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The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 58:M715-M720 (2003)
© 2003 The Gerontological Society of America

Walking Performance and Cardiovascular Response: Associations With Age and Morbidity—The Health, Aging and Body Composition Study

Anne B. Newman1, Catherine L. Haggerty1, Stephen B. Kritchevsky2, Michael C. Nevitt3 and Eleanor M. Simonsick4, for the Health ABC Collaborative Research Group

1 Division of Geriatric Medicine, Department of Medicine, University of Pittsburgh, Pennsylvania.
2 Department of Preventive Medicine, University of Tennessee, Memphis.
3 Prevention Sciences Group, University of California, San Francisco.
4 Intramural Research Program, National Institute on Aging, Baltimore, Maryland.


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 References
 
Background. The long-distance corridor walk is a timed 400-meter walk test used to assess walking endurance in well-functioning men and women aged 70–79 in the Health, Aging and Body Composition Study.

Methods. We examined walking time along with heart rate and blood pressure response in relationship to prevalent chronic conditions, weight, physical activity, and markers of subclinical disease. Of 3075 participants, 2324 (76%) completed the test with heart rate and blood pressure responses in the range expected for a moderate level of exertion.

Results. Slower walking time was influenced by both clinical and subclinical disease, and also was strongly related to both low and high body weight and low self-reported physical activity. Heart rate and blood pressure responses were higher with several clinical and subclinical diseases, but heart rate response and recovery were more strongly related to walking time than to disease. Higher body mass index and lower physical activity were associated with greater heart rate response and recovery.

Conclusions. The independent contribution of both clinical and subclinical disease to walking time supports the use of walking tests as a summary measure of disease in older adults. The independent association of walking time with physical activity suggests that it is sensitive to levels of fitness as well. Together these findings show that walking performance is a valid indicator of physiologic reserve in older adults.

WALKING endurance tests are increasingly used to estimate exercise capacity in older adults (1–3). The 6-minute walk test was developed to assess treatment response in patients with congestive heart failure (4) and chronic obstructive pulmonary disease (5) as an alternative to treadmill testing in those unable to maintain pace and balance (6). The long-distance corridor walk test (LDCW) was developed as an alternative to the 6-minute walk in order to extend the testing range of self-paced walking tests in older adults. It is similar to the 6-minute walk except that, instead of holding the time walking constant, it holds a distance (400 m) constant (7). In a head-to-head comparison in elderly subjects, the LDCW was more reproducible and more closely associated with VO2 max than the 6-minute walk test (7).

We used the LDCW to assess walking endurance in a cohort of well-functioning older adults to describe function in the normal to exceptionally high range. We also assessed heart rate and blood pressure response to the test, since heart rate and heart rate recovery are predictive of cardiovascular disease and mortality (8,9), and blood pressure response reflects myocardial work and oxygen consumption (10–12). In this article, we describe the range of performance and cardiovascular response to this test and associations with health factors. We hypothesized that walking endurance and cardiovascular response would vary substantially with the extent of common chronic conditions and also with subclinical disease. We further hypothesized that these conditions might explain a lower performance in older, overweight, and inactive participants.


   METHODS
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 Abstract
 Methods
Results
 Discussion
 References
 
Population
The study population consisted of 3075 men and women aged 70–79 participating in the Health, Aging and Body Composition (Health ABC) study, designed to prospectively assess the impact of weight and health conditions on incident mobility limitation. Eligibility criteria included no reported difficulty with walking a quarter mile, climbing 10 steps, or performing activities of daily living. Those with life-threatening cancer or plans of leaving the area within 3 years were excluded.

Long-Distance Corridor Walk
Participants were asked to walk 400 meters after a 2-minute warm-up. The course consisted of 10 laps in a long hallway around cones set 20 meters apart (40 meters per lap) with instructions to walk "at a pace that you can maintain for the full 10 laps." Standard encouragement was given at each lap. Persons with baseline potentially acute electrocardiogram (ECG) abnormalities, elevated blood pressure (>=200/110 mmHg), resting heart rate >120 or <40 beats per minute (bpm), recent exacerbation of chest pain, shortness of breath, or reporting a recent cardiac event or procedure were excluded for safety reasons. Heart rate was monitored with a Polar Pacer heart monitor (Model No. 61190; Woodbury, NY). The test was stopped if heart rate exceeded 135 bpm or if a participant reported chest pain or dyspnea during the test. Heart rate was recorded at rest before starting the walk, at completion, and at recovery 2 minutes later (6). Systolic blood pressure (SBP) was measured while standing prior to the walk and at completion.

Demographics and Health
Age, gender, and race were assessed along with a detailed health history and medication inventory. Weight, height, and other anthropometrics, blood pressure, heart rate, pulmonary function testing, ECG, ankle–arm blood pressure index (AAI), oral glucose tolerance test, and assessments of strength and physical functioning were assessed, in addition to dual energy x-ray absorptiometry (DEXA) for bone density as well as total and regional body composition (13). Prevalent health conditions were determined by a combination of self-report and use of specific medications. Knee pain was considered to be consistent with osteoarthritis if reported to be present for at least 1 month of the past year. Noninvasive tests including the AAI of <0.9 (14), major but nonacute ECG abnormalities (15), pulmonary function (FEV1/FVC [forced expiratory volume/forced vital capacity] <70%) (16), fasting glucose >126 (17), blood pressure >140/90 (18), and a Center for Epidemiologic Studies–Depression (CES-D) score of >15 (19) were examined as indicators of subclinical disease and as independent predictors of function and were not used to define prevalent disease. Physical activity was calculated as total kilocalories from metabolic equivalents assigned to self-reported physical activities and exercise (20). Body mass index (BMI) was calculated as kg/m2, and total fat and bone-free lean mass were measured by DEXA scan (13) (Hologic, Waltham, MA).

Analysis
Participants who were excluded from the 400-meter walk, those starting but not completing, and those completing the walk were compared by analysis of variance (ANOVA) and the chi-square test of proportions. In those who completed the 400-meter walk, mean walk time, heart rate response, heart rate recovery, and SBP response were compared using ANOVA. Stepwise linear regression was used to model the predictors of 400-meter walk time, heart rate response, heart rate recovery, and SBP response. In one set of models, body composition (fat mass, bone-free lean mass) and height were substituted for BMI. Interactions with race and gender were evaluated, and none were significant.


   RESULTS
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 Abstract
 Methods
 Results
Discussion
 References
 
Of 3075 participants, 2680 (87%) were eligible for the test and 2324 (76%) completed the full 400 meters. Of the 2680 that started the test, 1.8% could not complete the 2-minute walk, 2.2% did not start the 400-meter walk, and 9.4% did not complete the full distance due to elevated heart rate or symptoms. Those who were excluded or did not complete the 400-meter walk were slightly older, had a higher BMI, were less physically active, and had a greater prevalence of several conditions, compared with those who completed the test (Table 1).


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  		Table 1. Characteristics of Health, Aging and Body Composition Study Participants Who Were Excluded From, Stopped, or Completed the Long-Distance Corridor Walk.

 
Participants completed the 400-meter walk, on average, in about 320 seconds (5 minutes and 20 seconds). Times were slower in each older age group (Table 2), in women, and in blacks. For each clinical condition, participants with the condition were slower than those without. Participants at the extremes of BMI had slower times, while those with higher physical activity had faster times. Participants with any subclinical disease marker were slower than those without. In a multivariate regression model (Table 3), age, female gender, black race, peripheral artery disease, stroke, knee pain, depression, AAI <0.9, major ECG abnormality, and an FEV1/FVC <70%, higher BMI, and lower physical activity were all independently associated with slower time. Even after adjustment, gender and race differences remained quite large, with women taking about 32 seconds longer, on average, than men, and blacks taking about 30 seconds longer than whites. The adjusted association with age was fairly small per year of age, but would indicate about 30 seconds slower time across the decade of age in this study.


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  		Table 2. Factors Associated With 400-Meter Walk Time in Bivariate Associations, Health, Aging and Body Composition Study.

 

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  		Table 3. Factors Associated With 400-Meter Walk Time: Multivariate Linear Regression, Health, Aging and Body Composition Study.

 
Analyses were repeated replacing BMI with body composition including total fat mass, bone-free lean mass, and height. In bivariate analyses, there was a direct relationship between time and both height and lean mass, such that taller individuals and those with more lean mass had faster times, and those at the extremes of fat mass had slower times. Moving average plots suggested that walk time was optimal at a percent fat range of 19%–27% in men and 28%–37% in women. In the final model, walk time was significantly and independently related to the square of fat mass but not height or lean mass. This did not alter the associations with clinical or subclinical disease, although the association with female gender was partly attenuated.

The SBP response to the test averaged about 16.4 mmHg in men and 17.7 mmHg in women (Table 4). Within the men, there was no association with race, while among women, blacks had a higher SBP response. The SBP response varied very little by presence or absence of each health condition. The largest increase was noted in diabetics, whose SBP rose on average 17.3 ± 21.1 mmHg during the test compared with 11.3 ± 19.3 mmHg in those without diabetes (p <.0001). SBP response was greater in each higher gender-specific quartile of BMI, ranging from 10.1 to 14.5 mmHg from lowest to highest quartile, p =.007. In a multivariate model (Table 5), stroke, diabetes, knee pain, BMI, AAI <0.9, and major ECG abnormalities were all independently associated with greater SBP response, but these factors explained only 5% of the variance. When walk time was added to this model, it was independently associated with SBP response (Beta [SE]) = -0.05 (0.01), p value =.0001, model r2 = 7%), but did attenuate associations with disease.


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  		Table 4. Cardiovascular Responses to 400-Meter Walk by Age, Gender, and Race.

 

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  		Table 5. Factors Associated With Systolic Blood Pressure Response to 400-Meter Walk: Multiple Linear Regression.

 
Heart rate response averaged a little over 25 bpm, consistent with moderate exercise intensity (Table 4), and did not vary significantly with age, gender, or race. Those with coronary heart disease, stroke, and hypertension had somewhat lower heart rate responses of borderline significance, in accord with slower walk times for each of these groups. Those with higher BMI had slightly higher heart rate response varying from 23.4 ± 12.9 to 26.8 ± 31.1 from lowest to highest gender-specific quartile (p =.002). The differences were similar across lowest to highest physical activity group. None of the subclinical disease markers were associated with heart rate response. In a multivariate model (Table 6), coronary artery disease, lower BMI, higher physical activity, and higher CES-D were all independently associated with a lower heart rate response. In these models, women and blacks had greater heart rate response, while age was not related. These factors together only explained 2% of the variance in heart rate. Walk time itself, when added to the model, was strongly and independently associated with heart rate response (Beta [SE] = -0.09 (0.01), p value =.0001). The variance explained by the full model including walk time and the other factors was 17%.


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  		Table 6. Factors Associated With Heart Rate Response to the Long-Distance Corridor Walk Test: Stepwise Multiple Linear Regression.

 
Heart rate recovery at 2 minutes averaged about 11–12 bpm or about one half of heart rate response (Table 4). Recovery was highly correlated with response (r =.55, p <.001) and varied little by age, race, gender, or with presence or absence of clinical or subclinical disease. Those in the highest quartile of BMI and with lower physical activity had greater heart rate recovery. In a regression model (not shown), the explained variance was 2%, and, with the addition of walk time to the models, the r2 value increased to 14%.


   DISCUSSION
Top
 Abstract
 Methods
 Results
 Discussion
References
 
The majority of these well-functioning, nondisabled 70–79-year-old men and women in Health ABC were able to walk 400 meters, and completed the test with heart rate and blood pressure responses in the range expected for a moderate level of exertion. Walking performance was influenced by both clinical and subclinical disease, but was also strongly related to body weight and self-reported physical activity. The associations with BMI and physical activity were not explained by greater clinical or subclinical disease. Age, gender, and race remained associated with walk time after consideration of health, weight, and activity. These data support the use of this test as a measure of health status. The independent association with physical activity suggests that it is sensitive to levels of fitness as well.

Higher resting heart rate (21) and slow heart rate recovery (8) of <12 beats in 2 or more minutes have been associated with future cardiovascular mortality. The extent of both heart rate and blood pressure response to the LDCW test was reassuring in that the levels of blood pressure and heart rates achieved indicate a safe range for testing outside of a clinical ECG-monitored setting. The LDCW test, while it encourages a good effort, is self-paced so that a participant can stop at any time. A substantial number (356, or 13%) of those who started the test stopped walking because of an elevated heart rate (>135 bpm), fatigue, dyspnea, or leg pain. There were no symptoms requiring medical intervention during or following the testing. Most of the heart rate response and recovery was explained by the walk time itself. Since we did not push for either a maximal effort or a target heart rate, the heart rate response would be less standardized than during a treadmill test with a specified target heart rate. These cardiovascular responses will be examined as predictors of future health outcomes in this cohort, but may not be independent of actual walk performance as predictors. The "double product" of heart rate and SBP is thought to reflect myocardial oxygen consumption (22). The blood pressure response varied little, but was highest in diabetics and at higher BMI, such that a calculated double product for these groups would be consistent with higher myocardial work with walking.

The Cardiovascular Health Study (CHS) has also reported walk performance in community-dwelling older adults, but used the 6-minute walk test (23). The associations with obesity and clinical and subclinical disease were quite similar to those reported here. Although either test can be used to evaluate older adults, the approach of using a set distance is more reproducible and more closely related to maximal oxygen consumption (7). The U-shaped association with BMI was also noted in the CHS. We were able to examine body composition in more detail, and the findings are similar in that those at the extremes of directly measured body fat had a worse performance than those in the middle range. The ranges of percent body fat for optimal walk performance are similar to the optimal range found for this cohort for muscle strength (24). Lean mass is the major location of oxygen uptake during exercise, but was not independently associated with walk time in these analyses. This latter finding is consistent with the finding that fat mass was more strongly associated than lean mass with lower extremity functioning in this cohort (25).

Several factors should be considered when interpreting these data. We were cautious in excluding and stopping participants, and results may not generalize to those individuals. While we would assume that disease burden, higher weight, and lower activity would cause a lower walking ability, these data are cross-sectional and causality cannot be determined. Finally, we did not assess motivational factors, which can also influence performance (26).

The independent contribution of both clinical and subclinical disease to performance supports the use of walking tests as a measure of health status in older adults. We dichotomized subclinical measures at levels consistent with undiagnosed disease. In many cases the subclinical diseases were just as common as reported diagnoses. Performance on this test may be capturing very early effects of disease before classic symptoms occur, or decline in walking ability might be considered an early symptom of disease itself. Use of this test in clinical practice might raise awareness as to the extent that older adults may be impaired in walking performance.


   Acknowledgments
 
This study was supported by National Institute on Aging contracts N01-AG-6-2101, N01-AG-6-2103, and N01-AG-6-2106.

Address correspondence to Anne B. Newman, MD, MPH, Healthy Aging Research Program, University of Pittsburgh, Bellefield Professional Building, 130 North Bellefield Avenue, Room 532, Pittsburgh, PA 15213. E-mail: newmana{at}edc.pitt.edu

Received January 29, 2003

Accepted February 24, 2003


   References
Top
 Abstract
 Methods
 Results
 Discussion
 References
 

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