Method

Are Personal Characteristics Correlated with Measurement Error in Wearable Activity Monitors?

Zakkoyya H. Lewis BS, Elizabeth J. Lyons PhD, MPH, Sara Nowakowski PhD, MS, Maria C. Swartz PhD, MPH

The University of Texas Medical Branch, Galveston TX

Background

•Wearable activity monitors are widely used commercially and in behavioral interventions 1,2

•Popular models, such as Fitbit and Jawbone, show acceptable validity for measuring steps 3

•Individual characteristics may affect their accuracy •The purpose of this secondary data analysis was to identify personal characteristics that are correlated to bias error in Fitbit Flex, Jawbone UP24, and Misfit Shine.

•Significant personal characteristics are not correlated across study protocols•Several personal characteristics were approaching significance and may be correlated with measurement error in a larger sample•Bias error between devices were significantly correlated suggesting that device accuracy may be driven by another common, unmeasurable variable

Conclusions

•Participants (n=40) were recruited through University announcements to participate in a monitor validation study with a lab and lifestyle protocol•The lab protocol consisted of three 5-minute walking sessions (overland self-paced, 2.5 and 3.5 mph on a treadmill)

•Criterion measure: direct observation•The lifestyle protocol required participants to wear all three devices for 7-days

•Criterion measure: Actigraph wGT3X-BT mounted on the waist

•Personal characteristics included age, gender, body mass index (BMI), weight, race, overland cadence, and average cadence•Cadence was calculated from the number of steps per minute during overland walking and the average number of steps per minutes across all three walking sessions•Bias error (mean absolute percent error) was calculated from the measured number of steps for each device against the criterion measure

Results cont. •Average cadence was significantly correlated with Fitbit Flex lifestyle bias error and cadence (overland and average) were significantly correlated with Misfit lab bias error•No other measured personal characteristics impacted bias•UP24 bias error during the lifestyle protocol was significantly correlated with the Fitbit Flex (r=0.536, p<0.01) and Misfit lifestyle bias error (r=0.469, p<0.01).

This study was funded by the UTMB Claude D. Pepper Older Americans Independence Center (P30AG024832) and UTMB’s Sealy Center on Aging. ZHL is supported by a Predoctoral Fellowship Grant from the American Heart Association (16PRE27090012). EJL was supported by a Mentored Research Scholar Grant in Applied and Clinical Research, MRSG-14-165-01-CPPB, from the American Cancer Society and by a Beginning Grant-in-Aid, 13BGIA17110021, from the American Heart Association. SN was supported by a career development award from the National Institute of Nursing Research, National Institutes of Health (K23NR014008). MCS is supported by the Cancer Prevention and Research Institute of Texas, Comparative Effectiveness Research on Cancer in Texas (RP140020) and the National Institute on Disability, Independence Living and Rehabilitation Research, Department of Education (90AR5009). The funding agencies had no role in the study design; data collection, management, analysis, or interpretation; and does not hold ultimate authority over these activities.

Participants Characteristics(N=40)

Age (yr) Female (%)

BMI (kg/m2)

Weight (kg)

White (%)

Overland cadence

(steps/min)

Average cadence

(steps/min)

41.98 (14.03) 50% 27.62

(6.24)79.0

(15.70) 65.9% 115.42 (8.30)

114.18 (8.41)

Zakkoyya Lewis, BS, ATCPhD Candidate

American Heart Association Fellow301 University Blvd, Galveston, TX,

77551Division of Rehabilitation Sciences

O 409.772.2576E zalewisp@utmb.edu

Monitor Bias Error (%)

Fitbit Flex UP24 Misfit

Overland walking a -7.2±17.5 -1.1±12.1 +3.6±18.5

2.5 mph treadmill a -5.9±8.2 -2.5±11.2 -4.7±17.23.5 mph treadmill a -7.5±9.4 -2.1±2.1 -0.6±12.7

Lab protocol (mean) a -8.4±16.3 -1.9±4.2 -0.5±11.4Lifestyle protocol b +11.91±16.6 -7.33±15.1 -8.76±10.5

a compared to direct observation; b compared to waist-worn Actigraph

Pearson CorrelationFitbit Flex

lab protocolc

UP24 lab protocolc

Misfit lab

protocolc

Fitbit Flex

lifestyle protocol

UP 24 lifestyle protocol

Misfit lifestyle protocol

Age -0.124 0.068 -0.209 -0.015 -0.088 -0.019Gender -0.243 -0.059 -0.004 -0.200 0.055 -0.079

BMI 0.004 -0.028 -0.050 -0.271ᵻ -0.112 0.107Weight 0.129 0.037 -0.026 -0.208 -0.189 0.072Race 0.150 0.042 0.202 0.021 0.201 0.278ᵻ

Overland cadence -0.170 0.074 -0.314* 0.225 0.218 -0.005Average cadence -0.032 -0.015 -0.382* 0.429* 0.299ᵻ -0.007

*significant correlation (p<0.05); ᵻ approaching significant (p<0.10)c values taken from the mean bias error across all three lab walking

tests

References

Acknowledgements

1. Lewis, Zakkoyya H., et al. "Using an electronic activity monitor system as an intervention modality: A systematic review." BMC public health 15.1 (2015):

2. Cadmus-Bertram, Lisa A., et al. "Randomized trial of a Fitbit-based physical activity intervention for women." American journal of preventive medicine 49.3 (2015): 414-418.

3. Evenson, Kelly R., Michelle M. Goto, and Robert D. Furberg. "Systematic review of the validity and reliability of consumer-wearable activity trackers."International Journal of Behavioral Nutrition and Physical Activity 12.1 (2015): 1-22.

Results