Yan Kestens - Cardiovascular Diseases: Populations and Environments

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Presentation given at the 2012 CRCHUM Research Conference, with Ferid Murad, 1998 Nobel Price of Medicine.

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Yan Kestens - Cardiovascular Diseases: Populations and Environments

  1. 1. Cardiovascular DiseasesCardiovascular Diseases––Populations and EnvironmentsPopulations and EnvironmentsYan Kestens, Ph.D.spherelab.org
  2. 2. ForewordForewordFrom NO signalling…to population health …?
  3. 3. ForewordForewordSome ‘familiar’ concepts, (for a populationhealth researcher):- ‘microenvironments’- ‘interactions’- ’[cell] response to essentials signals in theirenvironment’- ‘response to changes in their immediateenvironment’
  4. 4. - Cells and people- Cell microenvironments and people’senvironments- Individuals and populationsWhy are ‘true’ built and social environmentspotentially important for cardiovasculardisease?Environments as Determinants ofEnvironments as Determinants ofCVD RiskCVD Risk
  5. 5. People get exposed to ‘environmental riskconditions’ which influence a ‘response’,generally a behavioural response, which isof interest in the pathway of many diseases,including cardiovascular diseaseEnvironments as Determinants ofEnvironments as Determinants ofCVD RiskCVD Risk
  6. 6. Environments as Determinants ofEnvironments as Determinants ofCVD RiskCVD RiskDaniel, M., S. Moore, Y. Kestens (2008) "Framing the biosocial pathways underlyingassociations between place and cardiometabolic disease." Health Place 14(2): 117-132.
  7. 7. The Strong Case for the Existence ofThe Strong Case for the Existence ofSocial Inequalities in HealthSocial Inequalities in HealthMarmot, M. G., G. Rose, et al.(1978). "Employment grade andcoronary heart disease in Britishcivil servants." J EpidemiolCommunity Health 32(4): 244-249.Relative risk of coronary heartdisease by social strataWhitehall studies
  8. 8. Marmot, M. G., G. Rose, et al.(1978). "Employment grade andcoronary heart disease in Britishcivil servants." J EpidemiolCommunity Health 32(4): 244-249.Whitehall studiesThe Strong Case for the Existence ofThe Strong Case for the Existence ofSocial Inequalities in HealthSocial Inequalities in Health
  9. 9. The Strong Case for Trends inThe Strong Case for Trends inPrevalence (e.g., Obesity)Prevalence (e.g., Obesity)No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  10. 10. Obesity Trends* Among U.S. AdultsObesity Trends* Among U.S. AdultsBRFSS, 1985BRFSS, 1985(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  11. 11. Obesity Trends* Among U.S. AdultsObesity Trends* Among U.S. AdultsBRFSS, 1986BRFSS, 1986(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  12. 12. Obesity Trends* Among U.S. AdultsObesity Trends* Among U.S. AdultsBRFSS, 1988BRFSS, 1988(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  13. 13. Obesity Trends* Among U.S. AdultsObesity Trends* Among U.S. AdultsBRFSS, 1989BRFSS, 1989(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  14. 14. Obesity Trends* Among U.S. AdultsObesity Trends* Among U.S. AdultsBRFSS, 1990BRFSS, 1990(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  15. 15. Obesity Trends* Among U.S. AdultsObesity Trends* Among U.S. AdultsBRFSS, 1992BRFSS, 1992(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  16. 16. Obesity Trends* Among U.S. AdultsObesity Trends* Among U.S. AdultsBRFSS, 1994BRFSS, 1994(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  17. 17. Obesity Trends* Among U.S. AdultsObesity Trends* Among U.S. AdultsBRFSS, 1995BRFSS, 1995(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  18. 18. Obesity Trends* Among U.S. AdultsObesity Trends* Among U.S. AdultsBRFSS, 1996BRFSS, 1996(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  19. 19. Obesity Trends* Among U.S. AdultsObesity Trends* Among U.S. AdultsBRFSS, 1997BRFSS, 1997(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  20. 20. Obesity Trends* Among U.S. AdultsObesity Trends* Among U.S. AdultsBRFSS, 1998BRFSS, 1998(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  21. 21. Obesity Trends* Among U.S. AdultsObesity Trends* Among U.S. AdultsBRFSS, 2000BRFSS, 2000(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
  22. 22. (*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)Obesity Trends* Among U.S. AdultsObesity Trends* Among U.S. AdultsBRFSS, 2002BRFSS, 2002
  23. 23. Obesity Trends* Among U.S. AdultsObesity Trends* Among U.S. AdultsBRFSS, 2004BRFSS, 2004(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  24. 24. Obesity Trends* Among U.S. AdultsObesity Trends* Among U.S. AdultsBRFSS, 2006BRFSS, 2006(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  25. 25. Obesity Trends* Among U.S. AdultsObesity Trends* Among U.S. AdultsBRFSS, 2008BRFSS, 2008(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  26. 26. Obesity Trends* Among U.S. AdultsObesity Trends* Among U.S. AdultsBRFSS, 2010BRFSS, 2010(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%
  27. 27. The Strong Case for Trends inThe Strong Case for Trends inPrevalence (e.g., Obesity)Prevalence (e.g., Obesity) Changes in the food environments Changes in built environments Changes in socio-spatial processes (increasing mobility,evolution of social networks)
  28. 28. ObesityDietPhysicalactivityMODIFIABLEEnvironmentsMODIFIABLECVDEckel RH, Kahn R, Robertson RM, Rizza RA. Preventing cardiovascular disease and diabetes: A call to action from the americandiabetes association and the american heart association. Circulation. 2006;113:2943-2946 2006: AHA reclassifies obesity as a ‘major, modifiable risk2006: AHA reclassifies obesity as a ‘major, modifiable riskfactor’ for CHD and diabetesfactor’ for CHD and diabetes
  29. 29. Luc F. Van Gaal, Ilse L. Mertens and Christophe E. De Block (2006) Mechanisms linking obesity withcardiovascular disease Nature 444, 875-880ObesityObesity CVDCVD
  30. 30. Diet, Physical activityDiet, Physical activityEnvironmentsEnvironments
  31. 31. Research on EnvironmentalResearch on EnvironmentalInfluences on CVDInfluences on CVDNeed to better understand people/place interactions,pathways between environments and healthDevelopment of novel methods to improve• Measurement of environments• Assessment of people-place interactions• Modeling of risk factors and disease
  32. 32. Improving Measurement ofImproving Measurement ofEnvironmentsEnvironmentsIncreasing use and capacities of Geographic InformationSystems (GIS)MEGAPHONE: Montreal Epidemiological and GeographicalAssessment of Population Health Outcomes andNeighbourhood EffectsContains a vast array of spatial information allowing forcomputation of exposures to built and social environmentsfor survey participants and patients in CanadaIntegrates spatial analysis techniques to account forspatial dimensions in epidemiological models
  33. 33. Improving Measurement ofImproving Measurement ofEnvironmentsEnvironmentsThis GIS is currently used to evaluate the influence ofenvironments on various health behaviours or outcomes,including:•Obesity•Diet•Walking•Physical activity•Smoking•Healthy aging•Pollution exposure and cancer•Depression and other mental health outcomes•Birth outcomes
  34. 34. Improving Measurement ofImproving Measurement ofEnvironmentsEnvironmentsGoing back to the definition of ‘environment’…Most studies look at place of residence to assessenvironmental exposuresYet people are increasingly mobileExposure to multiple environmentsNeed to account for this reality to better characteriseexposure and influence of ‘experienced’ environmentsNew tools to record mobility/activities of individuals
  35. 35. Improving Measurement ofImproving Measurement ofEnvironmentsEnvironmentsA novel web-based interactive mapping questionnaire tocollect data on activity locations, perceived spaces, andtripsVisualization and Evaluation of Route Itineraries, TravelDestinations, and Activity Spaces (VERITAS)
  36. 36. Improving Measurement ofImproving Measurement ofEnvironmentsEnvironmentsVERITAS•Survey frame for collection of ‘network of usual places’•Joint development : Montreal University, Canada,INSERM, France, (Chaix & Kestens)•Ongoing use of VERITAS in the second wave of theRECORD Cohort (n=7,300, Paris Region)•Already over 50,000 activity locations documented formore than 3,000 participants
  37. 37. Improving Measurement ofImproving Measurement ofEnvironmentsEnvironmentsUse of tracking devices for continuous monitoring oflocation, physiology, biology, and perceptionsSensors/ tracking devices, including:• Global Positioning System (GPS) devices• Accelerometers (physical activity)• Heart rate monitors• Glucose monitors• Momentary Impact Assessment (real-timequestionnaires)
  38. 38. Improving Measurement ofImproving Measurement ofEnvironmentsEnvironmentsUse of tracking devicesExample 1: CIRCUIT Lifestyle intervention for children withcardiometabolic risk factors (Collaboration with Ste-JustinePediatric Hospital)SPHERE Lab .org
  39. 39. Improving Measurement ofImproving Measurement ofEnvironmentsEnvironmentsCIRCUIT Lifestyle intervention+ +Trimble JunoSC GPS +ArcpadActigraphGT3XPolar HRmonitor7-day data collection Spatio-behaviouralindicators –SPHERELabArcToolBoxInteractive map-based webapplicationApplication supportslifestyle counseling
  40. 40. Improving Measurement ofImproving Measurement ofEnvironmentsEnvironmentsCIRCUIT Lifestyle intervention
  41. 41. Improving Measurement ofImproving Measurement ofEnvironmentsEnvironmentsCIRCUIT Lifestyle intervention
  42. 42. Improving Measurement ofImproving Measurement ofEnvironmentsEnvironmentsUse of tracking devicesExample 2: Study on impact of bicycle sharingimplementation (BIXI) in Montreal (PI: Gauvin)7-days continuous monitoring of 30 BIXI usersCombination of GPS, accelerometer and EMAReal-time data transmissionVisualisation of GPS tracks through interactive webapplication by participantsAdditional qualitative data collection of activities andtravel modes
  43. 43. Improving Measurement ofImproving Measurement ofEnvironmentsEnvironmentsBIXI GPS Study+HTC TouchPro (GPS +EMA)ActigraphGT3X7-day data collectionProcessing of GPStracksVisualisation ofGPS tracksParticipant visualisesmobility and providesadditional informationon activities and tripsReal-timetransmission ofGPS and EMA
  44. 44. Improving Measurement ofImproving Measurement ofEnvironmentsEnvironmentsDevelopment of a novel multisensor platform to improvecontinuous monitoring
  45. 45. Centre de Recherche du CHUMÉcole Polytechnique de MontréalWearable unit integrating GPS, Accelerometer,GPRS, ANT transmission modulesPossible addition of a variety of wireless sensornodesContinuous real-time monitoring of location,physiology and environmentSimple design for ease of use (elderly, children)A Multisensor Device for Health andPlace Monitoring
  46. 46. Central UnitGPS GPRSMemoryAccelerometerANT ModuleA Multisensor Device for Health andPlace Monitoring
  47. 47. Central UnitGPS GPRSMemoryAccelerometerANT ModuleGSMNetworkAcquisitionserverA Multisensor Device for Health andPlace Monitoring
  48. 48. AcquisitionserverCentral UnitGPS GPRSMemoryAccelerometerANT ModuleGlucosemonitorGalvanic skinresponseAccele-rometerHRmonitorBloodpressureOtherGSMNetworkA Multisensor Device for Health andPlace Monitoring
  49. 49. Multisensor PlatformCurrently tested in the RECORD GPS Study to evaluatelinks between mobility, environments and CVD (PIs:Chaix & Kestens)Currently used in Montreal to evaluate links betweenmobility, environments and diabetes (PI: Dasgupta)To be used in three cohorts of older adults (Montreal,Paris, Luxembourg) to evaluate links between mobility,environments and healthy aging (PI: Kestens)
  50. 50. ConclusionMicroenvironments (cells/individuals) and environments(humans/life environments) play an important role incardiovascular diseaseHypothesised or verified pathways are generally complexNeed to improve methods to increase understanding ofpeople(cell)-environment relations in order to guide andelaborate efficient interventions
  51. 51. Cardiovascular DiseasesCardiovascular Diseases––Populations and EnvironmentsPopulations and EnvironmentsThank you!Thank you!Yan Kestens, Ph.D.spherelab.org

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