Health-related fitness tests as predictors of difficulties in long-distance walking among high-functioning older adults.
OBJECTIVE
Health-related fitness (HRF) tests are valid predictors of self-reported mobility difficulties among high-functioning older adults. The aim of the present study was to identify optimal cut-off values for HRF tests predicting self-reported difficulties in walking 2 km (WD).


METHODS
Subjects were 55- to 69-year-old men and women who were free of WD at baseline. The HRF assessment in 1996 included seven test items, and postal questionnaires were used to assess occurrence of new WD in 2002. Analysis of covariance and receiver-operating characteristic analysis were used as statistical methods.


RESULTS
In a 1-km walk, the sensitivity and specificity at the optimal cut-off 10:15 (min:s) for men were 63% and 75%, and at the cut-off 10:47 for women 70% and 71%. In dynamic back extension, the sensitivity and specificity at the optimal cut-off 16.5 (repetitions) were 67% and 65% in men and 82% and 59% at cut-off 13.5 in women. Correspondingly, in backward walking, the sensitivity and specificity at the optimal cut-off 27.7 (seconds) were 65% and 69% in men and 74% and 61% at cutoff 35.0 in women.


CONCLUSIONS
The 1-km walk, dynamic back extension and backward walking tests had the best predictive value for WD. These tests, with identified cut-off values, can be used to screen individuals who are at increased risk of WD. Tests can also be used in physical activity counseling to target activity to those components of HRF that indicate poor fitness and are important for good walking ability.
Husu
Pauliina
P
UKK Institute for Health Promotion Research, FIN-33501 Tampere, Finland. pauliina.husu@uta.fi
Suni
Jaana
J
Pasanen
Matti
M
Miilunpalo
Seppo
S
D000368:Aged; D005080:Exercise Test / Q000592:standards*; D005260:Female; D005500:Follow-Up Studies; D006304:Health Status; D006801:Humans; D008297:Male; D008875:Middle Aged; D051346:Mobility Limitation; D011237:Predictive Value of Tests; D016138:Walking / Q000706:statistics & numerical data*