Academic journal article Research Quarterly for Exercise and Sport

Prediction Equations of Energy Expenditure in Chinese Youth Based on Step Frequency during Walking and Running

Academic journal article Research Quarterly for Exercise and Sport

Prediction Equations of Energy Expenditure in Chinese Youth Based on Step Frequency during Walking and Running

Article excerpt

Purpose: This study set out to examine the relationship between step frequency and velocity to develop a step frequency-based equation to predict Chinese youth's energy expenditure (EE) during walking and running. Method: A total of 173 boys and girls aged 11 to 18 years old participated in this study. The participants walked and ran on a treadmill at speeds of 3 km/hr, 4 km/hr, 5 km/hr, 6 km/hr, 7 km/hr, and 8 km/hr. EE was measured using indirect calorimetry of open circuit spirometry (Cosmed K4[b.sup.2] metabolic analyzer). Using multiple regression analysis, the relationship between step frequency and velocity was first examined, and the prediction equation of EE based on step frequency, age, and gender was derived. Results: The hypothesized relationship between step frequency and velocity was confirmed and an accurate ([R.sup.2] = .78) EE prediction equation was derived: Net EE = - 13.7744 + 1.8004 (step frequency) -5.5715 (age) -11.5244 (gender). Conclusion: A step frequency-, age-, and gender-based equation was derived to predict the EE of youth during walking and running. The equation can be used to develop a simple device to estimate EE during walking and running in this population.

Keywords: energy consumption, physical activity, regression equations, velocity

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Estimating the energy expenditure (EE) in walking is necessary for health, rehabilitation, and kinesiology studies, and this is especially true for children and youth considering the fast-spreading childhood obesity epidemic and chronic health conditions worldwide (Riner & Sellhorst, 2013). The estimation is also an important basis for diagnosing diseases in clinical settings (Pols, Peeters, Kemper, & Grobbee, 1998). However, challenges remain in estimating EE of individuals by means of a system that has a low cost, does not interrupt an individual's daily life, and is able to measure real-time EE and total EE using simple devices. The most accurate methods to measure and estimate EE of free-living activities are the doubly labeled water (DLW) method (Ainslie, Reilly, & Westerterp, 2003) and respiratory metabolism analysis (McLaughlin, King, Howley, Bassett, & Ainsworth, 2001; Pinnington, Wong, Tay, Green, & Dawson, 2001). DLW, in fact, is considered the "gold standard" in measuring total EE. The limitations of both methods are that they can only be used in clinical and laboratory settings and they are not viable measurement tools during physical activity. In recent years, some simple and convenient devices that measure EE during walking or running, such as pedometers, have been developed and used (Crouter, Schneider, Karabulut, & Bassett, 2003; Foster et al., 2005; Schneider, Crouter, & Bassett, 2004).

The design and price of pedometers vary greatly. The pedometer has three basic types of designs, including the spring-suspended lever arm with metal-on-metal contact, a magnetic reed proximity switch, and an accelerometer type (Crouter et al., 2003; Schneider, Crouter, Lukajic, & Bassett, 2003). Nevertheless, walking and running--two of the most common forms of physical activity--can be readily measured by pedometers. Pedometers have become increasingly popular as a measurement tool for physical activity. The accuracy and scope of application, however, are not known completely because of the commercial confidential restraints on computational algorithms used in pedometers. Developing and validating open computational algorithms that can predict EE is thus greatly needed.

One of the ideas to develop such an algorithm is to employ the "walk ratio" concept. According to Sekiya and Nagasaki (1998), Walk Ratio = Step Length / Step Rate or Step Frequency. The walk ratio is a speed-independent index of walking patterns, which remains constant within a broad speed range (Sekiya & Nagasaki, 1998). The gait velocity (or simply velocity)/speed of human walking is determined by the product of step length and step rate or step frequency. …

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