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1.
J Nutr Health Aging ; 11(4): 372-9, 2007.
Article in English | MEDLINE | ID: mdl-17653502

ABSTRACT

CONTEXT: Height is an important component of anthropometric assessment. Valid measures of height are difficult to obtain in the frail elderly. Equations to predict height, using knee height, were proposed for healthy but not for frail elderly. OBJECTIVE: The objectives of this study were to 1) develop and validate equations to predict height (measured and reported) in the frail elderly, 2) to verify the accuracy and reliability of equations, and 3) to compare predicted values with those predicted from existing equations for the healthy elderly. DESIGN AND SETTING: This is a secondary analysis of data from three cross-sectional studies and three randomized community trials in the Sherbrooke area, Quebec, Canada. PARTICIPANTS: Subjects (n=599) were Caucasian, aged 60 and over, and receiving community or Meals-on-Wheels services. ANALYSES: Variables associated with measured and reported heights were entered in multiple linear regression models (n = 409) to identify independent prediction factors. Reliability assessment and agreement analysis were performed with a sub-group of subjects (n=190). RESULTS: Knee height and age in men (R(2) = .718), and with the addition of weight and hip circumference in women (R(2) = .593), were identified as predictors of measured height. For reported height, knee height was a predictor in men (R(2) = .693), while weight was another predictor in women (R(2) = .540). These models predicted height just as well in the validation group (R(2) = .514 to .623). Errors of estimates ranged from +/- 3.31 cm to +/- 5.06 cm. Predicted values were closer to directly measured values in the frail elderly as compared to values obtained with equations in the healthy elderly which differed significantly. CONCLUSIONS: Equations were developed to predict measured and reported height in the frail elderly. These equations can be used when height cannot be measured directly or when postural problems (for measured height) or cognitive disorders (for reported height) can cause unreliable measurements.


Subject(s)
Anthropometry/methods , Body Height/physiology , Frail Elderly , Knee/anatomy & histology , Aged , Aged, 80 and over , Cross-Sectional Studies , Female , Humans , Male , Mathematics , Posture , Predictive Value of Tests , Regression Analysis , Reproducibility of Results , Sensitivity and Specificity , Sex Factors
2.
Disabil Rehabil ; 25(20): 1181-6, 2003 Oct 21.
Article in English | MEDLINE | ID: mdl-14534061

ABSTRACT

PURPOSE: Handgrip strength is necessary for performing activities of daily living, which, in turn, are required to maintain functional autonomy. The purpose of this study was to determine anthropometric and personal factors that affect handgrip strength in a group of free-living elderly at risk of malnutrition. METHOD: The factors associated with handgrip strength (Pearson r, t-test, alpha = 0.10) were entered in a multiple linear regression model (n = 166) to identify the independent prediction factors. Reliability of the model was verified with a sub-group of 65 subjects randomly selected from the initial sample. RESULTS: Both groups were statistically similar regarding all factors studied even though the validation group (n = 65) had more men (32%) compared to the development group (n = 166; 22%). Bivariate analyses showed that handgrip strength was associated with sex, age, pain, hand circumference, and waist-hip ratio. Multiple linear regression analysis identified age, pain, and sex as independent determinants of handgrip strength (R2 = 0.16). This model predicted handgrip strength better in the validation group (R2 = 0.29). CONCLUSIONS: As previously shown, women have a smaller handgrip strength than men. In addition, handgrip strength decreases with increasing age and the presence of pain. Emphasis should be placed on the importance of strategies to relieve pain in the free-living frail elderly population.


Subject(s)
Hand Strength/physiology , Malnutrition/physiopathology , Activities of Daily Living , Age Factors , Aged , Aged, 80 and over , Body Constitution/physiology , Female , Hand/anatomy & histology , Humans , Linear Models , Male , Pain/physiopathology , Regression Analysis , Risk , Sex Factors , Surveys and Questionnaires
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