy male adults in the age group of 18-60 years have been assessed for PEF using Wright Peak Flow Meter. Results: In the age group ≤ 40 years, PEF was on the average greater than in the age group > 40 years. Prediction equations were derived for PEF dependent on age and height in <40 age group and age and weight in >40 years age group. Conclusion: PEF appears to decline with advancing age, and to increase with height in younger subjects and weight in older subjects.
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OBJECTIVE: In the United States of America, 6.2 million individuals are using elliptical motion trainers in fitness centres. However, graded exercise test protocols to estimate peak oxygen consumption (VO2peak) using elliptical motion trainers have not been developed for the general population. METHODS: Fifty-nine subjects (mean age: 23.5 ± 4.1 years) were randomly divided into a validation (VAL: n = 39) or cross-validation (XVAL: n = 20) group. Peak oxygen consumption (ml×kg-1×min-1) was measured via indirect calorimetry on an elliptical motion trainer for both groups. Subjects exercised at 150 strides×min-1 against a resistance of four and a crossramp of 8%. The resistance was increased every two minutes by two units until exhaustion. For the VAL group, a stepwise regression analysis was used to predict VO2peak from resistance, maximal heart rate (HRmax), body mass index (BMI), height and gender (female = 0, male = 1). RESULTS: The prediction equation derived from this study was VO2peak (ml·kg-1·min-1) = 187.39403 + 12.97271 (gender) - 1.45311 (height) - 1.21604 (BMI) - 0.19613 (HRmax) + 1.57093 (resistance) (R² = 0.76, SEE = 4.47, p < 0.05). Using this equation, the predicted VO2peak of the XVAL group was 45.18 ± 6.42 ml·kg-1×min-1, while the measured VO2peak was 43.55 ± 6.23 ml·kg-1×min-1 CONCLUSION: No significant difference was found between the measured and predicted VO2peak in the XVAL group. Therefore, it appears this protocol and equation will allow individuals to accurately estimate their VO2peak without using direct calorimetry. However, future studies should investigate the validity of this protocol with diverse populations.
OBJETIVO: En los Estados Unidos de América, 6.2 millones de personas están utilizando actualmente entrenadores de movimiento elíptico en los gimnasios. Sin embargo, no se han desarrollado protocolos de pruebas de ejercicios graduados para la población general, con el fin de calcular el consumo máximo de oxígeno (VO2máx) usando entrenadores elípticos. MÉTODOS: Cincuenta y nueve sujetos (edad media: 23.5 ± 4.1 años) fueron divididos aleatoriamente en un grupo de validación (VAL: n = 39) y un grupo de validación cruzada (XVAL: n = 20) respectivamente. El consumo de oxígeno máximo (ml×kg-1×min-1) se midió mediante calorimetría indirecta en un entrenador de movimiento elíptico para ambos grupos. Los sujetos ejercitaron 150 pasos por minuto frente a una resistencia de cuatro y una rampa cruz de 8%. La resistencia fue aumentada cada dos minutos en dos unidades hasta la extenuación. Para el grupo VAL, se utilizó un análisis de regresión paso a paso para predecir el VO2máx de la resistencia, la frecuencia cardíaca máxima (FCmáx), el índice de masa corporal (IMC), la altura y el género (mujer = 0, hombre = 1). RESULTADOS: La ecuación de predicción derivada de este estudio fue VO2máx (ml·kg-1 min-1) = 187.39403 + 12.97271 (sexo) - 1.45311 (altura) - 1.21604 (IMC) - 0.19613 (FCmáx) + 1.57093 (resistencia) [R2 = 0.76, SEE = 4.47, p < 0.05]. Usando esta ecuación, la predicción en VO2máx para el grupo XVAL fue 45.18 ± 6.42 ml·kg-1 min-1, mientras que la medición de VO2máx fue 43.55 ± 6.23 ml·kg-1×min-1. CONCLUSIÓN: No se hallaron diferencias significativas entre los valores de la medición y la predicción de VO2máx en el grupo XVAL. Por lo tanto, se evidencia que este protocolo y esta ecuación permitirán a las personas calcular con precisión su VO2máx sin utilizar calorimetría directa. Sin embargo, los estudios futuros deben investigar la validez de este protocolo con distintas poblaciones.
Subject(s)
Humans , Male , Female , Adult , Young Adult , Oxygen Consumption/physiology , Exercise/physiology , Exercise Test/methods , Algorithms , Regression Analysis , Exercise Test/instrumentationABSTRACT
The aim of the present study was to examine the validation of prediction equation of basal metabolic rate (BMR) in Japanese female athletes. The study population consisted of 122 Japanese female athletes (age 20.2 ± 1.3 years, height 162.5 ± 6.3 cm, body weight (BW) 57.4 ± 7.7 kg, and fat-free mass (FFM) 45.5 ± 5.1 kg). Body composition was estimated by using air displacement plethysmography (BOD POD System). BMR was measured by indirect calorimetry using dougras bag tequnique, and predicted BMR was calculated from different equations based on FFM. When compared with measured BMR, predicted BMR from the equation of Taguchi et al. (BMR (kcal/day)= 26.9×FFM (kg)+ 36) and equation of Owen et al. were not significantly different. Whereas, predicted values from equation of Japan Institute of Sports Sciences, National Institute of Health and Nutrition and Cunningham were significantly different from measured value. Estimation error and Total error were smaller in equation of Taguchi et al. and Owen et al., however, equation of Owen et al. had a larger estimation error in the subjects who was small body size (less than 42kg) or large body size(more than 69kg). Furthermore, newer equation of Taguchi et al. (BMR=27.5×FFM+5) was developed from the pool data (n=205) in the present study. Standard error of estimation (SEE) of this equation was smaller than the equation of Taguchi et al., and systematic error was hardly observed.In conclusion, the newer equation of Taguchi et al. developed from measured BMR of Japanese female athletes was useful to predict BMR.
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The purpose of this study was to develop prediction models of sarcopenia in 1,894 Japanese men and women aged 18-85 years. Reference values for sarcopenia (skeletal muscle index, SMI; appendicular muscle mass/height2, kg/m2) in each sex were defined as values two standard deviations (2SD) below the gender-specific means of this study reference data for young adults aged 18-40 years. Reference values for predisposition to sarcopenia (PSa) in each gender were also defined as values one standard deviations (1SD) below. The subjects aged 41 years or older were randomly separated into 2 groups, a model development group and a validation group. Appendicular muscle mass was measured by DXA. The reference values of sarcopenia were 6.87 kg/m2 and 5.46 kg/m2, and those of PSa were 7.77 kg/m2 and 6.12 kg/m2. The subjects with sarcopenia and PSa aged 41 years or older were 1.7% and 28.8% in men and 2.7% and 20.7% in women. The whole body bone mineral density of PSa was significantly lower than in normal subjects. The handgrip strength of PSa was significantly lower than in normal subjects. Stepwise regression analysis indicated that the body mass index (BMI), waist circumference and age were independently associated with SMI in men; and BMI, handgrip strength and waist circumference were independently associated with SMI in women. The SMI prediction equations were applied to the validation group, and strong correlations were also observed between the DXA-measured and predicted SMI in men and women. This study proposed the reference values of sarcopenia in Japanese men and women. The prediction models of SMI using anthropometric measurement are valid for alternative DXA-measured SMI in Japanese adults.
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The purpose of this study was to develop prediction models of sarcopenia in 1,894 Japanese men and women aged 18-85 years. Reference values for sarcopenia (skeletal muscle index, SMI; appendicular muscle mass/height<sup>2</sup>, kg/m<sup>2</sup>) in each sex were defined as values two standard deviations (2SD) below the gender-specific means of this study reference data for young adults aged 18-40 years. Reference values for predisposition to sarcopenia (PSa) in each gender were also defined as values one standard deviations (1SD) below. The subjects aged 41 years or older were randomly separated into 2 groups, a model development group and a validation group. Appendicular muscle mass was measured by DXA. The reference values of sarcopenia were 6.87 kg/m<sup>2</sup> and 5.46 kg/m<sup>2</sup>, and those of PSa were 7.77 kg/m<sup>2</sup> and 6.12 kg/m<sup>2</sup>. The subjects with sarcopenia and PSa aged 41 years or older were 1.7% and 28.8% in men and 2.7% and 20.7% in women. The whole body bone mineral density of PSa was significantly lower than in normal subjects. The handgrip strength of PSa was significantly lower than in normal subjects. Stepwise regression analysis indicated that the body mass index (BMI), waist circumference and age were independently associated with SMI in men; and BMI, handgrip strength and waist circumference were independently associated with SMI in women. The SMI prediction equations were applied to the validation group, and strong correlations were also observed between the DXA-measured and predicted SMI in men and women. This study proposed the reference values of sarcopenia in Japanese men and women. The prediction models of SMI using anthropometric measurement are valid for alternative DXA-measured SMI in Japanese adults.
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Objective To establish lung function reference values and prediction equations in children and adolescents of the Han nationality in Heilongjiang province.Methods A survey in 588 healthy children and adolescents (292 males,296 females)aged 10 to 18 years old was carried out in Heilongjiang province in 2008.Eight flowvolume tests parameters were measured.Stepwise multiple regression was carried out to establish prediction equations for the parameters mentioned above.Results FVC and FEV1,were found,regardless of sex,to tend to go up with the increase of age(P ＜0.001).Beginning from the age of 14,male FVC and FEV1 became significantly higher than those of the female(P ＜0.001),the period of a fast increase of the male FVC and FEV1 taking place during the age of 13～14,while that of the female taking place in the age of 12 ～ 13,one age bracket earlier than the male.All lung volumes and flow rates,were found,regardless of sex,to tend to go up with the increase of age,height and weight(P ＜ 0.001).The regression equations of lung function were established.By comparison with the equations derived from our study and other authors' reports,it was found that the difference between measured data and predicted values from other authors was higher than those from our8.Conclusion Reference values and prediction equations for forced expiratory lung function applicable for children and adolescents of the Han nationality in Heilongiiang province were established.
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O presente estudo tem como objetivos: a) verificar a concordância entre os métodos da impedância bioelétrica (BIA) e da absortometria radiológica de dupla energia (DEXA), para a estimativa da massa muscular esquelética (MME); b) analisar o poder preditivo das variáveis antropométricas e de BIA para predição da MME em idosos. Foram avaliados 60 homens idosos (61 a 80 anos), residentes na região Sul do Brasil. Mensuraram-se as variáveis antropométricas (massa corporal e estatura), as variáveis de resistência e hidratação dos tecidos livres de gordura foram medidas pela técnica da BIA tetrapolar (Biodinamics - BF-310), realizou-se também um scan de corpo inteiro através da DEXA (LUNAR PRODIGY DF + 14319 Radiation e software 7.52.002 DPX-L). A diferença entre os métodos foi verificada pelo teste t, análise dos resíduos e o coeficiente de correlação. O valor preditivo das variáveis antropométricas e de BIA foi verificado pela regressão Linear Múltipla. Observou-se que a BIA superestimou em média 0,6 kg (dp= 1,59) a MME, quando comparada com a DEXA, contudo não houve diferença estatística (p<0,05). Foi observada uma forte relação entre os métodos (r=0,90; p<0,01). A análise de regressão demonstrou que a variável EST²/R explica 86 por cento da variação da MME, quando ajustada para massa corporal e idade e esta relação é independente das variáveis de gordura corporal, hidratação dos tecidos livres de gordura e IMC. Assim, nota-se que o método da BIA, aqui testado, é válido para a estimativa da MME em homens idosos e seus valores podem ser melhor preditos pelo modelo de regressão proposto a partir da medida de EST²/R ajustada para a massa corporal e idade.
The aim of the present study was twofold: a) to determine the agreement between bioelectrical impedance analysis (BIA) and dual energy X-ray absorptiometry (DEXA) for the estimation of skeletal muscle mass (SMM), and b) to analyze the predictive power of anthropometric variables and BIA for the prediction of SMM in the elderly. Sixty elderly men (61 to 80 years) from the southern region of Brazil were studied. Anthropometric variables (body weight and height) were measured, the resistance and hydration of fat-free tissues variables were determined by tetrapolar BIA (BF-310, Biodynamics). A whole body DEXA scan was also performed (Lunar Prodigy DF + 14319 Radiation and 7.52.002 DPX-L software). Differences between methods were analyzed using the t-test, analysis of residues and correlation coefficient. The predictive value of the anthropometric variables and BIA was evaluated by multiple linear regression. BIA overestimated SMM on average by 0.60 kg (sd=1.59) when compared to DEXA, however, no statistical difference was observed (p>0.05). There was a strong correlation between methods (r=0.90; p<0.01). Regression analysis demonstrated that the Ht²/R variable explained 86 percent of the variation in SMM when adjusted for body weight and age, and this relationship did not depend on body fat, hydration of fat-free tissues or BMI. Thus, BIA as tested here is a valid method for the estimation of SMM in elderly men and its values can be best predicted using the regression model proposed, which included Ht²/R adjusted for body weight and age.
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Humans , Female , Middle Aged , Aging , Body Composition , Densitometry , Electric Impedance , Muscle, SkeletalABSTRACT
O objetivo do presente estudo foi desenvolver uma equação para predição da carga de uma repetição máxima (1RM) em homens e mulheres, usando exclusivamente as características antropométricas. Participaram deste estudo 44 jovens de baixo risco, com experiência em treinamento de força, sendo 22 do sexo masculino (23 ± 4 anos, 76,6 ± 12,7kg, 173,9 ± 5,5cm, 11 ± 4,5 por cento de gordura) e 22 do feminino (22 ± 4 anos, 54 ± 6,0kg, 161 ± 5,8cm, 18 ± 2,2 por cento de gordura). Inicialmente, eles passaram por uma avaliação antropométrica seguida de um teste de 1RM de familiarização no exercício de desenvolvimento, que foi repetido após 48h. A repetibilidade do teste de 1RM foi testada pelo Wilcoxon matched paired test. Finalmente, a carga de 1RM foi modelada em função das variáveis antropométricas por regressão linear múltipla (forward stepwise) usando como critério de corte das variáveis independentes deltar² < 0,01. A confiabilidade dos modelos foi expressa pela análise de Bland e Altman. Adotou-se em todos os testes alfa = 0,05. Não se registraram diferenças entre teste e reteste, resultando em 44,6 ± 13,2kg e 12,2 ± 3,2kg nos indivíduos do sexo masculino (SM) e feminino (SF), respectivamente. Além das variáveis antropométricas, incluiu-se aos modelos o tempo de experiência em treinamento de força. No SM, o modelo resultou em 84 por cento da variância explicada, com erro padrão equivalente a 12 por cento. Por outro lado, no SF, a capacidade preditiva do modelo obtido foi mais fraca, resultando em 56 por cento da variância explicada e erro padrão equivalente a 20 por cento. Em conclusão, os modelos obtidos mostraram adequada confiabilidade, de forma que podem ser utilizados como ferramentas para predição da carga de 1RM.
The goal of the present study was to develop an equation for predicting the workload of one maximal repetition (1RM) in women and men, based exclusively on anthropometrical characteristics. Forty-four low-risk and experienced in strength training young subjects, being 22 male (23 ± 4 years, 76.6 ± 12.7 kg, 173.9 ± 5.5 cm, 11 ± 4.5 percent of body fat) and 22 female (22 ± 4 years, 54 ± 6.0 kg, 161 ± 5.8 cm, 18 ± 2.2 percent of body fat) volunteered for this study. All subjects were submitted to an anthropometrical evaluation followed by a 1RM familiarization test (shoulder press), which was repeated after 48h. The repeatability was tested using Wilcoxon Matched paired test. Finally, the 1RM workload was modeled in relation to the anthropometrical variables through multiple linear regression (forward stepwise) using as cutoff criteria for the independent variables deltar² < 0.01. The models reliability was expressed by the Bland and Altman analysis. All tests assumed alpha = 0.05. No significant differences were recorded between the two tests, resulting 44.6 ± 13.2 kg and 12.2 ± 3.2kg, for male (MS) and female (FS) subjects respectively. The time of practice in strength training was also included in the models. The model resulted in 84 percent of explained variance and a standard error of 12 percent for the MS. On the other hand, for the FS the predictive capacity was weaker than for = the MS, resulting in 56 percent of the explained variance and a standard error of 20 percent. In conclusion, the obtained models showed acceptable reliability so that they can be currently used as a tool for predicting the 1RM workload.
El objetivo del presente estudio ha sido desarrollar una ecuación para predecir la carga de una repetición máxima (1RM) en hombres y mujeres, usando exclusivamente las características antropométricas. Participaron de este estudio 44 jóvenes de bajo riesgo, con experiencia en entrenamiento de fuerza, 22 del sexo masculino (23 ± 4 años, 76,6 ± 12,7 kg, 173,9 ± 5,5 cm, 11 ± 4,5 por ciento de grasa) y 22 del sexo femenino (22 ± 4 años, 54 ± 6,0 kg, 161 ± 5,8 cm, 18 ± 2,2 por ciento de grasa). Al inicio, estos pasaron por una evaluación antropométrica seguida de un test de 1RM de familiarización en el ejercicio en desarrollo, que fue repetido después de 48 h. La repetibilidad del test de 1RM fue probada por Wilcoxon matched paired test. Finalmente la carga de 1RM fue modelada en función de las variables antropométricas por regresión lineal múltiple (forward stepwise) usando como criterio de aglomeración de las variables independientes deltar² < 0,01. La confiabilidad de los modelos se expresó por el análisis de Bland y Altman. En todos los tests se adoptó alfa = 0,05. No se registraron diferencias entre el test y el retest, resultando en 44,6 ± 13,2 kg y 12,2 ± 3,2kg en los individuos del sexo masculino (SM) y femenino (SF), respectivamente. Fuera de las variables antropométricas, se incluyó a los modelos el tiempo de experiencia en la actividad de fuerza. En el SM, el modelo resultó en 84 por ciento de la varianza explicada, con un error padrón equivalente a 12 por ciento. Por otro lado, en el SF, la capacidad predictiva del modelo obtenido no fue tan eficaz, resultando en 56 por ciento de la varianza explicada y un error padrón equivalente a 20 por ciento. En conclusión, los modelos obtenidos mostraron adecuada confiabilidad, de forma que pueden ser utilizados como herramientas para predecir la carga de 1RM.
Subject(s)
Humans , Male , Female , Young Adult , Body Composition , Exercise , Forecasting , Muscle Strength , Resistance TrainingABSTRACT
BACKGROUND: In order to treat obese individuals, control of caloric intake after determination of patient's energy expenditure and recommendation of exercise program with possible use of specific medication is advised. There are many limitations in measuring all individuals energy expenditure by calorimetry, thus estimation is made using many variables such as weight, height, age, and gender. But, commonly used equations to predict resting energy expenditure(REE) are thought to result in overestimation of energy expenditure for use with obese individuals. This study investigated difference between measured and predicted resting energy expenditure in obese individuals. METHODS: Subjects were 133 adults who were admitted either to Internal Medicine Department and ENT Department of Yeung Nam University Hospital and their resting energy expenditure was measured by indirect calorimetry. According to age, sex, smoking habits and body mass index, Measured REE by indirect calorimetry between groups was compared. Predicted REE estimated by 6 equations to measured REE was compared in the two groups by body mass index 27kg/m2 under 65 years old individuals. RESULTS: There was no significant difference of measured REE between groups according to smoking habits(p>0.05). In the older group(> or =65 years old), REE was lower compared to the younger groups(27kg/m2) measured REE was higher than the normal weight group(BMI<27kg/m2)(p<0.05). Among 108 individuals under 65 years old, other equation except for Fleish equation and Robertson and Reid equation were inaccurate when applied to the obese group. CONCLUSIONS: These commonly used prediction equations tend to overestimate the REE in obese individuals, and the best estimates for the obese seem to be derived from the Fleish and Robertson and Reid equations.
Subject(s)
Adult , Aged , Humans , Body Mass Index , Calorimetry , Calorimetry, Indirect , Energy Intake , Energy Metabolism , Internal Medicine , Obesity , Smoke , SmokingABSTRACT
OBJECTIVES: Changes in lung function are frequently used as biological markers to assess the health effects of criteria air pollutants. We tried to formulate the prediction models of pulmonary functions based on height, weight, age and gender, especially for children aged 12 years who are commonly selected for the study of health effects of the air pollution. METHODS: The target pulmonary function parameters were forced vital capacity(FVC) and forced expiratory volume in one second(FEV1). Two hundreds and fifity-eight male and 301 female 12-year old children were included in the analysis after excluding unsatisfactory tests to the criteria recommended by American Thoracic Sosiety and excluding more or less than 20% predicted value by previous prediction equations. The weight prediction equation using height as a independent variable was calculated, and then the difference of observed weight and predicted weight (i.e. residual) was used as the independent variable of pulmonary function prediction equations with height. RESULTS: The prediction equations of FVC and FEV1 for male are FVC(ml) = 50.84 x height(cm) + 7.06 x weight residual - 4838.86, FEV1(ml) = 43.57 x height(cm) + 3.16 x weight residual - 4156.66, respectively. The prediction equations of FVC and FEV1 for female are FVC(ml) = 42.57 x height(cm) + 12.50 x weight residual - 3862.39, FEV1(ml) = 36.29 x height(cm) + 7.74 x weight residual - 3200.94, respectively.
Subject(s)
Child , Female , Humans , Male , Air Pollutants , Air Pollution , Biomarkers , Forced Expiratory Volume , LungABSTRACT
This study was carried out in order to determine soft tissue response to incisor movement and mandibular repositioning and to determine feasibility of predicting vertical and horizontal changes in soft tissue with hard tissue movement. For this study, cephalometric records of 41 orthodontically treated adult females who had Angle's Class II division 1 malocclusion were selected and stepwise multiple regression analysis was employed. Following conclusions were obtained by analysing the changes of soft tissue and hard tissue before and after treatment. 1. Hard tissue measurements that showed significant changes before and after treatment were horizontal and angular changes of maxillary incisor, horizontal,vertical and angular changes of mandibular incisor, overjet, overbite, interincisal angle, mandibular repositioning, A,B, skeletal convexity and soft tissue measurements that showed significant changes were horizontal, thickness and angular changes of upper lip, horizontal and angular changes of lower lip, interlabial angle, nasolabial angle labiomental angle, Sri, Ss, Si and soft tissue convexity(P<0.05). 2. All Soft tissue measurements changed significantly before and after treatment had between one and four hard tissue independent variables at statistically significant level, indicating that all soft tissue changes were direct relationship with hard tissue changes 3. Ova jet, horizontal change of maxillary incisor, horizontal change of maxillary root apex and horizontal change of pogonion entered into prediction equations most frequentely indicating that they were more significant variables in prediction of vertical and horizontal changes in the soft tissue with treatment, but vertical changes of mandibular incisor not entered any prediction equations, indicating that it was not considered a good predictor for soft tissue changes with maxillary incisor retraction. 4. Horizontal and vertical changes in subnasale were found to have most independent variables, significant at the 0.05 level in prediction-equations(deltaSn(H): Ur, Is(H), Pg(H), UIA,deltaSn(V): Is(H), Pg(H), overjet, A), indicating that subnasale changes are influenced by complex hard tissue interaction. 5. Multiple correlation coefficient(R2) of the soft tissue prediction equations ranges from 0.2-0.6.
Subject(s)
Adult , Female , Humans , Incisor , Lip , Malocclusion , Overbite , OvumABSTRACT
The purpose of this study was to investigate activity fitness of daily living of elderly women in Korea. The subjects were 253 elderly women ranging in age from 65 to 84 years. Twenty items related to the activity fitness of daily living were measured. The Pearson's correlation coefficients between the performance test items and age were significant (<I>P</I><0.05) and the score of all items remarkably decreased with advancing age. In order to extract activity fitness of daily living, the principal component analysis was applied to the 20×20 correlation matrix. The first principal component was interpreted as fundamental activity fitness (FAF) of daily living. The results of the comparison clearly indicated that the 75-79 and 80-84 age groups were inferior in FAF of daily living. Furthermore, in order to analyze the factorial structure of these elderly women, extracted factors were rotated with normal varimax criterion. The activity fitness (AF) of daily living were categorized to 7 factors : muscular strength and movement of the whole body, flexibility, balance, coordination of upper limbs, agility of upper and lower limbs, endurance, and reaction time. Results of the comparison of AF factors showed that a decline with advancing age was significant for muscular strength and movement of the whole body. The prediction equations of FAF were developed using multiple regression analyses. Results indicated that 8 selected items from 7 factors were significant predictors of the dependent variable FAF. Equally clarified was that 3 of our 8 items could be excluded, while still yielding comparable precision in predicting FAF. On the basis of all our analyses and considering the practicability of the measurement, we recommend the equation FAFS=1.504 X<SUB>1</SUB>-0.838 X<SUB>2</SUB>-0.489 X<SUB>3</SUB>-0.363 X<SUB>4</SUB>-0.686 X<SUB>5</SUB>+68.71, with an R=0.850; where FAFS=fundamental activity fitness score, X<SUB>1</SUB>=arm curl, X<SUB>2</SUB> walking around two chairs in a figure 8, X<SUB>3</SUB>=one foot tapping in a sitting position, X<SUB>4</SUB>=sit and reach, X<SUB>5</SUB> carrying beans using chopsticks, which can predict FAF with high precision in elderly Korean women.
ABSTRACT
Objective To prospectively study the relation between transforming growth factor beta-1 (TGF-?_1), V_(20) and lung function (PFTs) and radiation pneumonia (RP), as well as to set up a prediction model of RP. Methods From Jan 2004 to Dec 2005, 121 valid patients with esophageal carcinoma or lung cancer were treated with conventional thorax radiotherapy(RT) by 15 MV X-ray beams to a total D_T 60-68 Gy over 30-34 fractions in 42-46 days. All patients received chest CT scanning before RT. Dose volume his- togram(DVH) and V_(20) were obtained through 3-dimensional TPS. Serum TGF-?_1 and PFTs of the patients were measured both before and after RT as well as on the 20th day after the beginning of RT. RP was diag- nosed basing on contrasted CT and clinical symptoms. Results RP was diagnosed in 32 of all 121 pa- tients. The results of Logistic Regression Statistic showed that V_(20) and TGF-?_1 ratio (after RT/before RT) significantly influenced the incidence of RP. Patients with V_(20)≥30% had more RP than patients with V_(20)