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Is Heart Disease Contagious? Issues in Communicability and Chronic Disease

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Presenters:
James H. Fowler, PhD
Professor of Medical Genetics and Political Science
University of California, San Diego

Andrew Rundle, DrPH
Co-Director of the Obesity Prevention Initiative
Associate Professor of Epidemiology
Mailman School of Public Health

Video: http://youtu.be/fUVVe17e2Q4
Dean's Chronic Disease Seminars: http://www.mailman.columbia.edu/events/deans-seminars-chronic-disease

Published in: Health & Medicine
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Is Heart Disease Contagious? Issues in Communicability and Chronic Disease

  1. 1. " , Connected ‘v The Surprising Power of Our Social Networks and How They Shape Our Lives -e-r QC ‘ ‘ NICHOLAS A. CHRIST/ lKlS_ MD. Phi] AND JAMES H. FOWLER, PhD mm “hum , nmwwwf”€ndS Qne ‘OW’ netw0r| <s }. ..; evenD€l‘§_Qnvmwmii . - new network . s>. :+: :e. rs. .s 0 C I al example foo _ ‘ '"a”V " ~ i. ... i., .also. hnninnnn. -u. un. nu
  2. 2. l . . . _ S . . , ..3s. .. . _ x.
  3. 3. Who Are Your Friends? Who do you discuss Important Matters with? Who do you spend your Free Time with?
  4. 4. l“w to re ole ?
  5. 5. Why do Widows Die?
  6. 6. FR/ —wi I i"C l‘iAi‘»'i H EART STU DY - P10jt(l oi the Nauorul Ht‘. IfL Lung and Hlood Institute and Boston Univ-rsity _ M‘- 4 ~. —._. . 9 _‘. ,_A‘ .9‘. ’ ’ . C. l . -'73“-T , -‘-*3‘-‘ _. M, ’ . IE] I ‘- E . ... s_ -' I. ’ X‘ X} I I it I’ E «l ‘i “ l‘ gas’ ~ ll I II I K‘.
  7. 7. Fl-ls Participants Living in Massachusetts Maximum any wave Number of Participants w’, J1 Iv’
  8. 8. FHS Participants in US States Number of Participants at Wave 7 o 1.10 11 - 75 76 - soo [=1 501 - 3339
  9. 9. Median Household Income by 1990 éloclt Group , — 1990 Block Group-. Median Income
  10. 10. ,' . - .1. ~ . -. = . - ' a ¢‘o 0.‘ 0 0' ‘ In . 0 u o I , '. o.~"‘. _ ‘ - ‘ , ..". ¢*, :.n. ?: 3.- o ‘f ’o ' I ' ' . . . " '1 --.2: . ‘- - ‘T-““ . --, .- 3;: 1-, . ' . ' S ; _'f “L, " 3; . . 7 4 ° ‘ o_. ‘ ' ; mi’ , " . .' °-u “ H -5 ‘.9. g ‘I"‘§{¢t . p‘. . . . u. ’_°_: ? . 0 -3 I’ , . ' . ' _4 _. ' ' _ I . a I , . . .. _ ' °. -. . . . 04 Exam 3 Friend Nominations C. -
  11. 11. The Spread of Obesity in a Large Social Network over 32 Years Nicholas A. Christakis, M. D., Ph. D., i/ l.P. l-i‘. , andjames H. Fowler, Ph. D. N ENGLJ MED 357;4 WWW. NEjM. ORG JULY 26,2007
  12. 12. Causes of Clustering A Homophily (selection effects) Influence (omitted variables) (induction)
  13. 13. Obesity “Clusters” RANDOM NETWORK OBSERVED NETWORK
  14. 14. Three Degrees of Association Relative Increase in Probability of Obesity in an Ego if Alter becomes Obese (96) 100 I Examination 1 Examination 2 80 I Examination 3 C] Examination 4 I Examination 5 so I Examination 6 C] Examination 7 40 20 0 1 2 3 4 6 Social Distance between the Ego and the Alter (degree of separation)
  15. 15. No Distance Effect l0O~ 8 1 S L Relative Increase in Probability ofObeslty in an Ego if Alter becomes Obese (%) o 8 8 L _L i Geographic Distance between the Ego and the Alter (mileage group)
  16. 16. 70'. ‘ 'a-yDur: .'k/ .'f'_o. 'e component hameaaaane ’a: yo; : qoamum cflstance: 20.-3m'r: .‘1n. 'un epmon : .'. ‘u: e . '.'x'; ae. ‘1,9.‘. ‘.s. '.‘-2‘-1 97.‘ ‘ Eco: -‘sun’ O.2Sni. ‘:‘aI Ns energy: 0 00:~$226t6B973.‘: “.‘#ec: .nu: v desfance
  17. 17. Direction and Causality James names Nicholas as a “friend”
  18. 18. Direction and Causality James names Nicholas as a “friend” Nicholas doesn’t name him back!
  19. 19. Direction and Causality James names Nicholas as a “friend” Nicholas doesn’t name him back! Nicholas affects James
  20. 20. Direction and Causality James names Nicholas as a “friend” Nicholas doesn’t name him back! Nicholas affects James James does NOT affect Nicholas I
  21. 21. Direction and Causality James names Nicholas as a “friend” Nicholas doesn’t name him back! Nicholas affects James James does NOT affect Nicholas yields strongest Mutual naming effect
  22. 22. The Basic Mloellel k ego _ , egn ‘ alter 1 alter I-I-I ])— 0! + /3.), + /3z. v,+. + /23.», + Z Y. -X; i= |
  23. 23. Estimating peer effects on health in social networks j. H. Fowler, NA. Christakis / joumal of Health Economics 27 (2008) 1386-1391 Estimated Effect of Induction 0.00 -0.10 0 20 Percent Contribution of Homophily to Social Tie Formation 40 60 80100 Estimated Effect of Induction 0.00 I When True Effect is 0.1 -0.10 0 20 40 60 80 100 Percent Contribution of Homophily to Social fie Formation
  24. 24. Alter Type Ego-perceived friend Mutual friend Alter-perceived friend Same-sex friend Opposite~sex friend Spouse Sbhng Same-sex sibling Opposite-sex sibling Immediate neighbor F“? Resets 0 100 200 300 Increase in Risk of Obesity in Ego (%)
  25. 25. Alter Type Ego-perceived friend Mutual friend Alter-perceived friend Same-sex friend Opposite-sex friend Spouse Sbhng Same-sex sibling Opposite-sex sibling Immediate neighbor Resu lifts 0 100 200 300 Increase in Risk of Obesity in Ego (%)
  26. 26. The Collective Dynamics of Smoking in a Large Social Network Nicholas A. Chrisiakis. M. D., Ph. D., M. P.l-l. , andjames H. Fowler, Ph. D. N ENGLJ MED 358;2i WWW. NE}M. ORG MAY 22,2008
  27. 27. Cluster Size Mean Size of Groups of Smokers Examination Number
  28. 28. Centrality Nonsmokers le—03 5e-O4 Eigenvector Centrality 9 f 8 1 2 3 4 5 6 7 Examination Number
  29. 29. The Spread of Alcohol consumption Behavior in a Large Social Network J. Niels Rosenquist. MD. PhD; Joanne Murabito. MD; James H. Fowler. PhD: and Nicholas A Chnstakis. MD. PhD 6 April 2010 . ‘m: uls otilzitcrnal Mcdicinr: Volume 152 ‘ Number 7 Ii . .— V A I Li :1 “ *' .1“ W31‘: rill -J ‘J 7 I 0 A '3 "3:-" 1.. in - 2 ‘J, J J A 4 2. a< ‘ 13:0 4.5 A _ * 9', ‘ . _‘ ; - I e ‘ ,4 ’ I n 4‘ .3 J‘ 2 if .1 " e 9:. 4 , , A lane ‘J 1 . .l_ ‘-". ‘ .1 . . I "’ Ii ‘ , ’ . i '1. 3 0 -a ' J 1 v . i .1’ l§: ' 1) . i i‘ 4'” 1 .4 J I 13'}. 4; A -‘ J . _ - -. J 0 . e J J to ~! 1 J_ . - ; ‘J , J , ‘ , . ‘if I‘ "' J_A )o. _v’. J_a Jag ' J , .{( ‘J . . Q. . f . 4., ‘ 0‘ A , . 4+; 4); ’ aaa'_¢l_‘ J ‘ '33 " 0.)! F4“ .4"! 0; 43*’ ’ ‘ .1; i _. _‘i. ._g 3-‘ «I I} , _". 4 .1 " P -. y, * -. ‘ J’. _l in "3, . ;‘ J“ ‘Jo I. V‘. .)q ‘_ - . a J I $4 e-- i Jul A ‘ 4 W . _ , 1.1- -1.. 3,, . J g, ; _‘e x A I" ‘ «J J . A . _ . . ,3 J a . . ‘J. ’ I ‘J __l I‘ ‘,4 '. 4 e 3 . I I O 1.: -. g 4' J0’ ‘ J“ 3.1 — 5 , V‘ .4 ‘J ‘ ~« 3 1. ' 1 °' f. 2-'3‘ ‘ . .1 [J . ‘ . 1 a "' .5 A ‘ J I - 5- ‘ ‘ o a “m ,1 1 ,1 __ ‘J’ D o-7‘ ’ A e a a J ' 3 . a 0'1‘, 1. ' _. i _ ia a 3* ‘-4 “' a a- J .
  30. 30. Contact Type Female friend Male friend Female contact—perceived friend Wife Husband Sister Brother Next-door neighbor Coworker 0 ‘l 00 200 300 Increase in Probability That Principal Drinks Heavily if Contact Drinks Heavily, %
  31. 31. Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham Heart James H Fowler, associate professor, ’ Nicholas A Christakis_ professor- . . . 73 . . 4-, .‘ J BM] 2008,337.a2338 07?, ‘ pig) A""£ V“ , —‘ J. ’— - -3'3 ' J‘ 1'11"») " J. lag’. - ; ' . - . l"'D_<v, -_‘ iii’ _, _ K _ «A» ~. I‘ ,1 J , .; . "‘ . ' F, --" 4 «J '. .l . I": ___, "'l _s . - *7 "7"" ' ix. .. . __; “*”J"‘ . _ N 3-»: __. LrL, ,4 : .v 3-? ‘ J ‘, fl_ —; ‘L . .' '2 ' " r-= ‘____>". ‘igg ‘ «$7.1 ‘ , _A ; J "; ""lvi ‘ « _'-'3 3'} ‘ . , I ‘ < _ -' 4 *3 . . ‘ I _‘ v -a- fig <~““: j%r: a _ -Au‘-' 3 — x * .5 v’-‘ , ' . ~': - . l . . J33’; 7;? ’ 3‘ § 7 7. , ""_x*“ —’. .:. ' --‘*1 “My , ii_. , V Ni“, ., -k >. ’_, o_: ._; ’:L_‘ _ . a. , '.‘i I '. r ”l l‘i‘i --‘ "'- ‘ ‘_ ‘— 7‘ Jul-(EV ‘,5? ‘3"'*'_’ ‘Jun l‘ H — ‘Q 7 "13?’-3“ ll-Jxh‘-3%» ‘at Ts: G ‘‘:9’’‘“ “*7 . is : I--': ;.‘‘‘*>. ;£. :’'7T''1:- “'3 7”” ’ “ ‘ft " "T‘—‘“ L . ~_ 5’ 4 ‘}1'7 2"‘; “~_‘: i‘*¢ ‘ . ~. , ' __i 4 ' T «x ’_ " . ‘ K, _g '33‘) 1Il~~o -1 '-3', ‘ .2,’ ii‘? ~. *4 4 7' i; ;3,—“_: “"» >» S __ rt‘ : .E}fi-~. aJ_,3q’ '3 er .4 ". ’_ P‘ ) / . , ’3‘ _ . _ -, ..-’«‘L-,3 - . _ ‘ 3- .321,” ‘J- I, ‘ . Q g In '> ; L2-I 4’: H K . a_’- ’ ' 3‘ .5;-i-£7‘) . J-4' H . .z .4 in 3
  32. 32. Increase in Probability of Ego Happiness If Alter ls Happy (%) 60 40 20 l Distance Ina. <2 <5 <10 Distance Between Ego and Alter (Miles) <O.5 <1
  33. 33. Increase in Probability of Ego Happiness If Alter ls Happy (%) 60 I Time . - I- <O.5 <1.5 <2 <2.5 Time Between Ego and Alter Exams (Years) <1
  34. 34. Alone in the Crowd: The Structure and Spread of Loneliness in a Large Social Network John T. Cacioppo James H. Fowler Nicholas A. Christakis Joumal of Personality and Social Psychology. 2009. Vol. 97. No. 6. 977-991
  35. 35. Social network determinants of depression JN Fiosenquist‘-2, JH Fowler‘‘ and NA Christakis“-5 Molecular Psychiatry (2011) 16. 273-281 V , -"“‘
  36. 36. Statistics ” Featured Article Received 22 November 2011. Accepted 21 February 2012 Published online I8 June 2012 in Wiley Online Lilxary lwileyonlinclihrarycomi DOI: l0.l002/sim5408 Social contagion theory: examining dynamic social networks and human behavior Nicholas A. Christakis“~b*l and James H. Fowler“-d Here. we review the research we have conducted on social contagion. We describe the methods we have employed (and the assumptions they have entailed) to examine several datasels with cornplemenmry strengths and week- iresses, including the Framingham Heart Study. the National Longitudinal Study of Adolescent Health. and other observational and experimental datasets that we and others have collected. We describe the regularities that led us to propose that human social networks may exhibit I ‘three degrees of influence’ property. and we review su- tisticnl approaches we have used to characterize interpersonal influence with respect to phenomena as diverse in obesity. smoking. cooperation. and happiness. We do not claim that this work is the rim] word. but we do believe that it provides some novel, informative. and stimulating evidence regarding social contagion in longitudinally followed networks. Along with other scholars, we are working to develop new methods for identifying causal efiects using social network data, and we believe that this area is ripe for statistical development as current methods have known and often unavoidable limitations. Copyright 9 2012 John Wiley & Sons. Ltd. Keyworcb: social networks; contagion; human behavior‘, homophily: causal inference
  37. 37. Estimating peer effects on health in social networks ]. H. Fowler, NA. Christakis / joumal of Health Economics 27 (2008) 1386-1391 Model 2: Effect of Model 3: Alter is the Model 1: Alter is the Named Friend with Person who Named the Named Friend School Trends Friend Coe . ' S. E. L Coe . S. E. _g Coe . S. E. L Contemporaneous Alter BM] 0.033 0.014 0.022 0.033 0.014 0.020 0.002 0.014 0.900 Al! erPreviou5BM7 -0.004 0.015 0.762 -0.005 0.015 0.759 0.002 0.015 0.908 EgoPreviousBMI 0.952 0.015 0.000 0.952 0.015 0.000 0.937 0.016 0.000 Ego Gender -0.129 0.085 0.129 -0.132 0.085 0.121 -0.176 0.100 0.078 Ego Age -0.079 0.030 0.008 -0.079 0.030 0.008 -0.071 0.033 0.033 Ego Hispanic 0.185 0.139 0.182 0.179 0.139 0.198 0.029 0.147 0.845 Ego Black 0.225 0.120 0.060 0.225 0.120 0.060 0.192 0.136 0.158 Wave 2.736 0.158 0.000 2.725 0.159 0.000 2.699 0.174 0.000 Maternal Education -0.041 0.020 0.037 -0.041 0.020 0.035 -0.023 0.021 0.279 Family Income 0.000 0.001 0.642 0.000 0.001 0.652 -0.001 0.001 0.425 School Trends 0.037 0.032 0.254 Constant -2.874 0.537 0.000 -2.8 54 0.540 0.000 -2.001 0.639 0.002 Deviance 55734 55732 27782 Null Deviance 240646 240646 107965 N 8504 8504 4742
  38. 38. Estimating peer effects on health in social networks j. H. Fowler, NA. Christakis / joumal of Health Economics 27 (2008) 1386- 1391 Table 2. New Model of F ramingham Heart Study Social Network Data Shows Framingham BMI Result is Robust to the Inclusion of Ego Fixed Effects Alter is the Named Friend Coef. SE. 3 Contemporaneous Alter B1011 0.053 0.018 0.003 Alter Previous BM -0.016 0.019 0.387 Ego Previous BMI 0.209 0.020 0.000 Ego Age 0.134 0.075 0.073 Wave 3 -0.192 0.346 0.578 Wave 4 -0.308 0.603 0.610 Wave 5 -0.373 0.874 0.670 Wave 6 -0.588 1.174 0.617 Wave 7 -0.879 1.380 0.524 843 Fixed Effects Not Shown Constant 14.547 10.567 0.169 R-‘ 0.88 N 2396
  39. 39. Acne Headaches Height
  40. 40. The "Unfriending" Problem: The Conse uences of Homophily in Friendship Retention for gausal Estimates of Social Influence Hans Noel University of Michigan - Ami Arbor, ha. nsnoe]. @um. id: .edu Brendan Nyhan University of Michigan - Ann Arbor, bnyhan@1nnich. edu Figure 3: Estimated bias for CF model in Monte Carlo simulations ‘tends? ’ n IE’>3"i)0fl - 0, 77 Fnencsmp re-moon - 0 6 : "l“s. ~ Y5‘ ucu-ma-~ i . “.| E D G O I" ‘mi honcoh y E Z c o D D 0(1) ooa fl T (‘:04 004 0 01 5, 0 D2 000 . ,. can 0 0600 ‘J 0125 0 0250 G 0375 0.0500 D 0000 0.0125 0 0250 0.0375 0 0560 unrrecv: -g nomccr y Ufllnendlnq homoormy
  41. 41. Homophily and Contagion Are Generically Confounded in Observational Social Network Studies Cosma Rohilla Shalizi' and Andrew C. Thomas'
  42. 42. Sensitivity Analysis for Contagion Effects in Social Networks Tyler J. VanderWeeIe' Table 1. Sensitivity Analysis for the Effect of a Friend‘: Obesity Status on an Ego's Obesity: Corrected Contagion Effect Estimates Under Latent Homophily for Obesity: Percentage Increase (95% confidence interval) Effect of Latent Factor U on Obesity ('3) Prevalence ofU 1.2 ii. 0.6.710 0.4 SI (2to 115) K. 0.65. lo 0.35 48 (0 to 11 I) 7:, _ 0.74., . 0.3 46(-1tol07) K. 0.7. no - 0.25 45 (-2 to 105) TI. - 0.75. no - 0.25 43 (-3 to I04) . -., - 0.8. no - 0.25 42 (-4 to I01) I) - 0.8.1.; - 0.2 41 (-510 I00) 15 45 (-2 to I05) 39 (-1 to 98) 34 (-10 to 90) 31 (-11 to 86) 28 (-13 to 82) 26 (-15 to 79) 23 (-17 to 75) 1.8 40 (-5 to 99) 32 (-1 1 to 88) 25 (-16 to 77) 21 (-18 to 72) I8 (-21 to 67) 15 (-22 to 63) II (-25 to 58) 2 37 (-7 to 95) 28 (-13 to 82) 20 (-19 to 70) I5 (-22 to 64) I2 (-24 to 59) 9 (-26 to 55) 5 (-29 to 49) 25 32 (-10 to 88) 21 (-18 to 72) I 1 (-25 to 58) 5 (-29 to 50) 2 (-31 to 44) -2 (-34 to 39) -7 (-37 to 31) 3 28 (-13 to 92) 16 (-21 no 64) 5 (-29 no 49) -2 (-38 no 39) -6 (-36 to 34) -9 (-39 to 29) -15 (43 ta 20) 4 23 (-17 to 75) 9 (-26 to 55) .4 (-35 to 37) -1 I (.40 to 26) -:5 (-43 to 20) -I9 (-45 to :4) -26 (-so to 5) Note: Semngs with K, < in, all result in percentage increases and 95% confidence intervals that are iarger than the observed estimate o( 57% (6% to 123%).
  43. 43. Can Longitudinal GEE Models Distinguish Network Influence and Homophily? An Agent-Based Modeling Approach to Measurement Characteristics Theodore J. lwashyna, MD, PhD {l, 2} Achamyeleh Gebremariam, MS {3} Meghan l-lutchins, MS {4} Joyce M Lee, MD, MPH {3} Panel B: Testing for Network Influence in Cases with Preferential Attachment (200 ABM model runs per column) Cohort = 30 Preferential Cohort = Preferential Attachment 1000 Attachment Homophily Homophily Homophily Homophily Absent Present Absent Present Sensitivity 100% 100% 100% 100% Specificity 93% 95% 92% 97% L 13+ 14.3 20.0 12.5 33.3 LR- 0 0 0 0
  44. 44. Statistical Tests for Contagion in Observational Social Network Studies Greg Ver Steeg and Aram Galstyan xii} -Ifl: «; _iz, ;;l _ / /. § T (1) , ../ .. "‘ H, V‘ (2) _. «/1‘h. / Ikglhl : At-i / Bi-1 ‘Al-l ' *B: -1 Lf ‘~ l . ‘ . . 3; W E E ’/ A e m li><ll l/ , l ii = Bi Alain.
  45. 45. Computational Social Science David Lazar. " Alex Pentlantl, ’ Lada Mamie, ’ Sinan Aral, “ Albert-Lészlo Barabasi. -5 Devon Brewer, ‘ Nicholas Christakis, ‘ Noshir Contractor, ’ James Fowler, ‘ Myron Gutmannf‘ Tony Johan, ’ Gary King, ‘ Michael Macy, ” Deb Roy, ’ Marshall Van Alstyne“ wvvw. sciencemag. org SCIENCE VOL 323 6FEBRUARY 2009
  46. 46. How Do We Study Social Networks Online?
  47. 47. L . ‘I «¢~, ,. II
  48. 48. llllsszl llllilllll Q in r. .i, i.. -~. .l Name - v- wwwxslyssa com I wrrn , i,. ..l1-- L 1': . I , ll -.1 . ~.zv-lye“ '.1nr: n! ':' lil3"' I . l i. r~. --. -.nnr~~nr1ru: r,r>-. Alvssaoolcom -’-P4 ; ~ ’ i '-~14.-Al'l". sv~»-. .. '. l:n: , mm. ‘ 0 mar E! h¢Il'| §uD| Q¢ . |,. .-. . , --
  49. 49. Ll E‘ la a zc 4‘ 1 : :~; a.cs Dam range last 30 days I Data source amazon corn 2 ADD'Y
  50. 50. 105 Close Friends in a Dorm
  51. 51. Friends plus Facebook!
  52. 52. ;F7EflE : facebook ; s;EflE-EELU 3;" K. 5; III C
  53. 53. fifimmfl *§EflQ . . A facebook lg’; igfimm
  54. 54. A Friendship Tie Overweight Obese Cluster of Women Overweight _ - Underweight J. ‘ , ‘- . — -' . '5 ‘ I _ *' Normal y_ * . — , — , - is __ >3 0 v‘ ‘ as :1 5 '4 ‘, — 0 Tie p A ' ' _ ". _ ‘.9 g .0 ‘ 1 ‘ ' Male ~-; ' is 4 : .—* i . » i x .0 ~* ‘ u . 6 7 l. ’ “e 6 . ,6 ‘ Female «» , c . i. r: ~ . * * s’ ‘ '5 lb . , , , 4 , i "I , V .7 ' _ ‘ 5 9 ‘ 9 - "‘ C C . _ . I . l‘ 5 V 3 ; ‘ _ 3 * I A, ‘ i I 3 g -E ,3 a’ i, ;, 0 ‘V 9. ‘ 5 I ,6" O . J ‘l A _ ‘ ~ ' J3 ‘ 3 ‘ ‘ ii 8 3 0 ‘g ‘G ‘a n ' " 6 ' , 6 '5 i . 7 , C . - i .6 ‘ 0 0 I 3 i . in , ‘_ | 3 t I‘ V‘ . 3 3 1‘ “ . 73 «e O Overweight ; ; Cluster of Men Source: conncctcdthcbaokrom
  55. 55. Email Data at Healthways J -Each node represents an employee -Each line represents 4 ' . J, .» , >100 emails transferred A A ’ ' ' * between nodes , . ) ‘rd » , I a 4 , , , . '4 _ 1. '4 I ‘ I , 4 . ‘ 4 ed a . — . "' 4 4‘: ' , -‘J ' :4 .4 . V_ ~'~ .1 1 A .4 ‘x 1 ix. ‘ ' . . ‘». 1 ' .1 "<4 J , _ .2 4' . , ’ . , I’ ‘ " ) "’ ' .4 H J J 1 , ’ ‘ J. 4 I ’ — — ,4 1 J I -. .i .1 l ' ; , . , A , 2' 1 . "’ -. v. , 4 . ; v, - ' . 7 .2 J ,1 - , 4 f , « ', I _. «I ; J 9 J ‘I . 4 1 I _. I J I 4 2 r ' ,2 4 ‘ , ‘ ‘ . I ‘ . J y ‘ , J ; ,"' 9 ‘ . J’ - 4 2 A I ' J M . ' ' A a .2 . ‘ v *’—’ ’ as U " 1,71‘, ’ g. ‘ ’ r . v I ’ I ’ ‘(J11 1; . ' ‘ l 1 , 4 4 J ' ' ‘ J‘ l ; - J‘, I . :4 4 A 1 ‘ « ; I 1 , r ’ . / - ‘ - I , , 4 . , 4’ A 4 ’ - 1 , 2’ 1 A, l 4 J . A . , .1 5': 5
  56. 56. BMI Ranks and Obesity at Healthways Red lines show bi-directional ties Grey lines are directed ties Body Mass Index (BMI) > 30 is considered obese go ‘ ' 0 ~ . 0. ,5-0° O; s~aii . Q 0. 5;. Clu_3Vli. -. ° ' o CBll; JE (lg; Activate Mtwuks . an. m. C
  57. 57. Bikewalk Program in Vitality Cities -Each node represents an . individual ' . . , _ -Green nodes are predicted . ‘t 0 , . . . adopters for the Bikewalk - ° . ' ' , program
  58. 58. Q Y; ME"S<; :.'CAY';4!~¢E ”- L — ‘“¢— ‘ . l l~, —.+. ‘MY FRIENDS __ lane MAKINGA ‘ ms CHE FAT. _/ your’: _ jt. « --“” » -- - - ~ FRlEND[ _ '5 ’____g___, -ct‘ V _exAi~ii>i. s i V t C. - _ _ — - _ . _ / ‘L ‘ “ -“ ‘ fr. ’ NEIG » r I C NA INHT ’ x l g as ’{_'f-‘I0!/5; , ‘ I ’— V ‘ ‘l EH ‘‘7._'_ '2 :1 1 J _ _ L S, L P‘ . ‘-u/ « 7—‘ _ _ _ ‘l J x k I { 9’ I ‘ i v UK! “ _ ' . __ ‘ l " I _ )2 fi, .': . o—. ‘ K‘ $11’ I W‘ -4-—. p-I-IF” l { ‘ ‘Y xkd 5'" I X 1 av‘ W “.1, l‘ ‘ ‘, I/ /'1 ' fig ‘
  59. 59. ‘IF on£ I5 oeese, nit omens me A ‘M. ciimcs I or stcouimo 08£3E'. ..0lD i ‘l‘iiE‘i RUILLY THINK ‘rim 9 vilauto oflive us APART ? .' we've NEVER BEES DORE comnmit) To STIMM6 8% EACH OTHERS DR‘! SRLAD AND A CUP OF WATER!
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