gotta catch’em all! pokémon go and physical activity · manuscript id bmj.2016.035580.r1 article...

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Gotta Catch’em All! Pokémon GO and Physical Activity: Difference in Differences Study

Journal: BMJ

Manuscript ID BMJ.2016.035580.R1

Article Type: Christmas

BMJ Journal: BMJ

Date Submitted by the Author: 07-Nov-2016

Complete List of Authors: Howe, Katherine; Harvard T.H. Chan School of Public Health, Epidemiology; Harvard T.H. Chan School of Public Health, Social and Behavioral Sciences Suharlim, Christian; Harvard T.H. Chan School of Public Health, Center for Health and Decision Science, Department of Health Policy and Management

Ueda, Peter; Harvard T.H. Chan School of Public Health, Department of Global Health and Population Howe, Daniel; n/a Kawachi, Ichiro; Harvard School of Public Health, Department of Society Human Development and Rimm, Eric; HSPH

Keywords: physical activity, Pokemon Go

https://mc.manuscriptcentral.com/bmj

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Gotta Catch’em All! Pokémon GO and Physical Activity: Difference in

Differences Study

Katherine B Howe, MPH1,2*

; Christian Suharlim, MD MPH3*

; Peter Ueda, MD PhD4,5*

; Daniel

Howe, BA; Ichiro Kawachi, MBChB PhD2; Eric B. Rimm, ScD

1,6,7

1. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA

2. Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public

Health, Boston, MA

3. Center for Health and Decision Science, Department of Health Policy and Management,

Harvard T.H. Chan School of Public Health, Boston, MA

4. Department of Global Health and Population, Harvard T.H. Chan School of Public

Health, Boston, MA

5. Clinical Epidemiology Unit, Institute of Medicine, Solna, Karolinska Institutet, Sweden

6. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA

7. Channing Division of Network Medicine, Department of Medicine, Brigham and

Women’s Hospital, Harvard Medical School, Boston, MA

*These authors contributed equally to this work.

Correspondence to: Katherine Howe [email protected]

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Abstract:

Objectives To estimate the effect of playing Pokémon GO on the number of steps taken per day

up to 6 weeks after installing the game.

Design Cohort study using online survey data.

Participants Amazon Mechanical Turk survey participants (n=1,182) residing in the US, aged

18 to 35 years and using iPhone 6 series smartphones.

Main outcome measures Number of daily steps taken each of the four weeks before and six

weeks after installation of Pokémon GO, automatically recorded in the Health application of the

iPhone 6 series smartphones, and reported by the participants. A difference-in-difference

regression model was used to estimate the change in daily steps in Pokémon players compared

with non-players.

Results 560 (47.4%) of the survey participants reported playing Pokémon Go and walked on

average 4,256 steps (SD=2,697) per day in the four weeks prior to installation of the game. The

difference-in-difference analysis showed that the daily average steps increased for Pokémon Go

players during the first week of installation by 955 additional steps (95% CI = 697-1,213), and

then this increase gradually attenuated over the subsequent five weeks. By the sixth week after

installation, daily steps had gone back to pre-installation levels. There was no significant effect

modification of Pokémon GO by sex, age, race group, weight status, or walkability of the area of

residence.

Conclusions Pokémon Go was associated with an increase in the daily number of steps after

installation of the game. However, the association was moderate and was no longer observed

after six weeks.

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Introduction

Pokémon GO is an augmented reality game in which players search real-world locations for

cartoon characters appearing on their smartphone screen. Since its launch in July 2016, the game

has been downloaded over 500 million times worldwide. Because walking is encouraged while

playing, Pokémon GO has been suggested to increase physical activity and improve public health,

but these claims have been based on anecdotal evidence.[1–3]

We used an online survey and automatically recorded step count data from iPhone devices to

estimate the change in daily steps following installation of Pokémon GO among young adults in

the US.

Methods

Study population

We conducted an online survey using the Amazon Mechanical Turk (MTurk), between August

1st and 31st, 2016. MTurk is a website for recruitment of online workers who receive a small

compensation for completing tasks including responding to surveys. It is widely used for

research purposes: it allows for fast recruitment of diverse study populations and the reliability of

the answers is similar to that of traditional survey methods.[4–6]

We recruited survey participants who were aged 18 to 35 years, resided in the US, and used an

iPhone 6 series smartphone, because these devices automatically record the number of steps

taken while carrying the device. Participants were paid 2 USD for completion of the survey. Of

the 2,225 individuals who responded to the survey, we excluded 115 participants who had

downloaded Pokémon GO but not achieved a “trainer level” of 5 or more which takes around 2 h

of walking to reach. At this level, functions integral to the game are unlocked, including joining

a team and competing for Pokemon Gyms. We further excluded 923 participants who did not

complete the full survey likely due to the complexities of multiple screen captures necessary for

participation. Our final study population consisted of 1,182 individuals.

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Covariates

Survey participants were asked about their zip code of residence, education level, household

income, marital status, and weight and height from which body mass index (BMI) in kg/m2 was

calculated. Participants who reported that they played Pokémon Go were asked to upload a

screenshot (picture of the screen content) of their Pokémon Go application which shows the

installation date. We matched the zip code of residence with a validated neighborhood

walkability index (Walk ScoreⓇ), which is categorized into four groups (Car-Dependent,

Somewhat Walkable, Very Walkable, and Walker’s Paradise).[7,8]

Participants were asked to upload screenshots showing their number of steps/day while carrying

their iPhone, for each day during the two months preceding the date of study participation. This

information is recorded by default in the ‘Health’ application of iPhone 6 series, using the

device’s built-in accelerometer.

Statistical analyses

We compared the average number of steps taken per day for each of the four weeks prior to

installing the game vs. the steps during each of the six weeks after installation in Pokémon

players and non-players respectively. For non-players, the number of steps was compared before

and after the median date of installation among Pokémon-playing participants. To examine the

causal association between Pokémon GO and daily steps, we conducted a difference-in-

difference analysis. This method attempts to mimic an experimental research design by

comparing the change in the outcome over time in the treated vs. control group, under the

assumption that the differences between the groups would have remained constant under no

treatment. We used a multivariate regression model; the estimate of change in steps after

Pokémon GO was obtained from interaction indicators for Pokémon GO players and each week

after installation of the game. The model also adjusted for time-invariant differences between

players and non-players, and fluctuations in steps across weeks before and after installation. We

calculated robust standard errors to account for the repeated measurements within the same

individuals.

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In separate models, we assessed effect modification of Pokémon GO by sex, age group (18-24

years and 25-35 years), household income (


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associated with an increase in steps of 955 (95% CI: 697 - 1,213) during the first week, the effect

was gradually attenuated over the subsequent weeks and by week six it was not significant (130

[-593 – 851]) (Figure 2 and Supplementary Table 1).

The analyses on effect modification of Pokémon GO by baseline variables showed no significant

interaction between the variables, Pokémon GO and week since installation of the game.

(Supplementary Table 2). Adjusting for differences in time trends in steps by baseline variables

did not materially affect the results (Supplementary Table 3).

Discussion

In this study on the impact of Pokémon GO on physical activity in young US adults, we found

that the game was associated with an increase in daily steps of 955 (95% CI= 697-1,213) in the

first week after installation. The association was attenuated during the subsequent weeks and was

no longer significant by the sixth week. Assuming steps of 0.8 m at a pace of 4 km/h,[11] the

change in steps in the first week would translate into 11 minutes of additional walking per day,

which is around half of the WHO recommendation of 150 minutes/week.[12]

Pokémon GO has been suggested to improve public health by promoting physical activity.[1–3]

Our results, however, indicate that the health impact of Pokémon GO may be moderate in our

study population. Interventions designed to increase walking typically increase steps by 2500

steps/day.[13] Even if smaller amounts of physical activity may also be important for health

outcomes,[12,14] the increase in steps from Pokémon GO, as with many physical activity

interventions,[15] was not sustained over time. Pokémon GO may also entail risks such as

injuries and traffic accidents.[16,17]

Strengths of this study include the use of automatically recorded steps data from the iPhone

which has been shown to accurately track step counts,[18] validation of Pokémon GO

installation and date using screenshots, and a study population from a wide range of socio-

demographic groups and regions of the US.

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Our study has limitations. First, steps were only recorded when the iPhone was carried. This may

lead to overestimation of the effect of Pokémon Go because physical activity could occur when

not carrying the phone (e.g. football) whereas all Pokémon-related activity was recorded. Second,

although our results did not change materially when adjusting for a number of baseline variables,

the difference-in-difference analysis is susceptible to confounding from changes in daily steps

that were unique to Pokémon-players but independent of Pokémon GO. Third, our study

population was limited to iPhone-users in the US, and MTurk workers are not representative of

the general population, e.g. in terms of sex (overrepresentation of women), political views and

personality.[6] Generalizability of our results may therefore be limited.

While the association between Pokémon GO and change in steps was short-lived in our study,

there may be individuals who sustain increased physical activity through the game. The effect of

Pokémon GO on physical activity may also be different in children which were not included in

our study. There may also be other potential benefits, such as increased social connectedness and

mood improvement.

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What is already known on this topic

● Pokémon GO is an augmented reality game overlaying graphics on the real world using

the camera function of smartphones.

● The game has been downloaded over 500 million times, and it is available in over 100

countries and regions.

● The game requires walking and has been suggested to increase physical activity.

What this study adds

● We estimated the changes in physical activity associated with playing Pokémon GO.

● Pokémon GO was associated with an increase in daily number of steps by 955 (95%

confidence interval = 697-1,213) steps during the first week after installation of the game.

The increase was attenuated with time and was no longer significant by the sixth week

after installation.

● Pokémon GO was associated with a moderate increase in daily steps that was not

sustained over time. The impact of Pokémon GO on physical activity in the broad

population may be limited.

References

1 McCartney M. Margaret McCartney: Game on for Pokémon Go. BMJ 2016;354.

2 Is Pokémon Go the answer to America’s obesity problem? Guardian. 2016 Jul 13.

3 University of Leicester. Press release: Pokémon Go could ease type 2 diabetes burden. 25

Jul 2016.

4 Berinsky AJ, Huber GA, Lenz GS. Evaluating online labor markets for experimental

research: Amazon.com’s mechanical turk. Polit Anal 2012;20:351–68.

doi:10.1093/pan/mpr057

5 Paolacci G, Chandler J, Ipeirotis PG. Running experiments on amazon mechanical turk.

Judgm Decis Mak 2010;5:411–9. doi:10.2139/ssrn.1626226

6 Paolacci G, Chandler J. Inside the Turk: Understanding Mechanical Turk as a participant

pool. Curr Dir Psychol Sci 2014;23:184–8. doi:10.1177/0963721414531598

7 Carr LJ, Dunsiger SI, Marcus BH. Validation of Walk Score for estimating access to

walkable amenities. Br J Sports Med 2011;45:1144–8. doi:10.1136/bjsm.2009.069609

8 Duncan DT, Aldstadt J, Whalen J, et al. Validation of walk score for estimating

neighborhood walkability: an analysis of four US metropolitan areas. Int J Environ Res

Public Health 2011;8:4160–79. doi:10.3390/ijerph8114160

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9 Wooldridge J. Econometric analysis of cross section and panel data. MIT Press 2002.

10 StataCorp. Stata statistical software: release 12. StataCorp LP, 2012. College Town, TX.

11 Knoblauch R, Pietrucha M, Nitzburg M. Field Studies of Pedestrian Walking Speed and

Start-Up Time. Transp Res Rec J Transp Res Board 1996;1538:27–38. doi:10.3141/1538-

04

12 WHO: Global recommendations on physical activity for health. World Health

Organisation. 2010.

13 Bravata DM, Smith-Spangler C, Sundaram V, et al. Using Pedometers to Increase

Physical Activity and Improve Health. JAMA 2007;298:2296.

doi:10.1001/jama.298.19.2296

14 Tanasescu M. Exercise Type and Intensity in Relation to Coronary Heart Disease in Men.

JAMA 2002;288:1994. doi:10.1001/jama.288.16.1994

15 Teixeira PJ, Carraça E V, Markland D, et al. Exercise, physical activity, and self-

determination theory: A systematic review. Int J Behav Nutr Phys Act 2012;9:78.

doi:10.1186/1479-5868-9-78

16 Ayers JW, Leas EC, Dredze M, et al. Pokémon GO—A New Distraction for Drivers and

Pedestrians. JAMA Intern Med 2016;11:e0159885. doi:10.1001/jamainternmed.2016.6274

17 Serino M, Cordrey K, McLaughlin L, et al. Pokémon Go and augmented virtual reality

games: a cautionary commentary for parents and pediatricians. Curr Opin Pediatr

2016;28:673–7. doi:10.1097/MOP.0000000000000409

18 Case MA, Burwick HA, Volpp KG, et al. Accuracy of Smartphone Applications and

Wearable Devices for Tracking Physical Activity Data. JAMA 2015;313:625.

doi:10.1001/jama.2014.17841

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Contributions: KBH, CS, and PU contributed equally and are co-first authors. KBH, CS, and DH

conceived and designed the project and collected data. CS, PU, and KBH analyzed the data.

KBH, CS, PU, and DH wrote the first draft of the manuscript. All authors contributed to the

manuscript. IK and EBR provided methodological guidance and financial support for data

collection. EBR is the guarantor.

Funding: This research received no specific grant from any funding agency in the public,

commercial, or not-for-profit sectors.

Competing interests: All authors declare: no financial relationships with any organizations that

might have an interest in the submitted work and no other relationships or activities that could

appear to have influenced the submitted work.

Ethical approval: This study received institutional review board exemption approval on August

1st 2016 from the Harvard T.H. Chan School of Public Health (Protocol # IRB 16-1243).

Transparency: The manuscript’s guarantor affirms that the manuscript is an honest, accurate, and

transparent account of the study being reported; that no important aspects of the study have been

omitted; and that any discrepancies from the study as planned have been explained

Data sharing: Statistical code and dataset are available from the corresponding author.

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Table 1 Characteristics of Pokemon Go-playing and non-playing survey participants. Data are shown in number (%) unless

otherwise indicated.

Not Players (n=622) Pokemon GO Players (n=560)

Date for Pokemon Go installation,

median (IQR) . July 8th (July 7 - 11th)

Mean age in years (SD) 27.3 (4.5) 25.6 (4.3)

Age group

18-24 years 188 (30.2) 242 (43.2)

25-35years 434 (69.8) 318 (56.8)

Sex

Female 453 (72.8) 390 (69.6)

Race

Asian 32 (5.1) 38 (6.8)

White 491 (78.9) 430 (76.8)

Black 68 (10.9) 36 (6.4)

Other 31 (5.0) 56 (10.0)

Education

High school or less 29 (4.7) 51 (9.1)

Some university 208 (33.5) 237 (42.5)

College degree 267 (43) 207 (37.1)

Graduate/professional degree 117 (18.8) 63 (11.3)

Marital status

Single 336 (54) 365 (65.2)

Married/cohabitating 256 (41.2) 174 (31.1)

Divorced/separated/widowed 30 (4.8) 21 (3.8)

Household income


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Figure 1 Average number of daily steps and 95% confidence intervals by week before and after installation of Pokemon

GO.

Average daily steps by week for non-Pokemon players are compared before and after the median installation date among

players (July 8th 2016)

2000

3000

4000

5000

6000

7000

Average steps per day

-4 -3 -2 -1 1 2 3 4 5 6

Week since installation

Pokemon Go players Non-players

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Figure 2 Average daily steps before and after installation of Pokemon GO in Pokemon GO players and non-players.

Among non-players, steps were compared before and after the median date of installation of the game among Pokemon GO-

playing participants. Confidence intervals are estimated using a difference-in-difference regression model. The full model is

shown in Appendix Table 1.

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nlySupplementary Table 1 Results from the difference-in-difference model used to estimate the

association between Pokemon GO playing and change in daily steps for each week after installation

of the game.

* Week 1 represents the first week since installation of Pokemon GO. Week -4 represents four weeks before

installation of the game.

Coefficient (95% CI)

Pokemon Go player (ref = non-player) 114 (-212 to 440)

Week (ref= week -4)*

Week -3 60 (-64 to 184)

Week -2 -88 (-224 to 48)

Week -1 -64 (-200 to 73)

Week 1 -111 (-300 to 78)

Week 2 -190 (-363 to -17)

Week 3 -130 (-314 to 54)

Week 4 -225 (-422 to -28)

Week 5 -552 (-785 to -320)

Week 6 -425 (-1065 to 216)

Interaction term between Pokemon GO and week

since installation of the game*

Week 1 955 (697 to 1213)

Week 2 906 (647 to 1164)

Week 3 544 (280 to 808)

Week 4 446 (169 to 722)

Week 5 381 (43 to 720)

Week 6 130 (-593 to 853)

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Confidential: For Review Only

Supplementary Table 2 Interaction terms between baseline variables, Pokemon GO and week since installation of the game. Separate regression models have been

used for each baseline variable with average daily steps per week as the dependent variable and the following independent variables: the baseline variable, week (four

weeks prior to Pokemon GO installation, and six weeks after installation), and interaction terms between week since installation of Pokemon GO and Pokemon GO,

and the interaction terms shown in the table.

Interaction term with Pokemon Go, baseline variable, and week since installation of the game

Baseline variable Week 1 Week 2 Week 3 Week 4 Week 5 Week 6

Sex (ref = men) Women 47 (-602 to 696) 5 (-643 to 653) 177 (-461 to 815) 436 (-196 to 1069) 110 (-581 to 801) 473 (-356 to 1303)

Age group (ref = 18-24 years) 25-35 years 5 (-564 to 574) 57 (-524 to 638) 89 (-466 to 643) -56 (-614 to 502) 458 (-141 to 1057) 389 (-345 to 1122)

Race (ref = Asian) White -608 (-1658 to 442) -1079 (-2271 to 112) -802 (-2013 to 409) -1038 (-2235 to 159) -1214 (-2541 to 112) -477 (-2045 to 1092)

Black -632 (-1917 to 653) -772 (-2201 to 657) -662 (-2131 to 806) 17 (-1525 to 1559) -794 (-2555 to 968) -1153 (-2935 to 629)

Other -807 (-2166 to 552) -245 (-1615 to 1125) -195 (-1654 to 1264) -318 (-1939 to 1303) 289 (-1546 to 2125) 4440 (3800 to 5081)

Household income (ref = /=100k 70 (-703 to 843) 209 (-630 to 1048) 166 (-636 to 969) 143 (-633 to 919) 122 (-807 to 1050) 586 (-481 to 1653)

Education (ref= no college degree) College degree or

higher

48 (-530 to 626) 54 (-532 to 640) 1 (-556 to 559) 436 (-122 to 995) 221 (-384 to 826) 94 (-635 to 823)

Weight status (ref= BMI/=25 kg/m2 -340 (-928 to 247) -307 (-904 to 291) -11 (-575 to 554) -285 (-854 to 284) 327 (-284 to 937) 461 (-268 to 1191)

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Walkability index (ref=

Car-dependent or Somewhat

walkable)

Very walkable or

Walker's Paradise

192 (-685 to 1069) -280 (-1056 to 497) -339 (-1073 to 394) -117 (-935 to 701) -87 (-963 to 789) -334 (-1332 to 664)

Urbanity (ref=rural) Suburban 268 (-648 to 1183) 374 (-538 to 1285) 488 (-368 to 1343) 472 (-435 to 1378) 667 (-262 to 1597) 234 (-888 to 1357)

Urban -198 (-829 to 433) 152 (-487 to 790) 157 (-452 to 765) 144 (-472 to 759) 321 (-338 to 981) 365 (-451 to 1180)

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nlySupplementary Table 3 Regression analysis using average daily steps per week as the dependent variable and

adjusted for baseline covariates and including interaction terms between baseline variables in week since

installation of Pokemon Go. Interaction terms between Pokemon Go and week since installation of the game show

the difference-in-difference in daily steps after Pokemon Go installation in players vs. non-players.

Variable Coefficient (95% CI)

Baseline variables Sex (ref = men) Women -2009 (-2392 to -1626)

Age group (ref = 18-24 years) 25-35 years 51 (-285 to 387)

Race (ref = Asian) White 398 (-262 to 1057)

Black -273 (-1066 to 521)

Other 32 (-729 to 792)

Household income (ref = /=100k 55 (-377 to 487)

Marital status (ref = single or divorced) Married/partnered -463 (-837 to -89)

Region (ref=Midwest) Northeast 47 (-440 to 533)

South -483 (-907 to -59)

West -163 (-556 to 231)

Education (ref= no college degree) College degree or higher 352 (33 to 671)

Weight status (ref= BMI/=25 kg/m2 -533 (-860 to -206)

Walkability index (ref= Car-dependent or

Somewhat walkable)

Very walkable or Walker's

Paradise

1002 (509 to 1495)

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nlyUrbanity (ref=rural) Suburban 222 (-191 to 635)

Urban 360 (-113 to 833)

Pokemon Go player (ref = non-player) Pokemon player 66 (-244 to 376)

Week (ref =Week -4)* Week -3 66 (-58 to 190)

Week -2 -91 (-227 to 45)

Week -1 -67 (-202 to 69)

Week 1 175 (-649 to 999)

Week 2 618 (-174 to 1409)

Week 3 803 (17 to 1589)

Week 4 580 (-285 to 1444)

Week 5 176 (-932 to 1283)

Week 6 -296 (-2066 to 1473)

Interaction terms

with week since

Pokemon Go

installation

Sex (ref = men) Female sex Week 1 216 (-91 to 522)

Week 2 33 (-275 to 341)

Week 3 -95 (-412 to 222)

Week 4 137 (-198 to 471)

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nlyWeek 5 -29 (-449 to 392)

Week 6 -231 (-1435 to 973)

Age group (ref =

18-24 years)

25-35 years Week 1 -1 (-315 to 312)

Week 2 -64 (-363 to 234)

Week 3 -149 (-457 to 159)

Week 4 -103 (-416 to 209)

Week 5 175 (-179 to 529)

Week 6 588 (-508 to 1683)

Race (ref = Asian) White Week 1 54 (-575 to 684)

Week 2 -527 (-1157 to 103)

Week 3 -504 (-1124 to 116)

Week 4 -793 (-1495 to -91)

Week 5 -908 (-1800 to -17)

Week 6 -222 (-1505 to 1061)

Black Week 1 3 (-671 to 677)

Week 2 -152 (-845 to 542)

Week 3 -358 (-1047 to 331)

Week 4 -88 (-952 to 776)

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nlyWeek 5 -448 (-1449 to 553)

Week 6 -465 (-1849 to 918)

Other Week 1 262 (-499 to 1022)

Week 2 -432 (-1191 to 327)

Week 3 -150 (-971 to 671)

Week 4 -142 (-1030 to 747)

Week 5 -339 (-1382 to 705)

Week 6 85 (-1245 to 1415)

Household income

(ref = /=100k Week 1 -311 (-695 to 73)

Week 2 -193 (-549 to 163)

Week 3 -199 (-606 to 209)

Week 4 -321 (-708 to 66)

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nlyWeek 5 -345 (-847 to 156)

Week 6 -494 (-1336 to 348)

Marital status (ref =

single or divorced)

Married/partnered Week 1 5 (-277 to 286)

Week 2 168 (-112 to 449)

Week 3 34 (-248 to 316)

Week 4 16 (-284 to 316)

Week 5 177 (-220 to 574)

Week 6 -399 (-1101 to 304)

Region

(ref=Midwest)

Northeast Week 1 -139 (-623 to 344)

Week 2 -75 (-506 to 357)

Week 3 -39 (-499 to 421)

Week 4 -40 (-475 to 394)

Week 5 -93 (-611 to 424)

Week 6 -222 (-959 to 515)

South Week 1 -199 (-538 to 139)

Week 2 -133 (-496 to 231)

Week 3 -113 (-474 to 248)

Week 4 -152 (-523 to 218)

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nlyWeek 5 -5 (-452 to 443)

Week 6 155 (-536 to 847)

West Week 1 -27 (-369 to 316)

Week 2 -101 (-423 to 221)

Week 3 -126 (-464 to 212)

Week 4 -222 (-567 to 124)

Week 5 -10 (-438 to 418)

Week 6 313 (-708 to 1334)

Education (ref= no

college degree)

College degree or higher Week 1 200 (-67 to 466)

Week 2 117 (-149 to 383)

Week 3 -42 (-313 to 229)

Week 4 332 (52 to 612)

Week 5 249 (-104 to 601)

Week 6 -242 (-1115 to 631)

Weight status (ref=

BMI/=25 kg/m2 Week 1 -330 (-606 to -55)

Week 2 -300 (-570 to -30)

Week 3 -249 (-524 to 27)

Week 4 -312 (-600 to -23)

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BMJ

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nlyWeek 5 -62 (-397 to 272)

Week 6 -240 (-1241 to 762)

Walkability index

(ref= Car-dependent

or Somewhat

walkable)

Very walkable or Walker's Paradise Week 1 5 (-450 to 460)

Week 2 -204 (-568 to 160)

Week 3 -309 (-726 to 108)

Week 4 -354 (-817 to 110)

Week 5 -158 (-685 to 369)

Week 6 -544 (-1289 to 201)

Urbanity (ref=rural) Suburban Week 1 -238 (-585 to 108)

Week 2 -137 (-491 to 218)

Week 3 138 (-206 to 483)

Week 4 185 (-154 to 524)

Week 5 -86 (-537 to 365)

Week 6 610 (-240 to 1460)

Urban Week 1 -170 (-559 to 218)

Week 2 -62 (-450 to 325)

Week 3 30 (-363 to 423)

Week 4 -16 (-429 to 397)

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BMJ

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nlyWeek 5 -228 (-732 to 277)

Week 6 342 (-353 to 1037)

Pokemon Go player

(ref = non-player)

Pokemon Go player Week 1 968 (705 to 1231)

Week 2 929 (667 to 1191)

Week 3 484 (221 to 746)

Week 4 429 (158 to 700)

Week 5 409 (73 to 745)

Week 6 -36 (-933 to 861)

*Week -4 represents 4 weeks prior to installation of Pokemon Go. Week 1 is the first week since installation of Pokemon Go. Date of Pokemon Go

installation among non-players was set to the median date among players (July 8th, 2016).

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gotta catch’em all! pokémon go and physical activity · manuscript id bmj.2016.035580.r1 article...

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