Exercise and non-exercise aerobic power prediction models using six-minute walk test

EQUAÇÕES DE PREDIÇÃO DA POTÊNCIA AERÓBICA USANDO O TESTE DE CAMINHADA DE SEIS MINUTOS

Abstracts

BACKGROUND AND OBJECTIVE:

A simple, low-cost approach commonly used to objectively analyze the cardiorespiratory fitness of individuals with different health conditions is the six-minute walk test (6-MWT). Our objective was to develop peak aerobic power prediction using the six-minute walk test in healthy older men.

METHODS:

We measured body composition (body mass [BM], body mass index [BMI], fat percentage [FAT]) and peak aerobic power breath-by-breath during cardiopulmonary exercise testing (CPET [velocity, heart rate [HR] and VO₂ at the anaerobic threshold and peak]) and a 6-MWT (distance [D], weight by distance [WxD], HR and oxygen consumption [VO₂] at peak) in 76 healthy older men aged 65 to 80 years (69.1 ± 0.3 yrs-old).

RESULTS:

We observed significant correlations for VO_2peak during the 6-MWT as a function of WxD (R = 0.75, P < 0.0005), BM (R = 0.56, P < 0.0005), D (R = 0.43, P = 0.0004) and maximum HR (R = 0.37, P = 0.001). Distance correlated significantly with FAT (R = -0.43, P = 0.005), BMI (R = -0.36, P = 0.021) and age (R = -0.31, P < 0.045), whereas WxD correlated with BM (R = 0.86, P<0.005).The inclusion of WxD increased the R2 from 0.65 to 0.74 and decreased the estimative error while yielding the following equation (R = 0.86, standard error of the estimate (SEE) = 182.1 mL•min-1, P < 0.0005) to predict VO_2peak: VO_2peak = 962.2 + (0.037 x WxD) + (8.565 x maximum HR). A non-exercise model was obtained by univariate regressions but not multiple regressions. The FAT (R = 0.43, SEE = 702.2 m, P < 0.005) yielded the best model for predicting distance, i.e., distance = 702.2 - (3.067 x FAT).

CONCLUSION:

Our prediction model seems to accurately estimate VO_2peak in healthy older men primarily when WxD is considered.

KEYWORDS:
Aging; Cardiorespiratory Fitness; Male; Maximal Oxygen Uptake

OBJETIVO:

O teste de caminhada de seis minutos (TC6M) é uma estrategia simples e de baixo custo operacional que objetivamente mede a aptidão cardiorrespiratória de indivíduos com diferentes condições de saúde. Nosso objetivo foi desenvolver equações de predição da potência aeróbica em homens idosos saudáveis usando o TC6M.

MÉTODOS:

Foram medidos a composição corporal (massa corporal [MC], índice de massa corporal [BMI], porcentagem de gordura [%G]) e potência aeróbica de pico através de teste cardiopulmonar de exercício máximo (velocidade, frequência cardíaca [FC] e consumo de oxigênio [VO₂] no limiar anaeróbico e no pico]) e através do TC6M (distancia [D], produto massa corporal x distância, FC e VO₂de pico) em 76 idosos saudáveis com idade entre 65 e 80 anos (69.1 ± 0.3 anos).

RESULTADOS:

Foram observadas correlações significativas para VO_2pico no TC6M em função do produto MCxD (R = 0,75, P < 0,0005), MC (R = 0,56, P < 0,0005), D (R = 0,43, P = 0,0004) e FC máxima (R = 0,37, P = 0,001). A correlacionou-se significativamente com %G (R = -0,43, P = 0,005), IMC (R = -0,36, P = 0,021) e idade (R = -0,31, P < 0,045), enquanto que a MCxD correlacionou-se com MC (R = 0,86, P < 0,005). A inclusão da MCxD aumentou o R ² de 0,65 para 0,74 e diminuiu o erro padrão da estimativa (EPE) gerando a equação (R = 0,86, EPE = 182,1 mL·min^-1, P < 0,0005) para a predição do VO_2peak: VO_2peak = 962,2 + (0,037 x MCxD) + (8,565 x FC máxima). Foi também gerado um modelo preditivo não dependente de exercício através de regressão univariada, mas não múltipla. A %G (R=0,43, EPE = 702,2 m, P < 0,005) gerou o melhor modelo para a predição da distancia, i.e., distancia = 702,2 - (3,067 x %G).

CONCLUSÃO:

Nossas modelos de predição parecem estimar precisamente o VO_2pico de idosos saudáveis, especialmente quando a MCxD é considerada.

PALAVRAS-CHAVE:
Aptidão cardiorrespiratória; consumo máximo de oxigênio; envelhecimento; homem

INTRODUCTION

The assessment of aerobic power during the aging process has been widely studied for decades not only because of the decline of this important health variable with increasing chronological age but also because regardless of the physical activity level, sedentary subjects, active subjects and athletes exhibit decreased aerobic power as they age. Cardiorespiratory fitness has been extensively analyzed because it represents an important predictor of functional independence in elderly individuals^1,2 and of all causes of mortality and cardiovascular events.³

A simple, low-cost approach commonly used to objectively analyze the cardiorespiratory fitness of individuals with different health conditions is the six-minute walk test (6-MWT).⁴ This procedure has been used as a standard reference criterion because the procedure captures a significant portion of the variability in the maximum oxygen consumption (VO_2max: 80%) and the maximum heart rate (MHR: 86%) obtained in the cardiopulmonary exercise testing (CPET).⁵ Thus, the 6-MWT can be used for individuals who are unable to satisfactorily complete a cardiopulmonary CPET in a standard stress test.^6,7 In addition, the 6-MWT reflects the physiological demands required for daily activities.^4,8-10 Moreover, in recent years, several studies have analyzed the possible clinical uses of the 6-MWT to measure the functional status and the cardiorespiratory fitness of healthy elderly individuals and of elderly individuals with cardiovascular and pulmonary disease and as a form of aerobic exercise for the elderly.^11-14 The 6-MWT test has been used to detect changes in the cardiorespiratory fitness of healthy elderly individuals after training¹⁵ and to predict cardiovascular events in patients with stable coronary heart disease.¹⁶

Thus, there has been an effort to establish standard reference norms that apply to a wide range of individuals.¹⁷ Most studies have sought to develop equations that predict the peak O₂ consumption (VO_2peak) or the distance walked during the 6-MWT as a function of variables that are intrinsic to the protocol per se, or are associated with clinical and sociodemographic characteristics.^18,19 These equations seem to explain approximately one- to two-thirds of the variability.^19,20 Clearly, the selection of the variable to be included in the model is an important factor,^21,22 because men seem to experience twice the VO_2max decline over a ten-year period as compared to women (14% versus 7%)²³, and exhibit a higher mortality risk.²⁴ However, when adjusted to factors known to be involved, such as body mass, the walking distance per se may represent a more accurate measure of the cardiorespiratory capacity than the walking distance in elderly men²⁵ and in patients with chronic diseases.²⁶ More recently, a generalized equation has been proposed to predict peak VO₂ from the 6-MWT using data collected from over 1,000 patients with cardiopulmonary disorders.²⁷ No similar proposals for healthy elderly individuals are available. Therefore, the purpose of this study is to develop VO_2peak and distance prediction models using body mass (BM), the body mass index (BMI), body fat (FAT), distance (D), the body weight-walking distance product (WxD) and the maximum heart rate (MHR) in healthy elderly men.

METHODS

Volunteers

Elderly male volunteers were recruited from the community. In total, 204 volunteers were contacted by telephone and submitted to a preliminary screening, which consisted of questions regarding past and current health, drug and cigarette use and physical activity. Afterward, to determine the health status of the volunteers more precisely before they were admitted to the study, the volunteers were invited to the hospital for a detailed clinical evaluation and a standard clinical and physical examination. The evaluation and examination included (i) a detailed assessment of current and past health status, (ii) a 12-lead electrocardiogram, (iii) a check for depression symptoms, (iv) an ascertainment of the ability to self-report and perform basic and instrumental activities of daily living, (v) an evaluation of body composition and (vi) laboratory parameters. The volunteers who were under treatment for acute or chronic cardiovascular, pulmonary or metabolic disease or using medication that influences the cardiovascular and pulmonary system were excluded. The following were additional reasons to exclude a volunteer were: (i) central or peripheral nervous system disorders, (ii) malnourishment or obesity, (iii) smoking, (iv) current or past cancer treatment, (v) surgery of any type during the previous three months, (vi) prescribed bed rest during the previous three months or (vii) any orthopedic disturbances would limit performance during a CPET.

Seventy-six elderly volunteers aged 65 to 80 years were included. The volunteers were cleared for participation and expressed their willingness to submit to the conditions of the experiment. They were informed regarding the procedures and risks before reading and providing written consent. This study was approved by the research ethics committee of our university (#1592/07).

Body composition

We measured height using an electronic scale (Bod Pod®, Life Measurement Inc., USA). The body mass index (BMI) was calculated by dividing the total body mass by the squared height (kg/m²). The body fat percentage (FAT%) and the fat-free mass were obtained by plethysmography (Bod Pod®, Life Measurement Inc., USA). The measurement procedures followed the criteria described by equipment manuals and literature.²⁸

Cardiopulmonary exercise testing

The peak oxygen consumption (VO_2peak) and the anaerobic threshold (AT) were determined using a CPET performed on a treadmill (Life Fitness®, 9700 HR, USA). The treadmill speed was initially set at 1.6 km.h^-1; this was followed by increases of 0.8 km.h^-1increments in speed and 1% increments in slope every two minutes until voluntary exhaustion.⁵ The expired gas samples were analyzed breath-by-breath at 20-second intervals, using a metabolic portable system (K4b2, Cosmed®, Italy). Before each test, the equipment was calibrated according to the manufacturer's recommendations. The heart rate was recorded simultaneously using a portable system (Polar®, Electro OU, Finland). VO_2peak was achieved when the following criteria were satisfied: (i) respiratory exchange ratio (RER) > 1.10, (ii) the age-predicted maximum heart rate (MHR) was reached, (iii) volitional fatigue and (iv) signs of exhaustion toward the test's end (unsteady gait, hyperpnea, sweating, facial flushing and grimacing).²⁹ The anaerobic threshold (AT) was evaluated through the V-slope method, using a computerized regression analysis of the slopes of the CO₂ uptake (VCO₂) versus the O₂ uptake (VO₂) plot, which detects the beginning of the excess CO₂ output generated by the buffering of [H+]. The respiratory compensation point (RCP) was detected by examining the minute ventilation per VCO₂ plot.³⁰

Six-minute walk test

The volunteers were instructed to walk at regular speed as far as possible carrying a portable metabolic system (K4b², Cosmed, Italy) for six minutes. Three tests were performed to control for the learning effect and the data reliability.⁵ The first two tests were performed on the same day separated by a one-hour interval. The third test was performed after 24 hours. The 6-MWT was performed in a 20 m corridor that was clear of obstacles. The corridor length was marked every meter, and the volunteers were informed every 60 seconds regarding the remaining test time.^4,31 The participants were instructed to walk at a self-selected regular pace to cover as much distance as they could during the allotted time. If necessary, slowing and stopping to rest were allowed. At the end of each minute, the participants were provided feedback on the elapsed time and standardized encouragement in the form of statements such as "you are doing well, keep it up" and "do your best". The VO_2peak was established as described in the previous section. The total walked distance was recorded in meters, and the longest distance of the two tests was used. The body weight-walking distance product was calculated by multiplying the body weight by the distance (W x D, kg·m).²⁵

Statistical analysis

The Kolmogorov-Smirnov test was used to analyze the data normality. A one-way analysis of variance with Bonferroni post-hoc compared subjects grouped into quartiles according to the 6-MWT VO_2peak (i.e., P₀-P₂₅, P₂₅-P₇₅ and P₇₅-P₁₀₀). The Pearson product-moment correlation coefficient was used to determine the association of VO_2peak with BM, BMI, body fat, D, WxD andMHR. Univariate regression analysis was used to investigate the associations of age with all of the other variables and the body weight-walking distance product as a function of VO₂ at the anaerobic threshold and peak. In addition, hierarchical multiple regression analyses were performed to develop exercise (VO_2peak) and non-exercise (D and WxD) prediction equation models as a function of BM, BMI, FAT, D, WxD and MHR. All of the analyses were performed using the Predictive Analytics Software17.0 version for Windows package (SPSS, Inc., USA). The data are presented as the mean ± standard error. Significance was set at p < 0.05.

RESULTS

General characteristics

Homogeneity of the population was observed throughout the variables of age and body composition (Table 1). However, VO₂ at the anaerobic threshold and peak (CPET and 6-MWT) were significantly higher in individuals at highest quartile (P₇₅-P₁₀₀). Similar results were observed for distance and the MHR during the 6-MWT (Table 2).

Table 1
Age and body composition of the elder healthy men

	Mean ± Standard deviation
Age (years)	69.1 ± 3.3 (65.0 - 80.0)
Body mass (kg)	74.0 ± 11.0 (53.1 - 104.8)
Body height (m)	1.69 ± 0.01 (1.52 - 1.85)
Body mass index (kg•m2)	25.8 ± 3.4 (17.0 - 34.9)
Lean body mass (kg)	53.7 ± 7.3 (39.2 - 74.3)
Body fat (%)	26.8 ± 7.3 (7.6 - 45.3)

Table 2
Cardiopulmonary exercise parameters according to percentile for VO_2peak at 6MWT and entire group*.

	VO2peak (L•min-1) at 6MWT
	P0-P25(a)	P25-P75(b)	P75-P100(c)	Entire group
CPET at anaerobic threshold
Velocity (km•h-1)	4.1 ± 0.2 (3.2 - 4.8)	4.1 ± 0.2 (2.4 - 5.6)	4.4 ± 0.2 (3.2 - 4.8)	4.2 ± 0.1 (2.4 - 5.6)
Heart rate (bpm)	98.0 ± 3.4 (79.0 - 110.0)	102.1 ± 2.5 (84.0 - 120.0)	98.2 ± 4.9 (75.0 - 118.0)	100.3 ± 1.9 (75.0 - 120.0)
V̇O2 (L•min-1)	1.1 ± 0.1 (0.9 - 1.3)c	1.1 ± 0.1 (0.83 - 1.3)c	1.4 ± 0.1 (0.9 - 1.7)	1.2 ± 0.1 (0.8 - 1.7)
CPET at peak	-----------------------------------
Velocity (km•h-1)	6.9 ± 0.2 (5.6 - 8.0)	7.2 ± 0.1 (5.6 - 8.0)	7.2 ± 0.0 (7.2 - 7.2)	7.1 ± 0.1 (5.6 - 8.0)
Heart rate (bpm)	148.1 ± 5.6 (112.0 - 171.0)	152.1 ± 3.2 (125.0 - 176.0)	153.9 ± 5.7 (129.0 - 177.0)	151.5 ± 2.5 (112.0 - 177.0)
V̇O2 (L•min-1)	1.9 ± 0.1 (1.5 - 2.3)c	2.0 ± 0.1 (1.5 - 2.6)c	2.5 ± 0.1 (2.1 - 2.7)	2.1 ± 0.1 (1.5 - 2.7)
6MWT at peak	-----------------------------------
Distance (m)	589.0 ± 14.8 (532.0 - 675.0)c	620.6 ± 9.2 (539.0 - 716.5)	653.8 ± 20.7 (562.0 - 765.0)	620.2 ± 8.1 (532.0 - 765.0)
Body weight by distance (kg•m)	40.2 ± 1.5 (33.4 - 49.4)	44.6 ± 1.1 (35.9 - 53.1)	54.2 ± 2.1 (46.3 - 66.2)	45.6 ± 1.3 (33.4 - 66.3)
Heart rate (bpm)	123.6 ± 4.4 (96.0 - 164.0)c	133.4 ± 2.6 (105.0 - 166.0)	141.6 ± 3.1 (109.0 - 170.0)	133.0 ± 2.0 (96.0 - 170.0)
V̇O2 (L•min-1)	1.5 ± 0.1 (1.3 - 1.6)bc	1.8 ± 0.1 (1.6 - 2.1)c	2.3 ± 0.1 (2.1 - 2.8)	1.9 ± 0.1 (1.3 - 2.8)

• ^*
  The dark shading indicates significant differences. CPET: cardiopulmonary exercise testing; AT: anaerobic threshold; 6MWT: six-minute walk test; V̇O₂: oxygen uptake

Age effects

We observed an age effect on the anaerobic threshold (velocity: β = -0.39, P = 0.010], heart rate ([β = -0.88, P = 0.0005]), MHR during the CPET ([β = -0.38, P = 0.012]) and D during the 6-MWT ([β = -0.31, P = 0.045]) (data not shown).

Body weight-walking distance product

We analyzed the product of body weight and distance (WxD) as a parameter that could reflect the work rate during the 6-MWT. A significant association was observed between WxD vs. the anaerobic threshold (r = 0.63, β = 0.018 ± 0.004 and P < 0.0005) and VO_2peak (r = 0.73, β = 0.031 ± 0.005, P < 0.0005) regardless of age (data not shown).

Univariate correlations

Peak oxygen uptake during the CPET correlated significantly with the corresponding peak oxygen uptake during the 6-MWT, as shown in Figure 1.

Figure 1
The high level of correlation between VO_2peak during the six-minute walk test and cardiopulmonary exercise test shows that the 6MWT is a reliable predictor of aerobic power.

Figure 2 exhibits the correlation of various parameters of the 6MWT with the respective VO_2peak: the best observed correlation is between distance x weight and peak oxygen consumption. However, distance, maximum heart rate and body mass also correlated significantly.

Figure 2
The four parameters relating to the six-minute walk test correlate significantly with peak O₂ consumption; the best correlation occurred for the distance x weight product.

Figure 3 illustrates the expected inverse correlations between body fat, body mass and age with travelled distance.

Figure 3
The percentage of body fat, body mass index and age correlate inversely with travelled distance.

Multiple regression analysis

We developed exercise and non-exercise models. The first strategy was based on a prediction equation to estimate VO_2peak predominantly as a function of the 6-MWT variables. Subsequently, we tested the hypothesis of a non-exercise prediction equation to estimate either distance (D) or the WxD product (Table 3). All of the variables of the respective models independently explained VO_2peak, D or WxD. When estimating VO_2peak, the inclusion of WxD increased the R² from 0.65 to 0.74, which represents a significant 9% increase in the explained variance of VO_2peak. Moreover, there was an important decrease in estimative error, which yielded the following equation (R = 0.86, SEE = 182.1 mL·min^-1 and P < 0.0005) for predicting VO_2peak:

VO_2peak = 962.2 + (0.037 x WxD) + (8.565 x MHR),

where WxD is the body weight-walking distance product in kg·m and MHR is the maximum heart rate in bpm. A non-exercise model was obtained by univariate regressions but not by multiple regressions. Body fat percentage (R = 0.43, SEE = 702.2m, P < 0.005) yielded the best model for predicting distance, i.e., D= 702.2 - (3.067 x FAT), where FAT represents the percentage of body fat.

Table 3
Exercise and non-exercise prediction models to estimate VO_2peak, distance or body weight-walking distance product as a function of body mass, body mass index, body fat, distance, body weight-walking distance product, and maximum heart rate.

Prediction model	Variable	Coefficients	SE	β	P	Constant	R(R2	SEE	P
Exercise model
V̇O2peak (L•min-1)	DxW	0.037	0.004	.777	.0005	962.2	0.86(0.74)	182.1a	.0005
	MHR	8.565	1.655	.422	.0005
V̇O2peak (L•min-1)	Body mass	20.302	3.084	.642	.0005	2064.0	0.80(0.65)	215.8a	.0005
	Distance	2.538	0.689	.383	.001
	MHR	6.431	2.115	.317	.004
Non-exercise model	-----------------------------------------
Distance	Body fat	-3.067	1.039	-.427	.005	702.2	0.43(0.18)	48.2b	.005
Distance	BMI	-5.581	2.318	-.356	.021	764.4	0.36(0.13)	49.8b	.021
DxW	BMI	1149.9	292.8	.528	.0005	15855.3	0.53(0.28)	6294.7b	.0005

• SE: standard error; SEE: standard error of the estimate (a: mL•min^-1; b: meters); MHR: maximum heart rate; BMI: body mass index; DxW: body weight-walking distance product.

DISCUSSION

An obstacle to measuring the aerobic power of elderly individuals (either in groups or clinical care) has been the lack of a practical, safe, low-cost and scientifically valid method to assess functional status, cardiovascular fitness and the impact of comorbidities on such individuals and capable of providing a parameter for the prescription of exercise. The present study proposes a novel model for predicting aerobic power in healthy elderly men. Our results provide normative data related to cardiopulmonary parameters for maximal CPET and for the 6-MWT in clinically healthy and physically inactive elderly men. The data resulting from this study can serve as an important reference standard for this age range because the strict eligibility criteria employed in the present study excluded participants with cardiopulmonary, metabolic or musculoskeletal disorders. In addition, these data support the hypothesis that WxD can be used as an indicator of the submaximal or maximal workload developed during the 6-MWT. Additionally, our data support the hypothesis that the VO_2peak achieved during the 6-MWT is significantly associated with the VO_2peak recorded in a maximal CPET performance, which facilitated the development of a VO_2peak prediction model with satisfactory accuracy. It was also possible to develop other models to estimate distance (based on a non-exercise pattern) but with low accuracy.

The absolute aerobic power (i.e., L·min^-1) was considered as the main outcome variable in our models. We tried to avoid potential multicollinearity between the BM and the WxD product in the models which considered the relative aerobic power (i.e., mL·kg^-1·min^-1). Therefore, the effect of the body mass in our models is not being overestimated by redundancy. Our analyses demonstrate that each of the predictor variables used in this study was independently related to the distance walked in the 6-MWT and the VO_2peak. However, the best models were extracted when VO_2peak was the main outcome variable.

There are numerous indirect methods to estimate VO_2peak in elderly subjects that result in good accuracy with correlations reaching up to 0.97.^21,22,32,33 These results are similar to the findings of our study for both of the generated exercise models, particularly compared with studies on the 6-MWT.³³ However, some differences in the magnitude of correlations may be partly explained by the type and the number of predictor variables included in the models.^21,22 Moreover, there seems to be a direct relationship between the severity of the clinical condition and the strength of the correlation in the analysis between the walked distance and the VO_2peak.^4,34,35 A linear mixed-model analysis was used to determine the SEE of the 6-MWT to estimate the peak oxygen uptake; the formula can be useful to compare the peak aerobic capacity without the CPET and can be applied to monitor the course of several cardiovascular and pulmonary diseases and the efficacy of potential treatments.²⁷

Although the VO_2peak prediction model developed in the present study has satisfactory accuracy, the extrapolation of the results could be limited because the elderly represent a select group of individuals. Therefore, future studies are required to determine the stability of the proposed model's VO_2peak prediction for individuals whose characteristics are substantially different from our sample amplitude (e.g., physical activity level and fitness, health condition and disease severity).

The present study is the first to demonstrate that WxD is a more important VO_2peak predictor in elderly individuals than weight and distance separately. In addition to characterizing the work rate performed during the 6-MWT^25,26, this strategy improved the regression model's ability to predict VO_2peak. The WxD parameter more accurately reflects the workload of walking than D and therefore should be used as an evaluation criterion of cardiorespiratory fitness in the absence of gas exchange analysis.²⁵ However, there may be other sociodemographic (e.g., gender) or physiological (e.g., resting heart rate) variables that would facilitate the development of a non-exercise prediction model to satisfactorily predict WxD. For instance, chronological age seems to represent an important discriminatory parameter of cardiopulmonary capacity, especially among elderly individuals.³⁶ Moreover, a significant proportion of the variability of the cardiorespiratory capacity estimate may be explained by anthropometric and sociodemographic variables.²⁶

Therefore, we may conclude that our prediction model seems to be an accurate strategy to estimate VO_2peak in healthy older men primarily when WxD is considered. The new exercise prediction model derived proposed in this study can be used to estimate VO_2peak in older men. However, further studies should develop non-exercise models, particularly models based on the WxD parameter.

• ¹
  Shephard RJ. Maximal oxygen intake and independence in old age. Br J Sports Med. 2009;43:342-6. doi: 10.1136/bjsm.2007.044800.
  » https://doi.org/10.1136/bjsm.2007.044800
• ²
  Paterson DH, Govindasamy D, Vidmar M, Cunningham DA, Koval JJ. Longitudinal study of determinants of dependence in an elderly population. J Am Geriatr Soc. 2004;52:1632-8. DOI: 10.1111/j.1532-5415.2004.52454.x
  » https://doi.org/10.1111/j.1532-5415.2004.52454.x
• ³
  Kodama S, Saito K, Tanaka S, Maki M, Yachi Y, Asumi M, et al. Cardiorespiratory fitness as a quantitative predictor of all-cause mortality and cardiovascular events in healthy men and women: a meta-analysis. JAMA. 2009;301:2024-35. doi: 10.1001/jama.2009.681.
  » https://doi.org/10.1001/jama.2009.681
• ⁴
  American Thoracic Society. Guidelines for the six-minute walk test. Am J Respir Crit Care Med 2002ATS Statement: Guidelines for the six-minute walk test. Am J Respir Crit Care Med 2002;166:111-7. DOI: 10.1164/rccm.166/1/111
  » https://doi.org/10.1164/rccm.166/1/111
• ⁵
  Kervio G, Carre F, Ville NS. Reliability and intensity of the six-minute walk test in healthy elderly subjects. Med Sci Sports Exerc 2003;35:169-74. DOI: 10.1249/01.MSS.0000043545.02712.A7
  » https://doi.org/10.1249/01.MSS.0000043545.02712.A7
• ⁶
  Rostagno C, Boddi V, Gensini GF. 6MWT predicts survival better than CPET in patients with stable cardiomyopathy. Br J Med Med Res 2012; 2:386-95.
• ⁷
  Kierkegaard M, Tollbäck A. Reliability and feasibility of the six minute walk test in subjects with myotonic dystrophy. Neuromuscul Disord 2007;17:943-9. DOI: 10.1016/j.nmd.2007.08.003
  » https://doi.org/10.1016/j.nmd.2007.08.003
• ⁸
  Braunschweig F, Linde C, Adamson PB, Magalski A, Erdmann E, Kjellstrom B, et al. Continuous central haemodynamic measurements during the six-minute walk test and daily life in patients with chronic heart failure. Eur J Heart Fail 2009;11:594-601. DOI: 10.1093/eurjhf/hfp045
  » https://doi.org/10.1093/eurjhf/hfp045
• ⁹
  Mudge S, Stott NS. Timed walking tests correlate with daily step activity in persons with stroke. Arch Phys Med Rehabil 2009;90:296-301. doi: 10.1016/j.apmr.2008.07.025.
  » https://doi.org/10.1016/j.apmr.2008.07.025
• ¹⁰
  Witham MD, Argo IS, Johnston DW, Struthers AD, McMurdo ME. Predictors of exercise capacity and everyday activity in older heart failure patients. Eur J Heart Fail 2006;8:203-7. DOI: 10.1016/j.ejheart.2005.03.008
  » https://doi.org/10.1016/j.ejheart.2005.03.008
• ¹¹
  Doutreleau S, Marco P, Talha S, Charloux A, Piquard F, Geny B. Can the six-minute walk test predict peak oxygen uptake in men with heart transplant?. Arch Phys Med Rehabil 2009;90:51-7. doi: 10.1016/j.apmr.2008.07.010.
  » https://doi.org/10.1016/j.apmr.2008.07.010
• ¹²
  Zainuldin M, Knoke D, Mackey M, Luxton N, Alison J. Prescribing cycle training intensity from the six-minute walk test for patients with COPD. BMC Pulm Med 2007;7:9-17. DOI: 10.1186/1471-2466-7-9
  » https://doi.org/10.1186/1471-2466-7-9
• ¹³
  Enright PL, McBurnie MA, Bittner V, Tracy RP, McNamara R, Arnold A,et al. The 6-min walk test. A quick measure of functional status in elderly adults. Chest 2003; 123:387-98. DOI: 10.1378/chest.123.2.387
  » https://doi.org/10.1378/chest.123.2.387
• ¹⁴
  Opasich C, Pinna G, Mazza A, Febo O, Riccardi R, Riccardi PG, et al. Six-minute walking performance in patients with moderate-to-severe heart failure. Eur Heart J 2001;22:488-96. DOI: 10.1053/euhj.2000.2310
  » https://doi.org/10.1053/euhj.2000.2310
• ¹⁵
  Santana M, Lira C, Passos G, Santos C, Silva AH, Yoshida CH, et al. Is the six-minute walk test appropriate for detecting changes in cardiorespiratory fitness in healthy elderly men? J Sci Med Sport 2012;15: 259-65. doi: 10.1016/j.jsams.2011.11.249.
  » https://doi.org/10.1016/j.jsams.2011.11.249
• ¹⁶
  Beatty A, Schiller N, Whooley M. Six-minute walk test as a prognostic tool in stable coronary heart disease: data from the heart and soul study. Arch Inter Med. 2012; 172:1096-102. doi: 10.1001/archinternmed.2012.2198.
  » https://doi.org/10.1001/archinternmed.2012.2198
• ¹⁷
  Casanova C, Celli BR, Barria P, Casas A, Cote C, de Torres JP, et al. The 6-min walk distance in healthy subjects: reference standards from seven countries. Eur Respir J 2011;37:150-6. doi: 10.1183/09031936.00194909.
  » https://doi.org/10.1183/09031936.00194909
• ¹⁸
  Jenkins S, Cecins N, Camarri B, Williams C, Thompson P, Eastwood P. Regression equations to predict 6-minute walk distance in middle-aged and elderly adults. Physiother Theory Pract 2009;25:516-22. doi: 10.3109/09593980802664711.
  » https://doi.org/10.3109/09593980802664711
• ¹⁹
  Enright PL, Sherrill DL. Reference equations for the six-minute walk in healthy adults. Am J Resp Crit Care Med 1998;158(5Pt1):1384-7.
• ²⁰
  Troosters T, Gosselink R, Decramer M. Six minute walking distance in healthy elderly subjects. Eur Resp J 1999;14:270-4. DOI: 10.1034/j.1399-3003.1999.14b06.x
  » https://doi.org/10.1034/j.1399-3003.1999.14b06.x
• ²¹
  Cao ZB, Miyatake N, Higuchi M, Ishikawa-Takata K, Miyachi M, Tabata I. Prediction of VO2max with daily step counts for Japanese adult women. Eur J Appl Physiol 2009;105:289-96. doi: 10.1007/s00421-008-0902-8.
  » https://doi.org/10.1007/s00421-008-0902-8
• ²²
  Cao ZB, Miyatake N, Higuchi M, Miyachi M, Ishikawa-Takata K, Tabata I. Predicting VO2max with an objectively measured physical activity in Japanese women. Med Sci Sports Exerc 2010;42:179-86. doi: 10.1249/MSS.0b013e3181af238d.
  » https://doi.org/10.1249/MSS.0b013e3181af238d
• ²³
  Stathokostas L, Jacob-Johnson S, Petrella RJ, Paterson DH. Longitudinal changes in aerobic power in older men and women. J Appl Physiol 2004;97:781-9. DOI: 10.1152/japplphysiol.00447.2003
  » https://doi.org/10.1152/japplphysiol.00447.2003
• ²⁴
  Oksuzyan O, Juel K, Vaupel JW, Christensen K. Men: good health and high mortality. Sex differences in health and aging. Aging Clin Exp Res 2008;20:91-102.
• ²⁵
  Chuang M-L, Lin I-F, Wasserman K. The body weight-walking distance product as related to lung function, anaerobic threshold and peak VO2 in COPD patients. Resp Med 2001;95:618-26.
• ²⁶
  Iwama AM, Andrade GN, Shima P, Tanni SE, Godoy I, Dourado VZ. The six-minute walk test and body weight-walk distance product in healthy Brazilian subjects. Braz J Med Biol Res 2009;42:1080-5. DOI: 10.1590/S0100-879X2009005000032
  » https://doi.org/10.1590/S0100-879X2009005000032
• ²⁷
  Ross R, Murthy J, Wollak I, Jackson A. The six minute walk test accurately estimates mean peak oxygen uptake. BMC Pulm Med 2010;10:31-39. doi: 10.1186/1471-2466-10-31.
  » https://doi.org/10.1186/1471-2466-10-31
• ²⁸
  Fields DA, Hunter GR. Monitoring body fat in the elderly: application of air-displacement plethysmography. Curr Opin Clin Nutr Metab Care 2004;7:11-4. DOI: 10.1097/01.mco.0000109597.04238.f7
  » https://doi.org/10.1097/01.mco.0000109597.04238.f7
• ²⁹
  American College of Sports Medicine. General principles of exercise prescription. In: Thompson WR, Gordon NF, Pescatello LS, editors.ACSM's Guidelines for Exercise Testing and Prescription.Philadelphia: Williams & Wilkins; 2010.p.152-175
• ³⁰
  Beaver WL, Wasserman K, Whipp BJ. A new method for detecting anaerobic threshold by gas exchange. J Appl Physiol 1986;60:2020-7.
• ³¹
  Enright PL. The six-minute walk test. Respir Care 2003;48:783-5.
• ³²
  Akalan C, Robergs RA, Kravitz L. Prediction of VO2max from an individualized submaximal cycle ergometer protocol. J Exerc Physiol Online 2008;11:1-17.
• ³³
  Huggett DL, Connelly DM, Overend TJ. Maximal aerobic capacity testing of older adults: A critical review. J Gerontol A BiolSci Med Sci 2005;60:57-66.
• ³⁴
  Solway S, Brooks D, Lacasse Y, Thomas S. A qualitative systematic overview of the measurement properties of functional walk tests used in the cardiorespiratory domain. Chest 2001;119:256-70. DOI: 10.1378/chest.119.1.256
  » https://doi.org/10.1378/chest.119.1.256
• ³⁵
  Guyatt GH, Thompson PJ, Berman LB, Sullivan MJ, Townsend M, Jones NL, et al. How should we measure function in patients with chronic heart and lung disease? J Chronic Dis 1985;38:517-24. DOI: 10.1016/0021-9681(85)90035-9
  » https://doi.org/10.1016/0021-9681(85)90035-9
• ³⁶
  Hovington CL, Nadeau S, Leroux A. Comparison of walking parameters and cardiorespiratory changes during the 6-minute walk test in healthy sexagenarians and septuagenarians. Gerontology 2009;55:694-701. doi: 10.1159/000240015.
  » https://doi.org/10.1159/000240015

Publication Dates

• Publication in this collection
  29 Sept 2016
• Date of issue
  Sep-Oct 2016

History

• Received
  06 June 2016
• Reviewed
  13 July 2016
• Accepted
  08 Sept 2016