Yan Kestens - Cardiovascular Diseases: Populations and Environments

Cardiovascular Diseases Cardiovascular Diseases – –

Populations and EnvironmentsPopulations and Environments

Yan Kestens, Ph.D.spherelab.org

ForewordForeword

From NO signalling…

to population health …?

ForewordForeword

Some ‘familiar’ concepts, (for a population health researcher):

- ‘microenvironments’- ‘interactions’- ’[cell] response to essentials signals in their

environment’- ‘response to changes in their immediate

environment’

- Cells and people

- Cell microenvironments and people’s environments

- Individuals and populations

Why are ‘true’ built and social environments potentially important for cardiovascular disease?

Environments as Determinants of Environments as Determinants of CVD RiskCVD Risk

People get exposed to ‘environmental risk conditions’ which influence a ‘response’, generally a behavioural response, which is of interest in the pathway of many diseases, including cardiovascular disease



Daniel, M., S. Moore, Y. Kestens (2008) "Framing the biosocial pathways underlying associations between place and cardiometabolic disease." Health Place 14(2): 117-132.

The Strong Case for the Existence of The Strong Case for the Existence of Social Inequalities in HealthSocial Inequalities in Health

Marmot, M. G., G. Rose, et al. (1978). "Employment grade and coronary heart disease in British civil servants." J Epidemiol Community Health 32(4): 244-249.

Relative risk of coronary heart disease by social strata

Whitehall studies

Marmot, M. G., G. Rose, et al. (1978). "Employment grade and coronary heart disease in British civil servants." J Epidemiol Community Health 32(4): 244-249.

Whitehall studies

The Strong Case for the Existence of The Strong Case for the Existence of Social Inequalities in HealthSocial Inequalities in Health

The Strong Case for Trends in The Strong Case for Trends in Prevalence (e.g., Obesity)Prevalence (e.g., Obesity)

No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

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%



No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%



No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%



No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%



No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%



No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%



No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%



No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%



No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%



No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%



No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%







No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%



No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%



No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%



No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

The Strong Case for Trends in The Strong Case for Trends in Prevalence (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)

Obesity

Diet

Physical activity

MODIFIABLEEn

viro

nmen

tsMODIFIABLE

CVD

Eckel RH, Kahn R, Robertson RM, Rizza RA. Preventing cardiovascular disease and diabetes: A call to action from the american diabetes association and the american heart association. Circulation. 2006;113:2943-2946

2006: AHA reclassifies obesity as a ‘major, modifiable risk 2006: AHA reclassifies obesity as a ‘major, modifiable risk factor’ for CHD and diabetesfactor’ for CHD and diabetes

Luc F. Van Gaal, Ilse L. Mertens and Christophe E. De Block (2006) Mechanisms linking obesity with cardiovascular disease Nature 444, 875-880

ObesityObesity CVDCVD

Diet, Physical activityDiet, Physical activityEnvironmentsEnvironments

Research on Environmental Research on Environmental Influences 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

Improving Measurement of Improving Measurement of EnvironmentsEnvironments

Increasing use and capacities of Geographic Information Systems (GIS)

MEGAPHONE: Montreal Epidemiological and Geographical Assessment of Population Health Outcomes and Neighbourhood Effects

Contains a vast array of spatial information allowing for computation of exposures to built and social environments for survey participants and patients in CanadaIntegrates spatial analysis techniques to account for spatial dimensions in epidemiological models


This GIS is currently used to evaluate the influence of environments 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


Going back to the definition of ‘environment’…

Most studies look at place of residence to assess environmental exposuresYet people are increasingly mobileExposure to multiple environmentsNeed to account for this reality to better characterise exposure and influence of ‘experienced’ environmentsNew tools to record mobility/activities of individuals


A novel web-based interactive mapping questionnaire to collect data on activity locations, perceived spaces, and tripsVisualization and Evaluation of Route Itineraries, Travel Destinations, and Activity Spaces (VERITAS)


VERITAS

•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 the RECORD Cohort (n=7,300, Paris Region)•Already over 50,000 activity locations documented for more than 3,000 participants


Use of tracking devices for continuous monitoring of location, physiology, biology, and perceptions

Sensors/ tracking devices, including:

• Global Positioning System (GPS) devices• Accelerometers (physical activity)• Heart rate monitors• Glucose monitors• Momentary Impact Assessment (real-time

questionnaires)


Use of tracking devices

Example 1: CIRCUIT Lifestyle intervention for children with cardiometabolic risk factors (Collaboration with Ste-Justine Pediatric Hospital)

SPHERE Lab .org


CIRCUIT Lifestyle intervention

+ +

Trimble Juno SC GPS + Arcpad

Actigraph GT3X

Polar HR monitor

7-day data collection Spatio-behavioural indicators – SPHERELab ArcToolBox

Interactive map-based web application

Application supports lifestyle counseling






Use of tracking devices

Example 2: Study on impact of bicycle sharing implementation (BIXI) in Montreal (PI: Gauvin)

7-days continuous monitoring of 30 BIXI usersCombination of GPS, accelerometer and EMAReal-time data transmissionVisualisation of GPS tracks through interactive web application by participantsAdditional qualitative data collection of activities and travel modes


BIXI GPS Study

+

HTC Touch Pro (GPS +

EMA)

Actigraph GT3X

7-day data collectionProcessing of GPS

tracks

Visualisation of GPS tracks

Participant visualises mobility and provides additional information on activities and trips

Real-time transmission of GPS and EMA


Development of a novel multisensor platform to improve continuous monitoring

Centre de Recherche du CHUMÉcole Polytechnique de Montréal

Wearable unit integrating GPS, Accelerometer, GPRS, ANT transmission modules

Possible addition of a variety of wireless sensor nodes

Continuous real-time monitoring of location, physiology and environment

Simple design for ease of use (elderly, children)

A Multisensor Device for Health and Place Monitoring

Central Unit

GPS GPRS

Memory

Accelerometer

ANT Module


Central Unit

GPS GPRS

Memory

Accelerometer

ANT Module

GSM

Net

work

Acquisition server


Acquisition server

Central Unit

GPS GPRS

Memory

Accelerometer

ANT Module

Glucose monitor

Galvanic skin response

Accele-rometer

HR monitorBlood

pressure

Other

GSM

Net

work


Multisensor Platform

Currently tested in the RECORD GPS Study to evaluate links between mobility, environments and CVD (PIs: Chaix & Kestens)

Currently used in Montreal to evaluate links between mobility, 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)

Conclusion

Microenvironments (cells/individuals) and environments (humans/life environments) play an important role in cardiovascular disease

Hypothesised or verified pathways are generally complex

Need to improve methods to increase understanding of people(cell)-environment relations in order to guide and elaborate efficient interventions

Cardiovascular Diseases Cardiovascular Diseases – –

Populations and EnvironmentsPopulations and Environments

Thank you!Thank you!

Yan Kestens, Ph.D.spherelab.org

Date post:	04-Jul-2015
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Yan Kestens - Cardiovascular Diseases: Populations and Environments

Health & Medicine