Using activity monitors to measure physical activity in free-living conditions.

Physical activity is a broad term used to define "any bodily movement produced by skeletal muscles that results in energy expenditure." (1)(p126) A physically active lifestyle is associated with a decreased risk for a variety of chronic diseases and health conditions such as cardiovascular disease, (2-5) hypertension, (6-8) diabetes mellitus, (9-2) certain cancers, (13-15) depression, (16-18) obesity, (19,20) cerebrovascular disease, and premature death. (21) The Surgeon General recommends 30 minutes for adults or 60 minutes for children of moderate-intensity activity on most, if not all, days of the week to be physically active and achieve a health benefit. (21) The Surgeon General's recommendation is comparable to expending approximately 150 kcal of energy per day (21) for an otherwise healthy individual whose principal mode of activity is walking. Two studies in Japan (22,23) and the popular press have promoted a pedometer-based target of 10,000 steps per day as a way for adults to meet the national physical activity guidelines. Research is ongoing, however, to determine whether this guideline is appropriate for all populations. (24-26) According to the Centers for Disease Control and Prevention, more than 25% of US adults do not engage in any leisure-time physical activity, and 60% do not achieve the Surgeon General's physical activity recommendations. (21,27,28) Women, (29,30) older adults, (31-36) racial and ethnic minority populations, and people with physical disabilities (27) are most likely to be inactive. (37) The US Department of Health and Human Services has set a national health objective for 2010 to reduce the prevalence of no leisure time activity from more than 25% to 20% of US adults. (37)

The assessment of physical activity is essential to: (1) determine whether physical inactivity is a problem, (2) set goals for physical therapy interventions to increase physical activity, (3) provide incentives and track adherence to recommendations made for increasing physical activity, and (4) utilize physical activity as an outcome measure for physical therapy interventions. As stated in the Guide to Physical Therapist Practice, (38) physical therapists are involved in prevention of disease and promotion of health and wellness. Physical therapists should be involved in preventing physical inactivity in susceptible populations (ie, primary prevention), decreasing the severity of disease through early diagnosis of physical inactivity and prompt intervention (ie, secondary prevention), and limiting the degree of disability and promoting physical activity in people with chronic and irreversible diseases (ie, tertiary prevention).

The purposes of this update are: (1) to discuss the general description and use of activity monitors, (2) to present the psychometric properties of various activity monitors, (3) to compare the advantages and disadvantages of selected activity monitors, and (4) to provide recommendations regarding the use of activity monitors.

Pedometers

General Description and Use

Pedometers are matchbook-sized, battery-operated movement monitors that are attached to the waistband in the midline of the thigh on either side of the body. Pedometers were designed to measure the number of steps that a person takes during ambulatory activity such as walking or running. Older mechanical-style pedometers had problems with reliability and validity, but the new electronic pedometers are more accurate. (39-42) Pedometers range in cost from approximately $10 to $200, (43) which makes them an attractive low-cost choice.

Types of Activities and Data Derived

Pedometers have gained attention over the past decade because of their ability to provide accurate measures of ambulatory behaviors and to capture intermittent or continuous activity participation throughout the assessment period of interest. The pedometer can be remarkably accurate in counting steps in people without impairments who walk at least 0.9 m/s. (44) Pedometers may underestimate steps taken at slower gait speeds (ie, <0.9 m/s) (45-47) or with irregular and unsteady gait patterns. (45,46,48-50) Because pedometers were specifically designed to measure ambulatory behavior, they may not accurately capture seated activity, upper-extremity activity, or indoor and outdoor household chores such as pushing, lifting, or carrying objects.(51-53)

Pedometers count the number of steps taken during ambulatory activity by using a horizontal spring suspended lever arm that moves up and down in response to vertical accelerations of the hip. This motion opens and closes an electrical circuit, which accumulates the number or steps taken and provides a digital display. Some pedometers that allow the input of the individual's stride length also provide an estimate of distance walked. The raw data (number of steps accumulated) are the most accurate descriptor of ambulatory activity obtained from a pedometer. (54,55) Pedometers do not have internal clocks, so they are unable to provide information on the pattern or duration of specific activities (ie, how many steps a person accumulated at 2:00 PM while walking the dog). Pedometers also do not take into account the intensity of vertical displacement; therefore, the steps on a pedometer cannot distinguish one intensity level from another. For instance, if one person sprinted 100 steps and a second person walked 100 steps, the pedometer would simply record approximately 100 steps for each person.

Based on currently available evidence, (25,56,57) Tudor-Locke and Bassett (58) in 2004 proposed the following indexes to classify pedometer-determined physical activity in adults who are free of disabilities or chronic disease: <5,000 steps a day for sedentary lifestyle, 5,000 to 7,499 steps a day for low activity, 7,500 to 9,999 steps a day for somewhat active, 10,000 to 12,499 steps a day for active, and [greater than or equal] 12,500 steps a day for highly active. Further investigation is needed to determine appropriate pedometer-derived step ranges in various populations (eg, people with physical disabilities). A systemic review of 23 published cross-sectional studies showed the following step range values for various populations: 12,000 to 16,00 steps a day for 8- to 10-year-old boys and girls (girls<boys), 7,000 to 13,000 steps a day for younger adults who are healthy, 6,000 to 8,500 steps a day for older adults who are healthy, and 3,500 to 5,500 steps a day for people with disabilities and chronic illnesses. (54)

Number of Measurement Days

A common protocol is to have the individual wear the pedometer for 1 week (5-7 days) and calculate the average number of steps per day (total number of steps accumulated/number of days worn). This approach reduces measurement variability and accounts for lower step counts on weekends versus weekdays. (45,53,56,59,60) Tudor-Locke et al (61) had 90 adult people who were healthy wear a Yamax pedometer * for 7 days in free-living conditions (activities performed in the home or community). Intraclass correlation analyses (the reliability of using any given single day to estimate steps per day computed using the whole week) revealed that a minimum of 3 days of wearing the pedometer was necessary to achieve a reliability value of .80 for estimating steps per day. (61) However, if an investigator wants to determine which day or days of the week an individual is most inactive, the individual could wear the pedometer and record the number of steps accumulated each day for several weeks. Perhaps the investigator would find 1 or 2 days per week in which the individual is inactive compared with other days. Once a weekly pattern of inactivity is identified, an individualized treatment program could be formulated to target those specific inactive days.

Psychometric Properties

The pedometer is an assessment tool that has been shown to yield valid and reliable data in a variety of laboratory and field settings. (45,56,57,62-64) Pedometers have been validated against accelerometers, (57,62-64) self-report measures of physical activity, (65-67) measures of energy expenditure, (45,57,66,68,69) and distance walked as measured by a calibrated measuring wheel. (56) The reliability and validity of data obtained with pedometers vary greatly and are model and brand dependent. The investigator must research the psychometric properties of the pedometer of interest before purchase and use because not all pedometers yield data that are equally accurate and valid. (43,45,68) Previous investigations (45,50,68,70) revealed that the Yamax Digiwalker pedometer * is accurate over various walking speeds (0.9-1.8 m/s) and on various surfaces (cement versus rubberized track) in people with normal weight and those who are overweight or moderately obese and produces data with good intra- and inter-instrument agreement.

Accelerometers

General Description and Use

Accelerometers are electronic sensors that measure the quantity and intensity of movement. (40) Accelerometers are capable of measuring and storing measurements of the intensity, frequency, pattern, and duration of activity. Accelerometery data are recorded by the activity monitor and then processed on a computer. The supplement to the journal Medicine and Science in Sports and Exercise titled "Objective Monitoring of Physical Activity: Closing the Gaps in the Science of Accelerometry" (71) provides a more detailed explanation of the technical aspects of accelerometers. Accelerometers can vary in size, weight, sensitivity, cost (approximately $600-$1,200), memory, and software capabilities.

Accelerometers are relatively small, and they can be worn on the waist, wrist, or ankle and are attached by belts, pouches, belt clips, or ankle and wrist Velcro bands. ([dagger]) In people with physical limitations such as visual impairments, arthritis, and neurologic deficits, the choice of accelerometer attachment is of special concern. For instance, fastening the accelerometer belt to the waist and unfastening it may be difficult for these individuals, and perhaps the use of a pouch or belt clip for attachment of the accelerometer would be more practical.

The preferred placement for the accelerometer is dependent on the type of accelerometer and the purpose for which it is used. Positioning on the waist is well suited for picking up accelerations that occur during normal ambulatory movement (72) and has been shown to yield the best prediction of energy expenditure. (73) Swartz et al (74) utilized the Computer Science and Application accelerometer (now termed "ActiGraph" ([double dagger]), which was worn on the wrist or the waist, as well as with a combined wrist and waist placement. The investigators found the combined wrist and waist accelerometer placement added minimally to the predictive accuracy of energy expenditure of a waist-mounted accelerometer worn alone. (74) The StepWatch Step Activity Monitor (SAM) ([section]) is an example of an accelerometer that was designed to be worn on the ankle. The SAM has been utilized to measure physical activity in people who are expected or known to have gait deviations (ie, people using lower-extremity prostheses, (75) people with neurologic disease (76) or joint replacements, (77,78) and people with other gait deviations (44,79-81).

Accelerometers are classified as uniaxial, biaxial, or triaxial depending on the number of planes in which movement is monitored. Uniaxial monitors record vertical acceleration in 1 plane, and biaxial monitors record acceleration in 2 planes. Triaxial monitors record acceleration in 3 planes by 3 different accelerometers positioned internally at 90 degrees from one another. Output from each accelerometer is reported along with a composite value of all 3 accelerometers, possibly providing a more stable indicator of overall body movements. On average, triaxial accelerometers are more expensive than uniaxial accelerometers although it has yet to be determined whether triaxial accelerometers provide a more accurate predictor of energy expended than the less expensive uniaxial accelerometer. (82-85) The SAM is a microprocessor-based instrument with a custom-made sensor, and the ActiGraph is uniaxially or biaxially dependent on the model.

Number of Measurement Days

Studies (60,86-89) have suggested that 4 to 12 measurement days are needed for reliable accelerometry estimates of habitual daily physical activities. To obtain consistent measurements of physical activity patterns in adults, Matthews (87) found that at least 7 days of monitoring are required. Trost et al (90) determined that 4 to 5 days of accelerometer monitoring in children and 8 to 9 days in adolescents were necessary to achieve a between-day intraclass correlation reliability level of .80. The maximum capacity of the monitor to record information and the battery life of the monitor also need to be considered when selecting the number of days to be monitored.

Types of Activity and Data Derived

Accelerometers can measure most types of physical activity that involve lower-extremity or trunk acceleration such as walking, running, and stair climbing. Because accelerometers are typically worn on the waist, measuring activities that involve upper-extremity movement or seated activities can be difficult. Therefore, accelerometer data may underestimate the energy expenditure of certain indoor and outdoor household chores (eg, vacuuming, mowing the lawn, gardening) and some recreational tasks. (56,64,85,91,92)

Data from the accelerometer are automatically expressed as counts. Accelerometer counts are a measure of the frequency and intensity of vertical accelerations and decelerations. Counts are dimensionless units whose values are specific for each brand of monitor. Counts are derived from the force and frequency of vertical displacement (eg, intensity). Because accelerometers have an internal clock, the physical activity counts are time stamped, and the activity can be broken down minute by minute. This allows the investigator to establish daily patterns of physical activity. For example, in a small sample of patients (N<10) in rehabilitation after hip fracture, we obtained ActiGraph accelerometer activity counts during physical therapy and occupational therapy sessions as well as during nontherapy waking hours. From this information, it would be possible to determine whether patients were more active during their therapy sessions than during nontherapy times while in the rehabilitation center.

Because accelerometers time stamp physical activity and record intensity, it is also possible to obtain a reliable measurement of time spent in various intensity categories. Establishing intensity categories is possible by estimating energy expenditure and storing data for later recall. The most work in setting activity intensity cut points has been performed on the ActiGraph. (51)

The number and duration of physical activity bouts (physical activity counts fluctuating from zero) throughout the day is an additional way to express accelerometry data. For instance, an investigator may hypothesize that active people get up and move around significantly more times in a day compared with physically inactive people. Perhaps a physically inactive individual only transitions from a stationary position 2 to 3 times a day for meals and toileting, whereas an active individual may transition 10 to 20 times a day. Recording bouts of activity is a relatively novel, yet developing, way to express and analyze accelerometer data.

Because accelerometers provide various ways to analyze physical activity, investigators report data from accelerometers in different ways, including total counts over a period of time, counts per day, counts per minute, total steps over a period of time, steps per day, steps per minute, minutes spent in specific activity intensities, number and duration of activity bouts per day, or estimates of energy expenditure. In investigating the literature on accelerometers, the measurement unit in which data are presented is important. It is difficult to compare various outputs from different accelerometers used in studies if the authors present their results in different measurement units.

Psychometric Properties

Accelerometers have been found to yield reliable and valid data in a variety of laboratory and free-living settings. The psychometric properties of accelerometers can significantly differ depending on the accelerometer brand and model, the characteristics of the people being assessed, and pertinent physical activities performed. Studies investigating the test-retest reliability of data obtained with accelerometers during walking revealed promising correlation coefficients for the ActiGraph (r=.85), TriTrac ([parallel]) (r=.96), and BioTrainer (#) (r=.89). (85,93) The SAM was found to yield data with excellent test-retest reliability (r=.92) during ambulation in patients with stroke and resultant hemiplegia. (48,94) Accelerometers have been utilized in research involving young active adults, older adults, children, people with obesity, people with physical disabilities, slow gait speeds, and so on. Accelerometers have been validated against direct observation, (95) heart rate monitors, (84,96) self-report measures, and measures of energy expenditure, (83,95,97,98) Welk et al (85) found higher correlations between accelerometers and measured energy expenditure for treadmill activity (r=.85-.92) compared with lifestyle activity (r=.48-.59). Additionally, with treadmill activity, the ActiGraph accelerometer yielded accurate predictions of energy expenditure, whereas the TriTrac and the BioTrainer tended to overestimate energy expenditure (101%-136% of measured value). (85)

Discussion

Before selecting an activity monitor, the psychometric properties, the feasibility of using the monitor, the characteristics of the people being assessed, and the goal of measuring physical activity should be considered. The Table summarizes the overall characteristics of pedometers and accelerometers that may be considered when selecting an activity monitor.

Psychometric Properties and Feasibility

If data from an activity monitor do not have some established reliability and validity, it is important for investigators to ascertain this before using the monitor in their population of interest. The investigator must cautiously interpret reliability and validity values for the data produced from accelerometers. Because data from accelerometers can be expressed in various ways (counts, counts per minute, energy expenditure, minutes spent in various intensity categories), the investigator should compare the unit of measurement for each study establishing reliability and validity. The psychometric properties should be established in the units of measurement the investigator plans to use. For example, if the investigator plans to look at bouts of physical activity from an accelerometer, then reliability and validity should be determined for bouts of physical activity and not counts per day or kilocalories. The feasibility of a method for measuring physical activity is influenced by the cost of the method as well as the burden placed on the individuals being assessed and the investigator. Measuring physical activity often requires the individual to wear the monitor outside the clinic. If the investigator's goal is to assess physical activity in a large number of individuals or in a population where damage is more likely to occur to the device (eg, in young children), then a pedometer, which is reasonably priced, would be an appropriate choice. Both pedometers and accelerometers limit the burden on the individual and investigator because the number of steps and movement counts, respectively, are recorded and stored as they occur. The individual or investigator must record steps from the digital output of the pedometer daily or weekly (depending on instructions from the investigator). We recommend providing the individual with a daily diary to record wear time and steps accumulated. Because accelerometry data are downloaded to a computer, manually recording data from the accelerometer is not necessary. The best choice for an activity monitor is one that is within the investigators' budget, has established inter-instrument and test-rest reliability, and has been validated in the population of interest for the activity that the investigators want to measure.

Individual Characteristics

Individual characteristics such as a person's primary type of physical activity and weight distribution may influence the selection of an activity monitor. The chosen monitor to measure physical activity should capture the physical activity type in which the person spends the highest percentage of his or her time. For instance, in older adults who are healthy, the most common type of physical activity is walking. (99) Therefore, a pedometer that captures walking activity is cost effective and appropriate. On the other hand, if the physical activity level of individuals include running, it has been suggested that accelerometers (ActiGraph specifically) are able to discriminate the intensity between walking and running, (100) whereas pedometers would erroneously assume that a participant expends a constant amount of energy per step (22,64,101,102)

Special considerations are needed in people who are obese (body mass index 30 kg/[m.sup.2]) (103) to ensure the accurate measurement of physical activity. If the pedometer or accelerometer is to be worn on the waist by an individual with central obesity, the monitor may not be vertically oriented and therefore may not accurately record steps or counts. Consequently, if the sample is small and has a high percentage of people with obesity (eg, perhaps a study investigating people with type II diabetes mellitus), the SAM may be a more accurate choice than a pedometer or an accelerometer that is worn on the waist. Results regarding the accuracy of activity monitors in people with obesity are conflicting with slightly stronger evidence indicating that waist-worn monitors can be problematic in people with obesity. (50,104-106)

Physical Activity Assessment

It is the investigator's decision, based on his or her goals, whether data from the activity monitor should be displayed to the person being assessed. If physical activity is being measured as an outcome in a research study and the individual needs to be masked, then accelerometers such as the ActiGraph and TriTrac that do not display the data output would be a good choice. However, if the purpose of measuring physical activity is to provide feedback and incentive to increase physical activity, then a monitor that provides a readout of the amount of activity or steps taken such as the BioTrainer accelerometer or the Yamax Digiwalker pedometer would be appropriate.

The 10,000-step goal often is cited as an acceptable level of physical activity, yet further research is necessary to determine whether this goal is comparable to the Surgeon General's recommendation of 30 minutes of moderate-intensity activity on most days of the week. Le Masurier and Tudor-Locke (63) had 59 sedentary women (aged 20-65 years) wear a Yamax pedometer and an ActiGraph accelerometer on the waist for 1 day to determine whether taking 10,000 steps in a day was equivalent to meeting the Surgeon General's recommendation. Both participants who took more than 10,000 steps and those who took fewer than 10,000 steps had more than 30 minutes of moderate-intensity activity that day [bar.X]=62.1 minutes [SD=27.7] and [bar.X]=38.8 minutes [SD=18.9], respectively; P<.05). Furthermore, the authors found the sensitivity and specificity of the 10,000-step goal in identifying individuals who met the Surgeon General's recommendation were 65% and 67% when all minutes of moderate physical activity were considered.

When using step counts to set goals for increasing physical activity, we believe that setting goals to increase a person's number of steps per day by a certain percentage is more appropriate than setting an immediate goal of 10,000 steps per day. For example, in people who are sedentary (ie, take fewer than 5,000 steps a day), setting an immediate goal of 10,000 steps may be overly ambitious, intimidating, and possibly even unsafe. Our experience is that a more reasonable goal of increasing the number of steps by 5% to 10% each week is more attainable and results in more permanent lifestyle changes. We feel it is important to begin with an achievable goal so that the individual has a better chance of being successful. There remains a need for continued research in: (1) measuring physical activity in specific populations (ie, people who are nonambulatory), (2) establishing the usefulness of activity monitoring in clinical practice, (3) determining the meaningfulness of change in activity monitor output with intervention, and (4) formulating a standard format to present activity monitor data.

Key Words: Accelerometer, Pedometer, Physical activity.

This article was received July 6, 2005, and was accepted March 16, 2006.

References

(1) Caspersen CJ, Powell KE, Christenson GM. Physical activity, exercise, and physical fitness: definitions and distinctions for health related research. Public Health Rep. 1985;100:126-131.

(2) Hu G, Tuomilehto J, Silventoinen K, et al. Joint effects of physical activity, body mass index, waist circumference and waist-to-hip ratio with the risk of cardiovascular disease among middle-aged Finnish men and women. Eur Heart J. 2004;25:2212-2219.

(3) Barengo NC, Hu G, Lakka TA, et al. Low physical activity as a predictor for total and cardiovascular disease mortality in middle-aged men and women in Finland. Eur Heart J. 2004;25:2204-2211.

(4) Hakim A, Curb J, Petrovitch H, et al. Effects of walking on coronary heart disease in elderly men: the Honolulu Heart Program. Circulation. 1999;100:9-13.

(5) Manson J, Hu B, Rich-Edwards J, et al. A prospective study of walking as compared with vigorous exercise in the prevention of coronary heart disease in women. N Engl J Med. 1999;341:650-658.

(6) Matsusaki M, Ikeda M, Tashiro E, et al. Influence of workload on the antihypertensive effect of exercise. Clin Exp Pharmacol Physiol. 1992; 19: 471-479.

(7) Paffenbarger RS Jr, Blair SN, Lee IM. A history of physical activity, cardiovascular health and longevity: the scientific contributions of Jeremy N Morris, DSc, DPH, FRCP. Int J Epidemiol. 2001;30:1184-1192.

(8) Blair SN, Collingwood TR, Reynolds R, et al. Health promotion for educators: impact on health behaviors, satisfaction, and general well-being. Am J Public Health. 1984;74:147-149.

(9) Tuomilehto J, Lindstrom J, Eriksson J, et al. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med. 2001;344:1343-1350.

(10) Manson J, Nathan D, Krolewski AS, et al. A prospective study of exercise and incidence of diabetes among US male physicians. JAMA. 1992;268:63-67.

(11) Manson J, Rimm EB, Stampfer MJ, et al. Physical activity and incidence of non-insulin-dependent diabetes mellitus in women. Lancet. 1991;338(8770):774-778.

(12) Knowler W, Barrett-Connor E, Fowler S, et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention of mefformin. N Engl J Med. 2002;346:393-403.

(13) Lee IM, Paffenbarger RS Jr, Hseih C. Physical activity and risk of developing colorectal cancer among college alumni. J Natl Cancer Inst. 1991;83:1324-1329.

(14) Slattery ML, Murtaugh M, Caan B, et al. Associations between BMI, energy intake, energy expenditure, VDR genotype and colon and rectal cancers. Cancer Causes Control. 2004;15:863-872.

(15) Garrett NA, Brasure M, Schmitz KH, et al. Physical inactivity: direct cost to a health plan. Am J Prev Med. 2004;27:304-309.

(16) King AC, Taylor CB, Haskell WL, DeBusk RF. Influence of regular aerobic exercise on psychological health: a randomized, controlled trial of healthy middle-aged adults. Health Psychol. 1989;8:305-324.

(17) Yancey AK, Wold CM, McCarthy WJ, et al. Physical inactivity and overweight among Los Angeles County adults. Am J Prev Med. 2004;27: 146-152.

(18) Varo Cenarruzabeitia JJ, Martinez Hernandez JA, Martinez-Gonzalez MA. Benefits of physical activity and harms of inactivity. Med Clin (Barc). 2003;121:665-672.

(19) Kokkinos P, Moutsatsos G. Obesity and cardiovascular disease: the role of diet and physical activity. J Cardiopulm Rehabil. 2004;24:197-203.

(20) Blair SN, LaMonte MJ, Nichaman MZ. The evolution of physical activity recommendations: how much is enough? Am J Clin Nutr. 2004;79:913S-920S.

(21) Physical Activity and Health: A Report of the Surgeon General. Atlanta, Ga: US Department of Health and Human Services, Centers for Disease Control and Prevention; 1996.

(22) Hatano Y. Use of the pedometer for promoting daily walking exercise. ICHPER. 1993;29:4-8.

(23) Yamanouchi K, Shinozaki K, et al. Daily walking combined with diet therapy is a useful means for obese NIDDM patients not only to reduce body weight but also to improve insulin sensitivity. Diabetes Care. 1995;18:775-778.

(24) Le Masurier GC, Sidman CL, Corbin CB. Accumulating 10,000 steps: does this meet current physical activity guidelines? Res Q Exerc Sport. 2003;74:389-394.

(25) Welk GJ, Differding JA, Thompson RW. The utility of the Digiwalker step counter to assess daily activity patterns. Med Sci Sports Exerc. 2000;32:S481-S488.

(26) Bassey EJ, Patrick JM, Irving JM, et al. Validation of a simple walking mechanical accelerometer (pedometer) for the estimation of walking activity. Fur J Appl Physiol. 1987;56:323-330.

(27) Physical Activity and Health Fact Sheet: A Report of the Surgeon General. Atlanta, Ga: US Department of Health and Human Services, Centers for Disease Control and Prevention; 1999.

(28) Physical Activity and Health At-a-Glance: A Report of the Surgeon General. Atlanta, Ga: US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion; 2001.

(29) Aaron DJ, Kriska AM, Dearwater SR. The epidemiology of leisure physical activity in an adolescent population. Med Sci Sports Exerc. 1993;25:847-853.

(30) Aaron DJ, Kriska AM, Dearwater SR, et al. Reproducibility and validity of an epidemiologic questionnaire to assess past-year physical activity in adolescents. Am J Epidemiol. 1995;142:191-201.

(31) Centers for Disease Control and Prevention. Daily dietary fat and total food-energy intakes: NHANES III, Phase 1, 1988-91. JAMA. 1994;271:1309.

(32) Sundquist J, Winkleby MA, Pudaric S. Cardiovascular disease risk factors among older black, Mexican-American, and white women and men: an analysis of NHANES III, 1988-1994. Third National Health and Nutrition Examination Survey. J Am Geriatr Soc. 2001;49:109-116.

(33) Caspersen CJ, Christensen CC, Pollard RA. Status of the 1990 physical fitness and exercise objectives: evidence from National Health Interview Survey, 1985. Public Health Rep. 1986;101:587-592.

(34) Kruger J, Galuska DA, Serdula MK, Kohl HW. Physical activity profiles of US adults trying to lose weight: National Health Interview Survey, 1998. Med Sci Sports Exerc. 2005;37:364-368.

(35) Barnes PM, Adams PF, Schiller JS. Summary health statistics for the US population: National Health Interview Survey, 2001. Vital & Health Statistics-Series 10: Data From the National Health Survey. 2003;217:1-82.

(36) Behavioral risk factor survey coordinators: monthly estimates of leisure time physical inactivity in the United States. MMWR. 1997;46: 393-397.

(37) Healthy People 2000 Review. Hyattsville, Md: National Center for Health Statistics, Centers for Disease Control and Prevention; 1999.

(38) Guide to Physical Therapist Practice, 2nd ed. Phys Ther. 2001;81: 9-746.

(39) Montoye HJ. Use of movement sensors in measuring physical activity. Med Sci Sports Exerc. 1988;3:223-236.

(40) Laporte R, Montoye HJ, Casperson CJ. Assessment of physical activity in epidemiologic research: problems and prospects. Public Health Rep. 1985;100:131-146.

(41) Saris WH, Binkhorst RA. The use of pedometer and actometer in studying daily physical activity in man, part I: reliability of pedometer and actometer. Eur J Appl Physiol Occup Physiol. 1977;37:219-228.

(42) Saris WH, Binkhorst RA. The use of pedometer and actometer in studying daily physical activity in man, part II: validity of pedometer and actometer measuring the daily physical activity. Eur J Appl Physiol Occup Physiol. 1977;37:229-235.

(43) Schneider PL, Crouter SE, Bassett DR Jr. Pedometer measures of free-living physical activity: comparison of 13 models. Med Sci Sports Exerc. 2004;36:331-335.

(44) Shepherd E, Toloza E, McClung C, Schmalzried T. Step activity monitor: increased accuracy in quantifying ambulatory activity. J Orthop Res. 1999;17:703-708.

(45) Bassett DR Jr, Ainsworth BE, Leggett S. Accuracy of 5 pedometers for measuring distance walked. Med Sci Sports Exerc. 1996;28:1071-1077.

(46) Cyarto EV, Myers AM, Tudor-Locke C. Pedometer accuracy in nursing home and community-dwelling older adults. Med Sci Sports Exerc. 2004;36:205-209.

(47) Motl RW, McAuley E, Snook EM, Scott JA. Accuracy of two electronic pedometers for measuring steps taken under controlled conditions among ambulatory individuals with multiple sclerosis. Mult Scler. 2005;11:343-345.

(48) Macko R, Haeuber E, Shaughnessy M, et al. Microprocessor-based ambulatory activity monitoring in stroke patients. Med Sci Sports Exerc. 2002;34:394-399.

(49) Schmalzried TP, Szuszczewicz ES, Northfield MR, et al. Quantitative assessment of walking activity after total hip or knee replacement. J Bone Joint Sung Am. 1998;80:54-59.

(50) Swartz AM, Bassett DR Jr, Moore JB, et al. Effects of body mass index on the accuracy of an electronic pedometer. Int J Sports Med. 2003;24: 588-592.

(51) Ainsworth BE, Bassett DR Jr, Strath SJ, et al. Comparison of three methods for measuring the time spent in physical activity. Med Sci Sports Exerc. 2000;32:S457-S464.

(52) Melanson E, Freedson P. Validity of the Computer Science and Applications Inc (CSA) activity motor. Med Sci Sports Exerc. 1995;27: 934-940.

(53) Bassett DR Jr, Strath SJ. Use of pedometers to assess physical activity. In: Welk GJ, ed. Physical Activity Assessments for Health-Related Research. Champaign, Ill: Human Kinetics Inc; 2002:163-177.

(54) Tudor-Locke C, Myers A. Methodological considerations for researchers and practitioners using pedometers to measure physical activity. Res Q Exerc Sport. 2001;72:1-12.

(55) Rowlands AV, Eston RG, Ingledew DK. Measurement of physical activity in children with particular reference to the use of heart rate and pedometry. Sports Med. 1997;24:258-272.

(56) Bassett DR Jr, Cureton AL, Ainsworth BE. Measurement of daily walking distance: questionnaire vs a pedometer. Med Sci Sports Exerc. 2000;32:1018-1023.

(57) Tudor-Locke C, Jones GR, Myers A. Contribution of structured exercise class participation and informal walking for exercise to daily physical activity in community-dwelling older adults. Res Q Exert Sport. 2002;73:350-356.

(58) Tudor-Locke C, Bassett DR Jr. How many steps/day are enough? Sports Med. 2004;34:1-8.

(59) Sequeira MM, Rickenbach M, Wietlisbach V, et al. Physical activity assessment using a pedometer and its comparison with a questionnaire in a large population survey. Am J Epidemiol. 1995;142:989-999.

(60) Gretebeck RJ, Montoye HJ. Variability of some objective measures of physical activity. Med Sci Sports Exerc. 1992;24:1167-1172.

(61) Tudor-Locke C, Burkett L, Reis JP, et al. How many days of pedometer monitoring predict weekly physical activity in adults? Prey Med. 2005;40:293-298.

(62) Le Masurier GC, Lee SM, Tudor-Locke C. Motion sensor accuracy under controlled and free-living conditions. Med Sci Sports Exerc. 2004;36:905-910.

(63) Le Masurier GC, Tudor-Locke C. Comparison of pedometer and accelerometer accuracy under controlled conditions. Med Sci Sports Exerc. 2003;35:867-871.

(64) Bassett DR Jr. Validity and reliability issues in objective monitoring of physical activity. Res Q Exerc Sport. 2000;71:30-35.

(65) Treuth MS, Sherwood NE, Butte NF, et al. Validity and reliability of activity measures in African-American girls for GEMS. Med Sci Sports Exerc. 2003;35:532-539.

(66) Kemper HC, Bakker I, Twisk JW, van Mechelen W. Validation of a physical activity questionnaire to measure the erect of mechanical strain on bone mass. Bone. 2002;30:799-804.

(67) Tsubono Y, Tsuji I, Fujita K, et al. Validation of walking questionnaire for population-based prospective studies in Japan: comparison with pedometer. J Epidemiol. 2002;12:305-309.

(68) Crouter SE, Schneider PL, Karabulut M, Bassett DR Jr. Validity of 10 electronic pedometers for measuring steps, distance, and energy cost. Med Sci Sports Exerc. 2003;35:1455-1460.

(69) Leenders N, Sherman W, Nagaiaja H. Comparison of four methods of estimating physical activity in adult women. Med Sci Sports Exerc. 2000;32:1320-1326.

(70) Schneider PL, Crouter SE, Lukajic O, Bassett DR Jr. Accuracy and reliability of 10 pedometers for measuring steps over a 400-m walk. Med Sci Sports Exerc. 2003;35:1779-1784.

(71) Objective monitoring of physical activity: closing the gaps in the science of accelerometry. Med Sci Sports Exerc Suppl. 2005:37.

(72) Welk GJ. Use of accelerometry based activity monitors to assess physical activity. In: Welk GJ, ed. Physical Activity Assessments for Health-Related Research. Champaign, Ill: Human Kinetics Inc; 2002:125-140.

(73) Bouten C, Koekkoek K, Verduin M, et al. Effects of placement and orientation of body-fixed accelerometers on the assessment of energy expenditure during walking. Med Biol Eng Comput. 1997;35:50-56.

(74) Swartz AM, Strath SJ, Bassett DR Jr, et al. Estimation of energy expenditure using CSA accelerometers at hip and wrist sites. Med Sci Sports Exerc. 2000;32:S450-S456.

(75) Coleman KL, Smith DG, Boone DA, et al. Step activity monitor: long-term, continuous recording of ambulatory function. J Rehabil Res Dev. 1999;36:8-18.

(76) Busse ME, Pearson OR, Van Deursen R, Wiles CM. Quantified measurement of activity provides insight into motor function and recovery in neurological disease. J Neurol Neurosurg Psychiatry. 2004;75: 884-888.

(77) Brandes M, Rosenbaum D. Correlations between the step activity monitor and the DynaPort ADL-monitor. Clin Biomech. 2004;19:91-94.

(78) Silva M, Shepherd E, Jackson WO, et al. Average patient walking activity approaches 2 million cycles per year: pedometers under-record walking activity. J Arthroplasty. 2002;17:693-697.

(79) Resnick B, Nahm ES, Orwig D, et al. Measurement of activity in older adults: reliability and validity of the Step Activity Monitor. Journal of Nursing Measurement. 2001 ;9:275-290.

(80) Hartsell H, Fitzpatrick D, Brand R, et al. Accuracy of a custom-designed activity monitor: implications for diabetic foot ulcer healing. J Rehabil Res Dev. 2002;39:395-400.

(81) McDonald C, Widman J, Abresch R, et al. Utility of a step activity monitor for the measurement of daily ambulatory activity in children. Arch Phys Med Rehabil. 2005;86:793-801.

(82) Eston R, Rowlands A, Ingledew D. Validity of heart rate, pedometry, and accelerometry for predicting the energy cost of children's activities. J Appl Physiol. 1998;84:362-371.

(83) Bouten C, Verboeket-van de Veene W, Westerterp K, et al. Daily physical activity assessment: comparison between movement registration and doubly labeled water. J Appl Physiol. 1996;81:1019-1026.

(84) Welk G, Corbin C. The validity of the TriTrac-R3D activity monitor for the assessment of physical activity in children. Res Q. 1995;66: 202-209.

(85) Welk G, Blair S, Wood K, et al. A comparative evaluation of three accelerometry-based physical activity monitors. Med Sci Sports Exerc. 2000;32:S489-S498.

(86) Pols MA, Peeters PH, Kemper HC, Grobbee DE. Methodological aspects of physical activity assessment in epidemiological studies. Eur J Epidemiol. 1998;14:63-70.

(87) Matthews CE. Use of self-report instruments to assess physical activity. In: Welk GJ, ed. Physical Activity Assessments for Health-Related Research. Champaign, Ill: Human Kinetics Inc; 2002:107-123.

(88) Coleman K, Epstein L. Application of generalizability theory to measurement of activity in males who are not regularly active: a preliminary report. Res Q Exerc Sport. 1998;69:58-63.

(89) Levin S, Jacobs D, Ainsworth BE, et al. Intra-individual variation and estimates of usual physical activity. Ann Epidemiol. 1999;9:481-488.

(90) Trost SG, Pate R, Freedson PS, et al. Using objective physical activity measures with youth: how many days of monitoring are needed? Med Sci Sports Exerc. 2000;32:426-431.

(91) Bassett DR Jr, Ainsworth BE, Swartz AM, et al. Validity of four motion sensors in measuring moderate intensity physical activity. Med Sci Sports Exerc. 2000;32:S471-S480.

(92) Hendelman D, Miller K, Bagget C, et al. Validity of accelerometry for the assessment of moderate intensity physical activity in the field. Med Sci Sports Exerc. 2000;32:S442-S449.

(93) Kochersberger G, McConnell E, Kuchibhatla M, Pieper C. The reliability, validity, and stability of a measure of physical activity in the elderly. Arch Phys Med Rehabil. 1996;77:793-795.

(94) Haeuber E, Shaughnessy M, Forrester L, et al. Accelerometer monitoring of home and community based ambulatory activity after stroke. Arch Phys Med Rehabil. 2004;85:1997-2001.

(95) Welk G, Corbin C. The validity of the TriTrac-R3D activity monitor for the assessment of physical activity, II: temporal relationship among objective assessments. Res Q Exerc Sport. 1998;69:395-399.

(96) Janz K. Validation of the CSA accelerometer for assessing children's physical activity. Med Sci Sports Exerc. 1994;26:369-375.

(97) Fogelholm M, Hilloskorpi H, Laukkanen P, et al. Assessment of energy expenditure in overweight women. Med Sci Sports Exerc. 1998; 30:1191-1197.

(98) Sallis JF, Buono MJ, Roby JJ, et al. The Caltrac accelerometer as a physical activity monitor for school-age children. Med Sci Sports Exerc. 1990;22:698-703.

(99) Yusuf HR, Croft JB, Giles WH. Leisure-time physical activity among older adults: United States, 1990. Arch Intern Med. 1996;156:1321-1326.

(100) Brage S, Wedderkopp N, Franks PW, et al. Reexamination of validity and reliability of the CSA monitor in walking and running. Med Sci Sports Exerc. 2003;35:1447-1454.

(101) Freedson PS, Miller K. Objective monitoring of physical activity using motion sensors and heart rate. Res Q Exerc Sport. 2000;71:21-29.

(102) Washburn R, Chin MK, Montoye HJ. Accuracy of pedometer in walking and running. Res Q Exerc Sport. 1980;51:695-702.

(103) National Heart, Lung, and Blood Institute. Obesity Education Initiative: The Evidence Report. Bethesda, Md: National Institutes of Health; 1998.

(104) Coleman KJ, Saelens BE, Wiedrich-Smith MD, et al. Relationships between TriTrac-R3D vectors, heart rate, and self-report in obese children. Med Sci Sports Exerc. 1997;29:1535-1542.

(105) Melanson EL, Knoll JR, Bell ML, et al. Commercially available pedometers: considerations for accurate step counting. Prey Med. 2004;39:361-368.

(106) Tudor-Locke C, Pangrazi RP, Corbin C, et al. BMI-referenced standards for recommended pedometer-determined steps/day in children. Prey Med. 2004;38:857-864.

* Yamax USA Inc, 4940 Broadway, Suite 230-A, San Antonio, TX 78209.

([dagger]) Velcro USA Inc, 406 Brown Ave, Manchester, NH 03103.

([double dagger]) ActiGraph LLC, 709 Anchors St, Fort Walton Beach, FL 33248.

([section]) Cyma Corp, 6405 218th St SW, Suite 100, Mountlake Terrace, WA 98043-2180.

([parallel]) Professional Products, 5708 Odana Rd, Madison, WI 53719.

(#) Premier Partners Marketing Inc, Boca Raton, FL 33432.

JE Berlin, PT, MPT, is Research Associate and Instructor, Department of Physical Therapy, University of Pittsburgh, 6035 Forbes Tower, Pittsburgh, PA 15260 (USA). Address all correspondence to Ms Berlin at: [e-mail].

KL Storti, MS, MPH, is Research Associate, Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh.

JS Brach, PT, PhD, GCS, is Assistant Professor, Department of Physical Therapy, University of Pittsburgh.

All authors provided concept/idea/project design and writing. Ms Storti and Dr Brach provided consultation (including review of manuscript before submission).

Table.
Characteristics of Activity Monitors

                          Predometer         Accelerometer

Monetary cost             Low ($10-$200)     Mid to high
                                             Computer interface=
                                               $300-$600
                                             Unit=$300-$600
Primary outcome           Steps              Counts
Activity
  Type                    Ambulatory         Lower extremity and trunk
  Frequency               No                 Yes
  Duration                No                 Yes
  Intensity               No                 Yes
Participant burden (a)    Low                Low
Investigator burden (b)   Low                Moderate
Data acquisition          Hand transcribed   Computer downloaded
Placement                 Waist              Waist, wrist (least
                                               preferred), or ankle
Central obesity           Yes                Possibly if worn on
  interferes with                              waist; not an issue if
  recording of activity                        worn on wrist or ankle

(a) Participant burden-time and effort the participant must put
forth during the measurement period (ie, taking the device on
and off).

(b) Investigator burden-technical aspects of the measurement
instrument such as data processing (ie, processing data to obtain
outcome of interest).