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Rationale, design, and methods for Canadian alliance for healthy hearts and minds cohort study (CAHHM)… Anand, Sonia S; Tu, Jack V; Awadalla, Philip; Black, Sandra; Boileau, Catherine; Busseuil, David; Desai, Dipika; Després, Jean-Pierre; de Souza, Russell J; Dummer, Trevor; Jacquemont, Sébastien; Knoppers, Bartha; Larose, Eric; Lear, Scott A; Marcotte, Francois; Moody, Alan R; Parker, Louise; Poirier, Paul; Robson, Paula J; Smith, Eric E; Spinelli, John J; Tardif, Jean-Claude; Teo, Koon K; Tusevljak, Natasa; Friedrich, Matthias G Jul 27, 2016

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STUDY PROTOCOLRationale, design, and melHathe brain, heart, carotid artery and abdomen to detect early subclinical vascular disease and ectopic fat deposition.se of morbid-rge burden ofpproximatelymany mores myocardialstimated thate system $22irect costs, aAnand et al. BMC Public Health  (2016) 16:650 DOI 10.1186/s12889-016-3310-8utable risk for dementia, mediated in large part by7Hamilton Health Sciences, Hamilton, CanadaFull list of author information is available at the end of the articlefigure that is expected to grow over time [2]. Addition-ally, CV risk factors account for up to half of the attrib-* Correspondence: anands@mcmaster.ca1McMaster University, Hamilton, Canadatremendous impact on the quality of life, longevity andhealth care costs in Canada, and globally. It is ofparamount importance to understand the early determi-nants of such dysfunction and its progression to clinicalevents, given the increasing prevalence of known cardio-vascular (CV) risk factors, which result in organdysfunction including heart failure, non-alcoholic fattydiovascular Disease (CVD) is a leading cauity and mortality in Canada, and places a lacost on the health care system. Each year a70,000 Canadians die from CV causes andsuffer life-threatening CV events such ainfarction (MI) and stroke [1]. It has been ecardiovascular diseases cost our health carbillion dollars each year in direct and indDiscussion: CAHHM is a prospective cohort study designed to investigate the impact of community level factors,individual health behaviours, and access to health services, on cognitive function, subclinical vascular disease, fatdistribution, and the development of chronic diseases among adults living in Canada.BackgroundCardiac, vascular, and cognitive dysfunction have aliver disease (NAFLD), and dementia, which threatensthe financial sustainability of health care systems. Car-and blood pressure are collected. In addition, eligible parDipika Desai , Jean-Pierre Després , Russell J. de Souza , Trevor Dummer , Sébastien Jacquemont ,Bartha Knoppers11, Eric Larose9, Scott A. Lear12, Francois Marcotte15, Alan R. Moody4, Louise Parker10, Paul Poirier6,9,Paula J. Robson13, Eric E. Smith14, John J. Spinelli17, Jean-Claude Tardif15, Koon K. Teo1,7, Natasa Tusevljak16,Matthias G. Friedrich11, on behalf of the CAHHM Study InvestigatorsAbstractBackground: The Canadian Alliance for Healthy Hearts and Minds (CAHHM) is a pan-Canadian, prospective,multi-ethnic cohort study being conducted in Canada. The overarching objective of the CAHHM is to understandthe association of socio-environmental and contextual factors (such as societal structure, activity, nutrition, socialand tobacco environments, and access to health services) with cardiovascular risk factors, subclinical vasculardisease, and cardiovascular and other chronic disease outcomes.Methods/Design: Participants between 35 and 69 years of age are being recruited from existing cohorts and anew First Nations Cohort to undergo a detailed assessment of health behaviours (including diet and physicalactivity), cognitive function, assessment of their local home and workplace environments, and their health servicesaccess and utilization. Physical measures including weight, height, waist/hip circumference, body fat percentage,ticipants undergo magnetic resonance imaging (MRI) ofCanadian alliance for heaminds cohort study (CAHCanadian cohort studySonia S. Anand1,7,8*, Jack V. Tu2,16, Philip Awadalla2, Sandr7,8 9 1© 2016 The Author(s). Open Access This articInternational License (http://creativecommonsreproduction in any medium, provided you gthe Creative Commons license, and indicate if(http://creativecommons.org/publicdomain/zeOpen Accessthods forthy hearts andM) – a PanBlack4, Catherine Boileau5, David Busseuil15,5 3le is distributed under the terms of the Creative Commons Attribution 4.0.org/licenses/by/4.0/), which permits unrestricted use, distribution, andive appropriate credit to the original author(s) and the source, provide a link tochanges were made. The Creative Commons Public Domain Dedication waiverro/1.0/) applies to the data made available in this article, unless otherwise stated.Anand et al. BMC Public Health  (2016) 16:650 Page 2 of 15difficult to detect microvascular disease of the brain.The rapid increase of overweight and obesity amongCanadians and its associated consequences, includinghypertension and diabetes add to the problem. Import-antly, CVD in Canada increasingly affects women andindividuals from non-white ethnic groups [1, 3]. Whilethe treatment of clinical events caused by CVD has im-proved, the effective prevention of CVD with its implica-tions on well-being and health care costs remains achallenge, due in part to knowledge gaps regarding theimpact of social and built environments in relation to in-dividual risk factors and thus on efficient political strat-egies to reduce CVD burden. Furthermore, there is alack of sensitive, early risk markers and thus informationon these relationships before the onset of symptomaticorgan dysfunction is limited. In order to address thesegaps in our knowledge, we convened the Canadian Alliancefor Healthy Hearts and Minds (CAHHM) – a prospectivecohort of men and women recruited through existingcohorts in Canada and an First Nations cohort.The specific objectives of the CAHHM are1) To understand the role of socio-environmental andcontextual factors (such as societal structure, activity,nutrition, social and tobacco environments, and accessto health services) on CV risk factors, subclinicaldisease, and clinical CV events at the individual andpopulation levels. This includes the impact of contextualfactors on geographic variation in CVD (ie rural vs.urban, and east to west gradient), and their relativeimpact compared to individual level factors.2) To characterize the unique patterns of contextualfactors as well as acculturation, cultural continuity, andmigration experience as related to individual CV riskfactors, health service utilization (ie screening, access todiagnostics and treatments), and clinical outcomesamong high risk ethnic groups including South Asian,Chinese, and African origin, as well as reserve-basedFirst Nations people from across Canada.3) To identify early subclinical dysfunction and tissueabnormalities in the brain, blood vessels and theheart, to characterize abdominal and pericardial fatdistribution, and to investigate the association ofdysfunction with contextual and individualdeterminants. Furthermore, the data will shed lighton the predictive value of novel markers ofsubclinical abnormalities and dysfunction on thedevelopment of clinical events related to cardiac,vascular and cognitive dysfunction.Methods/DesignCAHHM is a ‘cohort of cohorts’ as the majority ofparticipants (>80 %) will be recruited through existingcohorts: 1) Canadian Partnership for Tomorrow Project(CPTP), a harmonized longitudinal population study captur-ing health data, physical measures and biologics of over300,000 Canadians (www.partnershipfortomorrow.ca). CPTPparticipants provide broad consent to research by internaland external scientists, and linkage to administrative healthdata. CPTP is a federation of five regional cohorts: the BCGenerations Projects, Alberta’s Tomorrow Project, theOntario Health Study, CARTaGENE, and Atlantic PATH(Atlantic Partnership for Tomorrow's Health), 2) the Pro-spective Urban Rural Evaluation (PURE)-Canada cohort, 3)the Montreal Heart Institute (MHI) Biobank, and 4) a newlyformed First Nations Cohort study. The details of the separ-ate cohorts are found in the Additional file 1.Eligibility and recruitment of participants into CAHHMParticipants are eligible for CAHHM if they were be-tween ages 35 and 69 years (inclusively) at time ofscreening [or for First Nations participants ≥ 18 years]and willing to undergo an MRI scan and all other re-quired study procedures. In order to recruit the majorityof participants without existing CVD we asked each co-hort to include participants of whom less than 20 % haveknown CVD, and about 50 % are women, all balancedacross age strata 35–45, 46–55, 56–69 years. Some varia-tions exist between cohorts given their differences infeasibility of recruitment and access to MRI centres.(Table 1) Details on the new First Nations cohort will bepublished in a separate manuscript.Clinical assessmentThe clinical assessment for CAHHM participants con-sisted of: a) completion of questionnaires, b) physical mea-surements, c) collection of blood samples in someparticipants (stored blood samples will be used for others),and d) a MRI scan of brain, heart, carotid artery and abdo-men, details of each component are provided below.Health questionnairesPersonal and Medical History were collected usingstandardized questions including family history, andhealth behaviors. Diet and physical activity were col-lected using a food frequency questionnaire (FFQ) andthe short form International Physical activity Ques-tionnaire (IPAQ). (Table 2)Cognitive functionCognitive function measures in CAHHM were selectedbalancing the need for a brief, cost effective, and sensi-tive measure appropriate for use in a 35–69 year agegroup. Two assessments were chosen, first the DigitSymbol Substitution (DSS) test (Wechsler AdultIntelligence Scale IV version) was chosen because itdisplayed age-related effects over the age range of 40–70Table 1 Participant Selection Criteria for Alliance Recruitment – By CohortCARTaGENE OHS BCGP APATH Alberta’s tomorrowprojectPURE MHI First NationsPreliminary Selection Criteria of ParticipantsEmail Yes Yes Yes NA Yes NA NA NABlood Samplepreviously collectedYes – also newsampleYes Yes – also newsample collectedYes – also newsample collectedNA – obtainingnew blood sampleYes – new samplefor Hamilton onlyYes – also newsampleNA – new sampleGeographic Criteria MetropolitanMontreal andQuebec CityGreaterToronto Area,London,Hamilton,OttawaMetro Vancouver Halifax andsurrounding areaCalgary andEdmontonHamilton,Vancouver, QuebecCityMontreal Hazelton, Maskwacis,Lac La Ronge, Sandy Bay,Fort MacKay, Thunder Bay,Six Nations, Oneida, Wendat,Pictou LandingPrioritized Ethnic African South Asian,Chinese,AfricanEast Asian, SouthAsian, BlackNA NA NA NA First NationsCVD (−) Max 20 % can havehistory of: MI, strokeor cancer – if notthen expandExclude: MI,stroke, CABG,PTCA, CHF,cancerMax 20 % can havehistory of: MI,stroke, CABG, PTCA,CHF or cancerMax 20 % can havehistory of: MI,stroke, CABG, PTCA,CHF or cancerMax 20 % can havehistory of: MI,stroke, CABG, PTCA,CHF or cancerMax 20 % can havehistory of: MI,stroke, CABG, PTCA,CHF or cancerMax 20 % can havehistory of: MI,stroke, CABG, PTCA,CHF or cancerMax 20 % can have historyof: MI, stroke, CABG, PTCA,CHF or cancerAge 35–69 years at timeof entry35–69 yearsat time ofentry35–69 years at timeof entry35–69 years at timeof entry35–69 years at timeof entry35–69 years at timeof entry35–69 years at timeof entry18 years and upAdditional Sampling after above criteria consideredParticipant SelectionRandom Random Random Random Random Consecutive Consecutive VolunteerCohort specificselection criteriaPrioritized forexisting RNA sampleand genomicinformationApproachparticipants comingfor in-person followup visitExclusions Participants in theDiabetes/Depressionsubstudy or withpacemakerRecently invited toparticipate in othersub-studiesLog of participantkept or availableYes Yes Yes Yes Yes Yes Yes NAAnandetal.BMCPublicHealth (2016) 16:650 Page3of15HQf Imf ACieAnand et al. BMC Public Health  (2016) 16:650 Page 4 of 15years in participants in the PURE-MIND study, a con-temporary Canadian-based prospective cohort study of800 participants with similar entry criteria to the Canad-ian Alliance for Healthy Hearts and Minds [4]. In theDSS, the participant transcribes as many coded symbolsas possible within a given time (in this case, two mi-nutes). Lower scores indicate worse performance. TheDSS is sensitive to change over time [5], is lower in per-sons with silent brain infarct, is independent of language,is sensitive to mildly impaired cognition [6], and predictsTable 2 List of Measures/Questionnaires of Baseline VisitQuestionnaire/Measure SourcePhysical Activity IPAQ-S [71]Dietary Intake (Macro and Micro Nutrients) SHARE-FFQ [72] and DCognitive Function: Digital Symbol Substitution DSS [73]Montréal Cognitive Assessment MoCA [9]Community Factors (Individual Perception) EPOCH-2 [58]Immigrant Questionnaire Longitudinal Survey oAcculturation Vancouver Inventory oCVD related Health Services Questionnaire Multi-source: CanadianOntario Health StudyGeneral CVD Questionnaire Prior Longitudinal StudCPTP Core Baseline Health and LifestyleQuestionnaireCPTP Study [74]Physical Measures (blood pressure andheart rate via OMRONcuff, Body Fat & Weight via Tanita BIA)RA: Research Assistantclinically important events such as falls and mortality [7,8]. Second, the Montréal Cognitive Assessment (MoCA)was used as a global cognitive screening test. The MoCAtakes 10–15 min to administer and briefly evaluates thefollowing domains: delayed recall, verbal fluency, visuo-spatial skills, clock drawing, executive functions, calcula-tion, abstraction, language, orientation, attention andconcentration [9]. The test has a sensitivity of 90 % andspecificity of 87 % to detect mild cognitive impairmentin patients and distinguish them from normal controls[10]. The MoCA has been validated in memory clinicsettings for diagnosis of mild cognitive impairment ordementia [9–13]. The MoCA tests domains includingexecutive function and therefore should be more sensi-tive to vascular cognitive impairment than the FolsteinMini mental status examination [14–18], is more sensi-tive to milder forms of impairment [9, 15, 19] and showsless ceiling effect [19, 20].Physical measurementsParticipants height, weight, percent body fat using theTanita BIA machine, waist circumference, hip circumfer-ence, resting heart rate, and blood pressure using anautomated OMRON cuff are collected. All measure-ments are taken using a standardized protocol.Blood collectionNew blood samples are collected from cohorts in whichblood had not previously been collected from their par-ent cohort. A new blood sample will be collected fromFirst Nations participants, the Alberta’s Tomorrow Pro-ject, BC Generations, CARTaGENE, Atlantic PATH,MHI Biobank, and PURE (Hamilton site only).Time tocomplete (minutes)Method4 Self AdministeredII 22 Self Administered5 Administered by RA8 Administered by RA21 Self Administeredmigrants in Canada [60] 3 Self Administeredcculturation [61] 3 Self Administeredommunity Health Survey, 7 Self Administereds (SHARE, PURE) 7 Self Administered14 Self Administered10 ClinicRationale for MRI imagingImaging-derived markers can be acquired non-invasivelyand include focal tissue, thereby increasing the sensitiv-ity to detect vascular lesions and tissue pathology withprognostic impact. Among the available imaging tools,MR imaging combines an outstanding safety profile withexcellent accuracy and reproducibility. Its advantagesalso include a high spatial resolution, a small observerdependence, and excellent. Moreover, it allows for a com-prehensive, multi-target approach including morphology,mass, function, flow, vessel lumen, tissue composition,and metabolism. It can be considered the most efficientimaging tool for clinical or cohort studies in healthy indi-viduals. Several existing and conceptualized population-based cohorts utilize either cardiac or brain MRI, includ-ing the UK BioBank [21], The German National Cohortstudy [22], the Dallas Heart Study [23] the MESAstudy [24], Age, Gene/Environment Susceptibility –Rey-kjavik Study [25, 26], Framingham study [27, 28] and Rot-terdam study [29, 30]. However, few studies havecomprehensively assessed the cardiovascular systemusing MRI, including arterial imaging. In CAHHM,participants will undergo a comprehensive MR exam-ination of the brain, heart, carotid artery and abdo-men (for visceral and liver adiposity). Of note, theCAHHM not only uses markers with demonstratedvalue, but also novel candidates related to coronaryplaque stability and microvascular function.MRI ProtocolDetails of the CAHHMMRI protocol are found in Tables 3and 4. The protocol was developed in collaboration with amulti-disciplinary expert group (see working groups listedat the end of the conclusion section) balancing the scien-tific objectives with time efficiency. The protocol uses vali-dated standard techniques and provides information onTable 3 MRI key measures in Heart, Brain, Abdomen duringStandard MRI ProtocolStandardSequence ApproximateImaging Time(min)Outcome MeasureCardiac2D Cine SSFP(short axis only)10 LV global (EF) and regionalwall motion abnormalitiesfunctionLV mass indexLV end-systolic volume indexLV mass-to-volume ratioLA size and functionRV volume and globalfunctionBrain3D T1w MPRAGE 8 Brain Volume2D Flair 3 Covert stroke and whitematter lesion burdenAbdomenT1w TSE abdominal 2 Visceral fat areaTable 4 Extended MRI Scan ProtocolExtendedSequence ApproximateImaging Time(min)Outcome MeasureCardiacCine SSFP (3 long axisviews and 10–15 shortaxis views)12 LV global (EF) and regionalwall motion abnormalitiesfunctionLV mass indexLV end-systolic volumeindexLV mass-to-volume ratioLA size and functionCircumferential strainRV volume and globalfunctionPhase-contrast cine 4 Aortic elasticityLGE 12 Myocardial fibrosisT1 Mapping 10 Diffuse fibrosisT2 star-weightedsensitive sequence10 Microvascular functionBrain3D T1w MPRAGE 8 Brain VolumePD/T2 4 Covert stroke and whitematter lesion burdenT2 star-weightedgradient echo sequence4 Presence of microbleeds2D resting state fMRI 4 Functional connectivity3D arterial spin labeling(ASL)7 Cerebral blood flow2D diffusion tensorimaging (DTI)5 White matter connectivityAbdomenT1w TSE abdominaladipose tissue sequence2 Visceral fat areaLiver 2D multi-echogradient-echo sequence1 Liver fat %Cerebrovascular3D T1w MPRAGE 8 Plaque volume andintraplaque hemorrhagedetectionTOF 6 Plaque volume andintraplaque hemorrhagedetection3D T1w MPRAGE +contrast5 Lipid core, calcificationinflammation/angiogenesisAdditional time for positioningCoil Positioning 6Biobreak 10Total time 118Anand et al. BMC Public Health  (2016) 16:650 Page 5 of 15adipose tissuesequenceLiver 2D multi-echogradient-echosequence1 Liver fat %Cerebrovascular3D T1w MPRAGE 6 Plaque volume andintraplaque hemorrhagedetectionTOF 6 Plaque volume andintraplaque hemorrhagedetectionAdditional time for positioningCoil Positioning 6Total time 42aaNote this varies depending on: Scanner make and model, hardware andsoftware used for scanning, need for switching MR coils, participants heartrate, and MRI technologist experienceAnand et al. BMC Public Health  (2016) 16:650 Page 6 of 15morphology, function and tissue characteristics. Quantita-tive data are measured or calculated wherever possible. Asidefrom established parameters, novel markers are included,with most of them being acquired by additional images aspart of an extended protocol, performed with the MR con-trast agent gadobutrol.Cardiac dysfunctionCardiac MR (CMR) will provide data on global and re-gional left ventricular and right ventricular function. Thisrationale is based on data from the MESA cohort with itsmulti-ethnic population-based sample of 4510 individuals(mean age 61y), where a 25.6 % prevalence of regional wallmotion abnormalities (RWMA), with a 2.6 % heart failurerate (vs. 1.0 % in individuals without RWMA) was ob-served [31]. With its obvious potential as a predictor forheart failure, the correlation of RWMA with other riskmarkers and especially environmental factors becomes animportant target for preclinical research. Its standardizedacquisition [32, 33], high prevalence in the general popula-tion and strong predictive value for subsequent heartfailure render CMR-derived RWMA an excellent earlymarker and primary endpoint in CAHHM. Other markersinclude myocardial scarring [34, 35], and coronary vascu-lar function [36–38]. Furthermore, this is an unprece-dented opportunity to acquire multi-ethnic normal valuesfor numerous quantitative cardiac markers. Because of itsoutstanding safety profile, standardized approaches, accur-acy, reproducibility and comprehensive multi-parametricprotocols, we considered CMR the most useful tool fordetecting subtle, early and local changes which mayprecede cardiac, vascular and cognitive dysfunction.Covert stroke and cognitive dysfunctionRecent population-based studies have shown that the preva-lence of unrecognized “covert” brain infarcts is as high as30–40 % in the elderly/geriatric population, and current evi-dence is sufficient to document that covert strokes and is-chemic white matter damage in the elderly are associatedwith cognitive impairments despite the lack of associationwith specific symptoms, and are highly predictive of futurestroke and dementia. However, important gaps in knowledgeinclude the prevalence of brain infarcts prior to age 60 (asprevious studies have focused on the elderly), the predictivepower of covert stroke and ischemic white matter damageas a marker of important CV events in addition to futurestroke (such as myocardial infarction), and the relationshipbetween covert stroke and subclinical manifestations ofCVD in other organs. Additionally, both covert stroke andischemic white matter damage are partly heritable but thegenetic basis of this risk has not been well defined yet.Emerging evidence suggests that alterations in brainstructure and function accrue years before clinical symp-toms of stroke or cognitive dysfunction. In Alzheimer’sdisease, regional brain atrophy and altered glucose me-tabolism can be detected on neuroimaging 15 years be-fore the onset of symptoms [39]. By contrast, thechanges in brain structure and function associated withCV and cerebrovascular disease are largely unknown,because previous population-based studies used last-generation MRI technology without high resolution im-aging. We expect that changes in brain structure (eg asmeasured by volumetric brain MRI) and brain func-tional and structural connectivity (eg as measured byresting state functional MRI and diffusion tensor im-aging of white matter tracts) can be detected in associ-ation with CVD such as hypertension and diabetes,both in the presence and absence of MRI-visible signsof irreversible ischemic damage (that is, covert strokeand ischemic white matter damage). This hypothesiswill be addressed in the Alliance for Healthy Hearts andMinds, in which high-resolution brain MRI imagingand a comprehensive assessment of CV risk arecollected.Carotid atherosclerosisSubclinical atherosclerosis detected through imagingof the carotid arteries can provide insights into thetype and burden of atherosclerotic disease. Prior stud-ies have shown that the carotid vascular bed also actsas a good representative of vascular disease through-out the body providing a ‘vascular phenotype’ for theindividual [40]. A variety of imaging techniques areavailable for carotid artery imaging, for instance Ultra-sound generated intimal medial thickness (IMT) and3D ultrasound. These two sequences will providequantitative data regarding luminal narrowing andvessel wall volume to detect carotid plaque. Inaddition, the vessel wall imaging is able to characterizeplaques as high or low risk by detecting the presenceor absence of plaque hemorrhage [41]. Among thesubset of participants undergoing the extended scan inwhich intravenous gadolinium is administered plaquescan be further characterized for the presence of lipidwithin the plaques.Measuring ectopic fat deposition in CAHHMAlthough several imaging studies have documentedsignificant associations between measures of ectopic fataccumulation (including visceral adiposity), cardiometa-bolic risk markers and clinical outcomes, most of theselarge cohort studies (Framingham [42–48], JacksonHeart Study [49–51], MESA [52, 53], INSPIRE ME IAA[54], CARDIA [55, 56]) have used computed tomographyto quantify abdominal subcutaneous and visceral adiposityas well as the accumulation of unwanted lipid depositionin normally lean tissues such as the heart, the liver, thepancreas and perivascular adipose tissue. Furthermore,core.com), which provides information by postal codeon neighborhood walkability, land use mix, transporta-tion availability and location of food retail outlets [59].Social capital and social tiesA series of validated questions were used to measuresocial support from the family and the wider social en-vironment and included questions such as participa-tion in community organizations, civic engagement,perceived social standing, and intensity of social rela-tionships with close confidants, and type of contactwith confidants (ie in-person, telephone, email, Face-book, text messages).Culture and immigrationAmong immigrants to Canada we will probe the reasonsfor immigration (economic, family, refugee) and thesocio-cultural connections they have made since immi-gration using the Immigration Questionnaire [60] andthe Vancouver Inventory of Acculturation [61]. This infor-mation will be used along with measures of socioeco-nomic status (education, household income, employmentAnand et al. BMC Public Health  (2016) 16:650 Page 7 of 15among studies using MRI such as the Dallas Heart Study,the Chengdu Study and the NEO Study, most of themhave been limited in scope and do not cover the compre-hensive spectrum of outcomes considered in CAHHM.The present study will therefore be one of the most com-prehensive cardiometabolic MRI studies ever conductedand will provide a unique opportunity to decipher the re-spective contributions of specific ectopic fat depots to aplethora of clinical conditions, going way beyond variouscardiovascular outcomes including particular attention toseveral indices of brain function and health. Furthermore,the substantial subgroup of First Nations people will gen-erate very much needed data for that population forwhom we do not currently have adequate imaging data toproperly describe to what extent they are susceptible ornot to ectopic fat deposition.Contextual factors measured at the individual andcommunity levelData describing contextual factors that characterize thenutrition, physical and tobacco environments of commu-nities from which participants are recruited as well as in-dividual behaviors in these domains are collected usingthe modified EPOCH-1 and modified EPOCH-2 ques-tionnaires modified from the PURE study [57, 58].EPOCH-1 is a standardized community audit developedand validated in the PURE study [57] and EPOCH-2captures individual’s perceptions of their food, activity,and tobacco environment also developed in the PUREstudy [58] with added questions on social ties, alcoholuse, and workplace activity and food choices andbehaviors.Community auditsTo study community level contextual factors as relatedto individual risk factors and clinical events we retro-spectively defined “community” as participants arealready recruited. After review of the communities fromwhich participants in the 5 CPTP cohorts and the 2partner cohorts originate, the forward sortation areas(FSA) was deemed to be the optimal community unit.(Table 5) We have chosen the FSA as our definition ofcommunity because: 1) there was low representation ofcohort participants from census tracts in rural areas andeastern provinces of Canada, 2) the FSA are those re-ported by census respondents for their place of residenceand this information collected from the census is avail-able in aggregate for each FSA. This census informationincludes age, sex, marital status, families and householdinformation, housing costs, mobility and migration, im-migration and citizenship, income and earnings, and eth-nic groups. This is balanced by some limitations of thisapproach include: for certain highly populated urbanareas the FSA is too large to well represent thecommunity—in this scenario, we surveyed multiple pos-tal codes within the FSA to capture the diversity. Thecommunity level information will be used together withself-reported perception of community environment aswell as behavior patterns, ie shopping, activity, andworkplace. These will be used together with objectivemeasures of the built environment from publically avail-able databases (ie streetsmart walk-score at www.walks-Table 5 Number of FSAs represented by the 7 Cohorts makingup the CAHHMProvince FSAtotalFSA to beassessed inCAHHM(Postal Codes)*# in reliabilityassessment (%)Number of postalcodes withinFSAs beingassessed (sum)BC 190 190 (+50) 112904AB 153 153 (+46) 40 (21.1 %) 76924SK 49 49 (+8) 21541MN 66 66 (+12) 23943ON 526 526 (+208) 282123QC 419 419 (+108) 55 (10.4 %) 215565Atlantic 230 230 (+72) 92809NS 77 77 (+26) 28171NB 111 111 (+30) 59530PEI 7 7 (+2) 3995N/L 35 35 (+14) 1113*For FSA with income discrepancies across postal codes within the FSA, 2audits were done to reflect the 25th percentile anand marriage) which has already been collected in each ofthe participating cohorts.measure various outcomes have been validated anddescribed in detail elsewhere [63]. Most provincialhealth care administrative databases in Canada containa patient health card number as a unique identifierthat enables efficient deterministic data linkage of vari-ous data sets, in this instance cohort data sets withprovince- or region-specific administrative databases.To protect patient privacy, the health card number(HCN) in each database is typically scrambled creatinganother unique anonymized identifier before the actualdata linkage. All participants were asked on the in-Hypertensives who have their blood pressure treated and controlledParticipants with hyperlipidemia who have been treated withmedication to control their blood cholesterol levelsParticipants with atrial fibrillation who have been treated with bloodthinnersHealth system indicators measurable from administrative dataA. Structural variables# of family doctors/specialists per capita#, costs and types of ambulatory care visits#, costs and types of hospitalizationsB. Processes of CareCV and non-CV medications (statins, ACE inhibitors, diuretics, Beta-blockers)Laboratory screening rates (lipids, diabetes)Lab results (lipids, diabetes)ECG, Stress Test, Echo, CT scans, MRI scansCardiac CatheterizationPCICardiac SurgeryC. OutcomesMyocardial Infarction (STEMI/NSTEMI, unstable angina)Congestive Heart FailureStroke (Ischemic/Hemorrhagic/TIA)Death (including cause of death)Atrial FibrillationDiabetes and HypertensionAnand et al. BMC Public Health  (2016) 16:650 Page 8 of 15Exclusion criteria1. Participant is claustrophobic and/or is known tosuffer from moderate to severe anxiety during MRIscans or similar procedures2. Participant is obese and/or exceeds equipmentweight limit and/or circumference of the MRI portalat time of screening3. Participant has a metallic implant or another foreignbody which is not compatible with MagneticResonance Imaging (MRI) (eg pacemakers,defibrillator, vascular clips, drug pumps, implant(s),or any other foreign bodies, extensive tattoocovering a large part of their chest or head)4. Female participants that are or may be pregnant(confirmed or uncertain)5. Received an MRI contrast agent within 72 h prior tothe MRI scan.Record linkage with health administrative databasesData collected of participants from the CAHHM willbe linked with health care administrative databases,available in various provinces, for ascertainment ofcardiovascular-related health care services before andafter enrollment in the study as well as long-termInclusion criteria1. Participants between ages 35 and 69 y (inclusively)at time of screening2. Provision of Informed Consent3. The participant is willing to undergo an MRI scanAccess to and quality of health care servicesA health services questionnaire was developed to collectinformation at the individual level and will be supple-mented by record linkage to administrative, laboratoryand clinical databases available in various Canadianprovinces. With these data sources we plan to analyzeexisting population-based databases to create uniquecommunity-level profiles of access and quality of healthcare services including the rates of selected CV relateddiagnostic tests and treatments. This will be a uniquecomponent of this initiative because health care serviceshave not been a focus of most traditional cohort studiesto date and yet, it is increasingly recognized that qualityof health care provided to individuals can play a majorrole in determining their likelihood of suffering and sur-viving clinical events [62]. Furthermore, how Canadianswith CV risk factors are managed likely varies acrossthe country due to factors such as physician and alliedhealth care personnel availability, type and nature ofprimary care services, patient education, and socioeco-nomic status.CVD outcomes. (Table 6) The International Classifi-cation of Diseases (ICD) codes that will be used toTable 6 Health system quality indicatorsHealth system quality indicators measurable from the CPTP CVD SurveyParticipants with a family doctorDifficulties accessing primary or specialist careWeight assessment by a health professionalScreening for hypertension, diabetes, hyperlipidemiaDiabetics who have had eyes examined by an ophthalmologist, feetexamined, urine protein testedSmokers who have been offered smoking cessation counseling and/orstop smoking aidsformed consent if they were willing to provide HCNas part of their parent cohort participation or as aamong those with RWMA by MRI, high power to de-in diabetics which suggested that liver fat was associ-Anand et al. BMC Public Health  (2016) 16:650 Page 9 of 15entire country except for Quebec, Statistics Canadawhich houses the Canadian Mortality Database and theCanadian Cancer Registry and various provincial healthservices research units located across Canada includingthe Institute for Clinical Evaluative Sciences (ICES) inOntario, Population Data BC, the Population HealthResearch Unit, Dalhousie University, Régi de l’assur-ance maladie Québec (RAMQ), etc. - each of whichhold administrative databases for their region/province.Study outcomesPrimary outcomesThe primary outcomes include MI, Stroke, angioplasty,percutaneous coronary interventions, coronary arterybypass graft surgery, and other important chronic dis-ease outcomes and death. Associations between context-ual factors, CV risk factors and MRI markers will beevaluated with these outcomes individually and as acomposite measure of CV events.Secondary outcomesSecondary outcomes for this project include:– Congestive Heart Failure requiring hospitalizationNew onset established risk factors using validatedalogrithms [63, 64]– Incident diagnosis of diabetes by physician– Incident diagnosis of hypertension by physician– Incident diagnosis of significant cognitivedysfunction (ie dementia) by physician.Risk markers acquired through imaging and bloodsamples– Acquired parameters that are linked to the presenthealth status– Candidate parameters for predicting cardiovascularevents which affect cardiac and cognitivedysfunction. For further details, please refer to theoutcomes in the questionnaires and the MRIinvolve working with multiple data custodians and gov-ernments across the country, and will require under-standing of and compliance with each province’s healthinformation privacy legislation. The Alliance is plan-ning to work with key data custodians such as theCanadian Institute for Health Information (CIHI),which collects hospital discharge abstracts for thenew request (and thus far out of the first 1000 partici-pants 99.2 % have consented to provide their HCN).Due to the federated nature of the health care systemin Canada, there is no single repository of administra-tive databases. As a result, data linkage activities willprotocol described in the Design and Methodssection above.ated with a 1.9-fold increase in CV incidence [65], onthe other hand a study by Lazo et al. [66] reported thatNAFLD by ultrasound was not associated with excess inall-cause or cardiovascular mortality in the NHANESIII study – general population. While our power is toolow to detect a HR of 1.9 between liver fat and CVD,our multiethnic sample which includes 2 high riskgroups for visceral fat and especially liver fat and inwhom we are using a superior measure of liver fat(which has greater precision as compared to ultra-sound) [67] provides an opportunity for us to test thetect a HR of 2.85 for stroke among those with silentstroke by MRI. Further we will have approximately80 % power to detect a 1.6-fold increase in new diabetesin those with liver fat as estimated by MRI assuming anincidence of new diabetes of approximately 10 %. Esti-mations of power for sample sizes lower than this (ran-ging from 5000 to the anticipated 7000 subjects) arealso shown in Table 7. Given the limited information re-garding the predictive relationship between liver fat andCVD, we identified only one published study conductedStatistical considerationsPowerRisk factor proportionsThe proportion of risk factors will be examined acrosscohorts and overall. It is anticipated given the roughlyrepresentative subcohorts that recruitment of the targetsample of 7000 will provide high power to compare therelative frequency of risk factors comparing men andwomen, participants across age strata and between non-First Nations and First Nations' Participants.Risk factors to MRI findingsThe prevalence of traditional CV risk factors will enabledetermination of the relative risk of the risk factors onsubclinical MRI findings of RWMA, covert stroke andliver adipose tissue. For example, if among 7000CAHHM participants the frequency of hypertension is25 % and the frequency of covert stroke is 6.6 %, we willhave a high power to detect a relative risk of hyperten-sion on silent stroke of brain of 1.5 (95 % CI: 1.36 to1.65).MRI to clinical eventsSeveral MRI markers have been tested for their predict-ive value versus CV events in several populations.Given the planned 7000 subjects and a predicted inci-dent CV 5 year event rate of 5.98 %[1], we have highpower (ie >90 %) to detect a hazard ratio (HR) of 2.6association between liver fat and CVD events in other-wise understudied populations.ticiumOo598598974ipaAnand et al. BMC Public Health  (2016) 16:650 Page 10 of 15AnalysisTo investigate the association between risk factors andsubclinical MRI findings linear (visceral fat) and logistic(RWMA, covert stroke, liver fat %) regression modelsmust be built separately for each MRI outcome used asthe dependent variable. Exposures such as age, sex, eth-nicity, history of hypertension, diabetes, waist circumfer-ence, apolipoprotein B/A ratio, current smoking,physical activity, selected dietary (ie prudent diet score,or ratio polyunsaturated fat/saturated fat), and measuresof cognitive function (ie when covert stroke is the out-come) will first be tested univariately, and exposureswith a P < 0.10 will be taken forward and tested in multi-variate regression models. If ethnicity is found to be anindependent predictor of an MRI outcome, it will betested with a composite CV risk score for an interactionwith the outcome.After 5 years, when enough CVD events have been ac-crued and ascertained through record linkage, the MRIsubclinical exposure of covert stroke, global or regionalventricular function abnormalities, liver fat and visceralfat will be tested versus CVD and death to determinetheir predictive value of clinical events using the areaunder the curve (C statistics), and net reclassificationimprovement methods [68].Contextual factorsComparisons between urban and rural communities willbe conducted by linear mixed models for continuousvariables (ie BMI) and generalized linear mixed model(GLMM) l for categorical variables (ie CVD events), ineach case treating community as the random effect.Using a similar model, unadjusted correlations will beestimated between the perceived (EPOCH-2) and object-Table 7 Power of given sample size between 6400 and 7400 parExposure Assumed prevalenceof exposureOutcome AssofRegional Wall Motion Abnormality 0.253 CVD 0.0Silent Stroke 0.069 CVD 0.0Liver Fata 0.063 T2DM 0.01 Assuming 20 % of the participants will have existing CVD the Number of Particproportion of First Nations participants are retained, relative to other groups)ive environmental measures (EPOCH-1) with the con-tinuous or categorical outcomes. Multilevel modelingwill be used to evaluate the relation between exposuresat the community (FSA-level) and individual level withoutcomes for each individual. All models will examineboth perceived and objective environmental measures ascovariates adjusted for individual and community socio-demographics. Interaction terms between urban andrural and the perceived and objective environmentalmeasures will be investigated to determine if the con-textual factors differ based on the type of community ieurban or rural. The contribution of variance in out-comes explained by community risk factors as opposedto the individual risk factors will be quantified using thevariance partition coefficient from each model. For thecontinuous outcomes, linear multi-level modeling willbe used. For categorical outcomes (ie CVD), similar gen-eralized linear multi-level models will be fit. Models willbe adjusted a priori for individual (age, sex, ethnicity,and household income) and community variables.Data management and data accessParticipants provide information through self-reporting(eg Health Services Research - HSR, Food FrequencyQuestionnaire - FFQ) and interviewer administered tests(eg cognitive function testing). Participants are invited byemail/mail and then directed to provide a brief informedconsent and complete 2 questionnaires on-line (HSR,FFQ), once booked for an MRI visit and screened forcontraindication to MRI, they complete the remainder ofthe assessment at the MRI site prior to or immediatelyafter their MRI. Physical measurements are taken by clinicstaff following a standardized protocol. Participants aregiven a card or self–record their physical measurements,highlighting any abnormal results. Data is then entered atthe clinical site or faxed in using Datafax. Quality controlnotes are sent by the coordinating centre to the sites tocorrect any missing or abnormal values.Results reportingCV risk scoreAll participants receive a CV risk score report after theirbaseline assessment. The majority of participants receivethe non-lab INTERHEART risk score which includesage, sex, family history, diabetes, hypertension, diet, ac-pants recruited to detect expected hazard ratiosed incidenceutcomeExpectedhazard ratio7000/ (5920)1 6000 /(5120)1 5000/(4320)2.60 >0.99/>0.99 >0.99/0.99 >0.99/>0.992.85 >0.99 >0.99 >0.99–0.1275 1.60 0.82 0.76 0.68nts free of CVD and Cancer are shown in parenthesis; a (assuming a highertivity, smoking, second hand smoke and psychosocialfactors as previously described [69], and the First Na-tions participants receive the lab-based risk score whichinclude apolipoproteins A and B and HbA1c..Incidental findings (CIF)Four core labs separately assess the Brain (Calgary orSunnybrook), Cardiac (Montreal Heart Institute), Ca-rotid (Sunnybrook) and Abdomen (IUCPQ). The readersfollow a standardized reading protocol. Results are sentto the central project office, where they are linked withthe clinical data. These severe structural abnormalitiesare reported back to participants and their primary carephysicians if they consented to this on their informedconsent. (Fig. 1) The severe structural abnormalities areshown in the Table 8. The letter emphasizes that this isa research scan which should be followed up with a tar-geted clinical scan organized by the primary carephysician.DiscussionThe Canadian Alliance for Healthy Hearts and Mindsseeks to understand the individual and contextual ori-gins of CVD risk and will aid in the design of effectivepolicy and health interventions aimed at reducing popu-lation levels of risk factors in Canada. CAHHM is aunique cohort study which brings together participants’enrolled in diverse cohorts from chronic disease focusedcohort studies, in addition to creation of a new First Na-tions cohort.First, CAHHM is unique as MRI is being used to iden-tify subclinical disease, and is only one of two studies weare aware of interrogating the brain, heart, carotid arter-ies, and abdominal adiposity [70]. MRI represents an ad-vantage over other imaging modalities as it is sensitiveto detect early, subclinical stages of disease on a system-atic (blood) or regional (tissue) level. Availability of suchvalidated predictors may allow the development of moreeffective early treatment and personalized primary pre-vention strategies.Second, we developed a detailed health services ques-tionnaire which collects information on primary carevisits, counseling for health behaviors, screening for riskfactors, access to pharmacists, and visits to specialistphysicians. To our knowledge such a detailed collectionof cardiovascular-related health services information hasnot been collected on such a large cross section of Cana-dians and will provide valuable information to enablecreation of a Health Services “Report Card” for Cana-dians in urban and rural/remote regions.Third, our contextual assessment of communities acrossCanada together with data from individuals included inour partner cohorts will enable an investigation of the“causes of the causes”, specifically the influence of context-ual factors on CV risk factors. Two contextual factor as-sessments are being undertaken. The modified EPOCH-1is a standardized audit completed by research personnel atthe FSA level in all provinces of Canada and First Nationsreserves. This will provide information on the tobaccoAnand et al. BMC Public Health  (2016) 16:650 Page 11 of 15Fig. 1 MRI analysis and Clinical incidental Findings reportingFinance and Contracts: Beena Cracknell, Tanya Chow,Advisory Committee: Pierre Boyle, Jean Rouleau,Anand et al. BMC Public Health  (2016) 16:650 Page 12 of 15environment, nutrition environment, activity environment,and social connectedness. Their precise characterization incommunities across Canada will aid policy developmentand inform population health interventions aimed at redu-cing the risk for cardiac and cognitive dysfunction, andother chronic diseases.Finally, we strive to establish a diverse cohort. Specificstrategies we have adopted to enhance diverse ancestryrecruitment include: i. establishment of a new First Na-tions cohort recruited from 10 communities acrossCanada, ii. prioritization by ethnicity ie South Asian,Chinese and African origin participants in the CPTP co-horts’; and iii. targeted ethnic recruitment for SouthAsians and Chinese origin people in Ontario.Anticipated challengesThe CAHHM initiative is a massive undertaking to co-ordinate the recruitment of new and existing cohort par-ticipants from 7 existing cohorts and a new FirstNations cohort, facilitating MRI scanning in urban, ruraland remote regions, and conducting record linkage forclinical events using Health Card Number, across prov-Table 8 Severe Structural AbnormalitiesAbnormality CriteriaBrain infarct Diameter ≥15 mm or cortical locationMyocardialinfarctionHigh signal in LGE images from extended MRI scan ora segmental wall thickening of <10% (severehypokinesis/akinesis) for at least 1 of the 16standardized segments.AorticdilatationThoracic ˃50 mm (men), ˃45 mm (women)Abdominal ˃45 mm (men), ˃40 (women)ValvulardysfunctionModerate or severe, with LV dilatation ordysfunctionMass Positive criteria for malignancy or significantcompression or infiltration of vital structuresinces, at multiple future time points. However, the studyis robustly underway due to the strong commitment ofinterested participants, researchers, academic institu-tions, and funding agencies.ConclusionsThe Canadian Alliance for Healthy Hearts and Mindsis a prospective cohort being established in Canadawith unique features including recruitment of individ-uals from existing cohort studies, use of MRI of brain,heart, carotid artery and abdomen to detect subclinicalabnormalities, detailed measurement of health servicesutilization, and measurement of individual and commu-nity level contextual factors. The information generatedin CAHHM will be used to develop community and in-dividual level CV prevention strategies for the peopleof Canada.Eldon Smith, Caroline Wong.Magnetic Resonance Imaging Coordination: MontrealHeart Institute: Felipe Henriques, François Marcotte,Julie Lebel, Matthias Friedrich.Health Services/Record Linkage Coordination: JackTu, Natasa Tusevljak, Laura Maclagan.CPTP National Coordinating Centre: Jacques Magnan,Celine Moore.Imaging Working Group: Richard Frayne, CherylMcCreary, Eric Smith, Sandra Black, Alan Moody,Christopher Scott, Jean-Pierre Despres, Eric Larose,General Leung, Tarik Hafyane.Health Services Working Group: Finley McAlister,Nadia Khan, Jafna Cox, Dennis Ko, Douglas Lee, LouisePilote, Jack Tu.Contextual Working Group: Sonia Anand, JosephBeyene, Gillian Booth, Daniel Corsi, Russell deSouza, Lise Gauvin, Scott Lear, Ayesha Rana, FahadRazak, SV Subramamian, Jack Tu.First Nations Working Group: Sonia Anand, EllenToth, Sharon Bruce, Stewart Harris, Christopher Lai,Paul Poirier, Sylvia Abonyi, Heather Castleden, James Ir-vine, Diana Lewis, Laura Arbour.Ethnic Working Group: Maria Chiu, Gordon Moe,Jack Tu, Sonia Anand.Data Harmonization and Ethics: Isabel Fortier,Bartha Knoppers, Ma’n Zawati.Additional fileAdditional file 1: CAHHM Local Site Investigators and MRI Coordination.CAHHM Participating Cohorts PIs. (DOCX 12 kb)AcknowledgementsNot applicable.FundingCanadian Partnership Against Cancer (CPAC), Heart and StrokeFoundation of Canada (HSF-Canada), Canadian Institutes of HealthResearch (CIHR).Inosha Witharana, Colin Russell; Information and Com-munication Technology: Kevin Archibald, Kristen Avery;Statistics and Biometrics Programming: Karleen Schulze,Xiumei Yang, Cissy TangCAHHM coordination and working groupsCentral coordinationPopulation Health Research Institute: Project Manager:Dipika Desai; Study Coordinator: Melissa Thomas;Research and Data Management Assistants: Sherry Zafar,Shaathaka Nandakumar, Sheila Bouseh, Natalie Campbell.Availability of data and materialNot applicable.Anand et al. BMC Public Health  (2016) 16:650 Page 13 of 15Authors’ contributionsSSA, JVT, MGF, DD, RdS, PA, PR, JS, KKT, SL, LP, ES, EL, AM, SB contributed tothe overall study design; all other authors contributed to the design andimplementation of the study in their local centre SSA wrote the first draft ofthe manuscript; all other authors contributed to subsequent revisions. Allauthors read and approved the final manuscript.Authors’ informationThe Montreal Heart Institute Biobank is funded by Mr. André Desmarais andMrs. France Chrétien-Desmarais and the Montreal Heart Institute Foundation.SSA is supported by a Tier 1 Canada Research Chair in Ethnicity andCardiovascular Disease and Heart and Stroke Foundation Chair in PopulationHealth. JVT is supported by a Tier 1 Canada Research Chair in Health ServicesResearch and an Eaton Scholar award. EL is supported by the LavalUniversity Chair of Research & Innovation in Cardiovascular Imaging and theFonds de recherche du Québec – Santé. JT holds the Canada Research Chair(Tier 1) in translational and personalized medicine and the Université deMontréal Pfizer endowed research chair in atherosclerosis. LP holds theCanadian Cancer Society Chair in Population Cancer Research at DalhousieUniversity.A complete list of Canadian Alliance for Healthy Hearts and Minds LocalInvestigators is provided in the Additional file 1.Competing interestsThe authors declare that they have no competing interests.Consent for publicationNot applicable.Ethics approval and consent to participateThe project has been approved by Hamilton Integrated Research EthicsBoard: Project# 13–255. All participants have signed consent forms prior toparticipating in the study.Author details1McMaster University, Hamilton, Canada. 2University of Toronto, Toronto,Canada. 3University of Montreal, Montréal, Canada. 4Sunnybrook ResearchInstitute, Toronto, Canada. 5CARTaGENE, Quebec, Canada. 6Quebec Heart andLung Institute, Quebec, Canada. 7Hamilton Health Sciences, Hamilton,Canada. 8Population Health Research Institute, Hamilton, Canada. 9LavalUniversity, Québec, Canada. 10Dalhousie University, Halifax, Canada. 11McGillUniversity, Montréal, Canada. 12Simon Fraser University, Burnaby, Canada.13Alberta Health Sciences, Edmonton, Canada. 14University of Cagary, Calgary,Canada. 15Montreal Heart Institute, Montréal, Canada. 16Institute for ClinicalEvaluative Sciences, Toronto, Canada. 17BC Cancer Agency and University ofBritish Columbia, Vancouver, Canada.Received: 20 May 2016 Accepted: 8 July 2016References1. Tu JV, Nardi L, Fang J, Liu J, Khalid L, Johansen H. 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