Methodologic issues in objective assessment of activity in community samplesBrian Smith1, Diane Lameira1, Lihong Cui1, Haochang Shou2, Vadim Zipunnikov3, Ciprian Crainiceanu3, Kathleen Merikangas1

1Genetic Epidemiology Research Branch, Intramural Research Program, NIMH, Bethesda, MD 208922Biostatistics and Epidemiology Department, University of Pennsylvania School of Medicine, Philadelphia, PA 191043Department of Biostatistics, Johns Hopkins University, Baltimore, MD 21205

Address: 35 Convent Drive, Building 35A, Room 2E480 (MSC 3720), Bethesda, MD 20814 Phone: 301-402-6395 Email: brian.smith4@nih.gov

Background

Objectives

• Physical activity has been linked to general health, and to mental health in particular.

• Mobile technologies, including a wide range of actigraphy monitors (Table 1) can assist in objectively measuring physical activity.

• Differences in procedural and analytical methodologies in studies measuring physical activity (Table 2) make it difficult to review the aggregate evidence.

• To summarize specifications of available devices for recording of actigraphy and health.

• To review procedural and analytical methods in existing studies of mood disorders.

• To illustrate data collection methods in a large community based family study of comorbidity of mood disorders and medical disorders.

Sample

0

100

200

300

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800

900

Act

ivit

y

Time

Actiwatch vs. GENEActiv

Average of Actiwatch Activity Counts Average of GENEActiv Sum of Vector Magnitudes

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20

40

60

80

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120

Ave

rage

Su

m o

f V

ect

or

Mag

nit

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es

(SV

Mgs

)

Date

Dominant vs. Non-Dominant

Average of Non-Dominant Wrist Average of Dominant Wrist

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50

100

150

200

250

Act

ivit

y

Date

Actiwatch vs. GENEActiv

Average of Actiwatch Activity Counts Average of GENEActiv Sum of Vector Magnitudes

• Community-based family study in the greater Washington, DC metropolitan area.

• 339 participants- Sex: 137 male, 202 female- Age: mean= 41.9, range=10-84- BMI: mean= 27.2, SD=7.1

Methods• The Actiwatch® Score Minimitter was worn on the

non-dominant wrist for two weeks to acquire data from at least one weekend.

• To examine measurement accuracy and continuity of different devices, we compared data obtained from the Actiwatch simultaneously with another actimetrymonitor, GENEActiv® (ActivInsights) in a small subset of study participants.

Results• There were discrepancies in measured activity

between the Actiwatch and GENEActiv devices (Figure 2A-B).

• Differences in activity levels exist when comparing dominant vs. non-dominant wear (Figure 2C).

• Activity results vary for weekend vs. weekday (Figure 2D), age (Figure 2E), and time of day (Figure 2D-E).

Conclusions

• Standardization of procedural and statistical methodology is critical for the emerging field of actimetry research.

• Data collection spanning one weekend is necessary to acquire representative information on activity patterns.

• Wrist-worn activity monitors should be placed on non-dominant wrist for more conservative estimate of physical activity.

Name Manufacturer Size Weight MemoryBattery (Battery Life)

Body Placement

Maximum Recording Time

Cost per Unit

WaterproofData Type (Raw or Processed)

GENEActiv Original

ActivInsights(UK)

43mm x 40mm x 13mm

16g 0.5 GBRechargeable lithium polymer (45 days)

Wrist, Waist, Ankle

45 days $247 YesTri-axial (Raw)

Actiwatch Score Minimitter

Phillips Respironics (Bend, OR)

37mm x 35mm x 12mm

25g 32 KB CR 2025 (90 days)Wrist, Waist, Ankle

22.4 days $1,645 NoUni-axial (Raw)

wGT3X-BTActiGraph (Pensacola, FL)

46mm x 33mm x 15mm

19g 2 GBRechargeable lithium ion (25 days)

Wrist, Waist, Ankle, Thigh

120 days $225 ResistantTri-axial (Raw)

Motionlogger Watch

Ambulatory Monitoring (Ardsley, NY)

55mm x 45mm x 18mm

65g 2 MB DL2450 (30 days) Wrist N/A $1,295 Resistant N/A

Fitbit ZipFitbit, Inc. (San Francisco, CA)

35.5mm x 28mm x 9.65mm

8g 256 KBCR 2025 (4-6 months)

Waist, Chest 7 days $60 NoTri-axial (Processed)

Nike FuelbandNike, Inc. (Beaverton, OR)

Varies 27-32g 256 KBRechargeable lithium ion (4 days)

Wrist 4 days $79 ResistantTri-axial (Processed)

Study Sample Population Device Used Data Type Body location Length of wear

Ankers and Jones (2009) Bipolar Actiwatch Uni-axial non-dominant wrist 7 days

Gonzalez et al. (2014) Bipolar Motionlogger Tri-axial non-dominant wrist 7 days

Indic et al. (2011) Bipolar Actiwatch Score Minimitter Uni-axial non-dominant wrist 3-7 days

Harvey et al. (2005) Bipolar Motionlogger Uni-axial non-dominant wrist 8 days

Jones et al. (2005) Bipolar Actiwatch Uni-axial non-dominant wrist 7 days

Janney et al. (2013) Bipolar Actigraph Uni-axial waist 7 days

Krane-Gartiser et al. (2014) Bipolar Actiwatch Spectrum Uni-axial wrist of choice 1 day

St-Amand et al. (2013) Bipolar Actiwatch Score Minimitter Uni-axial non-dominant wrist 14 days

McKenna et al. (2014) Bipolar Actiwatch Spectrum Uni-axial left wrist 7 days

Faurholt-Jepsen (2012) Bipolar and Depression Actiheart Uni-axial chest 3 days

Todder et al. (2009) Depression Actiwatch Uni-axial non-dominant wrist 11 days

Berle et al. (2010) Schizophrenia Actiwatch Uni-axial right wrist 14 days

Winkler et al. (2005)Seasonal Affective Disorder

Actiwatch Uni-axial non-dominant wrist 28 days

Naslund et al. (2015)Schizophrenia, Bipolar, Depression

Fitbit, Nike Tri-axial wrist of choice 80-133 days

Hauge et al. (2011)Schizophrenia and Depression

Actiwatch Uni-axial right wrist 14 days

Table 2: Actigraphy studies on sample populations with mood disorders in the past decade.

Future Directions

• Future studies should utilize raw tri-axial data from easy-to-use activity monitors.

• Covariates such as age, time of day, and weekend vs. weekday that influence both activity and health outcomes should be included in analyses of activity.

• It may be possible to calibrate measures across devices that provide raw triaxial data.

Figure 2: (A-B) Large differences in measured activity data from one patient wearing both Actiwatch and GENEActiv devices shows that direct comparison of data obtained from two different brands cannot be done unless a standard measurement is in place, such as raw tri-axial vector magnitudes; (C) Wearing the GENEActiv device on the dominant wrist results in a higher magnitude of activity.

A

Figure 1: Actiwatch (left) and GENEActiv (right) devices.

B

C

Weekday vs. Weekend Activity

Age and Time of Day Activity

Time of Day

Time of Day

A

B

Figure 3: Data from 339 participants wearing Actiwatch monitors highlight differences in measured activity on weekdays versus weekends (A), as well as differences across ages and differences in time of day (B). Investigations into activity differences based on other covariates such as BMI, season, and medication use are ongoing.

Table 1: Comparison of select commercially-available* actigraphy monitors. *As of February, 2015

This research is supported by NIH Grant number: 1 ZIA MH002804-12 GEB